64 research outputs found
Graph Construction for Hyperspectral Data Unmixing
This chapter presents graph construction for hyperspectral data and associated unmixing methods based on graph regularization. Graph is a ubiquitous mathematical tool for modeling relations between objects under study. In the context of hyperspectral image analysis, constructing graphs can be useful to relate pixels in order to perform corporative analysis instead of analyzing each pixel individually. In this chapter, we review fundamental elements of graphs and present different ways to construct graphs in both spatial and spectral senses for hyperspectral images. By incorporating a graph regularization, we then formulate a general hyperspectral unmixing problem that can be important for applications such as remote sensing and environment monitoring. Alternating direction method of multipliers (ADMM) is also presented as a generic tool for solving the formulated unmixing problems. Experiments validate the proposed scheme with both synthetic data and real remote sensing data
Distributed Private Online Learning for Social Big Data Computing over Data Center Networks
With the rapid growth of Internet technologies, cloud computing and social
networks have become ubiquitous. An increasing number of people participate in
social networks and massive online social data are obtained. In order to
exploit knowledge from copious amounts of data obtained and predict social
behavior of users, we urge to realize data mining in social networks. Almost
all online websites use cloud services to effectively process the large scale
of social data, which are gathered from distributed data centers. These data
are so large-scale, high-dimension and widely distributed that we propose a
distributed sparse online algorithm to handle them. Additionally,
privacy-protection is an important point in social networks. We should not
compromise the privacy of individuals in networks, while these social data are
being learned for data mining. Thus we also consider the privacy problem in
this article. Our simulations shows that the appropriate sparsity of data would
enhance the performance of our algorithm and the privacy-preserving method does
not significantly hurt the performance of the proposed algorithm.Comment: ICC201
An Extensive Game-Based Resource Allocation for Securing D2D Underlay Communications
Device-to-device (D2D) communication has been increasingly attractive due to its great potential to improve cellular communication performance. While resource allocation optimization for improving the spectrum efficiency is of interest in the D2D-related work, communication security, as a key issue in the system design, has not been well investigated yet. Recently, a few studies have shown that D2D users can actually serve as friendly jammers to help enhance the security of cellular user communication against eavesdropping attacks. However, only a few studies considered the security of D2D communications. In this paper, we consider the secure resource allocation problem, particularly, how to assign resources to cellular and the D2D users to maximize the system security. To solve this problem, we propose an extensive game-based algorithm aiming at strengthening the security of both cellular and the D2D communications via system resource allocation. Finally, the simulation results show that the proposed method is able to efficiently improve the overall system security when compared to existing studies
Dynamic incentive strategy for voluntary demand response based on TDP scheme
Abstract-The enhanced real-time metering and communication capabilities from smart meters and their associated advanced metering infrastructure make it possible for utility company to extend demand response (DR) to small customers through timedependent pricing (TDP). Considering the economic reason and infrastructure cost, the utility company has to design an incentive scheme to attract the traditional flat pricing (FP) users to be engaged in the TDP scheme. In this process, the utility company may share its revenue from the TDP scheme to those TDP users. It is found, with properly analyzing the energy procurement cost and user elasticity, a dynamic incentive strategy can be considered in dual-tariffs system when flat pricing (FP) and TDP pricing are co-existed. This dynamic incentive strategy gives appropriate stimulus to the users who are involved into the TDP program, and guarantee the utility company's profit at the same time
Pengembangan Aplikasi Reservasi Berbasis Website Dengan ASP.NET Pada PT. Kalbe Farma Tbk (International Division)
Teknologi merupakan salah satu faktor penting yang dapat meningkatkan kinerja perusahaan. PT Kalbe Farma Tbk (International Division) adalah salah satu perusahaan yang telah memanfaatkan teknologi untuk kegiatan reservasi di perusahaan. Namun, aplikasi reservasi yang digunakan saat ini masih memiliki beberapa keterbatasan dan kekurangan, seperti fitur yang terbatas, akses yang terbatas, dan proses yang manual. Oleh karena itu, penulis ingin mengembangkan sebuah aplikasi reservasi berbasis website dengan ASP.NET yang dapat memberikan fitur-fitur baru dan memudahkan pengguna dalam melakukan reservasi ruangan, mobil, dan pengajuan surat. Tujuan dari penelitian ini adalah untuk membuat sebuah sistem reservasi yang lebih efektif, efisien, dan produktif bagi PT Kalbe Farma Tbk (International Division)
Randomized Rank-Revealing QLP for Low-Rank Matrix Decomposition
The pivoted QLP decomposition is computed through two consecutive pivoted QR
decompositions, and provides an approximation to the singular value
decomposition. This work is concerned with a partial QLP decomposition of
low-rank matrices computed through randomization, termed Randomized Unpivoted
QLP (RU-QLP). Like pivoted QLP, RU-QLP is rank-revealing and yet it utilizes
random column sampling and the unpivoted QR decomposition. The latter
modifications allow RU-QLP to be highly parallelizable on modern computational
platforms. We provide an analysis for RU-QLP, deriving bounds in spectral and
Frobenius norms on: i) the rank-revealing property; ii) principal angles
between approximate subspaces and exact singular subspaces and vectors; and
iii) low-rank approximation errors. Effectiveness of the bounds is illustrated
through numerical tests. We further use a modern, multicore machine equipped
with a GPU to demonstrate the efficiency of RU-QLP. Our results show that
compared to the randomized SVD, RU-QLP achieves a speedup of up to 7.1 times on
the CPU and up to 2.3 times with the GPU
Networked Twins and Twins of Networks : an Overview on the Relationship Between Digital Twins and 6G
Digital Twin (DT) is a promising technology for the new immersive digital life with a variety of applications in areas such as Industry 4.0, aviation, and healthcare. Proliferation of this technology requires higher data rates, reliability, resilience, and lower latency beyond what is currently offered by 5G. Thus, DT can become a major driver for 6G research and development. Alternatively, 6G network development can benefit from Digital Twin technology and its powerful features such as modularity and remote intelligence. Using DT, a 6G network (or some of its components) will have the opportunity to use Artificial Intelligence more proactively in order to enhance its resilience. DT's application in telecommunications is still in its infancy. In this article we highlight some of the most promising research and development directions for this technology
Spectral techniques for multiple-valued logic
83 p.The research work discussed in this thesis concerns spectral techniques for multiple-valued logic. The main objectives are the development of novel discrete transformations and fast algorithms for binary and multiple-valued switching circuits which find various potential applications in communication system, digital signal processing and in particular, the classical logic synthesis.Doctor of Philosophy (EEE
- …