On Lightweight Privacy-Preserving Collaborative Learning for IoT Objects

The Internet of Things (IoT) will be a main data generation infrastructure for achieving better system intelligence. This paper considers the design and implementation of a practical privacy-preserving collaborative learning scheme, in which a curious learning coordinator trains a better machine learning model based on the data samples contributed by a number of IoT objects, while the confidentiality of the raw forms of the training data is protected against the coordinator. Existing distributed machine learning and data encryption approaches incur significant computation and communication overhead, rendering them ill-suited for resource-constrained IoT objects. We study an approach that applies independent Gaussian random projection at each IoT object to obfuscate data and trains a deep neural network at the coordinator based on the projected data from the IoT objects. This approach introduces light computation overhead to the IoT objects and moves most workload to the coordinator that can have sufficient computing resources. Although the independent projections performed by the IoT objects address the potential collusion between the curious coordinator and some compromised IoT objects, they significantly increase the complexity of the projected data. In this paper, we leverage the superior learning capability of deep learning in capturing sophisticated patterns to maintain good learning performance. Extensive comparative evaluation shows that this approach outperforms other lightweight approaches that apply additive noisification for differential privacy and/or support vector machines for learning in the applications with light data pattern complexities.Comment: 12 pages,IOTDI 201

Potential of Interplanetary Torques and Solar Modulation for Triggering Terrestrial Atmospheric and Lithospheric Events

The Sun is forced into an orbit around the barycenter of the solar system because of the changing mass distribution of the planets. Solar-planetary-lunar dynamic relationships may form a new basis for understanding and predicting cyclic solar forcing functions on the Earth's climate.Comment: Invited Paper at the Fourth UN/ESA Workshop on Basic Space Science, Cairo, Egypt, July 1994. 7 pages LaTeX. Accepted for publication in the journal Earth, Moon, and Planet

A web-based learning system for software test professionals

Fierce competition, globalization, and technology innovation have forced software companies to search for new ways to improve competitive advantage. Web-based learning is increasingly being used by software companies as an emergent approach for enhancing the skills of knowledge workers. However, the current practice of Web-based learning is perceived as being less goal-effective due to a lack of alignment of learning with work performance. To solve this problem, a performance-oriented approach is presented in this study. Using this approach, a Web-based learning system has been developed for software testing professionals. An empirical study was conducted by inviting employees working in the software testing sector to use and evaluate the system. The results showed the effectiveness of the proposed approach. © 2011 IEEE.published_or_final_versio

Explicit parallel co-simulation approach: analysis and improved coupling method based on H-infinity synthesis

Co-simulation is widely used in the industry for the simulation of multidomain systems. Because the coupling variables cannot be communicated continuously, the co-simulation results can be unstable and inaccurate, especially when an explicit parallel approach is applied. To address this issue, new coupling methods to improve the stability and accuracy have been developed in recent years. However, the assessment of their performance is sometimes not straightforward or is even impossible owing to the case-dependent effect. The selection of the coupling method and its tuning cannot be performed before running the co-simulation, especially with a time-varying system. In this work, the co-simulation system is analyzed in the frequency domain as a sampled-data interconnection. Then a new coupling method based on the H-infinity synthesis is developed. The method intends to reconstruct the coupling variable by adding a compensator and smoother at the interface and to minimize the error from the sample-hold process. A convergence analysis in the frequency domain shows that the coupling error can be reduced in a wide frequency range, which implies good robustness. The new method is verified using two co-simulation cases. The first case is a dual mass–spring–damper system with random parameters and the second case is a co-simulation of a multibody dynamic (MBD) vehicle model and an electric power-assisted steering (EPAS) system model. Experimental results show that the method can improve the stability and accuracy, which enables a larger communication step to speed up the explicit parallel co-simulation

Influence of Fermion Velocity Renormalization on Dynamical Mass Generation in QED3_3

We study dynamical fermion mass generation in (2+1)-dimensional quantum electrodynamics with a gauge field coupling to massless Dirac fermions and non-relativistic scalar bosons. We calculate the fermion velocity renormalization and then examine its influence on dynamical mass generation by using the Dyson-Schwinger equation. It is found that dynamical mass generation takes place even after including the scalar bosons as long as the bosonic compressibility parameter $\xi$ is sufficiently small. In addition, the fermion velocity renormalization enhances the dynamically generated mass.Comment: 6 pages, 3 figures, Chinese Physics Letter, Vol 29, page 057401(2012

Design of a performance-oriented workplace e-learning system using ontology

E-learning is emerging as a popular learning approach utilized by many organizations. Despite the ever increasing practices of e-learning in the workplace, most e-learning applications fail to meet learners' needs or serve organization's quests for success. Significant gaps exist between organizational interests and individual needs when they come to e-learning, which make e-learning applications less goal-effective. To solve this problem, a performance-oriented approach is presented in this study. Key performance indicators (KPIs) are set up to clarify organizational training needs, and help learners establish rational learning objectives. In addition, ontology is used for constructing formal and machine-understandable conceptualization of the performance-oriented learning environment. Using this approach, a KPI-oriented learning ontology and prototype system have been developed and evaluated to demonstrate the effectiveness of the approach. © 2010 Elsevier Ltd. All rights reserved.postprin

Combined regenerated fibre Bragg gratings and Fabry-Perot etalons for dual strain and temperature sensing

© 2015 SPIE. A highly integrated fibre-optic sensor with regenerated fibre Bragg grating (RFBG) and a micro Fabry-Pérot (MFP) is proposed and demonstrated for simultaneous measurement of temperature and strain under high temperature (> 600°C). The MFP is fabricated by using a 157 nm fluorine gas (F2) laser to micromachine the core of a standard optical fibre. The RFBG is fabricated by regenerating a seed grating written over the Fabry-Pérot. Since the MFP and RFBG have different sensitivity coefficients, their combination can be used to realise simultaneous measurement of temperature and strain. It is believed that such a high-temperature strain sensor could find important applications in many areas where simultaneous measurement of temperature and strain under high temperature is required

Realizing Tunable Inverse and Normal Doppler Shifts in Reconfigurable RF Metamaterials

This work is supported by the National Basic Research Program (973) of China (No.2011CB922001), and National Natural Science Foundation of China (No.11234010

Pairing in the iron arsenides: a functional RG treatment

We study the phase diagram of a microscopic model for the superconducting iron arsenides by means of a functional renormalization group. Our treatment establishes a connection between a strongly simplified two-patch model by Chubukov et al. and a five-band- analysis by Wang et al.. For a wide parameter range, the dominant pairing instability occurs in the extended s-wave channel. The results clearly show the relevance of pair scattering between electron and hole pockets. We also give arguments that the phase transition between the antiferromagnetic phase for the undoped system and the superconducting phase may be first order