Max-Ratio Relay Selection in Secure Buffer-Aided Cooperative Wireless Networks

This paper considers the security of transmission in buffer-aided decode-and-forward cooperative wireless networks. An eavesdropper which can intercept the data transmission from both the source and relay nodes is considered to threaten the security of transmission. Finite size data buffers are assumed to be available at every relay in order to avoid having to select concurrently the best source-to-relay and relay-to-destination links. A new max-ratio relay selection policy is proposed to optimize the secrecy transmission by considering all the possible source-to-relay and relay-to-destination links and selecting the relay having the link which maximizes the signal to eavesdropper channel gain ratio. Two cases are considered in terms of knowledge of the eavesdropper channel strengths: exact and average gains, respectively. Closed-form expressions for the secrecy outage probability for both cases are obtained, which are verified by simulations. The proposed max-ratio relay selection scheme is shown to outperform one based on a max-min-ratio relay scheme

Numerical simulation on combustion process and optimization of structure for the reclaimed copper reverberatory furnace

Some problems, such as high energy consumption, short life and high frequency maintenance, exist in reverberatory furnace which is the key equipment for production of reclaimed copper. Measurement data for energy balance indicate the major reasons are incomplete combustion and too high temperature at some location. In this paper, the coupling numerical simulation on fluid flow, heat transfer and combustion process in a prototype of reverberatory furnace is performed based on FLUENT software, and the boundary conditions result from the comprehensive thermal measurement. The simulating results are verified via measuring data from operating furnace. In terms of the analysis of velocity and temperature field, it is found that the location of burner is not reasonable. A series of simulations have been conducted to maximize the furnace performance. The major parameters investigated include burner construction and installation location. The simulation results assist in understanding the critical factors which affects the production index, thus providing insight into furnace optimization. © 2012 IEEE

Privacy-Preserving Electricity Theft Detection based on Blockchain

In  most   electricity  theft  detection   schemes,  con-sumers’   power   consumption   data   is   directly   input   into   thedetection  center.  Although  it  is  valid  in  detecting  the  theft  ofconsumers,  the  privacy  of  all  consumers  is  at  risk  unless  thedetection center is assumed to be trusted. In fact, it is impractical.Moreover, existing schemes may result in some security problems,such  as  the  collusion  attack  due  to  the  presence  of  a  trustedthird party, and malicious data tampering caused by the systemoperator  (SO)  being  attacked.  Aiming  at  the  problems  above,we   propose   a   blockchain-based   privacy-preserving   electricitytheft  detection  scheme  without  a  third  party.  Specifically,  theproposed scheme uses an improved functional encryption schemeto  enable  electricity  theft  detection  and  load  monitoring  whilepreserving consumers’ privacy; distributed storage of consumers’data  with  blockchain  to  resolve  security  problems  such  as  datatampering, etc. Meanwhile, we build a long short-term memorynetwork (LSTM) model to perform higher accuracy for electricitytheft  detection.  The  proposed  scheme  is  evaluated  in  a  realenvironment,  and  the  results  show  that  it  is  more  accurate  inelectricity  theft  detection  within  acceptable  communication  andcomputational overhead. Our system analysis demonstrates thatthe  proposed  scheme  can  resist  various  security  attacks  andpreserve the consumer’s privacy.</p

Effects of Gaba on the Thymus Cytokines of Wenchang Chickens Submitted to Heat Stress

<div><p>ABSTRACT Under routine feeding conditions, 1-day-old male chicks were randomly divided into control group (CK), heat-stress group (HS), and GABA + heat stress group (GABA+HS). The thymus contents of IL-1, IL-2, TGF-β1, IFN-γ, GH and HSP70 were determined by enzyme-linked immunosorbent assays. The results showed that: (1) IL-1 and TGF-β1 contents of HS group were significantly lower than those of the CK group (p<0.05), and those of the GABA+HS group were significantly higher relative to the HS group (p<0.05); (2) IL-2 and IFN-γ contents of the HS group were significantly higher than those of the CK group (p<0.05), and those of the GABA+HS group were significantly lower relative to the HS group (p<0.05);(3) the thymus GH content of all three groups first increased and then decreased. The expression levels GH of the HS and GABA+HS groups were significantly lower than CK group (p<0.05); and (4) HSP70 expression levels in the thymus were significantly higher in the HS and GABA+HS groups relative to the CK group (p<0.05). These results indicate that heat stress affected thymus development, immune functions, and overall growth of chickens. Furthermore, it was shown that feeding GABA may significantly improve the immune responses of heat-stressed chickens by increasing the expression levels of IL-1 and TGF-β1, and effectively alleviate the negative effects of heat stress on thymus development by changing HSP70 expression and GH secretion.</p></div

A Kernel-based Real-time Adaptive Dynamic Programming Method for Economic Household Energy Systems

Modern home energy management systems (HEMS) have great flexibility of energy consumption for customers, but at the same time, bear a range of problems, such as the high system complexity, uncertainty and time-varying nature of load consumptions, and renewable sources generation. This has brought great challenges for the real-time control. To solve these problems, we propose a HEMS that integrates a kernel-based real-time adaptive dynamic programming (K-RT-ADP) with a new pre-processing short-term prediction technique. For the pre-processing short-term prediction, we propose a Gated Recurrent Unit-Bidirectional Encoder Representations from the Transformer (GRU-BERT) model to improve the forecasting accuracy of electrical loads and renewable energy generation. In particular, we classify household appliances into the temperature-sensitive loads, human activity sensitive loads and insensitive/constant loads. The GRU-BERT model can incorporate weather and human activity information to predict load consumption and solar generation. For real-time control, we propose and employ the K-RT-ADP HEMS based on the GRU-BERT prediction algorithm. The objective of the K-RT-ADP HEMS is to minimize the electricity cost and maximize the solar energy utilization. To enhance the nonlinear approximation ability and generalization ability of the ADP algorithm, the K-RT-ADP algorithm leverages kernel mapping instead of neural networks. Hardware-in-the-loop (HIL) experiments demonstrate the superiority of the proposed K-RT-ADP HEMS over the traditional ADP control through comparison

PA-CRT: Chinese Remainder Theorem Based Conditional Privacy-preserving Authentication Scheme in Vehicular Ad-hoc Networks

Existing security and identity-based vehicular communication protocols used in Vehicular Ad-hoc Networks (VANETs) to achieve conditional privacy-preserving mostly rely on an ideal hardware device called tamper-proof device (TPD) equipped in vehicles. Achieving fast authentication during the message verification process is usually challenging in such strategies and further they suffer performance constraints from resulting overheads. To address such challenges, this paper proposes a novel Chinese remainder theorem (CRT)-based conditional privacy-preserving authentication scheme for securing vehicular authentication. The proposed protocol only requires realistic TPDs, and eliminates the need for pre-loading the master key onto the vehicle's TPDs. Chinese remainder theorem can dynamically assist the trusted authorities (TAs) whilst generating and broadcasting new group keys to the vehicles in the network. The proposed scheme solves the leakage problem during side channel attacks, and ensures higher level of security for the entire system. In addition, the proposed scheme avoids using the bilinear pairing operation and map-to-point hash operation during the authentication process, which helps achieving faster verification even under increasing number of signature. Moreover, the security analysis shows that our proposed scheme is secure under the random oracle model and the performance analysis shows that our proposed scheme is efficient in reducing computation and communication overheads

Dynamic Features of Motor Electrical System in Locomotive Under Excitations of Wheel Polygonization

As a major component of the locomotive, wheels have great importance to realize their functions such as load carrying and power transmission through interactions with the track. However, the polygonised wheels will aggravate the dynamic performance of the locomotive and accelerate the component failures. Monitoring of the wheel polygonization is very important for the locomotive maintenance. In this paper, the effects of the wheel polygonization on the dynamic responses of the traction motor electrical system are analyzed based on the established locomotive dynamics system by considering the electromechanical coupling effect between the mechanical transmission subsystem and the electrical subsystem. The results indicate that the impact effect of the wheel polygonization has a great effect on the vibration of the wheelset and has almost no contribution to the vibration acceleration of the bogie frame, and the characteristic frequency of the lower order wheel polygonization can be found in the frequency spectrum of both the vibration responses of the mechanical system and the electrical signal of the traction motor. And this phenomenon can be used for the monitoring of the wheel polygonization

Centrifuge modeling of axial pipe-soil interaction of deep-water pipelines

This article describes equipment primarily developed for modeling axial pipe-soil interaction of offshore pipelines in a beam centrifuge. The equipment can displace the pipe axially and simulate vertical forces or oscillations acting on the pipe while the pipe is instrumented to measure the contact stresses, pore pressure, and sliding resistance. Axial motion is actuated by a servomotor actuator coupled to a chain-drive system that moves the pipe in the axial direction relative to the soil bed. A closed-loop servo-driven vertical actuator simulates the vertical forces or oscillations acting on the pipe. The centrifuge model tests were conducted under 10-g model gravity. The pipe penetration response, axial pipe-soil resistance, and pore pressure behavior beneath the pipe were investigated. A higher axial pipe-soil resistance was measured for axial shearing of the pipe that was relatively slow compared to rapid axial hearing. For rapid pipe shearing, high excess pore pressure was generated at the pipe invert compared to relatively low pore water pressure for slower movement of the pipe. The results show that the developed equipment is capable of producing highly consistent results over the range of drained and undrained response, which also agree well with recently reported finite element studies and shear box tests conducted to explore long-term axial friction. This makes the equipment potentially useful for generating high-quality data under controlled conditions in the centrifuge for mechanistic and validation studies

Unsupervised Image-to-Image Translation in multi-parametric MRI of Bladder Cancer

Detection of muscular invasive bladder cancer (MIBC) is critical for surgical selection of bladder cancer (BCa) patients. Currently, multi-parameter magnetic resonance imaging (mp-MRI) is the predominant approach for identifying MIBC. However, mp-MRI is still insufficient due to the presence of noise and artifacts. Our research aims to synthesize images from the existing sequences of mp-MRI to substitute missing or low signal-to-noise ratio sequences through image-to-image (I2I) translation. Using mp-MRI images of 255 BCa patients collected in our department, we here propose a one-to-many unsupervised I2I translation network with region-wise semantic enhancement to synthesize virtual samples. We introduce an improved adaptive instance normalization module to support the generator for synthesizing multi-domain images. In addition, a branch for region-wise semantic segmentation helps the generator to enhance the quality of image translation for a specific region. A semantically consistent loss is applied to maintaining the consistency between the synthesized and the input images via region-wise semantic segmentation. Experiments on the BraTS and BCa datasets indicate that our I2I translation approach outperforms several state of the art methods. Additionally, we perform clinical feasibility tests using the synthesis images. The clinicians reach a consensus between the Vesical Imaging Reporting and Data System (VI-RADS) scoring results from the synthesized and the real mp-MRI images. In addition, after the BCa training set has been expanded using the proposed generation model, the accuracy of the BCa muscular invasion classification is improved from 77.78% to 85.19%.</p

Metabolic analysis of adipose tissues in a rodent model of pre-pregnancy maternal obesity combined with offsprings on high-carbohydrate diet.

Maternal obesity is associated with adverse effects on the health of offsprings. Consumption of a high-carbohydrate (HC) diet has been found to promote abnormal fatty acid metabolism in adipose tissue. Therefore, we hypothesised that maternal obesity combined with an offspring HC diet would alter the fatty acid metabolism of adipose tissue and subsequently contribute to offspring obesity. Leprdb/+ mice were used to model pre-pregnancy maternal obesity and the C57BL/6 wildtype were used as a control group. Offspring were fed either HC diet or a normal-carbohydrate (NC) diet after weaning. Brown adipose tissue (BAT) and white adipose tissue (WAT) were collected from offspring at 20 weeks of age and their fatty acid metabolome was characterized using gas chromatography-mass spectrometry. We found that HC diet increased the body weight of offspring (males increased by 14.70% and females increased by 1.05%) compared to control mothers. However, maternal obesity alone caused a 7.9% body weight increase in female offspring. Maternal obesity combined with an offspring HC diet resulted in dynamic alterations of the fatty acid profiles of adipose tissue in male offspring. Under the impact of a HC diet, the fatty acid metabolome was solely elevated in female WAT, whereas, the fatty acid metabolites in BAT showed a similar trend in the male and female offsprings. 6,9-octadecadienoic acid and 12,15-cis-octadecatrienoic acid were significantly affected in female WAT, in response to offspring consumption of a HC diet. Our study demonstrated that maternal obesity and offspring HC diet have different metabolic effects on adipose tissue in male and female offsprings