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The traditional pulsar period estimation method using a single distorted profile averts multiple epoch folding processes, but still has space for accuracy to improve. To give consideration to both accuracy and computational load, we combine the fast butterfly epoch folding (FBEF) with the single distorted profile (SDP)-based pulsar period estimation, and propose the FBEF-based pulsar period estimation with a few distorted profiles (FBEF-FDP), which merely uses a few epoch folding processes to enhance accuracy sharply. Firstly, the fast butterfly epoch folding is used to produce a few distorted pulsar profiles with different periods. And then the single distorted profile-based pulsar period estimation explores each distorted prolife to provide a corresponding distortion degree. Finally, using these distortion degree values, the nonlinear search method for multiple minimums can get an optimal distortion degree estimation. Besides, we prove that distortion degree estimation errors of different accumulative distorted profiles from the same pulsar photon sequence are incompletely correlated. This is the theorical basis that the distortion degree estimation values from the same pulsar photon sequence can be fitted to obtain more highly accurate distortion degree estimation. The computational complexity demonstrates that the computational load increases with the number of groups. Thus, to ensure the real-time of the FBEF-FDP, the number of groups should not be too large. Simulation results demonstrate that the accuracy of the fast butterfly epoch folding-based pulsar period estimation using a few distorted profiles enhances at the cost of a small computational load.

The microwave dielectric properties of (Mg1-xCox)2SnO4 were investigated by X-ray diffraction (XRD) patterns, Rietveld refinement, Raman spectroscopy, and microstructural observation. The ceramic was prepared using the conventional solid-state reaction method. (Mg 0.95 Co 0.05 ) 2 SnO 4 ceramic that was sintered at 1550 °C for 4 h had a dielectric constant ( ) of 8.3, a quality factor (e r ) of 8.3, a quality factor (Q×f) of 120,200 GHz (at 17.6 GHz), and a temperature coefficient of resonant frequency (τ f ) of -63 ppm/°C. The development process and test results of dielectric resonator antenna temperature sensor composed of (Mg 0.95 Co 0.05 ) 2 SnO 4 ceramics were recorded. The resonant frequency and 3 dB bandwidth measured at room temperature were 17.566 GHz and 17.0 MHz, respectively. The sensitivity of -1.1 MHz/°C was successfully achieved.

We are designing ultra-wideband feed antennas for radio astronomy using nested coaxial waveguide horns. A limitation of coaxial waveguide horns is their poor matching to free space, and thus high reflection coefficient. In this work, we use an iris matching network to improve the aperture mismatch over a wide range of frequency. A design methodology for iris matching networks is presented and used to study bandwidth and matching tradeoffs. We present a 2-iris matching network design that reduces the overall reflection coefficient from −6.5 dB to −13 dB over a 2:1 bandwidth ratio.

Indoor positioning systems have gained a lot of attention in the last few years. With the introduction of the Internet of Things (IoT) paradigm, the knowledge of user's location has become crucial information to deliver the efficient and tailored Location Based Services (LBS), especially in indoor environments. In this paper we propose an AP (Access Point)-centred indoor positioning system that overcomes common limitations presented in conventional positioning systems, such as an excessive involvement of Mobile Devices (MDs). Our work merges ideas originally proposed in [1] and [2] to build an efficient, accurate and smart Probabilistic-FingerPrint (P-FP) algorithm that avoids the MD involvement and considers the signal strength measurements as a random variable in the positioning process. Numerical results, obtained in a real-world deployment, show better performance on positioning accuracy, energy consumption and latency with respect to the MD-based architecture.

5G standard emerges at a particular time in technology history when cloud transforms deeply almost all industries and services: it becomes obvious that innovations have to be made cloud-native for being successful. 5G must become the ubiquitous fabric blending universal connectivity (to humans, robots, sensors…) with cloud versatility and scalability. For realizing this vision, another model than IaaS must be adopted, the Platform as a Service (PaaS), which should be built to support telco-grade requirements and combine all sort of third-party applications. These are the core objectives of the Next Generation Platform as a Service (NGPaaS) project, a H2020 5G PPP Phase 2 project. The paper presents the project fundamentals, its architectural proposal and most relevant features.

Platform-As-A-Service (PaaS) systems offer customers a rich environment in which to build, deploy, and run applications. Today’s PaaS offerings are tailored mainly to the needs of web and mobile applications developers, and involve a fairly rigid stack of components and features. The vision of the H2020 5GPPP Phase 2 Next Generation Platform-as-a-Service (NGPaaS) project is to enable “build-to-order” customized PaaSes, tailored to the needs of a wide range of use cases with telcograde5G characteristics. This paper sets out the salient and innovative features of NGPaaS and explores the impacts on Operational Support Systems and Business Support Systems (OSS/BSS), moving from fixed centralized stacks to a much more flexible and modular distributed architecture.

Microbubble and its cavitation combined with ultrasound have been explored to improve the theranostics of vascular diseases. Inspiring achievements have been obtained in molecular imaging, drug delivery, and thrombolysis by using microbubbles. However, microbubbles flow along the vessel axis in the blood laminar flow, preventing the microbubbles from contacting with the targeting endothelium. Hence, transporting microbubbles to the desired site has the potential to improve the corresponding medical applications.

The indoor positioning technology plays an important role in the application scenarios requiring indoor location. In this paper, the WiFi signals under modern enterprise WiFi infrastructure and signal patterns between coexisting access points (APs) are investigated. Sibling signal patterns are defined and processed to generate Beacon APs that have higher confidence for positioning. Then a positioning approach using Beacon APs is proposed and shows improved positioning accuracy. The proposed schemes are fully designed, implemented and evaluated in a real-world environment, revealing its effectiveness and efficiency.

Nowadays the indoor location context becomes an important element in a number of real applications. Use of WiFi signals to fulfil the location detection of WiFi-enabled devices is a promising approach. In this paper an AP (Access Point)- centred indoor positioning system is proposed to address some common concerns in the conventional MH (Mobile Handheld)-based positioning system, such as excessive involvement of MH, in particular for scenarios of positioning multiple MHs simultaneously. Meanwhile the popularly-used fingerprint technique is combined into the AP-centred architecture to achieve higher positioning accuracy. The proposed system is fully designed, implemented and tested in a real-world deployment. In the environment covered by the APs running the proposed system, the location of the WiFi-enabled MHs appearing in this environment can be computed by a positioning server without disturbing MHs. The accuracy of positioning result obtained from the AP- centred positioning system is evaluated in comparison with a traditional MH-based system in the real experiments. The proposed AP-centred system shows not only the feasibility of AP-centred positioning but also better performance on positioning accuracy and energy consumption of MH.

Summarizing the main methods of current EPC global network discovery service, aiming at the large-scale RFID applications and the business control needs of the entire EPCIS, and through modeling the EPC events to describe all activities in the supply chain, the paper realizes the unstructured discovery service based on extended ONS. The discovery service can use RFID tags to complete "supply chain tracking", and make the query load balancing, reduce the routing hops and improve the query efficiency through the basic idea of P2P.

This paper summarizes about some methods of EPC network discover service and introduces the working process of unstructured discover service. Considering the defaults of discover service based on P2P, an unstructured discovery service method based on extended ONS is established by extending ONS information, which solves problems of exceptions and broken chain in discover service based on P2P.This method greatly improves in robust and commercial privacy protection.

With the developing of the high-speed railways, the requirement for railway signalling turns more and more strict. Came from France, the TVM430 signal has more information up to 27 bits digital word, with each bit corresponding to one of the 27 frequencies modulated onto the carrier frequency in the track circuits. The presence of a particular frequency indicates a "1" bit and lack of corresponds to a "0". But the slow demodulation is the biggest flaw for TVM430. To solve the above problems, we design a new digital coded track signal - Improved TVM430 Railway Signalling (ITRS). ITRS reduces the number of TVM430's modulation frequency while provides the same information capacity as TVM430. We also search for cycle generating polynomial, add parity checking to the important code - speed identification code. New frequency, amplitude and phase are defined for frequency modulated signals. ITRS performs better in information capacity, reliability and demodulation speed.

Railway signal is the most important factor in the train control system. Different kinds of railway signals and Train Control Systems are used in the world. In this paper, the simulation system of railway signal transmission and on-board cab signal receiving is presented and implemented. The system based on DSP (Digital Signal Processor) can simulate the working process of the railway signal system, including signal sending, transmission, receiving, decoding and controlling of the eight- signal display device, as well as support four existing railway signal standards used in China. This system can provide not only an experimental and demonstrating module for the teaching purpose, but also a platform for cab signal simulation for the purpose of research and development. It has a good prospect in application.

Artificial aggregate systems are used both by aggregate producers and the mining industry. It is a multi- attribute complicated system which has many uncertain or fuzzy factors, which means constructing a practical and satisfactory mathematical model for computer simulation and optimization is difficult. To achieve optimal performance of an artificial aggregate system, equipment Selection and coordination is very important. In this paper a novel method for artificial aggregate system equipment selection is presented based on the theory of fuzzy expert system by risky decision making. The risk is discussed on its result. Some practice of this system proved that it could improve the design quality and efficiency and the room for decision-making. But the initial values of risk and reliability are difficult to estimate and need to research further. Keywords-Risky Decision-making; Fuzzy Expert System; Equipment Selection; Artificial Aggregate System

An improved genetic algorithm (GA) is presented to solve Flexible Job Shop scheduling (FJSS) problem. This algorithm combines GA with constraint model based on polychromatic sets theory (PST). According to the characteristic of FJSS problem, this algorithm uses contour matrix to formalize the restrictions between workpiece and operations, and between operations and machines. During the process of encoding, decoding, crossover and mutation, the contour matrixes guarantee the genetic searching in the valid solution space. At the same time, the calculation of fitness value is simplified and the computer programming is easy developed. The disadvantage of traditional GA that is the premature convergence and slow convergent speed are improved. Experimental results demonstrate that this algorithm is very stable and its efficiency is improved. It is fit for solving FJSS problem and dynamic scheduling problem.

The mechanism and placement process of multi-head gantry mount machine (MHGM) is analyzed. Based on the engineering analysis, the optimization problem of placement process is decomposed to component grouping, component group pickup and component group placement problems, an integrated optimization model of MHGM is formulated, the minimum displacement of arm is objective. The component size, nozzle change and different component arrangement strategy in slots is considered. Combined with heuristic method and genetic algorithm (GA), a hybrid GA (HGA) is adopted to optimize the placement process. In the individual chromosome, the feeder index and slot index describe the arrangement sequence and position of component types in the slot. The HGA use improved order crossover, adaptive mutation and local search and contains a parallel structure. The component placement sequence and the feeder arrangement are optimized simultaneously to improve the assembly efficiency.

Based on the analysis of dual-gantry turret machine, the optimization problem of placement process is decomposed to component allocation, feeder arrangement and component placement sequence. Through the engineering analysis, an integrated optimization model of dual-gantry multi-head turret placement machine is formulated. The minimum displacement of gantry and workload balance is objective. Combined with heuristic method and genetic algorithm (GA), hybrid GA (HGA) is adopted to optimize the placement process. A two-dimensional piece-wise coding method is proposed. In a chromosome, component allocation, feeder arrangement and component placement sequence is described simultaneously. HGA uses improved order crossover, adaptive mutation and contains a reasonable fitness function. Under the condition of constraint satisfying of movement mechanisms, HGA guarantee that the genetic research can enter the available solution space quickly and research the optimal solution. The component allocation, component placement sequence and feeder arrangement are optimized simultaneously to improve the PCB assembly efficiency.

A class of order optimization (OO) with optimal computing budgets allocation (OCBA) based genetic algorithm (GA) is designed to perform local search in the framework of nested partitions method (NP). The local searching algorithm borrows from the idea of OO to ensure the quality of the design found with a reduction in computation effort and applies the evolutionary searching mechanism and learning capability of GA to effectively perform exploration and exploitation. Proposed hybrid algorithm retains the property of global search and convergence of NP and the powerful local searching capability of OO with OCBA based GA algorithm. The effectiveness of hybrid algorithm is demonstrated by numerical simulation results based on stochastic job-shop scheduling benchmarks and its optimization quality is much better than pure GA and OO with OCBA algorithm.

The component placement sequence and feeder arrangement are two critical factors determining the assembly time of chip-shooter machine. In addition, the different size of component and different arrangement strategy affect the feeder arrangement and component placement sequence. Based on the engineering analysis, an integrated optimization model of chip-shooter machine is established. The improved genetic algorithm (IGA) proposes a two-dimensional coding method. In the individual chromosome, the component number describes the component placement sequence, the slot number describes the feeder arrangement, and the component type number describes the relation between the component placement sequence and feeder arrangement. The IGA uses the improved order crossover, adaptive mutation, local search, and the parallel structure. The component placement sequence and feeder arrangement are optimized simultaneously. The performance of IGA is superior to other algorithms.

In 2006 and 2007, daily exposures to nitrogen dioxide were monitored in four groups of residents, including office workers, schoolchildren, taxi drivers and teachers. A total of 126 24-hour samples of personal NO2 exposure were collected with passive diffusion samplers. The results show that the average NO2 exposure is 0.049 mg/m3 overall. 11.9% of samples exceeded the national annual guideline standard, 0.080 mg/m3. Schoolchildren are exposed to the highest personal NO2 exposure level, and teachers are the lowest, with office workers and taxi drivers in an intermediate position. There is significant difference between schoolchildren and office workers. But the exposure levels changed after adjusted to day-to-day ambient concentrations, which are lowest for teachers, and different from other three groups exposed to a higher level.