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In recent years, multi-phase inverter-fed motors that realize additional advantages have been actively studied because of developments of power semiconductor switching devices. The authors also have proposed a MATRIX motor driven by H-bride inverters connected with each phase winding individually for the purpose of realizing electric motors with high functionalities. In addition, since motors are being applied to various applications that is close to people, further quietness of motor is required. In this paper, a method is proposed that 2nd order radial direction electromagnetic force can be suppressed by teeth flux density control in the MATRIX motor. By utilizing high degree of freedom of current control owe to multi-phase drive and local flux density observation capability of the MATRIX motor, the 2nd order radial force on each tooth and vibration are suppressed. The effectiveness of the proposed method was clarified by simulation results.

Permanent magnet synchronous motors (PMSMs) are widely used for many purposes due to their high efficiency and controllability. These frequent applications require less noise and fewer vibrations. This study focuses on three-group and three-phase PMSMs that can independently control the current among three groups and suppress the vibrations caused by air gap unbalances. For suppression control, the air gap unbalance must be detected. Its representative factors are static and dynamic eccentricity and the roundness degradation of the stator core. This study proposes a method to detect static eccentricity and roundness degradation by the third-order harmonic components of no-load line-line voltages, which are easily measurable in practical production processes. We apply our proposed method to a FEA model with these two types of air gap unbalances, confirm the detection ability, and describe the displacement of the air gap length.

Crowdsourcing enables users (task requesters) to outsource complex tasks to an unspecified crowd of workers. To guarantee the quality of crowdsourcing service, it is necessary to select the most appropriate task workers to complete the tasks. To this end, the crowdsourcing platform (broker) must conduct the mutual matching between tasks and workers based on the task requirements and worker preferences. However, both task requirements and worker preferences may contain sensitive information (e.g., time, location of the task, etc.), which should not be revealed to the broker and other adversaries. In this paper, we propose a secure and efficient task matching scheme to enable the broker to conduct the mutual matching between tasks and workers, according to task requirements and worker preferences with multiple keywords, while preserving the privacy of keywords contained in task requirements and worker preferences. Specifically, we design a new multi-reader and multi-writer searchable encryption primitive that can support the batch matching of multiple keywords. The security proof shows that our proposed task matching scheme is provably secure in the random oracle model under the Bilinear Diffie-Hellman (BDH) assumption. The performance evaluation shows that our multi-keyword batch matching can significantly reduce the computation cost compared to existing methods.

Since permanent magnet synchronous motors (PMSMs) have advantages of efficiency and energy density, they are now widely being used for many purposes. Based on such increased use, they require improved efficiency, lower acoustic noise, and fewer vibrations. However, such fabrication tolerances as eccentricity and roundness degradation generate a magnetic unbalance in the magnetic gap and cause low-order harmonics of electromagnetic force and cogging torque that create acoustic noise and vibrations. Since multi-three-phase PMSMs can individually control the phase current of each group, reducing the magnetic unbalance is possible in the magnetic gap. To control the phase current of each group, magnetic unbalance must be detected. In this study, we focus on static eccentricity as a representative fabrication tolerance and propose a method to detect it using the third-order harmonic component of no-load line-line voltages, which is easily measurable in practical production processes. We demonstrate our method that estimates the amount and direction of static eccentricity with a theoretical approach and confirm its detection by finite element analysis (FEA).

Permanent magnet synchronous machines (PMSMs) are widely used in a variety of applications. Dynamic eccentricity of the rotor is one of the obstacles in the manufacturing process. This obstacle causes an imbalanced electromagnetic force and causes unexpected vibrations. In this research, the effect of dynamic eccentricity on the temporal and spatial harmonic distribution of electromagnetic force and vibration are investigated. Moreover, compensation methods have been proposed to suppress the vibrations due to dynamic eccentricity by using multi-sector and multi-phase motor. The compensation current is obtained by optimization. The effectiveness of the proposed method is verified by finite element analysis (FEA).

This paper investigates the scheduling strategies for the virtual power plant (VPP) considering different development stages of the electricity market. Firstly, the operation models are formulated to characterize the aggregated components of VPP, including the distributed photovoltaic (PV), wind turbines, demand resources (DRs), electric vehicles (EV) and combined heat and power (CHP) unit as well as conventional units. Next, different operating frameworks have been proposed in order to derive the scheduling strategies of VPP for different development stages of the electricity market. Specifically, a price taker-based scheduling model is developed for VPP during the early stage of market construction. For the mature stage of market development, a bi-level framework is introduced to simulate the bidding and scheduling strategies of VPP acting as active participates. Moreover, the bi-level framework is further recast as a solvable problem. The proposed method is capable to characterize the scheduling strategies of VPP in different stages of market development.

The new round of power industry restructuring has brought new challenges to power grid companies, prompting them to further improve power grid investment. In order to fully employ data resources in power grid investment decisions, it is necessary to comprehensively use data mining and monitoring technologies so as to realize dynamic supervision of power grid investment decisions and improve investment efficiency. In this context, this paper summarizes the research results of each key link involved in the establishment of a power network investment optimization system based on data monitoring technology, summarizes the use and deficiencies of the existing research results, and proposes research suggestions for the next step of building the power grid investment optimization system based on data monitoring technology.

Permanent magnet synchronous machines (PMSMs) are widely used in a variety of applications. Static eccentricity of rotor and roundness degradation of stator are among common faults at the fabrication process. These faults cause unbalance electromagnetic force and exert unexpected vibration at the design process. This research investigates the impact of these faults on the time and spatial harmonic distribution of electromagnetic force and vibration. Moreover, a compensation method have been proposed to suppress vibration caused by these faults due to static eccentricity and roundness degradation by using triple three phase winding motor. The system of triple three phase winding motor rely on three independent sets of windings dedicated to control electromagnetic force in each winding. Therefore, the unbalance electromagnetic force can be restored and the vibration can be reduced by the system. The effectiveness of the proposal method is verified by Finite Element Analysis.

The Large UV/Optical/IR Surveyor (LUVOIR) is one of four Astro2020 Decadal Survey Missions, a concept for ‘flag-ship’ class space-borne observatory, operating across the multi-wavelength UV/Optical/NIR spectra. An Optical Telescope concept being considered is the segmented primary mirror architecture with composite backplane structure. In order to achieve the high-contrast imaging required to satisfy the primary science goals of this mission would require a pico-meter wavefront RMS stability over a wavefront control time step, a milli-Kelvin level thermometry sensing and control, and near-zero CTE materials. The LUVOIR primary mirror segment assemblies and composite backplane support structure require active thermal management to maintain operational temperature during flight operations. Furthermore, the active thermal control must be sufficiently stable to prevent time-varying thermally induced structure distortions to minimize optical aberrations. This paper describes a Thermal System Architecture of 2 concepts considered for the LUVOIR decadal study, and a systematic approach to developing a thermal architecture of modular composite sections of the mirror support structure and primary mirror segment assemblies.

The past decade has witnessed the rise of crowdsourcing, and privacy in crowdsourcing has also gained rising concern in the meantime. In this paper, we focus on the privacy leaks and sybil attacks during the task matching, and propose a privacy-preserving task matching scheme, called SybMatch. The SybMatch scheme can simultaneously protect the privacy of publishers and subscribers against semi-honest crowdsourcing service provider, and meanwhile support the sybil detection against greedy subscribers and efficient user revocation. Detailed security analysis and thorough performance evaluation show that the SybMatch scheme is secure and efficient.

The security of vehicular networks has been paid increasing attention to with the rapid development of automobile industry and Internet of Things (IoT). However, existing approaches mainly focus on ensuring data authentication and integrity, which are not sufficient to assess the credibility of received messages. Recently, reputation systems are proved to be effective approaches to solve the above problem. This paper proposes a new reputation system for data credibility assessment based on the blockchain techniques. In this system, vehicles rate the received messages based on observations of traffic environments and pack these ratings into a “block”. Each block is “chained” to the previous one by storing the hash value of the previous block. Then, a temporary center node is elected from vehicles and it is responsible for broadcasting its rating block to others. Based on ratings stored in the blockchain, vehicles are able to calculate the reputation value of the message sender and then evaluate the credibility of the message. Simulation results reveal that the proposed system is reliable in collecting, validating, and storing reputation information in vehicular networks.

With the rapid development of wireless communication and mobile devices, heterogeneous networks have emerged as a promising paradigm to enable users' data services. However, it lacks an experience blocking theory to optimize data services. Furthermore, due to the limited resources of spectrum, the spectrum sharing based on the quality of experience (QoE) in heterogeneous networks becomes a new challenge. Therefore, to tackle the above challenge, we present an experience blocking (EB) ratio based game-theoretic approach for spectrum sharing in heterogeneous networks where the small cell can lease the spare spectrum from macro cell. Specifically, firstly, a novel EB ratio based model is proposed to evaluate the efficiency of spectrum usage in a cell. Then a Stackelberg game is employed to formulate the interaction between macro cell and small cell according to the EB ratio. Finally, an EB table is given to evaluate the blocking status of a cell and simulation results show that the proposed scheme can improve the efficiency of spectrum sharing better than other schemes.

In big data era, data are usually stored in databases for easy access and utilization, which are now woven into every aspect of our lives. However, traditional relational databases cannot address users' demands for quick data access and calculating, since they cannot process data in a distributed way. To tackle this problem, non-relational databases such as MongoDB have emerged up and been applied in various Scenarios. Nevertheless, it should be noted that most MongoDB products fail to consider user's data privacy. In this paper, we propose a practical encrypted MongoDB (i.e., CryptMDB). Specifically, we utilize an additive homomorphic asymmetric cryptosystem to encrypt user's data and achieve strong privacy protection. Security analysis indicates that the CryptMDB can achieve confidentiality of user's data and prevent adversaries from illegally gaining access to the database. Furthermore, extensive experiments demonstrate that the CryptMDB achieves better efficiency than existing relational database in terms of data access and calculating.

Silicon photomultipliers (SiPMs) are attractive replacements for photomultiplier tubes (PMTs). However, many radiation detector applications require large volumes of monolithic scintillator and correspondingly large numbers of SiPMs. When multiples of SiPMs are used, the dark count noise and cost increase proportionally with the surface area covered. When too few SiPMs are used, non-uniformity of light collection degrades the energy resolution of the detector. Strategic placement of a limited number of SiPMs on a large scintillator can reduce the number of SiPMs necessary and decrease the cost-to-performance ratio. Simulations and experiments have been performed to find general guidelines regarding optimal positioning of SiPMs on large NaI(Tl) crystal scintillators. For example, if the SiPMs are placed near edges and vertices on one cuboid face, the number of SiPMs necessary to achieve adequate energy resolution need only cover 40% or less of the light output face.

In this paper, we propose a dynamic bandwidth allocation scheme based on Stackelberg game for a heterogeneous network to simultaneously offer mobile social users with bandwidth via multiple homing access. In specific, network operators in the heterogeneous network compete with each other to determine the price of the bandwidth based on the prediction of mobile social users' demands. Then, mobile social users with the same interests form a social community as a coalition to dynamically request bandwidth and share the cost with each other. We formulate the bandwidth allocation problem as a Stackelberg game to model the interactions among mobile social users and network operators. In addition, with a backward induction, an iterative algorithm is proposed to obtain the Stackelberg equilibrium. Finally, simulation results show that the proposed scheme can improve both the efficiency ratio of bandwidth allocation and load balance of networks compared with uniform bandwidth allocation, random bandwidth allocation, and single access scheme.

Cloud storage enables users to remotely store their data and share the data through the cloud. Existing integrity auditing schemes for shared data are often not identity-preserving and have high auditing cost, and hence are still far from practical application. In this work, we propose a public auditing scheme for shared data in cloud storage with identity privacy preservation. To preserve identity privacy against the auditor, we convert signatures computed by different users into signatures computed by the challenge user with proxy re-signature. Our scheme supports user revocation without re-signing signatures computed by revoked users, while the integrity of shared data can still be correctly checked. Furthermore, the auditing is efficient in the sense that the number of pairing operations during auditing is independent of the number of challenged blocks and users. We further present a batch auditing supporting multiple auditing delegations from different groups instead of only the same group. Security analysis demonstrates that our scheme is provably secure. Numeric analysis and simulation results show that both computation and communication costs of our scheme are lower than in existing schemes.

In this paper, we propose a Social-based Mobile Sybil Detection (SMSD) scheme to detect Sybil attackers from their abnormal contacts and pseudonym changing behaviors. Specifically, we first define four levels of Sybil attackers in mobile environments according to their attacking capabilities. We then exploit mobile users' contacts and their pseudonym changing behaviors to distinguish Sybil attackers from normal users. To alleviate the storage and computation burden of mobile users, the cloud server is introduced to store mobile user's contact information and to perform the Sybil detection. Furthermore, we utilize a ring structure associated with mobile user's contact signatures to resist the contact forgery by mobile users and cloud servers. In addition, investigating mobile user's contact distribution and social proximity, we propose a semi-supervised learning with Hidden Markov Model to detect the colluded mobile users. Security analysis demonstrates that the SMSD can resist the Sybil attackers from the defined four levels, and the extensive trace-driven simulation shows that the SMSD can detect these Sybil attackers with high accuracy.

Searchable encryption is an important and challenging issue. It allows people to search on encrypted data. This is a very useful function when more and more people choose to host their data in the cloud and the cloud server is not fully trustable. Existing solutions for searchable encryption are only limited to some simple functions of search, such as boolean search or similarity search. In this paper, we propose a scheme for Generalized Pattern-matching String-search on Encrypted data (GPSE) in cloud systems. GPSE allows users to specify their search queries by using generalized wildcard-based string patterns (such as SQL-like patterns). It gives users great expressive power in specifying highly targeted search queries. In the framework of GPSE, we particularly implemented two most commonly used pattern matching search functions on encrypted data, the substring matching and the longest-prefix-first matching. We also prove that GPSE is secure under the known-plaintext model. Experiments over real data sets show that GPSE achieves high search accuracy.

LaBr3:Ce crystal scintillator can be co-doped with various alkaline earth metals to improve light output and energy resolution of the basic scintillator. Another benefit is improvement of alpha/gamma discrimination via pulse shape analysis. LaBr3:Ce contains a low level of actinium contamination, which produces an alpha particle background. This background is difficult to discriminate from gamma rays. Conversely, the addition of co-dopant into the crystal makes the alpha response much easier to distinguish. LaBr3:Ce,Sr, for example, produces a second, longer decay component in the scintillation pulse when excited by radiation. The amplitude of this second decay component changes in response to a gamma ray versus a heavy charged particle. The change in pulse shape is used to eliminate the alpha background and enable detection of neutron reaction products.

Due to the high volume and velocity of big data, it is an effective option to store big data in the cloud, because the cloud has capabilities of storing big data and processing high volume of user access requests. Attribute-Based Encryption (ABE) is a promising technique to ensure the end-to-end security of big data in the cloud. However, the policy updating has always been a challenging issue when ABE is used to construct access control schemes. A trivial implementation is to let data owners retrieve the data and re-encrypt it under the new access policy, and then send it back to the cloud. This method incurs a high communication overhead and heavy computation burden on data owners. In this paper, we propose a novel scheme that enabling efficient access control with dynamic policy updating for big data in the cloud. We focus on developing an outsourced policy updating method for ABE systems. Our method can avoid the transmission of encrypted data and minimize the computation work of data owners, by making use of the previously encrypted data with old access policies. Moreover, we also design policy updating algorithms for different types of access policies. The analysis show that our scheme is correct, complete, secure and efficient.

This report presents the scintillation properties and temperature dependent neutron and gamma responses of Cs 2 LiLaBr 6 elpasolite crystals with 0.5, 2, and 3.5% Ce doping. Cs 2 LiLaBr 6 has excellent scintillation light output proportionality, high light output, and good energy resolution. It also shows good light output temperature stability. Pulse shape differences between neutron and gamma excited pulses are analyzed as a function of temperature. Neutron-gamma pulse shape discrimination is possible in a wide temperature range from −10°C up to at least 140 °C.

In the data center, a server can work in either active state or power-saving state. The power consumption in the power-saving state is almost 0, thus it is always desirable to allocate as many VMs as possible to some active servers and leave the rest to power-saving state in order to reduce the energy consumption of the data center. In this paper, we study such a VM allocation problem. Given a set VMs and a set of servers in a data center, each VM has a resource demand (CPU, memory, storage) and a starting time and a finishing time, and each server has resource capacity. There is an additional energy cost for a server to switch from power-saving state to active state. The servers are non-homogeneous. The problem of our concern is to allocate the VMs onto servers, such that the VMs resource demands can be met and the total energy consumption of servers is minimized. The problem is formulated as a boolean integer linear programming problem. A heuristic algorithm is proposed to solve the problem. Extensive simulations have been conducted to demonstrate our proposed method can significantly save the energy consumption in data centers.

In MIMO networks, there are two transmission strategies, SM (spatial multiplexing) and IC (interference cancellation). The use of SM and IC brings additional complexity for routing and transmission scheduling of the links. Almost all existing works on throughput optimization for MIMO systems are based on the assumption that traffic routing is given and they focus only on stream scheduling, where the performance of the system is limited. In this work, we study the joint optimization problem of routing and stream scheduling for MIMO networks, where the traffic is allowed to be routed through multiple paths to take benefit from concurrent transmissions. The problem is first formulated as an Integer Linear Programming (ILP) problem, and solved optimally by using the column generation approach. An efficient online heuristic algorithm for multi-path routing and stream scheduling with dynamic traffic load is then proposed based on the column generation approach. Extensive simulation results have been conducted to demonstrate the efficiency of the proposed algorithms.

Data access control is an effective way to ensure the data security in the cloud. However, due to data outsourcing and untrusted cloud servers, the data access control becomes a challenging issue in cloud storage systems. Existing access control schemes are no longer applicable to cloud storage systems, because they either produce multiple encrypted copies of the same data or require a fully trusted cloud server. Ciphertext-Policy Attribute-based Encryption (CP-ABE) is a promising technique for access control of encrypted data. It requires a trusted authority manages all the attributes and distributes keys in the system. In cloud storage systems, there are multiple authorities co-exist and each authority is able to issue attributes independently. However, existing CP-ABE schemes cannot be directly applied to data access control for multi-authority cloud storage systems, due to the inefficiency of decryption and revocation. In this paper, we propose DAC-MACS (Data Access Control for Multi-Authority Cloud Storage), an effective and secure data access control scheme with efficient decryption and revocation. Specifically, we construct a new multi-authority CP-ABE scheme with efficient decryption and also design an efficient attribute revocation method that can achieve both forward security and backward security. The analysis and the simulation results show that our DAC-MACS is highly efficient and provably secure under the security model.

The performance improvement of large size (φ = 60 mm, l = 80 mm) Sr2+ and Br2+ co-doped LaBr3:Ce3+ scintillation crystals is reported. The scintillation light output of both Sr2+ and Br2+ co-doped crystals are significantly improved. Compared to 70,000 ph/MeV (at 662 keV) for Ce3+ only LaBr3, Sr2+ and Ba2+ co-doping increase the light output by ~25% to 88,000 ph/MeV and 89,000 ph/MeV, respectively. The energy resolutions of both Sr2+ and Ba2+ co-doped crystals are improved over a wide energy range as well. The scintillation decay time is slightly lengthened with co-doping. No secondary slow component is observed. Co-doped crystals exhibit very similar emission and excitation characteristics to the Ce3+ only crystal. Both Sr2+ and Ba2+ show improved light output proportionality in the low energy range.

Cipher text-Policy Attribute-base Encryption (CP-ABE) is regarded as one of the most suitable technologies for data access control in cloud storage. In almost all existing CP-ABE schemes, it is assumed that there is only one authority in the system responsible for issuing attributes to the users. However, in many applications, there are multiple authorities co-exist in a system and each authority is able to issue attributes independently. In this paper, we design an access control framework for multi-authority systems and propose an efficient and secure multi-authority access control scheme for cloud storage. We first design an efficient multi-authority CP-ABE scheme that does not require a global authority and can support any LSSS access structure. Then, we prove its security in the random oracle model. We also propose a new technique to solve the attribute revocation problem in multi-authority CP-ABE systems. The analysis and simulation results show that our multi-authority access control scheme is scalable and efficient.

This paper presents the short-term joint optimal simulation operation simulation method for Qing River cascade hydropower system, which considering on time-of-use (TOU) power price and pursing maximum power generation benefit. In this method, the temporal-spatial variation of flow between cascade hydropower stations is considered. Correlation analysis is used for calibrating the measured data between hydropower stations, and an equation of linear regression is determined for dealing with the calculation of the temporal-spatial variation of flow. Furthermore, improved AGA with Sine-roulette wheel selection operator is found application in the simulation, which adopts trigonometric function to make a non-linear conversion to fitness in order to keep the diversity of population in the selection process and avoid premature of AGA. To a certain degree, the results of simulative optimal operation based on several representative hydrographs show that the improved AGA can find a more excellent solution in the same algebra.

The hydrological forecast error inevitably leads to the uncertainty of reservoir inflow, so the optimal operation of reservoirs group is also uncertain. This paper presents a method which combines the random simulation with the optimal operation of reservoirs group. The random simulation uses the method of Latin hypercube sampling to improve Monte Carlo method, which reduces the sampling frequency and improves the sampling accuracy compared with traditional sampling method. Ant colony algorithm is found application for solving the optimal operation problem of reservoirs group. According to the method presented we can obtain the scheduling scheme of reservoirs group under a given risk rate. At the same time the method changes the decision-making of stochastic operation into that of determinable operation. The study case of giant hydropower stations in Hubei Province shows that the method is practical.

This study demonstrates a trigate poly-Si nonvolatile memory (NVM) with an amorphous silicon (a-Si) charge trapping layer. The NWs SOAOS (silicon-oxide–amorphous silicon-oxide-silicon) NVM exhibits higher program/erase (P/E) efficiency than that of a conventional SONOS NVM. Moreover, SOAOS NVM shows greater endurance (> 2.4 V after 104 cycles) and longer charge retention time (> 109 s for 31% charge loss at 85°C). The result reveals that SOAOS-NVM has potential in system-on-panel and 3D stacked NVM applications.

Due to the packet-fairness property of the 802.11 WLANs, the clients with low rates take longer time to transmit a packet and would reduce the overall network throughput, as well as the per-node throughput of those high data rate clients. We propose a collaborative relay method, which allows high data rate clients to relay traffic for the low data rate clients to improve the network throughput. There are three original contributions made by this paper: 1) we develop a generalized model to analyze multi-hop relay for clients. By using this model, clients that are several hops away from each other may take the advantage of concurrent transmissions. 2) We propose a centralized algorithm to compute multi-hop relay topology for the clients and it can achieve the optimal throughput in our defined model. 3) We propose a distributed multi-hop relay protocol for clients dynamically connected to or disconnected from the network. Simulation results show that our algorithm can improve the throughput up to 42% on average, which is significantly better than the previous work. Up to 75% of the clients in the network use 1-hop or multi-hop relay, instead of connecting to the AP directly, for the performance gain; and up to 39% of the links have the opportunities to transmit concurrently with another link.

There are two widely used interference models to characterize interference in wireless communication, protocol model and physical model. The protocol model simplifies the interference by considering only two concerned communication links (or nodes). It ignores the cumulative interference from other links (or nodes). On the other side, the physical model considers the cumulative interference of the ambiance, but its application is very much limited due to the complexity to compute the physical interference of the whole system. In this paper, we study the AP placement problem in the physical interference model. By assuming a simple scheduling method, we propose a heuristic algorithm aiming to find the placement of minimal number of APs in an indoor region to meet the end users' QoS requirements. From the simulation results, we find that there is a significant difference in performance between the algorithms that use the physical model and the protocol model. It shows that the results obtained from AP placement algorithm in the protocol model are not close to the real situation due to neglect of cumulative interference.

Threshold User Authentication is widely used to provide distributed authentication service in Wireless Mesh Networks(WMNs). In a (t, n) threshold authentication scheme, secret authentication keys are shared among n mesh authentication servers (MAS) and any t out of n MASs can collaboratively provide the authentication service. The existing threshold authentication methods usually assume that MASs are static in the system. That is, t and n do not change after system initialization. However, in WMNs, MASs often join or leave the network freely. In this paper, we propose a novel threshold key redistribution protocol, aiming to cope with dynamic change of the authentication group. We also discuss the key redistribution protocol that can tolerate compromised MASs in the network.

Single crystal of strontium iodide doped with 1% europium (SrI 2 : 1% Eu2+) was grown by Vertical Gradient Freeze technique. Temperature response and thermoluminescence glow curves of SrI 2 : 1% Eu2+ were studied. UV excitation spectrum of SrI 2 : 1%Eu2+ at 298 K shows a broad excitation peak at 367 nm. At ∼ 24 K, additional excitation peaks appear in the range of 265 nm and 285 nm. UV excited emission spectra were measured as a function of temperature. Results indicates the thermal quenching of Eu emission starts from ∼ 400 K. The thermoluminescence curve indicates the elimination of the charge trap at 50 K may significantly expedite the scintillation process thus decrease the scintillation decay time of SrI 2 :Eu

A new family of Ce-containing scintillator materials is introduced. In this work, we report on the crystal growth of KGd 2 Cl 7 :Ce and CsGd 2 Cl 7 :Ce via the Vertical Gradient Freeze method. Various Ce concentrations from 0.5 to 10 at% have been tested to study the effect of dopant concentration on scintillation performance. Both KGd 2 Cl 7 :Ce and CsGd 2 Cl 7 :Ce have demonstrated good properties for gamma ray and thermal neutron detection. Scintillation light yield was ∼30,000 ph/MeV for KGd 2 Cl 7 : 3% Ce and ∼38,000 ph/MeV for CsGd 2 Cl 7 : 3% Ce. The crystals exhibited layered structure with cleavage planes.

In this research, we report our up-to-date results on the optical and scintillation properties of a new high light yield scintillation material: CsSr 1−x Eu x I 3 (x is in a range of 0 to 1). Single crystals with various Eu concentrations were successfully grown by Vertical Gradient Freeze technique in vacuum sealed quartz ampoules. Optical and scintillation properties were characterized. X-ray excited radioluminescence shows an emission peak at ∼450nm due to the 5d–4f transition in Eu2+. Scintillation light yield is 73,000 ph/MeV with 3.9% energy resolution at 662 keV for sample with Eu concentration of 7% relative to Sr. The scintillation time profile can be fitted by a single exponential with a time constant of 1.7–3.4 μs, depending on Eu concentration.

To make out a reasonable reference to the choice of sensor in the field of optical fiber temperature sensing, these temperature measurement experiments were carried out, including fiber Bragg grating, optical fiber Brillouin scattering, Raman Scattering Fiber Optic sensors, which are all packaged with FRP suitable for engineering applications. Then temperature measurement results are obtained. Meanwhile, the temperature characteristics of these sensors can be known by comparison between not only on sensing principle but experimental data. This can be a useful reference for the application of fiber optic temperature sensor in the temperature monitoring field.

With the development of wireless sensor network technology, more and more WSNs applications have the requirements of dealing with the critical mission. In this paper, we focus on the time critical problems of WSNs applications and design a new level control temporal consistency model with the priority tag. Then a Temporal Consistency Optimized Algorithm (TCO) is proposed to ensure that the packet will be delivered to sink before its lifetime is expected and schedule packets delivery according to their corresponding requirements. Finally, we analyze the performance of the TCO algorithm by theoretical derivation and experiment.