Optimal Replacement Time of Electrical Components Based on Constant-Interval Replacement Model: Equipment Inspection Method and Weibull Analysis

The operation of distribution system with the components in deteriorating condition makes the system reliability worsen. It is important to find the solution for balancing failure cost and maintenance benefits such as down-time and reliability. In this paper, time to replace the components in optimum condition based on constant-interval replacement mode is investigated. The optimal replacement time is mainly depended on component’s reliability and the cost ration of preventive replacement and failure replacement. In this paper, equipment inspection method and Weibull Analysis is applied to obtain the accurate reliability estimation. Weibull Analysis is applied with constant-interval replacement model to investigate the optimum replacement time for each component considering the different cost ratios. According to the quantitative results, the determination of the optimal replacement time (OPT) can minimize the total downtime and failure cost. Consequently, the reliability of the system is maximized and estimation also becomes more accurate due to sufficient approach.

Word Embeddings and Semantic Spaces in Natural Language Processing

One of the critical hurdles, and breakthroughs, in the field of Natural Language Processing (NLP) in the last two decades has been the development of techniques for text representation that solves the so-called curse of dimensionality, a problem which plagues NLP in general given that the feature set for learning starts as a function of the size of the language in question, upwards of hundreds of thousands of terms typically. As such, much of the research and development in NLP in the last two decades has been in finding and optimizing solutions to this problem, to feature selection in NLP effectively. This paper looks at the development of these various techniques, leveraging a variety of statistical methods which rest on linguistic theories that were advanced in the middle of the last century, namely the distributional hypothesis which suggests that words that are found in similar contexts generally have similar meanings. In this survey paper we look at the development of some of the most popular of these techniques from a mathematical as well as data structure perspective, from Latent Semantic Analysis to Vector Space Models to their more modern variants which are typically referred to as word embeddings. In this review of algoriths such as Word2Vec, GloVe, ELMo and BERT, we explore the idea of semantic spaces more generally beyond applicability to NLP.

Dynamic analysis, simulation, and control of a 6-DOF IRB-120 robot manipulator using sliding mode control and boundary layer method

Because of its ease of implementation,a linear PID controller is generally used to control robotic manipulators.Linear controllers cannot effectively cope with uncertainties and variations in the parameters;therefore,nonlinear controllers with robust performance which can cope with these are recommended.The sliding mode control(SMC)is a robust state feedback control method for nonlinear systems that,in addition having a simple design,efficiently overcomes uncertainties and disturbances in the system.It also has a very fast transient response that is desirable when controlling robotic manipulators.The most critical drawback to SMC is chattering in the control input signal.To solve this problem,in this study,SMC is used with a boundary layer(SMCBL)to eliminate the chattering and improve the performance of the system.The proposed SMCBL was compared with inverse dynamic control(IDC),a conventional nonlinear control method.The kinematic and dynamic equations of the IRB-120 robot manipulator were initially extracted completely and accurately,and then the control of the robot manipulator using SMC was evaluated.For validation,the proposed control method was implemented on a 6-DOF IRB-120 robot manipulator in the presence of uncertainties.The results were simulated,tested,and compared in the MATLAB/Simulink environment.To further validate our work,the results were tested and confirmed experimentally on an actual IRB-120 robot manipulator.

Smart phone-based context-aware augmentative and alternative communications system

A smartphone-based context-aware augmentative and alternative communication(AAC) was applied was in order to enhance the user's experience by providing simple, adaptive, and intuitive interfaces. Various potential context-aware technologies and AAC usage scenarios were studied, and an efficient communication system was developed by combining smartphone's multimedia functions and its optimized sensor technologies. The experimental results show that context-awareness accuracy is achieved up to 97%.

A New Evolutionary Method for Solving Combined Economic and Emission Dispatch

This paper presents a new evolutionary method called in Harvest Season Artificial Bee Colony (HSABC) algorithm for solving constrained problems of Combined Economic and Emission Dispatch (CEED). The IEEE-30 bus system is adopted as a sample system for determining the best solutions of the CEED problems considering operational constraints. Running outs of designed programs for the HSABC show that applications of various compromised factors have different implications on the CEED’s results, that minimum cost computations are started at different values, and that increasing load demands have affected costs, pollutant emissions and generated powers.

Study of Material Evaluation Probe Using a Longitudinal Wave and a Transverse Wave

Transmitting a longitudinal wave and a traverse wave into a composite material in a molten state has been studied in the online control of the composite material which cannot be evaluated by a conventional ultrasonic sensor as a final analysis, using the difference in the propagation characteristics of both modes. It is especially expected that measurement of the physical quantity which was not able to be conventionally measured can be performed by carrying out coincidence measurement of the ultrasonic wave in both modes. Therefore, in this research study, an ultrasonic probe, which can simultaneously transmit and receive a longitudinal wave and a traverse wave has been developed using an electromagnetic acoustic transducer (EMAT) because it has the advantage of measuring high temperature samples. In this study, two methods have been compared. The 1st method uses a traverse wave EMAT that travels in a vertical direction and a bar wave by which the low order mode is equivalent to longitudinal wave vibration. The other method is to carry out the mode conversion of the traverse wave by a traverse wave-EMAT. The longitudinal converted from the transverse wave are spread in the axis direction. As the experimental results of both optimizations of the drive conditions, it has been confirmed that the 2nd mode conversion method was promising. This paper reports about the trial process and the experimental results.

Mathematical Model with Energy and Clustering Energy Based Routing Protocols as Remediation to the Directional Source Aware Routing Protocol in Wireless Sensor Networks

In this paper, a routing protocol for wireless sensor network, baptized energy based protocol (EBP) is proposed. Wireless sensor network presents many challenges and constraints, and one of the major constraints is the routing problem. Due to the limited energy of sensor nodes, routing in this type of network shall perform efficiently to maximize the network lifetime. One of the proposed algorithms is the directional source aware routing protocol (DSAP) which, after simulation, showed a lot of limitations and drawbacks. The modified directional source aware routing protocol (MDSAP) was proposed by the authors of this paper to address some of the DSAP’s limitations but remains limited to a fixed topology, fixed source and stationary nodes. So EBP is proposed and operated under different scenarios and showed, after its simulation using TinyOS, many advantages in terms of load balancing, free looping, minimizing packet error rate and maximizing network lifetime.

Joint fuzzy background and adaptive foreground model for moving target detection

Moving target detection is one of the most basic tasks in computer vision.In conventional wisdom,the problem is solved by iterative optimization under either Matrix Decomposition(MD)or Matrix Factorization(MF)framework.MD utilizes foreground information to facilitate background recovery.MF uses noise-based weights to fine-tune the background.So both noise and foreground information contribute to the recovery of the background.To jointly exploit their advantages,inspired by two framework complementary characteristics,we propose to simultaneously exploit the advantages of these two optimizing approaches in a unified framework called Joint Matrix Decomposition and Factorization(JMDF).To improve background extraction,a fuzzy factorization is designed.The fuzzy membership of the background/foreground association is calculated during the factorization process to distinguish their contributions of both to background estimation.To describe the spatio-temporal continuity of foreground more accurately,we propose to incorporate the first order temporal difference into the group sparsity constraint adaptively.The temporal constraint is adjusted adaptively.Both foreground and the background are jointly estimated through an effective alternate optimization process,and the noise can be modeled with the specific probability distribution.The experimental results of vast real videos illustrate the effectiveness of our method.Compared with the current state-of-the-art technology,our method can usually form the clearer background and extract the more accurate foreground.Anti-noise experiments show the noise robustness of our method.

强抗泄漏的无条件安全动态秘密共享方案

(t,n)门限秘密共享中,分发者将秘密S分成n个秘密份额,使得任意不少于t个秘密份额可以成功重构秘密S,而小于门限t的秘密份额无法获得有关秘密的任何信息.为提高份额的机密性,减少验证份额过程所需的计算开销,增强秘密共享方案的防欺骗性、安全性、实用性以及抗泄漏性,本文提出了一种强抗泄漏的无条件安全动态秘密共享方案:(1)方案引入信息传递环和插值因子等技术作为重构通信方式和重构信息,有效提高份额的机密性;(2)方案分别为每个参与者分配一对验证钥以验证重构秘密的一致性,避免验证秘密份额的复杂过程,方案与可验证秘密共享方案具有相同的抗欺骗能力,可有效防止n-1参与者联合欺骗,较一般防欺骗方案(达到n/2或n/3防欺骗能力)有更强的抗欺骗能力;(3)方案安全性与敌手的计算能力无关,达到无条件安全性;(4)方案无需要更改秘密份额即可实现分享秘密的更新,达到动态性;(5)本文首次提出秘密共享中的最大泄漏率概念,用以描述秘密共享中最大可泄漏的秘密份额个数与总秘密份额个数的关系,可作为评价秘密共享机制中抗泄漏能力强弱的标准参数之一.

医疗大数据隐私保护多关键词范围搜索方案

随着医疗信息系统的急速发展,基于医疗云的信息系统将大量电子健康记录(EHRs)存储在医疗云系统中,利用医疗云强大的存储能力和计算能力对EHRs数据进行安全与统一的管理.尽管传统加密机制可以保证医疗数据在半诚实云服务器中的机密性,但对加密后的EHRs数据执行安全、快速、有效的范围搜索,仍是一个有待解决的关键问题.提出一种支持多关键词范围搜索的可搜索加密方案:利用向量积保持加密机制实现复杂查询结构的可搜索加密,可支持连接关键词查询、范围查询以及通配符的查询;通过随机化构建搜索索引和搜索陷门,实现搜索模式隐藏,达到搜索语句的隐私保护;采用矩阵哈达马积缩小所需密钥矩阵的维度.理论分析和实验结果表明:该方案在达到医疗数据隐私保证的同时,对用户的检索策略也进行了有效的隐私性保护,有效提高了检索效率,降低了创建索引及陷门所用时间,实现了多用户多文件下医疗数据的范围搜索能力.

3D depth image analysis for indoor fall detection of elderly people

This paper presents a new fall detection method of etderly people in a room environment based on shape analysis of 3D depth images captured by a Kinect sensor. Depth images are pre- processed by a median filter both for background and target. The sithouette of moving individual in depth images is achieved by a subtraction method for background frames. The depth images are converted to disparity map, which is obtained by the horizontal and vertical projection histogram statistics. The initial floor plane information is obtained by V disparity map, and the floor ptane equation is estimated by the least square method. Shape information of human subject in depth images is analyzed by a set of moment functions. Coefficients of ellipses are calculated to determine the direction of individual The centroids of the human body are catculated and the angle between the human body and the floor plane is calculated. When both the distance from the centroids of the human body to the floor plane and the angle between the human body and the floor plane are tower than some threshotds, fall incident will be detected. Experiments with different failing direction are performed. Experimental results show that the proposed method can detect fall incidents effectively.

Pipe Inspection System by Guide Wave Using a Long Distance Waveguide

In the industrial fields, many high temperature structures that require a non-destructive inspection exist. However, there are currently few sensors that can carry out non-destructive testing in a high temperature environment. In particular, the ultrasonic sensor is normally not used at over 50 degrees Celsius. Also, a special sensor for high temperature is currently available, but there are various constraints;it has not yet reached a level that is useful in industry. Therefore, we have been developing a new sensor system using a long waveguide which can transmit an ultrasonic wave from a long distance. Especially, this study focuses on applying the developed technique to a pipe which is used in a nuclear power plant. Therefore, the best rectangular-shaped waveguide was studied and attempted to be wound around a pipe to be driven by an acoustic source of a guide wave. Finally, the L (0, 2) and T (0, 1)-mode guide waves were successfully detected by optimizing the shape of the opposite edge of the rectangular-shaped waveguide that could detect the reflected signal from an artificial defect machined into a test pipe.

A Block Compressed Sensing for Images Selective Encryption in Cloud

The theory of compressed sensing(CS)has been proposed to reduce the processing time and accelerate the scanning process.In this paper,the image recovery task is considered to outsource to the cloud server for its abundant computing and storage resources.However,the cloud server is untrusted then may pose a considerable amount of concern for potential privacy leakage.How to protect data privacy and simultaneously maintain management of the image remains challenging.Motivated by the above challenge,we propose an image encryption algorithm based on chaotic system,CS and image saliency.In our scheme,we outsource the image CS samples to cloud for reduced storage and portable computing.Consider privacy,the scheme ensures the cloud to securely reconstruct image.Theoretical analysis and experiment show the scheme achieves effectiveness,efficiency and high security simultaneously.

Internet of Things: Towards a Solid Ecosystem of Interconnected Things

The Internet of Things (IoT) is a technological revolution that has changed everything we do and given us a new perspective on our daily lives, but despite the fact that numerous publications have focused on characterizing the many edges and technologies that make up an IoT system, the IoT ecosystem is still seen as too complex to be recognized as a stand-alone environment due to its significant diversity;hence, the objective of this research is to address such a complex environment in a way that highlights its components and distinguishes them both individually and in relation to their broader context. Therefore, the definition of IoT and its emergence were discussed and organized around the timeline of Internet development phases demonstrating that IoT has been a need that has accompanied the presence of the Internet since its early stages, and then its growth and impact were discussed and highlighted with estimates and numbers. On the technical side, each of the following groups, IoT components, protocols, and architectures, was defined, discussed, and grouped in such a way that their intergroup organization, as well as their placement and contribution to the overall ecosystem, was highlighted. This, in addition to the various examples mentioned throughout the discussion, will provide the reader with a better understanding of the Internet of Things and how deeply it has become entwined in our daily lives and routines as a result of its numerous applications.

Energy enhanced tissue texture in spectral computed tomography for lesion classification

Tissue texture reflects the spatial distribution of contrasts of image voxel gray levels,i.e.,the tissue heterogeneity,and has been recognized as important biomarkers in various clinical tasks.Spectral computed tomography(CT)is believed to be able to enrich tissue texture by providing different voxel contrast images using different X-ray energies.Therefore,this paper aims to address two related issues for clinical usage of spectral CT,especially the photon counting CT(PCCT):(1)texture enhancement by spectral CT image reconstruction,and(2)spectral energy enriched tissue texture for improved lesion classification.For issue(1),we recently proposed a tissue-specific texture prior in addition to low rank prior for the individual energy-channel low-count image reconstruction problems in PCCT under the Bayesian theory.Reconstruction results showed the proposed method outperforms existing methods of total variation(TV),low-rank TV and tensor dictionary learning in terms of not only preserving texture features but also suppressing image noise.For issue(2),this paper will investigate three models to incorporate the enriched texture by PCCT in accordance with three types of inputs:one is the spectral images,another is the cooccurrence matrices(CMs)extracted from the spectral images,and the third one is the Haralick features(HF)extracted from the CMs.Studies were performed on simulated photon counting data by introducing attenuationenergy response curve to the traditional CT images from energy integration detectors.Classification results showed the spectral CT enriched texture model can improve the area under the receiver operating characteristic curve(AUC)score by 7.3%,0.42%and 3.0%for the spectral images,CMs and HFs respectively on the five-energy spectral data over the original single energy data only.The CM-and HF-inputs can achieve the best AUC of 0.934 and 0.927.This texture themed study shows the insight that incorporating clinical important prior information,e.g.,tissue texture in this paper,into the medical imaging,such as the upstream image reconstruction,the downstream diagnosis,and so on,can benefit the clinical tasks.

Application of Fourier Series Expansion Method with PMLs to the Microcavities on Two-Dimensional Photonic Crystals

By using a Fourier series expansion method combined with Chew＇s perfectly matched layers （PMLs）, we analyze the frequency and quality factor of a micro-cavity on a two-dimensional photonic crystal is analyzed. Compared with the results by the method without PML and finite-difference time-domain （FDTD） based on supercell approximation, it can be shown that by the present method with PMLs, the resonant frequency and the quality factor values can be calculated satisfyingly and the characteristics of the micro-cavity can be obtained by changing the size and permittivity of the point defect in the micro-cavity.

A User Proprietary Obfuscate System for Positions Sharing in Location-Aware Social Networks

A user’s trajectory can be maliciously monitored by adversaries when they share the positions in location-aware social networking applications which require users to update their own locations continuously. An adversary infers user’s locations from the trajectories, and gleans user’s private information through them via location-aware social networking applications and public available geographic data. In this paper, we propose a user proprietary obfuscate system to suit situations for position sharing and location privacy preserving in location-aware social network. Users transform the public available geographic data into personal obfuscate region maps with pre-defined profile to prevent the location leaking in stationary status. Our obfuscation with size restricted regions method tunes user’s transformed locations fitting into natural movement and prevents unreasonable snapshot locations been recorded in the trajectory.

Ultrasonic Inspection System Using a Long Waveguide with an Acoustic Horn for High-Temperature Structure

The nondestructive inspection of a high temperature structure is required in order to guarantee its safety. However, there are no useful sensors for high temperature structures. Some of them cannot work at temperatures over 50°C. Another concern is that they are too expensive to use. A sensing system, which can transmit and receive an ultrasonic wave that travels a long distance using a long waveguide, has been studied. We confirmed that the optimal guided ultrasonic wave could travel more than 10 m using an electromagnetic transducer (EMAT) with a thin Ni-sheet surrounded on the surface of the bar and a 2-mm diameter bar as the waveguide. However, we had the difficult problem of receiving the reflected ultrasonic wave from the inside of a test specimen. We tried to improve the trial inspection system using an acoustic horn. An experiment in which the temperature of the test block was heated to about 500°C has now been completed. Finally, the condition of the bend in the waveguide to pass without reflection was confirmed.

High-Performance Magnetic-core Coils for Targeted Rodent Brain Stimulations

Objective and Impact Statement.There is a need to develop rodent coils capable of targeted brain stimulation for treating neuropsychiatric disorders and understanding brain mechanisms.We describe a novel rodent coil design to improve the focality for targeted stimulations in small rodent brains.Introduction.Transcranial magnetic stimulation(TMS)is becoming increasingly important for treating neuropsychiatric disorders and understanding brain mechanisms.Preclinical studies permit invasive manipulations and are essential for the mechanistic understanding of TMS effects and explorations of therapeutic outcomes in disease models.However,existing TMS tools lack focality for targeted stimulations.Notably,there has been limited fundamental research on developing coils capable of focal stimulation at deep brain regions on small animals like rodents.Methods.In this study,ferromagnetic cores are added to a novel angle-tuned coil design to enhance the coil performance regarding penetration depth and focality.Numerical simulations and experimental electric field measurements were conducted to optimize the coil design.Results.The proposed coil system demonstrated a significantly smaller stimulation spot size and enhanced electric field decay rate in comparison to existing coils.Adding the ferromagnetic core reduces the energy requirements up to 60%for rodent brain stimulation.The simulated results are validated with experimental measurements and demonstration of suprathreshold rodent limb excitation through targeted motor cortex activation.Conclusion.The newly developed coils are suitable tools for focal stimulations of the rodent brain due to their smaller stimulation spot size and improved electric field decay rate.