Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlating Optimal Size, Cycle Life Estimation, and Technology Selection of Batteries: A Two-Stage Approach for Microgrid Applications

A challenge in designing a microgrid system is determining the optimal size of the battery storage system (BSS). The annual investment cost of a BSS depends mainly on its size and the estimated BSS lifetime, which is defined as the total number of charge/discharge cycles. This depends heavily on how deep the battery is discharged during each cycle. Therefore, it is particularly important to determine the BSS's optimal size, depth of discharge, and lifetime cycling when adding a BSS in a microgrid. This paper introduces a two-stage approach to determine the optimal size, maximum Depth of Discharge (DoD), and service lifetime (in years) of a BSS. The proposed methodology is implemented in the following two stages: 1) mixed integer linear programing planning algorithm is developed in the first stage to determine the optimal size, maximum DoD, and number of performed partial cycles; and 2) second stage, which implements the obtained results from the first stage to estimate the battery's lifetime in years and selects the battery technology, as well as the equivalent number of complete cycles. The effectiveness of the proposed framework is validated using numerical simulations, as well as a comparative case study.
A PEER REVIEW OF THE PROCESSING TECHNOLOGIES AND APPLICATIONS OF GREEN COMPOSITES IN A BIOMEDICAL AREA

Use of green composites for contemporary medication, is anticipated to be a key subject of modernday chemistry research. As such, a lot of research is being carried out on the green materials and their potential use in biomedical applications. This paper discusses about the some basic applications of green materials in the field of the biomedical area and there production. Crucial production concepts of bio-composites, like the different types of natural biocomposites, the composing material classes and the common families and their fabrication techniques are discussed. The technologies discussed include extrusion/injection, compression, and pultrusion process for fabrication of these fibers is discussed.
MIMO Antenna H-Plane Isolation Enhancement using UC-EBG Structure and Metal Line Strip for WLAN Applications

This paper presents design of novel uniplanar compact Electromagnetic Band Gap (EBG) structure and its application in enhancement of isolation in H-Plane of MIMO antenna system for WLAN (5.8 GHz). Isolation enhancement or coupling reduction of 5.6 dB is achieved by etching out the proposed EBG structure from the ground plane of microstrip patch MIMO antenna. Center to center distance is reduced to 0. 45λ0 due to compactness of EBG. A metal line strip between radiating patches is used for further reduction in mutual coupling at 5.8 GHz. There is significant enhancement of 16.2 dB in isolation due to the introduction of metal line strip. Hence the total 21.8 dB reduction in mutual coupling is achieved and this coupling reduction is also verified by surface current plots and measured result. The envelope correlation coefficient (ECC) is less than 0.01 and channel capacity loss (CCL) is less than 0.1 bps/Hz at operating frequency.
Mapmaking for Language Documentation and Description

This paper introduces readers to map making as part of language documentation. We discuss some of the benefits and ethical challenges in producing good maps, drawing on linguistic geography and GIS literature. We then describe current tools and practices that are useful when creating maps of linguistic data, particularly using locations of field sites to identify language areas/boundaries. We demonstrate a basic workflow that uses CartoDB, before demonstrating a more complex workflow involving Google Maps and TileMill. We also discuss presentation and archiving of mapping products. The majority of the tools identified and used are open source or free to use.
A 9.6 nW, 8-Bit, 100 S/s Envelope-to-Digital Converter for Respiratory Monitoring

The signal’s envelope contains important features for a host of applications empowered by machine learning algorithms. Conventionally, the raw analog signal is digitized first, followed by feature extraction in the digital domain. This brief presents an ultra-low-power envelope-to-digital converter (EDC), with respiratory monitoring as one of its applications. The EDC consists of a passive switched-capacitor envelope detector and an inseparable successive-approximation-register analog-to-digital converter (ADC). The two blocks at different sampling rates directly integrate without a buffer between them thanks to a ping-pong operation of their sampling capacitors. An EDC prototype was fabricated in a 180-nm CMOS. It provides 7.1 effective bits of ADC resolution and supports input signal bandwidth up to 5 kHz and an envelope bandwidth up to 50 Hz while consuming 9.6 nW.
Fault Diagnosis and Tolerance Control of Five-Level Nested NPP Converter Using Wavelet Packet and LSTM

The five-level nested neutral-point-pilot (NPP) topology, as a new structure for converters, bears the advantages of a high power density, robustness, and flexibility and is therefore suitable for high-voltage and high-power applications. For a multilevel converter, as the number of power electronic switches increases, the risk of switch failure increases, together with the complexity of fault detection and tolerance control. The requirements for a higher operational stability and reliability continue to grow. However, studies on fault tolerance for multilevel converters are limited. In this paper, a fault diagnosis and tolerance solution for a five-level nested NPP converter is proposed. For the fault diagnosis, a deep learning method integrating the wavelet packet transform and long short-term memory is presented. Both open- and short-circuit switch failures can be precisely detected and located without the requirement of a large sample set. Two software-based control strategies for fault tolerance are adopted, and low-cost hardware reconfigurations are also implemented to prevent failure expansion and ensure continuous operation. Furthermore, the voltages of dc-link capacitors and flying capacitors are effectively balanced with the improved algorithm even when a failure occurs. Finally, the effectiveness of the fault-tolerant strategy are proven by simulations and experiments.
A COMPACT MULTIBAND MIMO ANTENNA FOR IEEE 802.11 A/B/G/N APPLICATIONS

A compact multiband multiple-input-multiple-output (MIMO) antenna for WLAN applications is presented in this paper. The proposed MIMO antenna consists of two symmetric monopole radiating elements designed to operate over 2.45, 5.2, and 5.8 GHz bands. The isolation is enhanced by using several techniques such as parasitic elements and defected ground structure. The measured S11 < −10 dB is obtained over 2.36–2.68 GHz and 4.81–5.95 GHz, which can cover IEEE 802.11 a/b/g/n frequency bands (2.4–2.4835 GHz, 5.15–5.35 GHz, and 5.725–5.875 GHz). The measured isolation values S21 are less than −24 dB and −27 dB over the lower and higher frequency bands, respectively. The envelope correlation coefficient (ECC) of the proposed antenna is less than 0.027 and 0.005 over the lower and higher operating bands, respectively. The overall size of the proposed antenna is 50 × 30 × 1.59 mm3. The proposed antenna is a good candidate for IEEE 802.11 a/b/g/n applications.
Ubiquitous User Interfaces: Multimodal Adaptive Interaction for Smart Environments

Computer technology is currently changing our lives and the way we handle technology. The computer moves from a business machine dedicated to specific tasks in a well defined environment to a universal problem solver in all areas of live. Powerful mobile devices that are always online, and the ongoing paradigm shift towards ubiquitous computing concepts (Weiser, 1993) provide increasingly complex functionality and allow remote access to additional services and information. Wireless ad-hoc network technologies and the upcoming Internet of Things AbsTRACT
The Forgotten Dimension

Thank you for reading the forgotten dimension. Maybe you have knowledge that, people have search numerous times for their favorite novels like this the forgotten dimension, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they are facing with some infectious bugs inside their desktop computer. the forgotten dimension is available in our digital library an online access to it is set as public so you can download it instantly. Our book servers spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the the forgotten dimension is universally compatible with any devices to read.
Tactile display technology and its developing trend

The tactile physiology and phenomena related to tactile display are first described in this paper,and then the tactile language and the status of tactile stimulation technologies employed in tactile display which include the vibration stimulation,electrical stimulation,waterjet stimulation,pneumatic stimulation and blunt pin stimulation,etc.,and in the end of this paper,the author makes a summary of the hotspots and developing trends in tactile display field,and an brief introduction to fusion tactile,color-tactile,spatio-temporal tactile,ramp tactile and multimodal tactile.
Choosing a Good Toolkit, II: Simulations and Conclusions

This paper continues our study of heuristics employed to choose dynamically tools to put in a toolkit, where the value of any tool can be discovered only by choosing it. This is a multi-armed bandit problem with “arms” that are not independent, hence it is a problem for which the optimal solution is virtually impossible to find. We study the relative performance of a number of heuristic decision rules for discount factors from 0.7 to 0.99 via simulation in the context of a small number of test problems, learning the strengths and weaknesses of the various heuristics.
Development of the USAF HyTech Scramjet Engine Demonstrator

This paper will deal only with the hypersonic missile component of the Hytech program - specifically with the development of the current generation hydrocarbon fuelled engine for the missile developed throughout the HySet sub program. The paper reviews the Aerojet Strut jet Concept, Performance Test Engine and the first and second generation Ground Engine Demonstrator with a review of the tests conducted. The paper concludes with a description of the flight testing still to be done within the program.
COMPACT WILKINSON POWER DIVIDER WITH HIGHER ORDER HARMONICS SUPPRESSION FOR LTE APPLICATION

This paper presents a compact Wilkinson power divider (WPD) operating at 0.7 GHz (LTE band) with higher order harmonics suppression based on step impedance shunt stubs (SISSs) and defected ground structure (DGS). The quarter wavelength lines of conventional WPD are replaced by a host line loaded with a DGS and a pair of SISSs. The DGS and SISS of the proposed line serve as a high series inductance and shunt capacitance, respectively. Therefore, a compact quarter wavelength line is designed compared to conventional one. A prototype of the proposed power divider is designed based on the proposed line, which provides a size reduction of 71% as compared to conventional WPD (CWPD) at 0.7 GHz. In addition, upper edge selectivity is found to be 40 dB/GHz along with higher order harmonics suppression up to the 10th order (7 GHz) by a level better than 20 dB. The proposed power divider is experimentally verified with the simulated one and found to be same.
Fully Configurable Capacitor-Less Oversampling DC Offset Cancellation for Direct Conversion Receivers

This brief presents a fully integrated dc offset cancellation (DCOC) scheme with configurable cut-off frequency and settling time. The proposed digitally assisted real-time DCOC scheme prevents the high gain baseband circuitry from saturation in direct conversion receivers. The proposed DCOC is designed and implemented in a $0.18~\mu \text{m}$ CMOS process. It occupies an area of 0.042 mm2 and consumes a current of 0.58 mA for I and Q paths under 1.8 V supply. The residual output dc offset voltage (DCOV) is less than 5 mV under the maximum baseband gain of 62 dB. The 3-dB high-pass cut-off frequency can be configured from 100 Hz to 1 kHz and settling time varying from 5.7 ms to 0.7 ms when the receiver operates under the maximum baseband gain.
Research on the Method for Fog Detection and Removal Based on Traffic Video

Fog causes traffic video images blurred and is not conducive to the extraction of various traffic parameters. The paper proposes a traffic-video based foggy weather identification method and a fast restoration approach for traffic image blurred by foggy. Firstly,the current background is generated from the real-time traffic video. Difference image is obtained by subtracting the current background image from the sunny background image which is generated in advance. And then,texture analysis is executed on the difference image to recognize the current weather. Finally,if it is foggy,the current traffic video images are recovered by the simplified dark channel prior principle. To verify the effectiveness of our algorithm,traffic videos about the same traffic scene,at the same position and within different weather conditions are collected and stitched together randomly. Experimental results show that the proposed algorithm not only can accurately identify the current weather and improve traffic image quality when the current weather is fog,but also decrease time complexity when comparing with various other algorithms and satisfy real-time requirement.
Research on current situations for functional classification of timing

Time is a fundamental variable that must be quantified by organisms to survive. Depending on the previous functional definition, timing can be divided into explicit timing and implicit timing. For an explicit timing task, the estimation of the stimulus duration is given in the form of perceptual discrimination (perceptual timing) or a motor response (motor timing). For implicit timing, participants can subconsciously (exogenous) or consciously (endogenous) establish temporal expectation. However, the ability of humans to explicitly or implicitly direct attention in time varies with age. Moreover, specific brain mechanisms have been suggested for temporal processing of different time scales (microseconds, hundreds of milliseconds, seconds to minutes, and circadian rhythms). Furthermore, there have been numerous research studies on the neural networks involved in explicit timing during the measurement of sub-second and supra-second intervals. Zhihan Xu Okayama University, Japan Qiong Wu Okayama University, Japan Chunlin Li Capital Medical University, China Yujie Li Central China Normal University, China Hongbin Han Peking University, China Dehua Chui Peking University, China Satoshi Takahashi Okayama University, Japan Jinglong Wu Okayama University, Japan Research on Current Situations for Functional Classification of Timing 223 FUNCTIONAL CLASSIFICATION OF TIMING Temporal processing is crucial for human behavior and cognition. It allows us to determine what is occurring in our environment and when to respond to events. The ability to direct attention to task-relevant information can enhance our behavioral performance. Temporal orienting selective attention is central for optimizing performance by biasing the neural processing of relevant information and suppressing irrelevant items (Moran & Desimone, 1985). Coull and Nobre (2008) suggested that tasks used temporal cues might be divided on the basis of whether the cue is explicitly or implicitly processed. Explicit timing is engaged when the participants make a deliberate estimate of a discrete duration. Implicit timing is engaged, even without a specific instruction to time, whenever sensorimotor information is temporally structured and can be used to predict the duration of future events. In explicit timing, the subjects are instructed to pay attention to the duration of a stimulus. In contrast, implicit timing requires the participants to perform tasks in which timing is important but not the main focus of the task (J. Coull & Nobre, 2008). For example, in a collision judgment task, participants must judge the speed of one or more objects that are moving and then predict the future location of the objects. Thus, this temporal processing focuses on collision judgment; however, time is not central to the task. The critical distinction between explicit timing and implicit timing is whether the task instructions require the participants to afford an overt estimate of duration.
DACADE: a systematic data collection and analysis tool for design students

Creating a successful product is a goal of every designer. To do so, it is important for a designer to understand consumers’ perceptions of a product early in the design process. One way to do this is by collecting data systematically from consumers representing the target audience and then to analyze those data statistically. Norman has claimed that design students lack the skills and knowledge of data collection, user testing and data analysis to support design solutions in the product design and development process. Consequently, their products might not be acceptable to the intended consumers and thus result in a failure in the marketplace. Norman, however, cites no empirical evidence in support of his claim. This study therefore took up the challenge of producing such evidence. Via a comprehensive archival search, it first scrutinized university design curricula to establish if design students are actually taught data collection and analysis methods. This was followed by a survey and a series of interviews with design students and lecturers. The results supported Norman’s claim, suggesting that there is a need to overcome this deficit. Further investigations were then carried out into existing tools supporting the running of user tests. These revealed that no suitable tool existed. It was therefore decided to develop a simple software tool, DACADE, to help design students gather consumer opinions and run simple data analyses. Paper prototypes of DACADE were prepared and evaluated in two formative usability tests to ensure that DACADE would not contain any usability flaws. Based on the results in the first usability test, a tutorial was added and tested in the second usability test to aid design students’ DACADE usage. Upon implementation, a User Acceptance Test was conducted to determine the level of user satisfaction, perceived usability and aesthetic appeal of DACADE among design students. Given design students’ sensitivity to aesthetics, that measure was considered especially important. Results indicated that, despite the presence of the tutorial, the design students tested were still unable to grasp the necessary understanding and acquire the essential skill of collecting and analyzing data systematically. The general discussion addresses several theoretical implications concerning the transfer of learning, the appropriateness of graphics used in a software tool, and user motivation in a learning environment. It also proposed future studies. It provides strong empirical support for Norman’s provocative claim.
Estimation and inference for time-varying spectra of locally stationary SLEX processes : In Memory of Jonathan A. Raz

Ombao et al (JASA, 2001) have proposed an automatic procedure to estimate the time-varying spectrum of a bivariate non-stationary process. This Auto-SLEX method uses the so-called Smooth Localized complex EXponential basis function which are simultaneously orthogonal and localized in both the time and frequency domain. In this paper we investigate the properties of the SLEX estimator under a new model of locally stationary SLEX processes which have a well defined time-varying SLEX spectrum. The SLEX model is a sequence of SLEX processes defined via a spectral representation with respect to the SLEX basis as stochastic building blocks and having spectra which are piecewise constant over time. In the asymptotic limit it allows for a smoothly-varying ”evolutionary” spectrum. Due to its special structure this new model allows for simple synthesis of non-stationary processes of finite length and, hence, can be used to perform statistical inference on the SLEX estimator. We propose two different bootstrap procedures for inference in the frequency domain for non-stationary processes. We evaluate the performance of these procedures via a small simulation study.
A common language effect size statistic.

Some of the shortcomings in interpretability and generalizability of the effect size statistics currently available to researchers can be overcome by a statistic that expresses how often a score sampled from one distribution will be greater than a score sampled from another distribution. The statistic, the common language effect size indicator, is easily calculated from sample means and variances (or from proportions in the case of nominal-level data). It can be used for expressing the effect observed in both independent and related sample designs and in both 2-group and n-group designs
CS:APP2e Web Aside ASM:SSE: SSE-Based Support for Floating Point

The material in this document is supplementary material to the book Computer Systems, A Programmer’s Perspective, Second Edition, by Randal E. Bryant and David R. O’Hallaron, published by Prentice-Hall and copyrighted 2011. In this document, all references beginning with “CS:APP2e ” are to this book. More information about the book is available at csapp.cs. cmu.edu. This document is being made available to the public, subject to copyright provisions. You are free to copy and distribute it, but you should not use any of this material without attribution.
Steganalysis of digital images using rich image representations and ensemble classifiers

Modern detectors of steganographic communication in digital images are implemented as supervised classifiers trained in pre-defined feature spaces also called image models. Currently, the Support Vector Machine (SVM) is the machine-learning tool of choice in the steganalysis community due to its accuracy and a well-founded theory. However, in order to keep the SVM training computationally feasible, feature spaces need to be designed to be low-dimensional. Consequently, their construction often consists of a series of clever tricks and heuristic dimensionality-reduction techniques. Recent trends in steganalysis, however, have shown that more complex and higher-dimensional image models could deliver substantially better performance. In this dissertation, we propose a novel framework for steganalysis of digital images in which we replace SVMs with the ensemble classifier, a scalable machine-learning alternative offering comparable accuracy at a fraction of a computational cost. This allows us to approach the feature-space building process in a more systematic and exhaustive way. In particular, we propose to construct feature spaces as collections of a large number of simpler submodels, each of them capturing different types of dependencies among image coefficients. As a result, we obtain a high-dimensional rich statistical descriptor of images, the so-called rich model, which is then used for the classifier training. To demonstrate the power of the proposed methodology, we construct rich models for images in raster formats and JPEGs, the two most commonly used image representations. The 34, 671-dimensional spatial domain rich model consists of co-occurrences of neighboring samples of noise residuals obtained by various filters, and the 22, 510-dimensional JPEG domain rich model consists of submodels capturing different types of dependencies among DCT coefficients of JPEG images. Both rich models, combined with the ensemble classifier, are shown to significantly outperform previous art across a wide range of steganographic schemes hiding data in both domains. This work is presented as a self-contained text, covering all technical details of the ensemble classifier and the rich-model construction, their implementation, and experimental performance evaluation.