Analysis on error and tolerance for the wavefront reference source of point diffraction interferometer

2014 ◽  
Vol 7 (5) ◽  
pp. 855-862
Author(s):  
代晓珂 DAI Xiao-ke ◽  
金春水 JIN Chun-shui ◽  
于杰 Yu Jie
Keyword(s):  
Reference Source

Reference Source for Special Topics

1973 ◽  
Vol 18 (9) ◽  
pp. 434-434
Author(s):  
MICHAEL GABRIEL
Keyword(s):  
Reference Source

Penerapan Psikologi Islam dalam Praktek Profesi Psikolog Muslim

2020 ◽  
Vol 3 (1) ◽  
pp. 47-60
Author(s):  
Yulia Hairina ◽  
Mubarak Mubarak
Keyword(s):  
Discussion Group ◽  
Qualitative Approach ◽  
Psychological Services ◽  
Reference Source ◽  
Sampling Techniques ◽  
Purposive Sampling ◽  
Primary Reference ◽  
Islamic Psychology

This research aims to describe the application of Islamic Psychology in the practice of Muslim psychologists and the obstacles in its application. This study uses a qualitative approach for taking respondents using purposive sampling techniques. There are twenty respondents in this study. The method used in collecting data from this study is the interview and Focus Discussion Group. This study found that the understanding of Islamic Psychology was quite diverse, but in essence, an approach that used the Qur'an and Hadist was the primary reference source. Its application, including the psychological services, and the process of counseling and therapy were carried out by integrating psychology and Islam. The cases also handled varied, not limited to severe or mild cases. The challenges were related to the ability of the psychologists and the acceptance of the clients.

Ultrahigh-precision measurement timing jitter based on self-reference source

2020 ◽  
Vol 28 (11) ◽  
pp. 2429-2436
Author(s):  
Peng XU ◽  
◽  
Yuan-shan LIU ◽  
Jian-guo ZHANG ◽  
◽  
...  
Keyword(s):  
Precision Measurement ◽  
Timing Jitter ◽  
Reference Source ◽  
Self Reference

scholarly journals A New Application-Aware No-Reference Quality Assessment Method for IP Voice Services

2021 ◽  
Vol 29 (3) ◽  
Author(s):  
Péter Orosz ◽  
Tamás Tóthfalusi
Keyword(s):  
Service Quality ◽  
Performance Metrics ◽  
Assessment Method ◽  
Reference Source ◽  
User Privacy ◽  
Quality Model ◽  
Estimation Model ◽  
Full Reference ◽  
Reference Quality ◽  
The Voice

AbstractThe increasing number of Voice over LTE deployments and IP-based voice services raise the demand for their user-centric service quality monitoring. This domain’s leading challenge is measuring user experience quality reliably without performing subjective assessments or applying the standard full-reference objective models. While the former is time- and resource-consuming and primarily executed ad-hoc, the latter depends upon a reference source and processes the voice payload that may offend user privacy. This paper presents a packet-level measurement method (introducing a novel metric set) to objectively assess network and service quality online. It is accomplished without inspecting the voice payload and needing the reference voice sample. The proposal has three contributions: (i) our method focuses on the timeliness of the media traffic. It introduces new performance metrics that describe and measure the service’s time-domain behavior from the voice application viewpoint. (ii) Based on the proposed metrics, we also present a no-reference Quality of Experience (QoE) estimation model. (iii) Additionally, we propose a new method to identify the pace of the speech (slow or dynamic) as long as voice activity detection (VAD) is present between the endpoints. This identification supports the introduced quality model to estimate the perceived quality with higher accuracy. The performance of the proposed model is validated against a full-reference voice quality estimation model called AQuA, using real VoIP traffic (originated in assorted voice samples) in controlled transmission scenarios.

scholarly journals A Comprehensive Survey on Local Differential Privacy

2020 ◽  
Vol 2020 ◽  
pp. 1-29 ◽  
Author(s):  
Xingxing Xiong ◽  
Shubo Liu ◽  
Dan Li ◽  
Zhaohui Cai ◽  
Xiaoguang Niu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Statistical Learning ◽  
Data Privacy ◽  
Statistical Estimation ◽  
Differential Privacy ◽  
Future Research ◽  
Reference Source ◽  
Complex Data ◽  
Comprehensive Survey

With the advent of the era of big data, privacy issues have been becoming a hot topic in public. Local differential privacy (LDP) is a state-of-the-art privacy preservation technique that allows to perform big data analysis (e.g., statistical estimation, statistical learning, and data mining) while guaranteeing each individual participant’s privacy. In this paper, we present a comprehensive survey of LDP. We first give an overview on the fundamental knowledge of LDP and its frameworks. We then introduce the mainstream privatization mechanisms and methods in detail from the perspective of frequency oracle and give insights into recent studied on private basic statistical estimation (e.g., frequency estimation and mean estimation) and complex statistical estimation (e.g., multivariate distribution estimation and private estimation over complex data) under LDP. Furthermore, we present current research circumstances on LDP including the private statistical learning/inferencing, private statistical data analysis, privacy amplification techniques for LDP, and some application fields under LDP. Finally, we identify future research directions and open challenges for LDP. This survey can serve as a good reference source for the research of LDP to deal with various privacy-related scenarios to be encountered in practice.

Pulsed reference source for photon‐counting systems

1976 ◽  
Vol 47 (9) ◽  
pp. 1144-1147 ◽  
Author(s):  
E. C. Hagen ◽  
P. C. Eklund
Keyword(s):  
Photon Counting ◽  
Reference Source

The impact of different proportions of knitting elements on the resistive properties of conductive fabrics

2018 ◽  
Vol 89 (5) ◽  
pp. 881-890 ◽  
Author(s):  
Su Liu ◽  
Yanping Liu ◽  
Li Li
Keyword(s):  
Contact Resistance ◽  
Reference Source ◽  
Wearable Electronics ◽  
Electronic Textiles ◽  
Knitted Fabrics ◽  
Conductive Yarns ◽  
Key Factor ◽  
Resistive Networks ◽  
The Impact ◽  
Resistive Property

Conductive yarn is the key factor in fabricating electronic textiles. Generally, three basic fabric production methods (knit, woven, and non-woven) combined with two finishing processes (embroidery and print) are adopted to embed conductive yarns into fabrics to achieve flexible electronic textiles. Conductive yarns with knit structure are the most flexible and effective form of electronic textiles. Electronic textiles present many advantages over conventional electronics. However, in the process of commercialization of conductive knitted fabrics, it is a great challenge to control the complicated resistive networks in conductive knitted fabrics for the purpose of cost saving and good esthetics. The resistive networks in conductive knitted fabrics contain length-related resistance and contact resistance. The physical forms of conductive yarns in different fabrication structures can be very different and, thus, the contact resistance varies greatly in different fabrics. So far, study of controlling the resistive property of conductive fabrics has not been conducted. Therefore, establishing a systematic method for the industry as a reference source to produce wearable electronics is in great demand. During the industrialization of conductive knitted fabrics, engineers can estimate the resistive property of the fabric in advance, which makes the production process more effective and cost efficient. What is more, the resistive distribution in the same area of knitted fabrics can be fully controlled.

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