scholarly journals A Method for Detecting and Analyzing Facial Features of People with Drug Use Disorders

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1562
Author(s):  
Yongjie Li ◽  
Xiangyu Yan ◽  
Bo Zhang ◽  
Zekun Wang ◽  
Hexuan Su ◽  
...  
Keyword(s):  
Drug Use ◽  
High Performance ◽  
Large Scale ◽  
Facial Features ◽  
Clinical Workflow ◽  
Performance Accuracy ◽  
Drug Use Disorders ◽  
Large Scale Dataset ◽  
Novel Method ◽  
Facial Images

Drug use disorders caused by illicit drug use are significant contributors to the global burden of disease, and it is vital to conduct early detection of people with drug use disorders (PDUD). However, the primary care clinics and emergency departments lack simple and effective tools for screening PDUD. This study proposes a novel method to detect PDUD using facial images. Various experiments are designed to obtain the convolutional neural network (CNN) model by transfer learning based on a large-scale dataset (9870 images from PDUD and 19,567 images from GP (the general population)). Our results show that the model achieved 84.68%, 87.93%, and 83.01% in accuracy, sensitivity, and specificity in the dataset, respectively. To verify its effectiveness, the model is evaluated on external datasets based on real scenarios, and we found it still achieved high performance (accuracy > 83.69%, specificity > 90.10%, sensitivity > 80.00%). Our results also show differences between PDUD and GP in different facial areas. Compared with GP, the facial features of PDUD were mainly concentrated in the left cheek, right cheek, and nose areas (p < 0.001), which also reveals the potential relationship between mechanisms of drugs action and changes in facial tissues. This is the first study to apply the CNN model to screen PDUD in clinical practice and is also the first attempt to quantitatively analyze the facial features of PDUD. This model could be quickly integrated into the existing clinical workflow and medical care to provide capabilities.

scholarly journals An Australian Twin Study of Cannabis and Other Illicit Drug Use and Misuse, and Other Psychopathology

2012 ◽  
Vol 15 (5) ◽  
pp. 631-641 ◽  
Author(s):  
Michael T. Lynskey ◽  
Arpana Agrawal ◽  
Anjali Henders ◽  
Elliot C. Nelson ◽  
Pamela A. F. Madden ◽  
...  
Keyword(s):  
Drug Use ◽  
Large Scale ◽  
Illicit Drugs ◽  
Illicit Drug ◽  
Age Of Onset ◽  
Cannabis Use ◽  
Drug Use Disorders ◽  
Illicit Drug Abuse ◽  
Highly Correlated ◽  
Adult Twins

Cannabis is the most widely used illicit drug throughout the developed world and there is consistent evidence of heritable influences on multiple stages of cannabis involvement including initiation of use and abuse/dependence. In this paper, we describe the methodology and preliminary results of a large-scale interview study of 3,824 young adult twins (born 1972–1979) and their siblings. Cannabis use was common with 75.2% of males and 64.7% of females reporting some lifetime use of cannabis while 24.5% of males and 11.8% of females reported meeting criteria for DSM-IV cannabis abuse or dependence. Rates of other drug use disorders and common psychiatric conditions were highly correlated with extent of cannabis involvement and there was consistent evidence of heritable influences across a range of cannabis phenotypes including early (≤15 years) opportunity to use (h2 = 72%), early (≤16 years) onset use (h2 = 80%), using cannabis 11+ times lifetime (h2 = 76%), and DSM abuse/dependence (h2 = 72%). Early age of onset of cannabis use was strongly associated with increased rates of subsequent use of other illicit drugs and with illicit drug abuse/dependence; further analyses indicating that some component of this association may have been mediated by increasing exposure to and opportunity to use other illicit drugs.

Large-scale fabrication of porous bulk silver thin sheets with tunable porosity for high-performance binder-free supercapacitor electrodes

RSC Advances ◽  
2015 ◽  
Vol 5 (56) ◽  
pp. 45194-45200 ◽  
Author(s):  
Xiangyu Wang ◽  
Pinghui Zhang ◽  
Sascha Vongehr ◽  
Shaochun Tang ◽  
Yongguang Wang ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Thin Sheets ◽  
Bulk Silver ◽  
Binder Free ◽  
Novel Method

We report a novel method for the large-scale fabrication of porous bulk silver thin sheets (PSTS) built from three-dimensionally interconnected nanoparticles (NPs).

A MapReduce Clone Car Identification Model over Traffic Data Stream

2013 ◽  
Vol 346 ◽  
pp. 117-122
Author(s):  
Wen Chuan Yang ◽  
Guang Jie Lin ◽  
Jiang Yong Wang
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Ad Hoc ◽  
Image Data ◽  
Traffic Information ◽  
Identification System ◽  
Traffic Data ◽  
Traffic Surveillance ◽  
Fine Grain ◽  
Large Scale Dataset

Accompany the widely use of Intelligent Traffic in China, all traffic input data streams to the Traffic Surveillance Center (TSC). Some metropolitan TSC, such as in Beijing, produces up to 18 million records and 1T image data arriving every hour. Normally, the job of the TSC is to monitor and retain data. There is a tendency to put more capability into the TSC, such as ad-hoc query for clone car identification and feedback abnormal traffic information. Thus we definitely need to think about what can be kept in working storage and how to analysis it. Obviously, the ordinary database cannot handle the massive dataset and complex ad-hoc query. MapReduce is a popular and widely used fine grain parallel runtime, which is developed for high performance processing of large scale dataset. In this paper, we propose CarMR, a MapReduce Clone Car Identification system based on Hive/Hadoop frameworks. A distributed file system HDFS is used in CarMR for fast data sharing and query. CarMR supports fast locating clone car and also optimizes the route to catch fugitive. Our results show that the model achieves a higher efficiency.

Research of a MapReduce Model to Process the Traffic Big Data

2014 ◽  
Vol 548-549 ◽  
pp. 1853-1856 ◽  
Author(s):  
Wen Chuan Yang ◽  
He Chen ◽  
Qing Yi Qu
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Ad Hoc ◽  
Processing System ◽  
Traffic Information ◽  
Traffic Data ◽  
Fine Grain ◽  
Large Scale Dataset ◽  
Data Processing Center ◽  
Mapreduce Model

Normally, the job of the Traffic Data Processing Center (TDPC) is to monitor and retain data. There is a tendency to put more capability into the TDPC, such as ad-hoc query for speeding car identification and feedback abnormal traffic information. Thus we definitely need to think about what can be kept in working storage and how to analysis it. Obviously, the ordinary database cannot handle the massive dataset and complex ad-hoc query. MapReduce is a popular and widely used fine grain parallel runtime, which is developed for high performance processing of large scale dataset. In this paper, we propose MRTP, a MapReduce Traffic Processing system based on Hive/Hadoop frameworks. A distributed file system HDFS is used in MRTP for fast data sharing and query. MRTP supports fast locating speeding car and also optimizes the route to catch fugitive. Our results show that the model achieves a higher efficiency.

The Structure and Properties of MoSi2 Thin Film in Mos Process

1980 ◽  
Vol 38 ◽  
pp. 326-327
Author(s):  
C.K. Wu ◽  
P. Chang ◽  
N. Godinho
Keyword(s):  
Thin Film ◽  
Integrated Circuits ◽  
High Performance ◽  
Large Scale ◽  
Process Development ◽  
Structure And Properties ◽  
Metal Silicides ◽  
High Oxidation ◽  
Important Approach ◽  
High Oxidation Resistance

Recently, the use of refractory metal silicides as low resistivity, high temperature and high oxidation resistance gate materials in large scale integrated circuits (LSI) has become an important approach in advanced MOS process development (1). This research is a systematic study on the structure and properties of molybdenum silicide thin film and its applicability to high performance LSI fabrication.

Psychiatric and drug use disorders among veterans infected with hepatitis C virus

2001 ◽  
Vol 120 (5) ◽  
pp. A409-A409
Author(s):  
H ELSERAG ◽  
M KUNIK ◽  
P RICHARDSON ◽  
L RABENECK
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Drug Use ◽  
Drug Use Disorders

FACE RECOGNITION USING FUZZY INFERENCE SYSTEM

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Neural Networks ◽  
Fuzzy Inference ◽  
Facial Features ◽  
Facial Appearance ◽  
Feature Points ◽  
Inference System ◽  
Detection Techniques ◽  
The Face ◽  
Hair Style ◽  
Facial Images

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.

RECOMMENDATIONS FOR THE CHOICE OF MILKING INSTALLATIONS IN LOOSE HOUSING SYSTEMS OF COWS

2020 ◽  
Author(s):  
В.В. ГОРДЕЕВ ◽  
В.Е. ХАЗАНОВ
Keyword(s):  
Dairy Cows ◽  
High Performance ◽  
Large Scale ◽  
Dairy Farms ◽  
Economic Indicators ◽  
Technical Level ◽  
Housing Systems ◽  
Working Shift ◽  
Technical And Economic Indicators

При выборе типа доильной установки и ее размера необходимо учитывать максимальное планируемое поголовье дойных коров и размер технологической группы, кратность и время одного доения, продолжительность рабочей смены дояров. Анализ технико-экономических показателей наиболее распространенных на сегодняшний день типов доильных установок одинакового технического уровня свидетельствует, что наилучшие удельные показатели имеет установка типа «Карусель» (1), а установка типа «Елочка» (2) требует более высоких затрат труда и средств. Установка «Параллель» (3) занимает промежуточное положение. Из анализа пропускной способности и количества необходимых операторов: установка 2 рекомендована для ферм с поголовьем дойного стада до 600 голов, 3 — не более 1200 дойных коров, 1 — более 1200 дойных коров. «Карусель» — наиболее рациональный, высокопроизводительный, легко автоматизируемый и, следовательно, перспективный способ доения в залах, особенно для крупных молочных ферм. The choice of the proper type and size of milking installations needs to take into account the maximum planned number of dairy cows, the size of a technological group, the number of milkings per day, and the duration of one milking and the operator's working shift. The analysis of technical and economic indicators of currently most common types of milking machines of the same technical level revealed that the Carousel installation had the best specific indicators while the Herringbone installation featured higher labour inputs and cash costs. The Parallel installation was found somewhere in between. In terms of the throughput and the required number of operators Herringbone is recommended for farms with up to 600 dairy cows, Parallel — below 1200 dairy cows, Carousel — above 1200 dairy cows. Carousel was found the most practical, high-performance, easily automated and, therefore, promising milking system for milking parlours, especially on the large-scale dairy farms.

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