scholarly journals A Cognitive Model of the «Spread of Drug Abuse»

2019 ◽  
Vol 13 (4) ◽  
pp. 535-546
Author(s):  
Alexander Sukhodolov ◽  
Valentina Marenko ◽  
Anna Bychkova
Keyword(s):  
Drug Abuse ◽  
Cognitive Modeling ◽  
Large Scale ◽  
Leisure Activities ◽  
Cognitive Model ◽  
Cognitive Structure ◽  
Cognitive Map ◽  
Prevention Measures ◽  
Contributing Factors ◽  
Systemic Feature

The authors examined the problem of the spread of drug abuse and describe a research procedure based on the method of cognitive modeling. To achieve this, the authors formulated the problems that are solved through cognitive mode­ling, which includes the following stages: outlining the problem field, building a cognitive map in the form of an orgraph, coordinating expert evaluations of the mutual impact of various factors, working out expert rules based on the cause-and-effect speculations, and conducting an imitation experiment. The first stage of cognitive modeling included an overview of research publications on the problem, which allowed the authors to identify the set of contributing factors. Stages of cognitive mo­deling were used to build a cognitive model «The spread of drug abuse» with such influencing factors as «the condition of the dwelling and utilities sphere», «professional occupation», «degree of the society’s criminalization», «organization of leisure activities and cultural work for the population», «prevention measures». The target factor was «the spread of drug abuse». The adequacy of the developed cognitive structure was verified by the systemic feature of «sensitivity» in the imitation experiment that recreates some semblance of reality in laboratory conditions. Analytical procedures were used to determine the expert evaluations of the mutual impact of factors and to work out expert rules. A cognitive map was developed in the form of a weighed orgraph, which was viewed as the framework of the problem where it was possible to observe the changes in the overall holistic situation by influencing its various points. The imitation experiment was conducted using Microsoft Excel, and its results agree with the logics of speculations. It is stated that although the simplified cognitive map includes five factors that influence the problem, increasing their number to build a more large-scale version of the cognitive model will contribute to deeper and more comprehensive research of the problem. The presented model is a promising area for the application of modern methods of researching the spread of drug abuse and spread of crimes in the sphere illegal drug trade with the use of Big Data technology.

scholarly journals Theoretical justification of pedagogical situations cognitive modeling

2018 ◽  
Vol 7 (2) ◽  
pp. 245-247
Author(s):  
Alsu Raufovna Kamaleeva ◽  
Svetlana Yurevna Gruzkova
Keyword(s):  
Cognitive Modeling ◽  
Cognitive Model ◽  
Cognitive Map ◽  
Educational Process ◽  
Theoretical Justification ◽  
Second Stage ◽  
The Third ◽  
Third Stage ◽  
Major Factors

The following paper deals with the application of methodology of pedagogical situations cognitive modeling, which is considered by the authors as a process consisting of six consecutive and interconnected stages. The first stage is a formulation of the purpose and the corresponding tasks. The second stage provides collecting, systematization and analysis of a pedagogical situation with the subsequent allocation of the major factors influencing development of the situation and determination of interrelation between them, i.e. creation of a cognitive map. At the third stage a focused count is created as a result of accounting of the cause and effect chains reflecting the system of interaction between the educational process subjects and allowing to form a pedagogical theory on the basis of basic person study categories: consciousness, thinking, knowledge, understanding, etc. The fourth stage assumes combination of the cognitive map and the focused count in a uniform cognitive model of the studied pedagogical situation. The fifth stage is focused on a real pedagogical situation cognitive model adequacy check i.e. on its verification. The last sixth stage allows to define possible options of a pedagogical situation development by a cognitive model, to find ways and mechanisms of a situation impact.

scholarly journals Dynamic Network Strategies for SARS-CoV-2 Control on a Cruise Ship

2020 ◽  
Author(s):  
Samuel M. Jenness ◽  
Kathryn S. Willebrand ◽  
Amyn A. Malik ◽  
Benjamin A. Lopman ◽  
Saad B. Omer
Keyword(s):  
Clinical Response ◽  
Large Scale ◽  
Leisure Activities ◽  
Dynamic Network ◽  
Optimal Strategies ◽  
Transmission Model ◽  
Contact Network ◽  
Prevention Measures ◽  
Contact Networks ◽  
Before And After

ABSTRACTSARS-CoV-2 outbreaks have occurred on several nautical vessels, driven by the high-density contact networks on these ships. Optimal strategies for prevention and control that account for realistic contact networks are needed. We developed a network-based transmission model for SARS-CoV-2 on the Diamond Princess outbreak to characterize transmission dynamics and to estimate the epidemiological impact of outbreak control and prevention measures. This model represented the dynamic multi-layer network structure of passenger-passenger, passenger-crew, and crew-crew contacts, both before and after the large-scale network lockdown imposed on the ship in response to the disease outbreak. Model scenarios evaluated variations in the timing of the network lockdown, reduction in contact intensity within the sub-networks, and diagnosis-based case isolation on outbreak prevention. We found that only extreme restrictions in contact patterns during network lockdown and idealistic clinical response scenarios could avert a major COVID-19 outbreak. Contact network changes associated with adequate outbreak prevention were the restriction of passengers to their cabins, with limited passenger-crew contacts. Clinical response strategies required for outbreak prevention included early mass screening with an ideal PCR test (100% sensitivity) and immediate case isolation upon diagnosis. Public health restrictions on optional leisure activities like these should be considered until longer-term effective solutions such as a COVID-19 vaccine become widely available.

scholarly journals The synthesis of strategies for the efficient performance of sophisticated technological complexes based on the cognitive simulation modelling

2021 ◽  
pp. 110-117
Author(s):  
N.A Zaiets ◽  
O.V Savchuk ◽  
V.M Shtepa ◽  
N.M Lutska ◽  
L.O Vlasenko
Keyword(s):  
Cluster Analysis ◽  
Energy Efficiency ◽  
Cognitive Modeling ◽  
Mutual Influence ◽  
Cognitive Model ◽  
Oriented Graph ◽  
Cognitive Map ◽  
Fuzzy Cognitive Maps ◽  
Fuzzy Cognitive Map ◽  
Systems Methodology

Purpose. Improving the productivity and energy efficiency of complex technological complexes through the development and use of scenario-cognitive modeling in control systems. Methodology. Fuzzy cognitive maps, in the form of a weighted oriented graph, were used to develop a scenario-cognitive model. As a result of the conducted research studies, a new strategy of generalization of an expert estimation of mutual influences of concepts on the basis of methods of the cluster analysis is offered. Findings. Based on experimental research and object-oriented analysis of a complex technological complex, a structure of a fuzzy cognitive model is created. A scenario-cognitive model in the form of a weighted oriented graph (fuzzy cognitive map) has been developed, which illustrates a set of connections and the nature of the interaction of expertly determined factors. To solve the problem of impossibility of operative interrogation of experts in case of change in parameters of functioning of difficult technological complexes, expert estimations of values of weight coefficients of mutual influence of concepts are received. Cluster analysis methods were used to group expert assessments and determine a single value as a result of the research. The results of the scenario-cognitive modeling of the enterprise showed that production shutdowns and abnormal situations related to the failure of electrical equipment, deviations of the technological regime and the quality of wastewater treatment have a significant impact on the dynamics of productivity, energy efficiency and efficient use of equipment. Originality. The new scenario-cognitive model developed for forecasting the situation in the absence of accurate quantitative information consists in creating a fuzzy cognitive map, for modeling which many parameters of complex technological complexes are expertly determined. Using the developed methodology, a degree of interaction of these parameters is found, which allows determining dynamics of change in target criteria of functioning under various management strategies. Practical value. On the basis of the created scenario-cognitive model, software has been developed which allowed analyzing dynamics of change in productivity, energy efficiency and efficiency of use of the equipment under possible scenarios of functioning of difficult technological complexes is developed.

scholarly journals Psychiatric disorders in China: strengths and challenges of contemporary research and clinical services

2021 ◽  
pp. 1-14
Author(s):  
Xiao Chang ◽  
Qiyong Gong ◽  
Chunbo Li ◽  
Weihua Yue ◽  
Xin Yu ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Disease Burden ◽  
Large Scale ◽  
Well Being ◽  
Research Quality ◽  
Psychiatric Research ◽  
Clinical Services ◽  
Contributing Factors ◽  
Brain Functions ◽  
Neuroscience Research

Abstract China accounts for 17% of the global disease burden attributable to mental, neurological and substance use disorders. As a country undergoing profound societal change, China faces growing challenges to reduce the disease burden caused by psychiatric disorders. In this review, we aim to present an overview of progress in neuroscience research and clinical services for psychiatric disorders in China during the past three decades, analysing contributing factors and potential challenges to the field development. We first review studies in the epidemiological, genetic and neuroimaging fields as examples to illustrate a growing contribution of studies from China to the neuroscience research. Next, we introduce large-scale, open-access imaging genetic cohorts and recently initiated brain banks in China as platforms to study healthy brain functions and brain disorders. Then, we show progress in clinical services, including an integration of hospital and community-based healthcare systems and early intervention schemes. We finally discuss opportunities and existing challenges: achievements in research and clinical services are indispensable to the growing funding investment and continued engagement in international collaborations. The unique aspect of traditional Chinese medicine may provide insights to develop a novel treatment for psychiatric disorders. Yet obstacles still remain to promote research quality and to provide ubiquitous clinical services to vulnerable populations. Taken together, we expect to see a sustained advancement in psychiatric research and healthcare system in China. These achievements will contribute to the global efforts to realize good physical, mental and social well-being for all individuals.

scholarly journals Development and Evaluation of Geostatistical Methods for Estimating Weather Related Collisions: A Large-Scale Case Study

2021 ◽  
pp. 036119812110200
Author(s):  
Andy H. Wong ◽  
Tae J. Kwon
Keyword(s):  
Large Scale ◽  
Mean Squared Error ◽  
Hot Spot ◽  
High Ratio ◽  
Contributing Factors ◽  
Geostatistical Methods ◽  
Road Users ◽  
Statistical Measures ◽  
Weather Events

Winter driving conditions pose a real hazard to road users with increased chance of collisions during inclement weather events. As such, road authorities strive to service the hazardous roads or collision hot spots by increasing road safety, mobility, and accessibility. One measure of a hot spot would be winter collision statistics. Using the ratio of winter collisions (WC) to all collisions, roads that show a high ratio of WC should be given a high priority for further diagnosis and countermeasure selection. This study presents a unique methodological framework that is built on one of the least explored yet most powerful geostatistical techniques, namely, regression kriging (RK). Unlike other variants of kriging, RK uses auxiliary variables to gain a deeper understanding of contributing factors while also utilizing the spatial autocorrelation structure for predicting WC ratios. The applicability and validity of RK for a large-scale hot spot analysis is evaluated using the northeast quarter of the State of Iowa, spanning five winter seasons from 2013/14 to 2017/18. The findings of the case study assessed via three different statistical measures (mean squared error, root mean square error, and root mean squared standardized error) suggest that RK is very effective for modeling WC ratios, thereby further supporting its robustness and feasibility for a statewide implementation.

scholarly journals Universal Masking to Control Healthcare-Associated Transmission of SARS-CoV-2

2021 ◽  
pp. 1-24
Author(s):  
Eliza R. Thompson ◽  
Faith S. Williams ◽  
Pat A. Giacin ◽  
Shay Drummond ◽  
Eric Brown ◽  
...  
Keyword(s):  
Large Scale ◽  
Infection Prevention ◽  
Index Patient ◽  
Field Investigation ◽  
Point Prevalence ◽  
Control Measures ◽  
Prevention Measures ◽  
Infection Control Measures ◽  
Va Health Care System ◽  
Healthcare Associated

Abstract Objective: To assess extent of a healthcare-associated outbreak of SARS-CoV-2 and evaluate effectiveness of infection control measures, including universal masking Design: Outbreak investigation including 4 large-scale point-prevalence surveys Setting: Integrated VA Health Care System with 2 facilities and 330 beds Participants: Index patient and 250 exposed patients and staff Methods: We identified exposed patients and staff and classified them as probable and confirmed cases based on symptoms and testing. We performed a field investigation and assessment of patient and staff interactions to develop probable transmission routes. Infection prevention interventions implemented included droplet and contact precautions, employee quarantine, and universal masking with medical and cloth facemasks. Four point-prevalence surveys of patient and staff subsets were conducted using real-time reverse-transcriptase polymerase chain reaction for SARS-CoV-2. Results: Among 250 potentially exposed patients and staff, 14 confirmed cases of Covid-19 were identified. Patient roommates and staff with prolonged patient contact were most likely to be infected. The last potential date of transmission from staff to patient was day 22, the day universal masking was implemented. Subsequent point-prevalence surveys in 126 patients and 234 staff identified 0 patient cases and 5 staff cases of Covid-19, without evidence of healthcare-associated transmission. Conclusions: Universal masking with medical facemasks was effective in preventing further spread of SARS-CoV-2 in our facility in conjunction with other traditional infection prevention measures.

scholarly journals A Large-Scale Study of the Twitter Follower Network to Characterize the Spread of Prescription Drug Abuse Tweets

2019 ◽  
Vol 6 (6) ◽  
pp. 1232-1244
Author(s):  
Ryan Sequeira ◽  
Avijit Gayen ◽  
Niloy Ganguly ◽  
Sourav Kumar Dandapat ◽  
Joydeep Chandra
Keyword(s):  
Drug Abuse ◽  
Prescription Drug ◽  
Large Scale ◽  
Prescription Drug Abuse ◽  
Large Scale Study

scholarly journals Large-scale cognitive model design using the Nengo neural simulator

2016 ◽  
Vol 17 ◽  
pp. 86-100 ◽  
Author(s):  
Sugandha Sharma ◽  
Sean Aubin ◽  
Chris Eliasmith
Keyword(s):  
Large Scale ◽  
Cognitive Model ◽  
Model Design

Enriching Activity-Based Models using Smartphone-Based Travel Surveys

2018 ◽  
Vol 2672 (42) ◽  
pp. 280-291 ◽  
Author(s):  
Bat-hen Nahmias-Biran ◽  
Yafei Han ◽  
Shlomo Bekhor ◽  
Fang Zhao ◽  
Christopher Zegras ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Large Scale ◽  
Leisure Activities ◽  
Behavior Modeling ◽  
Machine Learning Techniques ◽  
Initial Field ◽  
Activity Data ◽  
Large Variability ◽  
Tel Aviv ◽  
Household Travel Surveys

Smartphone-based travel surveys have attracted much attention recently, for their potential to improve data quality and response rate. One of the first such survey systems, Future Mobility Sensing (FMS), leverages sensors on smartphones, and machine learning techniques to collect detailed personal travel data. The main purpose of this research is to compare data collected by FMS and traditional methods, and study the implications of using FMS data for travel behavior modeling. Since its initial field test in Singapore, FMS has been used in several large-scale household travel surveys, including one in Tel Aviv, Israel. We present comparative analyses that make use of the rich datasets from Singapore and Tel Aviv, focusing on three main aspects: (1) richness in activity behaviors observed, (2) completeness of travel and activity data, and (3) data accuracy. Results show that FMS has clear advantages over traditional travel surveys: it has higher resolution and better accuracy of times, locations, and paths; FMS represents out-of-work and leisure activities well; and reveals large variability in day-to-day activity pattern, which is inadequately captured in a one-day snapshot in typical traditional surveys. FMS also captures travel and activities that tend to be under-reported in traditional surveys such as multiple stops in a tour and work-based sub-tours. These richer and more complete and accurate data can improve future activity-based modeling.

Sign in / Sign up

Export Citation Format

Share Document