scholarly journals Data collection for seed system network analysis

2018 ◽  
Author(s):  
Christopher E Buddenhagen ◽  
Kelsey F Andersen ◽  
James C Fulton ◽  
Karen A Garrett
Keyword(s):  
Statistical Analysis ◽  
Network Analysis ◽  
Data Collection ◽  
Seed Systems ◽  
Present Survey ◽  
Multilayer Network ◽  
Network Analyses ◽  
Variety Selection ◽  
Seed System ◽  
System Success

We present survey questions useful for describing agricultural seed systems. The questions are designed so that they can be used for standardized comparisons among seed systems, addressing both networks for seed movement and networks for the communication of information related to variety selection and integrated pest management. This approach provides information that can be used in multilayer network analyses of how information influences seed system success. Also provided are example data sheets with field descriptors that should provide for straightforward statistical analysis after data collection.

scholarly journals Data collection for seed system network analysis

2018 ◽  
Author(s):  
Christopher E Buddenhagen ◽  
Kelsey F Andersen ◽  
James C Fulton ◽  
Karen A Garrett
Keyword(s):  
Statistical Analysis ◽  
Network Analysis ◽  
Data Collection ◽  
Seed Systems ◽  
Present Survey ◽  
Multilayer Network ◽  
Network Analyses ◽  
Variety Selection ◽  
Seed System ◽  
System Success

We present survey questions useful for describing agricultural seed systems. The questions are designed so that they can be used for standardized comparisons among seed systems, addressing both networks for seed movement and networks for the communication of information related to variety selection and integrated pest management. This approach provides information that can be used in multilayer network analyses of how information influences seed system success. Also provided are example data sheets with field descriptors that should provide for straightforward statistical analysis after data collection.

scholarly journals Survey methods for seed system network analysis

2017 ◽  
Author(s):  
Christopher E Buddenhagen ◽  
Kelsey F Andersen ◽  
James C Fulton ◽  
Karen A Garrett
Keyword(s):  
Statistical Analysis ◽  
Network Analysis ◽  
Survey Methods ◽  
Seed Systems ◽  
Present Survey ◽  
Multilayer Network ◽  
Network Analyses ◽  
Variety Selection ◽  
Seed System ◽  
System Success

We present survey questions useful for describing agricultural seed systems. The questions are designed so that they can be used for standardized comparisons among seed systems, addressing both networks for seed movement and networks for the communication of information related to variety selection and integrated pest management. This approach provides information that can be used in multilayer network analyses of how information influences seed system success. Also provided are example data sheets with field descriptors that should provide for straightforward statistical analysis after data collection.

scholarly journals Impact Des Facteurs Intersubjectifs Sur L'engagement Des Cadres Ivoiriens Au Développement De Leur Localité d’Origine

2018 ◽  
Vol 14 (32) ◽  
pp. 237
Author(s):  
Daboné Inoussa ◽  
Méité Zoumana
Keyword(s):  
Statistical Analysis ◽  
Data Collection ◽  
Public Administration ◽  
Rural Areas ◽  
Present Survey ◽  
Urban Populations ◽  
Local Populations ◽  
Personal Commitment ◽  
Rural And Urban

Despite the policy of developing localities initiated by the Ivorian state, disparities between rural and urban populations are still obvious. The lack of interest in this process of development from localities’ native executives is highlighted. The present survey tempts to examine this lack of personal commitment from executives in relation with intersubjective factors such as sympathy, autonomy, mystical practices and communication. In so doing, a sample of 121 executives from the Ivorian public administration are selected rationally in the purpose of data collection through a questionnaire. Statistical analysis indicate that, except the autonomy to bring innovations in rural areas, the targeted intersubjective factors have a significant impact on the executives' level of commitment in their locality’s development. As regards to practical repercussions, these results underline the necessity to develop the local populations’ mind of sympathy and communication towards their executives. Local populations have also to put an end to any mystical practice able to frighten their native executives if they want them to fully take part in the development of their different localities.

Developing a sustainable Digital Health Innovation Ecosystem in a rural and resource-poor region: A monitored networking approach (Preprint)

2020 ◽  
Author(s):  
Arunangsu Chatterjee ◽  
Sebastian Stevens ◽  
Sheena Asthana ◽  
Ray B Jones
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Data Collection ◽  
Digital Health ◽  
Resource Poor Setting ◽  
Quadruple Helix ◽  
Innovation Ecosystem ◽  
Resource Poor ◽  
Quadruple Helix Model ◽  
Over Time

BACKGROUND Digital health (DH) innovation ecosystems (IE) are key to the development of new e-health products and services. Within an IE, third parties can help promote innovation by acting as knowledge brokers and the conduits for developing inter-organisational and interpersonal relations, particularly for smaller organisations. Kolehmainen’s quadruple helix model suggests who the critical IE actors are, and their roles. Within an affluent and largely urban setting, such ecosystems evolve and thrive organically with minimal intervention due to favourable economic and geographical conditions. Facilitating and sustaining a thriving DH IE within a resource-poor setting can be far more challenging even though far more important for such peripheral economics and the health and well-being of those communities. OBJECTIVE Taking a rural and remote region in the UK, as an instance of an IE in a peripheral economy, we adapt the quadruple helix model of innovation, apply a monitored social networking approach using McKinsey’s Three Horizons of growth to explore: • What patterns of connectivity between stakeholders develop within an emerging digital health IE? • How do networks develop over time in the DH IE? • In what ways could such networks be nurtured in order to build the capacity, capability and sustainability of the DH IE? METHODS Using an exploratory single case study design for a developing digital health IE, this study adopts a longitudinal social network analysis approach, enabling the authors to observe the development of the innovation ecosystem over time and evaluate the impact of targeted networking interventions on connectivity between stakeholders. Data collection was by an online survey and by a novel method, connection cards. RESULTS Self-reported connections between IE organisations increased between the two waves of data collection, with Small and Medium-sized Enterprises (SMEs) and academic institutions the most connected stakeholder groups. Patients involvement improved over time but still remains rather peripheral to the DH IE network. Connection cards as a monitoring tool worked really well during large events but required significant administrative overheads. Monitored networking information categorised using McKinsey’s Three Horizons proved to be an effective way to organise networking interventions ensuring sustained engagement. CONCLUSIONS The study reinforces the difficulty of developing and sustaining a DH IE in a resource-poor setting. It demonstrates the effective monitored networking approach supported by Social Network Analysis allows to map the networks and provide valuable information to plan future networking interventions (e.g. involving patients or service users). McKinsey’s Three Horizons of growth-based categorisation of the networking assets help ensure continued engagement in the DH IE contributing towards its long-term sustainability. Collecting ongoing data using survey or connection card method will become more labour intensive and ubiquitous ethically driven data collection methods can be used in future to make the process more agile and responsive.

How Art Works

2018 ◽  
Author(s):  
Ellen Winner
Keyword(s):  
Statistical Analysis ◽  
Data Collection ◽  
Social Science ◽  
Modern Art ◽  
Hard Work ◽  
Objective Truth ◽  
The Arts ◽  
Art Form ◽  
Art Works ◽  
Truth Value

This book is an examination of what psychologists have discovered about how art works—what it does to us, how we experience art, how we react to it emotionally, how we judge it, and what we learn from it. The questions investigate include the following: What makes us call something art? Do we experience “real” emotions from the arts? Do aesthetic judgments have any objective truth value? Does learning to play music raise a child’s IQ? Is modern art something my kid could do? Is achieving greatness in an art form just a matter of hard work? Philosophers have grappled with these questions for centuries, and laypeople have often puzzled about them too and offered their own views. But now psychologists have begun to explore these questions empirically, and have made many fascinating discoveries using the methods of social science (interviews, experimentation, data collection, statistical analysis).

scholarly journals Proposal for Tower Crane Productivity Indicators Based on Data Analysis in the Era of Construction 4.0

Buildings ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 21
Author(s):  
Thomas Danel ◽  
Zoubeir Lafhaj ◽  
Anand Puppala ◽  
Sophie Lienard ◽  
Philippe Richard
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Statistical Analysis ◽  
Data Collection ◽  
Structural Phase ◽  
Sampling Technique ◽  
Construction Site ◽  
Data Logger ◽  
Tower Crane ◽  
Productivity Indicators

This article proposes a methodology to measure the productivity of a construction site through the analysis of tower crane data. These data were obtained from a data logger that records a time series of spatial and load data from the lifting machine during the structural phase of a construction project. The first step was data collection, followed by preparation, which consisted of formatting and cleaning the dataset. Then, a visualization step identified which data was the most meaningful for the practitioners. From that, the activity of the tower crane was measured by extracting effective lifting operations using the load signal essentially. Having used such a sampling technique allows statistical analysis on the duration, load, and curvilinear distance of every extracted lifting operation. The build statistical distribution and indicators were finally used to compare construction site productivity.

scholarly journals 907. Technology and Medicine: Prediction of Surgical Site Infection in Clean Surgeries using Artificial Neural Networks

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S487-S487
Author(s):  
Flávio Henrique Batista de Souza ◽  
Braulio Roberto Gonçalves Marinho Couto ◽  
Felipe Leandro Andrade da Conceição ◽  
Gabriel Henrique Silvestre da Silva ◽  
Igor Gonçalves Dias ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Data Collection ◽  
Infection Control ◽  
Surgical Site Infection ◽  
Predictive Power ◽  
Hospital Infection ◽  
Automated System ◽  
Site Infection ◽  
Average Hospital ◽  
Hospital Infection Control

Abstract Background In Belo Horizonte, a city with 3,000,000 inhabitants, a survey was performed in six hospitals, between July 2016 and June 2018, about surgical site infection (SSI) in patients undergoing clean surgery procedures. The main objective is to statistically evaluate such incidences and enable an analysis of the SSI predictive power, through MLP (Multilayer Perceptron) pattern recognition algorithms. Methods Through the Hospital Infection Control Committees (CCIH) of the hospitals, a data collection on SSI was carried out through the software SACIH - Automated System for Hospital Infection Control. So, three procedures were performed: a treatment of the collected database for use of intact samples; a statistical analysis on the profile of the collected hospitals; an evaluation of the predictive power of five types of MLPs (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay and Quick Propagation) for SSI prediction. The MLPs were tested with 3, 5, 7 and 10 neurons in the hidden layer and with a division of the database for the resampling process (65% or 75% for testing, 35% or 25% for validation). They were compared by measuring the AUC (Area Under the Curve - ranging from 0 to 1) presented for each of the configurations. Results From 45,990 records, 12,811 were able for analysis. The statistical analysis results were: the average age is 49 years old (predominantly between 30 and 50); the surgeries had an average time of 134.13 minutes; the average hospital stay is 4 days (from 0 to 200 days), the death rate reached 1% and the SSI 1.49%. A maximum prediction power of 0.742 was found. Conclusion There was a loss of 60% of the database samples due to the presence of noise. However, it was possible to have a relevant sample to assess the profile of these six hospitals. The predictive process, presented some configurations with results that reached 0.742, what promises the use of the structure for the monitoring of automated SSI for patients submitted to surgeries considered clean. To optimize data collection, enable other hospitals to use the prediction tool and minimize noise from the database, two mobile application were developed: one for monitoring the patient in the hospital and other for monitoring after hospital discharge. The SSI prediction analysis tool is available at www.nois.org.br. Disclosures All Authors: No reported disclosures

scholarly journals A Learning Analytics Framework to Analyze Corporal Postures in Students Presentations

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1525
Author(s):  
Felipe Vieira ◽  
Cristian Cechinel ◽  
Vinicius Ramos ◽  
Fabián Riquelme ◽  
Rene Noel ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Data Collection ◽  
Pattern Mining ◽  
New Technologies ◽  
Personal Information ◽  
Sequential Pattern Mining ◽  
Complex Problem ◽  
Sequential Pattern ◽  
Background Information ◽  
Professional Relationships

Communicating in social and public environments are considered professional skills that can strongly influence career development. Therefore, it is important to proper train and evaluate students in this kind of abilities so that they can better interact in their professional relationships, during the resolution of problems, negotiations and conflict management. This is a complex problem as it involves corporal analysis and the assessment of aspects that until recently were almost impossible to quantitatively measure. Nowadays, a number of new technologies and sensors have being developed for the capture of different kinds of contextual and personal information, but these technologies were not yet fully integrated inside learning settings. In this context, this paper presents a framework to facilitate the analysis and detection of patterns of students in oral presentations. Four steps are proposed for the given framework: Data collection, Statistical Analysis, Clustering, and Sequential Pattern Mining. Data Collection step is responsible for the collection of students interactions during presentations and the arrangement of data for further analysis. Statistical Analysis provides a general understanding of the data collected by showing the differences and similarities of the presentations along the semester. The Clustering stage segments students into groups according to well-defined attributes helping to observe different corporal patterns of the students. Finally, Sequential Pattern Mining step complements the previous stages allowing the identification of sequential patterns of postures in the different groups. The framework was tested in a case study with data collected from 222 freshman students of Computer Engineering (CE) course at three different times during two different years. The analysis made it possible to segment the presenters into three distinct groups according to their corporal postures. The statistical analysis helped to assess how the postures of the students evolved throughout each year. The sequential pattern mining provided a complementary perspective for data evaluation and helped to observe the most frequent postural sequences of the students. Results show the framework could be used as a guidance to provide students automated feedback throughout their presentations and can serve as background information for future comparisons of students presentations from different undergraduate courses.

scholarly journals Data collection and advanced statistical analysis in phytotoxic activity of aerial parts exudates of Salvia spp

2011 ◽  
Vol 21 (5) ◽  
pp. 856-863 ◽  
Author(s):  
M. Giacomini ◽  
A. Bisio ◽  
E. Giacomelli ◽  
S. Pivetti ◽  
S. Bertolini ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Data Collection ◽  
Phytotoxic Activity ◽  
Aerial Parts

scholarly journals PENGARUH MODEL PEMBELAJARAN KOOPERATIF TIPE STAD TERHADAP DAYA INGAT DAN HASIL BELAJAR SISWA PADA MATERI HIDROLISIS GARAM KELAS XI IPA SMA KEMALA BHAYANGKARI 1 SUNGAI RAYA

2017 ◽  
Vol 5 (1) ◽  
Author(s):  
Sahara Sahara ◽  
Dedeh Kurniasih ◽  
Rizmahardian Azhari Kurniawan
Keyword(s):  
Statistical Analysis ◽  
Data Collection ◽  
Cooperative Learning ◽  
Learning Outcomes ◽  
Effect Size ◽  
Teaching Method ◽  
Control Group ◽  
Learning Method ◽  
Control Group Design ◽  
And Control

ABSTRACT The process of learning chemistry which only focused on teacher as informant caused the students’ memory lower. This could make the students’ learning outcomes lower, thus, it was needed STAD type of Cooperative Learning Method which had the process of interaction between student and teacher, and could help the students comprehend the material. Therefore, it was necessary to make a research which had the purpose to know the difference between students’ learning outcomes and memory which used STAD type ofCooperative Learning Method and lectures teaching method as well as how large the effect of STAD type of Cooperative Learning Method on salt hydrolysis material was. This research was Quasi Experimental Nonequivalent Control Group Design. The sample of the research was choosen by using saturated sampling which XI IPA 1 as experimental class and XI IPA 2 as control class. The techniques of data collection used measurement technique, observation, and interview while the tools of data collection used tests such as essayquestion, observation sheet, and interview guide. The statistical analysis of posttest result using U-man whitney test obtained significant value 0.000. This value was smaller than α (0.005) which meant that there was difference in learning outcome between experimental and control class. The statistical analysis result of U-man whitney delayed test obtained significant value 0.006, this value was smaller than α (0.005) which meant that there was difference between students’ memory in experimental and control class. The calculation of effect size showed value 1.64 with high criteria which gave high effect on students’ learning outcomes which was 44.95%, while the calculation of students’ memory effect size showed value 0.69 with moderate criteria which gave effect on students’ memory which was 26,42%. Keywords : Memory, Learning Outcomes, Salt Hydrolysis, STAD type of Cooperative Learning Method

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