Using Research Methods in Human Computer Interaction to Design Technology for Resilience

Research in human computer interaction (HCI) covers both technological and human behavioural concerns. As a consequence, the contributions made in HCI research tend to be aware to either engineering or the social sciences. In HCI the purpose of practical research contributions is to reveal unknown insights about human behaviour and its relationship to technology. Practical research methods normally used in HCI include formal experiments, field experiments, field studies, interviews, focus groups, surveys, usability tests, case studies, diary studies, ethnography, contextual inquiry, experience sampling, and automated data collection. In this paper, we report on our experience using the evaluation methods focus groups, surveys and interviews and how we adopted these methods to develop artefacts: either interface’s design or information and technological systems. Four projects are examples of the different methods application to gather information about user’s wants, habits, practices, concerns and preferences. The goal was to build an understanding of the attitudes and satisfaction of the people who might interact with a technological artefact or information system. Conversely, we intended to design for information systems and technological applications, to promote resilience in organisations (a set of routines that allow to recover from obstacles) and user’s experiences. Organisations can here also be viewed within a system approach, which means that the system perturbations even failures could be characterized and improved. The term resilience has been applied to everything from the real estate, to the economy, sports, events, business, psychology, and more. In this study, we highlight that resilience is also made up of a number of different skills and abilities (self-awareness, creating meaning from other experiences, self-efficacy, optimism, and building strong relationships) that are a few foundational ingredients, which people should use along with the process of enhancing an organisation’s resilience. Resilience enhances knowledge of resources available to people confronting existing problems.

Gesture based IoT light control for smart clothing

In this paper, a smart wireless wristband is proposed. The potential of innovative gesture based interactivity with connected lighting solutions is reviewed. The solution is intended to offer numerous benefits, in terms of ease of use, and enhanced dynamic interactive functionality. A comparative analysis will be carried out between this work and existing solutions. The evolution of lighting and gesture controls will be discussed and an overview of alternative applications will be provided, as part of the critical analysis.

Iowa Nutrient Reduction Strategy : a science and technology-based framework to assess and reduce nutrients to Iowa waters and the Gulf of Mexico (2016)

On November 19, 2012, Iowa Gov. Terry Branstad, Iowa Secretary of Agriculture Bill Northey, Director Chuck Gipp from the Iowa Department of Natural Resources and Dr. John Lawrence of Iowa State University announced the release of the Iowa Nutrient Reduction Strategy for public comment. A two-month public comment period and several informational meetings allowed the public to provide feedback on the draft strategy. Updates and improvements were made to the draft based on the public comments. The final version of the strategy was released May 29, 2013. The Iowa Nutrient Reduction Strategy is a science and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of Mexico. The strategy outlines voluntary efforts to reduce nutrients in surface water from both point sources, such as wastewater treatment plants and industrial facilities, and nonpoint sources, including farm fields and urban areas, in a scientific, reasonable and cost effective manner. The development of the strategy reflects more than two years of work led by the Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources and Iowa State University. The scientific assessment to evaluate and model the effects of practices was developed through the efforts of 23 individuals representing five agencies or organizations, including scientists from ISU, IDALS, DNR, USDA Agricultural Research Service and USDA Natural Resources Conservation Service. The strategy was developed in response to the 2008 Gulf Hypoxia Action Plan that calls for the 12 states along the Mississippi River to develop strategies to reduce nutrient loading to the Gulf of Mexico. The Iowa strategy follows the recommended framework provided by EPA in 2011 and is only the second state to complete a statewide nutrient reduction strategy. This strategy is the beginning. Operational plans are being developed and work is underway. This is a dynamic document that will evolve over time, and is a key step towards improving Iowa’s water quality. The impetus for this report comes from the Water Resources Coordination Council (WRCC) which states in its 2014‐15 Annual Report “Efforts are underway to improve understanding of the multiple nutrient monitoring efforts that may be available and can be compared to the nutrient WQ monitoring framework to identify opportunities and potential data gaps to better coordinate and prioritize future nutrient monitoring efforts.” This report is the culmination of those efforts.

Iowa Nutrient Reduction Strategy : a science and technology-based framework to assess and reduce nutrients to Iowa waters and the Gulf of Mexico (2014)

In May 2014, the Iowa Department of Agriculture and Land Stewardship, Iowa State University College of Agriculture and Life Sciences, and the Iowa Department of Natural Resources met to identify needed updates to the Iowa Nutrient Reduction Strategy. Updates were necessary to keep the text of the strategy up¬‐to¬‐date based on current information and status of efforts related to the strategy. Proposed updates were presented to the Water Resources Coordinating Council (WRCC) at its July 29 meeting, along with the annual strategy progress report. Comments were requested from both the WRCC and the Watershed Planning Advisory Council. Based on those comments, the draft report was updated and presented to the WRCC again on September 18, and finalized following that meeting. Below is a summary of the updates that have been made to the May 29, 2013 strategy document.

Iowa Nutrient Reduction Strategy : a science and technology-based framework to assess and reduce nutrients to Iowa waters and the Gulf of Mexico (2013)

On November 19, 2012, Iowa Gov. Terry Branstad, Iowa Secretary of Agriculture Bill Northey, Director Chuck Gipp from the Iowa Department of Natural Resources and Dr. John Lawrence of Iowa State University announced the release of the Iowa Nutrient Reduction Strategy for public comment. A two-month public comment period and several informational meetings allowed the public to provide feedback on the draft strategy. Updates and improvements were made to the draft based on the public comments. The final version of the strategy was released May 29, 2013. The Iowa Nutrient Reduction Strategy is a science and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of Mexico. The strategy outlines voluntary efforts to reduce nutrients in surface water from both point sources, such as wastewater treatment plants and industrial facilities, and nonpoint sources, including farm fields and urban areas, in a scientific, reasonable and cost effective manner. The development of the strategy reflects more than two years of work led by the Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources and Iowa State University. The scientific assessment to evaluate and model the effects of practices was developed through the efforts of 23 individuals representing five agencies or organizations, including scientists from ISU, IDALS, DNR, USDA Agricultural Research Service and USDA Natural Resources Conservation Service. The strategy was developed in response to the 2008 Gulf Hypoxia Action Plan that calls for the 12 states along the Mississippi River to develop strategies to reduce nutrient loading to the Gulf of Mexico. The Iowa strategy follows the recommended framework provided by EPA in 2011 and is only the second state to complete a statewide nutrient reduction strategy. This strategy is the beginning. Operational plans are being developed and work is underway. This is a dynamic document that will evolve over time, and is a key step towards improving Iowa’s water quality. The impetus for this report comes from the Water Resources Coordination Council (WRCC) which states in its 2014‐15 Annual Report “Efforts are underway to improve understanding of the multiple nutrient monitoring efforts that may be available and can be compared to the nutrient WQ monitoring framework to identify opportunities and potential data gaps to better coordinate and prioritize future nutrient monitoring efforts.” This report is the culmination of those efforts.

Iowa Nutrient Reduction Strategy : a science and technology-based framework to assess and reduce nutrients to Iowa waters and the Gulf of Mexico (2012)

On November 19, 2012, Iowa Gov. Terry Branstad, Iowa Secretary of Agriculture Bill Northey, Director Chuck Gipp from the Iowa Department of Natural Resources and Dr. John Lawrence of Iowa State University announced the release of the Iowa Nutrient Reduction Strategy for public comment. A two-month public comment period and several informational meetings allowed the public to provide feedback on the draft strategy. Updates and improvements were made to the draft based on the public comments. The final version of the strategy was released May 29, 2013. The Iowa Nutrient Reduction Strategy is a science and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of Mexico. The strategy outlines voluntary efforts to reduce nutrients in surface water from both point sources, such as wastewater treatment plants and industrial facilities, and nonpoint sources, including farm fields and urban areas, in a scientific, reasonable and cost effective manner. The development of the strategy reflects more than two years of work led by the Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources and Iowa State University. The scientific assessment to evaluate and model the effects of practices was developed through the efforts of 23 individuals representing five agencies or organizations, including scientists from ISU, IDALS, DNR, USDA Agricultural Research Service and USDA Natural Resources Conservation Service. The strategy was developed in response to the 2008 Gulf Hypoxia Action Plan that calls for the 12 states along the Mississippi River to develop strategies to reduce nutrient loading to the Gulf of Mexico. The Iowa strategy follows the recommended framework provided by EPA in 2011 and is only the second state to complete a statewide nutrient reduction strategy. This strategy is the beginning. Operational plans are being developed and work is underway. This is a dynamic document that will evolve over time, and is a key step towards improving Iowa’s water quality. The impetus for this report comes from the Water Resources Coordination Council (WRCC) which states in its 2014‐15 Annual Report “Efforts are underway to improve understanding of the multiple nutrient monitoring efforts that may be available and can be compared to the nutrient WQ monitoring framework to identify opportunities and potential data gaps to better coordinate and prioritize future nutrient monitoring efforts.” This report is the culmination of those efforts.

Healthcare Computer Reasoning Addressing Chronically Ill Societies Using IoT: Deep Learning AI to the Rescue of Home-Based Healthcare

The authors present a proposal to develop intelligent assisted living environments for home based healthcare. These environments unite the chronical patient clinical history sematic representation with the ability of monitoring the living conditions and events recurring to a fully managed Semantic Web of Things (SWoT). Several levels of acquired knowledge and the case based reasoning that is possible by knowledge representation of the health-disease history and acquisition of the scientific evidence will deliver, through various voice based natural interfaces, the adequate support systems for disease auto management but prominently by activating the less differentiated caregiver for any specific need. With these capabilities at hand, home based healthcare providing becomes a viable possibility reducing the institutionalization needs. The resulting integrated healthcare framework will provide significant savings while improving the generality of health and satisfaction indicators.

Feasibility assessment of sugarcane expansion in southwest Goiás, Brazil based on the GIS technology.

The current study approaches the sugarcane culture expansion in Southwestern Goiás, especially in Mineiros, Quirinópolis and Rio Verde counties, which represent different times and responses to this process. The current logistics structure and future prospects for sugarcane and its derivatives transportation are studied at national level with emphasis to the aforementioned micro-region. Maps showing land use and land cover in three different years were generated from Landsat TM-5 satellite images and they were used to analyze the dynamics of changes in land use and in land cover. The region is marked by strong and rapid growth in the agricultural sector and its sugar-energy industry has been expanding in recent years, although with different aspects among its counties. Since it is a promising region in this sector, due to the favorable soil and weather conditions to the crop, the region requires more investment and planning in logistics to ensure production flow and to make it stronger within domestic and foreign markets.

Computer vision in aseptic pharmaceutical manufacturing: a deep learning-based approach to vial inspection and pack formation during a lyophilizer loading cycle

Vision systems are powerful tools playing an increasingly important role in modern industry, to detect errors and maintain product standards. With the enlarged availability of affordable industrial cameras, computer vision algorithms have been increasingly applied in industrial manufacturing processes monitoring. Until a few years ago, industrial computer vision applications relied only on ad-hoc algorithms designed for the specific object and acquisition setup being monitored, with a strong focus on co-designing the acquisition and processing pipeline. Deep learning has overcome these limits providing greater flexibility and faster re-configuration. In this work, the process to be inspected consists in vials’ pack formation entering a freeze-dryer, which is a common scenario in pharmaceutical active ingredient packaging lines. To ensure that the machine produces proper packs, a vision system is installed at the entrance of the freeze-dryer to detect eventual anomalies with execution times compatible with the production specifications. Other constraints come from sterility and safety standards required in pharmaceutical manufacturing. This work presents an overview about the production line, with particular focus on the vision system designed, and about all trials conducted to obtain the final performance. Transfer learning, alleviating the requirement for a large number of training data, combined with data augmentation methods, consisting in the generation of synthetic images, were used to effectively increase the performances while reducing the cost of data acquisition and annotation. The proposed vision algorithm is composed by two main subtasks, designed respectively to vials counting and discrepancy detection. The first one was trained on more than 23k vials (about 300 images) and tested on 5k more (about 75 images), whereas 60 training images and 52 testing images were used for the second one.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Desenvolvimento de ferramentas de análise de desempenho de atletas em 3 diferentes modalidades : Handebol, Provas Combinadas e Salto com Vara

Universidade Estadual de Campinas. Faculdade de Educação Física

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.