Non-technical Individuals Research Articles

Atlas of AI Risks: Enhancing Public Understanding of AI Risks

The prevailing methodologies for visualizing AI risks have focused on technical issues such as data biases and model inaccuracies, often overlooking broader societal risks like job loss and surveillance. Moreover, these visualizations are typically designed for tech-savvy individuals, neglecting those with limited technical skills. To address these challenges, we propose the Atlas of AI Risks—a narrative-style tool designed to map the broad risks associated with various AI technologies in a way that is understandable to non-technical individuals as well. To both develop and evaluate this tool, we conducted two crowdsourcing studies. The first, involving 40 participants, identified the design requirements for visualizing AI risks for decision-making and guided the development of the Atlas. The second study, with 140 participants reflecting the US population in terms of age, sex, and ethnicity, assessed the usability and aesthetics of the Atlas to ensure it met those requirements. Using facial recognition technology as a case study, we found that the Atlas is more user-friendly than a baseline visualization, with a more classic and expressive aesthetic, and is more effective in presenting a balanced assessment of the risks and benefits of facial recognition. Finally, we discuss how our design choices make the Atlas adaptable for broader use, allowing it to generalize across the diverse range of technology applications represented in a database that reports various AI incidents.

Development of an AI literacy assessment for non-technical individuals: What do teachers know?

With the exponential development and vast interest in artificial intelligence (AI), the global economic impact of AI is expected to reach $15.7 trillion by 2030. While AI has infiltrated everyday life, a lack of knowledge of what AI is and how AI works is ubiquitous across all ages and professions. Teaching AI literacy to non-technical individuals has become imperative and requires immediate attention, however, assessing AI literacy has heavily relied on subjective measurements such as qualitative assessment and self-reported surveys, which may lead to biased results. This study contributes to the field by developing and validating an assessment created based on a well-established AI literacy framework. A total of 196 responses were collected from pre-and in-service teachers in the United States, and 186 responses were included in the analysis to validate the assessment. The final assessment comprises 25 objective-based items reduced from an originally 31-item assessment. Both experts’ insights were sought, and statistical methodology was employed to ensure the validity of the assessment. The results indicate that pre-and in-service teachers have a moderate level of AI literacy and in-service teachers performed slightly better than pre-service teachers on our assessment. Inconsistent answers across various AI concepts indicate that teachers may possess an even more ambiguous understanding of certain AI concepts.

Data Analytics: Unlocking Multivision’s Future Perspectives

This research examines the problem of making data analysis understandable to non-technical consumers in today’s world of extensive data. We present a project that combines a user-friendly web application built on the Django framework with simple data analysis using linear regression. Through the use of the simple statistical technique of linear regression, even non-technical people may obtain valuable insights from large-scale datasets. Easy-to-use online application that makes data uploading, analysis, and interpretation a breeze. Our method uses built-in linear regression methods in the Django framework to automate dataset analysis. In this paper, the user interface design and the use of linear regression are explained, together with technical architecture insights. Facilitating inclusion across several areas, the major objective is to democratize data analysis. Our goal is to empower non-technical individuals and enable a wider audience to understand and apply data for informed decision-making by providing a tool that combines the efficiency of linear regression with an easy-to-use online interface.

Supporting Social Inclusion with DIY-ATs: Perspectives of Kenyan Caregivers of Children with Cognitive Disabilities

Do-It-Yourself assistive technologies (DIY-ATs) that can be designed, fabricated, or customized by non-technical individuals can enable people with disabilities and their community members to create and customize their own technological solutions. DIY-ATs may better fit user needs than mass-produced alternatives. Recently, researchers have started to explore the possibilities and challenges of using DIY-ATs in contexts other than the Global North, where access to digital ATs is limited. Previous research has not yet studied the perspectives of caregivers of children with disabilities towards these technologies. We present findings from an interview study with caregivers of children and youth with cognitive disabilities in Western Kenya who used a DIY-AT system as a research probe. Participants described how negative beliefs about people with disabilities result in social exclusion and discrimination and explained how increased opportunities for social interaction and learning mediated through DIY and other customizable ATs for their children could support their inclusion, safety, and access to future opportunities.

On the Employment of Machine Learning in the Blockchain Selection Process

Given the growing increase in the number of blockchain (BC) platforms, cryptocurrencies, and tokens, non-technical individuals face a complex question when selecting a BC that meets their requirements (e.g., performance or security). In addition, current approaches that aid such a selection process present drawbacks (e.g., require specific BC knowledge or are not automated and scalable), which hinders the decision process even further. Fortunately, techniques such as Machine Learning (ML) allow the creation of selection models without human interaction by identifying the BC features that match the requirements provided by the user in an automated and flexible manner. Thus, this work presents the design and implementation of an ML-based BC selection approach that employs five ML models to select the most suitable BC given user requirements (e.g., BC popularity, fast block inclusion, or Smart Contract - SC support). The approach follows an ML-specific data flow and defines a novel equation to quantify the popularity of a BC. Furthermore, it details the models’ accuracy and functionality in two distinct use cases, which shows their good accuracy (>85%). Finally, discussions on (a) the ML usefulness, (b) advantages over rule-based systems, and (c) the most relevant features for the BC selection are presented.

Development of a microcontroller EEG-based system for diagnosis of autism spectrum disorder in developing countries

Biomedical signals consists of records of electrical activity in the human body, and they represent the health status of individuals. The biomedical signal otherwise called neural signals includes Electro-encephalogram (EEG) Signals, Electro-cardiogram (ECG) Signals, Heart Rate Variability (HRV) Signals, Electro oculorgram (EOG) Signals, Electro-myogram (EMG) Signals, magnetoencephalography (MEG) signals, and electro gastrography (EGG). It is often difficult for health practitioners to visually examine these long records to diagnose a patient to arrive at conclusions. The process of classifying a biomedical signal is done by carefully attaching a signal to a disease state or healthy state and also the quality of features extracted from the signals, well pre – processed signal and the classification process determines the classification Accuracy (CA). The spectral content of the signals contains critical information on state of health of a person that can used for early detection of a particular disease. Developing an Automated system which could help in Automated classification of these signals can greatly assist the Doctors and non-technical individuals in the diagnostic process. In response to the above drawback, this paper intends to develop a prediction machine in a dual level approach using a Microcontroller EEG - based system and machine learning Algorithms for early diagnosis of Autism Spectrum Disorder using EEG signals. The performance of the proposed system will be evaluated using CA, amplitude, power frequency ratio, execution time, specificity, sensitivity, power spectral density ratio, memory usage and power consumption in a microcontroller platform time.

Development of a Universal Water Quality Index (UWQI) for South African River Catchments

The assessment of water quality has turned to be an ultimate goal for most water resource and environmental stakeholders, with ever-increasing global consideration. Against this backdrop, various tools and water quality guidelines have been adopted worldwide to govern water quality deterioration and institute the sustainable use of water resources. Water quality impairment is mainly associated with a sudden increase in population and related proceedings, which include urbanization, industrialization and agricultural production, among others. Such socio-economic activities accelerate water contamination and cause pollution stress to the aquatic environment. Scientifically based water quality index (WQI) models are then essentially important to measure the degree of contamination and advise whether specific water resources require restoration and to what extent. Such comprehensive evaluations reflect the integrated impact of adverse parameter concentrations and assist in the prioritization of remedial actions. WQI is a simple, yet intelligible and systematically structured, indexing scale beneficial for communicating water quality data to non-technical individuals, policymakers and, more importantly, water scientists. The index number is normally presented as a relative scale ranging from zero (worst quality) to one hundred (best quality). WQIs simplify and streamline what would otherwise be impractical assignments, thus justifying the efforts of developing water quality indices (WQIs). Generally, WQIs are not designed for broad applications; they are customarily developed for specific watersheds and/or regions, unless different basins share similar attributes and test a comparable range of water quality parameters. Their design and formation are governed by their intended use together with the degree of accuracy required, and such technicalities ultimately define the application boundaries of WQIs. This is perhaps the most demanding scientific need—that is, to establish a universal water quality index (UWQI) that can function in most, if not all, the catchments in South Africa. In cognizance of such a need, this study attempts to provide an index that is not limited to certain application boundaries, with a contribution that is significant not only to the authors, but also to the nation at large. The proposed WQI is based on the weighted arithmetic sum method, with parameters, weight coefficients and sub-index rating curves established through expert opinion in the form of the participation-based Rand Corporation’s Delphi Technique and extracts from the literature. UWQI functions with thirteen explanatory variables, which are NH3, Ca, Cl, Chl-a, EC, F, CaCO3, Mg, Mn, NO3, pH, SO4 and turbidity (NTU). Based on the model validation analysis, UWQI is considered robust and technically stable, with negligible variation from the ideal values. Moreover, the prediction pattern corresponds to the ideal graph with comparable index scores and identical classification grades, which signifies the readiness of the model to appraise water quality status across South African watersheds. The research article intends to substantiate the methods used and document the results achieved.

Automated configuration of modern ATE

Modern Automatic Test Equipment (ATE) must perform many tasks to support testing of devices. The devices being tested may be anything from simple circuit cards to complex multi-device systems. In addition, they may employ analog, digital and / or radio frequency testing. This, coupled with the desire to test the devices as quickly as possible, can drive ATE systems to employ multiple systems with their own associated computers in order to perform complex testing in as short a time as possible. Another requirement of modern ATE is that they are able to be quickly repaired and be able to be configured quickly to perform their intended function. Since the platforms on which the tested equipment is installed cannot be used unless they are completely operational, the ATE used to test that equipment must be available to perform the testing. Additionally, it is often intended that the testing and repair tasks be performed by non-technical or semi-technical individuals. It is this last capability that can drive the desire to support the ability to perform automated installation and configuration of the ATE systems.

RAPID THERMAL LOAD ESTIMATION USING A SET OF SMART GRAPHS

The purpose of this research was to develop simple thermal load smart graphs for rapid thermal load estimation. These graphs were generated in order to facilitate a quick estimation of the thermal load. This is especially important when computer-aided heating, ventilation and air-conditioning (HVAC) design software is unavailable. Hundreds of calculations have been carried out using various heat transfer equations and an hourly analysis program (HAP) generated graphs displaying the external and internal sensible and latent heat gains of analyzed spaces. These smart graphs are very user friendly; non-technical individuals can easily calculate the thermal load using these graphs. The smart graphs are time-saving and give results more accurate than thumb rules. In fact, they give a total thermal load estimate that is less than few percent different from the estimate generated using commercial software programs.

Stick-On Piezoelectromagnetic AC Current Monitoring of Circuit Breaker Panels

We present a stick-on wireless electric current monitoring system that is designed to measure and report electricity usage from circuit breaker panels in residential and commercial settings. This monitoring system uses piezoelectromagnetic (PEM) AC current sensors to couple to the magnetic fields produced by the current-carrying conductors. The PEM sensors can be easily attached to the surfaces of common circuit breaker panels, facilitating the installation by non-technical individuals. This paper describes the sensing principles and provides an analytical model of the PEM AC sensors. It also presents the architecture for a wireless current monitoring system and describes its implementation for sub-metering a circuit breaker panel in a building at the University of California, Berkeley. The theory and experimental validation of a signal deconvolution and calibration method, essential for extracting signals from cross-coupled magnetic fields, are also included.

Application of the Water Quality Index (QWI) to characterize the lower course of the São João River

O emprego de índices vem sendo estimulado pela Agência Nacional de Águas (ANA), pois seu uso auxilia a padronização nas coletas e análises de água; além disto, eles facilitam a leitura das condições de qualidade para todos os públicos, inclusive os não-técnicos (ANA, 2009). Tem-se como objetivo, no presente trabalho, avaliar a qualidade da água no rio São João por meio da utilização do Índice de Qualidade da Água (IQA), a fim de responder a questionamentos relativos à poluição proveniente de esgoto doméstico. Para realização dos cálculos foram analisados os seguintes parâmetros: temperatura, turbidez, resíduo sólido total, pH, oxigênio dissolvido, DBO, fósforo total, nitrogênio total e Escherichia coli. Os resultados obtidos no índice indicam que a qualidade da água no rio pode ser considerada boa na maioria dos pontos coletados, tendo como parâmetros críticos os resíduos sólidos e Escherichia coli. Com o estudo realizado foi possível verificar como ações antrópicas estão influenciando a bacia. Dessa forma, conclui-se que a utilização do referido índice é relevante para o monitoramento da qualidade da água na área de estudo, tendo em vista que não foi possível obter qualquer bibliografia sobre a região que se utilize de índices para avaliação da qualidade da água no referido rio.

EDITORIAL

The search for sustainable energy solutions has accelerated significantly in recent years driven by concerns caused by supply limitations, such as Peak Oil (or Gas, Coal, and Uranium), and by climate change. Many communities and industries are now facing the prospect of increased energy costs, potential energy supply disruptions, and carbon emission limits. Recently, the scientific academies of 13 countries1 (including Brazil) issued a joint statement calling on world leaders to increase energy efficiency, promote a shift to less-polluting energy sources, and intensify research into new energy technologies that produce no emissions. Also recently, a coalition of 16 of the world’s biggest cities (São Paulo is one of them), under a plan developed by the William J. Clinton Foundation2, pledged investments of billions of dollars to cut building energy use and releases of heat-trapping gases linked to global warming.The field of thermal sciences plays a critical role in managing these challenges. In a recent initiative, the National Science Foundation3 invited a number of thermal science researchers to identify frontier challenges and associated opportunities in five areas, one of which was sustainable energy technologies (the remaining were biological systems and biotechnology, security, information technology, and nanotechnology). While a final report was not yet published when this editorial was written, the passionate discussions pointed to action in research and education from academic institutions, government, and industry. Some of the topics discussed include fuel cells, seawater agriculture, biomass, sustainability metrics, carbon sequestration, and broad education of non-technical individuals on thermal sciences.The research findings published in Engenharia Térmica in the past have shown significant progress in areas related to energy, particularly oil and renewables. We are confident we will continue to receive articles’ submissions that help enable sustainable energy solutions in the near future.

A FUZZY DECISION SUPPORT SYSTEM TO IDENTIFY ESTABLISHMENTS WITH LOW PAID EMPLOYEES IN THE BRITISH ECONOMY

Enforcing compliance with the National Minimum Wage (NMW) in the British economy requires the identification of those establishments that are likely to pay a substantial proportion of their employees less than the NMW. In this paper, a fuzzy decision support system is constructed to aid in the elucidation of such an establishment and their proportion of employees paid less than the NMW. Moreover, through an inductive fuzzy decision tree approach, a set of fuzzy rules enables the prediction of this proportion value. These fuzzy rules allow a more human linguistic approach to the problem, which can be interpreted by non-technical individuals whose role it is to target certain establishments for further inspection. Through a semi-automated procedure for the construction of the fuzzy set theory related membership functions, the whole process mitigates the need for the influence of subjective expert opinion. With rule description and a comparison to multivariate discriminant analysis models, these fuzzy rules are shown to be an appropriate tool for the elicitation of establishments not in compliance with the NMW.

Perfil sensorial de diferentes muestras de nuez (Juglans regia L.)/Sensory profiles of different walnuts (Juglans regia L.)

The nutritional and sensory properties of walnuts (Juglans regia L.) are well known and appreciated by consumers. Despite this, few studies about their basic sensory characteristics or about the effect of agronomic and technological factors on them have been carried out. In this study six different types of walnut were sensorially described, using expert and non-expert assessors, in order to obtain a simple sensory profile which would enable discrimination between the samples studied. The final sensory profile was made up of 18 descriptors. This profile was useful for differentiating and describing samples from several varieties of fruit, two different geographical origins and two different post-harvest treatments. Using only 10 of these descriptors and through discriminant analysis it was possible to classify correctly 100% of the samples into their respective groups. The use of non-expert assessors in the generation of descriptors pointed out the simplicity of the profile, probably allowing for interpretation by non-technical individuals. Selection and interpretation of descriptors was easier and faster than usual as a result of asking the assessors, especially the consumers, to add their own description of the attributes chosen. This also seemed to have affected, in an important way, the number of attributes generated by non-expert assessors.

Optimal Allocation of Water Withdrawals in a River Basin

An increasing number of states use permit programs to coordinate and to control water resource allocations. A general approach is suggested for allocating and permitting water withdrawals in a river basin. A mathematical programming methodology facilitates optimal streamflow allocation while maintaining desired levels of instream flow. The approach uses a graphical tool, the flow duration curve, to illustrate the quantity and frequency of joint streamflow withdrawals in a river basin. The methodology is unique because while it uses mathematical programming methods, it is implemented using a spreadsheet optimization tool, Microsoft Excel Solver, and the solution is illustrated in a graphical form so that nontechnical individuals can easily understand the methodology results. The ability to apply the methodology and clearly explain the results is extremely important since many nontechnical individuals are involved as policymakers in water allocation decisions.

An investigation of the roles of individual differences and user interface on database usability

This research seeks to understand to what extent leveraging the graphical user interface's ability to convey spatial information can improve a user's ability to write effective database queries. This capability is believed to be especially important when nontechnical individuals, with diverse backgrounds and cognitive abilities, are expected to interact directly with these systems in the query formulation process.This study makes use of recent developments in graphical user interface technology to manipulate the level of spatial visualization support provided by the interface. A laboratory experiment was conducted to explore the influence of interface style and the spatial visualization ability of the user on the performance of the query development process. The application used in the experiment was a visual database query system developed for this study. One hundred sixty-two volunteers participated in the experiment. Spatial visualization ability was assessed using a paper-folding test. The results indicate that both spatial visualization support of the system and spatial visualization ability of the user are important components of database usability.

A time-sharing computer system for patient-care activities

An experimental, time-sharing, remote-access computer system is being developed as part of a research project in the use of automatic data-processing techniques in patient-care procedures in the Massachusetts General Hospital. Programs have been designed that allow a user on a patient-care unit to order medications, retrieve laboratory test results, admit and discharge patients, etc. These programs are still in an experimental phase and duplicate the present hospital function. The system is designed to take advantage of the total data base in the computer storage to carry out operations which would be impossible using present methods. One such feature allows the routing of a message or the modification thereof to be determined by the contents of the message, and by the state of the data base. Because the system will be used by nontechnical individuals, the programs have been designed to appear to the user in a “conversational mode”, where in the computer types a question and the user a response.