Intuitive Elements Research Articles

Everyday Triangulation within Challenging Informational and Legal Contexts: Exploring Everyday Triangulation in Individuals Considering Cannabis Use during Pregnancy or Lactation

ABSTRACTMedical evidence on the risks and benefits of cannabis is limited; existing research is often inconclusive or conflicting. In the United States, cannabis use during pregnancy is stigmatized and often subject to complex legal constraints; these contextual components may have significant effects on information seeking and informed decision‐making processes. This study applies Reflexive Thematic Analysis to 23 telephone interviews with individuals considering cannabis use in pregnancy or lactation to explore their information needs; how adequately those needs were met; and how information triangulation, and other information seeking behaviours, were used to make decisions given the dearth of scientific evidence. Findings suggest that information needs are complex and contextual, and that participants used forms of triangulation that included relational and intuitive elements as well as cognitive assessment processes. A new model of Everyday Triangulation (ET) is presented to represent these complex assessment practices in a holistic manner.

Intentional water and tired wood: exploring causes for primary teachers’ reference to intuitive construals in science education

ABSTRACT Research reveals that teachers regularly refer to intuitive construals (IC) in formal science education. Only a few studies, however, have investigated why teachers refer to them. Alarmingly, these studies suggest didactic consideration is not the main reason for this. Instead, teachers introduce IC unintentionally or due to a lack of expertise. A possible explanation for an unconsidered reference to IC – a part of lack of expertise – is that teachers spontaneously align their language with the students’ perspective as a form of implicit didactisation. We asked fifty prospective primary teachers to explain a basic scientific phenomenon of inanimate nature to fictitious recipients of varying expertise (a science expert and a student). We reasoned that if lack of knowledge was the reason for using IC, explanations should be equally intuitive for all addressees. If spontaneous language didactisation is the reason, only the explanations for students should contain intuitive elements. Results show that the majority of participants use IC exclusively when addressing students and not when addressing experts. In a substantial minority, however, lack of knowledge is a more likely cause. We conclude that there might be a tendency towards language didactisation even outside didactic professional knowledge. Implications for teacher training are discussed.

Role and challenges of ChatGPT, Gemini, and similar generative artificial intelligence in human resource management

The integration of generative artificial intelligence (AI) systems, such as ChatGPT, into Human Resource Management (HRM) has marked the beginning of a groundbreaking era in innovative workforce management and employee engagement. This research investigates the pivotal role played by ChatGPT and analogous generative AI technologies in HRM, underscoring their significance in the realms of recruitment, employee training, and organizational communication. Leveraging their natural language processing abilities, these AI systems streamline the recruitment process, ensuring unbiased candidate selection and enhancing the overall efficiency of HR departments. Moreover, in training and development initiatives, ChatGPT facilitates tailored learning experiences, adjusting content to meet individual employee needs, thereby fostering skill enhancement and professional growth. Nevertheless, the widespread adoption of ChatGPT in HRM is not without its challenges. Ethical concerns, such as data privacy and algorithmic bias, necessitate thorough examination to prevent discriminatory practices and guarantee equitable treatment of employees. Additionally, the requirement for continuous monitoring and refinement of AI algorithms to align with evolving organizational cultures and goals presents a significant hurdle. Moreover, striking a harmonious balance between AI-driven automation and human intervention is imperative to preserve the human touch in HRM processes, safeguarding the empathetic and intuitive elements that are essential for effective employee management. This research delves into these complex dynamics, shedding light on the transformative potential of ChatGPT and akin generative AI technologies in HRM, while also emphasizing the need for vigilance and strategic planning to address the associated challenges. Through an exhaustive analysis of real-world case studies and ethical frameworks, this study offers valuable insights for HR professionals, policymakers, and researchers endeavoring to navigate the intricate landscape of AI-powered HRM.

Physicochemical Modeling of Electrochemical Impedance in Solid-State Supercapacitors.

Solid-state supercapacitors (SSCs) consist of porous carbon electrodes and gel-polymer electrolytes and are used in novel energy storage applications. The current study aims to simulate the impedance of SSCs using a clearly defined equivalent circuit (EC) model with the ultimate goal of improving their performance. To this end, a conventional mathematical and a physicochemical model were adapted. The impedance was measured by electrochemical impedance spectroscopy (EIS). An EC consisting of electrical elements was introduced for each modeling approach. The mathematical model was purely based on a best-fit method and utilized an EC with intuitive elements. In contrast, the physicochemical model was motivated by advanced theories and allowed meaningful associations with properties at the electrode, the electrolyte, and their interface. The physicochemical model showed a higher approximation ability (relative error of 3.7%) due to the interface impedance integration in a more complex circuit design. However, this model required more modeling and optimization effort. Moreover, the fitted parameters differed from the analytically calculated ones due to uncertainties in the SSC's microscale configuration, which need further investigations. Nevertheless, the results show that the proposed physicochemical model is promising in simulating EIS data of SSCs with the additional advantage of utilizing well-reasoned property-based EC elements.

Water Quality Grade Identification for Lakes in Middle Reaches of Yangtze River Using Landsat-8 Data with Deep Neural Networks (DNN) Model

Water quality grade is an intuitive element for people to understand the condition of water quality. However, in situ water quality grade measurements are often labor intensive, which makes measurement over large areas very costly and laborious. In recent years, numerous studies have demonstrated the effectiveness of remote sensing techniques in monitoring water quality. In order to automatically extract the water quality information, machine learning technologies have been widely applied in remote sensing data interoperation. In this study, Landsat-8 data and deep neural networks (DNN) were employed to identify the water quality grades of lakes in two cities, Wuhan and Huangshi, in the middle reach of the Yangtze River, central China. Additionally, linear support vector machine (L-SVM), random forest (RF), decision tree (DT), and multi-layer perceptron (MLP) were selected as comparative methods. The experimental results showed that DNN achieved the most promising performance compared to the other approaches. For the lakes in Wuhan, DNN gave water quality results with overall accuracy (OA) of 93.37% and Kappa of 0.9028. For the lakes in Huangshi, OA and kappa given by DNN were 96.39% and 0.951, respectively. The results show that the use of remote sensing images for water quality grade monitoring is effective. In the future, our method can be used for water quality monitoring of lakes in large areas at a low cost.

EXPERT SYSTEMS KNOWLEDGE BASES FOR SOLVING VETERINARY PROBLEMS

Undoubtedly, the factor leading to the death of cattle is the spread of diseases that can worsenthe health of animals. Diagnosing animal diseases is difficult if a qualified veterinary professional is notavailable, which is usually due to the remoteness of livestock farms from scientific veterinary centres. Thus,the use of expert systems for solving veterinary medicine problems is proposed as a solution. An expertsystem for diagnosing animal diseases is required to simplify the work of veterinarians and subsequentlyreduce the incidence of animal diseases.The consequence is that the need to implement decision support toolsis undeniable, as veterinary medicine is a science that involves possible diagnostic errors, decision-makingcomplexity and an extensive knowledge base. As a result, the use of cognitive maps, the functionality ofwhich is described in this article, is proposed. The development of these decision support tools includesboth discrete analytical information and intuitive elements that optimise their impact on everyday veterinarypractice. Cognitive maps are active knowledge resources that use animal data to generate case-specificrecommendations to support diagnostic decision-making. The knowledge sources used and the process ofobtaining, analyzing and evaluating knowledge are described in detail. Productive rules are used as a toolto represent knowledge, which is also used to address the uncertainties that arise in the decision-makingprocess. Introducing one-dimensional tables when structuring a knowledge library is an appropriate solutionfor system design. Creating a knowledge base in the way described can solve the initial goals of developinga software product for veterinary applications.

A Modified Hierarchical Risk Parity Framework for Portfolio Management

This article introduces a modified hierarchical risk parity (MHRP) approach that extends the HRP approach by incorporating three intuitive elements commonly used by practitioners. The new approach (1) replaces the sample covariance matrix with an exponentially weighted covariance matrix with Ledoit–Wolf shrinkage; (2) improves diversification across portfolio constituents both within and across clusters by relying on an equal volatility, rather than an inverse variance, allocation approach; and (3) improves diversification across time by applying volatility targeting to portfolios. The author examines the impact of the enhancements on portfolios of commodity trading advisors within a large-scale Monte Carlo simulation framework that accounts for the realistic constraints of institutional investors. The author finds a striking improvement in the out-of-sample Sharpe ratio of 50%, on average, along with a reduction in downside risk. TOPICS:Statistical methods, simulations, big data/machine learning Key Findings • The author introduces a modified hierarchical risk parity (MHRP) approach, which incorporates three popular portfolio management techniques into the hierarchical risk parity framework of Lopez de Prado. • He reports a striking improvement in the out-of-sample Sharpe ratio of 50%, on average, for portfolios of commodity trading advisors. • The author argues that the MHRP framework has broad applications for portfolios of traditional and alternative investments.

Cobot programming for collaborative industrial tasks: An overview

Collaborative robots (cobots) have been increasingly adopted in industries to facilitate human–robot collaboration. Despite this, it is challenging to program cobots for collaborative industrial tasks as the programming has two distinct elements that are difficult to implement: (1) an intuitive element to ensure that the operations of a cobot can be composed or altered dynamically by an operator, and (2) a human-aware element to support cobots in producing flexible and adaptive behaviours dependent on human partners. In this area, some research works have been carried out recently, but there is a lack of a systematic summary on the subject. In this paper, an overview of collaborative industrial scenarios and programming requirements for cobots to implement effective collaboration is given. Then, detailed reviews on cobot programming, which are categorised into communication, optimisation, and learning, are conducted. Additionally, a significant gap between cobot programming implemented in industry and in research is identified, and research that works towards bridging this gap is pinpointed. Finally, the future directions of cobots for industrial collaborative scenarios are outlined, including potential points of extension and improvement.

Role of intuitive knowledge in the diagnostic reasoning of hospital specialists: a focus group study

Background and objectiveIntuition is an important part of human decision-making and can be explained by the dual-process theory where analytical and non-analytical reasoning processes continually interact. These processes can also...

Development of an explanatory framework for the solution of electricity problems

Problem solving is considered a higher order thinking skill and is included as one of the 21st century’s core competencies. To demonstrate how students’ use of a specific mathematical approach leads to a particular type of understanding when solving problems in electricity, an interpretive framework was developed. This interpretive framework combined two extensively used frameworks, namely Mathematical Resources (MR) and Extended Semantic Model (ESM) and was rationalised in electricity subtopics namely electric circuit, electric force and electric field. An interpretivist research paradigm was chosen to explain and derive meaning from fifteen first year physics students’ mathematical approaches in solving electricity problems. In general, students were found to be more inclined to activate formal mathematical rules, even when the use of basic or everyday mathematics that require activation of intuitive knowledge elements and reasoning primitives, would be more efficient. The need for a qualitative approach to solving physics problems rather than a quantitative one was presented and this has implications for future approaches to teaching science.

THE DESIGN & SIMULATION OF LOW NOISE AMPLIFIER FOR 1 -2.8 GHZ USING ALN SUBSTRATE

In this paper, we have designed low noise amplifier using 2 stage Cascade topology. We have focused on intermediate matching network design of amplifier for low noise figure and selection of transistor PHEMT is based on noise figure as well as quiescent point required for 0 grid voltage so that amplifier will need only single DC supply i.e. Vdd. Depends upon different topologies used for LNA design with wide band requirement, we chose cascaded topology for good gain with low noise amplifier and optimized for greater bandwidth. Practical inductors are bulky as well as counter intuitive elements for high frequency as they behave as capacitors and to reduce S11. Several windings in inductors make them resistive which increases noise by 0.2-0.4 dB. So we proposed inductor-less input matching network for both stages so that we can increase bandwidth as well as perfect match for low noise figure. This LNA is designed using Advanced Design System (ADS) software to provide 0.5 dB noise figure with power gain of 25 dB and 1-2.5 GHz Bandwidth. So it can be used an L-Band satellite modem that is used in an asset tracking application. Layout is designed using muruta manufacturing lumped components and Aluminum Nitride (AlN) substrate having high dielectric constant and high thermal conductivity.

Duality as a category-theoretic concept

In a paper published in 1939, Ernest Nagel described the role that projective duality had played in the reformulation of mathematical understanding through the turn of the nineteenth century, claiming that the discovery of the principle of duality had freed mathematicians from the belief that their task was to describe intuitive elements. While instances of duality in mathematics have increased enormously through the twentieth century, philosophers since Nagel have paid little attention to the phenomenon. In this paper I will argue that a reassessment is overdue. Something beyond doubt is that category theory has an enormous amount to say on the subject, for example, in terms of arrow reversal, dualising objects and adjunctions. These developments have coincided with changes in our understanding of identity and structure within mathematics. While it transpires that physicists have employed the term ‘duality’ in ways which do not always coincide with those of mathematicians, analysis of the latter should still prove very useful to philosophers of physics. Consequently, category theory presents itself as an extremely important language for the philosophy of physics.

Fuzzy cognitive maps: a tool to improve diagnostic decisions.

Anticipating that the problem of diagnostic errors will not easily be solved through education, debiasing techniques or incentives-based systems, experts have proposed the systematic use of decision support tools (or decision aids) in medical practice. These tools are active knowledge resources that use patient data to generate case-specific advice to support clinical decision making. We argue that designing these decision support tools incorporates both discrete, analytical information as well as intuitive elements that would optimize their impact on clinical everyday activities. The use of fuzzy cognitive maps should allow developers to achieve this aim, by incorporating published evidence, intuition and qualitative assessment in a low-cost software program that could be implemented in various clinical settings.

Goffman on Emotions: The Pride‐Shame System

This essay proposes that Goffman's basic method was the intuitive recognition of generic examples of social interaction. This focus on examples, when considered from the point of view of two of Cooley's general propositions, helps explain the meaning of Goffman's metaphor of theatrical performance, and his insistence on the risk of shame in all interaction. These ideas make sense following Pascal's emphasis on the intuitive element in finding new knowledge, and Spinoza's part/whole idea. This latter approach leads to what will be called the Goffman/Cooley conjecture: we run the risk of shame in all human interaction. Although they didn't explain why, it seems that the pace of modern alienated societies punishes the mammalian urge that humans have for connectedness (pride) with others. These ideas seem to be supported by studies by Helen Lewis and Norbert Elias, and by my own recent study of Ngrams. As Elias's study proposed, virtually all shame is hidden in modern societies. The idea of hidden shame requires a new definition of shame that is quite different than vernacular usage.

Teaching and learning clinical decision-making for person-centered medicine: recommendations from a systematic review of the literature

Rationale, aims and objectives: Clinical decision-making (CDM) has been studied from diverse perspectives, including diagnostic cognition, clinical error and probabilistic modelling of patient management under uncertainty. This paper aims to establish the current knowledge base for CDM by systematic review, in order to produce recommendations for clinicians and clinical teachers. Method: Biomedical, social science and education databases were searched. All English-language articles concerning CDM in medical education, from peer-reviewed academic journals, were included. Meeting abstracts were hand searched for relevance. 236 citation abstracts were kept for consideration, then themed for ease of analysis. Current thinking was reviewed and discussed, and key recommendations for teaching CDM were made for clinicians. Results: The hypothetico-deductive cognitive method is criticised, as experts use little hypothesis testing. Clinical expertise is associated with better content-specific memory, consisting of encapsulated biomedical and clinical knowledge as goal-directed knowledge-structures (illness scripts). These are rich, accessible and activated intuitively (pattern recognition). Decision theory and Bayes’ theorem provide a mathematical rule for rationalising a hypothesis and decision analysis updates this for complex decisions. Clinicians should appreciate the nature and impact of cognitive errors on CDM and use cognitive forcing strategies to lessen them. Conclusion: Analytical and non-analytical (intuitive) models of CDM are not mutually exclusive and dual-process or additive models of CDM account for this. Key recommendations for clinical teaching include development of knowledge encapsulations as individual constructs, combined learning of analytical and intuitive elements and reducing cognitive error by metacognition, forcing strategies and constructive feedback.

Measuring Business Performance: Emerging Perspectives Of The Balanced Scorecard

<p class="MsoBodyText" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">Benchmarking business performance over time is an emerging managerial capability that is used for continuous improvement of existing value adding activities and processes that become leading indicators of strategic success.<span style="mso-spacerun: yes;">  </span>To achieve this success, corporations first define success, and then they decide how to get there from where they are presently.<span style="mso-spacerun: yes;">  </span>Financial information has long been the language of business with accountants adding up the numbers and defining success in bottom-line figures.<span style="mso-spacerun: yes;">  </span>What have been missing are the non-financial elements of business enterprises, elements that can be quantified and linked to the bottom line as predictors of financial success. This paper utilizes Kaplan & Norton’s Balanced Scorecard (BSC) and an extensive pilot study of ski resorts to explore an awareness of using non-financial information as a supplement to financial information in explaining overall strategic performance in one segment of the tourism industry. </span></span></p><p class="MsoBodyText" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;"> </span></span></p><p class="MsoBodyText" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">Leading and lagging indicators of a non-financial nature were used in the study to help focus on the strategic and operational management practices at selected ski resorts in Colorado, Montana, Canada, and the Pacific Northwest.<span style="mso-spacerun: yes;">  </span>A list of potential critical success factors and non-critical success factors that help build value and best business practices for ski resort management, were identified through written and oral interview survey techniques following a combination Delphi & Nominal Group Techniques.<span style="mso-spacerun: yes;">  </span>Previous work on the balanced scorecard by Kaplan and Norton aided in the identification and description of indicators within each of four balanced perspectives.<span style="mso-spacerun: yes;">  </span>Recognition of the intuitive elements of non-financial measures represents a departure from prevalent theory that favors the more traditional financial perspective.</span></span></p>

A New Digital Relaying Scheme for Parallel Transmission Line

This paper presents a scheme for the protection of parallel transmission line having two different configurations (geographical locations). In the proposed scheme, the six line currents at a common end of a parallel line or three line currents at a separate end of a parallel line are decomposed using wavelet packet transform (WPT) in order to derive the operating quantities for relay operation. The proposed scheme provides stability against close-in faults, more sensitivity towards high resistance faults and reliability for discriminating in-zone and out-zones faults during complete loss of generation at one of the buses. When the conventional relay, without an intuitive directional element, fails to trip for a remote end fault located in the vicinity of remote bus, the proposed method solves the said problem and also avoids the voltage signal used in conventional relays. Furthermore, the suggested scheme completely avoids the requirement of a distance algorithm as a backup protection in case of the disconnection of one line (due to maintenance or fault). Moreover, the proposed scheme analyzes solves the problem of simultaneous same phase fault on parallel lines. To validate the proposed scheme, numerous computer simulations have been carried out on realistic data of part of the Indian 400 kV power transmission system network.

Harmonic Focus Case Study: Leading Innovation Through Unique User Research Methods and Tools

Ethicon Endo-Surgery's Harmonic FOCUS is a curved-shear (blade with clamp arm) surgical instrument that combines the intuitive elements of a classic precision instrument with a Harmonic ultrasonic hand piece for a revolutionary multifunction precision device. We propose to describe the unique approach to user research used in the development of the product and how the team used these innovative methods and tools to identify and meet the following design and engineering challenges: 1. Combine the surgical tasks of dissecting, grasping and simultaneously cutting and coagulating into one precision device for the first time. The Harmonic FOCUS was developed as a result of three years of extensive market assessment and a unique research methodology, including a novel process of ethnographically observing and graphically mapping thyroidectomy procedures. 2. Miniaturize the hand piece (transducer) from the existing ultrasonic product line while retaining its clinical performance (speed and hemostasis). The following dramatic and extensive design changes offer improved clinical performance: Reducing the volumetric size of the transducer 55% relative to the predecessor device. Achieving reliable control of clamp force. Curving the blade to resemble typical surgical instruments. Improving speed of operation. Reduction of residual heat. 3. Provide the surgeon with superior and intuitive ergonomics by leveraging elements of a classic precision tool. The team combined the essential elements of a classic precision tool with Harmonic (ultrasonic) technology to develop a revolutionary, multifunctional device with superior and intuitive ergonomics. Surgeons concur with the versatile, comfortable design. 4. Use materials that are all sterilization-compatible. Extensive research was done to identify and use materials that were all compatible with ethylene oxide sterilization. The device is packaged in flexible packaging and ethylene-oxide sterilized prior to sale. Harmonic FOCUS is designed for single-patient use. The Harmonic Blue Hand Piece is sold non-sterile and is qualified for multiple sterilization methods readily available in hospitals. The hand piece can be reused up to 100 times.

Using the Principles of Interactive Cartography to Communicate the Mechanisms of Migraine Pain

The program entitled ‘Mapping Migraine Pain’ was created based on the principles of interactive cartography to communicate the complexity of the mechanisms of migraine pain. An innovative zoom slider was developed to enhance spatial orientation and comprehension of multiple scales of information from the anatomical to the cellular and molecular levels. Think‐aloud protocols were conducted with ten undergraduate first‐year medical students to evaluate the significance and usability of the program. The zoom slider, based on interactive cartography, proved to be an effective and intuitive navigational element.

An Ethical Decision-Making Model for Operational Psychology

Operational psychology is an emerging subdiscipline that has enhanced the U.S. military's combat capabilities during the Global War on Terrorism. What makes this subdiscipline unique is its use of psychological principles and skills to improve a commander's decision making as it pertains to conducting combat (or related operations). Due to psychology's expanding role in combat support, psychologists are being confronted with challenges that require the application of their professional ethics in areas in which little if any guidance has been provided. Operational psychologists are at the forefront of this expansion. Accordingly, they need a decision model to assist them in this complex dynamic environment. To this end, this article reviews various decision models and ethical frameworks, selects the most appropriate, and then applies it to the challenges faced by operational psychologists. A naturalistic decision model that integrates rational and intuitive elements is recommended.