Graphical Interface for the Recommendation System

Today, mathematics plays a huge part of our everyday life. But due to the poor school education and lack of open access resources, many students find it difficult to be fully prepared for the independent external evaluation in mathematics, especially geometry. Although much has already been done to conduct higher knowledge results, lots of students still have gaps in understanding simple problem solving. Clearly, geometry requires a more fundamental and visual implementation to the studying process than algebra in order to increase the overall knowledge level of Ukrainian applicants for higher education. Students often do not have access to innovative studying instruments in their schools necessary for successful completion of geometry classes, which is why they receive weak results in tests.In the research, we are concentrating on the planimetry problems, because they can be easily produced in a written form. After analyzing all types of describing a problem, the best option for the system is the open-type problems with the short answer.The article concentrates on creating a graphical interface module, implementing it to the existing language processing module, and introducing a recommendation system that demonstrates a new fundamental instrument that can change the learning technique and give a comprehensive way of explaining geometry problems.The created system receives an open-type planimetry problem in Ukrainian language, processes it using the NLP module, and transfers the data directly to the interface module, which creates an image of the problem. Then the student can try to draw all the required figures, while the system continuously checks the progress. Recommendations (hints) can be applied during the process by the system.Interface and the NLP modules were created separately, independently, and using different programming languages. For that purpose, we use an intermediate stage – JSON file, which is used to transfer the processed information.

Organizational Learning Capacity and Sustainability Challenges in Times of Crisis: A Study on Tourism SMEs in Galicia (Spain)

The COVID-19 crisis has encouraged a major shift towards greater environmental awareness and sustainable consumption. However, in times of severe crisis, SMEs primarily look to return to normalcy and their own survival rather than implementing a sustainable agenda. This paper aims to contribute to the understanding of the learning problems faced by small tourism enterprises in a crisis such as the COVID-19 pandemic. This paper explores the learning capacity of SMEs and the importance of establishing mechanisms that provide SMEs with the keys to organizational learning as a source of continuous knowledge. Open-ended semi-structured interviews with 39 tourism SMEs managers in Galicia (Spain) were conducted during the toughest months of the COVID-19 pandemic. The results show that SMEs have not been fully involved in the learning process, which is mainly related to knowledge transfer and integration. DMOs can act as promoters of knowledge management for organizational preparedness by providing SMEs with learning mechanisms and strategies to go beyond simple problem solving when they arise.

Identifying tumor cells at the single cell level

Tumors are highly complex tissues composed of cancerous cells, surrounded by a heterogeneous cellular microenvironment. Tumor response to treatments is governed by an interaction of cancer cell intrinsic factors with external influences of the tumor microenvironment. Disentangling the heterogeneity within a tumor is a crucial step in developing and utilization of effective cancer therapies. Single cell sequencing has the potential to revolutionize personalized medicine. In cancer therapy it enables an effective characterization of the complete heterogeneity within the tumor. A governing challenge in cancer single cell analysis is cell annotation, the assignment of a particular cell type or a cell state to each sequenced cell. We propose Ikarus, a machine learning pipeline aimed at solving a perceived simple problem, distinguishing tumor cells from normal cells at the single cell level. Automatic characterization of tumor cells is a critical limiting step for a multitude of research, clinical, and commercial applications. Automatic characterization of tumor cells would expedite neoantigen prediction, automatic characterization of tumor cell states, it would greatly facilitate cancer biomarker discovery. Such a tool can be used for automatic annotation of histopathological data, profiled using multichannel immunofluorescence or spatial sequencing. We have tested ikarus on multiple single cell datasets to ascertain that it achieves high sensitivity and specificity in multiple experimental contexts.

Integrating AI Microservices into Hard-Real-Time SoS to Ensure Trustworthiness of Digital Enterprise Using Mission Engineering

Due to the increased complexities and operating speeds of today’s and tomorrow’s system-of-systems (SoS) architectural configurations for digital enterprises, the design of new domain architecture management systems is required. A key element of these new designs will be the incorporation of Artificial Intelligence (AI) microservices to provide dynamically containerized and orchestrated service capabilities within a lightweight interoperability fabric with the ability to operate in hard-real-time environments. Each containerized AI microservice exposes an independent, programmable function, which enables it to be easily reused, evolved, or replaced without compromising interoperability across critical mission essential functions to execute mission threads. In addition, embedded in this design needs to be a trust management layer to enforce reliable messaging and trust amongst the actors. This paper provides a framework for planned research and demonstrates the feasibility of microservices using a representative simple problem to demonstrate the application of the framework. Early positive analysis results using AI microservices within an SoS environment shows that the 500 milli-second (ms) threshold for latency can be met.

Measuring Cognitive Load: Are There More Valid Alternatives to Likert Rating Scales?

Cognitive load researchers have used varying subjective techniques based on rating scales to quantify experienced cognitive load. Although it is generally assumed that subjects can introspect on their cognitive processes and have no difficulty in assigning numerical values to the imposed cognitive load, little is known about how visual characteristics of the rating scales influence the validity of the cognitive load measure. In this study we look at validity of four subjective rating scales (within groups) differing in visual appearance by participants rating perceived difficulty and invested mental effort in response to working on simple and complex weekday problems. We used two numerical scales (the nine-point Likert scale most often used in Cognitive load theory research and a Visual Analogue Scale ranging between 0–100%) and two pictorial scales (a scale consisting of emoticons ranging from a relaxed blue-colored face to a stressed red-colored face and an “embodied” scale picturing nine depicted weights from 1–9 kg). Results suggest that numerical scales better reflect cognitive processes underlying complex problem solving while pictorial scales Underlying simple problem solving. This study adds to the discussion on the challenges to quantify cognitive load through various measurement methods and whether subtleties in measurements could influence research findings.

A-175 Personality as a Proxy for Positive Effort: The Role of Grit, Need for Cognition, and Extraversion in Problem-Solving

Objective This study aimed to examine the effect of personality traits on a simple problem-solving test of intelligence. Method The sample consisted of 82 undergraduates. Participants completed an online battery that included an open source Five Factor Model measure (IPIP FFM), Grit scale, Need for Cognition (NFC) scale, and the Cognitive Reflection Test (CRT). CRT is a simple 3 question test of intelligence. An interaction variable for positive effort was created by multiplying the total raw scores for the Grit and NFC scales (Grit x NFC). Correlations were conducted between the Grit x NFC, IPIP FFM, and the CRT total score. Scales that significantly correlated with CRT total score were entered into a regression model. Results Pearson correlations revealed a significant positive association between Grit x NFC and CRT performance, (r = 0.240, p < 0.05). A significant correlation was also found between IPIP FFM Extraversion factor and CRT performance (r = 0.230, p < 0.05). A regression model found that Grit x NFC and IPIP FFM Extraversion accounted for 9.2% of the variance in CRT total scores, (R2 = 0.092, F(1,82) = 3.92, p = 0.024). When examined individually, no individual predictors were significant. Conclusion These findings suggest that personality traits that reflect positive effort such as Grit and NFC as well as other personality features influence performance on problem-solving bases measures of intelligence. Future research should examine these findings in a larger sample with a broader array of cognitive measures to quantify the role of positive effort in cognitive performance.

Slow-burning instabilities of Dufort-Frankel finite differencing

DuFort–Frankel averaging is a tactic to stabilize Richardson’s unstable three-level leapfrog timestepping scheme. By including the next time level in the right-hand-side evaluation, it is implicit, but it can be rearranged to give an explicit updating formula, thus apparently giving the best of both worlds. Textbooks prove unconditional stability for the heat equation, and extensive use on a variety of advection–diffusion equations has produced many useful results. Nonetheless, for some problems the scheme can fail in an interesting and surprising way, leading to instability at very long times. An analysis for a simple problem involving a pair of evolution equations that describe the spread of a rabies epidemic gives insight into how this occurs. An even simpler modified diffusion equation suffers from the same instability. Finally, the rabies problem is revisited and a stable method is found for a restricted range of parameter values, although no prescriptive recipe is known which selects this particular choice. doi:10.1017/S1446181121000043

Policy Networks in Improving the Quality of Housing and Settlements in Indonesia (A Case Research of Bandung District)

Studies on slum housing and settlements have been carried out in many countries. The various studies show that the problem of housing and settlement areas can no longer be considered a simple problem. Different from the various studies on housing and settlement areas, this research employs the perspective of policy networks as a new public administration paradigm. The development issue on housing and settlement areas is regarded as one of the contemporary international issues contained in one of the 17 Sustainable Development Goals (SDGs). Several countries have become the focus of attention, such as: India, Mongolia, Sri Lanka, Pakistan, and Thailand. In Indonesia, the development of housing and settlement areas is mandated by law. The Local Government of Bandung District has made efforts to improve the quality of housing and settlements through such programs as the PLPBK, Rutilahu, and Kotaku. However, the improvement in the quality of housing and settlements in general has not touched the basic problem, namely the welfare of the community. The development is limited to physical improvements and lasts 1 (one) to 2 (two) years. In the third year the restored area becomes irregular / slum again. Therefore, it is recommended that the Bandung District government issue a local regulation in the form of a Regent Regulation concerning the improvement of housing and settlement quality and a plan for handling it as the legal bases. In addition, a collaboration of actors in policy networks should be formed based on the pentahelix model incorporating the actors of business, government, community, academic, and media.

Can a Skywalker Localize the Midpoint of a Rope?

This article poses a question about a simple localization problem. The question is if an oblivious walker on a line segment can localize the midpoint of the line segment in a finite number of steps observing the direction (i.e., Left or Right) and the distance to the nearest end point. This problem arises from self-stabilizing location problems by autonomous mobile robots with limited visibility , which is an abstract model attracting a wide interest in distributed computing. Contrary to appearances, it is far from trivial whether this simple problem is solvable, and it is not settled yet. This article is concerned with three variants of the problem with a minimal relaxation and presents self-stabilizing algorithms for them. We also show an easy impossibility theorem for bilaterally symmetric algorithms.