Analogical Mapping Research Articles

Characterisation of analogue MAPS fabricated in 65 nm technology for the ALICE ITS3

The ALICE ITS3 project foresees the use of ultra-light MAPS, developed in the 65 nm imaging process, for the vertex detector in the ALICE experiment at the LHC to drastically improve the vertexing performance. This new development, initiated by an international consortium of the ALICE ITS3 collaboration and the CERN EP R&D project, enhances the overall MAPS performance.Small-scale prototypes are designed to study the analogue properties of the TPSCo 65 nm technology and compare the charge collection performance in different processes, pitches, pixel geometries, and irradiation levels. Recent results from lab and test-beam characterisation detailing the efficiency and the spatial resolution of the APTS with different pixel geometries and pitches satisfy the ALICE ITS3 requirements. A quantitative evolution of the charge collection and sharing among pixels is evident in the CE-65 with different in-pixel readouts. Attaining a spatial resolution better than 3μm with a 10μm pitch and over 99% efficiency in the moderate irradiation environment of ALICE also supports the viability of using 65 nm MAPS for FCC-ee vertex detectors.

Analyzing the Impact of the Climate Emergency on Shipping through Analogical Interpretation of the COVID-19 Pandemic

Abstract A profound apprehension across the scientific and political landscape on the increasing severity of the adverse effects of climate change has provoked a rethink on tackling the challenges. These challenges have questioned the status quo on current governance arrangements and its relevance in addressing extant environmental exigencies. Besides the urgent need to reduce anthropogenic emissions and the swiftly intensifying trajectory of global warming, there is also the urgent need to adapt to the consequences of the changing climate due to its impact on societal well-being. The quest for societal behaviors to remain in sync with a rapidly changing environment has propelled scholarly exploration in the direction of the climate emergency. However, as the issue of the climate emergency in shipping is largely unexplored, research into understanding of the phenomenon is an essential prerequisite. The article uses experiences gained from the impact of the COVID-19 pandemic on global shipping as a tool to address the governance of climate emergencies in global shipping. This goal is achieved through the application of expert opinion in analogical mapping which lays the foundation for the knowledge interpretation. The results of the analysis confirmed the existence of structure similarities between pandemics and the climate emergency through attribute variables that are common to both phenomena.

Neural Correlates of Analogical Reasoning on Syntactic Patterns.

Analogical reasoning is central to thought and learning. However, previous neuroscience studies have focused mainly on neural substrates for visuospatial and semantic analogies. There has not yet been research on the neural correlates of analogical reasoning on syntactic patterns generated by the syntactic rules, a key feature of human language faculty. The present investigation took an initial step to address this paucity. Twenty-four participants, whose brain activity was monitored by fMRI, engaged in first-order and second-order relational judgments of syntactic patterns as well as simple and complex working memory tasks. After scanning, participants rated the difficulty of each step during analogical reasoning; these ratings were related to signal intensities in activated regions of interest using Spearman correlation analyses. After prior research, differences in activation levels during second-order and first-order relational judgments were taken as evidence of analogical reasoning. These analyses showed that analogical reasoning on syntactic patterns recruited brain regions consistent with those supporting visuospatial and semantic analogies, including the anterior and posterior parts of the left middle frontal gyrus, anatomically corresponding to the left rostrolateral pFC and the left dorsolateral pFC. The correlation results further revealed that the posterior middle frontal gyrus might be involved in analogical access and mapping with syntactic patterns. Our study is the first to investigate the process of analogical reasoning on syntactic patterns at the neurobiological level and provide evidence of the specific functional roles of related regions during subprocesses of analogical reasoning.

Information sculpting

AbstractIn this paper, I propose sculpting as an analogy for information use. I provide a background to the use of metaphors and analogies in Information Science, propose five analogical mappings between sculpting and information use, and then discuss the benefits to this analogy for thinking about how we use information.

Teaching loss of brand control to engineering entrepreneurship students through analogical mapping

The advent of the digital environment is leading to ongoing removal of the brand from the sphere of corporate control. Applying analogical mapping derived from Gentner's theory, this conceptual paper proposes an interdisciplinary analogy to learn about loss of brand control, aligning the dynamics of branding with planetary dynamics. This analogy based on Newtonian physics provides insight into the loss of brand control caused by managerial inadequacy and stakeholder empowerment. The paper is one of the first to propose analogical mapping as a teaching-learning tool for brand management teaching in entrepreneurship education. The use of the analogy about loss of brand control holds the potential to assist engineering scholars who teach entrepreneurship in providing their students with valuable insights into the contemporary dynamics of brand management. By providing a deeper understanding of these dynamics, scholars can orient their students towards adopting open, flexible, and participatory approaches to management, as well as a more humble and transparent leadership style. This conceptual paper views the widespread use of analogy within entrepreneurship programs as a driver that could lead to a change in the business model, stimulating the development of required managerial mindsets and skills.

Mapy i inne formy geowizualizacji wykorzystywane w enoturystyce

The article concerns the utility of traditional maps as well as different forms of geovisualization in wine tourism (enotourism). At various stages, the so-called tourist experience (stages: anticipation, planning, travel-to, on-site, travel-from and recollection), the usefulness of analogue maps and geovisualization is different. The introduction and development of the Internet makes new forms of cartographic communication more popular and mobile applications has begun to replace traditional maps.

Lattice-Based Analog Mappings for Low-Latency Wireless Sensor Networks

We consider the transmission of spatially correlated analog information in a WSN through fading SIMO MAC with low latency requirements. A lattice-based analog JSCC approach is considered where vectors of consecutive source symbols are encoded at each sensor using an n-dimensional lattice and then transmitted to a multi-antenna central node. We derive a MMSE decoder that accounts for both the multi-dimensional structure of the encoding lattices and the spatial correlation. In addition, a sphere decoder is considered to simplify the required searches over the multi-dimensional lattices. Different lattice-based mappings are approached and the impact of their size and density on performance and latency is analyzed. Results show that, while meeting low-latency constraints, lattice-based analog JSCC provides performance gains and higher reliability with respect to the state-of-the-art JSCC schemes.

Students' Analogical Reasoning in Solving Trigonometric Target Problems

Analogical reasoning plays a crucial part in problem-solving since it requires students to connect prior knowledge with the issues at hand in learning mathematics. However, students struggle when developing solutions to the issues utilizing analogies even if there is a connection between mathematical creativity and analogical reasoning. The aims of this study were to assess students' use of Ruppert's phases to solve problems and identify students' analogy patterns to solve target problems. This study is qualitative in nature. Of 19 research participants, six were then chosen using the purposive sampling technique based on their levels of mathematical creative ability. Test, interview, and documentation were the data gathering techniques used in this study. The study's findings suggested that good analogical reasoning skills did not serve as a prerequisite for students with strong mathematical creative thinking skills. Only one subject out of three who possessed necessary mathematical creative thinking abilities could go through the four steps of analogical reasoning-structuring, mapping, applying, and verifying. All other subjects were unable to complete the four steps of analogy, and even their creative thinking skills were weak. This was because the students did not comprehend the idea and could not connect prior knowledge with the issues at hand. In order to remind students of their prior knowledge and experiences, it would therefore be necessary at this analogy stage to establish an initial stage before structuring. The format and degree of difficulty of the questions were assumed to be other elements that might influence students' responses. The results of this study are expected to be a reference for further research, namely increasing analogical reasoning optimally as an effort to increase students' prior knowledge and students' mathematical creative thinking abilities in solving mathematical problems.

Zero-shot visual reasoning through probabilistic analogical mapping

Human reasoning is grounded in an ability to identify highly abstract commonalities governing superficially dissimilar visual inputs. Recent efforts to develop algorithms with this capacity have largely focused on approaches that require extensive direct training on visual reasoning tasks, and yield limited generalization to problems with novel content. In contrast, a long tradition of research in cognitive science has focused on elucidating the computational principles underlying human analogical reasoning; however, this work has generally relied on manually constructed representations. Here we present visiPAM (visual Probabilistic Analogical Mapping), a model of visual reasoning that synthesizes these two approaches. VisiPAM employs learned representations derived directly from naturalistic visual inputs, coupled with a similarity-based mapping operation derived from cognitive theories of human reasoning. We show that without any direct training, visiPAM outperforms a state-of-the-art deep learning model on an analogical mapping task. In addition, visiPAM closely matches the pattern of human performance on a novel task involving mapping of 3D objects across disparate categories.

VASR: Visual Analogies of Situation Recognition

A core process in human cognition is analogical mapping: the ability to identify a similar relational structure between different situations. We introduce a novel task, Visual Analogies of Situation Recognition, adapting the classical word-analogy task into the visual domain. Given a triplet of images, the task is to select an image candidate B' that completes the analogy (A to A' is like B to what?). Unlike previous work on visual analogy that focused on simple image transformations, we tackle complex analogies requiring understanding of scenes. We leverage situation recognition annotations and the CLIP model to generate a large set of 500k candidate analogies. Crowdsourced annotations for a sample of the data indicate that humans agree with the dataset label ~80% of the time (chance level 25%). Furthermore, we use human annotations to create a gold-standard dataset of 3,820 validated analogies. Our experiments demonstrate that state-of-the-art models do well when distractors are chosen randomly (~86%), but struggle with carefully chosen distractors (~53%, compared to 90% human accuracy). We hope our dataset will encourage the development of new analogy-making models. Website: https://vasr-dataset.github.io/

Deception Island 1967–1970 Volcano Eruptions from Historical Aerial Frames and Satellite Imagery (Antarctic Peninsula)

Aerial frames and satellite imagery are widely recognized data sources from which to produce maps. For volcanoes, maps enable the quantification of erupted ash and the destruction caused. The last eruptive sequence on Deception Island was endured from 1967 to 1970. Analogue maps were produced via classical photogrammetric methods with a high degree of human intervention mainly to analyse the volcanic-centres areas only. However, historical aerial frames cover the whole of Deception Island. Structure from motion photogrammetry, a near-automated compilation of digital image processing strategies, minimizes the degree of human intervention to produce orthographic mosaics and digital elevation models from digital aerial frames. Orthographic mosaics were produced from historical aerial frames of 1956 and 1968, and a Kompsat-3 image of 2020. Their shared root-mean-square deviation was 1.8 m and 1.7 m in easting and northing, respectively, at ground control points measured with phase-differential global navigation satellite systems. The digital elevation models were processed with a root-mean-square deviation of 2.3 m and 3.6 m from 1956 and 1968 aerial frames, respectively. As the first application, erupted ashfall and the subsequent destruction, mainly at the former Chilean and British bases, were identified, and the volume of erupted ash was assessed to be over 0.16 km3 within the area mapped by these new digital cartographic products.

Preschoolers' Perceptual Analogical Reasoning and Map Reading: A Preliminary Study on the Mediating Effect of Spatial Language.

Reading and interpreting a map represents an essential part of daily life, enabling appropriate orientation and navigation through space. Based on the idea that perceptual analogical reasoning is critical in aligning the spatial structure of the map with the spatial structure of the space and given the critical role of language, especially spatial language, in encoding and establishing spatial relations among elements in the environment, the present study investigated the joint contribution of perceptual analogical reasoning and spatial language in map reading. The study was conducted with 56 typically developing 4- to 6-year-old children, and the results indicated that perceptual abstract reasoning affected map reading through the mediating effect of spatial language. These findings yielded theoretical and practical implications regarding the role of perceptual abstract reasoning and spatial language in shaping map-reading abilities in the early stages of life, highlighting that domain-specific language competencies are necessary to improve the encoding of spatial relations, to establish object correspondences, and to ensure successful navigation. Limitations and future research directions were discussed.

Kemampuan Penalaran Analogi Matematis di Indonesia: Systematic Literature Review

This study aims to describe the results of research on students' analogical reasoning abilities in learning mathematics. This study uses the Systematic Literature Review (SLR) method. The sample consisted of 17 articles from SINTA and Google Scholar indexed journals published from 2018 to October 2022. The results of this study were reviewed based on the journal index, year of publication, year of publication, journal index, level of study, sample size, research location, and material covered. used in research analysis of students' analogical reasoning abilities in learning mathematics. By using the SLR method, it was found that the most articles were published in SINTA 4, there was an increase in the number of articles published in SINTA each year, the sample size used was less than 30 subjects, the location was dominated by Java, algebra and geometry materials were mostly used. used in students' mathematical literacy research based on cognitive style, and in terms of the four components of analogical reasoning, namely encoding, inferring, mapping, and application it was found that there were still many students who had difficulty in the mapping and applying.

Localization of the Nevrian and Scythian Plowmen Tribes in the Context of Ethnogenesis of Eastern Slavs

Archaeological researches of settlements and hillforts of the VII-III centuries B.C. in the Middle and Upper Dnieper region on the territory of Ukraine and Belarus in the 20th and 21st centuries contributed to the possibility of further ethnological research of the Slavs. B. Rybakov in the 1980s developed a system of the Eastern Slavs ethnogenesis research from the Bronze Age to Ruthenia using the methods of historical geography, based on the research of Ukrainian (S. Berezanska, V. Illinska, O. Terenozhkina, etc.) and Belarusian (O. Melnykivska, L. Pobolia) archaeologists. He compared the maps of the homeland of the Proto-Slavic tribes from different periods and found the sameness of their main contours for two millennia. This fact became the basis of our further research.During the Scythian period, a civilizational breakdown took place in Rome and Athens – a change from the natural tribal system to the imperial-oligarchic one. In Eastern Europe during these ages and before the emergence of Kyivan Rus, Slavic tribes continued to live in a tribal system. In this work, we aim to prove the tribal structure of the Slavs by locating the nests of the ancestral settlements of the Slavic tribes of the Herodotus’ Neurs and Scythian farmers in the basins of the Dnieper, Prypiat, and Desna rivers on the modern maps at a scale of 1:250,000. Analogous mapping of the nests of Scythian farmers’ tribal settlements of the Left Bank of Ukraine was published in the previous issue of the Ukrainoznavstvo journal. These and further similar studies will reveal the characteristic features of the ethnogenesis of Ukrainian Slavs from the annalistic tribes of Kyivan Rus to the Iron, Bronze, and Copper Ages.

Global thermal spring distribution and relationship to endogenous and exogenous factors

Here we present digitization and analysis of the thermal springs of the world dataset compiled by Gerald Ashley Waring in 1965 into a collection of analog maps. We obtain the geographic coordinates of ~6,000 geothermal spring areas, including complementary data (e.g., temperature, total dissolved solids, flow rate), making them available in electronic format. Using temperature and flow rate, we derive the heat discharged from 1483 thermal spring areas (between ~10−5 and ~103 MW, with a median value of ~0.5 MW and ~8300 MW in total). We integrate this data set with other global data sets to study the relationship between thermalism and endogenous and exogenous factors with a supervised machine learning algorithm. This analysis confirms a dominant role of the terrestrial heat flow, topography, volcanism and extensional tectonics. This data set offers new insights and will boost future studies in geothermal energy exploration.

Probabilistic analogical mapping with semantic relation networks.

The human ability to flexibly reason using analogies with domain-general content depends on mechanisms for identifying relations between concepts, and for mapping concepts and their relations across analogs. Building on a recent model of how semantic relations can be learned from nonrelational word embeddings, we present a new computational model of mapping between two analogs. The model adopts a Bayesian framework for probabilistic graph matching, operating on semantic relation networks constructed from distributed representations of individual concepts and of relations between concepts. Through comparisons of model predictions with human performance in a novel mapping task requiring integration of multiple relations, as well as in several classic studies, we demonstrate that the model accounts for a broad range of phenomena involving analogical mapping by both adults and children. We also show the potential for extending the model to deal with analog retrieval. Our approach demonstrates that human-like analogical mapping can emerge from comparison mechanisms applied to rich semantic representations of individual concepts and relations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Concordance of functional MRI memory task and resting-state functional MRI connectivity used in surgical planning for pediatric temporal lobe epilepsy.

Assessing memory is often critical in surgical evaluation, although difficult to assess in young children and in patients with variable task abilities. While obtaining interpretable data from task-based functional MRI (fMRI) measures is common in compliant and awake patients, it is not known whether functional connectivity MRI (fcMRI) data show equivalent results. If this were the case, it would have substantial clinical and research generalizability. To evaluate this possibility, the authors evaluated the concordance between fMRI and fcMRI data collected in a presurgical epilepsy cohort. Task-based fMRI data for autobiographical memory tasks and resting-state fcMRI data were collected in patients with epilepsy evaluated at Seattle Children's Hospital between 2010 and 2017. To assess memory-related activation and laterality, signal change in task-based measures was computed as a percentage of the average blood oxygen level-dependent signal over the defined regions of interest. An fcMRI data analysis was performed using 1000 Functional Connectomes Project scripts based on Analysis of Functional NeuroImages and FSL (Functional Magnetic Resonance Imaging of the Brain Software Library) software packages. Lateralization indices (LIs) were estimated for activation and connectivity measures. The concordance between these two measures was evaluated using correlation and regression analysis. In this epilepsy cohort studied, the authors observed concordance between fMRI activation and fcMRI connectivity, with an LI regression coefficient of 0.470 (R2 = 0.221, p = 0.00076). Previously published studies have demonstrated fMRI and fcMRI overlap between measures of vision, attention, and language. In the authors' clinical sample, task-based measures of memory and analogous resting-state mapping were similarly linked in pattern and strength. These results support the use of fcMRI methods as a proxy for task-based memory performance in presurgical patients, perhaps including those who are more limited in their behavioral compliance. Future investigations to extend these results will be helpful to explore how the magnitudes of effect are associated with neuropsychological performance and postsurgical behavioral changes.

Optimizing Low-Complexity Analog Mappings for Low-Power Sensors With Energy Scheduling Capabilities

Power consumption is a major challenge for a massive deployment of wireless sensors in Internet of Things (IoT) networks. This article studies the use of analog joint source-channel coding (AJSCC) mappings in low-power sensing schemes. In particular, we propose a novel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">triangular</i> mapping geometry as a low-complexity dimension reduction mapping. The proposed triangular mapping is employed for analog compression of multiple sensor readings into one signal and, thus, limits the need for power-hungry analog-to-digital conversion and processing at the sensing nodes. A comprehensive performance analysis of the proposed triangular mapping in terms of the mean squared error (MSE) performance is provided analytically and verified numerically. The problem of mapping adaptation to different source distributions is also studied. Moreover, the proposed triangular mapping is adopted in an energy scheduling problem in which the sensing nodes schedule their use of the received powers at different time instants and adjust the mapping parameters accordingly with the goal of minimizing the sum distortion at the receiver. We present a fast low-complexity algorithm for optimal energy scheduling and verify its performance in comparison with commercial convex optimization solvers. It is shown that the proposed mapping provides a very good MSE performance compared to the AJSCC benchmarks despite having a much lower complexity circuit implementation.

언어의 생산과 이해, 그리고 뇌의 예측성

The purpose of this paper is to argue that the theories of language production and comprehension adopt the predictive process of the brain. Predictive processes can be found in many domains of language: discourse, syntactic, semantic, and phonological domains. In the discourse domain, the predictive process is found in the conversations that take turns in about 200 milliseconds. Syntactically anomalous structures, e.g., garden-path sentences, elicit a large positive wave (P600), indicating the unexpectedness of the structure. Semantic prediction is exhibited in an evoked response (N400), whose amplitude is modulated when a given word is not congruous in a context. A phonological rule of a mother tongue also creates predictions about phonologically legal forms in pseudowords. The predictive mechanism of the brain is supported by neurological studies: Bar et al. (2007) show the default mode or baseline of the brain areas (Raichle et al. 2001) overlap with the regions activated by tasks that recruit associative processing. This means associative activation equals the process of the brain's baseline state. Bar et al. (2007) propose that continuous generation of predictions is derived from associative processes and analogical mapping of the brain. This study proposes that language production and comprehension theories employ this predictive process of the brain in that prediction seems to affect speech errors as well as implicature recovery.

VOXEL-BASED POINT CLOUD SEGMENTATION AND BUILDING DETECTION

Abstract. In the recent years, point cloud technologies, such as Unmanned Aerial Vehicles (UAV), Terrestrial Laser Scanners (TLS), Aerial Laser Scanners (ALS), let alone Mobile Mapping Systems (MMS), have come into the focus of attention and have been a subject of considerable public concern in mapping. Thanks to these new techniques, experts can survey large areas with sufficient and homogenous accuracy with high resolution. It comes from this that there are several areas where the point clouds can be used. One of the possible applications of point clouds is updating land registry maps. Many countries worldwide face the issue that a significant part of their large-scale land registry maps are outdated and inaccurate. One of these countries is Hungary, where more than eighty percent of digital cadastre maps were digitised using analogous maps in a scale range of 1:1000 – 1:4000. In this paper, a novel processing queue is presented to find the footprints of the building. Our solution is based on primarily well-known algorithms (RANSAC, DBSCAN) implemented in open-source Python packages. An automated flow was developed, composed of simple processing steps, to cut the point cloud into wall and roof segments and vectorise the wall points under roofs into building footprints. The algorithms and Python programs were tested in villages where detached houses are typical. Tests were made on three study areas in Hungary and we achieved well-promising results.