Intuitive Form Research Articles

Decomposed Dissimilarity Measure for Evaluation of Digital Image Denoising

A new approach to the evaluation of digital image denoising algorithms is presented. In the proposed method, the mean absolute error (MAE) is decomposed into three components that reflect the different cases of denoising imperfections. Moreover, aim plots are described, which are designed to be a very clear and intuitive form of presentation of the new decomposed measure. Finally, examples of the application of the decomposed MAE and the aim plots in the evaluation of impulsive noise removal algorithms are presented. The decomposed MAE measure is a hybrid of the image dissimilarity measure and detection performance measures. It provides information about sources of errors such as pixel estimation errors, unnecessary altered pixels, or undetected and uncorrected distorted pixels. It measures the impact of these factors on the overall correction performance. The decomposed MAE is suitable for the evaluation of algorithms that perform a detection of the distortion that affects only a certain fraction of the image pixels.

A family of consistent normally distributed tests for Poissonity

A family of consistent tests, derived from a characterization of the probability generating function, is proposed for assessing Poissonity against a wide class of count distributions, which includes some of the most frequently adopted alternatives to the Poisson distribution. Actually, the family of test statistics is based on the difference between the plug-in estimator of the Poisson cumulative distribution function and the empirical cumulative distribution function. The test statistics have an intuitive and simple form and are asymptotically normally distributed, allowing a straightforward implementation of the test. The finite sample properties of the test are investigated by means of an extensive simulation study. The test shows satisfactory behaviour compared to other tests with known limit distribution.

Analysis on the path of integrating traditional culture into illustration design based on visual communication

Abstract The illustration is a very intuitive form of language expression in modern graphic design. It expresses character scenes, allegorical dialogues, etc. in the form of vivid paintings. Synthesizing the connotation and form of all aspects from literature to art. Illustration art pervades all areas of daily life. It can be said that its formal beauty has become a fashion trend in the decorative art world. Based on the back-propagation algorithm, this paper constructs a BPA-transformation model. Through comparative analysis, it can be seen that illustrations that are not integrated into the theme of Peking Opera have low story inclusion, only 45%. As for the illustrations that incorporate Peking Opera themes, the storyline is highly inclusive, accounting for 68%. Illustrations that incorporate traditional Peking Opera themes are highly realistic, up to 93%. Through comparative analysis, the integration of ink and wash artistic conception is relatively high. Ink illustrations are 40% more innovative.

SimpleMind: An open-source software environment that adds thinking to deep neural networks.

Deep neural networks (DNNs) detect patterns in data and have shown versatility and strong performance in many computer vision applications. However, DNNs alone are susceptible to obvious mistakes that violate simple, common sense concepts and are limited in their ability to use explicit knowledge to guide their search and decision making. While overall DNN performance metrics may be good, these obvious errors, coupled with a lack of explainability, have prevented widespread adoption for crucial tasks such as medical image analysis. The purpose of this paper is to introduce SimpleMind, an open-source software environment for Cognitive AI focused on medical image understanding. It allows creation of a knowledge base that describes expected characteristics and relationships between image objects in an intuitive human-readable form. The knowledge base can then be applied to an input image to recognize and understand its content. SimpleMind brings thinking to DNNs by: (1) providing methods for reasoning with the knowledge base about image content, such as spatial inferencing and conditional reasoning to check DNN outputs; (2) applying process knowledge, in the form of general-purpose software agents, that are dynamically chained together to accomplish image preprocessing, DNN prediction, and result post-processing, and (3) performing automatic co-optimization of all knowledge base parameters to adapt agents to specific problems. SimpleMind enables reasoning on multiple detected objects to ensure consistency, providing cross-checking between DNN outputs. This machine reasoning improves the reliability and trustworthiness of DNNs through an interpretable model and explainable decisions. Proof-of-principle example applications are provided that demonstrate how SimpleMind supports and improves deep neural networks by embedding them within a Cognitive AI environment.

Simple master equations for describing driven systems subject to classical non-Markovian noise

Driven quantum systems subject to non-Markovian noise are typically difficult to model even if the noise is classical. We present a systematic method based on generalized cumulant expansions for deriving a time-local master equation for such systems. This master equation has an intuitive form that directly parallels a standard Lindblad equation, but contains several surprising features: the combination of driving and non-Markovianity results in effective time-dependent dephasing rates that can be negative, and the noise can generate Hamiltonian renormalizations even though it is classical. We analyze in detail the highly relevant case of a Rabi-driven qubit subject to various kinds of non-Markovian noise including 1/f fluctuations, finding an excellent agreement between our master equation and numerically-exact simulations over relevant timescales. The approach outlined here is more accurate than commonly employed phenomenological master equations which ignore the interplay between driving and noise.

Toxicity Impact Assessment of Nitrogen Oxide and Sulfur Dioxide Emissions in China’s Textile Industry With Chemical Footprint Method

Emissions of air pollutants cause adverse impacts on human health and the environment. As typical air pollutants, nitrogen oxide and sulfur dioxide cause acid rain and particulate matter (PM). Significant emissions of nitrogen oxide and sulfur dioxide in the production phases make the textile industry face tremendous challenges. Determining the chemical footprint is an effective method for transforming the potential environmental risks of pollutant emissions into an intuitive form of toxicity. In this study, we adopted the chemical footprint method to assess the toxicity impact of nitrogen oxide and sulfur dioxide emissions from China’s textile industry. The results indicate that the chemical footprint of nitrogen oxide and sulfur dioxide in China’s textile industry showed a significant decreasing trend from 2001 to 2019, and the chemical footprint of nitrogen oxide was about 11 times higher than that of sulfur dioxide. Among the three sub-sectors of China’s textile industry, the textile manufacturing sector had the highest chemical footprint, accounting for 57.1–65.7% of the total chemical footprint. The remaining chemical footprint is allocated to the chemical fibers manufacturing sector, and the textile wearing apparel, footwear, and cap manufacturing sector. The chemical footprint intensity of China’s textile industry also showed a decreasing trend from 2006 to 2015, and the chemical footprint intensity of the three sub-sectors was in the order of the chemical fibers manufacturing sector, the textile manufacturing sector, and the textile wearing apparel, footwear, and cap manufacturing sector.

Rapid Three-Dimensional Reconstruction of Underwater Defective Pile Based on Two-Dimensional Images Obtained Using Mechanically Scanned Imaging Sonar

Three-dimensional (3-D) reconstruction based on sonar imaging is an intuitive and comprehensible form for describing an underwater defective pile. Most existing 3-D reconstruction methods are inefficient as they require the extraction of numerous feature points from many sonar images. A rapid 3-D reconstruction method for underwater defective piles based on two-dimensional (2-D) images obtained using mechanically scanned imaging sonar (MSIS) is proposed herein. First, the correspondences between the geometric features of MSIS images and actual defects are established based on the mapping relationship between actual object and MSIS image. Subsequently, no more than three feature points are extracted from 2-D MSIS images to recognize the contour segments. The contour segments are assembled into the entire cross section and then into the entire defective pile. The applicability of the proposed method is verified via a 3-D reconstruction for a scaled-down pile with multiple defect distributions.

Older adults' experience with virtual conversational agents for health data collection.

Virtual conversational agents (i.e., chatbots) are an intuitive form of data collection. Understanding older adults' experiences with chatbots could help identify their usability needs. This quality improvement study evaluated older adults' experiences with a chatbot for health data collection. A secondary goal was to understand how perceptions differed based on length of chatbot forms. After a demographic survey, participants (≥60 years) completed either a short (21 questions), moderate (30 questions), or long (66 questions) chatbot form. Perceived ease-of-use, usefulness, usability, likelihood to recommend, and cognitive load were measured post-test. Qualitative and quantitative analyses were used. A total of 260 participants reported on usability and satisfaction metrics including perceived ease-of-use (5.8/7), usefulness (4.7/7), usability (5.4/7), and likelihood to recommend (Net Promoter Score = 0). Cognitive load (12.3/100) was low. There was a statistically significant difference in perceived usefulness between groups, with a significantly higher mean perceived usefulness for Group 1 than Group 3. No other group differences were observed. The chatbot was perceived as quick, easy, and pleasant with concerns about technical issues, privacy, and security. Participants provided suggestions to enhance progress tracking, edit responses, improve readability, and have options to ask questions. Older adults found the chatbot to be easy, useful, and usable. The chatbot required low cognitive load demonstrating it could be an enjoyable health data collection tool for older adults. These results will inform the development of a health data collection chatbot technology.

Teacher's Efforts to Improve Elementary Students' Understanding of the Value of Truth in the Qur'an

Teaching the truth is a principal matter that must be given to children from an elementary age. Because, children will easily actualize the value of truth if it is imprinted from the foundation. This study aims to describe the efforts of teachers in increasing the understanding of elementary students aged 6-12 years about the concepts of Islamic teachings including bayani, 'irfani, and burhani. Of course, this theory of truth will be compared between the truth from Western and Islamic perspectives. This research uses a qualitative approach with the method of literature study. Obtaining and analyzing data comes from literature review materials in the form of books, scientific articles, proceedings, and final assignments (thesis, thesis, dissertation). Research data analysis materials were obtained from credible websites such as Google Scholar and Sinta. The results of this study concluded that the teacher's efforts to increase elementary-age students' understanding of bayani, 'irfani and burhani as basic concepts of truth from an Islamic perspective were carried out well. This is based on (1) mainstreaming truth based on revelation/al-Qur'an (the word of Allah swt.) as the highest authority in measuring truth. Then (2) logic in the form of reason, empirical and intuition becomes a supporting factor for students in understanding the truth of Divine words.

Identifying COVID-19 Vaccine Deserts and Ways to Reduce Them: A Digital Tool to Support Public Health Decision-Making.

A private-academic partnership built the Vaccine Equity Planner (VEP) to help decision-makers improve geographic access to COVID-19 vaccinations across the United States by identifying vaccine deserts and facilities that could fill those deserts. The VEP presented complex, updated data in an intuitive form during a rapidly changing pandemic situation. The persistence of vaccine deserts in every state as COVID-19 booster recommendations develop suggests that vaccine delivery can be improved. Underresourced public health systems benefit from tools providing real-time, accurate, actionable data. (Am J Public Health. 2023;113(4):363-367. https://doi.org/10.2105/AJPH.2022.307198).

Holistic Cognitive Style, Chinese Culture, and the Sinification of Buddhism

According to many experiments in cross-cultural psychology, East Asians exhibit holistic cognitive style typified by use of resemblance heuristics, field dependence, external sources of causation, intuitive forms of reasoning, and interdependent forms of social thinking. Holistic cognitive style contrasts with analytic cognitive style, which is common to Westerners. Section 1 presents information on the background of Buddhism’s entry into and treatment by China. Section 2 discusses experimental evidence for the representation of holistic cognitive style in contemporary East Asians. Section 3 presents preliminary evidence for the interaction between holistic cognitive style and the history of ideas in China at large. Section 4 analyzes two discussions of the same philosophical problem conducted by Chinese Buddhist philosopher Fazang and Indian Vedic philosopher Shankara. It is provisionally argued that the interpretive strategies displayed by Fazang interact with several components of holistic cognitive style, in contrast with Shankara. Implications are discussed.

Filsafat Kenabian Ibnu Sina dan Murtadha Muthahhari

The purpose of this study is to discuss the philosophy of prophethood according to Ibn Sina and Murtadha Mutahhari. The method used in this research is the library method with a qualitative approach. Sources of data used in this study are primary data in the form of books written directly by Ibn Sina and Murtadha Mutahhari, and secondary data in the form of books, journals, documents, and others related to the object under study. The results of this study are differences of opinion regarding the concept of prophethood, according to Ibn Sina, humans are humans who have obtained divine power in the form of divine intuition given by God to the human He chooses. Meanwhile, according to Murtadha Mutahhari, the Prophet is a human being chosen by God to guide mankind and every Prophet has his characteristics. Among the characteristics of the Prophet are miracles, infallibility, guidance from Allah, noble goals, constructive, striving, and possessing human values, and having revelations in the form of holy books. This research is expected to have a contribution both theoretically and practically. Theoretically, this research is expected to provide insight into the treasures of Islamic scholarship, while practically it is expected to provide benefits for research readers.

Evolution and Influencing Factors of Landscape Pattern in the Yellow River Basin (Henan Section) Due to Land Use Changes

The temporal and spatial evolution of landscape pattern is the most intuitive form of land use transition. Analyzing the change of landscape pattern and its driving factors is of great significance to land use management and water quality protection in the basin. Based on the land use data obtained from the remote sensing image interpretation of the Yellow River Basin (Henan section) in 1990, 2000, 2010, and 2020, the landscape pattern evolution characteristics of the Yellow River Basin (Henan section) were quantitatively studied using the methods of multi-angle land use transfer matrix, land use information atlas, and landscape pattern index, and the influencing factors of landscape pattern evolution of the Yellow River Basin (Henan section) were revealed using the geographic detectors (a new statistical method to measure the explanatory power of independent variables to dependent variables mainly by analyzing the overall differences among various types of geographical spaces). The results show that: (1) From 1990 to 2020, the mutual transformation of land use types in the Yellow River Basin (Henan section) was frequent, and the transformation tracks were diversified. Among them, the outflow behavior of land use types is mainly manifested in the transformation from cultivated land to construction land, and the inflow behavior of land use types is mainly manifested in the transformation from grassland and water to cultivated land. (2) In the information map of land use change in the Yellow River Basin (Henan section) from 1990 to 2020, the stable type had the widest distribution range, accounting for 94.60% of the total area of the study area, with two main change patterns: “cultivated land-cultivated land-cultivated land-cultivated land” and “woodland-woodland-woodland-woodland”, which indicates that the landscape pattern of the basin dominated by cultivated land and woodland has not changed fundamentally. The four land use change structure types, repeated change, early change, intermediate change and continuous change, account for a relatively small proportion and are concentrated in the vicinity of the Yellow River. (3) At the landscape level, the watershed generally shows the trend of decreasing landscape fragmentation, increasing landscape heterogeneity and constantly balancing landscape patch types. At the level of patch type, the landscape dominance of cultivated land decreases, while that of construction land increases. The occupation of construction land is the main reason for the fragmentation and homogenization of cultivated land. (4) From the perspective of landscape scale and patch type scale, through the geographical exploration of various natural factors and socio-economic factors that potentially affect the landscape pattern evolution, it is found that the spatial differences of natural factors such as slope, elevation, temperature, and precipitation can better reflect the spatial heterogeneity of the landscape pattern in the Yellow River Basin (Henan section) than those of socio-economic factors such as GDP and population density, and the interaction of any two driving factors has a greater influence on the spatial distribution characteristics of landscape pattern than any single factor, indicating that the formation of spatial heterogeneity in the Yellow River Basin (Henan section) is the result of the interaction of various influencing factors. The results of this study can provide ideas for exploring the trend and influencing mechanism of landscape pattern change in the basin, and have important reference significance for ecological environment management, ecosystem protection, and land use planning in the Yellow River Basin (Henan section).

TBRm: A Time Representation Method for Industrial Knowledge Graph

With the development of the artificial intelligence industry, Knowledge Graph (KG), as a concise and intuitive data presentation form, has received extensive attention and research from both academia and industry in recent years. At the same time, developments in the Internet of Things (IoT) have empowered modern industries to implement large-scale IoT ecosystems, such as the Industrial Internet of Things (IIoT). Using knowledge graphs (KG) to process data from the Industrial Internet of Things (IIoT) is a research field worthy of attention, but most of the researched knowledge graph technologies are mainly concentrated in the field of static knowledge graphs, which are composed of triples. In fact, many graphs also contain some dynamic information, such as time changes at points and time changes at edges; such knowledge graphs are called Temporal Knowledge Graphs (TKGs). We consider the temporal knowledge graph based on the projection and change of space. In order to combine the temporal information, we propose a new representation of the temporal knowledge graph, namely TBRm, which increases the temporal dimension of the translational distance model and utilizes relational predicates in time add representation in time dimension. We evaluate the proposed method on knowledge graph completion tasks using four benchmark datasets. Experiments demonstrate the effectiveness of TBRm representation in the temporal dimension. At the same time, it is also practiced on a network security data set of the Industrial Internet of Things. The practical results prove that the TBRm method can achieve good performance in terms of the degree of harm to IIoT network security.

An intuitive form of the energy functional for resistive plasma perturbations

The energy functional of ideal magnetohydrodynamics (MHD) is extended to the regime of finite resistivity and transformed into an intuitive form, which separates pressure-gradient, current-density drive and stabilising phenomena, analogously to the ideal version of the functional derived by Greene and Johnson (Plasma Phys., vol. 10, issue 8, 1968, pp. 729–745). The resulting resistive energy functional is not in the form of a solvable eigenvalue problem but is intended to analyse the energetic composition of eigenfunctions which were calculated in advance by solving the MHD equations. The new resistive energy functional provides information on the different energetic drives and stabilising phenomena of an eigenfunction. The new energy functional has been implemented in the CASTOR3D code in general 3D curvilinear coordinates and successfully validated across three different coordinate systems for a numerical test case.

Hermann Cohen’s logic of the pure knowledge as a philosophy of science

The connection of Hermann Сohen’s “The Logic of Pure Knowledge” with the revolutionary transformations in physics and mathematics at the end of the 19th century is shown. Сohen criticised Kant’s answer to the question “How is mathematics possible”? If Kant refers to a priori forms of pure intuition, Сohen sees in it a restriction of freedom of mathematical thinking by limits of intuition. It has been shown that Cohen's position is in accordance with the main development of mathematics in the last decades of the 19th century, in particular, with K. Weierstrass’ striving to get rid of geometrical or mechanical images and intuitions in the mathematical analysis. Cohen was also well informed about the latest ideas in physics of his time. They are also discussed in “The Logic of Pure Knowledge.” The revolutionary spirit of physics and mathematics was appealing to Cohen, and he felt a corresponding enthusiasm for it. The ongoing scientific revolution is consonant with Cohen’s assertion that the foundations of science are hypotheses. The purity of pure thinking does not guarantee the correctness of any of its constructions. Each step in the development of science requires a critique of existing notions. The development of knowledge from the naive to the critical one shows a movement from a picture of the world as a set of stable things to a picture of continuous movement and change, where change is more important than what changes. Cohen sees such a development in an evolution of the concept of substance in modern physics and he welcomes the replacement of material substance by energy, seeing this movement as a confirmation of critical idealism. Finally, it is discussed whether we can speak of the actuality of Cohen’s logic of pure knowledge.

Towards a Unity of Theoretical and Practical Reason: On the Constitutive Significance of the Transcendental Dialectic

AbstractThe article focuses on re-evaluating Kant’s Transcendental Dialectic by initially highlighting its seemingly negative function within theCritique of Pure Reasonas a mere regulative form for cognition and experience. The Dialectic, however, does not only have such a negative-regulative function but also its very own positive and founding character for cognition that even is present in the supposedly most immediate forms of intuition. In exploring this positive side of the Transcendental Dialectic it becomes clear that it manifests itself as a bridge between the so-called theoretical and practical reason inasmuch as it fills in their gap within Kant’s philosophy. From the practical side, the Dialectic is manifest as an action full of purposiveness, maxims, and imperatives within cognition, from a theoretical side it assumes the form of syllogistic inference, which is the adequate and acting theoretical form of practical reason. Therefore, the unity of reason is shown in presenting its inner gap as a dialectical misunderstanding that Kant not only highlights in the Transcendental Dialectic but also tends to leave unsolved mostly. Nevertheless, the Dialectic can be shown as thea priorisynthetic act of unifying reason, if investigated in the context of Kant’s complete critical endeavour.

Simulating fusion reactions from Coulomb explosions within a transport approach

We have studied nuclear fusion reactions from the Coulomb explosion of deuterium clusters induced by high-intensity laser beams within a transport approach. By incorporating the D+D $\rightarrow$ n + He$^3$ channel as inelastic collisions based on the stochastic method, we have calibrated the neutron yield from the simulation in a box system with that from the reaction rate equation. After justifying the Coulomb explosion of a single cluster by comparing results with available theoretical limits, we have then investigated the dynamics from Coulomb explosions of systems with different cluster numbers and different deuteron numbers in clusters. We find that the kinetic energy spectrum of deuterons at the final stage is different from that when neutrons are abundantly produced, corresponding to significantly different reaction rates. We also extrapolate the neutron yield result from small systems to large systems based on an intuitive parameterized form and compare with the available experimental result. The present framework can be extended by incorporating more channels, and useful for further studies of nuclear fusion reactions in plasma systems at higher energies reached in more recent experiments.

Application of Deep Learning in College Physical Education Design under Flipped Classroom.

With the development of information technology, teaching reform has also undergone major changes. The traditional college physical education teaching method cannot meet the needs of the majority of students, and the physical education teaching mode continues to be reformed. Microcourse is the most intuitive form of deep integration of information technology and physical education. From the perspective of the flipped classroom (FC), the physical education model has gradually changed from teacher centered to student centered. Deep learning (DL) emphasizes that learners have the ability to actively construct knowledge, effectively transfer knowledge, and solve real problems. This design applies DL and convolutional neural network to the teaching design of physical gymnastics in colleges and universities. The application of the DL teaching model based on FC in the microcourse teaching of gymnastics in colleges and universities is studied and evaluated. The results show that the current utilization of microcourse teaching resources is too low. Interest-oriented teaching microcourses cannot improve students' interests. The proportion of students who are interested is relatively small, and more than 50% of students are not interested. Teachers generally believe that the current gymnastics microcourse needs further optimization and improvement. The poor quality of microvideos and the lack of supervision and reward mechanism in the course are the main reasons for the insufficient students' interest. The complexity of the videos and the liveliness of the discussions are the main problems of low resource utilization. The student's interest in learning is greatly improved after the application of the designed model, and the proportion increases to 82.4%. The effect on ordinary college students is the most obvious, and the effect of microvideo learning has been significantly promoted. Design mode has the most obvious improvement in improving learning efficiency and autonomous learning ability. The improvement of learning ability has increased from 18% to 72%, and the improvement of learning efficiency has increased from 39% to 82%. Meanwhile, students' interest in learning is stimulated, and the utilization of resources is improved.

Ontologi, Epistimologi, dan Aksiologi dalam Perspektif Filsafat Ilmu Dakwah di Era Komunikasi Digital

Ontology, Epistemology, and Axiology in the Philosophical Perspective of Da'wah in the Age of Digital Communication. The development of the era of globalization is forcing people to be technology literate. Coupled with the Covid-19 pandemic, forcing people to carry out digital communication for daily needs, including spiritual needs. This is what underlies the da'i to be able to transform da'wah into the digital realm. But before that, it is necessary for the da'i to explore the philosophy of da'wah in order to create valuable content in communicating in the digital realm. This paper aims to find out more deeply about ontology epistemology and axiology in order to better know the benefits of da'wah. This paper uses a qualitative approach with a literature study method (library review), namely the technique of collecting writings, readings and other literature, both physical and digital specifically, and then analyzing the content of the study based on the focus of the problems discussed. The results showed 1) ontology in the form of the essence of the existence of da'wah in communication between da'i and mad'u. 2) epistemology in Islamic da'wah, namely bayani epistemology, in the form of sources used in preaching on social media, irfani epistemology, in the form of intuition from da'i and burhani epistemology, in the form of intellectual activity. 3) In understanding axiology, the preacher must first master his knowledge. While mad'u must be selective in choosing their da'i, Da'i and mad'u both must realize that digital users are very diverse. When the da'i does da'wah, he must be ready to face all kinds of mad'u. for that it is necessary to create a dialogue space in digital.