General Transformation Research Articles

A semi-analytic method to solve nonlinear differential equations with arbitrary order

In this paper, we describe the new Adomian Decomposition General Transform Method (ADGTM). Further, the efficacy of the method is proved by applying it to well-known equations, such as the logistic equation, Emden–Lane–Fowler equation, Gardner equation, and Cahn–Hilliard equation, in fractional order to study the intrinsic behavior. We compare the results with other well-known methods like RPSM, and q-HATM to prove the reliability and accuracy of the proposed method. For the selected applications, we frame 2D and 3D graphs to explain how the fractional-order derivative affects the behavior of the obtained solutions.

A general geometric transformation model for line-scan image registration

A reasonable geometric transformation model is the key to image registration. When the relative motion direction between the line-scan camera and the object is strictly parallel to the planar object, it is possible to align the image by using the eight-parameter geometric transformation model of the line-scan image. However, it will be invalid when the relative motion direction is arbitrary. Therefore, a new general geometric transformation model of line-scan images is proposed for line-scan image registration in this paper. Considering the different initial poses and motion directions of the line-scan camera, the proposed model is established based on the imaging model of the line-scan camera. In order to acquire line-scan images to verify the proposed model, a line-scan image acquisition system was built. The method based on feature points is used to register the line-scan images. The experimental results show that the proposed geometric transformation model can align the line-scan image collected under arbitrary relative motion direction, not just the parallel case. Besides, the statistical errors of the image feature point coordinates are the best performance after registration. The accuracy of the registration results is better than that of other existing geometric transformation models, which verifies the correctness and generality of the geometric transformation model of the line-scan camera proposed in this paper.

A Theory of Merge-and-Shrink for Stochastic Shortest Path Problems

The merge-and-shrink framework is a powerful tool to construct state space abstractions based on factored representations. One of its core applications in classical planning is the construction of admissible abstraction heuristics. In this paper, we develop a compositional theory of merge-and-shrink in the context of probabilistic planning, focusing on stochastic shortest path problems (SSPs). As the basis for this development, we contribute a novel factored state space model for SSPs. We show how general transformations, including abstractions, can be formulated on this model to derive admissible and/or perfect heuristics. To formalize the merge-and-shrink framework for SSPs, we transfer the fundamental merge-and-shrink transformations from the classical setting: shrinking, merging, and label reduction. We analyze the formal properties of these transformations in detail and show how the conditions under which shrinking and label reduction lead to perfect heuristics can be extended to the SSP setting.

Hierarchical Interactive Multimodal Transformer for Aspect-Based Multimodal Sentiment Analysis

Aspect-based multimodal sentiment analysis (ABMSA) aims to determine the sentiment polarities of each aspect or entity mentioned in a multimodal post or review. Previous studies to ABMSA can be summarized into two subtasks: aspect-term based multimodal sentiment classification (ATMSC) and aspect-category based multimodal sentiment classification (ACMSC). However, these existing studies have three shortcomings: (1) ignoring the object-level semantics in images; (2) primarily focusing on aspect-text and aspect-image interactions; (3) failing to consider the semantic gap between text and image representations. To tackle these issues, we propose a general Hierarchical Interactive Multimodal Transformer (HIMT) model for ABMSA. Specifically, we extract salient features with semantic concepts from images via an object detection method, and then propose a hierarchical interaction module to first model the aspect-text and aspect-image interactions, followed by capturing the text-image interactions. Moreover, an auxiliary reconstruction module is devised to largely eliminate the semantic gap between text and image representations. Experimental results show that our HIMT model significantly outperforms the state-of-the-art methods on two benchmarks for ATMSC and one benchmark for ACMSC.

THE RETURNABILITY OF INTEGRALS OF CONDITIONALLY PERIODIC FUNCTIONS

A range of issues related to the returnability of integrals of conditionally periodic functions with zero mean value is discussed. In the case of smooth functions on the torus, the returnability of integrals obviously holds for all initial phases. A new observation is that for almost all initial phases, the returnability property simultaneously holds not only for integrals, but also for phase points on the torus. Moreover, this result is also valid in the case where the corresponding functions on the torus are only continuous. These observations are transferred to the general case ergodic transformations of compact metric spaces with Carateodori measure.

A Performance-Driven Economic Analysis of a LSTM Neural Network Used for Predicting Building Energy Consumption

Abstract The energy sector occupies a central role in European policy regarding the sustainability and climate change ambitions. This economic sector gained even more importance in the context of a growing energy demand and the threat to energy security and stability in Eastern Europe. The administrative changes from the past years and the shift towards renewable energy sources created the momentum for a general transformation of the energy sector. The research in this field is much needed in order to find the best solutions to predict the energy demand and how to efficiently satisfy it. The purpose of this paper is to assess the economic impact of using artificial neural networks on a dataset that captures information from one building about the energy consumption. The network follows a Long – Short Term Memory architecture and it is characterized by a Root Mean Squared Propagation function for optimization. The analysis consists in the comparison of the performance of three activation functions: Rectified Linear Unit, Sigmoid and Tanh. The results complement the existing research in the field by focusing on the prediction of energy consumption at building level. The case study indicates that the Rectified Linear Unit and Tanh functions are more appropriate than Sigmoid to be used in an LSTM network applied on energy consumption data. The former performs better in terms of accuracy, measured by the Mean Absolute Value, and has similar computational costs to Tanh, with a slightly larger value for training time.

The Changing Trends and International Comparison of Chinese Women's Fertility Pattern under Low Fertility Level

Using data from Chinese national population censuses and 1% population sampling surveys from 2000 to 2020, by analyzing the age-specific fertility contribution rate curve, the Mean age at birth, the Standard deviation in Mean age at birth in different years, and comparing with the transformation process of fertility pattern in developed countries, this paper analyses the changing trends in Chinese women's fertility pattern under low fertility level. The results find that under low fertility level, the growth rate of Chinese women's Mean age at birth turns from fast to slow, the dispersion of fertility pattern rises first and then falls, and the distribution of child-bearing age is overall postponed. Compared with developed countries, the transformation of Chinese women's fertility pattern started late, changed quickly, and fluctuated greatly, from significantly lagging behind the general transformation process of fertility pattern in developed countries to rapidly approaching the average level of fertility pattern in developed countries. The adjustment of Chinese fertility policy has had a significant impact on the fertility pattern, leading to a turning point in the changing trends of the fertility pattern after 2010. With the development of economy and society and the continuous adjustment of fertility policy, the future fertility pattern of Chinese women may show trends that women's child-bearing age will continue to rise, but the dispersion of fertility pattern will slightly decline in fluctuations.

Structural investigation of lithium borate glasses by Raman spectroscopy: Quantitative evaluation of structural units and its correlation with density

Lithium borate glass is a widely studied system, mainly due to its good ionic conductivity, thermal conductivity and thermoluminescence properties. The properties of lithium borate glass are determined by its structure, and the change of microstructure unit has great influence on its properties. In this work, the xLi2O⋅(1-x) B2O3 (0.1 ≤ x ≤ 0.48) glass was studied by Raman spectroscopy combined with peaks fitting and density analysis. Through quantitative analysis of Raman spectrum, the change in trend of each structural unit as well as the change of the tetracoordinated boron content (N4) were obtained with the increase of Li2O content. Especially, a more detailed assignment and general transformation mechanism of structural units were presented, and the common inflection points of properties (mass density, molar volume, etc.) and structural units content changes were found. The correlation between the properties (mass density, atomic density and molar volume) and the basic structural units (BØ3, BØ2O− and BØ4−) of the lithium borate glass was established by the genetic function approximation algorithm (GFA). The study on the structural units in xLi2O⋅(1-x) B2O3 (0 ≤ x ≤ 0.48) glass network and the mutual transformation mechanism between each structural unit is helpful to explore the effects on macroscopic properties as the structural units change.

Modification of The Oil Cooler to Avoid Oil Leaking in Generator Transformer PLTU Labuan “Moderator”

The Main Generator Transformer for PLTU Labuan is a transformer with a power capacity of 350 MVA and a cooling system of 6 pcs OFAF (Oil Force Air Force) type. During operation, a disturbance to the Main Generator Transformer (GT) was caused by an oil cooler leak. This is caused by the corrosive expand tube caused by the constituent material consisting of 2 different types of materials. The oil leak caused environmental pollution, decreased oil level, and increased winding temperature and oil temperature on GT. During the decade of operation of the PLTU Labuan, GT oil cooler leaks almost always occur every year, both in unit 1 and unit 2. To anticipate this, we made modifications to the end tube design by changing the type of material on the expanded tube from initially using iron to aluminum such as tube material outside the expanded position. The next design change is to increase the length of the end tube which is equipped with the knock and glue with an expansion strength above normal operating temperature which makes the end tube more reliable by increasing the surface area attached to the body oil cooler. In addition to making changes to the design, this modification reuses used oil coolers that have good tube quality so that they can be reused with more reliable quality. By making these modifications, it can increase the readiness of generating unit production (EAF) by 3.33% in one MO event due to the replacement of the oil cooler generator transformer and lower maintenance costs for the required transformer oil cooler. The modified Oil Cooler was installed during the Maintenance Outage in Unit 1 and Overhaul unit 2 in 2021 and is still operating well for 20 months of operation.

Precipitation kinetics of niobium carbide (NbC) during homogenization heat treatment of additively manufactured inconel 718 superalloy

High cooling rate of the laser powder bed fusion (L-PBF) additive manufacturing can suppress the formation of niobium carbide (NbC) phase in the fabricated Inconel 718 nickel-based superalloy parts. However, it might precipitate during elevated temperature exposure. Accordingly, in the present work, the precipitation kinetics of the NbC carbide was investigated during homogenization heat treatment at temperatures in the range of 1000–1150 °C for soaking times of 15 min to 10 h. It was observed that increasing the homogenization temperature leads to the faster kinetics of NbC formation. The precipitation kinetics was modeled by the general phase transformation kinetics formula (based on the transformed fraction of 0.5 or 50%, t0.5) and Johnson–Mehl–Avrami–Kolmogorov (JMAK) analysis, resulting in the precipitation activation energies of 159.2 and 157.4 kJ/mol, respectively. It was concluded that the diffusion of both C and Nb atoms in the Ni matrix are the underlying mechanisms for the NbC carbide formation during homogenization heat treatment. The relationship of 1/t0.5∝exp(0.0097T) was also obtained for the precipitation rate as a function of temperature.

Risk, Vulnerability, and Resilience in Agriculture and Their Impact on Sustainable Rural Economy Development: A Case Study of Greece

Promoting rural development is essential for the general economic transformation of people, hence requiring great attention from different government systems. This study assessed the risk, vulnerability, and resilience of agriculture, as well as its impact on sustainable rural economy development, using Greece as the case study. The study employed a quantitative research approach based on a cross-sectional survey design. A survey questionnaire was used to gather data from 304 Greek farmers. The results show that, although farmers are no longer at risk of being short of food and clothing in Greece, they still face different challenges associated with climate change or low productivity, and this can greatly affect yields if not given great attention. The study showed that increasing farmers’ resilience and the efficacy of risk response are both essential tactics to use in order to effectively combat threats to the residential environment. However, the results show that vulnerability in agriculture has a significant negative influence on rural development. This research demonstrates how the development of a new, beautiful nation must involve improvements to and a guarantee of the safety of farmers’ rural living environments, in order to reduce the impacts of risk and vulnerability, as well as strengthen the nation’s resilience. The results show that, in rural governance, the general preservation of living conditions is not only one of farmers’ top priorities, but is also a crucial factor in enhancing their ability to deal with risks, and is the only route to real rural development. Governments should design their social protection programs to enhance agricultural production, safeguard the lives of the most vulnerable populations, strengthen their resilience, and achieve the broadest possible rural transformation.

Band unfolding with a general transformation matrix: From code implementation to interpretation of photoemission spectra

Unfolding of a supercell band structure into a primitive Brillouin zone is important for understanding implications of structural distortions, disorder, defects, and solid solutions on materials electronic structure. The necessity of band unfolding is also recognized in the interpretation of angle-resolved photoemission spectroscopy (ARPES) measurements. We describe an extension of the fold2Bloch package by implementing an arbitrary transformation matrix used to establish a relation between the primitive cell and supercell. This development allows us to overcome limitations of supercells constructed exclusively by scaling of primitive cell lattice vectors. It becomes possible to transform between primitive and conventional cells as well as include rotations. The fold2Bloch is publicly available from a GitHub repository as a FORTRAN code. It interfaces with the all-electron full-potential WIEN2k and the pseudopotential VASP density functional theory packages. The fold2Bloch is supplemented by additional pre- and post-processing utilities that aid in generating k points in the supercell (such that they later fall onto a desired path in the primitive Brillouin zone after unfolding) and plotting the unfolded band structure. We selected ▪ as an illustrative example and, for the first time, present its properly unfolded band structure in direct comparison with ARPES measurements. In addition, critical importance of the band unfolding for interpretation of ▪ ARPES data is illustrated and discussed as a perspective.

Inhomogeneity Axiom and Generalized Energy Conservation and Transformation Law

Inhomogeneity Axiom and Generalized Energy Conservation and Transformation Law

Finite-Time Discontinuous Control of Nonholonomic Chained-Form Systems

A finite-time discontinuous control method is proposed for controlling nonholonomic chained-form systems. Through a general discontinuous coordinate transformation, the nonholonomic system is transformed into two decoupled subsystems that are independently stabilized with control laws. Sufficient conditions for the existence of decoupled subsystems and finite-time convergence of system states are given. Furthermore, the finite-time discontinuous control laws are proposed to ensure that the system states reach the equilibrium in a finite time. Simulation results are presented to demonstrate the effectiveness and advantages of the proposed approach.

Noninertial Proper Motions of the Minkowski Metric, the Sagnac Effect, and the Twin Paradox

The Sagnac effect and related twin paradox with a rotating disc are analyzed. It may seem that the special theory of relativity gives an easy and exhaustive treatment here. However, such consideration is deceptive since the principles of special relativity are originally established only for the inertial frames of reference, whereas the Sagnac experiment and the twin paradox exist in a noninertial one. We introduce an additional group of motions related to the rotation with uniform angular speed and show that these transformations leave the Minkowski metric invariant. Thus, we can give a firm mathematical ground to a usual easy consideration of the Sagnac effect. It should be noted that the presented result is true for a special case of motions; general coordinate transformations into accelerating frames of reference do not preserve the metric.

Series of Convergence Rate −1/4 Containing Harmonic Numbers

Two general transformations for hypergeometric series are examined by means of the coefficient extraction method. Several interesting closed formulae are shown for infinite series containing harmonic numbers and binomial/multinomial coefficients. Among them, three conjectured identities due to Z.-W. Sun are also confirmed.

Exploring Transformer and Graph Convolutional Networks for Human Mobility Modeling

The estimation of human mobility patterns is essential for many components of developed societies, including the planning and management of urbanization, pollution, and disease spread. One important type of mobility estimator is the next-place predictors, which use previous mobility observations to anticipate an individual’s subsequent location. So far, such predictors have not yet made use of the latest advancements in artificial intelligence methods, such as General Purpose Transformers (GPT) and Graph Convolutional Networks (GCNs), which have already achieved outstanding results in image analysis and natural language processing. This study explores the use of GPT- and GCN-based models for next-place prediction. We developed the models based on more general time series forecasting architectures and evaluated them using two sparse datasets (based on check-ins) and one dense dataset (based on continuous GPS data). The experiments showed that GPT-based models slightly outperformed the GCN-based models with a difference in accuracy of 1.0 to 3.2 percentage points (p.p.). Furthermore, Flashback-LSTM—a state-of-the-art model specifically designed for next-place prediction on sparse datasets—slightly outperformed the GPT-based and GCN-based models on the sparse datasets (1.0 to 3.5 p.p. difference in accuracy). However, all three approaches performed similarly on the dense dataset. Given that future use cases will likely involve dense datasets provided by GPS-enabled, always-connected devices (e.g., smartphones), the slight advantage of Flashback on the sparse datasets may become increasingly irrelevant. Given that the performance of the relatively unexplored GPT- and GCN-based solutions was on par with state-of-the-art mobility prediction models, we see a significant potential for them to soon surpass today’s state-of-the-art approaches.

Critical exploration of AI-driven HRM to build up organizational capabilities

PurposeHuman resource management (HRM) processes are increasingly artificial intelligence (AI)-driven, and HRM supports the general digital transformation of companies' viable competitiveness. This paper points out possible positive and negative effects on HRM, workplaces and workers’ organizations along the HR processes and its potential for competitive advantage in regard to managerial decisions on AI implementation regarding augmentation and automation of work.Design/methodology/approachA systematic literature review that includes 62 international journals across different disciplines and contains top-tier academic and German practitioner journals was conducted. The literature analysis applies the resource-based view (RBV) as a lens through which to explore AI-driven HRM as a potential source of organizational capabilities.FindingsThe analysis shows four ambiguities for AI-driven HRM that might support sustainable company development or might prevent AI application: job design, transparency, performance and data ambiguity. A limited scholarly discussion with very few empirical studies can be stated. To date, research has mainly focused on HRM in general, recruiting and HR analytics in particular.Research limitations/implicationsThe four ambiguities' context-specific potential for capability building in firms is indicated, and research avenues are developed.Originality/valueThis paper critically explores AI-driven HRM and structures context-specific potential for capability building along four ambiguities that must be addressed by HRM to strategically contribute to an organization's competitive advantage.

Some Properties and Applications of a New General Triple Integral Transform “Gamar Transform’’

The goal of this study is to suggest a new general triple integral transform known as Gamar transform. Next, we compare the current transform to a number of existing triple integral transforms such as those by Laplace, Sumudu, Elzaki, Aboodh, and Laplace–Aboodh–Sumudu. We outline its essential properties and prove some important results, including linearity property, existence theorem, triple convolution theorem, and derivatives properties. Moreover, the proposed new transform is applied to solve some partial differential equations (PDEs) such as Laplace, Mboctara, and Wave equations. The capacity of general triple integral transforms to change PDEs into simple algebraic equations is demonstrated.

А New Personality for Digital Technologies: New Challenges in Higher Education

Introduction. The article highlights the problems arising in the field of higher education in connection with the introduction of digital technologies in the practice of teaching. Currently, such concepts as information space, information society, digitalization and the like are constant and ubiquitous in cultural and business environment. These terms describe the current stage of development of society, its technological state, the ways of its further evolution, as well as the consciousness and attitude of the modern individual. Digitalization of the educational process as an advanced effective tool provides the teacher with new means of improving the quality of learning through visualization and updating of the studied material, a huge selection of additional resources, as well as encourages the student’s desire for self-education.Materials and methods. In the course of writing this article, the following methods of scientific research were used: analysis, synthesis, abstraction and philosophical generalization, as well as induction and testing. When analyzing the main directions of the use of digital methods in education, a characteristic of the new reality of higher school work is given, the advantages and disadvantages of the formation of a digital educational environment are highlighted.Results of the study. The author comes to the conclusion that the widespread introduction of digital methods leads to a general transformation not only of the industrial and business environment, but also to significant changes in the worldview of new generations, as well as their approaches to obtaining information, its analysis and evaluation, as well as to communication challenges.Discussion and conclusions. The paper concludes, that digital learning, with all its undeniable advantages and wide opportunities, cannot be considered an equivalent replacement for traditional forms of education due to largely limited communication between teachers and students. Other serious challenges of the modern digital society in terms of the educational process are cardinal changes in the thinking of young people due to the difference in their everyday life experience from the routines of previous “predigital” generations. Thus, the optimal solution to the problem of adapting higher education to new realities is an effective combination of the latest resources and techniques with a traditional approach to the process of forming a new personality of the 21st century.