Reviewerly/exHarmony huggingface dataset:
Gegenbauer Parameter Effect on Gegenbauer Wavelet Solutions of Lane-Emden Equations

In this study we aim to solve Lane Emden equations numerically by Gegenbauer wavelet method. This method is mainly based on orthonormal Gegenbauer polynomials and takes the advantage of orthonormality which reduces the computational cost. As a further advantage, Gegenbauer polynomials are associated with a real parameter allowing them to be defined as Legendre polynomials or Chebyshev polynomial for some values. Although this provides an opportunity to be able to analyze the problem under consideration from a wide point of view, the effect of the Gegenbauer parameter on the solution of Lane Emden equations has not been studied so far. This study demonstrates the robustness of the Gegenbauer wavelet method on three problems of Lane Emden equations considering different values of this parameter.
Modelling an RDF Knowledge Graph with Transitivity and Symmetry for Bus Route Path Finding

A key property of Linked Data is the representation and publication of data as an inter-connected labelled graph where different resources linked to each other form a network of meaningful information. A problem of path finding can be seen as searching important relationships between resources, such as, looking for chains of intermediate nodes. In this paper, we tackle this problem in the context of public transport navigation system, where we aim to find candidates of bus route path given two bus stations. We model a novel lightweight bus network as Resource Description Framework (RDF) triples of directed bus lines and walking paths between connected stations. Indeed, we demonstrate that lightweight bus network can be achieved by exploiting the sub-property of RDF Schema (RDFS) and the transitivity and symmetry provided by Web Ontology Language (OWL). We also perform a scalability test of our approach using a real-world bus network in Bangkok, Thailand. Various patterns of SPARQL Protocol and RDF Query Language (SPARQL) query statements are validated, showing the usefulness of the RDF model. The further step of this paper is to work with bus schedules and travel time analysis in order to select some proper candidates for users through an application.
Study of water channels and gates to improve water wheel performance

Glintung Water Street (GWS) in Malang City harnesses water flow in its canal to drive water wheels for electricity generation. However, the discharge of water has not been optimized, necessitating the design of the canal and sluice gate to maximize discharge while mitigating flooding risks. This research aims to determine the optimal design and operational system of the sluice gate to minimize backwater impact. Data collection involved observational techniques and literature review, including hydrology, map, and hydraulic data. Results indicated that the required discharge for the micro-hydro power plant (PLTMH) in the Glintung Water Street (GWS) area was 88 liters or approximately 0.088m3/s. The primary channel's flow rate was measured at 0.104 m3/s, with planned channel inflow at 0.088 m3/s. The sluice gate effectively prevented backwater impact, as water levels did not surpass the sluice height. Planning involved a sluice gate made of mild steel plate (100 cm x 100 cm) with a door height of 200 cm and a thickness of 0.18 cm, operated by a handlebar with a diameter of 2 cm. In conclusion, the backwater effect on the primary channel's water level was minimal, affirming the efficacy of the designed sluice gate.
Juridical review of moral rights ownership in copyright of photographic works used for artificial intelligence algorithms

This research delves into the legal landscape concerning moral rights ownership within the realm of copyright for photographic works, specifically exploring their utilization within artificial intelligence (AI) algorithms. Focusing on the intersection of intellectual property law and AI technology, the study investigates the rights and protections accorded to creators of photographic works under copyright laws. The analysis encompasses the ethical and legal considerations pertaining to the use of these works in AI algorithms, scrutinizing issues related to attribution, integrity, and the recognition of creators. By examining the current legislative frameworks and jurisprudence, this research aims to provide insights into the challenges, implications, and potential regulatory adaptations required to ensure the preservation of moral rights for creators within the context of AI-utilized photographic works.
Optimizing SaaS Solutions for Enhanced Sustainability and Predictive Management of Cloud Assets

Identifying waste resources in modern-scale cloud infrastructures is a critical sustainability issue since it helps free up additional capacities for extra tasks and improves the performance of the systems while optimizing their costs. It is already well-recognized as a challenging task for human operators regarding manual and massive action efforts. At the same time, the problem is quite complicated – a complete and satisfactory solution is yet to be achieved. The paper proposes a novel and AI-driven approach to the problem. Applying rule induction learning across the history of service deployment instances to the log event data of the underlying entities, we extract conditions that lead to specific patterns, such as Resource Termination, thus providing a predictive mechanism for detecting objects subject to such actions in a real-time fashion. This explainable recommender system (called Cloud Sweeper) serves as an AI operations assistant for cloud users and Site Reliability Engineers (SRE) in their administrative duties.
CoT-STS: A Zero Shot Chain-of-Thought Prompting for Semantic Textual Similarity

The emergence of Large Language Models (LLMs) have revolutionized the field of Natural Language Processing (NLP) by changing the focus of technical development from features engineering, architecture engineering, and objective engineering to prompt engineering. The main goal of the prompt engineering is to craft clear and concise instructions, known as input prompts, for LLMs to effectively perform the targeted NLP task. Semantic Textual Similarity (STS) is one such significant NLP task, which aims to assess the similarity between the semantic meanings of two input sentences. Numerous approaches have been proposed in the literature, including syntactic similarity evaluations, word-embedding based methods, and dedicated model training. However, these approaches require substantial effort, such as creating extensive annotated datasets and training dedicated STS models.
MINERAL POTENTIAL OF STRATEGICAL AND CRITICAL MINERAL RAW MATERIALS FOR DEVELOPMENT OF HIGH TECHNOLOGICAL INDUSTRY &#x0D; OF THE RUSSIAN FEDERATION

The paper briefly describes the state system of regional geological study of the subsoil, implemented by Rosnedra and VSEGEI, which provides an assessment of the country's mineral resource potential for strategic types of minerals. In 2022, VSEGEI completed the compilation of a set of digital monometal maps of distribution patterns and prediction of strategic and critical types of minerals in the Russian Federation at a scale of 1:2.5 M in GIS format. Reserves of these types of minerals were assessed based on the state accounting system, and an expert reassessment of inferred resources was carried out. As a result, regional predictive criteria concerning the localization of areas promising for the discovery of mineral deposits were developed. Recommendations were given on the organization of additional site appraisal-200/2 and (or) geological and mineragenic mapping-200 on specific nomenclature sheets, promising for exploration for strategic types of minerals
SEARCH-ORIENTED TECHNIQUE OF THE NUMERICAL FORECASTING OF THE RARE-METAL PROXIMAL (NEAR DRIFT) PLACERS: EVIDENCE FROM THE LOVOZERO PLACER DISTRICT

Rare metals (including rare earth metals) are significant raw materials which determine technical and scientific level of development of the industry; first of all – innovative technologies. An important source of rare metals can be a group of unique in genesis and mineral composition of loparite placers associated with the Lovozero massif of nepheline syenites (Cola peninsula). In the present work Within the Northern periphery of the Lovozero massif, which includes the Revda placer deposit, the authors have identified the main factors controlling the formation of proximal (near drift) rare-metal loparite placers. They have performed the formalization (numerical evaluation) of this factors and developed multiplicative indicators that reflect the placer potential of territories. To assess the effectiveness of the proposed technique based on the developed multiplicative coefficients, independent forecasts of placer metal content for the western and eastern placer-bearing areas of the Revda group of placers were calculated. For additional verification of the technique, the paper compares the obtained results with similar forecasts obtained using the methods of Linear Regression and Random forest of Regression trees. The developed method allows automating the process of forecasting of placer parameters, which is especially important for assessing deep-seated placers that are difficult to search and exploration and are not shown on the surface.
SILVER SULFIDES AND SELENIDES IN ORES FROM Au-Ag EPITHERMAL DEPOSITS OF THE OKHOTSK-CHUKOTKA VOLCANIC BELT

Mineral associations and compositions of sulfoselenides and other silver chalcogenides from epithermal deposits of the Okhotsk-Chukotka volcanic belt (North-East Russia) - Rogovik, Lunnoye, Julietta, Valunistoe, Corrida and Pepenveem have been studied. Different types of relationships between S-naumannite and Se-acanthite in the ores of the studied deposits have been established. It is shown that a general pattern in the sequence of formation of silver chalcogenides is the replacement of S-naumannite and Se-bearing minerals (Se-galena, Se-stephanite) of early parageneses by Se-acanthite or acanthite at later stages. Based on the results of thermodynamic calculations and data on the composition of the main productive mineral associations, the physicochemical parameters (T, ƒS2, ƒSe2, ƒO2, pH) of ore formation at these deposits were reconstructed.
Simple Dynamic Threshold Decryption Based on CRT and RSA

In the paper we present a simple threshold decryption system based on the RSA cryptosystem. Our model avoids the application of the Shamir secret sharing protocol and is based only on the Chinese reminder theorem. The flexibility in the threshold level is attained due to the suitable preparation of the input data. The second part of the article describes a modification of the basic model, which admits the sender’s impact on the choice of the real receiver’s group.
Non-destructive evaluation of internal cracks in glass fiber reinforced composites using the laser shearing interferometry method

Laser shearing interferometry is one of the new methods of non-destructive testing, which is based on the interference of monochromatic waves reflected from the surface of the sample. This method can evaluate the entire surface of the sample with high accuracy and speed, by directly measuring the out-of-plane displacement gradient. In this paper, the possibility of detecting subsurface cracks with various lengths and angles in composite samples has been investigated using the shearing method and thermal stimulation system. To this aim, artificial and controlled cracks of different lengths and angles were created in the manufactured composites. After validating the performance of the shearing arrangement, two radiation heat sources were used to apply the load on the samples. The effect of loading size variables, shearing size and direction, crack length, and their angle on the quality of the results was investigated. The results show that the change in loading size plays a more important role than the change in shearing size in correct crack detection. To achieve the best results in crack detection on the selected samples, optimal loading in thermal mode equal to 12 and 15 seconds from the front of the sample was obtained. Moreover, the optimal size of the shearing in the examined composite samples was estimated to be about 10% of the width of the image recorded by the camera. Using the optimized values, all subsurface cracks were identified.
Development of E-learning Teaching Materials Graphic Media Development Course for Students’ Educational Curriculum and Technology

This study aims at identifying the feasibility and efficacy of e-learning material for graphic media development subject by using the e-learning material provided by Universitas Negeri Surabaya. The study takes place in The Department of Technology of Education, Universitas Negeri Surabaya. The subject involves students who have participated in media graphic course. The samples are selected through simple random sampling with the amount of samples in experiment and control class is 30 students each. This development research is carried out using the development model of Four-D Model with the stages of Define, Design, Develop, Disseminate. The validation test on each unit of test proved that all of them are considered valid at Sig. 5%, while the reliability coefficient of the test is = 0.83. Feasibility test on the material and media each gains 88.5% and 87.7%, which means very feasible to apply. The effectiveness test on the e-learning material is conducted using quasi experimental group analysis technique. Based on the Independent sample t test, it was gained that (p &lt; 0.05). N-Gain from the experiment class is 0.6 which categorized as fairly effective, while the N-Gain of the control class is 0.45 and perceived as less effective. The findings presented that e-learning material is deemed feasible and fairly effective to be used during the teaching and learning activity and could improve the students’ learning outcome.
The Impact of Collaborative Learning on Interpersonal Intelligence

This research aims at examining the impact of collaborative learning on children’s interpersonal intelligence and differences after learning using collaborative learning models. The research used a quantitative approach through an experimental method with a True Experiment Design in the form of a posttest-only control group design involving 58 Grade-III students of SD Mujahidin Pontianak as the population. The data were collected through observation and questionnaire. The data were once analyzed using the post-test data. In this research, the researchers discussed the impact of collaborative learning on students' interpersonal intelligence. The research findings indicated that the students' interpersonal intelligence was classified into moderate category. In this category, the students had the average ability to communicate and were adequately capable of forming their social relationships. Thus, it can be concluded that collaborative learning models impacts the students' interpersonal intelligence. The t-test result was 0.021 &lt; 0.05, meaning that Hₐ was accepted, while Ho was rejected. Thus, the implementation of collaborative learning methods impacted the students’ interpersonal intelligence at grade III of SD Mujahidin Pontianak.
TRADITIONAL GAMES PARK AT SOUTH BORNEO’s SPORT CENTER

South Kalimantan will be involving in national sports events by building a Sports Center as a place for training athletes, so there are opportunities and challenges to reach broader development targets, namely how to create a sports space for the public. Through the concept of Organized Flexible Space, the design of a Traditional Game Park in a Sports Center can become a forum for the development and fostering of recreational sports for the public community through flexible spaces to accommodate various functions (sports, games, and education) based on the context of physical activity of traditional games. The Modular Architecture Approach will ease and accelerate the design process in achieving indoor and outdoor spaces with organized circulation and an attractive and safe arrangement on the contour site.
Learning assisted by evaluation in the online conditions of the academic training of teachers

The article specifies the completeness of the teacher’s training process components from the perspective of constructivist and competence pedagogy with arguments for the need to promote the strategy for assisted learning and evaluation in online conditions, a strategy aimed at formative and holistic assessment of students’ achievements of learning tasks in each topic/module of the UPS „I. Creangă” Master’s Program in Educational Management, using specific assessment criteria. In this context, learning is understood, approached, researched and practiced as a progressive transformation of behavior in interaction with knowledge objects and life situations, which imprints a creative learning, creative thinking that results in learning products percieved as a "result", that expresses a "purpose", "the result of an experience","value".
On the Construction of the Graph of Discrete States of a Switched Affine System

The problem of constructing the graph of states of a switched affine system closed by a static state feedback is considered. To solve this problem, a constructive algorithm based on the study of the consistency of systems of linear algebraic inequalities is proposed.
Some Theoretical Aspects of the Neural Network Approach to Stabilization of Switched Interval Systems

We consider the problem of stabilization of a switched interval linear system with slow switchings that are inaccessible to observation. It is proposed to look for a solution in the class of variable structure controllers. To ensure the functionality of such a controller, it is necessary to construct an observer of the switching signal. This paper is devoted to some theoretical issues related to the period of quantization of the neural observer’s operating time.
Comparison of environmental performance for 3 types of cement by EU PEF Guide

Environmental assessment was performed according to the EU PEF method for three types of cement that emit large GHG emissions. The results were calculated as an eco-point. As a result, Portland Cement has the highest eco-point of 1.17E-01. This is due to the fact that the global warming effect of Portland cement is significantly higher than those of other cements. However, eco-cement had the highest particulate matter effect. The replacement of calcium sulfate is necessary for reducing the particulate matter effect of eco-cement.
PHYSICO-CHEMICAL CONDITIONS FOR THE FORMATION OF PRODUCTIVE MINERAL ASSOCIATIONS OF GOLD DEPOSITS OF THE TAIMYR-NORTH EARTH ORGEN

For the first time, based on the data of the study of fluid inclusions, the PTX parameters of the formation of gold mineralization of the Taimyr-Severozemelsky orogen were established. The temperature of formation of gold ores covers the range from 310 to 105°C, the pressure was not lower than 110–96 MPa. The ore-forming fluids were characterized by NaCl + KCl + H2O + CO2 + CH4 + N2 composition and salinity up to 9.7 wt. % in equiv. NaCl. The composition of native gold (fineness varies from 960 to 550‰) and minerals of productive mineral associations has been determined. Ore-forming fluids of gold-sulfide-quartz ore occurrences of the accretionary Schrenk-Fadeevskaya zone (Yasnenskoye and Malinovskoye in North-East Taimyr) are more oxidized and less saline compared to the gold-quartz occurrences of the orogenic type of the Mininsko-Bolshevitskaya myogeoclinal zone (Nizhnelitkenskoye, Vidimoe, Nerpichye).
SEMIPRODUCTS, PRODUCTS, AND MODAL PREDICATE LOGICS: SOME EXAMPLES

We study two kinds of combined modal logics, semiproducts and products with S5, and their correlation with modal predicate logics. We obtain examples of propositional modal logics when these semiproducts or products are axiomatized in the minimal way (semiproduct- or product-matching with S5), as well as counterexamples for these properties. The fmp for (semi)products together with (semi)product-matching allow us to show decidability of corresponding 1-variable modal predicate logics.
ON ANALOGUES OF HERBRAND’S AND HARROP’S THEOREMS FOR THE JOINT LOGIC OF PROBLEMS AND PROPOSITIONS QHC

In this paper analogues of Herbrand’s and Harrop’s theorems for the logic QHC are proved.
Reuse and Recycle Knowledge, Not Only Data

Summary Exploration, development, and investment decisions in any energy project requires consistent, trusted, and auditable technical and economic support material, that often takes too long to create and delivers results that are not comparable. In particular, valuable time is wasted while trying to find adequate knowledge and data or by duplicating work. If the users could easily access, consume, and recycle corporate knowledge digitally, which contains the direct link back to the raw data, considerable time and cost would be saved and results would be more consistent helping to support corporate decisions. One technology to efficiently search corporate digital knowledge is the knowledge graph using defined ontologies enabling deep and efficient utilization of corporate knowledge. The knowledge graph accommodates the relationships inherent to the knowledge and associated data. By using a graph database, information can be accessed that enables users to find the knowledge and data they require, thus saving valuable time and cost.
Closing the Information Gap: Making COVID-19 Information Accessible for People with Disabilities.

It is essential that people with disabilities have equitable access to COVID-19 communication resources to protect themselves, their families, and their communities. The Accessible Materials and Culturally Relevant Messages for Individuals with Disabilities project aimed to deliver essential COVID-19 information in braille, American Sign Language (ASL), simplified text, and other alternative formats, along with providing additional tools and trainings that people with disabilities and organizations that serve them can use to apply the COVID-19 guidance. Lessons learned from this project can be implemented in future public health emergencies as well as in general public health messaging for people with disabilities. This project, led by Georgia Tech's Center for Inclusive Design and Innovation (CIDI) and with technical assistance from the Centers for Disease Control and Prevention (CDC), was supported by the CDC Foundation, using funds from the CDC Foundation's COVID-19 Emergency Response Fund.
ATCBBC: A Novel Optimizer for Neural Network Architectures

For deep neural networks, gradient descent (GD) is the backbone. Slow convergence is an issue with GD. Using momentum is the well-known method of overcoming delayed convergence. GD's learning factor is considerably improved by momentum. Several strategies, including Adam, diffGrad, and AngularGrad, have notably been put out to better manage the momentum for optimization toward the global minima (GM). Adam reduces momentum by reducing it through the square root of the moving average of the square of the past gradients, or the second moment. Sometimes the gradient overshoots the optimal solution and settles at the local minima (LM) as a result of the second moment's abrupt decline. The friction factor in DiffGrad, which reduces this issue, is dependent on the difference between Adam's current gradient and its recent gradient. Slow convergence is caused by the frictional constant, which further reduces the momentum. AngularGrad adapts the step size using smallest tangent values of the angles of two consecutive gradient. The novel optimization method described in this research, called ATCBBC, or adaptive term calculation, only uses bias correction, does away with the overshooting gradient issue in Adam, provides a smooth trajectory, and outperforms conventional optimizers in terms of classification accuracy on real-world datasets.