Development Of Technology Research Articles

Use of magnetic nanomaterials in wastewater treatment: a review.

The growing need for clean water, as well as the mounting problems of water pollution, have prompted the development of innovative and efficient water treatment technologies. The unique qualities of magnetic nanomaterials (MNMs), including their large surface area, magnetic responsiveness, and ease of functionalization, have made them a potential option. MNMs are produced via chemical, physical, or biological means. MNMs are used in membrane filtration, adsorption, catalysis, and magnetic separation for the treatment of wastewater. They may adsorb contaminants, act as catalysts, improve membrane filtering performance, and enable facile recovery and reuse via magnetic separation. MNMs have high specificity, efficiency, and recyclability, but they confront environmental and health risks, high production costs, and scaling concerns. Therefore, the ongoing research must focus on eco-friendly approaches, improving stability, studying synergistic effects, and conducting risk analysis of MNMs to ensure safe use. Moreover, the MNMs investigated are only applicable for synthetic or small-scale wastewater treatment. Only a few MNMs are operating at an industrial level; therefore, more investigation is suggested for the applicability of MNMs on a large scale and real wastewater treatment.

Improved data query analysis techniques based on structure optimization and efficiency optimization

With the rapid development of information technology and the Internet, the existing data query system suffers from poor performance, single structure and slow efficiency in processing data. In view of this, the study introduces the GmmCube multidimensional data intelligent query system and combines column-to-block structure and single-dimension matrix for structure optimization. On the basis of guaranteeing specific dimensions, it continues to introduce the sparse prefix sum for efficiency optimization. The experimental results showed that the maximum storage space consumption was 1050 MB in the training set and 1040 MB in the test set after comparing with three commonly used algorithms: prefix sum array, binary index tree, and segment tree. The maximum deviation in query time was 0.1 hours. When querying Weibo big data (10 million records), the lowest measured absolute error was 2%, the precision rate was 93.56%, and the recall rate was 93.74%. It can be concluded that the novel data query technique proposed by the study is superior in data query performance and efficiency, and can provide an effective solution for big data query analysis.

Development of Patient-Specific Lattice Structured Femoral Stems Based on Finite Element Analysis and Machine Learning

Hip implant optimization is increasingly receiving attention due to the development of manufacturing technology and artificial intelligence interaction in the current research. This study investigates the development of hip implant stem design with the application of lattice structures, and the utilization of the MATLAB regression learner app in finding the best predictive regression model to calculate the mechanical behavior of the implant’s stem based on some of the design parameters. Many cases of latticed hip implants (using 3D lattice infill type) were designed in the ANSYS software, and then 3D printed to undergo simulations and lab experiments. A surrogate model of the implant was used in the finite element analysis (FEA) instead of the geometrically latticed model to save computation time. The model was then generalized and used to calculate the mechanical behavior of new variables of hip implant stem and a database was generated for surgeon so they can choose the lattice parameters for desirable mechanical behavior. This study shows that neural networks algorithms showed the highest accuracy with predicting the mechanical behavior reaching a percentage above 90%. Patients’ weight and shell thickness were proven to be the most affecting factors on the implant’s mechanical behavior.

Implementation of Consumer Protection Act in the Digital Era

The development of information and communication technology has changed the global economic landscape, encouraging the emergence of a digital economy. Ecommerce has become the core of transactions, offering convenience and competitive prices. However, this convenience also opens up risks for consumers, especially in terms of consumer rights, product quality, privacy, data security, and dispute resolution. Consumer protection in online transactions in Indonesia is regulated by the Consumer Protection Act and Electronic Information and Transactions Act. These two laws provide sufficient legal protection, covering consumer rights and obligations as well as dispute resolution mechanisms. However, this legal protection is considered inadequate, especially for digital products. The gap between law and practice, lack of consumer knowledge, and weak supervision are challenges. Therefore, strengthening consumer protection mechanisms, especially in the context of international platforms, is crucial to ensure safety and fairness in e-commerce transactions.

Penggunaan Video Pembelajaran Terhadap Peningkatan Hasil Belajar Pendidikan Agama Hindu Dan Budi Pekerti Siswa Kelas VII

Implementing video media as a learning tool by utilising the development of information and communication technology (ICT) to create a more structured, directed and effective teaching and learning process. This study aims to determine the effect of using learning videos on improving learning outcomes of Hindu Religious Education and Budi Pekerti class VII students at State Junior High School 5 Mataram. The research method used in this research is descriptive quantitative associative using ex-post facto research design. Data analysis using sedernaha regression test, based on simple regression data analysis obtained data that t count 0.359 is smaller than t table 1.1980 with a significant level value of 0.721 greater than 0.05, it can be concluded that Ho is accepted and Ha is rejected, which means that there is no significant effect of using learning videos on improving the learning outcomes of seventh grade students at State Junior High School 5 Mataram. the average value (mean) of the variable use of learning videos (X) is 70.18 with a percentage of 70.73% in the sufficient category. The report card value of learning outcomes (Y) with an average value (mean) of 89.16 with a percentage of 80.48% in the very high category.

A Study on the Attitude towards Social Science among Secondary School Students Studying in Selected MBOSE Affiliated Schools Located in Shillong, East Khasi Hills, Meghalaya

This study investigates the attitudes of secondary school students towards Social Science in selected MBOSE-affiliated schools in Shillong, East Khasi Hills, Meghalaya. Using a descriptive research design, data were collected from 240 students in Classes IX and X across twelve schools, ensuring balanced representation by gender and school type viz. the government aided schools and private non-aided schools. The research employed a self-constructed Likert attitude scale and a supplementary questionnaire to assess students’ interest, perceived benefits, perceived difficulty, and demographic factors influencing their attitudes. Findings reveal that both boys and girls generally hold positive attitudes toward Social Science, with boys showing slightly higher interest and lower perceived difficulty, particularly across History, Civics, Geography, and Economics. Students from aided schools demonstrated more favorable attitudes than those from private unaided schools, highlighting the impact of institutional support and teaching practices. While most students recognize the relevance of Social Science for civic awareness and personal development, challenges such as memorization, perceived difficulty (especially among girls), and uncertainty about career relevance persist. The study highlighted the importance of innovative, student-centered pedagogies, contextualized content, and experiential learning to sustain engagement. Recommendations include integrating technology, community involvement, differentiated instruction, and continuous teacher professional development. The research advocates for curriculum reforms and supportive learning environments to make Social Science education more meaningful, inclusive, and future-oriented considering the scope of Secondary School Education.

Quantification of Quality in Publicly- Funded Biomedical and Pharmaceutical Research and Technology Development Settings in India

Quantification of Quality in Publicly- Funded Biomedical and Pharmaceutical Research and Technology Development Settings in India

Issues of evaluating the effectiveness of company's management in the context of Industry 4.0 and 5.0

Subject. The article addresses the assessment of company's management effectiveness in the context of digital transformation caused by the transition to Industry 4.0 and 5.0. Special attention is paid to the development of indicators for evaluating the effectiveness of management decisions at different stages of the company's digital maturity. Objectives. The purpose is to develop recommendations for evaluating the effectiveness of management processes at enterprises in the context of the transition to Industry 4.0 and the initial stages of implementation of the Industry 5.0 concept. Methods. The research includes the analysis, systematization, and comparative evaluation of the most commonly used approaches to assessing the effectiveness and efficiency of management decisions in the context of digitalization. Results. The paper presents a system of indicators to assess management effectiveness at each stage of enterprise digitalization. At the initial stages of digital transformation, the focus is on operational and financial efficiency indicators; at the average level – on process flexibility and labor productivity; at the advanced stage, close to Industry 5.0, indicators of sustainability and social impact of business are highlighted. Recommendations are given on the application of these indicators, the choice of software, and the preparation of data for evaluation. Conclusions. The developed recommendations and a system of indicators can be useful for companies at various stages of digitalization, striving to assess and control the effectiveness and efficiency of management decisions in the most reasonable and objective manner in modern conditions of technological development.

Understanding Purchase intention of Gen Z: Combined role of Social Media Influencers, Government initiatives and User Experience

As consumer markets evolve with an increasing emphasis on digital solutions and sustainability, it becomes crucial to comprehend the factors influencing purchase intentions, particularly concerning emergent technologies such as electric vehicles (EVs). This research investigates the combined effects of social media influencers, governmental initiatives, and user experience on Generation Z’s intentions to purchase Electric vehicles. Employing the source credibility model as a foundational framework, the analysis assesses how dimensions of social media influencer’s attitudes such as trustworthiness, attractiveness, expertise, affect purchase intention. In parallel, the investigation considers governmental initiatives, including financial incentives and infrastructure enhancements, as significant motivational elements. Moreover, user experience factors, encompassing perceived ease of use, satisfaction, and performance, are analysed as a vital moderating component. The study employs a survey based quantitative methodology, utilizing structural equation modelling to interpret responses from potential EV purchasers. Initial findings indicate that the credibility of influencers and government support are substantial determinants of purchase intention, while a favourable user experience further enhances this relationship. These insights provide practical implications for marketers, policymakers, and technology developers seeking to increase consumer adoption through effective influence and robust support frameworks. Keywords: Electric vehicles, Purchase intention, social media influencer, Government initiatives, user experience.

Fostering creativity through the exploitation of scientific and technological knowledge

Abstract The most creative inventions—i.e., inventions that are both novel and highly valuable—in the lithium-ion battery field are developed by inventors that exploit their own field-specific knowledge base, leveraging scientific and technological knowledge components they previously developed. This observation contrasts with the findings of prior literature, which has argued that exploration driven by inventors new to a field tends to drive novel and breakthrough inventions. We argue that the technological context and characteristics of the recombinant search process underlying technology development provide important theoretical boundaries to these prior findings and should be considered. In a complex and science-driven technology field, we expect an inventor’s own accumulated scientific and technological field-specific knowledge base to play an important role in advancing that technology field and to matter more for generating novel and breakthrough inventions.

Technologies for Lithium Extraction from the Mineral Zinnwaldite – History, Present and Future

This article provides an overview of the technological development of lithium extraction from zinnwaldite, the principal lithium-bearing mineral in the Czech Republic, focusing on the historically significant Cinovec deposit. Historically, various chemical methods have been applied for lithium separation, including acidic and alkaline processing. The Research Institute for Inorganic Chemistry (RIIC) located in the city of Ústí nad Labem played a pioneering role in this field, having developed and tested multiple processing technologies, particularly during the mid-20th century. Among these, the gypsum-based method showed the highest separation efficiency for lithium, and current efforts aim to optimize this process using industrial by-products, such as flue-gas desulfurization gypsum. RIIC's extensive experimental base and expertise contributed significantly to the advancement of hydrometallurgical processing of silicate lithium ores and laid the foundation for current research. Modern approaches integrate both pyro- and hydrometallurgical techniques with the objective of enhancing lithium recovery rates while minimizing environmental impact. Among innovative developments is the InCeMeTs process, which utilizes cement kilns for thermal processing, thereby reducing material input and water consumption. Additionally, pre-concentration via magnetic separation, particularly effective for zinnwaldite due to its iron content, has emerged as a promising step. Plans are underway to establish a mining and lithium processing facility at Cinovec by 2030, which could play a key role in securing strategic raw materials for the European Union. The combination of rich geological resources, established expertise in lithium processing (led historically by RIIC), and renewed institutional and industrial interest makes the Czech Republic a potential significant contributor to the European battery materials supply chain.

Pelatihan Penyusunan Laporan Auditan oleh Kantor Akuntan Publik (KAP) Sarastanto dan Rekan bagi Mahasiswa STIE Semarang

The rapid technological developments of this decade have had a positive impact on the transparency of information in financial reports. Transparent financial report information demonstrates the quality of the financial reports. Public accountants are tasked with providing an opinion on the fairness of the presented financial reports. The standard used by a public accountant in assessing the fairness of financial reports is the Public Accounting Auditing Standards (SPAP). The SPAP contains guidelines for carrying out the audit cycle systematically and in accordance with procedures, starting from the pre-engagement, planning, and reporting stages. Therefore, it is crucial to conduct audit report preparation training for prospective auditors, conducted by a team of lecturers from the Faculty of Economics and Business, Dian Nuswantoro University through a community service program. This community service activity took as participants prospective auditors from STIE Semarang students at KAP Sarastanto and Rekan in Semarang City. This activity was carried out so that prospective auditors could be provided with the knowledge and skills to complete the audit cycle from pre-engagement to reporting. The methods used in this community service program were presentations and mentoring, while the training material for preparing audit reports was carried out by the community service team and practitioners (auditors) from KAP Sarastanto and Rekan. The results of this training show that prospective auditors (STIE Semarang students) are able to understand the audit cycle systematically and are able to realize the importance of audit reports for stakeholders.

Improving students’ classroom motivation and learning efficiency based on deep learning

With the rapid development of educational technology, personalized learning and intelligent teaching have become the key to improving students’ learning efficiency and motivation. However, traditional teaching methods are often difficult to adapt to the learning needs of different students, resulting in low student participation and poor learning results. In this paper, from these two main indicators, based on deep learning technology, we construct a classroom learning model based on Transformer. Our model has three major modules, namely, student module, course module, and optimization module, which provide students and teachers with personalized classroom design. Through experimental validation, we have conducted experiments in English and math groups, and the performance is good. Specifically, our model outperforms the traditional model in both English and math teaching. This study not only helps to promote the application and development of educational technology but also has important significance for improving teaching practice and promoting the all-round development of students.

Application of Intuitionistic Fuzzy Approaches and Bonferroni Mean Operators in the Selection of Suppliers of Agricultural Equipment and Machinery for the Needs of the Agriculture 4.0 System

The development of technology has influenced agricultural production and the establishment of the Agriculture 4.0 system in practice. This research is focused on the selection of equipment and machinery suppliers for the needs of the MAMEX Company. When selecting suppliers, an approach based on the application of an intuitionistic fuzzy set for decision-making was used. This approach allows the uncertainty present in decision-making to be incorporated, considered, and, hopefully, reduced in order to make a final decision on which of the observed suppliers is the most suitable for this company. Ten criteria were used that enable the application of sustainability in the supply chain. Eight local suppliers of equipment and machinery were observed with these criteria. The results obtained by applying the SWARA (Step-wise Weight Assessment Ratio Analysis) method showed that the most important criterion for selecting suppliers is the reliability and quality of equipment and machinery, while the results of the CORASO (COmpromise Ranking from Alternative Solutions) method showed that the SUP2 supplier is the best choice for establishing partnership relations with the MAMEX company. This supplier should help the MAMEX company improve its business and achieve better results in the market. The contribution of this research is to improve the application of intuitionistic fuzzy sets in decision-making, and to emphasize the importance of equipment and machinery in agricultural production in the Agriculture 4.0 system.

COST-jet characterization via optical emission spectroscopy and mass spectrometry in carbon dioxide conversion

Abstract Non-thermal plasma conversion of carbon dioxide (CO2) has attracted much interest in recent years because it can be operated at low temperatures and under atmospheric pressure. The development of new conversion technologies, comparison with other applied methods, and understanding of complex processes require numerical modeling. A crucial part of modeling is the calculation of the electron impact dissociation. Due to the linear configuration of CO2 in the ground state and the different multiplicity of products, the dissociation is a complicated process with several sequential stages. Very different electron impact dissociation cross sections can be found in the literature. Using optical emission spectroscopy and mass spectrometry, a radio frequency plasma jet (COST-jet) operated with a He/CO2 /N2 gas mixture is characterized and CO2 conversion along the discharge is simulated. The applied method can help to select a reliable cross section of electron impact dissociation of CO2 and to determine the probability of heterogeneous recombination.

РАЗРАБОТКА КОНЦЕПТУАЛЬНОГО ПОДХОДА К ПРОЕКТИРОВАНИЮ ЕДИНОГО ИНФОРМАЦИОННОГО ПРОСТРАНСТВА УПРАВЛЕНИЯ ИТ-ПРОЕКТАМИ

In the conditions of rapid development of information technologies, effective IT project management is of particular relevance. The process of IT project management is considered, including the stages of initiation, planning, realization, control and completion. The relevance of the topic is determined by the need to optimize the management and communication processes in IT projects to improve the quality and competitiveness of the created products. The paper reveals the contradictions associated with information gaps and data duplication in the use of disparate information systems, which leads to problems of reduced team efficiency and product inconsistency with customer expectations. By disparate information systems is meant a set of independent and unrelated systems within one or several organizations, functioning without unified integration, and receiving and processing heterogeneous data in the context of different structure and format. The proposed solution to the problem is the development of a conceptual approach to design the integration of the systems used and the transition to centralized platforms, as well as the organization of a single information space, in which all the systems used, as well as the data stored in them, are combined into a common system, which will improve the consistency of heterogeneous data, reduce risks and increase team productivity.

Engineering Framework Materials in Water Systems for Targeted Ion Extraction and Spontaneous Energy Harvesting.

Developing techniques that can extract required salt resources and harvest spontaneous energy from natural water environment is essential to promote the global decarbonization and electrification. Construction of advanced framework materials with intrinsic nanochannels has been considered the most promising solution to implement this technique owing to the specific fluid transport performances in such confined space. However, this design requires a deep understanding of the structural properties of framework material nanochannels in different scenarios, as well as the corresponding construction strategies. Consequently, it is an urgent necessity to elucidate the specific ion capture behavior and fluid transport mechanism in these framework materials to build targeted nanofluidic systems for guiding developments in water related resources and energy acquisition technologies. Herein, the recent advances in ion extraction and energy harvesting based on metal-organic framework and covalent-organic framework materials have been outlined, along with the discussion about the nanochannels specificity by combining ions and fluid properties and nanochannel structures. Finally, an outlook to trends, challenges and emerging opportunities is given to foresee the future developments in this important field.

Understanding the Concepts of Smart E‐Nose Technology in Combination With Machine Learning for New Era of Food Safety: An Advanced Review

ABSTRACTElectronic‐nose (E‐Nose) technology delivers fast and precise detection of volatile substances by utilizing sophisticated data processing techniques such as principal component analysis (PCA) and artificial neural networks (ANN). This makes E‐Nose technology a useful substitute for conventional sensory evaluation methods. E‐Nose systems are now even more capable because of the incorporation of artificial intelligence, which allows for complex pattern recognition and odor classification. Ongoing developments in sensor technology and data processing algorithms are anticipated to cement the position of E‐Nose systems as crucial instruments in guaranteeing food safety, environmental health, and precise medical diagnostics, notwithstanding obstacles associated with sensor stability and environmental sensitivity. This technology's future depends on ongoing innovation and improvement in analytical techniques as well as sensor designs. E‐Nose technology has shown great potential in some fields, including medical diagnostics, environmental monitoring, and food quality evaluation. This is especially true when combined with machine learning. The development of E‐Nose systems from large power‐hungry equipment to small, lightweight, and effective gadgets is examined in this research study.

Chromosome-level genome assembly of starry flounder (Platichthys stellatus).

Starry flounder (Platichthys stellatus) is widely distributed along the coastlines of the North Pacific. As an euryhaline flatfish, it can adapt to a wide range of environmental salinity ranging from freshwater to seawater, and is a promising aquaculture flatfish species in Korea and North China. However, no high-quality starry flounder reference genome has been reported to date, which greatly limits the studies of genetics and functional genomics. Here, we obtained a high-quality chromosome-level starry flounder genome assembly with alength of 643.56 Mb (scaffold N50: 26.19 Mb, contig N50: 10.00 Mb) combining short-reads sequencing, PacBio HiFi sequencing, and Hi-C sequencing. Approximately 94.02% of assembled sequences were anchored into 24 pseudochromosomes, and a total of 18 telomeres were detected. Totally 22,835 protein-coding genes and 227.87 Mb repetitive sequences were identified. In summary, the high-quality chromosome-level genome assembly not only provides valuable resources for genetic research in starry flounder, but also advances the development of molecular breeding technology of starry flounder.

Validation of a New High-Throughput Cell Separation Method for Downstream Molecular Applications

The development of new cell separation technologies has continued as the demand for sorted cell populations for molecular testing increases. The goal is to increase through-put potential and reduce the manual handling of samples required whilst ensuring that cells are sorted efficiently with high purity. Herein, we review two affinity-based methods utilising magnetic beads to isolate cells: one is currently used within a clinical laboratory as standard of care and the other is a newly developed larger platform using the same principle. Cells were sorted simultaneously on both platforms and assessments were made of the purity, cell recovery, and hands-on time, indicating that the new larger platform is sufficient for use in a clinical laboratory as it not only increased cell sorting capacity and reduced manual processing but was also able to isolate cells with sufficient purity levels for downstream molecular testing.