bluuebunny/crossref_metadata_2025 huggingface dataset:
Parameter Selection for Digital Satellite Model Updating with Knowledge Graph
Authors: Liew Yingjia , Dong Yunfeng
Published: December 2023

Digital twin technology has played an indispensable role in the recent satellite life cycle, specifically in design, testing, and operation monitoring. A digital twin is created according to a physical satellite and can mirror its performance and parameters. The physical satellite is occasionally affected by dynamic disturbances when in orbit, causing inconsistencies with its digital twin, thus requiring the digital twin model to be continuously updated through model parameter adjustments. Nonetheless, the digital twin model involves numerous parameters with coupled relationships; adjusting all simultaneously might be impractical as it requires high computational and time. Since only some of the model parameters have a significant impact on the digital model’s outputs, we propose a parameter selection method that utilizes knowledge graph technology for digital satellite model updating. Firstly, the satellite state variables and their related telemetry parameters of satellite subsystems in the digital satellite model are defined. Secondly, a knowledge graph consisting of the correlation and sensitivity relationships of the state variables and telemetry parameters is built. Thirdly, a clustering algorithm and graph reasoning algorithms are employed on this knowledge graph to select and group the state variables and telemetry parameters required in model updating. The results show that by updating the state variables and telemetry parameters selected from the knowledge graph, not only can the state variables converge to optimal values in fewer iterations, but a more accurate digital satellite model can also be obtained.
A Revised PDE for Traffic Lattice Model
Authors: Ren Xiufang , Zhao Shiji
Published: December 2023

In this paper, a threshold of sensibility for the stability of a generalized traffic lattice PDE with multiple factors, including lane-changing, multiple sites, multiple density difference, curved lane and multi-mode solutions factors has been derived in detail. The profiles of the density waves are simulated in detail and two indexes, congestion degree and entropy, which have opposite monotonicity are defined to describe the traffic conditions. The technique is based on the perturbation theory and the result can be helpful for minimizing the traffic congestion.
Application Research of Metamaterial Multilayer Structure in Electromagnetic Shielding
Authors: Lu Xiangdong , Wang Rongfu , Li Yongning , Yu Liang
Published: December 2023

The wave transmission characteristics of metamaterial dielectric slab is studied, and the expressions of total reflection and transmission coefficients of multilayer structure composed of metamaterial and dielectric slabs are deduced. Based on the theory of small reflection approximation, a high-performance reflection coating can be made by applying metamaterial multilayer dielectric structure, which can effectively improve the electromagnetic external shielding performance.
Analysis of Load Current Ripple in a Five Level Buck Converter
Authors: Chow Emerson Brilliant , Khan M.K.A. Ahamed , Mokayef Mastaneh
Published: December 2023

A buck converter, sometimes known as a step-down converter, is a kind of DC-to-DC converter that belongs to the DC chopper family. Buck converters are a sort of switching power electrical device that is typically used to provide an alternating DC output voltage that is less than the constant DC input voltage source. The primary focus in the field of electronic appliances is on the root cause of harmonic distortion in a Buck converter system, where interference from harmonic signals frequently appears at both the input and output terminals of the load side, affecting the efficiency and performance of the buck converter. This research paper focuses on the load current ripple content and the harmonic problem encountered by a five-level buck converter. The research consists of ten buck converters with varying levels and two different loads, R load and RLC load, and all of these converters were used to compare one to the other as one of the objectives of this research. After repeated calculations, trial and error, and conclusion of the study hypothesis, the research got intriguing findings where the buck converter ripple and harmonic content were minimized by raising the buck converter level.
Prediction of Myopia Progression Based on Artificial Intelligence Model
Authors: Swain Subhalaxmi , Sivakumar R
Published: December 2023

This study gives an idea about myopia which become a leading health concern and socio-economical issue with a big threat to the pediatric population. Also, give an idea about some genetic and environmental factors for myopia progression. Clinical, environmental markers for predicting this visual threatening disease. Involvement of corneal biomechanics, a different mode of managing myopia, most important, different approaches for predicting myopia and an efficient model selection for handling such huge data from EMR and predicting the disease perfectly with the help of AI.
The Study on Distribution Characteristic of Positive Friction Resistance in Thick Loess Area
Authors: Wang Xudong
Published: December 2023

The bearing capacity of pile foundation engineering in large thickness loess area is mainly provided by the positive frictional resistance of pile side during normal operation and load test. Compared with the coupling effect of side resistance and end resistance of short piles, the side resistance of long piles is clearer in the mechanical mechanism, especially the side resistance of long piles in the large thickness loess area with uniform soil quality is of more significance for analysis and research. Based on the statistical analysis of load test data of empty bottom pile, the formula of lateral resistance and displacement is fitted for three stages of pile-soil interaction. Based on the numerical simulation, the load test of empty bottom pile is inverted, and then the results are obtained: (1) The distribution curve of lateral friction within the pile range is inverted “S” type, and the distribution curve of pile-soil relative displacement within the pile range is “Z” type. There are three areas in the pile body for the distribution of lateral friction, namely the pile top area, the pile in the area and the pile bottom area. The distribution of pile-soil displacement can also be compared with the above three areas; (2) By comparing the lateral friction distribution with the pile-soil displacement distribution, it is found that the derivative relationship between lateral friction and pile-soil displacement is present in the range of pile body.
The Analysis of Intelligent Real-Time Image Acquisition System Based on Data Mining
Authors: Zhang Xiaohuan
Published: December 2023

The purpose is to enhance the timeliness of news, provide real-time news for the audience, and attract more traffic for the news media, thereby helping news media grow financially and strengthening the network security communication efficiency and accuracy. First, an intelligent real-time image acquisition system is introduced, and its principle and advantages are analyzed. Second, an intelligent real-time image acquisition model based on DL (Deep Learning) algorithm is established by combining DM (Data Mining) technology. Finally, the application of an intelligent image acquisition system in network communication is adjusted. The research results show that the combination of DL intelligent real-time image acquisition system with DM technology can effectively deal with various network communication scenarios, enhancing the accuracy and timeliness of network communication. The AlexNet model performs excellently in all aspects, with or without data enhancement or equalization. The recognition rate reaches 99.6% after data equalization and enhancement, and the AlexNet model can accurately classify news and non-news sceneries. This shows that the application of an intelligent real-time image acquisition system based on DM technology can effectively enhance the real-time performance of network communication. The results set an example for the application of relevant intelligent image acquisition technology in the journalism industry.
Based on the Digital Platform of Road Construction Machinery and Equipment Maintenance Management Methods
Authors: Zong Guangpeng
Published: December 2023

The practical application of data mining technology aims to provide guarantee for better fault prediction of electromechanical equipment and safe and stable operation of expressways. In order to improve the accuracy of electromechanical equipment health status recognition, an automatic health status recognition model based on data mining was constructed. Firstly, the health status data of electromechanical equipment is collected, and the wavelet transform is used to denoise the health status data of the equipment. Then, the Elman neural network in data mining technology is introduced to design the automatic health status recognition model of electromechanical equipment, and the parameters of the Elman neural network are optimized. Finally, through the simulation test of automatic health status recognition of electromechanical equipment, the results show that, the automatic recognition effect of this model is good, and the error rate and rejection rate of the health status of mechanical and electrical equipment are lower than other models, which verifies the superiority of the automatic recognition of the health status of mechanical and electrical equipment of this model. This paper analyzed the application value of data mining technolog, and the demand for fault prediction of electromechanical equipment on expressways is explained.
Intelligent Building Hoisting Operation Detection System Based on APC Algorithm Assisted Sensor Monitoring
Authors: Deng Tao
Published: December 2023

With the development of intelligence in today’s society, APC Algorithm technology has also emerged in the computer industry, playing a very accurate role in monitoring various aspects. Now, due to the progress of the times, we can use APC Algorithm assisted sensors to monitor our lifting operations. Intelligent buildings are leading a new direction in the construction industry. In modern building construction, more and more buildings are committed to creating intelligent functions, but currently, lifting operations, as an important component of buildings, still lack the creation of intelligent functions. By comparing the performance of three deep learning model algorithms, Fast RCNN, SSD, and YOLO, this paper identifies a monitoring algorithm suitable for intelligent building lifting operations using APC Algorithm sensors for auxiliary monitoring, which can be used to solve monitoring problems in lifting operations. In order to achieve the people-oriented work goal, it is very important to monitor the safety of lifting operators in complex building environments through APC Algorithm monitoring algorithms. Experiments have shown that through APC Algorithm assisted monitoring, we can better regulate intelligent lifting operations and ensure the safety of workers. However, due to the insufficient comprehensiveness and diversity of the algorithms we study, further research is needed on the combination of APC Algorithm and algorithms.
Network Security Prevention Based on D-DNNsafe
Authors: Diao Zhihao
Published: December 2023

Network security refers to the ability to protect computer networks from unauthorized access, destruction, theft or damage. With the popularization of the Internet and the acceleration of information development, network security has become a very important issue. Network security situational awareness is a new network security protection technology that evaluates the security status of the current network operating environment and predicts the security change trend of the network operating environment in the future period based on the relevant elements in the current network operating environment, with the ultimate purpose of ensuring network security. At present, researches on network security situation approach mainly focus on improving the accuracy of logical judgment, which is difficult to achieve a balance between logical processing and spatio-temporal complexity. In addition, there are some problems such as high complexity and lack of objectivity of the implementation model. Based on this, this paper designs a new network security situation assessment method based on D-S evidence theory. Firstly, aiming at the deficiency of objectivity in traditional single D-S evidence theory, Deep Neural Networks (DNN) is proposed to obtain OP to reduce its subjective dependence. Secondly, in order to solve the problems of low accuracy and low time efficiency when DNN processes massive data, SAE is used to reduce the dimensionality of massive high-dimensional data, and D-DNNsafe network security situation assessment model is constructed.
Risk identification for business blockchain-based technology adoption via an advanced fuzzy MRDM architecture
Authors: Hu Kuang-Hua , Chen Fu-Hsiang , Zeng Jhih-Hong , Lin Sin-Jin
Published: December 2023

Blockchain technology holds considerable amount of potential for all types of industries by executing transactions in a verifiable, efficient, and permanent channel. It has been widely viewed as a standard requirement for making industry ready for the future, but when it comes to practical applications, it still arouses numerous risks/challenges that need to be addressed. Therefore, it is essential to address this gap and establish a comprehensive and effective practical framework to align the information technology revolution with sustainable value creation. The purpose of this research is to realize to what extent an enterprise legacy system’s transformation benefits a blockchain-based system and to minimize its specific risk through a hybrid fuzzy MRDM (multiple rule-based decision making) model that integrates data envelopment analysis with rough set theory (DEA-RST) and the fuzzy DEMATEL approach grounded on a questionnaire derived from domain experts. We aim to point out the inherent risks of blockchain-based technology adoption and to assist senior engineers in designing or adopting a suitable architecture for practical operation and planning of any future integration and development. The potential risk evaluation of business blockchain adoption reveals that the priority improvement sequence based on dimensions is smart contract risk, value transfer risk, and standard risk. Furthermore, law and regulation are the most critical criteria.
A total distance ranking approach to fuzzy AHP-based MCDM method for selecting sustainable manufacturing facility location
Authors: Nghiem Thi Bich Ha , Chu Ta-Chung
Published: December 2023

Selecting a sustainable facility location is a crucial strategy for manufacturing companies to achieve long-term success in today’s competitive environment. Various quantitative and qualitative criteria with different importance in a multiple level structure must be considered and aggregated to assist the company in decision-making. How to determine these criteria weights and select the sustainable manufacturing facility locations have become research questions. To resolve this problem, this paper proposes a total distance ranking approach to fuzzy analytic hierarchical process (AHP)-based multiple criteria decision-making (MCDM) method. Currently, the membership functions of fuzzy weighted ratings in the MCDM with a multilevel structure cannot be developed. A ranking method is needed to defuzzify those fuzzy numbers used for fuzzy AHP and qualitative criteria in the MCDM for better executing decision-making procedure. The total distance ranking method related to the centroid on x-axis, centroid on y-axis and the distances of centroids point to the two tangent lines of a fuzzy number are considered in the proposed ranking approach. Formulas of the proposed approach will be presented, and some properties will be investigated to derive formulas for trapezoidal and triangular fuzzy numbers. A comparison with relevant ranking methods will be made to show the advantages of the proposed ranking approach. The proposed ranking approach is then applied to defuzzify the fuzzy numbers used in fuzzy AHP and linguistic values under qualitative criteria to obtain the criteria weights under multi-level structure and crisp values under qualitative criteria, respectively. The final scores of alternatives can be obtained by aggregating crisp criteria values and their corresponding weights by simple additive weighting method to obtain the ranking result. A numerical example will be conducted to show the effectiveness of the proposed model. Finally, a comparison with Best-Worst method (BWM) will be presented to show the persuasiveness of the proposed method.
RETRACTED: Fixed-time tracking control of manipulators based on non-singular fast terminal sliding surface
Authors: Li Dan , Chen Ming , Peng Kaixiang , Wu Libing
Published: December 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
DLAN:Modeling user long- and short-term preferences based on double-layer attention network for next point-of-interest recommendation
Authors: Wu Yuhang , Jiao Xu , Hao Qingbo , Xiao Yingyuan , Zheng Wenguang
Published: December 2023

The next Point-of-Interest (POI) recommendation, in recent years, has attracted an extensive amount of attention from the academic community. RNN-based methods cannot establish effective long-term dependencies among the input sequences when capturing the user’s motion patterns, resulting in inadequate exploitation of user preferences. Besides, the majority of prior studies often neglect high-order neighborhood information in users’ check-in trajectory and their social relationships, yielding suboptimal recommendation efficacy. To address these issues, this paper proposes a novel Double-Layer Attention Network model, named DLAN. Firstly, DLAN incorporates a multi-head attention module that can combine first-order and high-order neighborhood information in user check-in trajectories, thereby effectively and parallelly capturing both long- and short-term preferences of users and overcoming the problem that RNN-based methods cannot establish long-term dependencies between sequences. Secondly, this paper designs a user similarity weighting layer to measure the influence of other users on the target users leverage the social relationships among them. Finally, comprehensive experiments are conducted on user check-in data from two cities, New York (NYC) and Tokyo (TKY), and the results demonstrate that DLAN achieves a performance in Accuracy and Mean Reverse Rank enhancement by 8.07% -36.67% compared to the state-of-the-art method. Moreover, to investigate the effect of dimensionality and the number of heads of the multi-head attention mechanism on the performance of the DLAN model, we have done sufficient sensitivity experiments.
Picture fuzzy cubic graphs and their applications
Authors: Khatun Jasminara , Amanathulla Sk , Pal Madhumangal
Published: December 2023

In the realm of handling imprecise information, picture fuzzy cubic sets have emerged as a more versatile tool compared to cubic sets, cubic intuitionistic fuzzy sets, and similar models. These sets offer better adaptability, precision and compatibility with the system than existing fuzzy models. This paper extends the concept of picture fuzzy cubic sets to the domain of graph theory, introducing the novel concept of picture fuzzy cubic graphs that surpasses previous results in terms of generality. The paper explores various essential operations, including composition, the Cartesian product, P-join, R-join, P-union, R-union of picture fuzzy cubic graphs. It also investigates the order and degree of picture fuzzy cubic graphs. Furthermore, this work presents two practical applications of picture fuzzy cubic graphs. The first application involves computing the impact of other companies on a specific company and the second application focuses on evaluating the overall impact within a group of companies.
An automatic anomaly application detection system in mobile devices using FL-HTR-DBN and SKLD-SED K means algorithms
Authors: Lakshmana Kumar R. , Jayanthi S. , Muthu BalaAnand , Sivaparthipan C.B.
Published: December 2023

The proliferation of mobile technology has given rise to a multitude of applications, among them those designed with malicious intent, aimed at compromising the integrity of mobile devices (MDs). To combat this issue, this study introduces an innovative anomaly application detection system leveraging Federated Learning in conjunction with a Hyperbolic Tangent Radial-Deep Belief Network (FL-HTR-DBN). This system operates through two distinct phases: training and testing. During the training phase, the system first extracts log files and transforms them into a structured format, harnessing the power of the Hadoop System. Subsequently, these structured logs are converted into vector representations using the Updating Gate-BERT (UG-BERT) technique, thereby facilitating feature extraction. These features are then annotated utilizing the Symmetric Kullback Leibler Divergence squared Euclidean distance-based K Means (SKLD-SED K Means) algorithm. The FL-HTR-DBN model is subsequently trained using these labelled features. The detected anomalies are hashed and securely stored within an index tree, alongside their corresponding hashed Media Access Control (MAC) addresses. In the testing phase, log files are cross-referenced with the hashed index tree to identify potential anomalies. Notably, this novel approach outperforms many valuable outcomes in comparison with the existing approaches ConAnomaly, QLLog and LogCAD in terms of precision 97.5, recall 97.1, accuracy 95.9, F-measure 93.9, sensitivity 94.8 and specificity 95.9.
Optimizing graphics for understanding real-scene using 3D image registration and tracking and mapping
Authors: Alkhalifah Eman S.
Published: December 2023

A satisfactory graphic design and good-looking 3D models and environments are the backbones of a positive user experience, especially in Augmented Reality (AR) / Virtual Reality (VR) app development. Where these technologies is seen as the an excellent realm of human-computer interaction. The purpose is to fool the viewer by the seamless incorporation of simulated features. Every AR system relies on true interaction and three-dimensional registration to function properly. In this research, we present a strategy for real-world 3D image registration and tracking. The primary foci of this study are the first three stages: initial registrations and matrix acquisitions, road scene feature extraction, and virtual information registration. At initial registration, a rough virtual plane is estimated onto which the objects will be projected. To this, we propose YoloV3 for transferring features from a virtual to a real-world setting. The projection process concludes with a guess at the camera’s posture matrix. This tech is used in the vehicle’s head-up display to augment reality. The average time required to register a virtual item is 43 seconds. The final step in making augmented reality content is to merge the computer-generated images of virtual objects with real-world photographs in full colour. Our results indicate that this method is effective and precise for 3D photo registration but has the potential to dramatically increase the verisimilitude of AR systems.
RETRACTED: Enhanced edge detection model for low resolution images
Authors: Deepak Raj D.M. , Arulmurugan A. , Shankar G. , Arthi A. , Panthagani Vijaya Babu , Sandeep C.H.
Published: December 2023

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Advanced deep learning approach for enhancing crop disease detection in agriculture using hyperspectral imaging
Authors: Zekrifa Djabeur Mohamed Seifeddine , Lamani Dharmanna , Chaitanya Gogineni Krishna , Kanimozhi K.V. , Saraswat Akash , Sugumar D. , Vetrithangam D. , Koshariya Ashok Kumar , Manjunath Manthur Sreeramulu , Rajaram A.
Published: December 2023

Crop diseases pose significant challenges to global food security and agricultural sustainability. Timely and accurate disease detection is crucial for effective disease management and minimizing crop losses. In recent years, hyperspectral imaging has emerged as a promising technology for non-destructive and early disease detection in crops. This research paper presents an advanced deep learning approach for enhancing crop disease detection using hyperspectral imaging. The primary objective is to propose a hybrid Autoencoder-Generative Adversarial Network (AE-GAN) model that effectively extracts meaningful features from hyperspectral images and addresses the limitations of existing techniques. The hybrid AE-GAN model combines the strengths of the Autoencoder for feature extraction and the Generative Adversarial Network for synthetic sample generation. Through extensive evaluation, the proposed model outperforms existing techniques, achieving exceptional accuracy in crop disease detection. The results demonstrate the superiority of the hybrid AE-GAN model, offering substantial advantages in terms of feature extraction, synthetic sample generation, and utilization of spatial and spectral information. The proposed model’s contributions to sustainable agriculture and global food security make it a valuable tool for advancing agricultural practices and enhancing crop health monitoring. With its promising implications, the hybrid AE-GAN model represents a significant advancement in crop disease detection, paving the way for a more resilient and food-secure future.
Securing energy horizons: Cloud-driven based machine learning methods for battery management systems
Authors: Zekrifa Djabeur Mohamed Seifeddine , Saravanakumar R. , Nair Sruthi , Pachiappan Krishnagandhi , Vetrithangam D. , Kalavathi Devi T. , Ganesan T. , Rajendiran M. , Rukmani Devi S.
Published: December 2023

The increasing need for effective energy storage solutions has led to the prominence of lithium-ion batteries as a crucial technology across multiple industries. The proficient administration of these batteries is imperative in order to guarantee maximum efficiency, prolong their longevity, and uphold safety measures. This study presents a novel methodology for enhancing battery management systems (BMS) through the integration of cloud-based solutions, artificial intelligence (AI), and machine learning approaches. In this study, we present a conceptual framework that utilises cloud computing to augment the practical functionalities of battery management systems (BMS) specifically in the context of lithium-ion batteries. The incorporation of cloud computing facilitates the implementation of scalable data storage, remote monitoring, and processing resources, hence enabling the execution of real-time analysis and decision-making processes. By leveraging the capabilities of machine learning and artificial intelligence, our methodology focuses on addressing crucial battery metrics, including the state of charge (SoC) and state of health (SoH). Through the ongoing collection and analysis of data obtained from battery systems that are deployed in real-world settings, the framework iteratively improves its predictive models, hence facilitating precise assessment of battery states. Ensuring safety is a crucial element in the management of batteries. The solution we propose utilises anomaly detection algorithms driven by artificial intelligence to detect potential safety issues, facilitating prompt responses and mitigating dangerous circumstances. In order to showcase the efficacy of our methodology, we offer practical implementations in several industries, encompassing the integration of renewable energy, use of electric vehicles, and optimisation of industrial processes. Through the utilisation of cloud-based machine learning techniques, we are able to enhance the efficiency of energy storage and consumption, while simultaneously enhancing the dependability and security of battery systems. This study highlights the potential of the proposed framework to revolutionise battery management paradigms, thereby guaranteeing secure and efficient energy prospects for a sustainable future.
Relationship between playing-related factors and occupational balance in professional violinists
Authors: Yucel Hulya
Published: December 2023

BACKGROUND: Playing performance of musicians may affect their occupational balance. The violin is one of the riskiest string instruments for the musculoskeletal health. OBJECTIVE: To show the effect of socio-demographics, playing posture, pain, and functionality on occupational balance in professional violinists in Istanbul. METHODS: Forty-five violinists aged 29.1±10.6 years were included. The Personal Information Form, the Edinburgh Handedness Inventory, the Wong-Baker Faces Pain Rating Scale, the Disability of Arm, Shoulder and Hand - Sports/Musicians (DASH-SM), the Rapid Upper Limb Assessment, and the 11-item revised version of the Occupational Balance Questionnaire (OBQ11 - T) were used. Spearman correlation analysis was performed to examine the relationship between the variables and occupational balance. RESULTS: The only significant correlation was found between doing regular exercise and occupational balance (r = 0.539, p < 0.001) with those having an exercise habit reporting higher occupational balance scores. The mean pain score of the violinists increased from a pre-performing mean of 1.6±2.3 to a post-performance mean of 3.91±2.4. CONCLUSIONS: Musicians indicate that they practice physical exercise regularly. A strong methodological limitation of this study is that variables like exercise were evaluated with a self-reported survey which limited the analysis and so we hardly find any relationships between them. To the best of our knowledge, this is the first study to evaluate the relationship between playing-related factors and occupational balance in violinists. There may be other factors affecting occupational balance in violinists and also in the other musicians. Similar studies are needed in other countries also using different assessments specific to musicians.
Efficient Management of Information Communication Technology Resources in an Organisation
Authors: Matayo Vincent Amnon , Adamu Ahmed Aminu , Abdulganiyu Jamilu , Musa Mohammed Nura
Published: December 2023

The ongoing management of information and communication technology (ICT) resources in organisations is the main topic of this study. It begins by highlighting the main ideas discussed, including the definition of ICT resource management, its effects on effectiveness and productivity, cost optimisation, and security and risk reduction. The study illustrates the continuing nature of ICT resource management and underlines its importance in the rapidly changing technological environment of today. It emphasises how important it is for businesses to keep up with emerging technology and match its ICT infrastructure to evolving customer demands. Organisations can uncover inefficiencies and improvement opportunities through ongoing management, which boosts productivity and lowers costs. The study also emphasises the significance of risk mitigation in ICT resource management, highlighting the necessity of putting strong security measures in place and remaining attentive against new threats. The study's discussion of future trends in ICT resource management covers the use of cloud computing, the incorporation of automation and artificial intelligence, the opportunities and challenges presented by the Internet of Things, and the application of data analytics and predictive insights. These trends give businesses fresh options for allocating resources efficiently, increasing effectiveness, and selecting ICT resources wisely.
The role of children’s reception centers in the fight against child homelessness and neglect in the Kazakh SSR during the war years (1941-1945)
Authors:   Karaganda State University named after academician E. A. Buketov, Abdukarimova Zh. , Saktaganova Z. ,   Karaganda State University named after academician E. A. Buketov
Published: December 2023

Children’s reception centers-distributors of the NKVD (People’s Commissariat for Internal Affairs) during the Great Patriotic War played an important role in the fight against child neglect and homelessness. Their work helped to streamline the process of distributing Soviet children to children’s institutions of the People’s Commissariat for Health, the People’s Commissariat for Education, and the People’s Commissariat for Social Welfare. The article deals with the work of children’s reception centers in the Kazakh SSR in 1941-1945. On the basis of data from domestic and foreign archives, the authors show that child homelessness and neglect had a constant dynamic of growth during the war years, which became a huge problem of state scale. One of the elements of solving this problem was the mass work of children’s reception centers-distributors of the NKVD. The number of receivers in the country was growing together with their capacity. The authors have identified the main sources of minors’ admission to NKVD reception centers, the reasons why children were most often placed in difficult living conditions and their further placement. The authors also study the conditions of children’s stay in reception centers by regions of the Kazakh SSR. As well as problems related to the supply of food and clothing allowances, schooling and medical care for children in reception centers. The novelty of the work lies in the fact that the problems of functioning of children’s reception centers-distributors of the NKVD in the Kazakh SSR, as a measure to combat homelessness and neglect, are considered by the authors on the basis of previously unused archival documents.
Teachers understanding of the use of everyday contexts in the teaching of Mathematics at three selected urban junior secondary schools in Windhoek, Namibia
Authors: Kapenda Hileni M. , Kasanda Choshi D. , Naweseb Fillemon T.
Published: December 2023

The primary aim of this study was to gain insight into how effectively BETD teachers used everyday contexts to facilitate a meaningful understanding of the Mathematics content by the learners. The study used a qualitative research approach conceptualized within a constructivist framework. Nine Mathematics teachers from three junior secondary schools were purposively selected for the study. The data were collected using questionnaires, and interviews with the teachers. The results revealed varying levels of integration and effectiveness of everyday contexts used by the teachers to facilitate meaningful conceptual understanding of mathematics by the learners. The findings suggested that preference of procedural mathematical skills over conceptual understanding impeded the effective integration of contextual teaching. The teachers also regarded the use of everyday contexts as time consuming. From this study, it can be concluded that the teachers had a clear understanding of the essence of contextual teaching of Mathematics and its advantages. Nonetheless, several factors seemed to affect their use of everyday contexts in the teaching of Mathematics. There is a need to change the perceptions of the Mathematics teachers toward the use of everyday contexts as a waste of time if teachers are to use everyday experiences in their Mathematics classrooms.
Teachers use and integration of ICT in the teaching of Life Science
Authors: Simon Wilhelmina Etuna , Ngololo Elizabeth Ndeukumwa
Published: December 2023

Many developing countries recognised the importance of Information and Communication Technology (ICT) in education for teaching and learning. In Namibia, ICT use and integration in the classrooms remains limited. This study has sought to investigate how Life Science teachers with access to technologies use and integrate ICT into their classroom through collaborative and creative teaching. The study was designed as a qualitative research using a multiple case study approach. The study was guided by activity theory as a theoretical framework. Two Life Science teachers were observed and semi-structured interview were conducted. The findings of the study revealed that Life Science teachers demonstrated use of ICT in their classrooms through smart boards connected to e-Learning Management Systems and collaborated with each other by sharing notes but did not co-teach nor developed their own teaching materials. The study recommends that teachers be provided with the necessary tools and be trained to develop teaching materials, and to co-teach for purposes of enhancing collaborative teaching.
Lesson planning for teacher effectiveness
Authors: Manyarara Barbra C.
Published: December 2023

Well planned lessons enable learners to learn better and to develop better attitudes towards their work. The paper emanates from formal observations of the University of Zimbabwe Graduate Diploma in Education (Grad. D. E.) student teachers on three months teaching practice attachment. Many student teachers were found to be clearly on the path to becoming effective teachers but a sizeable portion, about 20-25%, were thought to be experiencing problems. In their planning of lessons, a wide range and variety of problems were noted. These include lack of real appreciation of the need to plan lessons, lack of the understanding that in order to be effective teachers they had to deploy different pedagogic approaches to meet the learning needs of the subject, inability to address lesson objectives and to match the maturity and social milieu of the learners in their care. Thus it is hoped that this paper may stimulate more interest in educators and student teachers alike beyond these student teachers passing or failing the teaching practice component to preparing really effective practitioners.
Social media in education contexts: implicationsfor critical media literacy and ethical challenges for teachers and educational institutions in Namibia
Authors: Haipinge Erkkie
Published: December 2023

The proliferation of social media and its use by students has raised a lot of research interest in attempts to seek ways of appropriating these new technologies for instructional and learning purposes. Critical media literacy deals with the critical analysis of various popular culture media in terms of their ideological and power implications, as well as the meaning of their messages. Although critical media literacy views new media as beneficial in their democratised nature, concerns remain about students’ ability to decipher and analyse the content that they both consume and create through social media. The two can be termed critical consumption and creation respectively. Similarly, social media poses potential ethical challenges for the teaching profession and for educational institutions. This is a qualitative research that employed the Phenomenography method where data was collected through focus group interviews. The paper sheds light on student teachers’ current social media practices. Analysing student teachers’ social media practices through the lens of critical media literacy, the paper highlights potential ethical challenges that are encountered while using social media in educational contexts. Recommendations include critical and ethically considerate approaches to using social media in educational contexts, as well as methods of incorporating the teaching critical media literacy skills in teacher education curricula.
ICTs in teacher education: enhancing quality language teaching and learning in Zimbabwe
Authors: Gora Ruth B. , Manyarara Barbra C.
Published: December 2023

113 Rapid advances in the development of ICT have been seen to offer new opportunities for enhancing the quality and effectiveness of language teaching and learning. The computer offers educators immense possibilities, and has been widely used, in computer assisted language learning (CALL). CALL has made significant advances towards finding a solution to and changing the way that language courses are conceived and taught. Although CALL developments tended to follow behaviouristic pedagogies that produced electronic imitations of drill and practice, for example, CALL now provides endless opportunities for interaction with a rich set of media types, characters and cultural information. However, educational institutions have lagged behind in fully recognising such opportunities. This prompts a call for re-orientation of education and training of language teachers. The paper therefore intends to guide teachers’ colleges on integrating ICT into their language learning and teaching activities. The guide is specifically aimed at language lecturers, lecturers-in-charge (LICs), heads of departments (HODs) and administrators in Zimbabwean teachers’ colleges while exploring the challenges of introducing ICT driven language education in traditionally face-to-face tertiary institutions in developing African countries.
Developing Art Market Desain in Medan (With a Neo-vernacular Approach)
Authors: Rifai Nasution Irwanda , Fitri Isnen
Published: December 2023

Abstract. Medan is a historical and multi-ethnic city which is one of the tourist destinations in Indonesia. Medan has many cultures that produce a lot of arts and crafts from each culture. However, the facilities and infrastructure for culture are still lacking. Only Cultural Park and PRSU are cultural spaces facilitated by the government. From the private sector, several galleries sell creative cultural industries that are managed privately. Therefore, this study aims as a boost where it is necessary to build a centre for a complete arts and crafts shop as a medium for art artisans to explore their talents and to help the economy of the surrounding community. Data collection in this study relies on secondary data obtained from libraries, related offices related to urban planning such as the Medan City Planning Agency and online sources. Then proceed with observing the location of potential sites as art markets. These observations emphasize apart from the location of the site as well as on the environment and infrastructure around the site. The results of the study show that: the right location for designing an art market in Medan is on Palang Merah street. This location is considered suitable because of its strategic location, close to the city centre and close to culinary spots. With this art market, it can become a workshop or marketing place for the creative industry in Medan.
Performance Indicators for Energi Management of Tourism in The Pangururan District Kabupaten Samosir
Authors: Haqqul Mulki Muhammad , Octofryana Yousca Marpaung Beny
Published: December 2023

. The Lake Toba area is a national tourist area visited by various tourists both from within and outside the country, and is included in the 88 national tours which are the parent of tourism development in Indonesia. One of the infrastructures that must be considered is the availability of electrical energy sources in the tourist area of ​​Lake Toba. Pangururan District as one of the tourism and administrative areas in the Lake Toba area must have sufficient electrical energy needs and become sustainable tourism. The purpose of this study was to examine the Performance of Tourism Energy Management in Pangururan District, Samosir Regency with an approach to analyzing the level of energy use and conservation, energy management programs, and utilization of renewable energy sources. The research method used is direct field observation and literature study, both theory and supporting documents in the research, which is then analyzed by interpreting the data obtained based on the theory and applicable policies. The results of this study are to identify that the need for electrical energy in the tourist area in the Pangururan sub-district is quite evenly distributed and the need for electrical energy is also met, but in the tourist area in the Pangururan sub-district conservation activities and the use of sustainable energy sources carried out by the government and the tourism business unit are still very low. a little. In addition, this research is expected to be a source of knowledge about Energy Management in the Tourism Sector.
Redesign Hotel Resort with Regionalism Architecture Approach In Lumban Pea Integrated Tourism Area Development Masterplan
Authors: Defriza Harisdani Devin , Berkat Simalango Arifanda
Published: December 2023

Lumban Pea Integrated Tourism Development Masterplan is one of the tourism development in the Toba Lake Area located in Toba Samosir Regency. In this masterplan, there are several tourism facilities, one of which is the hotel. The hotel design still does not show and apply the cultural values/identity of the surrounding environment in its design. The building is designed in a contemporary form that does not contain cultural attractions in the form of mass, facades, or cosmological values so that it is contrary to the development of tourism in the Lake Toba area which is still full of strong traditions. This study aims to improve the hotel design in the Master Plan by redesigning the hotel. The redesign of the hotel has created a resort hotel that is capable of blending contemporary design but also capturing its cultural side well. The redesign stage begins with conducting a survey, collecting data. In addition, the application of the Regionalism Architecture approach is one of the methodologies used to obtain design criteria which include cultural values, ornaments, forms, and other cultural resonances which are then analyzed and applied to the design. The hotel serves as a temporary residence and recreation facility for tourists. The redesign of this hotel by applying regional values to be a means of education and cultural attractions so that the culture is better known to the wider community and not eroded by the times. Besides, the redesign of this hotel can create a new economic center.
Design of Ulos Weaving Handicraft Centre in Samosir Regency with Green Architecture Approach
Authors: Tantya Febiola Sihotang Cathrine , Tamiami Fachrudin Hilma
Published: December 2023

Indonesia is famous for its rich culture, especially the traditional fabrics of each region.  North Sumatra is one of the contributions to that cultural heritage. Weaving Ulos or 'Kain Ulos' is an ancestral cultural heritage that is a symbol of the Batak Toba community in the form of long scarves whose existence decreases dramatically and can experience extinction. The lack of a place or container to preserve Ulos is one of the issues to consider. The design of this ulos weaving craft center must pay attention to the facilities, design concepts, and application of green architecture to the building. The aim is to design suitable support facilities for ulos weaving craft centers, making the ulos weaving craft center as one of the containers to preserve ulos weaving to improve the economy of the surrounding community and apply green architecture to the design to preserve the surrounding environment as well. The process of design approach used in this design is qualitative descriptive. Method by analyzing data collected through field observations to the location of craft centers and literature studies. Energy savings become important points that will be applied to the design of the craft center, such as utilizing sunlight, rainwater and also minimizing artificial air conditioning. Samosir is a strategic and supportive location to apply a green architectural approach in the design of this craft center.