bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Analysis of Machine Learning Techniques and Data Sources for Dead Tree Detection: What Is the Best Way to Go?
Authors: Matejčíková Júlia , Vébrová Dana , Surový Peter
Published: August 2024

In Central Europe, the extent of bark beetle infestation in spruce stands due to prolonged high temperatures and drought has created large areas of dead trees, which are difficult to monitor by ground surveys. Remote sensing is the only possibility for the assessment of the extent of the dead tree areas. Several options exist for mapping individual dead trees, including different sources and different processing techniques. Satellite images, aerial images, and images from UAVs can be used as sources. Machine and deep learning techniques are included in the processing techniques, although models are often presented without proper realistic validation.This paper compares methods of monitoring dead tree areas using three data sources: multispectral aerial imagery, multispectral PlanetScope satellite imagery, and multispectral Sentinel-2 imagery, as well as two processing methods. The classification methods used are Random Forest (RF) and neural network (NN) in two modalities: pixel- and object-based. In total, 12 combinations are presented. The results were evaluated using two types of reference data: accuracy of model on validation data and accuracy on vector-format semi-automatic classification polygons created by a human evaluator, referred to as real Ground Truth. The aerial imagery was found to have the highest model accuracy, with the CNN model achieving up to 98% with object classification. A higher classification accuracy for satellite imagery was achieved by combining pixel classification and the RF model (87% accuracy for Sentinel-2). For PlanetScope Imagery, the best result was 89%, using a combination of CNN and object-based classifications. A comparison with the Ground Truth showed a decrease in the classification accuracy of the aerial imagery to 89% and the classification accuracy of the satellite imagery to around 70%. In conclusion, aerial imagery is the most effective tool for monitoring bark beetle calamity in terms of precision and accuracy, but satellite imagery has the advantage of fast availability and shorter data processing time, together with larger coverage areas.
Assessment of Hygroscopic Behavior of Arctic Aerosol by Contemporary Lidar and Radiosonde Observations
Authors: Eggers Nele , Graßl Sandra , Ritter Christoph
Published: August 2024

This study presents the hygroscopic properties of aerosols from the Arctic free troposphere by means of contemporary lidar and radiosonde observations only. It investigates the period from the Arctic Haze in spring towards the summer season in 2021. Therefore, a one-parameter growth curve model is applied to lidar data from the Koldewey Aerosol Raman Lidar (AWIPEV in Ny-Ålesund, Svalbard) and simultaneous radiosonde measurements. Hygroscopic growth depends on different factors like aerosol diameter and chemical composition. To detangle this dependency, three trends in hygroscopicity are additionally investigated by classifying the aerosol first by its dry color ratio, and then by its season and altitude. Generally, we found a complex altitude dependence with the least hygroscopic particles in the middle of the troposphere. The most hygroscopic aerosol is located in the upper free troposphere. A hypothesis based on prior lifting of the particles is given. The expected trend with aerosol diameter is not observed, which draws attention to the complex dependence of hygroscopic growth on geographical region and altitude, and to the development of backscatter with the aerosol size itself. In a seasonal overview, two different modes of stronger or weaker hygroscopic particles are additionally observed. Furthermore, two special days are discussed using the Mie theory. They show, on the one hand, the complexity of analyzing hygroscopic growth by means of lidar data, but on the other hand, they demonstrate that it is in fact measurable with this approach. For these two case studies, we calculated that the aerosol effective radius increased from 0.16μm (dry) to 0.18μm (wet) and from 0.28μm to 0.32μm for the second case.
Developing a Generalizable Spectral Classifier for Rhodamine Detection in Aquatic Environments
Authors: Pérez-García Ámbar , Martín Lorenzo Alba , Hernández Emma , Rodríguez-Molina Adrián , van Emmerik Tim H. M. , López José F.
Published: August 2024

In environmental studies, rhodamine dyes are commonly used to trace water movements and pollutant dispersion. Remote sensing techniques offer a promising approach to detecting rhodamine and estimating its concentration, enhancing our understanding of water dynamics. However, research is needed to address more complex environments, particularly optically shallow waters, where bottom reflectance can significantly influence the spectral response of the rhodamine. Therefore, this study proposes a novel approach: transferring pre-trained classifiers to develop a generalizable method across different environmental conditions without the need for in situ calibration. Various samples incorporating distilled and seawater on light and dark backgrounds were analyzed. Spectral analysis identified critical detection regions (400–500 nm and 550–650 nm) for estimating rhodamine concentration. Significant spectral variations were observed between light and dark backgrounds, highlighting the necessity for precise background characterization in shallow waters. Enhanced by the Sequential Feature Selector, classification models achieved robust accuracy (>90%) in distinguishing rhodamine concentrations, particularly effective under controlled laboratory conditions. While band transfer was successful (>80%), the transfer of pre-trained models posed a challenge. Strategies such as combining diverse sample sets and applying the first derivative prevent overfitting and improved model generalizability, surpassing 85% accuracy across three of the four scenarios. Therefore, the methodology provides us with a generalizable classifier that can be used across various scenarios without requiring recalibration. Future research aims to expand dataset variability and enhance model applicability across diverse environmental conditions, thereby advancing remote sensing capabilities in water dynamics, environmental monitoring and pollution control.
Fine-Scale Mangrove Species Classification Based on UAV Multispectral and Hyperspectral Remote Sensing Using Machine Learning
Authors: Yang Yuanzheng , Meng Zhouju , Zu Jiaxing , Cai Wenhua , Wang Jiali , Su Hongxin , Yang Jian
Published: August 2024

Mangrove ecosystems play an irreplaceable role in coastal environments by providing essential ecosystem services. Diverse mangrove species have different functions due to their morphological and physiological characteristics. A precise spatial distribution map of mangrove species is therefore crucial for biodiversity maintenance and environmental conservation of coastal ecosystems. Traditional satellite data are limited in fine-scale mangrove species classification due to low spatial resolution and less spectral information. This study employed unmanned aerial vehicle (UAV) technology to acquire high-resolution multispectral and hyperspectral mangrove forest imagery in Guangxi, China. We leveraged advanced algorithms, including RFE-RF for feature selection and machine learning models (Adaptive Boosting (AdaBoost), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Light Gradient Boosting Machine (LightGBM)), to achieve mangrove species mapping with high classification accuracy. The study assessed the classification performance of these four machine learning models for two types of image data (UAV multispectral and hyperspectral imagery), respectively. The results demonstrated that hyperspectral imagery had superiority over multispectral data by offering enhanced noise reduction and classification performance. Hyperspectral imagery produced mangrove species classification with overall accuracy (OA) higher than 91% across the four machine learning models. LightGBM achieved the highest OA of 97.15% and kappa coefficient (Kappa) of 0.97 based on hyperspectral imagery. Dimensionality reduction and feature extraction techniques were effectively applied to the UAV data, with vegetation indices proving to be particularly valuable for species classification. The present research underscored the effectiveness of UAV hyperspectral images using machine learning models for fine-scale mangrove species classification. This approach has the potential to significantly improve ecological management and conservation strategies, providing a robust framework for monitoring and safeguarding these essential coastal habitats.
Path Planning of UAV Formations Based on Semantic Maps
Authors: Sun Tianye , Sun Wei , Sun Changhao , He Ruofei
Published: August 2024

This paper primarily studies the path planning problem for UAV formations guided by semantic map information. Our aim is to integrate prior information from semantic maps to provide initial information on task points for UAV formations, thereby planning formation paths that meet practical requirements. Firstly, a semantic segmentation network model based on multi-scale feature extraction and fusion is employed to obtain UAV aerial semantic maps containing environmental information. Secondly, based on the semantic maps, a three-point optimization model for the optimal UAV trajectory is established, and a general formula for calculating the heading angle is proposed to approximately decouple the triangular equation of the optimal trajectory. For large-scale formations and task points, an improved fuzzy clustering algorithm is proposed to classify task points that meet distance constraints by clusters, thereby reducing the computational scale of single samples without changing the sample size and improving the allocation efficiency of the UAV formation path planning model. Experimental data show that the UAV cluster path planning method using angle-optimized fuzzy clustering achieves an 8.6% improvement in total flight range compared to other algorithms and a 17.4% reduction in the number of large-angle turns.
Continuous Wavelet Transform Peak-Seeking Attention Mechanism Conventional Neural Network: A Lightweight Feature Extraction Network with Attention Mechanism Based on the Continuous Wave Transform Peak-Seeking Method for Aero-Engine Hot Jet Fourier Transform Infrared Classification
Authors: Du Shuhan , Han Wei , Kang Zhenping , Lu Xiangning , Liao Yurong , Li Zhaoming
Published: August 2024

Focusing on the problem of identifying and classifying aero-engine models, this paper measures the infrared spectrum data of aero-engine hot jets using a telemetry Fourier transform infrared spectrometer. Simultaneously, infrared spectral data sets with the six different types of aero-engines were created. For the purpose of classifying and identifying infrared spectral data, a CNN architecture based on the continuous wavelet transform peak-seeking attention mechanism (CWT-AM-CNN) is suggested. This method calculates the peak value of middle wave band by continuous wavelet transform, and the peak data are extracted by the statistics of the wave number locations with high frequency. The attention mechanism was used for the peak data, and the attention mechanism was weighted to the feature map of the feature extraction block. The training set, validation set and prediction set were divided in the ratio of 8:1:1 for the infrared spectral data sets. For three different data sets, the CWT-AM-CNN proposed in this paper was compared with the classical classifier algorithm based on CO2 feature vector and the popular AE, RNN and LSTM spectral processing networks. The prediction accuracy of the proposed algorithm in the three data sets was as high as 97%, and the lightweight network structure design not only guarantees high precision, but also has a fast running speed, which can realize the rapid and high-precision classification of the infrared spectral data of the aero-engine hot jets.
Enhancing Extreme Precipitation Forecasts through Machine Learning Quality Control of Precipitable Water Data from Satellite FengYun-2E: A Comparative Study of Minimum Covariance Determinant and Isolation Forest Methods
Authors: Shen Wenqi , Chen Siqi , Xu Jianjun , Zhang Yu , Liang Xudong , Zhang Yong
Published: August 2024

Variational data assimilation theoretically assumes Gaussian-distributed observational errors, yet actual data often deviate from this assumption. Traditional quality control methods have limitations when dealing with nonlinear and non-Gaussian-distributed data. To address this issue, our study innovatively applies two advanced machine learning (ML)-based quality control (QC) methods, Minimum Covariance Determinant (MCD) and Isolation Forest, to process precipitable water (PW) data derived from satellite FengYun-2E (FY2E). We assimilated the ML QC-processed TPW data using the Gridpoint Statistical Interpolation (GSI) system and evaluated its impact on heavy precipitation forecasts with the Weather Research and Forecasting (WRF) v4.2 model. Both methods notably enhanced data quality, leading to more Gaussian-like distributions and marked improvements in the model’s simulation of precipitation intensity, spatial distribution, and large-scale circulation structures. During key precipitation phases, the Fraction Skill Score (FSS) for moderate to heavy rainfall generally increased to above 0.4. Quantitative analysis showed that both methods substantially reduced Root Mean Square Error (RMSE) and bias in precipitation forecasting, with the MCD method achieving RMSE reductions of up to 58% in early forecast hours. Notably, the MCD method improved forecasts of heavy and extremely heavy rainfall, whereas the Isolation Forest method demonstrated a superior performance in predicting moderate to heavy rainfall intensities. This research not only provides a basis for method selection in forecasting various precipitation intensities but also offers an innovative solution for enhancing the accuracy of extreme weather event predictions.
Remote Sensing of Target Object Detection and Identification II
Authors: Tripicchio Paolo
Published: August 2024

The ability to detect and identify target objects from remote images and acquisitions is paramount in remote sensing systems for the proper analysis of territories [...]
An Integrated Bayesian Best–Worst Method and Consensus-Based Intuitionistic Fuzzy Evaluation Based on Distance from Average Solution Approach for Evaluating Alternative Aircraft Models from a Sustainability Perspective
Authors: Arı Ergun , Dursun Mehtap
Published: August 2024

Sustainability in transportation is vital for lessening environmental effects and ensuring the long-term viability of the transportation industry. The aviation sector, a significant player in sustainable transport, has encountered obstacles in reducing its ecological footprint, especially in aircraft design and operation. Symmetry and asymmetry exist widely in the aviation sector, as in other industrial applications. Multicriteria decision making (MCDM) is an important research topic that is widely applied to practical decision-making problems and is considered a complex tool with which to balance the symmetry between goals and conflicting criteria. This research assesses different airplane models in order to pinpoint the most environmentally friendly options using the Bayesian best–worst (BWM) method for evaluating criteria and the consensus-based intuitionistic fuzzy evaluation based on distance from average solution (IF EDAS) method for assessing alternatives. The Bayesian BWM approach facilitates group decision making on criteria evaluation and systematically evaluates factors like fuel efficiency, emissions, and noise levels, offering a holistic view of each airplane model’s sustainability performance. Conversely, consensus-based IF EDAS allows for the ranking of alternatives based on their distance to the average solution for a sustainable airplane model while concurrently considering multiple criteria, guiding decisionmakers to a consensus and eliminating the asymmetry between opinions before the final decision. This study reveals that technical features are the critical criteria for airplanes and significantly influence alternative rankings. The findings indicate that the chosen decision criteria greatly impact the selection of the most sustainable airplane model as part of a sustainable transportation system, potentially altering ranking orders.
Resistance of Transgenic Maize Cultivars to Mycotoxin Production—Systematic Review and Meta-Analysis
Authors: Gomes Ana Silvia de Lara Pires Batista , Weber Saulo Henrique , Luciano Fernando Bittencourt
Published: August 2024

Approximately 25% of cereal grains present with contamination caused by fungi and the presence of mycotoxins that may cause severe adverse effects when consumed. Maize has been genetically engineered to present different traits, such as fungal or insect resistance and herbicide tolerance. This systematic review compared the observable quantities, via meta-analysis, of four mycotoxins (aflatoxins—AFL, fumonisins—FUM, deoxynivalenol—DON, zearalenone—ZEA) between genetically modified (GM) and conventional maize kernels. This study was conducted following the PRISMA guidelines, with searches performed using PubMed, Web of Science, Scopus, Google Scholar, and CAPES journals databases. Analyses were conducted using RevMan v.5.4 software. Transgenic maize showed a 58% reduction in total mycotoxins (p < 0.001) compared to conventional maize. FUM were the most impacted, with a 59% reduction (p < 0.001) in GM maize. AFL and ZEA levels were also lower in GM maize by 49% (p = 0.02) and 51% (p < 0.001), respectively. On the other hand, DON levels increased by 6% (p < 0.001) in GM maize compared to conventional maize. However, results for ZEA and DON were inconclusive due to the limited research and sample sizes. We conclude that transgenic maize reduces total mycotoxins by over 50%, primarily fumonisin and aflatoxin. Most studies presented maize varieties that were resistant to insects or herbicides, not fungal pathogens, showing a positive collateral effect of these genetic alterations. Therefore, transgenic maize appears to be a safer product for animal and human consumption from a toxicological point of view. Further studies with larger sample sizes are needed to confirm our findings for ZEA and DON in transgenic maize.
Gestión pública educativa en los procesos de tutoría integral en Perú
Authors: Lau Li Alicia Yunching
Published: August 2024

La gestión pública educativa es crucial para la modernización de la a––dministración pública. Este estudio examinó la influencia de la gestión pública educativa en los procesos de tutoría integral. La investigación, de enfoque cuantitativo, analizó las variables de gestión pública educativa y procesos de tutoría integral. Se aplicó un cuestionario a 18 gestores públicos y se utilizó el software estadístico SPSS versión 26 para el análisis de datos. Los resultados revelaron una relación positiva significativa entre la gestión pública educativa en sus cuatro dimensiones (estratégica, administrativa, pedagógica y comunitaria) y el proceso de tutoría integral. Se sugiere la implementación de procesos de tutoría integral respaldados por políticas educativas, así como la modernización de la gestión pública educativa mediante el uso de herramientas que promuevan el bienestar estudiantil y generen un impacto positivo en el desarrollo social y nacional.
Felette igen nagy jó – Intenzitásjelölők variációja 16–18. századi regiszterekben
Authors: Varga Mónika
Published: August 2024

The history of Hungarian intensifiers – elements that scale upwards the strength of the meaning of the item they modify – is unexplored. The present paper studies common adverbial intensifiers with similar meaning to ‘very’, such as igen, felette ~ felettébb, nagy and nagyon. The analysis also focuses on register differences in Middle Hungarian based on two corpora, TMK and KED, containing private letters, records of witch trials, dramas and memoirs from the period between the 16th and the 18th century. The main results are as follows: during the 16th and 18th century (and even later), igen was the dominant default variant in every text type; nevertheless, nagyon starts to spread in the 18th century, especially in witch trials, although this text type show a somewhat modest preference of intensifiers in general, compared to letters, memoirs and dramas. However, considering the latter cases, particular authors of a given period had an effect on the use of the intensifiers, and not the registers per se (although writers of memoirs provided rather extreme frequencies). From a structural and semantic point of view, the targets themselves and the word class of the target also had an effect on the distribution and preference of one or other variant of the studied intensifiers.
The Benefits, Challenges, and Future of Blockchain and The Internet of Things
Authors: Mufiidah Andi Nabiilah , Destiani Romanda Dwi
Published: August 2024

The Internet of Things (IoT) has expanded internet connectivity beyond computers andpeople to include most objects in our environment. The Internet of Things (IoT) can connectbillions of items at once, which has the effect of improving the need for information sharing andultimately enhancing our quality of life. Due to its centralized server/client approach, which limitsthe IoT's potential benefits, there are numerous obstacles to IoT adoption in the real world. Forinstance, the network's excessive number of IoT items can cause scalability and securityproblems. The server/client approach necessitates that all devices connect to and areauthenticated by the server, creating a single point of failure. As a result, shifting the IoT systemto a decentralized approach might be the best course of action. Blockchain is one of the mostwell-known decentralization technologies. The Blockchain is a potent technology thatdecentralizes administration and computation processes, which can address many IoTproblems, particularly security. The benefits and difficulties of the integration of the blockchainwith the IoT are highlighted in this paper's review. There is also a discussion of the potentialresearch avenues for blockchain and IoT. We conclude that combining blockchain technologywith IoT can result in a potent strategy that can significantly open the door for new businessmodels and distributed applications
Blockchain Technology Application for Information System Security in Education
Authors: Ajeng Michiko , Kirei Anaya , Amanda Keiko
Published: August 2024

The benefit of using blockchain technology for information system security in the field of education is that all entered data cannot be easily faked, lost, or damaged. With blockchain, one can also communicate data and information instantly and be decentralized without depending on third parties. Blockchain is a distributed ledger that effectively and efficiently records transactions between two parties in a verifiable and everlasting way. Yet, even though blockchain technology has not yet been applied extensively in the field of education Yet, to meet the goals of this study and produce results that apply to the field of education, researchers attempt to assess the security of information systems in education using fingerprints by integrating cryptographic hash security sensors. These topics and the SWOT analysis used in this research approach will be explored.
EXPERIENCE OF IMPROVEMENT FELLING IN ARTIFICIAL ELM-MAPLE STANDS OF NORTHERN KAZAKHSTAN
Authors: Панкратов Владислав Константинович , Данчева Анастасия Васильевна , Залесов Сергей Вениаминович , Платонов Евгений Петрович
Published: August 2024

Определена лесоводственная эффективность рубок ухода различной интенсивности в искусственных вязово-кленовых насаждениях. Указанные насаждения были созданы в условиях сухой типчаково-ковыльной степи на территории санитарно-защитной зоны г. Нур-Султан. В качестве главных пород были выбраны вяз приземистый (Ulmus pumila L.) и клен ясенелистный (Acer negundo L.). Схема смешения при посадке рядовая. Состав древостоев 8В2К. Установлено, что рубки ухода интенсивностью 22, 32 и 60 % по количеству деревьев (густоте) в высокополнотных вязово-кленовых насаждениях второго класса возраста способствуют увеличению основных таксационных показателей. В частности, средние диаметр и высота увеличиваются на 25-26 и 14-17 %, соответственно. При этом спустя 4 года после рубок абсолютная полнота и запас увеличились на 7-27 и 7-33%, соответственно, в сравнении с аналогичными показателями в контрольном древостое. В насаждениях, пройденных рубками ухода, отмечается увеличение показателей состояния, индексов относительного жизненного состояния по густоте и крупности, снижение коэффициента напряженности роста до значений, при которых древостои характеризуются, как «здоровые» или биологически устойчивые. Рубки ухода способствуют увеличению средних значений биометрических показателей кроны на 10-40% в сравнении с контролем. Лучшим вариантом изреживания для поддержания биологической устойчивости вязово-кленовых насаждений на данном этапе их роста является 22-32 % по густоте.

The paper deals with definition of various intensity improvement felling in artificial elm-maple stands. The specified plantation were created in dry fescue-feather grass steppe in the sanitary-protective zone of Nur-Sultan city. A squat-elm (Ulmus pumila L.) and ash-leaved maple (Aces negundo L.) have been chosen as the main breeds. The pattern is drill sowing. The stands composition is 2B2K. It was established that improvement felling of 22, 32 and 60% intensity as concerns their density in highly density elm-maple stands of the second-aged klass contributes to the main taxation indicators. An particular, the average diameter and height are increased by 25-26 and 14-17% accordingly. At the same time after 4 years of felling the absolute normality and growing stock were increased by 7-27 and 7-33% accordingly compared with this figure in the control stand. An stands passed by improvement felling it is noted increasing of relative leving condition index by density and size, decreasing in tension coefficient of growth to values at which the stands are characterized as healthy or biologically stable. Improvement felling promotes increasing of average biometric indicator value of the crown by 10-40% as compared with the control. The best option for thinning to maintain elm-maple plantation biologic stability at the given growth stage is 22-32% in density.
NATURE REFORESTATION ON SEISMIC PROFILES IN THE CONDITIONS OF THE WEST - SIBERIAN NORTH TAIGA LOWLAND FOREST REGION
Authors: Морозов Андрей Евгеньевич , Осипенко Регина Александровна , Башегуров Константин Андреевич , Залесов Сергей Вениаминович
Published: August 2024

На основании материалов 15 пробных площадей проанализирована динамика количественных и качественных показателей подроста на сейсморазведочных профилях в условиях зеленомошной группы типов леса Западно-Сибирского северо-таежного равнинного лесного района Ханты-Мансийского автономного округа - Югры. Установлено, что при разрубке сейсморазведочных профилей шириной 4 м и проведении сейсморазведочных работ в зимний период при промерзшем грунте и глубине снега более 50 см они не оказывают существенного влияния на экологическую обстановку. Процесс естественного формирования древостоев на сейсморазведочных профилях протекает успешно. Уже через 4 года после завершения сейсморазведочных работ густота жизнеспособного подроста в пересчете на крупный составляет 10,9 тыс. шт/га, в том числе хвойного - 2,6 тыс. шт/га и сосны сибирской - 1,6 тыс. шт/га. Спустя 9 лет после разрубки сейсморазведочных профилей общая густота подроста в пересчете на крупный достигает 19,0 тыс. шт/га, в т.ч. хвойного - 8,3 тыс. шт/га и сосны сибирской - 5,9 тыс. шт/га, что позволяет перевести профили в покрытые лесной растительностью земли. Быстрое зарастание сейсморазведочных профилей хозяйственно ценными породами исключает необходимость проектирования мероприятий по лесовосстановлению, а отсутствие системы просек позволяет рекомендовать перевод сейсморазведочных профилей в объекты лесной инфраструктуры.

On the basis of the materials from 15 test plots, the dynamics of quantitative and qualitative indicators of undergrowth on seismic profiles in the conditions of greenish group of forest types in the western Siberian north taiga pain forest region in Khanty-Mansiysk Autonomous Okrug - Yugra was analyzed. It was found that when developing seismic profiles with a width of 4 meters and carrying out seismic surveys in winter with frozen soil and a snow depth at more than 50 sm they do not effect significantly on the ecologic situation. The process of stand natural for motion on seismic profiles proceeds successfully. Already four years after the completion of seismic exploration, the density of viable undergrowth in terms of large is 10.9 th. pc/ha, including coniferous 2.6 th. pcs/ha and Siberian pine 1.6 th. pcs/ha. 9 years after the seismic profiles separation, the total density of the adolescent, in terms of large ones reaches 19.0 th. pa/ha, chelating coniferous - 8.3 th. pa/ha and Siberian pine - 5.9 th. pcs/ha, which allows the profill to be transferred to the land covered with forest vegetation. Rapid overgrowth of seismic profiles with economically valuable species eliminates the necessity to design measures for reforestation, the absence of breanth rough system maxes possible to recommend the transfer of seismic profiles to forest infrastructure facilities.
Entre cuentos y juegos: el desarrollo del discurso explicativo en el hogar durante la primera infancia
Authors: Stein Alejandra , González Lynn Eliana Belén , Franco Accinelli Ailín Paula
Published: August 2024

El presente trabajo se propone contribuir al estudio de la adquisición de la explicación como forma de discurso extendido en la infancia. Se analizó comparativamente el habla explicativa producida en situaciones de lectura de cuento y de juego con 12 niños de 30 meses de edad y sus cuidadores, residentes en hogares de sectores medios de la Ciudad de Buenos Aires, Argentina. Las unidades explicativas identificadas (256) fueron analizadas según el tipo de explicación, quién las iniciaba y producía, y su nivel de distanciamiento respecto del contexto físico inmediato. Los resultados pusieron de manifiesto que, en ambos contextos de actividad, los participantes produjeron distintos tipos de explicaciones, en su mayoría, iniciadas por la madre. Durante el juego, los niños produjeron más explicaciones de manera independiente. En estas situaciones también se registró una tendencia hacia un predominio de explicaciones de nivel alto que contribuyen al uso de habla no inmediata de gran relevancia para el desarrollo cognitivo y socioemocional infantil. En conjunto, los hallazgos del estudio proporcionan evidencia adicional acerca de la importancia de las experiencias infantiles tempranas en el hogar para el desarrollo discursivo y contribuyen a dar cuenta de la especificidad de los contextos de actividad considerados para promover el desarrollo del discurso explicativo.
MODEL KEWIRAUSAHAAN SOSIAL PADA LEMBAGA AMIL ZAKAT DI LIHAT DARI SUDUT PANDANG BISNIS
Authors: Waldelmi Idel , Aquino Afvan
Published: August 2024

An approach that combines entrepreneurial principles with a social mission to have a positive impact on society, especially through the management of zakat funds. In this context, amil zakat institutions not only act as collectors and distributors of zakat, but also as agents of change who initiate sustainable programs that can improve the welfare of the community at large. There is a uniqueness of social entrepreneurship practiced in amil zakat institutions. This study used a sample of 200 administrators of amil zakat institutions in Pekanbaru City and was collected using an online questionnaire. Data were analyzed using descriptive techniques. The results showed that the social entrepreneurship that has been carried out by managers in the Riau province Amil Zakat Institution can be said to be good although there must still be continuous evaluation to improve the ability of social entrepreneurship in the ranks of the administrators.
BUDAYA FILANTROPI ISLAM PADA BMT SEBAGAI WADAH BISNIS BERBASIS ISLAM
Authors: Despileny Iren , Nurnasrina Nurnasrina
Published: August 2024

Organizational culture in Islamic philanthropy is a reflection of Islamic values, principles, and ethics that are carried out in various charitable and social activities. Islamic philanthropic organizations have a mission to help the community, especially the underprivileged, by distributing resources fairly and sustainably. Through descriptive research with a sample of 100 BMT members in Pekanbaru, the results showed that the culture of Islamic philanthropy is interpreted in the criteria of good enough to good, this indicates that the culture of Islamic philanthropy that has been running in BMT can be said to be quite good even though there must still be continuous evaluation to improve improvement and perfect the culture in an Islamic manner.
Keywords: Organizational Culture, BMT, Islamic Philanthropy
Material Ecologies: Defining Alternative Grounds
Authors:   Cornell University, Hong Zaneta
Published: August 2024

Materials, in essence, do not arrive to us as neutral entities – without baggage, cost, or meaning. Materials have had previous lives. They have been extracted, amassed, and compiled from previous forms and valued as lucrative economic and cultural commodities. They have been involved in previous relationships, as part of other masses that once occupied prior territories, and they have taken part in various industrial and domestic chronicles.
DYNAMIC-ENERGY ANALYSIS OF A ROTARY TILLER WITH A VERTICAL ROTATION AXIS
Authors: TARVERDYAN Arshaluys , ALTUNYAN Artur , HARUTYUNYAN Gevorg , GRIGORYAN Аlbert
Published: August 2024

The article consideres the issue of dynamic and energy analysis of the rotary tiller with planetary transmission gear and vertical rotation axis designed for orchards and vineyards. In the result of investigations, analytical expressions have been derived, which enable to determine the resistance force factors of the cultivated medium affecting the rotary tiller and to set up their changing patterns during a single rotation of the rotor in conditions of forward movement of the aggregate/working unit. It has been confirmed that in case of binary symmetric blades located at 120 degree, the resistance forces transmitted from the tiller satellites to the rotor shaft mutually balance each other, as a result of which the traction resistance force of the unit receives the possible minimum value. As regard to the resistance moments transmitted from the tiller satellites to the rotor shaft and to their main moments, it should be noted that they change significantly during a single rotation of the rotor. Particularly, the extreme values of the main moment for each tiller satellite are obtained at the finite points of the rotor’s diameter perpendicular to the forward movement of the tillage machine. Based on the driving and resistance force factors of the machine, as well as the differential equation of the motion, the term has been identified by means of the energy research of the rotary tiller, in case of which the angular acceleration of the rotor’s shaft will be equal to zero and the machine will operate without oscillations and vibrations.
Path Analysis Tingkat Pengangguran Terbuka dan Kemiskinan di Kabupaten Langkat
Authors: Harahap Muhammad Arfan , Hasibuan Sri Wahyuni
Published: August 2024

Pengangguran dan kemiskinan tetap menjadi masalah yang terus diupayakan solusinya oleh pemerintah, khususnya pemerintah daerah. Analisis pengangguran dan kemiskinan di setiap daerah dapat berbeda-beda tergantung pada data yang digunakan. Penelitian ini mengungkap data terbaru terkait variabel penelitian di Kabupaten Langkat. Analisis jalur digunakan dalam penelitian ini untuk mengukur secara akurat pengaruh variabel melalui variabel intervening dengan data makroekonomi yang dinamis. Model regresi pada sub-struktural 1 menunjukkan bahwa terdapat pengaruh langsung pertumbuhan ekonomi dan inflasi terhadap pengangguran dengan pengaruh simultan sebesar 65%. Selain itu, model regresi sub-struktural 2 menunjukkan bahwa terdapat pengaruh langsung pengangguran terhadap kemiskinan, sementara pertumbuhan ekonomi dan inflasi tidak memiliki pengaruh langsung. Namun, secara simultan, pertumbuhan ekonomi, inflasi, dan pengangguran menunjukkan pengaruh sebesar 85%. Temuan lain menggunakan analisis jalur menunjukkan adanya pengaruh tidak langsung pertumbuhan ekonomi dan inflasi terhadap kemiskinan melalui pengangguran. Hasil penelitian ini memperkuat literatur terkait pengangguran dan kemiskinan serta menambahkan data baru pada studi serupa di berbagai daerah di Indonesia. Temuan ini diharapkan dapat digunakan sebagai referensi dalam pembuatan kebijakan terkait pengurangan pengangguran dan penanggulangan kemiskinan di Kabupaten Langkat.
A Comparative Linguistic Study on the System of Presentation and Delay between Arabic and Indonesian Languages
Authors: Hariyanto  , Muhaimin Abd , Robati Kisti
Published: August 2024

This study aims to uncover similarities and differences between these languages, particularly from a grammatical perspective. To obtain necessary data, the researcher employed a descriptive-analytical method utilizing relevant literature and research. The comparative analysis method was used to contrast the systems of anteriority and posteriority between the two languages, deriving similarities and differences. Based on the findings, this research identified eight points of similarity in the anteriority and posteriority system between Arabic and Indonesian grammar: placing the modifier before the modified, placing the verb before its object originally, placing the first object before the second object, permitting the anteriority of time and place adverbs and their posteriority, similar to their referents, placing the number before the counted object, delaying moral emphasis (all, every) on the affirmed, permitting the posteriority of the object and the anteriority of the subject. Regarding points of divergence, particularly in the anteriority and posteriority system between Arabic and Indonesian grammar, nine aspects were identified: Arabic has rules allowing, necessitating, or prohibiting the anteriority of the modifier to its referent, the anteriority of the object to the verb and subject, and the anteriority of the counted object to the number sometimes. Additionally, Arabic differs from Indonesian in anteriority of demonstrative pronouns to their referents, anteriority of the subject to the verb in the Indonesian structure, anteriority and posteriority of interrogative pronouns in Indonesian, anteriority of the adjective to its noun in Indonesian, and the anteriority of the absolute object in Indonesian, contrasting with Arabic norms.
Um recorte no universo musical de 'Chants populaires'
Authors: Serra dos Santos Elizabeth
Published: August 2024

Considerando a relação que o poeta contemporâneo francês Philippe Beck (1963-) estabelece entre poesia e música, o presente artigo propõe investigar o fraseado rítmico de Chants populaires (2007), observando como o autor transforma a palavra em objeto de pensamento por meio da música. De fato, a sonoridade própria, cortante dos versos de Beck leva o leitor/ouvinte a escutá-los novamente para ser capaz de produzir significados. Os cantos de Beck, uma reescrita de 72 contos dos irmãos Grimm, retomam questões sobre identidade e nação, que se reapresentam ao mundo contemporâneo. O próprio autor traz em sua memória emocional vestígios das discórdias entre França e Alemanha, que abalaram a formação de um conceito de identidade nacional. Natural de Estrasburgo, Beck escreve seus poemas em um “quase-francês” - como ele mesmo chama - uma língua atravessada por forças históricas. Segundo Beck, esse francês alsaciano torna o canto de sua poesia um canto maculado, aberto a “um sentido sempre por fazer”, nas palavras de Jean – Luc Nancy. Este trabalho se concentrará em três aspectos centrais da poesia de Beck: a elisão dos artigos; as intensificações; e os neologismos, tomando por base a análise de um dos poemas da obra em questão.
Relasi Tawassul dan Tabarruk Menurut Sulaiman al-Jamal (Studi Penafsiran terhadap Surah al-Ma'idah Ayat 35 dan Surah al-Baqarah Ayat 248)
Authors: Ramadhani Miftahul , Fansuri Fuad , Noorthaibah Noorthaibah , Hasan Muhammad
Published: August 2024

Tawassul adalah salah satu metode berdoa untuk mendekatkan diri kepada Allah dengan perantara sesuatu serta sebagai media untuk mencapai suatu tujuan. Sementara tabarruk adalah kegiatan mencari berkah melalui sesuatu yang diistimewakan oleh Allah dengan limpahan keberkahan sehingga memiliki pengaruh untuk mendatangkan keberkahan kepada orang lain atas pertolongan Allah. Beberapa ulama cenderung salah dalam memahami hakikat sebenarnya dari tawassul dan tabarruk. Mereka beranggapan bahwa umat Islam yang mempraktekkan tawassul dan tabarruk sama dengan orang kafir yang menyembah berhala. Namun, bagi mayoritas umat Islam tawassul dan tabarruk masih terus dijalankan dan dipertahankan. Jenis penelitian ini adalah kepustakaan (library research). Adapun pendekatan yang digunakan adalah pendekatan kontekstual dengan sumber data yang meliputi; sumber primer (kitab tafsir al-Futu>h{a>t al-Ila>hiyyah) dan sumber sekunder (karya-karya yang memiliki relevansi dengan tawassul dan tabarruk). Dalam mencari dan mengolah data, metode kepustakaan selanjutnya akan dilakukan dengan menggunakan metode deskriptif-analisis.
OPTIMISATION OF THE MIXTURE OF ACTIVATED CHARCOAL AND RED GINGER EXTRACT WITH THE ADDITION OF SANSEVIERIA TO THE FOOD CABINET FILTER
Authors: Astuti Siswi , F. Endah Kusuma Rastini  , Ester Priskasari  , Djoko Hari Praswanto
Published: August 2024

Spoiled or unhealthy food is the causative agent of a disease called ptomaine poisoning. This disease can come from consuming water, milk, other drinks, or food in raw or cooked form provided in a place that contains agents that can produce disease in sufficient quantities—an amount needed to cause various diseases. Various agents that can cause disease in food are plants, bacteria, chemicals, animals, agents that use food as a means of transferring themselves, radionuclides, and microbes. Food damage caused by microbes is usually due to the condition of the food, which has a high water content, improper storage of food, or types of food that are not durable. Microbes that cause harm can come from slime molds, yeasts, bacteria and viruses in a variety of ways. Can come from polluted air, cross-contamination from food storage areas. The purpose of this research is to make an air filter in a food storage cupboard that has the optimum ability to inhibit the growth of pathogenic microbes so that the stored food is not easily damaged. The method of implementation in this study was to make a filter mixture composition consisting of activated charcoal from bamboo ori, sanseviera, and red ginger extract, where the material has anti-bacterial and antiviral benefits. The filter composition to be tested is a mixture of activated charcoal, sanseviera, and ginger extract. red in the ratio: 3:1:4; 4:1:4; 4:1:3; 2:2:4; 4:2:4; 4:2:2, samples containing protein. The best results that can inhibit the growth of Bacillus substillis are obtained in filters with a composition of 4:2:4.
OPTIMIZING BRIQUETTE CHARACTERISTICS BASED ON THE RATIO OF BAMBOO AND COCONUT FIBER UNDER CONVENTIONAL METHOD
Authors: Anggorowati Dwi Anna , A.S. Mardhiyah , N. Rizky , K. Ido , Adam Yonanda  , Jamilulchal M
Published: August 2024

This study aims to optimize the potential of biobriquettes produced from a mixture of bamboo and coconut fiber using starch adhesive. The focus of the research includes determining the composition ratio of bamboo and coconut fiber that gives the best results, as well as the physicochemical characteristics of the briquettes, including moisture content, volatile matter, ash content, and calorific value. In the carbonization process, bamboo is processed for 5 hours, while coconut fiber is processed for 2 hours, with an operating temperature of 140°C. This study considered variations in the ratio of bamboo and coconut fiber mixture, such as 1:1, 5:1, and 9:1. Starch adhesive was used in a concentration of 25% of the total mixture as a determining factor in the formation of biobriquettes. The results showed that the bamboo:coconut fiber mixture ratio of 5:1 gave the best biobriquette characteristics. These briquettes have low moisture content, optimal volatile matter, standard ash content, and high calorific value of 5679.15 cal/gram. Carbonization at 140°C positively influenced the physicochemical properties of the biobriquettes.
Predicting Smart City Traffic Models using Adaboost Regression Method
Authors: Bezek Güre Özlem
Published: August 2024

In parallel with the population density in cities, noise, traffic congestion, parking problems and environmental pollution also increase. To address these problems, smart transportation and traffic systems have emerged, which benefit from internet technologies to offer solutions that concern nearly everyone. These systems generate a vast amount of data, often analyzed through machine learning methods. This study has utilized the Adaboost Regression method from the ensemble methods family within the machine learning framework to predict a smart city's traffic model. This method is a combination of many weak learners randomly selected from the data set and created by applying machine learning algorithms to form a strong learner. The Adaboost Regression method has been applied on a smart city traffic models data set found in the Kaggle database. This data set consists of a total of 48,120 rows and 4 columns, including variables such as the number of vehicles, number of intersections, date and time, and ID number. New variables have been created from the date and time variable before starting to analyze the data. The analyses performed with the Adaboost Regression method were carried out in Orange, a free Python-based program. Performance indicators such as Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and the coefficient of determination (R2) have been used in the study. A 10-fold cross-validation method was used to ensure the validity of the model and to avoid overfitting. The analysis resulted in an MSE value of 24.19; RMSE value, 4.91; MAE value, 3.00; and R2, 0.94. In conclusion, it has been observed that the AdaBoost Regression method performs successful predictions with low error rates. The Adaboost Regression method, which estimates with minimum error, is also recommended for applications in areas such as smart grid, smart hospital, and smart home, in addition to smart traffic prediction.