bluuebunny/crossref_metadata_2025 huggingface dataset:
Intelligent Analysis of E-commerce Reviews based on Complex-Valued Spatio-temporal Graph Convolutional Neural Network Optimized Tyrannosaurus Optimization Algorithm
Authors: Ting Chen
Published: May 2024

Intelligent analysis of E-commerce reviews based on multimodal social media big data using applies the benefit of innovative artificial intelligence method, especially deep learning algorithms, to study and realize web-based product consider and social network data connected to e-commerce. In this manuscript, Intelligent Analysis of E-commerce reviews based on Complex-Valued Spatio-temporal Graph Convolutional Neural Network Optimized Tyrannosaurus Optimization Algorithm (IAER-CVSGCNN-TOA)is proposed for Intelligent Analysis of E-commerce Reviews. The input data are collected from E-commerce big Dataset. Then data are pre-processing utilizing federated neural collaborative filtering (FNCF) to remove the noise and clean the data. The pre-processed data is provided to the CVSGCNN is used for intelligent analysis of e-commerce reviews. In general, CVSGCNN does no express adapting optimization approaches to determine optimal parameters to ensure accurate prediction. Hence, proposed to utilize the Tyrannosaurus Optimization Algorithm enhancement CVSGCNN for intelligent analysis of e-commerce reviews. The proposed IAER-CVSGCNN-TOA method is implemented on python. Then performance of proposed technique is analyzed with other existing techniques. The proposed technique attains 30.26%, 28.70% and 46.25%  higher accuracy, 20.53%, 32.60%, and 53.43% higher precision, 25.23%, 23.15%, and 22.33%higher recall, 25.75%, 44.30% and 53.70%higher specificity comparing with the existing methods such as a Retracted: Online Troll Reviewer Detection Utilizing Deep Learning Methods (IAER-CNN), Developing an Intelligent System and DL Algorithms for Sentiment Analysis of E-Commerce Product Reviews(IAER-LSTM), Intelligent Perception System of Big Data Decision in Cross-Border e-Commerce Depend on Data Fusion(IAER-DFN) respectively.
Optimized Hamiltonian Deep Neural Network-Based Art Education Teaching Content and Evaluation System
Authors: Qiuyu Long
Published: May 2024

The organized educational processes and experiences created to promote a comprehension and appreciation of the visual arts are referred to as art education. It includes a variety of exercises designed to foster artistic abilities, the ability to express oneself creatively, and a greater understanding of artistic ideas and background. There are several places where art instruction can take place, such as private studios, museums, community centers, and schools. In this manuscript, Optimized Hamiltonian Deep Neural Network-Based Art Education Teaching Content and Evaluation System (HDNN-AETC-ES) is proposed. Initially the data is collect from MADS dataset. To execute this, input data is pre-processed using Adaptive Distorted Gaussian Matched Filter (ADGMF) and it removes the noise from collected data. Then, data is fed to Hamiltonian Deep Neural Network (HDNN)for effectively categorized Technology-Based Art Teaching Platform. Generally, HDNN doesn’t express adapting optimization approaches to determine optimal parameters to ensure accurate art teaching. Hence, the Tasmanian Devil Optimization Algorithm (TDOA) to optimize Hamiltonian Deep Neural Network which accurately evaluated the art teaching. Then the proposed HDNN-AETC-ES is implemented and the performance metrics likes accuracy, precision, recall, F1-score, computation time, ROC are analyzed. Performance of the HDNN-AETC-ES approach attains 18.41%, 24.08% and 32.57% higher accuracy, 20.31%, 21.08% and 22.57% higher Precision and 21.41%, 22.08% and 23.55% higher recall when analyzed through existing techniques like art education teaching content using optimization of digital art teaching platform depend on information technology with deep learning (DAT-IT-DL), building arts education policy utilizing tools of out-of-school time youth arts organizations (BAEP-ST-YAO) and investigating arts education effects on school engagement with climate (IAE-ES-EC) methods respectively.
Enhancing Music Genre Classification through Multi-Algorithm Analysis and User-Friendly Visualization
Authors: Navin Kamuni
Published: May 2024

The aim of this study is to teach an algorithm how to recognize different types of music. Users will submit songs for analysis. Since the algorithm hasn't heard these songs before, it needs to figure out what makes each song unique. It does this by breaking down the songs into different parts and studying things like rhythm, melody, and tone via supervised learning because the program learns from examples that are already labelled. One important thing to consider when classifying music is its genre, which can be quite complex. To ensure accuracy, we use five different algorithms, each working independently, to analyze the songs. This helps us get a more complete understanding of each song's characteristics. Therefore, our goal is to correctly identify the genre of each submitted song. Once the analysis is done, the results are presented using a graphing tool, making it easy for users to understand and provide feedback.
Teaching Management System for Higher Vocational and Technical Education Using Wasserstein Generative Adversarial Network Optimized by Fire Hawk Optimization
Authors: Jinxiu Wu
Published: May 2024

The vocational education system is currently undergoing purposeful reform and innovation, recognizing the importance of vocational training in the entire educational framework. Assessing and improving teaching quality in vocational education is critical, and addressing this challenge necessitates. The utilize of AI technology, primarily deep learning, is particularly effective in addressing the diverse and sophisticated aspects of evaluating and improving teaching quality. In this research work, Teaching Management System for Higher Vocational and Technical Education Using Wasserstein Generative Adversarial Network Optimized by Fire Hawk Optimization (TMS-WGAN-FHO) is proposed. The input data are gathered from School database (Educational data),then, input data are pre-processed using Square Root Cubature Kalman Filter for cleaning data. Then, pre-processed data are given to Wasserstein Generative Adversarial Network (WGAN) for evaluating and improving the teaching quality for Higher Vocational and Technical Education. In general, WGAN does not express some adoption of optimization strategies for determining optimal parameters to evaluating, improving quality of teaching management system. Hence Fire Hawk Optimization Algorithm (FHOA) is proposed to optimize WGAN classifier which precisely evaluates the teaching quality Higher Vocational and Technical Education. The proposed TMS-WGAN-FHO method is implemented in MATLAB, and it assessed with several performance metrics likes accuracy, cross validation scores, recall, F1-score, ROC. The results show TMS-WGAN-FHO attains 25.8%, 28.5%, and 21.6% higher Accuracy, 15.1%, 17.2%, and 32.8%higher Precision, 27.5%, 24.6% and 22.3% higher Recall are analysed with existing methods such as, evaluation of the vocational education teaching reform's quality using deep learning (EVE-TRQ-DL), art higher vocational education curriculum design incorporating AI-aided virtual reality technology (AHVE-DIAI-VRT), integrating big data analysis with higher vocational education approaches to educate entrepreneurship and innovation (IBDA-HVE-EEV) methods respectively.
Research and Development of Digital Work Ticket Information Sharing System Based on Mathematical Differential Improved Vector Space Model
Authors: Su Huang
Published: May 2024

In the traditional production business operation and maintenance maintenance involves the work ticket filled by hand, easy to produce errors, and need to review, approval and other operations, low efficiency. The author proposes a digital work ticket sharing system based on mathematical differential improved vector space model, through the integration with PMS2.0 system and security risk management and control platform, achieve mobile office management away from WEB, in terms of functions, it realizes all the functions of the work ticket module in the PMS2.0 system, and integrates various requirements of the on-site paper work ticket, through the application of digital work ticket, real-time data collection and comprehensive sharing of the whole process and business of work ticket are realized, at the same time, according to the requirements of security management and control, data fusion with the security risk management and control platform is realized to improve work efficiency and security sharing.
Integrated Approach for Enhancement of Vapor Compression Refrigeration Systems with Spiral Condenser Retrofitting and Refrigerant Blend Compatibility
Authors: Sourabh Kulkarni
Published: May 2024

An integrated approach for enhancing Vapor Compression Refrigeration Systems (VCRS) through Spiral Condenser retrofitting and compatibility with refrigerant blends is proposed in this paper. The objectives include the design and development of an experimental setup compatible with refrigerant blends, experimentation and analysis of results for retrofitting the setup with a Spiral Condenser, validation of experimental results, and determination of system energy effectiveness and payback period. The methodology involves systematic design, experimentation, validation, and analysis, culminating in insights into VCRS enhancement strategies. The findings contribute to advancing VCRS technology, optimizing performance, and promoting sustainability in refrigeration systems.
Efficient Cyber Security Framework for IoT Using Machine Learning Algorithms
Authors: Urvashi Sangwan
Published: May 2024

Through the network's infrastructure, the IoT can impart perception, recognition, and remote control to inanimate objects. Due to IoT's characteristics, it's possible to integrate the real world into a digital system, which improves precision, productivity, and bottom line. While traditional internet infrastructure comprises of highly capable computers and servers, IoT gadgets have limited processing power and storage space. The authentication and key agreement system SecureAuthKey is very lightweight. The suggested technique is meant to solve the security and privacy problems that plague modern constraint-based CPS programmes. A lightweight approach for authenticating cyber-physical objects is one of the expected outcomes. Adaptation and autonomy in cyber-physical systems need not be compromised by a lack of trust or security in users' data or the devices themselves, according to a new type of security algorithm. To provide flexibility and scalability, a new middleware module has been developed on the Raspberry platform to facilitate communication between CPS-based devices and services. Secure Internet of Things (IoT) evaluation methodology that may be used in a variety of contexts and is user-focused. With the suggested system, the two CPS units will be able to authenticate one another. When a network grows larger, the possibility of an attack rises. Therefore, the IoT network is much more susceptible to attacks than conventional networks. As the number of connected devices grows, so do the number of potential threats to their security. To protect the IoT ecosystem from current threats, cutting-edge technology is essential. The proposed approach must be very efficient and have low computational overheads. It creates random session keys to protect wireless transmissions. The system is protected from a variety of cyber threats. The current constraint-based CPS system requires a new lightweight security solution.
Transfer Learning-Based Models for Comparative Evaluation for the Detection of AI-Generated Images
Authors: Ans Ibrahim Mahameed
Published: May 2024

As the pace of artificial intelligence (AI) evolution accelerates, the line separating authentic from AI-produced imagery becomes increasingly indistinct. This shift carries profound consequences for sectors such as content verification and digital investigation, underscoring the need for proficient AI-generated image identification systems. Our study utilizes established architectures like AlexNet, Convolutional Neural Networks (CNNs), and VGG16 to explore and evaluate the effectiveness of models based on transfer learning for spotting AI-crafted images. Transfer learning, which applies models pre-trained on large datasets, has proven beneficial in numerous computer vision tasks. In this research, we modify the intricate patterns recognized by AlexNet, CNNs, and VGG16 from extensive datasets to specifically target the detection of AI-generated content. We introduce models that are trained, validated, and tested on a comprehensive dataset that includes both real and AI-generated images. Our experimental findings demonstrate the utility of transfer learning methods in discerning between real and synthetic visuals. By conducting a comparative analysis, we highlight the comparative advantages and limitations of each model in terms of metrics such as precision, recall, accuracy, and the F1-score. Further, we investigate the distinct features identified by each model to elucidate their contribution to accurate classification.
Research on strong noise environment and piano teaching application based on virtual data space system
Authors: Ning Zhang
Published: May 2024

Music is the art of both sound and hearing. Among many musical instruments, the piano has the title of "king of instruments". Unlike the violin, which is delicate and soft, the piano's tone is noble and graceful. The pianist Nergoz once said that the purpose of all piano playing is to make sound and to create sound. So, how to use the piano to create a beautiful sound? This is an essential concern for all piano players. Therefore, it is important to practice tone, both in practice and in playing music, and only when the fingers touch the keys can a beautiful tone be produced. Tone is important in the whole process of piano playing. Both the expressiveness of the piano and its appeal to the listener are closely related to the quality of the tone. The part of the key that is touched, the intensity and the technique all have an important influence on the tone. The scientific approach to finger touch is a particularly important skill and technical criterion, both in the process of learning the piano and when performing it.
The Impact of Big Data on the Teaching Development of University Teachers in the Mobile Internet Era
Authors: Huizhong Zhang
Published: May 2024

With the continuous development and progress of network and information technology, Internet + has gradually penetrated into various fields. Internet + is to apply Internet technology to various traditional industries, organically combine traditional industries with information technology, and develop traditional industries. In order to objectively and accurately evaluate the teaching quality of college teachers, a teaching quality evaluation method based on sawfcm algorithm is proposed. This method takes the influencing factors related to teaching quality as samples in the feature space. Each run re classifies each state and updates the weight of each sample based on the current data, but it is highly dependent on the randomly selected initial clustering center and the randomly generated initial membership matrix. Taking our university as an example, the experimental analysis is carried out to verify the feasibility of the model.
Integrated Two-Level New Energy Monitoring and Big Data Centers: A Comprehensive Approach for Urban Sustainability
Authors: Bin WU
Published: May 2024

This study examines the transition to green energy in Wenzhou City and suggests a novel plan for integrating an energy monitoring and data center. The aim is to improve the city's sustainability through the building of a large-scale wind-solar integrated energy monitoring system by a group in Wenzhou City. The solution uses the Internet of Things and intelligent data analysis technology to realize real-time data collection, processing and operation and maintenance decision support for distributed power stations. The system adopts storage-computer separation and data encryption technology to ensure data security and system stability and improves data processing efficiency through containerization and microservice architecture. In addition, the study also explores the application potential of this technical scheme in regional energy planning, which provides a new idea for Wenzhou to achieve green energy transformation and low-carbon development.
Alternating Optimization Algorithms for Hybrid beamforming in mm wave MIMO systems
Authors: Srinivasa Rao Reddi
Published: May 2024

Millimeter wave (mmWave) interchanges has been viewed as a critical empowering innovation for 5G organizations, as it offers significant degrees more noteworthy range than current cell groups. As opposed to traditional various info numerous output (MIMO) frameworks, precoding in mmWave MIMO unable to performed completely at baseband utilizing computerized precoders, as just a predetermined no. of sign blenders and Analog to-digital converters (ADCs) can be upheld thinking about their expense and power utilization. Hybrid precoding transceiver design, joining a digital precoder and analog precoder, has as of late gotten impressive consideration. Nonetheless, the ideal plan of such half breed precoders has not been completely perceived. In this paper, treating the hybrid precoder plan as a lattice factorization issue, alternating minimization (AltMin) calculations will be proposed for two different half and half precoding structures, i.e., the completely associated what's more, somewhat associated structures. Specifically, for the fully connected structure, an AltMin calculation in view of complex advancement is proposed to move toward the exhibition  of the completely computerized precoder, which, notwithstanding, has a high intricacy. Subsequently, a low-intricacy AltMin calculation is then proposed, by implementing a symmetrical limitation on the computerized precoder. Besides, for the to some degree associated structure, an AltMin calculation. Be that as it may, the ideal plan of is additionally evolved with the assistance of semidefinite unwinding. For commonsense execution, the proposed AltMin algorithms are additionally stretched out to the broadband setting with symmetrical recurrence division multiplexing (OFDM) adjustment. Recreation results will show critical execution gains of the proposed AltMin calculations over existing half breed precoding calculations. In addition, in light of the proposed calculations, recreation correlations between the two mixture precoding designs will give significant plan experiences.
A Survey on Facial Emotion Recognition and Fake Emotion Detection Techniques
Authors: Husna Shaikh
Published: May 2024

Facial expressions play a crucial role in depicting the thoughts and feelings of any human. Moreover, they might even serve as the distinguishing factor in categorizing whether a person is genuine or not. In this survey, the authors have carried out a systematic literature review of the past work done on facial emotion recognition and discrimination of genuine and fake emotions. Various datasets that are previously and currently being used in this field have been surveyed. The main objective of this paper is to study the state-of-the-art techniques that are being used to analyze and identify facial emotions and to distinguish between their genuineness. For this purpose, papers from distinguished publications have been researched and a comprehensive review of the literature has been fulfilled.
A Novel Approaches to Crop Variety Development for Sustainable Agriculture using Hybrid Machine Learning Model
Authors: Kavitha Prithiviraj
Published: May 2024

The growing global population and changing climate need sustainable agriculture practices and new crop varieties. This study proposes a hybrid machine learning technique that combines linear regression and logistic regression to identify and extract unique traits from a broad range of crop species. The system integrates these qualities to create new crop types with a variety of benefits. The system begins by collecting detailed data on multiple crop species, including production potential, drought resilience, disease tolerance, nutritional content, and adaptation to different climates. Preprocessing ensures data quality. The hybrid machine learning algorithm uses the revised dataset. Linear regression identifies variables with strong connections with the required attributes, making it easier to find good candidates for the new crop variety. Logistic regression analyzes categorical data, including disease resistance genes and nutritional variables that affect crop quality. The method efficiently identifies and ranks the best characteristics across varied crop species by combining regression model findings. The traits have been strategically combined to create a pioneering cultivar that optimizes crop productivity, robustness, nutritional composition, and versatility while reducing vulnerability to pathogenic diseases and ecological challenges. The innovative crop variety is tested in various agricultural situations to determine the system's effectiveness. The topic under inquiry is compared to current kinds in terms of yield, quality, and sustainability. This unique hybrid machine learning technology may combine the best qualities from multiple sources to develop cutting-edge agricultural cultivars. The system's speed and accuracy in identifying beneficial traits promotes sustainable agriculture by reducing monospecific breeding and increasing crop resilience to environmental challenges. This work advances global food security and resource-efficient crop varieties.
Reliability Evaluation of Radial Distribution System with different locations and ratings of Photovoltaic
Authors: P. Sangeetha
Published: May 2024

The primary objective of this work is to examine how strategically positioning Photovoltaic (PV) units can have effect on reliability of a distribution system. Feeder-1 of RBTS BUS2 system is used for the reliability evaluation. The study utilizes FMEA technique to evaluate the reliability indices, System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), Energy Not Supplied (ENS) and Average Service Availability (ASAI) linked to electrical interruptions in two different situations such as no PV unit and PV units are placed at different locations with different ratings along the feeder. The outcomes of installing PV units at different points along the distribution feeder are examined and compared. The prime focus lies in identifying the reliability based optimal placement of the PV unit, a determination made based on the reliability indices. By systematically analyzing and comparing the reliability indices under varying conditions, the research aims to provide insights into how the strategic positioning of PV units can lead to a substantial enhancement in the overall reliability of the distribution system. The findings contribute to the broader understanding of integrating renewable energy sources for reliability improvement within distribution systems and offer practical guidance for decision-makers in the field of energy distribution and planning.
GRU-RNN Model to Analyze and Predict the Inflation by Consumer Price Index
Authors: Jitendrasinh Jamadar
Published: May 2024

The general population need data on the expected rate of inflation for educational expenses to plan for and manage family budgets. When formulating educational policy, this data is also useful for the government. Chennai serves as one of Indonesia's educational hubs, yet there is a lack of publicly accessible data on the city's inflation rate for education expenses. Furthermore, there is a lack of prior studies on forecasting that specifically used the Education Expenditure Group's Consumer Price Index (CPI) information to determine inflation rates in education prices utilizing the Deep Learning approach. The goal of this study is to utilize the Deep Learning Method to create a model that can predict how much tuition will rise in Chennai. The Education Expenditure Group in Chennai relied on Consumer Price Index (CPI) information for its study. An improvement in the Long and Short-Term Memory (LSTM) and Recurrent Neural Network (RNN), approach is used for predicting purposes. A method with four hidden nodes and a single hidden layer produced the best results, with RMSE=8.38 and MAPE=2.8766%.
Enhancing Diagnostic Accuracy of Co-occurring Diabetic and Thyroid Diseases using Machine Learning Techniques
Authors: Alkwai Lulwah M.
Published: May 2024

Efficient classification methods are crucial for accurately predicting co-occurring diabetic and thyroid diseases, addressing substantial global health challenges. These conditions affect individuals across diverse demographics, including males, females, infants, adolescents, and the elderly. This study employs ML algorithms to forecast co-occurring diabetic and thyroid diseases (DTD). Utilizing a dataset sourced from the UCI Machine Learning Repository, feature selection techniques were applied to identify relevant attributes and optimize predictive accuracy. Seven distinct machine learning algorithms, including ID3, J48, Zero R, Random Forest, Multilayer Perceptron, and Naive Bayes, were employed to classify subjects based on their disease status. Our analysis of various machine learning algorithms for predicting co-occurring diabetic and thyroid diseases (DTD) demonstrates notable differences in their performance. The Random Forest (RF) algorithm outperformed others with a remarkable accuracy rate of 95.123%, showcasing its potential for accurate disease classification. Following closely, the Naïve Bayes algorithm achieved an accuracy of 93.8596%, indicating its effectiveness in this context. Additionally, the ID3 algorithm demonstrated respectable performance with an accuracy of 87.7193%. These findings underscore the significance of employing machine learning methodologies, particularly Random Forest and Naïve Bayes, to enhance diagnostic accuracy and inform treatment strategies for individuals affected by thyroid or diabetic disorders.
EXPLORING TEAM COHESION IN PROJECT MANAGEMENT
Authors:   University of Craiova, Craiova, Romania, Denisa Maria COJOACĂ (ALNIȚI)
Published: May 2024

Project management represents an essential area of research with a significant impact on society and the economy. This paper aims to critically analyze the scientific literature on team cohesion and its influence on project outcomes. We employ a qualitative approach based on secondary sources to identify and evaluate critical factors such as knowledge exchange, trust, and team cohesion and to examine how these contribute to project success. The novelty of our work lies in its interdisciplinary approach, integrating perspectives from organizational psychology and project management to investigate the dynamics of team cohesion and its impact on project performance. Within this article, we critically analyzed team cohesion through the lens of individual team member competencies first, leadership styles second, and the relationship between them third. Our results indicate that integrating team cohesion into project dynamics maximizes operational efficiency and enhances resilience and adaptability against unexpected challenges. Managers who adopt specific leadership approaches (e.g., transformational and transactional) are identified as crucial factors in creating and maintaining project team cohesion. Furthermore, the article emphasizes that integrating team cohesion into management practices contributes not only to project success but also to its sustainability. Managers can develop effective strategies and interventions to enhance collaboration and outcomes within project teams by profoundly understanding the relationship between team cohesion and project performance.
Upaya Kepala Sekolah Dalam Mengembangkan Keterampilan Siswa Melalui Tenun Ikat Pada Sma Kristen Loli Kecamatan Polen Kabupaten Timor Tengah Selatan
Authors: Baun Soleman , Soinbala Nusriwan Chr. , Fomeni Melti , Tabun Ayub
Published: May 2024

The purpose of this article is to discuss the Principal's Efforts in Developing Student Skills Through Ikat Weaving at Loli Christian High School, Polen District, North Central Timor Regency. The research method used is descriptive qualitative. The subjects in this research were school principals with teacher respondents and craftsmen students. Data collection techniques are interviews, documentation. The results show that the efforts of the school principal in developing student creativity through woven ikat have been carried out in accordance with the function and role of the school principal so that the handicrafts owned by the students can be developed properly.
WADITRA JUNGGA PADA MASYARAKAT KAMBERA, KABUPATEN SUMBA TIMUR, NUSA TENGGARA TIMUR
Authors: Kabnani Jefri , Salau Triati Lestari , Iswanto Iswanto , Lakapu Luisa
Published: May 2024

Penelitian ini mengkaji waditra Jungga pada masyarakat Kambera, kabupaten Sumba Timur, Nusa Tenggara, Timur. Etnomusikologi menjadi dasar teoritis dalam penelitian ini. Hasil penelitian menunjukkan bahwa Jungga merupakan alat musik tradisional asal Sumba Timur yang dimainkan dengan cara dipetik. Jungga di Sumba ada beberapa macam yaitu jungga dua dawai, empat dawai dan enam dawai. Pada jungga enam senar berpola double string ‘setiap dawai rangkap’. Alat musik jungga Sumba Timur  pertama kali masuk di daerah Kecamatan Kambera. Jungga merupakan alat musik yang melekat pada budaya Sumba yaitu marapu, sehingga jungga dikultuskan baik dari pembuatannya hingga cara, waktu dan tempat memainkannya. Representasi budaya masyarakat Sumba juga tergambar dalam syair lagu yang diiringi dengan jungga. Salah satu contoh lagu kerja panen Anda Mara ‘jalan yang benar’ menggambarkan budaya asli merapu dalam lagu dan iringan waditra jungga. Komunitas adat pada suku bangsa Sumba yang terdapat di Pulau Sumba yang dikenal dengan kepercayaan Marapu ini tersebar diseluruh wilayah Pulau Sumba.
Dois Amores
Authors: Vieira Júlia França Sales , Ranuci Maria Eduarda Alves , Selvatici Mônica
Published: May 2024

Este trabalho tem como objetivo trazer um estudo sobre as Tríbades, nomenclatura utilizada durante a Roma Antiga para designar relações amorosas entre mulheres no Império Romano,  com o intuito de apresentar a forma na qual as relações homoeróticas femininas eram interpretadas, assim como também as diferenças de seu tratamento pela sociedade em comparação com as relações homoeróticas masculinas, e através do auxílio da obra Amores de Luciano de Samósata, na qual sua história, contemporânea do período que é objetivado neste trabalho, retrata as ideias e costumes da época perante o assunto, nos ajudará a conclusão deste estudo.
Analisis pengaruh biaya produksi, biaya distribusi dan volume penjualan terhadap laba bersih perusahaan
Authors: Lalitasari Iven Nandia , Pratiwi Desy Nur , Samanto Hadi
Published: May 2024

This research aims to determine the effect of production costs, distribution costs, and sales volume on the company's net profit. The population of this research is food and beverage sector manufacturing companies listed on the IDX for the 2019–2022 period. This research used a purposive sampling method to obtain 76 samples. This research uses secondary data, namely financial reports of manufacturing companies in the food and beverage sector for the 2019–2022 period. The data analysis technique uses multiple linear regression tests. The research results show that production costs significantly affect net profit. The distribution cost variable has a significant effect on net profit. The sales volume variable has a significant effect on net profit. Simultaneously, the variables of production costs, distribution costs, and sales volume significantly affect net profit. The influence of research variables on net profit is 93.6 percent, and the remainder is influenced by variables other than those used in this research.
Pengaruh asuransi kesehatan nasional terhadap pengeluaran kesehatan pada penduduk lanjut usia di Indonesia
Authors: Chrisnahutama Adrian
Published: May 2024

This study aims to analyze the effect of ownership or access to national health insurance, namely National Health Insurance (JKN), on health expenditure among the elderly population in Indonesia. This study uses cross-section data from the 2019 Socio-Economic Survey (Susenas). This study found that older adults with JKN have health expenditures that are 0.110 percentage points higher than older people who do not have JKN. Furthermore, national health insurance ownership is unrelated to health expenditure among poor older adults. The result shows that JKN has not been utilized as financial protection for the elderly when accessing health services.
Pengaruh kemiskinan, pendidikan, dan kesehatan terhadap pertumbuhan ekonomi di Jawa Tengah pada era Ganjar Pranowo
Authors: Ayumna Frida Salma , Sukardi Agung Slamet
Published: May 2024

This research aims to determine the influence of poverty, education, and health on economic growth in Central Java during the Ganjar Pranowo era. This research uses a quantitative approach, and the data comes from BPS Central Java Province. The analysis technique used is multiple regression analysis. The research results show that poverty hurt increasing economic growth in Central Java Province during the Ganjar Pranowo era. However, other results show that education does not affect economic growth in Central Java. Other findings also show that health has a negative effect on economic growth.
Financial management analysis of Culinary Micro, Small, and Medium Enterprises (MSMEs)
Authors: Putri Arie Rachma , Husna Faizah Khotimatul
Published: May 2024

Micro, Small, and Medium Enterprises (MSMEs) are the main backbone of Indonesia's economy. The challenges MSME business operators face include product marketing, technology, financial management, capital, and human resource quality. This research aims to understand the financial management applied to culinary MSMEs located on Pabrik Karung Goni Street, Delanggu, Klaten. The research methodology employs qualitative descriptive analysis with a case study approach. Data analysis involves four financial management indicators: budget utilization, recording, reporting, and control. Data collection techniques include interviews, questionnaires, and literature review. The population in this study comprises culinary business operators in the area. The research findings indicate that the understanding of MSME operators regarding budget utilization, recording, reporting, and financial control still needs to improve. Financial management is still basic, manual, and irregularly conducted, and not all business operators report their finances. This is due to a need for more understanding and knowledge of business financial management. Therefore, further learning and understanding of financial management are needed to assess businesses' health and development better.
Pendampingan penyusunan laporan keuangan berdasarkan SAK EMKM pada UMKM di Desa Sukosari
Authors: Sugiharti Rr. Retno , Khabibah Nibras Anny , Septiani Yustirania
Published: May 2024

Recently, MSMEs have still experienced problems in accessing capital. This is mainly due to the lack of adequately recorded, structured, standardized financial reports. MSMEs still use simple records that do not refer to SAK ETAP. With the principle of convenience and expecting that MSMEs will be able to gain more comprehensive access to capital, SAK EMKM exists as a simpler financial reporting standard compared to the complicated SAK ETAP. Unfortunately, since it was established in 2018, MSMEs still rarely use financial reports based on SAK EMKM. Therefore, to socialize the use of SAK EMKM to MSMEs, it is necessary to provide inclusive assistance. With focussing in Sukosari Village, Magelang Regency, where the majority of the village population are running MSMEs, community service activities were carried out in the form of assistance to provide socialization and assistance regarding bookkeeping and prepare financial reports based on SAK EMKM. The evaluation results showed an increase in understanding of MSME actors in Sukosari Village regarding SAK EMKM by 65.45 percent, from recording manual financial reports to recording using simple SAK EMKM standards. The obstacles faced in implementing activities are a lack of understanding from business actors or managers regarding the correct flow of financial recording and the importance of financial reports.
A Helpful Measure to Measure Help: The Construction and Validation of the Intergroup Giving and Intergroup Acting in Favor of Refugees Scale (IGIAF)
Authors: Hanioti Mado , Roblain Antoine , Azzi Assaad , Licata Laurent
Published: May 2024

Since 2015, Europe has experienced two important influxes of vulnerable migrants, refugees, and asylum seekers. Despite heterogenous reactions within and across countries, acts of humanitarianism and solidarity have occurred in a diverse range of behaviors. Given the particularities of Intergroup Helping in favor of refugees, a more nuanced understanding of intentions to engage in helping behaviors would enrich theoretical and applied research. We developed and validated a scale of Intergroup Helping in favor of refugees, that covers the two dimensions of help, i.e., Intergroup Giving (alleviating the suffering of others) and Intergroup Acting (addressing injustices and inequalities). Following scale construction practices, we proceeded in three phases. First, we identified and defined our domains of interest, and proceeded to collect representative helping behaviors, using secondary data of semi-structured interviews on volunteers. These behaviors were pre-tested. Then, across two studies, we examined the scale’s reliability, dimensionality, and validity qualities. Study 1 was distributed among a student sample at two time-points. Results yielded robust internal consistency, test-retest reliability, and predictive validity, and displayed preliminary evidence of the bidimensional structure. Study 2 was distributed among a non-student sample and supported the bidimensional structure of the scale. This research demonstrates that Intergroup Helping intentions in favor of refugees can be classified into Intergroup Giving and Intergroup Acting behaviors and offers a predictive tool to investigate these behaviors in an intergroup context.
Nitrate removal in a mangrove estuary within a Great Barrier Reef catchment
Authors: Adame MF , Iram N , Kavehei E , Cadier C
Published: May 2024

Nitrogen (N) pollution threatens the ecological integrity of the Great Barrier Reef (GBR). However, at the end of some of the GBR catchments, mangroves are extensive and may be buffering the excess N exported, but this effect has not been tested at the landscape scale. We measured N fluxes within the Moresby, a confined subcatchment dominated by sugarcane production with only one outlet to the ocean fringed by a large mangrove forest (2675 ha). We sampled nutrient fluxes across three seasons and tested the hypotheses that the mangrove estuary will reduce nitrate inputs to the ocean and that reductions will be highest during periods of high N concentrations and long residence times. Nitrate concentrations were reduced as water moved through the estuary at higher rates than expected from dilution with seawater. The reductions were equivalent to about 26% and 47% of the catchment annual nitrate and dissolved inorganic N (DIN) loads, respectively. The highest removal rates were measured in the dry-cool season when nitrate concentrations in the upper estuary were high (0.10 mg L−1 NOx−-N) and residence times were long due to low rainfall. These results complement current prioritization processes in the GBR, in which catchments have been targeted for water quality improvement primarily based on land use, soil type, slope, and rainfall, without explicitly considering the effect of wetlands. This study shows that under certain conditions, mangroves at the end of the catchment can significantly reduce the DIN entering the GBR Lagoon.
Analytical Study On Opportunities and Challenges for Empowerment of Rural Girls through Higher Education
Authors: PhD Aneesha Henry, , PhD Kirti Cutting, , Hafeez Nida Tariq , PhD Pradhyuman Singh Lakhawat, , PhD Shivalika Sarkar,
Published: May 2024

Education is a fundamental right for every individual, regardless of gender. However, in India, girls have long been denied this right due to societal norms and prejudices. As the rapid development happened in the industrial sector also affecting on the education sector in terms of skilled manpower requirement. But the accessibility of the education is not easy for everyone, at the same time the higher education is still dream of the many girls in rural areas. Education plays a vital role in development of a country. Education is also significant in terms of the development of individual’s level of intellectual ability which in turn elevates chances of employability. 231 dropouts and 154 currently studying rural female students were considered for the study in the Prayagraj district’s rural areas. The study has revealed, that number institutions in the rural areas are comparatively less with urban area. In addition to this larger portion of the rural family have mindset in educating their children based on their genders. Most of the times male have been encouraged to pursue their education compared to female. The poor financial condition again playing a crucial role which restricts them to pursue their higher education in rural areas. Awareness about the opportunities from the higher education is comparatively less in the rural areas in parents and the potential candidates of the higher education. To reach education destination aren’t at acceptable condition in terms safety and frequency of the public transport vehicles. The present study focuses on challenges faced by rural girl students in the rural areas to pursue their higher education.
Transesterificación y epoxidación del aceite de coco
Authors: Gilces Zambrano Eduardo Patricio , Moreira Mendoza Karen Estefanía , García Muentes Segundo Alcides , Cevallos Cedeño Ramón Eudoro , García Bowen Ariana Milena
Published: May 2024

Debido al avanzado incremento demográfico en el mundo, la contaminación y el aumento gradual del precio del petróleo por el agotamiento de las reservas naturales, provoca pensar y actuar de manera inmediata ante una solución para reemplazar dicho combustible en opciones rentables, productivas y amigables con el planeta; como lo es el biodiesel a partir de grasas animales y vegetales por medio de la transesterificación. También se prueban dichas materias primas en la epoxidación de la cual se obtienen productos como: elementos intermediarios para la producción de poliuretanos, lubricantes, cosméticos o bien como estabilizadores de PVC. Este artículo presenta una revisión bibliográfica ante similares estudios y demostración a escala de laboratorio, donde se comprobó que el aceite de coco cumplió con la mayoría de los parámetros de la norma NTE INEN 24:1973 a excepción del  porcentaje de acidez y humedad, haciéndolo óptimo para procesos de transesterificación y epoxidación respectivamente, cumpliendo también con la mayoría de los parámetros de la norma NTE INEN 2482:2009 a excepción del índice de yodo, siendo éste apto para el uso de energía alternativa. En cuanto a la epoxidación los valores variaron considerablemente categorizándolo en el grado 5 de viscosidad ISO para lubricante.
Atendimento nutricional em instituição de ensino superior: aplicação dos pressupostos do aconselhamento nutricional
Authors: Maia Xenofonte Martins Xênia , Carvalho de Castro e Silva Isabela , Mourão Catunda Farias Andrade Elayne , Sanders Oliveira Indira
Published: May 2024

O presente artigo tem o objetivo de analisar os atendimentos dos discentes do curso de nutrição com base nos princípios do aconselhamento nutricional não diretivo. Trata-se de um estudo observacional com corte transversal, de caráter analítico, com abordagem. Foram observadas consultas nutricionais, nas quais se aplicou um check list contendo 3 blocos, subdivididos em 25 itens que englobam os pressupostos do aconselhamento nutricional. A amostra foi composta por 15 atendimentos organizados em 3 grupos, de acordo com a conformidade em relação ao check list: grupo A, considerado satisfatório (70 a 100% de conformidade), grupo B, parcialmente insatisfatório (50 a 70% de conformidade) e grupo C, insatisfatório (0 a 50% de conformidade). Resultados: 20% dos atendimentos encaixaram-se no grupo A, 11 atendimentos no grupo B e apenas 1 atendimento no grupo C. Dentre os blocos de observação, o bloco 1 é o que contempla melhor percentual de conformidade (68,30%) enquanto o bloco 3 é o que está com menor média percentual de conformidade (53,32%). Conclusão: a maioria dos atendimentos observados apresentou conformidade intermediária em relação aos princípios do aconselhamento nutricional não diretivo.
effect of rewards and physical work environment on employee performance with work motivation as an intervening variable
Authors: Puteri Sarah , Andriana Isni , Hadjri Muhammad Ichsan , Yuliani Yuliani , Farla Wita
Published: May 2024

This research aims to determine the direct influence of rewards and the physical work environment on employee performance, the indirect influence of rewards and the physical work environment on employee performance with work motivation as an intervening variable at PT. Laras Astra Kartika. The population used in this research was 84 people using all respondents as samples, the sampling technique used saturated sampling or census. The data analysis technique used is the Structural Equation Model (SEM). The results of the research show that rewards have no significant effect on employee performance, rewards have a positive and significant effect on employee performance through work motivation as an intervening variable, the physical work environment has a positive and significant effect on employee performance, the physical work environment has a positive and significant effect on employee performance through motivation work as an intervening variable.