bluuebunny/crossref_metadata_2025 huggingface dataset:
Harvesting the power of the oceans: Advancements, challenges, and the promising future of wave energy
Authors: Wang Jiaqi
Published: July 2024

This dissertation explores the pivotal domain of wave energy, delving into its historical evolution, technological advancements, and economic prospects. In response to escalating environmental challenges and the imperative to address climate change, the pursuit of sustainable and ecologically benign energy sources has gained prominence. Wave energy emerges as a compelling frontier within the realm of renewable energy, tapping into the perpetual undulations of oceans. The study traces the conceptual antecedents of wave energy from the 19th century to its current status as a burgeoning renewable energy source. Significant strides in technology during the 1990s and 2010s marked a shift towards optimizing energy conversion efficiencies, exploring novel materials, and refining wave energy converter designs. The dissertation analyzes diverse wave energy converter types, their operational principles, and their potential applications. Despite challenges such as environmental impact, operational reliability, and high capital costs, the unwavering commitment of researchers positions Wave Energy as a sanguine contender in the renewable energy landscape. The economic outlook for wave energy is promising, with global potential estimated at 2 billion kilowatts, fostering socio-economic benefits and contributing to carbon emission reduction. By presenting a comprehensive examination of wave energy, this dissertation underscores its significance in the pursuit of sustainable, environmentally friendly, and reliable energy solutions.
STM32 microcontroller and CAN bus based FSAE racing car electrical part design
Authors: Jin Shihao
Published: July 2024

A microcontroller is a kind of chip in integrated circuits, which is a device that integrates multiple components together to accomplish a certain function. Compared with the traditional digital module, the advantages of a microcontroller lie in smaller size, lower power consumption, and higher flexibility. Its performance and functionality of the expansion depend on the design and manufacturing process of integrated circuits, and the wide application of microcontrollers cannot be separated from the support of integrated circuits. With the continuous development of integrated circuits, the application of microcontrollers is also more and more extensive; in automotive electronics, industrial control, and embedded systems have been applied on a large scale. CAN bus is a kind of serial communication protocol used for communication between various electronic components in the vehicle. It is one of the most widely used communication buses in the world, and it has been applied on a large scale in the fields of the automotive industry, aerospace industry, industrial control, safety protection, and so on. Scale application. This paper mainly discusses the application of STM32 microcontrollers and their ability to bus in FSAE racing cars, the functions they can realize, and the enhancement of racing car performance.
Robotic technology in Autism intervention: Design and application of the CARS cat-like robot
Authors: Yan Tianshuo
Published: July 2024

This study introduces a novel robotic system designed to aid individuals with Autism Spectrum Disorder (ASD) in enhancing their social communication and interaction skills. Incorporating advanced artificial intelligence, sensors, and image recognition technologies, the robot simulates human social interactions and provides tailored feedback, aiming to improve the quality of life for individuals with ASD. Through a detailed examination of hardware design, software functionalities, and data processing mechanisms, this paper evaluates the system's practical applications and identifies ongoing challenges and potential improvements. The findings suggest that while the robotic system significantly enhances social interaction and learning for autistic individuals, challenges such as technological adaptability, cost, and physical design require further innovation. This research contributes to the field of assistive technologies by offering insights into how robotic systems can be optimized to meet the unique needs of the autism community, thus paving the way for more effective therapeutic tools.
A method to shorten the time of high-dimensional matrix operations and convolution operations
Authors: Zhang Hongfei
Published: July 2024

Serverless computing, or Function-as-a-Service (FaaS), is a cloud computing execution model where the cloud provider dynamically manages the allocation and provisioning of servers which is a new way to solve the problem that the need of client.By serverless computing clients can easily solve their problems anytime,anywhere.However, the complex convolution operations and high-dimensional matrix operations can still consume a lot of resources such as computation time and memory occupancy in serverless computing. In this paper, firstly, the author selects two frequently used models in serverless computing, and then divide them into different numbers of partitions respectively to study the impact of partitioning methods on the computation time and memory occupancy. The author show that different partitioning methods can make an obviously impact on the computation time and memory occupancy,whitch shows that the proper partitioning of high-dimensional matrices and tensors can make a significantly reduction of calculation time and memory occupancy.
Federated learning implementation based on DDS data distribution service
Authors: Liu Hao
Published: July 2024

Federated learning allows multiple local private clients to collaborate on training the same model without sharing each client's private data. It can achieve collaborative training between users while protecting data privacy and security. Therefore, it is advocated for use in the fields of Internet of Things, Internet of Vehicles, etc. There are security issues in the transmission process of federated learning models. How to ensure data privacy during local data collection, local model parameter transmission, model aggregation and performance testing while maximizing the use of private data is a question that people have been exploring. This paper proposes a DDS-based FL framework (FL-DDS) to achieve secure transmission of model parameters. The client and server are used as nodes in the DDS security domain, and the DDS data distribution mechanism is used to transmit model parameters. Through the DDS topic-based publish-subscribe mechanism, the global model and local model are transmitted through the DDS topic. At the same time, the DDS authentication component, access control component and encryption component are used to achieve domain-level security and intra-domain security of model transmission. Experiments show that (FL-DDS) can protect the privacy of model parameters without affecting communication performance.
Research on investment returns prediction based on machine learning
Authors: yan Tingyu
Published: July 2024

With the development of the Internet and the continuous improvement of the information disclosure mechanism of the securities market, individual investors have more and more ways to obtain investment information, including company research reports from analysts. However, analysts have mixed qualifications and publish a huge number of reports. For retail investors, how to analyze and distinguish these reports and make informed investment decisions based on them has become the key to profiting in a securities market where information is asymmetrical and risks and opportunities coexist. This is a priority that every retail investor should prioritize. In recent years, machine learning has become increasingly widely used in the financial sector, especially in the prediction of return on investment. In this work, a most advanced machine learning model Transformer is used, which is widely used in a variety of scenarios due to its advantages in processing sequence data. The Transformer model can effectively process and analyze large-scale financial time series data through the self-attention mechanism to capture subtle fluctuations and potential correlations in the market. We designed a Transformer-based architecture to combine multi-source data such as market macroeconomic indicators, stock trading data, and social sentiment analysis for comprehensive learning. Experimental results show that the model significantly improves the accuracy of investment return prediction and provides investors with efficient analysis tools.
Research on high-frequency trading strategies optimization based on deep learning
Authors: Tian Haocheng
Published: July 2024

High-frequency trading is derived from programmatic trading and market maker mechanisms, and unlike low-frequency trading, it uses ultra-high-speed computers to acquire and analyze high-frequency trading data in the market, so as to identify price change patterns and quickly execute trades to complete the change of hands. In this work, we focused on optimizing high-frequency trading strategies using deep reinforcement learning. Specifically, we employ a dual deep Q network model, which consists of two deep neural networks that are used to generate action value estimates and provide target action values, respectively. The advantage of this structure is that it reduces bias in the estimation process, thereby improving the stability and efficiency of learning. The input layer of the model receives multi-dimensional features of market data, such as price, volume, order depth, etc., which are normalized and then fed into the network. The hidden layer includes multiple layers of fully connected layers to enhance the nonlinear representation of the model and the ability to handle complex market dynamics. We have also introduced batch normalization and dropout layers in the network to prevent overfitting merges and improve the generalization ability of the model. Eventually, the output layer generates action values corresponding to each possible trading action, deciding to buy, sell, or hold a position. In the experimental analysis, this study verifies the superiority of the proposed model in processing high-frequency trading data and executing trading decisions by comparing it with traditional trading strategies and other machine learning methods.
Exploring global-local feature fusion for pedestrian re-identification
Authors: Liu Jiahao
Published: July 2024

Pedestrian re-identification (ReID) is a challenging problem in computer vision, crucial for surveillance and security applications. Despite significant advancements, existing methods like Identity Discriminative Embedding (IDE) and Part-based Convolutional Baseline (PCB) have limitations. IDE captures global features but lacks detailed local information, while PCB focuses on local details without considering the global context. To address these issues, this paper attempts a fused model combining the strengths of both approaches. The fused model integrates global features from IDE and part-based features from PCB, creating a comprehensive representation that captures both holistic and localized details. Experimental results on Market-1501 and DukeMTMC datasets demonstrate the fused model's improved performance, significantly outperforming IDE and achieving comparable results to PCB. The fused model offers a balanced solution, apparently enhancing IDE performance and maintaining low computational consumption.
Implementing and evaluating simple resampling techniques in federated learning for imbalanced data
Authors: Chen Lingyun
Published: July 2024

Federated Learning (FL) has emerged as a promising paradigm for privacy-preserving collaborative machine learning. However, the challenge of data imbalance, exacerbated by the non-IID nature of distributed datasets, significantly impacts model performance and fairness in FL systems. This paper investigates the implementation and evaluation of simple resampling techniques to address data imbalance within the FL framework. Using the MIMIC-III healthcare dataset, a simulated FL environment with ten virtual clients was created to test various resampling methods: SMOTE, random undersampling, and a hybrid approach. The study employed logistic regression models and evaluated performance using common and novel FL-specific metrics. Experimental results demonstrate that the hybrid resampling technique significantly outperforms other methods, improving the F1-score by 13.1% and reducing communication rounds by 25.3%. Statistical analyses, including repeated measures ANOVA and hierarchical linear modeling, confirm the robustness of these findings across varied client data distributions. This research provides a replicable framework for addressing data imbalance in FL, contributing to enhanced model fairness and efficiency in privacy-sensitive applications.
A method based on GA solver for optimizing the design parameters of the right frustum resistance frame for indoor earthquake shelters
Authors: Cao Xuanyu
Published: July 2024

This paper proposes a new method to enhance the impact resistance of earthquake shelters. Traditional methods for protecting individuals during earthquakes focus on improving or reinforcing the building structures, which is time-consuming and inflexible. The SHELTER project developed an earthquake shelter using a conventional cubic frame. This study builds upon the SHELTER project by optimizing its frame structure to improve the shelter's impact resistance against falling debris during an earthquake. Firstly, a right frustum frame is selected as the basic geometric configuration for optimization (with the cuboid being a particular case of the frustum). Six critical design parameters serve as variables for optimization, establishing a mathematical model. Secondly, to maximize the permissible impact loads in both vertical and horizontal directions (F1 and F2), a multi-objective optimization using the NSGA-II algorithm is performed on the selected parameters, resulting in a Pareto front. Furthermore, to choose a solution from the Pareto front that meets the needs of this study, the relationship between the forces F1 and F2 applied to the shelter frame by falling debris during an earthquake is examined, converting the multi-objective optimization problem into a single-objective optimization problem. Finally, based on the relationship between F1 and F2, a single-objective optimization function is established and solved using the Genetic Algorithm (GA) to obtain the optimal parameters. The shelter frame manufactured with these optimal parameters exhibits better overall impact resistance than the cubic frame. This improvement is attributed not only to the geometric properties of the frustum, which results in a lower centre of gravity, but also to the optimization method, which enhances the frame's vertical impact resistance while maintaining good horizontal impact resistance.
Applications of artificial intelligence in the field of drones
Authors: Chen Jiandong
Published: July 2024

Drones, now equipped with sophisticated sensors and high-resolution cameras, have evolved into highly advanced tools capable of executing a diverse range of tasks with precision and efficiency. The integration of Artificial Intelligence (AI) has been a game-changer, endowing these aerial vehicles with the ability to process information, make autonomous decisions, and perform complex operations without direct human intervention. This paper delves into the transformative potential of AI-integrated drones across various industries, highlighting their role in revolutionizing the way we approach tasks such as autonomous navigation, package delivery, warehouse inventory management, and disaster response. The paper concludes with a comprehensive summary of the findings, emphasizing the potential benefits of AI-integrated drones in various sectors. It also looks forward to future research directions, which will focus on addressing significant challenges such as ensuring data privacy, improving the robustness and reliability of AI algorithms, and navigating the complex regulatory landscape that governs drone usage.
Cognitive machine learning techniques for predictive maintenance in industrial systems: A data-driven analysis
Authors: Chai Yinxuan , Jin Liangning , Zhang Wentao
Published: July 2024

This paper delves into the intricate relationship between machine learning (ML) and data analysis, spotlighting the recent advancements, prevailing challenges, and emerging opportunities that underscore their integration. By conducting an extensive review of scholarly literature and real-world case studies, this article uncovers the synergistic potential of ML and data analysis, emphasizing their combined influence across diverse industries and domains. The exploration is framed around pivotal themes including algorithmic innovations, which are at the heart of ML's ability to transform vast and complex datasets into actionable insights. Moreover, the discussion extends to predictive modeling techniques, a cornerstone of data analysis that leverages historical data to forecast future trends, behaviors, and outcomes. Practical applications are scrutinized to demonstrate how the confluence of ML and data analysis is pioneering solutions in fields as varied as healthcare, where predictive analytics can save lives, to finance, where it is used to navigate market uncertainties. This paper also addresses the barriers to effective integration, such as data privacy concerns and the need for robust data governance frameworks. Through this comprehensive examination, the article sheds light on the rapidly evolving landscape of ML-driven data analysis, offering insights into how these technological advancements are reshaping research methodologies, industry practices, and societal norms.
Research on the optimize doctor-patient matching in China
Authors: Luo Zhihan
Published: July 2024

In China, patients are given the opportunity to know background information about their doctors, and patients choose their doctors to see. Due to the shortage of medical resources and the uncertainty of the quality of medical services, as well as some external factors, patients will prefer to choose well-known doctors in the hope of getting a better medical experience. In order to match the preferred healthcare resources, they may choose to lie to increase the chance of visiting the doctor. This study adopts a combination of theoretical modeling and algorithmic simulation. Through theoretical analysis, a framework model of doctor-patient matching is established. Doctors with different skills and experience, who select patients according to their conditions and their own preferences in the matching process, as well as patients with different conditions and preferences, who want to receive treatment by matching to a suitable doctor, are clarified. The Deferred Acceptance algorithm is written and operated to simulate the matching process where patients apply to doctors and doctors are screened based on their priorities. Analyze and evaluate the performance of Strategy-Proofness and Pareto Efficiency in matching by iterating the algorithm. In this case, the DA algorithm establishes a stable match between the patient and the physician despite the possibility that the patient may deceive his/her preferences. However, patient behavior may affect the efficiency and fairness of the matching process, highlighting the importance of transparency and integrity of the doctor-patient matching system.
Facial recognition - A literature review
Authors: Wang Shengdi
Published: July 2024

This paper analyses the main technologies for face recognition, a critical biometric tool for identity verification and security across various sectors. A comprehensive overview of traditional and modern facial recognition technologies will be provided, examining their key features such as age, pose, and illumination. The study discusses the evolution and current state of facial recognition, highlighting significant advancements and applications in recent years. The objective is to offer a detailed understanding of how these technologies function and their implications for security and identity verification.
The survey and discussion of research on heart disease prediction based on Apache Spark
Authors: Hu Junyu
Published: July 2024

Heart is the most important part of the human body, diseases that are related to heart cause a huge thread to human health. In this paper, methods that applied Apache Spark to heart disease related works would be shown and discussed in order to classify these methods and make a conclusion about the innovations and shortcomings of these works. These works are defined into two categories: the ones that adopted traditional machine learning method and the ones that used deep learning methods. By classifying these works into two types, commonalities and similar innovative approaches in the same category of methods can be better observed and summarized, facilitating a clearer comparison of the similarities and differences in the innovative focuses among similar yet distinct methods. By doing so, conclusions were made to show that apart from enhancing operational efficiency and reliability of models for diagnosing and treating heart diseases, current research utilizing Apache Spark in this field also identifies areas for improvement such as expanding sample data representation, speeding up data processing, and addressing concept drift issues with proposed solutions. By addressing these challenges, researchers aim to optimize existing methods using Apache Spark and advanced data analytics techniques to combat heart diseases.
Research on macroeconomic indicators and stock market correlation analysis based on machine learning
Authors: Tian Haocheng
Published: July 2024

The stock market is known as the barometer of the national economy, and macroeconomic factors have an important impact on the volatility of the stock market. Therefore, considering the impact of macroeconomic factors on the sustainability of stock market volatility will help to capture the time-varying characteristics of volatility persistence, so as to significantly improve the estimation and forecasting effect of volatility. In this work, the generalized autoregressive conditional heteroskedasticity-mixing data sampling (GARCH-MIDAS) model is adopted, which combines the advantages of the GARCH model in short-term volatility modeling and the advantages of MIDAS regression in integrating macroeconomic variables of different frequencies. The GARCH model provides an accurate depiction of intraday volatility in financial markets by capturing the dynamic nature of short-term volatility. MIDAS regression introduces long-term macroeconomic factors into volatility modeling by integrating macroeconomic data with different sampling frequencies, thus making up for the shortcomings of traditional measurement methods in frequency matching. By combining these two methods, the GARCH-MIDAS model can more comprehensively reflect the dynamic changes of stock market volatility, considering both the impact of short-term market volatility and the role of long-term macroeconomic factors, thus providing a more accurate and in-depth analytical tool for volatility prediction and risk management. The results show that the GARCH-MIDAS model can significantly improve the accuracy of volatility forecasting, and provide more reliable decision support for investors, policymakers and economists.
Pendekatan Arsitek Franky Parulian Simanjuntak pada Pengembangan Simarjarunjung Hound Sky
Authors: Nasution Aulia Muflih , Andrian Frenky
Published: July 2024

Lake Toba is one of the five North Sumatra destinations considered to be Indonesian Super Priority Destinations. Information obtained from the Central Statistics Agency (BPS) of Simalungun Regency indicates that the number of visitors to Lake Toba tourism spots within Simalungun Regency increased by 55% in 2023. Most of these visitors come from the Parapat and Bukit Indah Simarjarunjung regions. As a result of the numerous national and international events held on Lake Toba, such as the International Formula 1 Powerboat Championship event (F1 Powerboat), the number of accommodations will increase to 83 in 2022. As a consequence of this, the Simalungun region of Lake Toba generally has a high number of accommodations that are in high demand. To accommodate tourists, the Toba Caldera region calls for establishing resorts and other tourist accommodations. Qualitative research methodologies are utilised in this research method. To ensure that the design that is implemented incorporates the Neo-Vernacular architecture of the Simalungun Batak culture, the development of Simarjarunjung Hound Sky in the Toba Caldera region can be accomplished through the approach of architect Franky Parulian Simanjuntak. This can be accomplished by incorporating elements of local culture into the design and utilising Neo-Vernacular architecture.
Pemetaan Bibliometrik Perkembangan Penelitian Biofilik di Indonesia
Authors: Ratnasari Anisza , Dwisusanto Yohanes Basuki
Published: July 2024

Biophilic design, which focuses on integrating natural elements into the built environment, has developed from the biophilia hypothesis. Currently, biophilic research has expanded into various fields. This literature review using bibliometric analysis aims to explore the trends of biophilic research in Indonesia. Data was collected through Publish or Perish for the period 2014-2024. VOSviewer was used for scientific mapping, while Lens.org was used for performance analysis. The results indicate that publications in scientific journals have increased over the past 5 years. Author mapping indicates some researchers are highly productive but show no co-authorship correlation. Meanwhile, mapping based on keywords depicts the dominance of research in the fields of design, architecture, and sociology. Recently, biophilic research in Indonesia has still focused on the implementation and evaluation of biophilic concepts in design, so that it is possible to open up opportunities for research collaboration in the fields of psychology, health, and ecology.
ANALISIS PROSEDUR RESTITUSI KELEBIHAN PEMBAYARAN PAJAK PERTAMBAHAN NILAI PADA KANTOR PELAYANAN PAJAK PRATAMA PEMATANG SIANTAR
Authors: Lingga Felik Jianli Princen , Saragih Afni Eliana
Published: July 2024

This study aims to determine how the implementation of restitution procedures at KPP Pratama Pematang Siantar. The population of this research is the entire procedure of VAT refunds for corporate taxpayers at KPP Pratama Pematang Siantar. The sample of this research is the procedure of VAT refunds for 2017-2021 corporate taxpayers recorded at the KPP Pratama Pematang Siantar. The analytical method used is descriptive analysis by collecting restitution procedures.
               Based on the results of the study, it shows that the application of the restitution procedure at the Pematang Siantar KPP Pratama has not been realized properly, there are still many taxpayers who do not complete the documents requested by the Pematang Siantar KPP Pratama and the application of the restitution procedure that occurs at the Pematang Siantar KPP Pratama is not in accordance with the restitution procedure in accordance with the provisions Applicable laws and SOP.
 
Keywords: Value Added Tax, Tax Overpayment, Restitution, Restitution Procedure
PENGARUH PARTISIPASI PENYUSUNAN ANGGARAN DAN SISTEM PELAPORAN TERHADAP AKUNTABILITAS SEKOLAH SMK NEGERI KABUPATEN BELALAWAN DI PEKANBARU
Authors: Sinaga Wenny Juleha , Sembiring Sabeth
Published: July 2024

This study aims to prove that Participation in Budgeting and Reporting Systems has an effect on Performance Accountability of the Pelalawan District Vocational High School in Pekanbaru. The sample in this study was obtained by simple random sampling, with a total sample of 52 respondents. Data collection technique is by distributing questionnaires. The data analysis technique used is descriptive statistical analysis, data quality test, classical assumption, multiple linear regression and hypothesis testing using t test and f test with a significance level of 5% using SPSS 26.
            From the results of research using SPSS, it is known that the coefficient of determination (R Square) is 0.563. Participation in Budgeting and Reporting Systems together affects Performance Accountability by 56%. Based on the results of multiple linear regression analysis, it can be concluded that Participation in Budgeting and Reporting Systems has a positive and significant impact on the Accountability of Performance in the Pelalawan District Vocational School in Pekanbaru. The higher the Participation in Budgeting and Reporting Systems it will affect Performance Accountability.
 
Keywords: Participation in Budgeting, Reporting System, Performance Accountability
PENGARUH PENERAPAN GOOD GOVERNANCE TERHADAP KINERJA PENGELOLAAN KEUANGAN DESA PADA KECAMATAN SILIMAKUTA
Authors: Sirait Sri Andika , Parhusip Poltak Theodorus
Published: July 2024

This study aims to determine the effect of the implementation of good governance on the performance of village financial management in Silimakuta sub-district. This study used primary data of 60 people from the village government apparatus of Sinar Baru and Purba Sinombah with the sampling technique used was purposive sampling. The data analysis techniques used are multiple linear regression analysis using the SPSS 22 program and hypothesis testing using t test and F test with a significance level of 5%.
From the results of testing using SPSS, it is known that, the results of hypothesis testing with F test (simultaneous) show that the implementation of good governance has a significant effect on the performance of village financial management, this is obtained from the ttable > calculation, which is 16,680 > 3,156 and a significance value of 0.000 < 0.05. The results of hypothesis testing with a t test (partial) show that the variable of transparency application has a significant effect on the performance of village financial management, this is obtained from the ttable > tcal, which is 5,106 > 1,672 and a significance value of 0.002 < 0.05 , which means that if the implementation of the principle of transparency in village financial management will have a positive impact on governance and will increase the accountability of the village government,  Then the performance of village financial management will improve for the better. The variable of the application of accountability has a significant effect on the performance of village financial management, this is obtained from the calculation of the ttable >, namely increasing trust and satisfaction with financial management by the village government, the performance of village financial management will improve for the better.
 
Keywords: Good Governance, Transparency, Accountability, and Performance of Village Financial Management.
Analisis Waktu dan Biaya Erection Girder dengan Metode Perancah dan Launcher pada Proyek Penggantian Jembatan Perningkloji Mojokerto
Authors: Chakim Ahmad Ibnul , Putra I Nyoman Dita Pahang
Published: July 2024

Jembatan merupakan bangunan yang menghubungkan dua jalan  yang dipisah oleh suatu dataran yang lebih rendah seperti sungai. Proyek penggantian jembatan perningkloji merupakan proyek pembangunan jembatan yang melintasi sungai di desa Perning sebagai penghubung antara Kabupaten Mojokerto dengan Kabupaten Gresik. Karena kondisi pilar jembatan dan gelagar komposit terdapat retakan dan guncangan, sehingga semua struktur jembatan salah satunya adalah gelagar diganti menggunakan PCI girder. Terdapat beberapa permasalahan seperti lalu lintas yang padat dan sungai yang dalam sehingga diperlukan metode pelaksanaan erection girder yang baik. Penelitian ini membahas tentang metode erection girder yaitu perancah dan launcher. Hasil penelitian didapatkan biaya pelaksanaan erection girder dengan metode launcher dan gantry perancah yaitu untuk metode perancah sebesar Rp 2.434.742.403,26 dan biaya metode launcher sebesar Rp1.469.797.136,90. serta waktu yang dibutuhkan untuk melakukan erection girder dengan metode perancah lebih cepat yaitu 21,25 hari sedangkan waktu erection girder metode launcher adalah 26,93 hari. Sehingga metode pelaksanaan yang dipilih adalah metode launcher.
PENGARUH RETURN ON ASSET (ROA), EARNING PER SHARE (EPS), NET PROFIT MARGIN (NPM), DAN PRICE EARNING RATIO (PER) TERHADAP HARGA SAHAM PADA PERUSAHAAN LQ-45 YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2018-2021
Authors: Simanjuntak Adi , Silalahi Esli , Silalahi Donalson
Published: July 2024

The purpose of this research is to know and explain the effect Return On Assets (ROA), Earning Per Share (EPS), Net Profit Margin (NPM), and Price Earning Ratio (PER) on stock  prices in LQ-45 companies listed on the Indonesia Stock Exchange in 2018-2021 both simultaneously and partially.The population in this study were 45 companies. The sampling technique used was a purposive sampling technique so that a sample of 18 companies was obtained with a 4-year research period. The analysis technique used is a multiple linear regression model by conducting the t test and F test. The results of the t test show that the variable Return On Assets (ROA) has a positive and significant effect on stock prices, Earning Per Share (EPS) has a positive and significant effect on stock prices, Net Profit Margin (NPM) has a positive and significant effect on stock prices, and Price Earning Ratio (PER) has a positive and significant effect on stock prices in LQ-45 companies listed on the Indonesia Stock Exchange in 2018-2021 The results of the F test indicate that Return On Assets (ROA), Earning Per Share (EPS), Net Profit Margin (NPM) and Price Earning Ratio (PER) have a significant effect on  stock price of listed LQ-45 companies on the Indonesia Stock Exchange in 2018-2021. The coefficient of determination of 88.8% means that variations  Return On Assets (ROA), Earning Per Share (EPS), Net Profit Margin (NPM), and Price Earning Ratio (PER) are able to explain variations in stock prices of 8.8%. the remaining 11.2% is influenced by other variables
PENGARUH STRUKTUR MODAL, KEPEMILIKAN INSTITUSIONAL, KEBIJAKAN DIVIDEN, DAN PERTUMBUHAN PERUSAHAAN TERHADAP HARGA SAHAM PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2019-2021
Authors: Sinaga Irma Suryani , Munthe Kornel
Published: July 2024

The aim of this research is to determine and explain the influence of capital structure, institutional ownership, dividend policy and company growth on share prices in manufacturing companies listed on the Indonesia Stock Exchange for the 2019-2021 period, both simultaneously and partially. This research focuses on manufacturing companies listed on the Indonesia Stock Exchange for the 2019-2021 period, totaling 179 companies. By using the purposive sampling method, a sample of 34 companies was obtained. The analysis technique used is a multiple linear regression model with descriptive statistical tests, classical assumption tests, and hypothesis testing. The research results show that capital structure and institutional ownership have a negative and insignificant effect on share prices, dividend policy and company growth have a positive and significant effect on share prices.
PENGARUH PERSONAL SELLING DAN DIRECT MARKETING TERHADAP PENINGKATAN VOLUME PENJUALAN MOTOR BEAT PADA PT. HONDA INDAKO BINJAI
Authors: Halawa Nuraida Hasna , Saragih Nawary
Published: July 2024

The aim of the research is to determine the influence of personal selling and direct marketing on increasing the sales volume of Beat motorbikes at PT. Honda Indako Binjai. Data collection was carried out by distributing questionnaires to 92 consumers who purchased Honda Beat motorbikes at PT. Honda Indako Binjai. The testing technique used is multiple linear regression analysis, hypothesis testing, F test and t test. Data processing using SPSS version 25. The research results show that simultaneously personal selling and direct marketing have a positive and significant effect on increasing sales volume with 5 percent. Partially, it shows that personal selling and direct marketing have a positive and significant effect on increasing sales volume with 5 percent. The coefficient of determination (R Square) value is 0.676, meaning that the increase in sales volume can be explained by personal selling and direct marketing by 67.6%, while another 32.4% is explained by other factors not explained in this research.
Exploring Female Agency in Abdulrazak Gurnah’s By the Sea: A Postcolonial Feminist Analysis
Authors: Kamran Farooqi  , Dr. Taimur Kayani
Published: July 2024

This study examines the portrayal of female agency in post-independence Zanzibar, as depicted in Abdulrazak Gurnah's novel By the Sea. Specifically focusing on the characters Asha, Bi Sara, and Bi Maryam, the study employs Gayatri Spivak's theoretical framework to analyze the interactions and responses of these characters in the face of oppressive forces and marginalization. The research sheds light on how these female characters navigate power dynamics, confront their lower social status, and resist oppression through nuanced strategies, particularly using silence. Through a detailed exploration of the characters' experiences, this study seeks to contribute to a deeper understanding of the agency and resilience of marginalized women in colonial settings. Ultimately, this research aims to underscore the significance of silence as a tool for resistance and endurance, highlighting its role in challenging prevailing narratives and advocating for women's rights in postcolonial contexts.
Keywords: Abdulrazak Gurnah, colonialism, female agency, postcolonialfeminism, Patriarchy
Սոմատիկ բաղադրիչներով վերլուծական կառույցների տիպաբանությունը հայերենում
Authors: Խաչատրյան Լալիկ , Միրումյան Մարգուշ
Published: July 2024

Linguistic units, defined in a synchronous section of the language by their semantics and grammar, can undergo various semantic and structural changes in diachrony, as a result of which their lexical and grammatical meanings also change, and some units can be reinterpreted. Changes of this kind have their own linguistic and logical foundations, which emphasize the realities of transformation.
Языковые единицы, определяемые в синхронном срезе языка их семантикой и грамматикой, могут претерпевать различные семантико- структурные изменения в диахронии, в результате чего меняются также их лексические и грамматические значения, а некоторые единицы могут быть переосмыслены. Изменения такого рода имеют свои языковые и логические основы, которые подчеркивают реалии трансформации.
El trabajo como una categoría para entender la vida de las personas en la carrera de Trabajo Social
Authors: Gavilán Dominga , Rodríguez Mirian , Galeano Blanca
Published: July 2024

La asignatura de Abordaje Profesional I, de la Carrera de Trabajo Social, de la Facultad de Ciencias Sociales de la Universidad Nacional de Asunción, tiene como objetivo desarrollar la categoría trabajo y su importancia en la formación profesional. Este ensayo inicia la reflexión de la categoría trabajo como constitutivo del ser social y a partir de ella entender, interpretar y comprender las contradicciones que se dan en el sistema capitalista y cómo afecta la vida de las personas principalmente en el ámbito social, económico, político, culturales entre otros. En este contexto se ubica el análisis sobre el profesional del Trabajado Social, como un trabajador que se encuentra inserta en la división socio-técnica del trabajo, con una autonomía relativa, situación que limita su ejercicio profesional, pero al mismo tiempo lo fortalece puesto que permite interactuar con actores sociales de diferentes estratos en contribución constante al mejoramiento de las condiciones de vida de las familias a través de su quehacer profesional.
Normalizar como supervivencia: discutiendo lo normopático desde un equipo bañadense de Atención Primaria de la Salud
Authors: Barúa Caffarena Agustín , Estigarribia Ángel , Soto Waldina , Armoa Báez Valeria Esperanza
Published: July 2024

En el subcampo de la salud mental, tanto a nivel profesional como de manera extendida, la normalidad mental suele ser un tema ausente de reflexiones. En esta investigación se trabajó el tema normalidad tensionándolo con la noción de “normopatías”, analizado desde la experiencia cotidiana de quienes integran un Equipo de Salud de la Familia del Bañado Tacumbú de Asunción, de personas vecinas que este equipo acompaña y de sus directivos del Ministerio de Salud. Se abordó metodológicamente desde un abordaje cualitativo antropológico durante el segundo semestre del 2022. Como resultados se observó una validación de lo normopático por el equipo y por la estrategia de Atención Primaria; lo normal entendido como alienación y como supervivencia, entre otros puntos. La pesquisa generó, como algunas de las líneas a profundizar, problematizar en instituciones sanitarias y en las vecindades la relación entre salud y normopatías; desarrollar estrategias de intercuidados entre trabajadores de salud; saldar la deuda histórica de los derechos humanos con la población bañadense.
Reflexiones en torno al valor-trabajo y al bienestar social desde la economía política de Ricardo y Marx
Authors: Bogarín Colmán Alan
Published: July 2024

Considerar a la economía política como una disciplina de amplio espectro es una propuesta que abre posibilidades para la interpretación de los fenómenos socioeconómicos, tanto los históricamente superados como los actuales. Aunque en muchos aspectos diametralmente opuestos, Marx y Ricardo aportan perspectivas amplias y enriquecedoras con relación al valor-trabajo y al bienestar social. El análisis de la economía política clásica y del pensamiento de Marx recogerá ideas fundamentales para la reflexión sobre problemáticas propias del mundo actual. Por un lado, se verá la concepción de valor-trabajo en las obras de Ricardo y Marx, y sus diferencias interpretativas respecto del capitalismo y los fenómenos asociados; por otro, se reflexionará acerca del bienestar social en tanto que manifiesta una íntima relación con el valor-trabajo, el excedente y las condiciones de trabajo que reproduce el sistema capitalista.
Vulnerabilidad y Precariedad Laboral: estudio de casos sobre la situación de los trabajadores de delivery en Paraguay en el contexto de la pandemia del COVID-19 (2020-2021)
Authors: González Ignacio
Published: July 2024

La pandemia del COVID-19 evidenció el crecimiento exponencial del sector de reparto o delivery en Paraguay. Este trabajo de investigación busca indagar en las situaciones en que este sector se desempeñó durante ese periodo, específicamente, tiene como objetivo conocer las condiciones laborales de los trabajadores de este rubro. La estrategia metodológica desarrollada es un estudio de caso de carácter exploratorio, con un enfoque cualitativo, utilizando entrevistas y análisis de fuentes secundarias. Para la selección de la muestra, se tomaron los siguientes criterios de inclusión: el ejercicio del trabajo en el sector del reparto y la presentación por parte de los trabajadores de demandas de violación de derechos laborales y la residencia de estos en el Área Metropolitana de Asunción. Los resultados, aunque no generalizables, muestran que el trabajo de reparto en el contexto de la pandemia del COVID-19 presentó situaciones recurrentes de vulneración de derechos laborales.
Bir Giriş Denemesi: Sülemî’nin Tabaḳāt’ında Zühd Kavramının Kullanımı Tasavvuf Tarihi Dönemlendirmesi Bağlamında Okunabilir mi?
Authors: Orhan Abdullah Taha
Published: July 2024

Bir ilmin tarihini yazabilmek ve onu dönemlendirmek o ilmin gelişim seyrini takip edebilmek için oldukça önemlidir. Bu, o ilmi bugüne ve yarına taşıyabilmek açısından elzemdir. Tasavvuf tarihi açısından da bu böyledir. Bu meyanda çağdaş tasavvuf araştırmaları literatüründe doğrudan veya dolaylı şekilde yapılmış tasavvuf tarihi dönemlendirmeleri mevcuttur. Fakat dönemlendirme açısından bakmamız gereken önemli bir literatür daha vardır ki o da özellikle hicrî dördüncü ve beşinci asır sûfî müelliflerinin kendilerinden önceki birkaç yüzyıllık tarihî birikimi tasavvuf açısından nasıl değerlendirdikleridir. Zira onlar, yaşadıkları çağda tasavvuf ilminin temsilcileri iken aynı zamanda birer tasavvuf tarihçisi olarak da vazife görmüşlerdir. Sülemî (öl. 412/1021), Kuşeyrî (öl. 465/1072) ve Hücvîrî (öl. 465/1072) bu bağlamda özellikle göz önünde bulundurulması gereken yazarlardandır. Biz bu çalışmada bu isimlerden kronolojik olarak ilk sırada yer alan Sülemî’ye odaklanacağız. Sülemî’nin tebeu’t-tâbiîn tabakasına kadar gelen dönemi “zühd” kelimesini kullandığı bir isimle (Kitâbü’z-zühd), kronolojik olarak İbrahim b. Edhem’le başlayan dönemiyse “sûfiyye” kelimesini kullandığı bir isimle (Ṭabaḳātü’ṣ-ṣûfiyye) kitaplaştırması onun zihninde var olan tasavvuf tarihi okumasını anlamamız açısından bir ipucu barındırır. Çalışmada bu ipucundan hareketle onun Ṭabaḳātü’ṣ-ṣûfiyye’sinde zühd/zâhid kavramlarını kullanımını anlamaya ve yorumlamaya çalışacağız. Bunu yaparken Sülemî külliyâtının diğer eserlerine de bu bağlamda müracaat edeceğiz. Tespitimize göre Sülemî Ṭabaḳāt’ta ve diğer eserlerinde zühdü temelde üç farklı bağlamda kullanmıştır: amel/ibadet/riyâzat ve mücâhede olarak zühd; marifete/tasavvufî ilme kıyasla nâkıs bir makâm olarak zühd ve tasavvuf anlamında zühd. Özelden genele doğru giden bu üç bağlamdan zühdün tasavvuf anlamında zikredildiği bağlamın en belirleyici anlam alanı olduğu görülür. Sonuç olarak Sülemî’ye göre zühd ve tasavvuf arasında bir süreklilik ve kısmen aynîleşme olduğu göze çarpar. Bir eseri merkeze alarak yapılan bu kısa hacimli çalışmadan “Sülemî’nin tasavvuf tarihi dönemlendirmesi” gibi büyük bir amaca ulaşmak elbette mümkün değildir, fakat burada ulaştığımız mütevazı sonuçların ileride bu yönde, yani klasik dönem sûfî müelliflerinin tasavvuf tarihi algılarını ortaya çıkarma noktasında ışık tutucu olacağına inanıyoruz. Benzer araştırmaların söz gelimi yukarıda ismi geçen Kuşeyrî ve Hücvîrî bağlamlarında da gerçekleştirilmesi birer tasavvuf tarihçisi olarak erken dönem sûfî müelliflerinin tasavvuf tarihi kavramsallaştırmalarını daha iyi anlamamızı sağlayacaktır. Diğer taraftan Sülemî’nin zühd kavramı kullanımı üzerinden yaptığımız bu okumanın bağlamı farklı kavramlar üzerinden de ilerletilebilir. Örneğin sıdk, fakr, melâmet ya da fütüvvet gibi ana kavramların Sülemî’nin düşüncesindeki yerini görmek onun tasavvuf tarihi dönemlendirmesini doğruya daha yakın olarak konumlandırmamızı kolaylaştıracaktır.