bluuebunny/crossref_metadata_2025 huggingface dataset:
The application of deep learning in autonomous driving
Authors: Zhang Tingyu
Published: March 2024

Autonomous driving technology is currently a globally prominent subject, with its relevance and impact readily apparent. Leveraging advanced sensors, sophisticated algorithms, and state-of-the-art computer vision techniques, autonomous vehicles can autonomously navigate, mitigate traffic accidents, and alleviate urban congestion. Furthermore, this technology is poised to accelerate innovation within the automotive sector, drive industrial advancement, and enhance people's convenience and safety in their travel experiences. The importance of autonomous driving technology is not only reflected in its own advantages, but also in its ability to lead the development direction of intelligent transportation in the future, helping to promote the development of intelligent transportation systems, realize the intelligent interconnection between vehicles and vehicles, vehicles and road infrastructure, and further enhance the safety and convenience of traffic travel. Therefore, autonomous driving technology is a significant innovation that will bring a better and more convenient future for mankind. In this study, a method based on sensor internal and external parameter calibration transformation matrix, road target detection algorithm, automatic vehicle detection method, pedestrian intention prediction technology and automatic pedestrian recognition system are analyzed, which are applied to object detection and obstacle avoidance. This article provides a good overview of the field of autonomous driving.
Neural network-based Raman spectral recognition model for milk powder and wheat flour
Authors: Li Peichen , Wu Mingxuan , Wu Weibing
Published: March 2024

The problem of counterfeit milk powder has occurred in recent years, and one of the standard techniques is to adulterate milk powder with wheat flour to reduce the cost. Since the morphology and colour of wheat flour are similar to that of milk powder, it is not easy to distinguish it from the naked eye, so a rapid method for detecting wheat flour adulteration in milk powder is urgently needed. This study used Raman spectral analysis as a novel and efficient screening technique. With the advantages of high sensitivity, non-destructive detection, low cost, no contamination, and online analysis, this method can play an essential role in rapid food detection and production control. By processing and analyzing the spectral data, a neural network model for identifying milk powder and wheat flour based on Raman spectroscopy has been developed in this study, and the model's performance has been evaluated. The results show that the model can quickly and accurately identify the proportion of wheat flour in milk powder to determine whether milk powder is adulterated or not. The results of this study are of great significance in ensuring the safety of infant milk powder. In the future, the method can be further optimized, for example, to improve detection speed and accuracy and to provide a more reliable quality control method for the milk powder industry.
Application analysis of data encryption technology
Authors: Li Bingcheng , Li Dingkang , Zhu Mingyuan
Published: March 2024

Data encryption technology is a key method to secure sensitive data. The privacy and confidentiality of data is protected by encrypting the data, i.e., transforming the original data into a form that cannot be understood without authorization. However, the security of traditional encryption algorithms is gradually challenged with the increase in computing power. Therefore, studying how to apply more advanced encryption techniques has become a current research hotspot. This study aims to analyze the application of data encryption techniques and explore the advantages and applicability of emerging encryption algorithms. This paper presents a variety of methods for preventing users' privacy breaches, with a primary focus on the principles of homomorphic encryption and how data can be accessed by users without decryption. Additionally, the working principles of secure multiparty computation are discussed, allowing multiple users to perform calculations on shared data while preserving data privacy. Furthermore, the paper explores data encryption techniques that employ specific algorithms to convert plaintext into ciphertext, ensuring both data consistency and privacy. Finally, a summary and future prospects are provided.
Stock price forecasting by supervised learning methods
Authors: Lu Jinzhong
Published: March 2024

Predicting stock prices has already long been a popular but challenging topic due to unavoidable uncertainties in various factors. With continuous exploration and development of machine learning algorithms over the years, they have become more and more popular in forecasting stock value changes. This paper aiming to predict future stock prices using returns from the past by applying three different supervised learning methods to the seemingly unpredictable dataset, namely Long Short-Term Memory (LSTM), Linear regression and Fully connected Neural Networks (FNN). R-squared and MSE were used as statistical indicators of the performance of each model. The calculated R-squared values for linear regression, LSTM and FNN were 0.876975, 0.898741 and 0.929504 respectively. In addition, the MSE of the corresponding models were 5.7786893, 0.0007542 and 0.0005237. As a conclusion, FNN performed the best in the sense that it put out the highest R-squared and lowest MSE value. As a result, FNN may take priority to the other manners in future predictions.
Application of artificial intelligence technology in hospital management systems
Authors: Xinrui Zhang
Published: March 2024

This article explores the application of artificial intelligence technology in hospital management systems, specifically using the innovative work order project as an example. The system can interact with users through intelligent AI interaction through text and voice, enabling intelligent work order repair and query processing. The project includes multiple functions such as work order form generation, attachment uploading, voice file uploading, work order query, and interface docking. In addition, this article also introduces the requirements for integrating hospital logistics business with Turing CHATGPT application scenarios, including equipment failure repair, patient satisfaction surveys, patient follow-ups, and medical staff training and learning. Through detailed descriptions of interface docking, data flow, and functions, this article highlights the potential of AI technology to enhance work efficiency and user experience in hospital management systems. Finally, this article discusses the current achievements and future development directions and calls for further innovation and progress in medical information management systems.
Vehicle collaborative detection based on YOLOv5
Authors: Gong Zikun , Guo Kezhen , Yang Danyao
Published: March 2024

Object detection has always been a popular research issue in the computer vision community. It has often been used in many downstream fields in recent years, especially vehicle and pedestrian detection in autonomous driving tasks. To improve the detection accuracy of vehicles or pedestrians, significant progress has been made in previous works. However, few of them specifically study the detection under extreme environments. Considering the need for real-time detection in research on vehicle and pedestrian detection, based on the detailed investigation of existing researches on vehicle and pedestrian detection as well as general object detection algorithms, we study the structure and framework of YOLOv5 algorithm and discuss the advantages and improvements. Then, we collect the dataset of vehicle detection based on YOLOv5 and conduct extensive experiments to analyze the detection performance. Experimental results show that our method can detect vehicles and pedestrians in different scenarios, and we hope to provide some new insights for the future development of this research field.
Performance analysis of three recommendation algorithms on Amazon datasets
Authors: Meng Yuyang
Published: March 2024

Recommendation systems play a crucial role in enhancing user satisfaction and driving sales for businesses. They are essential in todays marketplaces, as they are able to suggest products and services that may interest a particular individual based on their past purchases. In this paper, empirical research is conducted on three distinct subsets of the Amazon dataset, namely Sports & Outdoors, Movies & TV, and Video Games, to comprehensively evaluate the performance of three distinct recommendation methods based on deep learning algorithms. These methods include the dot product method, (an updated version of the singular value decomposition algorithm), the neural network method, and the neural collaborative filtering model with natural language processing method. The results of this study reveal that deep learning-based recommendation systems can achieve more accurate results compared to traditional recommendation systems for three types of products. The implementation of these methods on Amazons dataset can help improve sales by correctly identifying customers interests and suggesting relevant items.
TabTranSELU: A transformer adaptation for solving tabular data
Authors: Mao Yuchen
Published: March 2024

Tabular data are most prevalent datasets in real world, yet the integration of deep learning algorithms in tabular data often garners less attention despite their widespread utilization in other field. This phenomenon could be attributed to the dominance of the classical algorithms in their simplicity and interpretability, and the superior performance of the gradient boosting tree models in tabular data. In this paper, a simple yet affective adaptation of the Transformer architecture tailored specifically for tabular data is presented, not only achieving good performance but also retains a high degree of explain ability. The model encodes both continuous and categorical features, alongside their respective names, and feed them into an enhanced Transformer structure enriched with Scaled Exponential Linear Unit activation. Through rigorous experimentation, our model not only outperforms classical algorithms and similar Transformer-based counterparts, but also are comparable to the performance of gradient boosting tree models.
An examination of non-wearable methods for fall detection
Authors: Zhang Caoyang
Published: March 2024

Amidst the emergence of an aging global population, elderly healthcare has evolved into a pressing societal concern. The World Health Organization reports that approximately 646,000 individuals across the globe succumb to fatal falls annually. Notably, those aged over 60 experience the highest mortality rate, representing the most significant portion of these deaths. Given these stark statistics, there has been a surge of interest in researching fall detection methodologies. This article delves into non-wearable fall detection techniques, emphasizing their various classifications and applications. Initially, we provide an overview of distinct categories within the non-wearable fall detection landscape. Following this, each method is elaborated upon, elucidating its mechanisms and practical applications. To complement this, a brief discourse on prevalent machine learning algorithms employed in fall detection is presented. In culmination, a comparative analysis of each technique is provided, highlighting their respective merits and limitations. The objective is to furnish readers with a holistic perspective on the current state of non-wearable fall detection. As we gaze towards the horizon, it becomes evident that advancing this domain is paramount to safeguarding our elderly and reducing preventable fatalities.
FPGA acceleration of convolutional neural networks: Current applications and future prospects
Authors: Li Zexiao
Published: March 2024

In the contemporary era of big data, the utilization of deep learning technology has become widespread in the extraction of valuable analytical insights from the data under consideration. This technology finds extensive applications in various domains, including image information recognition, speech processing, and text language analysis. When it comes to accelerating convolutional neural networks (CNNs), the utilization of Field-Programmable Gate Arrays (FPGAs) offers distinct advantages over other hardware accelerators. Nevertheless, it is important to acknowledge that FPGA-based acceleration also comes with its own structural limitations. This article places its focus on two main aspects: firstly, it delves into the present-day application landscape and the latest developmental trajectories of convolutional neural networks. Secondly, it elucidates the inherent characteristics of FPGA implementations of CNNs. Furthermore, the article conducts a comprehensive examination of the pertinent constraints associated with FPGA-accelerated deep learning algorithms. The discussion extends beyond the present moment and ventures into the future, offering insights into the potential advancements in the field of deep learning. Importantly, it also brings into focus the prospective avenues for further research regarding the application of FPGAs in the domain of convolutional neural networks.
Lightweight convolutional neural networks for real-time lane segmentation
Authors: Yu Zhengxiao
Published: March 2024

Autonomous driving depends on reliable perception systems that involve various perception modules and advanced computer vision techniques. One crucial component of these systems is lane detection, which traditional methods often rely on basic features like color or edges that are sensitive to lighting and perspective changes. Recently, convolutional neural networks (CNNs), have revolutionized lane detection. Nevertheless, existing methods still have some limitations, such as the need for pixel-level labeling and computational inefficiency for real-time applications. To address these challenges, this work leverages PP-LiteSeg for real-time semantic segmentation. PP-LiteSegs key elements are its Simple Pyramid Pooling Module (SPPM), Unified Attention Fusion Module (UAFM), and Flexible and Lightweight Decoder (FLD), which optimize lane detection efficiency. The FLD flexibly adjusts computational costs between the encoder and decoder, balancing efficiency and accuracy. The UAFM enhances feature representations using attention mechanisms, increasing segmentation accuracy. The SPPM efficiently aggregates contextual information while reducing computational complexity. The comprehensive method for lane segmentation achieves competitive results on popular lane detection datasets. The proposed model can adapt to different computational capabilities and significantly enhances lane detection efficiency for real-time applications.
Analysis of the methods and performances for data augmentation: Image, text and audio
Authors: Jin Yuying
Published: March 2024

With the rapid development in computation ability as well as machine learning scenarios, various artificial intelligence applications can be achieved in recent years. With this in mind, this study will explore the application of data augmentation in machine learning and deep learning. To be specific, this paper first introduces the background and research history of data augmentation and then discusses the research progress in recent years. The basic description of this study describes the definition, common methods, and evaluation metrics of data augmentation in detail. At the same time, three data augmentation models, AutoAugment, AugGPT, and SpecAugment++, are introduced respectively, including their principles, experimental results, as well as evaluation. Finally, according to the analysis, the limitations and prospects of the field are discussed and demonstrated, as well as summarize the main findings and research implications of the full paper. Overall, these results shed light on guiding further exploration of data augmentation.
Neo-humanism and the Modern World: A Philosophical Perspective through the Lens of Philip Roth's Everyman
Authors: Dhivya A. Chrispin Antonieta , A. Prakash , Mathanavalli S. , RP Monika , S Sweetline
Published: March 2024

Everyman by Philip Roth is a realistic work that covers the life of an unnamed Jewish American from childhood to adulthood in a bildungsroman style, slowly revealing mundaneness in every element of life and potentially being related to "Everyman" who exists in the world. An individual's self-centered focus and an abundance of ideas that examine his very existence and the proportion of significance he has had in the lives of those around him relate to the exciting phases of life that parallel the universal narrative of marriage, divorce, betrayal, sex, regret, emptiness, introspection, anxiety, ageing illness, and death. Everyman by Philip Roth makes many allusions to the memories and experiences of immigrants. It speaks to people who live lives torn between the past and the present, between freedom and religion, and between finding transcendence through humanism rather than via faith in God. It also talks on the ideological conflicts that have developed between dads and sons as a result of contemporary upheavals. The potential conclusion of the study is that modern humanism is founded on this through negation in the creation and consumption of texts, on the notion that human civilization is not monolithic but rather multifaceted and dynamic, meaning that understanding it requires a long gaze through immense time and the novel perspectives of modernity.
The Perception of Cosmetic Brand Names among Saudi Consumers: Implications for Intercultural Advertising
Authors: Olwi Alaa , Alshammari Alya
Published: March 2024

As the global cosmetics market expands rapidly, the importance of cultural sensitivity in advertising becomes evident. However, certain brand names used internationally may unintentionally offend specific audiences due to linguistic and cultural differences. This study examines the perceptions and attitudes of 770 Saudi individuals toward brand names deemed inappropriate or provocative within the Saudi sociocultural context. The research aims to shed light on the implications for intercultural advertising targeting Saudi consumers. The findings reveal strong negative reactions to brand names with sexual references, with respondents using terms such as "disgusting," "shocking," and "shameless" in their descriptions. The study also highlights the impact of these names on religious and moral values cherished in Saudi society. The implications for international cosmetic companies targeting Gulf consumers include careful consideration of name translations and connotations in Arabic-speaking markets, involvement of local expertise in advertising campaigns, and enhanced cultural sensitivity training for marketing professionals operating abroad. This research contributes to the understanding of intercultural advertising and provides insights for improving cultural competence in English language education, particularly in the context of teaching English for advertising. By raising awareness of these issues, appropriate choices of brand identifiers can be discussed to benefit both businesses and target audiences.
Thực trạng hoạt động đầu tư trái phiếu của các ngân hàng thương mại Việt Nam
Authors: Đinh Thị Phương Anh , Đặng Thị Minh Nguyệt , Nguyễn Trần Việt
Published: March 2024

Đầu tư trái phiếu là một nhu cầu tự nhiên, tất yếu của các NHTM. Việc nắm giữ chứng khoán có vai trò quan trọng không thể phủ nhận, giúp các ngân hàng gia tăng thu nhập, tăng cường thanh khoản và tính đa dạng trong danh mục tài sản của mình, qua đó hạn chế rủi ro trong hoạt động của các NHTM. Tuy nhiên, đầu tư trái phiếu của các NHTM cũng tiềm ẩn nhiều rủi ro, dễ dẫn đến những biến tướng hay hành vi đầu tư mạo hiểm. Bài viết nghiên cứu hoạt động đầu tư trái phiếu của 04 ngân hàng thương mại điển hình ở Việt Nam trong giai đoạn 2015-2023 theo các khía cạnh quy mô và cơ cấu đầu tư cùng hệ thống khuôn khổ pháp lý có liên quan trong khoảng thời gian này. Trên cơ sở phân tích, đánh giá thực trạng cùng hệ thống khuôn khổ pháp lý có liên quan trong khoảng thời gian này. Trên cơ sở phân tích, đánh giá thực trạng, một số hàm ý cho các ngân hàng thương mại được đưa ra nhằm hoàn thiện hoạt động đầu tư trái phiếu của các ngân hàng thương mại Việt Nam theo hướng lành mạnh và bền vững.
Relationship between Social Media Use and Sleep Disturbance among Adults in Afghanistan
Authors: Khpalwak Abdul Tawab , Hamidi Mohammad Salim
Published: March 2024

This study aimed to investigate the impact of excessive social media use on sleep and mental well-being among adults in Afghanistan. An online survey was conducted across 19 provinces in Afghanistan to assess social media usage and its effects on sleep. 407 Afghan adults Participated in the survey and were asked about their usage patterns, perceived addiction, and impact on their sleep quality and mental well-being. The survey revealed that many Afghan adults exhibited excessive social media usage and showed signs of addiction. ¾ participants reported a strong urge to use social media. Social media usage, particularly before bedtime, significantly affected sleep patterns and mental well-being. 68% of participants identified social media as a problem. A direct correlation was observed between the duration of social media usage and sleep disturbances, with increased usage leading to poor sleep quality and difficulty concentrating on daily activities. This study highlights the need for awareness and interventions to address the harmful effects of excessive social media use on sleep and mental well-being. Mental health professionals, policymakers, and health organizations are urged to collaborate and develop strategies to promote mental well-being and address the issue of excessive social media usage.
Exploring a Meta-cosmic Way out for Cambodia's Development
Authors: Yu Wangyu , Xia Zhiliang
Published: March 2024

The cooperation between Chinese and Cambodian vocational colleges and universities and enterprises aims to realize resource sharing and teacher exchange, and enhance the influence and core competitiveness of vocational colleges on both sides. This cooperation not only meets the needs of mutually beneficial cooperation in vocational education between China and Cambodia, but also actively promotes the reform and development of vocational education in both countries. The transnational vocational education alliance established with Cambodia has become a new model with the characteristics of The Times.
A Review of Durability of New and Old Concrete Joints
Authors: Long Jianzhong
Published: March 2024

The purpose of this study is to explore the durability of the new and old concrete joints, including chloride ion erosion, freeze-thaw phenomena, and the influence of aggregates. Firstly, taking into account the difference in material properties between the old and new concrete, this study analyzes the chloride ion transport characteristics of the joints in detail, focusing on the key areas of the joints, that is, the areas where the old concrete may have been eroded by chloride ions. Secondly, this study explores the change in the properties of the joints under freeze-thaw conditions, and the influence of different interface treatment methods on the properties of the joints. Finally, this study examines the influence of the type and content of aggregates on the durability of the joints. Through the above research, this paper aims to provide some useful guidance and suggestions for the durability design of the old and new concrete structures.
Application of EEG Technology in Kansei Engineering
Authors: Li Xiangyu
Published: March 2024

This paper introduces the theory of EEG technology, operation process and the concept of Kansei Engineering, and discusses how EEG technology can be applied to Kansei Engineering. By recording the EEG signals of participants and analyzing the changes of these signals, EEG technology can help designers to understand the needs and responses of users more deeply, thus optimizing product design and improving user experience and market competitiveness. And the future combination of the two in more aspects is prospected.
Countermeasures for the Planning and Construction of Villages and Towns in the View of Rural Revitalization
Authors: Yao Sisi , Liu Siqi
Published: March 2024

In recent years, the state has put rural revitalization in an important position of the national development strategy, emphasizing that rural revitalization must be realized in order to solve the problems of agriculture, rural areas and farmers and improve rural economic income. Under the rural revitalization strategy, in order to restore the overall vitality of villages and towns, we must give priority to the development of agricultural and rural areas. However, due to the restriction of the dual structure of urban and rural areas, the planning and construction of villages and towns are faced with many problems, such as the absence of the main body of village planning and construction management, the crisis of abandoning cultivated land for other purposes, poor living conditions and even destruction. This paper emphasizes practical village planning, pays attention to the construction of ecological civilization and the principle of construction and development according to local conditions, constructs a diversified development space, and provides effective assistance for the implementation of the strategy of rural revitalization, as well as the development of practical rural planning.
Analýza faktorů asociovaných s vícečetnými příčinami smrti v Česku v roce 2018 pomocí XGBoost regrese a metody SHAP
Authors: Ukolova Bety , Burcin Boris
Published: March 2024

This study focuses on the factors that are associated with recording multiple causes as the cause of death in Czechia. An XGBoost multiple regression is used in the analysis and its results are interpreted with SHAP values. The most significant factors associated with the number of causes of death, ranked in order of importance, are the place of death, the region, and the underlying cause of death. Age and autopsy also contribute, albeit to a lesser extent. Several important interactions were identified as well.
Enhancing Procurement Integrity: Key Factors Influencing Internal Audit Effectiveness in Tanzania Public Procurement
Authors: David Joseph I. , Ntegwa Magashi J.
Published: March 2024

This paper analyses the effects of internal audit competence, independence, and procedures on internal audit effectiveness in the procurement process in the public sector of Tanzania. The study is quantitative, and data were collected through questionnaires from accounting officers, senior management officers, audit committees, and internal audit units in public sectors. A total of 318 responses were collected. A Partial Least Structural Equation Modelling (PLS-SEM) technique was applied using R-studio to analyse the collected data, assess the model and test hypotheses. The findings revealed that internal audit characteristics procedures, independence and competence influence internal audit effectiveness in procurement. The study findings provide useful insights for policymakers, academics, and internal audit practitioners on the effect of the characteristics of internal audits in improving the effectiveness of internal audits in procurement in Tanzania.
CHATBOT WITH FACIAL RECOGNITION BY USING AI
Authors: K Harish
Published: March 2024

Creating a concept for a facial recognition chatbot is the main objective of the project. The work of chatbots in a variety of fields, such as marketing, education, healthcare, entertainment, has grown significantly in recent years. A chatbot is a piece of software that performs text or text-to-speech internet chats in place of face-to-face contact. Chatbots and other dialog systems are utilized for a number of purposes, including information gathering, request routing, and customer assistance. Some chatbot solutions look for generic keywords and respond with frequently used phrases that are pulled from a related library, while others utilize sophisticated AI, natural language processing, and intricate word categorization techniques. Here, we have added additional features including facial and language recognition. A facial recognition system is a technological device that uses a database of faces and digital images or video frames to identify a person's face. This kind of equipment locates and quantifies face features from a picture, usually to confirm users' identities through ID verification services.
Shoe Customizer
Authors: Makwana Yash
Published: March 2024

This project presents the development of a Unity WebGL application titled "Shoe Customizer" within the context of an internship at WebWorld Developing. The application offers users the ability to personalize shoe designs by adjusting colors and materials, providing an engaging and interactive experience. The project involved utilizing Unity's game development platform, WebGL technology for web deployment, and a combination of programming languages such as C# and JavaScript. The report outlines the objectives, methodology, and implementation details of the project, including the design process, software development lifecycle, and user testing procedures. Furthermore, it discusses the challenges encountered during development and the solutions devised to overcome them. Through this project, valuable insights into web-based 3D customization applications and their potential applications in e-commerce and interactive marketing are gained, highlighting the significance of immersive digital experiences in engaging and satisfying user interactions.
Mayfly Optimization Algorithm: A Nature-Inspired Approach with Advanced Termination for Efficient Minimization
Authors:   Apex Institute of Engineering and Technology, Jaipur
Published: March 2024

The Mayfly Optimization Algorithm (MO), inspired by the swarming and mating behavior of adult mayflies, offers a promising approach for tackling minimization problems. However, traditional MO can suffer from unnecessary iterations and exploration of suboptimal regions in the search space. This paper addresses these limitations by introducing two key advancements: greedy selection and auto-termination. Greedy selection ensures the algorithm prioritizes solutions with lower fitness values during position updates, guiding the search towards the minimum more effectively. Auto-termination monitors fitness function changes over a defined window and terminates the algorithm if improvement stagnates, reducing computation time. We evaluate the performance of the enhanced MO algorithm on various benchmark minimization functions. The results demonstrate that the incorporation of greedy selection and auto-termination significantly improves the convergence speed and efficiency of MO compared to the traditional approach. This paves the way for MO to be a more competitive and efficient tool for tackling various real-world minimization problems. Index Terms— Mayfly Optimization Algorithm (MO), Minimization Problems, Greedy Selection, Auto-Termination, Fitness Function, Convergence Speed, Efficiency, Swarm Intelligence, Nature-Inspired Optimization
Cancer Risk Identification using Machine Learning
Authors:   Department of Information Technology Vivekanand Education Society, Institute of Technology. Mumbai 400074, India, Sondur Dr. Shanta
Published: March 2024

In this comprehensive study, we explore the SEER (Surveillance, Epidemiology, and End Result) dataset to meticulously craft a predictive model aimed at understanding patient survivability, focusing keenly on outcomes like patient survival diagnosis and treatments. Employing a good approach involving rigorous data cleaning, intricate feature extraction, and detailed correlation analysis, we identify the dominant attributes that significantly influence patient outcomes. Our methodology integrates classical machine learning models, including decision trees and random forests, with modern techniques such as neural networks. This mix of methodologies allows us to accurately predict patient survivability. Furthermore, our study delves into the intricate relationships between attributes, models, and algorithms, aiming to identify the dominant factors that influence the outcomes. Our groundbreaking findings underscore the enormous potential of integrating these dominant attributes, paving the way for the creation of exceptionally robust predictive models. These models will substantially enhance medical decision-making processes and, in turn, elevate the overall quality of patient care. Keywords - SEER dataset, patient survivability, machine learning, decision trees, random forests, neural networks, data cleaning, feature extraction, clinical data, medical decision-making.
STRATEGY FOR OPTIMIZING PURCHASE INTENTION OF ELECTRIC VEHICLES MEDIATED WILLINGNESS TO PAY
Authors: Harno Rinto , Hasibuan Putri Septi Naulina , Rinawati Liya
Published: March 2024

Currently, many people have the purchasing power to buy Battery Electric Vehicle (BEV) cars, making them a popular trend in the automotive industry due to their ability to reduce air pollution in the long term. This research aims to identify important factors that influence the purchasing decision of BEV cars. The study employed a quantitative research design, where data were collected through questionnaires distributed to potential BEV car users. Data analysis was done using a multiple regression model. The results showed that there was an influence between Cost, Technology and Macro Level on Purchase Intention either partially or simultaneously. To increase BEV car purchases, strategies should be focused on minimizing the production cost of the cars, introducing modern yet user-friendly technology, and promoting the benefits of BEV cars over conventional ones. This can help shift people's attitudes and behaviors towards BEV cars.
MARKETING PUBLIC RELATIONS STRATEGY IN WEDDING PARTY EVENTS AT HORISON HOTEL BEKASI
Authors: Pratama Rismandha Kusuma , Anggraini Rosita
Published: March 2024

Currently, hotel services do not stop at providing the best rooms, but also include a variety of experiences, one of which is the wedding party event service as a special event. However, with the Covid- 19 pandemic, the hotel business had to re-think so that the business could run and survive. One of the hotels that has been able to survive the pandemic that also offers wedding party event services is the Horison Ultima Bekasi hotel. The purpose of this study was to determine the marketing public relations strategy in the wedding party event at the Horison Bekasi hotel. The theory used in this study is the marketing public relations strategy of Thomas L. Harris which consists of a pull, push, and pass strategy. This research approach is qualitative. This type of research is descriptive. Information obtained from 4 informants. Data collection techniques through interviews, observation, and documentation. Data analysis techniques through the stages of data reduction, data presentation, drawing conclusions, and data verification. The results of the study show that the Horison Bekasi hotel uses conventional media and social media for publicity as a pull strategy, improving service quality and promos as a push strategy, as well as maintaining good relations with consumers and customer testimonials as a pass strategy. This is in accordance with the MPR strategy model put forward by Thomas L. Harris, namely the pull, push, and pass strategy.
EFFECTIVENESS OF THE ROLE OF PROGRAM COMMUNITY FACILITATORS NATIONAL AFFORDABLE HOUSING PROGRAM (NAHP) MINISTRY OF PUPR IN BALI PROVINCE
Authors: Tifani Aurellia , Anwar  , Kurniawan Agung Widhi , Sahabuddin Romansyah , Wardhana Haeruddin Muhammad Ilham
Published: March 2024

The National Affordable Housing Program (NAHP) implemented by the Ministry of PUPR (Public Works and Public Housing) aims to address housing affordability issues in the province of Bali. As part of the program, program community facilitators play a crucial role in facilitating the implementation and ensuring the program's effectiveness. Therefore, it becomes essential to evaluate the effectiveness of these facilitators in achieving the program's objectives. This study aims to determine the effectiveness of the role of program community facilitators National Affordable Housing Program (NAHP) Ministry of PUPR in the Province of Bali. The type of research used is descriptive qualitative. Descriptive provides a systematic description of cycles, problems, phenomena, services, programs, or information to individuals or groups wishing to study. The findings of this study explain the effectiveness of the role of the program has been achieved. The results of interviews with co-facilitators and beneficiary communities assessed the effectiveness of program understanding, target accuracy, timeliness, goal attainment, and real changes from the results of interviews with co-facilitators and beneficiary communities.
THE INFLUENCE OF ORGANIZATIONAL CULTURE, WORK ENVIRONMENT, AND WORKLOAD ON TURNOVER INTENTION OF EMPLOYEES PT. BUMI JAYA TRANSINDO SEJAHTERA
Authors: Dunan Hendri , Novita Fadila Rama
Published: March 2024

This study examines the effects of organizational culture, workload, and work environment on employee turnover at PT. Bumi Jaya Transindo Sejahtera. Using a quantitative research approach, the study collected data from all 74 employees at the organization through a questionnaire. The sampling technique used was saturated sampling due to the small population size. The data was analyzed using multiple linear regression analysis. The results showed that Organizational Culture (X1) and Work Environment (X2) had no significant impact on turnover intention. However, Workload (X3) was found to have a significant influence on turnover intention. Overall, this research highlights the importance of Organizational Culture, Work Environment, and Workload in understanding turnover intention. These findings provide valuable insights for organizations looking to improve employee retention strategies. Future research can explore specific interventions and policies to effectively address organizational culture, work environment, and workload concerns and reduce turnover intentions.
THE INFLUENCE OF TRAINING AND COMPENSATION ON EMPLOYEE PERFORMANCE IN WILD TIGER PRAWN FARMS IN TANGGAMUS
Authors: Fanni Yo , Iskandar Iskandar
Published: March 2024

Human resources play a crucial role in the success of a company. Therefore, it is essential for companies to provide effective training and fair compensation to enhance employee performance and ensure the smooth functioning of the organization. The objective of this study is to examine the impact of training and compensation on employee performance in windu alam tiger prawn farm. The research sample consisted of 30 employees, and the entire population was included using Non-Probability Saturation sampling technique. Data collection was done through a questionnaire system, and the analysis was conducted using multiple linear regression with the assistance of SPSS version 25. Various tests such as validity, reliability, normality, multicollinearity, and heteroscedasticity were performed to analyze the data. The hypothesis testing included simultaneous, partial, and R2 determination coefficient tests. The findings revealed that Training (X1) has a positive influence on Employee Performance (Y), and Compensation (X2) also has a positive impact on Employee Performance (Y). Moreover, the study concluded that both Training and Compensation have a positive effect on employee performance. This research holds both theoretical and practical implications, contributing to the field of human resource management and providing valuable insights for companies in making informed decisions.
Renoprotective strategies
Authors: Raikou Vaia D
Published: March 2024

Kidney disease remains a condition with an increasing incidence, high morbidity and mortality associated with cardiovascular events. The incidence of end-stage renal disease is expected to increase. Despite of the technical improvement, dialysis never achieved a full clearance of the blood dialysis. Therefore, the demand for new renoprotective measures has never been greater. Here, we report new strategies for preventing renal damage.
Prevalence and outcomes of polycystic kidney disease in African populations: A systematic review
Authors: Ndongo Modou , Nehemie Lot Motoula , Coundoul Baratou , Diouara Abou Abdallah Malick , Seck Sidy Mohamed
Published: March 2024

BACKGROUND

Polycystic kidney disease (PKD) is the most common genetic cause of kidney disease. It is a progressive and irreversible condition that can lead to end-stage renal disease and many other visceral complications. Current comprehensive data on PKD patterns in Africa is lacking.

AIM

To describe the prevalence and outcomes of PKD in the African population.

METHODS

A literature search of PubMed, African journal online, and Google Scholar databases between 2000 and 2023 was performed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses were followed to design the study. Clinical presentations and outcomes of patients were extracted from the included studies.

RESULTS

Out of 106 articles, we included 13 studies from 7 African countries. Ten of them were retrospective descriptive studies concerning 943 PKD patients with a mean age of 47.9 years. The accurate prevalence and incidence of PKD were not known but it represented the third causal nephropathy among dialysis patients. In majority of patients, the diagnosis of the disease was often delayed. Kidney function impairment, abdominal mass, and hypertension were the leading symptoms at presentation with a pooled prevalence of 72.1% (69.1–75.1), 65.8% (62.2–69.4), and 57.4% (54.2–60.6) respectively. Hematuria and infections were the most frequent complications. Genotyping was performed in few studies that revealed a high proportion of new mutations mainly in the PKD1 gene.

CONCLUSION

The prevalence of PKD in African populations is not clearly defined. Clinical symptoms were almost present with most patients who had kidney function impairment and abdominal mass at the diagnostic. Larger studies including genetic testing are needed to determine the burden of PKD in African populations.
Implementasi Framework Laravel Untuk Pengembangan Website Penjualan Ayam Potong Dengan Pemanfaatan Midtrans Menggunakan Metode Fast
Authors: Gibran Chaidir , Rafika Dewi Arie , Hadinata Edrian
Published: March 2024

Perusahaan ayam potong memiliki strategi untuk meningkatkan penjualan, peran penting dalam meningkatkan penjualan salah satunya dengan menerapkan strategi marketing dan promosi. Penelitian ini bertujuan untuk merancang sistem penjualan ayam potong berbasis website agar pembelian ayam potong secara online dan melakukan transaksi pembayaran melalui midtrans cepat dan efisien. Metode yang digunakan FAST (Framework for the application of systems thinking) dengan beberapa fase yaitu definisi lingkup, analisis permasalahan, analisis kebutuhan, desain logis, analisis keputusan dan desain fisik. Hasil dari penelitian ini adalah telah terciptanya sebuah website e-commerce dengan menggunakan bahasa pemrograman PHP yang di kombinasikan dengan database MySql, kelebihan website ini adalah mudah diakses oleh siapa saja secara online, melihat produk lengkap dengan detail dan melakukan transaksi pembayaran dengan mudah.
Penerapan Model Prototype Rancang Bangun Sistem Bimbingan Konseling Berbasis Web pada SMK Muhammadiyah 3 Pekanbaru
Authors: Marisa Vania , Ardi Wijaya Setiawan , Tsabitah Nayla
Published: March 2024

Unit Bimbingan Konseling adalah salah satu elemen penting pada praktik lembaga pendidikan untuk dapat melakukan pemantauan dan evaluasi terhadap akademik dan perilaku sosial siswa di SMK Muhammadiyah 3 Pekanbaru. Sebelumnya SMK Muhammadiyah 3 Pekanbaru melakukan kegiatan administrasi dan pengarsipan data yang bersifat konvensional. Permasalahan yang diperoleh berdasarkan observasi diantaranya pengolahan data konseling siswa yang dilakukan secara sederhana dengan pencatatan dan pengarsipan berkas siswa yang bersifat fisik serta waktu konseling yang tidak terjadwal yang dapat mengganggu kegiatan belajar siswa di kelas. Maka dari itu, dilakukan suatu Rancang Bangun Sistem Informasi untuk memfasilitasi layanan bimbingan konseling berbasis website yang terdigitalisasi agar tidak terjadinya pemborosan serta bertujuan untuk menanggulangi kekurangan yang ada dengan menggunakan bahasa pemrograman PHP, framework Laravel, dan menggunakan metode pengembangan sistem yaitu model prototype dan Unified Modeling Languange (UML) sebagai tools perancangan sistem serta menggunakan penyimpanan database terstruktur yaitu MySQL. Sistem telah melalui uji fungsional dengan metode pengujian black box. Hasil penelitian ini adalah Sistem Informasi yang dibangun dapat menjadi fasilitas bagi Unit BK di SMK Muhammadiyah 3 Riau dalam memberikan pelayanan konseling meliputi proses konseling, pemantauan rekam jejak siswa hingga penjadwalan konseling yang terdigitalisasi guna mencapai perkembangan yang sesuai dengan potensi siswa melalui aplikasi berbasis website yaitu SIMBEKA.
Makna Kasih Persaudaraan Kristiani
Authors: Angelo Luciani Moa Dosi Woda
Published: March 2024

In the midst of fast-paced times and the spread of various views, it feels like people are starting to forget the meaning of Christian brotherhood. It is as if the spirit of loving our fellow brothers and sisters like the Lord Jesus loved us is fading away. Now, modern humans are more likely to be "indifferent" to other people, and feel confident in determining themselves. Is this view true? What are the causes and bad effects of this wrong attitude? Can we overcome this prolonged crisis? What steps should be taken? We learn again to understand and appreciate Christian brotherly love.
Persepsi Dan Minat Pelaku UMKM Pengolahan Hasil Ternak Terhadap Sertifikasi Halal Di Kota Kediri
Authors: Chanifan Ibadi Fajar Herlambang  , Siti Azizah
Published: March 2024

Kediri City is considered to have significant potential for developing a halal market industry. The Muslim population in Kediri City is reported to be 271,215 according to the 2022 data on Subdistricts and Religions Practiced in Kediri City. With the majority of the population in Kediri City being Muslim, this presents a great opportunity for micro, small, and medium-sized enterprises (MSMEs) to continue developing their products to meet the community's needs for halal products in Kediri City. This research aims to understand the perceptions and interests of MSMEs players in livestock product processing regarding halal certification in Kediri City, using a qualitative method. Sample selection for this research utilized purposive sampling and snowball sampling. There were two types of informants in this study: 2 (two) expert informants, consisting of the Cooperative and MSMEs Office and the local Ministry of Religion, and 10 (ten) key informants, namely MSMEs actors in livestock product processing business. According to Article 4 of the UUJPH (Halal Product Assurance Law), products entering, circulating, and traded in Indonesia's territory must have halal certification. The halal label can have a positive impact on businesses as it is considered to enhance consumer trust in products with the halal label. Based on the research results, MSMEs players in livestock product processing business in Kediri City feel a lack of knowledge due to the government's insufficient comprehensive dissemination to every element of society.