While the benefits of nature—such as clean air, food, and recreational spaces—are widely acknowledged, a recent study by Tajima et al. (2025) sheds light on a more personal dimension of our relationship with the natural world: relational values. These refer to the values individuals place on nature stemming from their sense of identity, lived experiences, and the social connections fostered through nature. Centered on Japan’s culturally significant Nagara River Basin—renowned for its enduring traditions like cormorant fishing and washi papermaking—the study (...) surveyed 2,031 residents to explore how and why they value the river. (shrink)

Tập trung vào lưu vực sông Nagara ở Nhật Bản—một khu vực có giá trị văn hóa lâu đời với các truyền thống như đánh cá bằng chim cốc và làm giấy washi—nghiên cứu đã khảo sát 2.031 cư dân để tìm hiểu cách thức và lý do họ trân trọng con sông này.

Many trading desks across the financial industry still rely heavily on Excel-based tools for pricing, risk assessment, and reporting workflows. While these spreadsheets offer flexibility and familiarity, they present challenges in scalability, collaboration, version control, and integration with modern trading infrastructure. This paper presents a cloud-native migration framework that transforms trader-centric Excel tools into robust, scalable applications using Java and Python. The framework incorporates modular microservices, RESTful APIs, AWS services, and real-time data processing. It also addresses migration challenges such (...) as formula translation, data validation, and end-user adoption. The resulting system improves performance, auditability, and maintainability while retaining the usability traders expect. (shrink)

Accurate and timely validation of trade inputs is critical in high-frequency commodity and financial trading environments. Manual or delayed validation can result in erroneous trades, compliance risks, and operational inefficiencies. This paper presents a real-time input validation system for traders, implemented using low-latency Java APIs and AWS Kinesis. The system ensures that inputs are checked against business rules and market constraints in milliseconds before proceeding to execution workflows. Our architecture leverages AWS Kinesis for high-throughput data streaming, Java-based microservices (...) for synchronous rule enforcement, and DynamoDB for persistent rule management and transaction tracking. The system demonstrates strong scalability, low latency, and adaptability across diverse trading desks. (shrink)

- As cloud computing continues to drive digital transformation, multi-tenant application architectures have emerged as a foundational paradigm for delivering scalable and cost-effective software-as-a-service (SaaS) solutions. These architectures enable multiple tenants—representing different organizations or user groups—to share a common application instance while maintaining strict isolation, performance guarantees, and security compliance. However, ensuring resilience in such environments introduces significant architectural and operational complexities. This paper presents a comprehensive study on designing resilient multi-tenant applications using popular Java-based frameworks such as Spring (...) Boot, Quarkus, and Micronaut. (shrink)

Following the Special Autonomy Law in 2001, the number of Papuan students studying out of town soared, resulting integration into a new culture becomes inevitable. The authors were interested in exploring academic and social integration experiences amongst Papuan university students in Java. Semi-structured interview was used to collect data from six Papuan students (four males and two females). Data was analyzed using thematic analysis to identify factors influencing integration strategy and to explore how stereotypes affect the minority student’s acculturation (...) strategy. These factors included the student’s personality traits and motivation, prior contact with outgroup members, support from the university, academic barriers, and language/communication barriers. Additionally, the study found that negative stereotypes were more commonly experienced by indigenous Papuan students compared to mixed-Papuan students. This suggests that cultural background of the students may play a role in their integration experiences. While the sample size of this study was small and may not be representative of the broader population, the findings provide important implications for educational institutions. The study highlights the importance of involving ethnic minorities in shaping educational policies related to integration. By addressing the factors identified in this study, educational institutions can create a more positive environment for all students. (shrink)

Abstract. Intelligent Tutoring System Builder (ITSB) is an authoring tool designed and developed to aid teachers in constructing intelligent tutoring systems in a multidisciplinary fields. The teacher is needed to create a set of pedagogical fundamentals, which, in line, are inured to automatically build up a broad tutor framework and construct an intelligent tutoring system. In this paper an explanation of the theory and the architecture of the tool is outlined. A presentation of several system components, the requirements of the (...) different components, integration of these components in ITSB tool are shown. Furthermore, implanting of requirements, cognitive principle, and common design fundamentals in the tool to ease the use of teachers. A variety of design matters, an example of building an intelligent tutoring system for teaching Java language using ITSB tool and an evaluation are presented. (shrink)

In fact, people get neck problems due to something such as sports or woke and Wrong sleep habits. In this paper an expert system was designed to help users to correctly diagnose neck problems world (muscle spasm, Muscle aches, Meningitis, herniated cervical disc, Fibromyalgia, Cervical spondylosis, Trigger points) with some information about the disease and self-care. Java language was used to design and implement this expert system.

This comprehensive article explores the convergence of cloud computing and Java technologies, highlighting their synergistic relationship in modern software development. It examines key concepts in cloud computing, including virtualization, microservices architecture, CI/CD practices, and serverless computing. The article also discusses various cloud service models (SaaS, PaaS, and IaaS), their applications, and essential tools and technologies for cloud development. A financial institution's infrastructure modernization case study illustrates the practical implementation of these concepts, demonstrating how cloud technologies and Java can (...) enhance agility, reliability, cost-efficiency, and innovation in traditional industries. (shrink)

When a widely reused ontology appears in a new version which is not compatible with older versions, the ontologies reusing it need to be updated accordingly. Ontobull has been developed to automatically update ontologies with new term IRI(s) and associated metadata to take account of such version changes. To use the Ontobull web interface a user is required to (i) upload one or more ontology OWL source files; (ii) input an ontology term IRI mapping; and (where needed) (iii) provide update (...) settings for ontology headers and XML namespace IDs. Using this information, the backend Ontobull Java program automatically updates the OWL ontology files with desired term IRIs and ontology metadata. The Ontobull subprogram BFOConvert supports the conversion of an ontology that imports a previous version of BFO. A use case is provided to demonstrate the features of Ontobull and BFOConvert. (shrink)

Randomization procedures are used in legal and statistical applications, aiming to shield important decisions from spurious influences. This article gives an intuitive introduction to randomization and examines some intended consequences of its use related to truthful statistical inference and fair legal judgment. This article also presents an open-code Java implementation for a cryptographically secure, statistically reliable, transparent, traceable, and fully auditable randomization tool.

In the competitive and dynamic world of financial technology (fintech), high performance and low latency are crucial for real-time transactions and data processing. Microservices architecture, combined with efficient caching mechanisms, significantly enhances scalability and responsiveness. VMware GemFire, an in-memory data grid, provides robust caching solutions that, when paired with Java 17’s Z Garbage Collector (ZGC) and heap Least Recently Used (LRU) eviction strategies, can maximize cache performance. This paper proposes a system integrating GemFire with ZGC to optimize memory management, (...) reduce latency, and maintain high throughput. The heap LRU eviction strategy ensures that the least recently used data is evicted first when memory limits are reached, maintaining high cache hit rates and reducing the risk of the JVM running out of memory. By adjusting ZGC and using heap LRU eviction, this combined method makes it easier for microservices to handle changing workloads, grow horizontally, and speed up data access, which improves the overall performance and reliability of the system. Different settings for SoftMaxHeapSize have different effects on heap usage, operation throughput, and garbage collection performance. The results of the experiments show how to tune GemFire cache performance to work best in a microservices environment. (shrink)

Kuda Lumping, or ébég, is a deep spiritual traditional art form from Indonesia. Communities, especially in Java, are increasingly focused on preserving it. The dance is not just entertainment, but also has a spiritual dimension with frequent possessions. It involves dancers, horse-shaped vehicles made of animal skin or bamboo, and spiritual figures. As an intangible cultural heritage, Kuda Lumping serves to bind communities, educate, perform rituals, and express art. Evolving interpretations regarding its profane and sacred aspects will be unveiled (...) through cultural research. This research utilizes a literature review method with hermeneutics as an interpretative tool to understand related texts. Data is collected through readings and analyzed using content analysis. Hermeneutics, as a social-humanistic approach, focuses on the internal aspects of humans. In conclusion, Kuda Lumping expresses its spiritual function, provides entertainment and education, and conveys messages about awareness and goodness. Preservation requires attention to choreography and philosophy. Government, artists, society, and academics play an important role in promoting and developing this dance while considering the Tri Tangtu concept. (shrink)

This paper shows the smart walking stick based on ultrasonic sensors and Arduino for outwardly debilitated individuals. There are roughly 37 million individuals over the globe who are visually impaired as indicated by the World Health Organization. Individuals with visual inabilities are regularly subjected to outer help which can be given by people, trained dogs, or electronic gadgets as supportive networks for basic assistance. Thus, this played as the motivation to develop a smart cane white stick to survive these restrictions (...) which includes ultrasonic sensors at particular positions to the stick that gave data about nature to the client by initiating the signal sound and vibrations. We proposed minimal effort and light weight framework structured with micro controller that processes signal and alerts the visually impaired person over any obstacle, water or dark areas through beeping sounds or vibrations. The system comprises of obstacle and moisture detection sensors for process of receiving, processing and sending signals to the alarm system which finally alerts the user for prompt action. The system was designed, programmed using Java language and tried for exactness by the visually impaired. Our gadget can recognize obstacle inside the separation of around 2m from the client. (shrink)

Abstract—Breast cancer is considered the second most common cancer in women compared to all other cancers. It is fatal in less than half of all cases and is the main cause of mortality in women. It accounts for 16% of all cancer mortalities worldwide. Early diagnosis of breast cancer increases the chance of recovery. Data mining techniques can be utilized in the early diagnosis of breast cancer. In this paper, an academic experimental breast cancer dataset is used to perform a (...) data mining practical experiment using the Waikato Environment for Knowledge Analysis (WEKA) tool. The WEKA Java application represents a rich resource for conducting performance metrics during the execution of experiments. Pre-processing and feature extraction are used to optimize the data. The classification process used in this study was summarized through thirteen experiments. Additionally, 10 experiments using various different classification algorithms were conducted. The introduced algorithms were: Naïve Bayes, Logistic Regression, Lazy IBK (Instance-Bases learning with parameter K), Lazy Kstar, Lazy Locally Weighted Learner, Rules ZeroR, Decision Stump, Decision Trees J48, Random Forest and Random Trees. The process of producing a predictive model was automated with the use of classification accuracy. Further, several experiments on classification of Wisconsin Diagnostic Breast Cancer and Wisconsin Breast Cancer, were conducted to compare the success rates of the different methods. Results conclude that Lazy IBK classifier k-NN can achieve 98% accuracy among other classifiers. The main advantages of the study were the compactness of using 13 different data mining models and 10 different performance measurements, and plotting figures of classifications errors. (shrink)

: Serverless computing has revolutionized the way modern cloud-native applications are developed and deployed, offering a paradigm in which developers can focus solely on writing code without the burden of managing infrastructure. Among the various Function-as-a-Service (FaaS) offerings, AWS Lambda stands out as a widely adopted platform due to its automatic scaling, event-driven execution, and pay-per-use pricing model—making it ideal for applications ranging from microservices to complex event-driven workflows. However, serverless architectures present challenges in cold start latency, performance tuning, and (...) cost optimization, particularly when using heavyweight runtimes like Java or under sporadic invocation patterns. This study systematically evaluates AWS Lambda’s performance under varying load conditions by analyzing runtime performance (Java vs. Python), memory allocation, payload size, and traffic types including steady, burst, and spiky patterns. Key metrics such as cold start time, average execution duration, and cost per invocation are examined using real-world traffic simulations and observability tools like AWS CloudWatch and X-Ray. The findings demonstrate that tuning memory allocation, applying provisioned concurrency, and selecting lightweight runtimes can significantly improve latency and cost-efficiency. The paper concludes with best practices for serverless workload optimization, offering actionable insights for software architects and DevOps teams aiming to balance scalability, responsiveness, and operational cost in cloud-native deployments. (shrink)