User Control Research Articles

Trends in clinical characteristics, medication use, and glycemic control in insulin-treated patients with type 1 and type 2 diabetes in Finland in 2012-2019: Nationwide real-world evidence study.

To describe the clinical characteristics and medication purchases of insulin-treated adults in Finland at index (January 1, 2012 or first insulin purchase) and December 31, 2019. Additionally, to describe basal insulin (BI) treatment patterns and associated changes in hemoglobin A1c (HbA1c) values. In this descriptive study using nationwide registries, we included adults with at least two reimbursed insulin purchases within 12 months of the first purchase between January 1, 2012 and December 31, 2019. We formed four study groups: type 1 diabetes (T1D) and type 2 diabetes (T2D)-diagnosed people who were further divided into prevalent or naïve users (start of insulin use before or after January 1, 2012). Insulin treatment patterns were estimated from medication purchase data and glycemic control from HbA1c results. Out of 145 020 people included, 34 359 had T1D and 110 661 T2D. By 2019, in parallel with the adaptation of new noninsulin medications, second-generation basal insulin (BI) analogues were adopted by 45.9% and 21.1% of prevalent T1D and T2D users. At index, HbA1c target (≤53 mmol/mol) was reached by 17% and 35% of T2D naïve and prevalent users, respectively, and by 17% of T1D prevalent users. At study end, the target was reached respectively by 41%, 34%, and 22% of insulin users. Insulin initiation improved and discontinuation worsened glycemic control in T2D, with lesser effects seen after treatment gaps or switches between BIs. Our study showed that glycemic control in insulin users has remained stable or improved between 2012 and 2019 despite aging population and in parallel with introduction of new treatment options, providing valuable insight into Finnish national diabetes care.

Modifying RL Policies with Imagined Actions: How Predictable Policies Can Enable Users to Perform Novel Tasks

It is crucial that users are empowered to use the functionalities of a robot to creatively solve problems on the fly. A user who has access to a Reinforcement Learning (RL) based robot may want to use the robot's autonomy and their knowledge of its behavior to complete new tasks. One way is for the user to take control of some of the robot's action space through teleoperation while the RL policy simultaneously controls the rest. However, an out-of-the-box RL policy may not readily facilitate this. For example, a user's control may bring the robot into a failure state from the policy's perspective, causing it to act in a way the user is not familiar with, hindering the success of the user's desired task. In this work, we formalize this problem and present Imaginary Out-of-Distribution Actions, IODA, an initial algorithm for addressing that problem and empowering user's to leverage their expectation of a robot's behavior to accomplish new tasks.

Distributed Data-Driven Learning-Based Optimal Dynamic Resource Allocation for Multi-RIS-Assisted Multi-User Ad-Hoc Network

This study investigates the problem of decentralized dynamic resource allocation optimization for ad-hoc network communication with the support of reconfigurable intelligent surfaces (RIS), leveraging a reinforcement learning framework. In the present context of cellular networks, device-to-device (D2D) communication stands out as a promising technique to enhance the spectrum efficiency. Simultaneously, RIS have gained considerable attention due to their ability to enhance the quality of dynamic wireless networks by maximizing the spectrum efficiency without increasing the power consumption. However, prevalent centralized D2D transmission schemes require global information, leading to a significant signaling overhead. Conversely, existing distributed schemes, while avoiding the need for global information, often demand frequent information exchange among D2D users, falling short of achieving global optimization. This paper introduces a framework comprising an outer loop and inner loop. In the outer loop, decentralized dynamic resource allocation optimization has been developed for self-organizing network communication aided by RIS. This is accomplished through the application of a multi-player multi-armed bandit approach, completing strategies for RIS and resource block selection. Notably, these strategies operate without requiring signal interaction during execution. Meanwhile, in the inner loop, the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm has been adopted for cooperative learning with neural networks (NNs) to obtain optimal transmit power control and RIS phase shift control for multiple users, with a specified RIS and resource block selection policy from the outer loop. Through the utilization of optimization theory, distributed optimal resource allocation can be attained as the outer and inner reinforcement learning algorithms converge over time. Finally, a series of numerical simulations are presented to validate and illustrate the effectiveness of the proposed scheme.

ASSESSMENT OF SERVICE QUALITY OF PASURUAN E-SAMBAT APPLICATION WITH E-GOVQUAL DIMENSION APPROACH

Public services are government mediators in providing services to the needs of the community. The development of technology makes it easier for state and regional apparatuses to provide public services through an application called E-Government. Similarly, the Pasuruan City Communication and Information Agency has tried to organize the E-Sambat application. This study aims to provide an understanding of the quality of E-Sambat services based on the E-GovQual dimension approach, the gap between E-Sambat performance and public expectations for the E-Sambat application, and knowing which items will be prioritized to be immediately improved in the E-Sambat application. To analyze the feasibility of the application using GAP and the Important Performance Analysis (IPA) method is used to analyze items that are prioritized for improvement. Respondents in this study were 445 respondents. Based on the results of the analysis conducted, the quality of E-Sambat application services is very feasible with a feasibility percentage value of 100%, application performance GAP and public expectations for the Ease of Use variable of 0.08, Trust variable of -0.04, Functionality of the Interaction Environment variable of 0.02, Reliability variable of -0.03, Content and Information Display variable of 0.01, and the Community Support variable of 0.00. The overall average gap is 0.01 which means that people are satisfied with the E-Sambat application service. There are six items that are prioritized for improvement, namely TR 1 (security of personal data of E-Sambat users), TR 6 (access control of E-Sambat users), RLB 1 (speed in downloading E-Sambat forms), CAI 7 (use of colors in the E-Sambat application), CAI 8 (graphics in the E-Sambat application), and CS 5 (User questions answered quickly).

Multi-replicas integrity checking scheme with supporting probability audit for cloud-based IoT.

Nowadays, more people are choosing to use cloud storage services to save space and reduce costs. To enhance the durability and persistence, users opt to store important data in the form of multiple copies on cloud servers. However, outsourcing data in the cloud means that it is not directly under the control of users, raising concerns about security and integrity. Recent research has found that most existing multicopy integrity verification schemes can correctly perform integrity verification even when multiple copies are stored on the same Cloud Service Provider (CSP), which clearly deviates from the initial intention of users wanting to store files on multiple CSPs. With these considerations in mind, this paper proposes a scheme for synchronizing the integrity verification of copies, specifically focusing on strongly privacy Internet of Things (IoT) electronic health record (EHR) data. First, the paper addresses the issues present in existing multicopy integrity verification schemes. The scheme incorporates the entity Cloud Service Manager (CSM) to assist in the model construction, and each replica file is accompanied with its corresponding homomorphic verification tag. To handle scenarios where replica files stored on multiple CSPs cannot provide audit proof on time due to objective reasons, the paper introduces a novel approach called probability audit. By incorporating a probability audit, the scheme ensures that replica files are indeed stored on different CSPs and guarantees the normal execution of the public auditing phase. The scheme utilizes identity-based encryption (IBE) for the detailed design, avoiding the additional overhead caused by dealing with complex certificate issues. The proposed scheme can withstand forgery attack, replace attack, and replay attack, demonstrating strong security. The performance analysis demonstrates the feasibility and effectiveness of the scheme.

Key interoperability Factors for patient portals and Electronic health Records: A scoping review

AimTo identify the key requirements and challenges to interoperability between patient portals and electronic health records (EHRs). IntroductionPatient portals provide patients with access to their health information directly from EHRs within hospitals, primary care centres and general practices (GPs). Patient portals offer many benefits to patients including improved communication with healthcare providers and care coordination. However, many challenges exist with the integration and automatic and secure sharing of information between EHRs and patient portals. It is critical that countries learn from international experiences to successfully develop interoperable national patient portals. MethodsA scoping review methodology was undertaken. A search strategy using index terms and keywords was applied across four key databases, an additional grey literature search was also run. The identified studies were screened by two reviewers to determine eligibility against defined inclusion criteria. Data were abstracted from the eligible studies and reviewed to identify the key requirements and challenges to interoperability of patient portals with EHRs. ResultsAfter screening 3,462 studies, 34 were included across 11 countries. Of the 29 unique patient portals studied, few offered patients access to their entire healthcare record across multiple sites and a number of different functionalities were available. Key interoperability requirements and challenges identified were: Data Sharing Incentives & Supports; Heterogenous Organisations & Information Systems; Data Storage & Management; Available Information & Functionalities; Data Formats & Standards; Identification of Individuals; User Access, Control & Consent; and Security & Privacy. ConclusionSeamless exchange of health information across patient portals and EHRs required organisational and individual factors, as well as technical considerations. Interorganisational collaboration and engagement of key stakeholders to determine standards and guidelines for consent and sharing of information, as well as technical standards and security measures were recommended.

Exact hierarchical reductions of dynamical models via linear transformations

Dynamical models described by ordinary differential equations (ODEs) are a fundamental tool in the sciences and engineering. Exact reduction aims at producing a lower-dimensional model in which each macro-variable can be directly related to the original variables, and it is thus a natural step towards the model’s formal analysis and mechanistic understanding. We present an algorithm which, given a polynomial ODE model, computes a longest possible chain of exact linear reductions of the model such that each reduction refines the previous one, thus giving a user control of the level of detail preserved by the reduction. This significantly generalizes over the existing approaches which compute only the reduction of the lowest dimension subject to an approach-specific constraint. The algorithm reduces finding exact linear reductions to a question about representations of finite-dimensional algebras. We provide an implementation of the algorithm, demonstrate its performance on a set of benchmarks, and illustrate the applicability via case studies. Our implementation is freely available at https://github.com/x3042/ExactODEReduction.jl.

COVID-19 Outcome and Tobacco Product Use: Case-Control and Retrospective Cohort Studies Using Nationwide Samples.

Conflicting evidence exists regarding the association between smoking and the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We investigated the association between combustible cigarette (CC) smoking, noncombustible tobacco product (NCTP) use, and the use of any tobacco product with various coronavirus disease 2019 (COVID-19) outcomes. A case-control study was conducted using the Korea Disease Control and Prevention Agency-COVID19-National Health Insurance Service (NHIS) cohort. A retrospective cohort study was conducted using 12,571,698 individuals from the NHIS cohort. Logistic regression evaluated the association between CC smoking, NCTP use, and use of any tobacco product with SARS-CoV-2 infection. Poisson regression evaluated the association between these forms of tobacco product use and COVID-19-related hospitalization and mortality. In the case-control study, we identified 30,878 cases of SARS-CoV-2 infection. The odds ratios (95% confidence intervals [CIs]) for SARS-CoV-2 infection were lower among current CC smokers (0.51, 0.48-0.54), current- and former-NCTP users (0.80, 0.74-0.88; 0.82, 0.74-0.91), and current users of any tobacco product (0.52, 0.49-0.55) relative to never user controls. In retrospective cohort study, we identified 16,521 COVID-19-related hospitalization and 362 COVID-19-related deaths. The relative risks (95% CIs) for COVID-19-related hospitalization were lower among current CC smokers (0.51, 0.48-0.54) and current users of any tobacco product (0.53, 0.50-0.56) relative to never user controls. There was no association between the use of tobacco product and COVID-19-related mortality. Current CC smokers and current users of any tobacco product showed reduced risk of SARS-CoV-2 infection and COVID-19-related hospitalization. It remains uncertain whether these relationships are causal.

Architectural Design of IoT Agricultural System in Indonesia

Indonesia’s agricultural system is gradually transitioning towards a contemporary agricultural system. The agricultural system in Indonesia is characterized by its distinctiveness, encompassing a wide range of commodities and diverse meteorological conditions. Situations of this nature necessitate an automation approach based on the Internet of Things (IoT). We design three primary components in its architectural design: the user control and monitoring module, the sensing module, and the action module. The user control and monitoring module facilitates instantaneous monitoring and control through mobile devices and websites, while securely storing gathered data on remote cloud servers. The sensing module acquires environmental data, including light intensity, temperature, and soil moisture, and subsequently transmits this data to the control system via LoRa technology. The control system analyses this data and provides commands to modules that carry out operations such as irrigation, lighting, and nutrient spraying. LoRa technology is highly suitable for long-range communications with minimal power usage, making it an excellent choice for rural locations with unreliable networks. This architectural design enables independent monitoring and control of environmental factors to guarantee the most favourable conditions for crop development, consequently enhancing agricultural efficiency, productivity, and sustainability.

The ethical significance of user-control in AI-driven speech-BCIs: a narrative review.

AI-driven brain-computed interfaces aimed at restoring speech for individuals living with locked-in-syndrome are paired with ethical implications for user's autonomy, privacy and responsibility. Embedding options for sufficient levels of user-control in speech-BCI design has been proposed to mitigate these ethical challenges. However, how user-control in speech-BCIs is conceptualized and how it relates to these ethical challenges is underdetermined. In this narrative literature review, we aim to clarify and explicate the notion of user-control in speech-BCIs, to better understand in what way user-control could operationalize user's autonomy, privacy and responsibility and explore how such suggestions for increasing user-control can be translated to recommendations for the design or use of speech-BCIs. First, we identified types of user control, including executory control that can protect voluntariness of speech, and guidance control that can contribute to semantic accuracy. Second, we identified potential causes for a loss of user-control, including contributions of predictive language models, a lack of ability for neural control, or signal interference and external control. Such a loss of user control may have implications for semantic accuracy and mental privacy. Third we explored ways to design for user-control. While embedding initiation signals for users may increase executory control, they may conflict with other aims such as speed and continuity of speech. Design mechanisms for guidance control remain largely conceptual, similar trade-offs in design may be expected. We argue that preceding these trade-offs, the overarching aim of speech-BCIs needs to be defined, requiring input from current and potential users. Additionally, conceptual clarification of user-control and other (ethical) concepts in this debate has practical relevance for BCI researchers. For instance, different concepts of inner speech may have distinct ethical implications. Increased clarity of such concepts can improve anticipation of ethical implications of speech-BCIs and may help to steer design decisions.

Evolution-Based Shape and Behavior Co-Design of Virtual Agents.

We introduce a novel co-design method for autonomous moving agents' shape attributes and locomotion by combining deep reinforcement learning and evolution with user control. Our main inspiration comes from evolution, which has led to wide variability and adaptation in Nature and has significantly improved design and behavior simultaneously. Our method takes an input agent with optional user-defined constraints, such as leg parts that should not evolve or are only within the allowed ranges of changes. It uses physics-based simulation to determine its locomotion and finds a behavior policy for the input design that is used as a baseline for comparison. The agent is randomly modified within the allowed ranges, creating a new generation of several hundred agents. The generation is trained by transferring the previous policy, which significantly speeds up the training. The best-performing agents are selected, and a new generation is formed using their crossover and mutations. The next generations are then trained until satisfactory results are reached. We show a wide variety of evolved agents, and our results show that even with only 10% of allowed changes, the overall performance of the evolved agents improves by 50%. If more significant changes to the initial design are allowed, our experiments' performance will improve even more to 150%. Our method significantly improved motion tasks without changing body structures, and it does not require considerable computation resources as it works on a single GPU and provides results by training thousands of agents within 30 minutes.

A Robotic Teleoperation System Enhanced by Augmented Reality for Natural Human–Robot Interaction

Telekinesis, as commonly portrayed in science fiction literature and cinema, is a super power wherein users control and manipulate objects absent in physical interaction. In real world, enhancing human–robot interaction needs the synthesis of human intuitive processes with robotic arm. This paper introduces a robotic teleoperation system achieving the essence of telekinetic operations, combining the profound capabilities of augmented reality (AR) with the robotic arm operations. Utilizing AR, the proposed methodology offers operators with a visual feedback, facilitating a level of control surpassing the capacities of natural interfaces. By using AR-driven visual recognition, this system achieves operations in a virtual environment, subsequently actualized in the real world through the robotic arm. Through multiple experiments, we found that the system has a small margin of error in telekinesis operations, meeting the needs of remote operation. Furthermore, our system can operate on objects in the real world. These experiments underscore the capability of the remote control system to assist humans in accomplishing a wider range of tasks through the integration of AR and robotic arms, providing a natural human–robot interaction approach.

A Usability Survey of a Quality Improvement Data Visualization Tool among Medical Intensive Care Unit Nurses

Abstract Background Cognitive overload is prevalent among intensive care unit (ICU) clinicians. Data visualization may decrease cognitive load by assisting with data interpretation and task prioritization. We developed the Bundle Board to display real-time data from the electronic medical record (EMR), highlighting opportunities for action in standardized ICU patient care. This study evaluates the practical usability of this data visualization tool among nurses in the ICU. Methods The tool is offered as an application separate from the EMR and was available in the medical ICU for 8 months before we surveyed unit nursing staff. To evaluate usability of the tool, we adapted the Health-Information Technology Usability Scale and included an option to provide open-ended feedback. Survey data were analyzed using quantitative and qualitative methods. Results ICU nurses were invited to participate through email and verbal announcements. Of the potential participants, 38% (N = 47) responded. The survey demonstrated that the tool was perceived as usable. For each subscale, mean scores were as follows: Perceived Ease of Use 4.40, Impact 4.14, User Control 4.07, and Perceived Usefulness 3.61. There were no significant differences between core and contracted nurses or after stratifying by duration of Bundle Board use. Fifteen respondents completed the optional free-text portion of the survey. Qualitative analysis revealed six subthemes focusing on perceived impacts on quality and safety, cognitive burden and workload, and emotional impact of the Bundle Board. Conclusion The Bundle Board demonstrated good usability among ICU nurses, who provided substantive feedback for its improvement. These observations may be generalizable to other comparable interventions. Iterative feedback from end users is vital to developing and implementing a digital health intervention. Our study provides a framework for performing a usability analysis within a specific clinician population and environment.

The Impact of Problematic Social Media Use on Inhibitory Control and the Role of Fear of Missing Out: Evidence from Event-Related Potentials.

The general deficit in inhibitory control of problematic social media users has received widespread attention. However, the neural correlates of problematic social media use (PSMU) and inhibitory control remain unclear. Additionally, the co-occurrence of the fear of missing out (FoMO) with social media use is common, yet its role in the relationship between PSMU and inhibitory control has not been investigated. This study aimed to examine the electrophysiological correlates of PSMU and inhibitory control using a modified two-choice oddball task combined with event-related potentials (ERPs), and to explore the role of FoMO in this relationship. A total of 66 participants with varying degrees of PSMU were included in the analysis based on the Problematic Mobile Social Media Usage Questionnaire. The study found that PSMU could impact inhibitory control. Specifically, as the PSMU score increases, the N2 amplitude is greater for social media-related pictures, and the P3 amplitude is smaller, while no significant differences are observed for neutral pictures. This suggests that PSMU affects inhibitory control by consuming more cognitive resources in the early conflict detection stage and leading to insufficient cognitive resources in the later stages of the inhibitory process. Furthermore, FoMO played a mediating role between PSMU and inhibitory control. PSMU could further impact inhibitory control through FoMO. This study provides electrophysiological evidence for deficits in inhibitory control in PSMU and suggests that FoMO may further reduce inhibitory control in PSMU individuals.

Design and Implementation of an Autonomous Wheelchair with Medical Kit Access Using Raspberry Pi

This paper presents an autonomous wheelchair system designed to enhance the mobility of elderly individuals and people with disabilities through advanced automation and artificial intelligence. Recognizing the importance of independent movement for promoting physical and psychological well-being, this system addresses the challenges faced by those with limited mobility. The wheelchair leverages various sensors to minimize the need for human intervention, thereby fostering autonomy and reducing reliance on caregivers. The system includes an Android interface connected via Bluetooth, allowing for intuitive user interaction and control. Utilizing Raspberry Pi technology, the research aims to create a reliable framework that can adapt to user needs through data processing and analysis. Additionally, the system enables effective communication through head-mounted support, allowing users to record and relay information. Ultimately, this autonomous wheelchair aims to improve mobility and confidence for individuals with disabilities while enhancing their overall independence and quality of life.

Decentralized Finance: Principles of Functioning, Infrastructure, Risks

The article analyzes the differences between centralized and decentralized exchanges in the cryptocurrency market. The author notes the impact of bankruptcies of centralized representatives who provided services in the cryptocurrency market on the interaction of users with decentralized finance instruments. The publication considers the key representatives of decentralized finance, their capitalization, available capital, and technological developments. It substantiates the advantages and risks of using decentralized finance instruments and studies the differences between centralized, decentralized, and algorithmic stablecoins. To assess the capitalization of decentralized finance instruments, the asset value indicator TVL (Total Value Locked) is used. TVL represents the amount of assets currently placed in a particular decentralized finance instrument or protocol. The RWA narrative is significant in the crypto space as it demonstrates increased interconnectedness. DeFi, previously isolated from TradFi, has now become an integral part of a more holistic financial ecosystem. Blockchain technology has demonstrated its potential for transformation through real-world use cases. Real-world assets (RWAs) are an attractive option due to the large traditional finance market. While they offer benefits such as portfolio diversification and enhanced returns, it is crucial to mitigate default risk. Platforms like Goldfinch have a proven track record. Tokenizing RWAs can increase market participation and financial inclusivity. The study's results indicate significant development of decentralized finance instruments over the past three years. This is evidenced by the amount of capital invested in these instruments and the number of users, despite the technological and regulatory risks associated with them. The study's conclusions indicate that despite the technological novelty, users are increasingly interested in interacting with decentralized finance instruments. However, users face difficulties in understanding how these instruments work and in gaining experience with these products. The comparative analysis by Saif Ahmed Abdulhakeem and Qiuling Hu titled "CeFi vs. DeFi — Comparing Centralized to Decentralized Finance" systematically contrasts Centralized Finance (CeFi) with Decentralized Finance (DeFi) across legal, economic, security, privacy, and market manipulation dimensions. It aims to provide a structured approach for distinguishing between CeFi and DeFi services, emphasizing DeFi's transparency and user control advantages. However, unresolved issues in decentralized finance, such as regulatory frameworks and risk assessment, necessitate further research. The study also underscores the importance of improving user experience design and overcoming adoption challenges for DeFi. In their academic discourse titled "Powered by Blockchain Technology, DeFi (Decentralized Finance) Strives to Increase Financial Inclusion of the Unbanked by Reshaping the World Financial System," Abdulhakeem and Hu analyze DeFi's potential to enhance financial inclusion for the unbanked. They highlight the pivotal role of blockchain, particularly Ethereum, in enabling DeFi. While acknowledging DeFi's decentralization benefits, the article suggests it as a complement rather than a replacement for traditional finance. It advocates for future research on integrating DeFi with global banking systems and improving user interface and security. Overall, while recognizing DeFi's transformative potential, the article underscores the need for ongoing research to address challenges and integrate DeFi into mainstream finance seamlessly.

A User Control Framework for Cloud Data Migration in Software as a Service

A User Control Framework for Cloud Data Migration in Software as a Service

Development of a self-contained microfluidic chip and an internet-of-things-based point-of-care device for automated identification of respiratory viruses.

The COVID-19 pandemic greatly impacted the in vitro diagnostic market, leading to the development of new technologies such as point-of-care testing (POCT), multiplex testing, and digital health platforms. In this study, we present a self-contained microfluidic chip integrated with an internet-of-things (IoT)-based point-of-care (POC) device for rapid and sensitive diagnosis of respiratory viruses. Our platform enables sample-to-answer diagnostics within 70 min by automating RNA extraction, reverse transcription-loop-mediated isothermal amplification (RT-LAMP), and fluorescence detection. The microfluidic chip is designed to store all the necessary reagents for the entire diagnostic assay, including a lysis buffer, a washing buffer, an elution buffer, and a lyophilized RT-LAMP cocktail. It can perform nucleic acid extraction, aliquoting, and gene amplification in multiple reaction chambers without cross-contamination. The IoT-based POC device consists of a Raspberry Pi 4 for device control and data processing, a CMOS sensor for measuring fluorescence signals, a resistive heater panel for temperature control, and solenoid valves for controlling the movement of on-chip reagent solutions. The proposed device is portable and features a touchscreen for user control and result display. We evaluated the performance of the platform using 11 clinical respiratory virus samples, including 5 SARS-CoV-2 samples, 2 influenza A samples, and 4 influenza B samples. All tested clinical samples were accurately identified with high specificity and fidelity, demonstrating the ability to simultaneously detect multiple respiratory viruses. The combination of the integrated microfluidic chip with the POC device offers a simple, cost-effective, and scalable solution for rapid molecular diagnosis of respiratory viruses in resource-limited settings.

인공지능 기반의 문학번역에 관한 저작권법 문제

Translation is a form of creativity, and AI creativity is making remarkable strides in many fields, including music, art, and literature, but especially in literature translation, where AI-based machine translation is becoming a reality. The recent happening about the winner of the Newcomer Award Competition of Literature Translation Institute of Korea, who was found to have utilized machine translation, has drawn attention to the question of how to set the boundaries between machine and human translation. I argue that AI-generated translation (AIGT), which is a purely AI translation without human assistance, is only reproduction under copyright law, while AI-assisted translation (AIAT), which is a human translation with the help of AI, can be a derivative work under copyright law as a translation. The distinguishing factor between the two is the control and subjectivity of human users of machine translation in the post-editing process, and the context surrounding the translation. This paper points out that excessive pre-editing by human users to facilitate machine translation may undermine the diversity of the original text. Once the legal status of machine translation output has been determined, I discuss the legal responsibility of human users to exercise due care at the stage of publication. The legal liability of failing to disclose that a work is the result of machine translation is also discussed, as well as plagiarism liability, which is not a legal liability.

Pengaruh Literasi Keuangan Terhadap Perilaku Konsumtif dan Locus of Control Pada Penggunaan Shopee Paylater

This study aims to determine the effect of Financial Literacy on Consumptive Behavior Through Locus Of Control in Using Shopee Payleter in Millennial Generation (Study on University Students in Lamongan). The object of this research is all the millennial generation or university students in Lamongan. The sample in this study were students majoring in Accounting class of 2019 and 2020 at universities in Lamongan. This study uses primary data by distributing questionnaires online to 100 respondents using the solvin formula, which is a university millennial generation in Lamongan aged 22-40 years and is a Shopee Paylater user. This study uses the technique of Probability Sampling with Simple Random Sampling Technique. This study uses the Partial Least Square (PLS) approach using the SmartPLS Version 3.0 application. The results showed that financial literacy has a significant effect on the consumptive behavior of shopee paylater users with a positive relationship direction. Financial literacy has a significant effect on the locus of control of shopee paylater users with a positive relationship direction. Locus of control has a significant effect on the consumptive behavior of shopee payleter users. can mediate the relationship of financial literacy to the consumptive behavior of Shopee Paylater users with a positive relationship direction.