Hasil untuk "Commercial law"

P. Walsh, K. Abernethy, M. Bermejo et al.

Zhe Li, Kun Cheng, Hanyue Mo et al.

A vision-based trajectory analysis solution is proposed to address the "zero-speed braking" issue caused by inaccurate Controller Area Network (CAN) signals in commercial vehicle Automatic Emergency Braking (AEB) systems during low-speed operation. The algorithm utilizes the NVIDIA Jetson AGX Xavier platform to process sequential video frames from a blind spot camera, employing self-adaptive Contrast Limited Adaptive Histogram Equalization (CLAHE)-enhanced Scale-Invariant Feature Transform (SIFT) feature extraction and K-Nearest Neighbors (KNN)-Random Sample Consensus (RANSAC) matching. This allows for precise classification of the vehicle's motion state (static, vibration, moving). Key innovations include 1) multiframe trajectory displacement statistics (5-frame sliding window), 2) a dual-threshold state decision matrix, and 3) OBD-II driven dynamic Region of Interest (ROI) configuration. The system effectively suppresses environmental interference and false detection of dynamic objects, directly addressing the challenge of low-speed false activation in commercial vehicle safety systems. Evaluation in a real-world dataset (32,454 video segments from 1,852 vehicles) demonstrates an F1-score of 99.96% for static detection, 97.78% for moving state recognition, and a processing delay of 14.2 milliseconds (resolution 704x576). The deployment on-site shows an 89% reduction in false braking events, a 100% success rate in emergency braking, and a fault rate below 5%.

Kaisei Higeta, Masakatsu Ogawa, Tomoki Murakami et al.

With the advent of the 6G era, Integrated Sensing and Communications (ISAC) has attracted increasing attention. One representative of use cases is crowd flow estimation on outdoor streets. However, most existing studies have focused on indoor environments or vehicles, and demonstrations of outdoor crowd flow estimation using commercial LTE base station remain limited. This study addresses this use case and proposes an analysis of a crowd flow estimation method using Reference Signal Received Power (RSRP) obtained from a commercial LTE base station. Specifically, pedestrian counts derived from a camera-based object recognition algorithm were associated with the variance of RSRP. The features obtained from the variance were quantitatively evaluated by combining a CatBoost regression model with SHapley Additive exPlanations (SHAP) analysis. Through this investigation, we clarified that an optimal variance window size for RSRP is 0.1 to 0.2 seconds and that enlarging the counting area increased the features obtained from the variance of RSRP, for machine learning. Consequently, this study is the first to quantitatively demonstrate the effectiveness of outdoor crowd flow estimation using commercial LTE, while also revealing the characteristic behavior of variance window size and counting area size in feature design.

Ryo Yonetani

This paper presents Piggyback Camera, an easy-to-deploy system for visual surveillance using commercial robot vacuums. Rather than requiring access to internal robot systems, our approach mounts a smartphone equipped with a camera and Inertial Measurement Unit (IMU) on the robot, making it applicable to any commercial robot without hardware modifications. The system estimates robot poses through neural inertial navigation and efficiently captures images at regular spatial intervals throughout the cleaning task. We develop a novel test-time data augmentation method called Rotation-Augmented Ensemble (RAE) to mitigate domain gaps in neural inertial navigation. A loop closure method that exploits robot cleaning patterns further refines these estimated poses. We demonstrate the system with an object mapping application that analyzes captured images to geo-localize objects in the environment. Experimental evaluation in retail environments shows that our approach achieves 0.83 m relative pose error for robot localization and 0.97 m positional error for object mapping of over 100 items.

Tyler J Poore, Christopher J Pinard, Aleena Shabbir et al.

Large language models (LLMs) are increasingly used in clinical settings, yet their performance in veterinary medicine remains underexplored. We evaluated three commercially available veterinary-focused LLM summarization tools (Product 1 [Hachiko] and Products 2 and 3) on a standardized dataset of veterinary oncology records. Using a rubric-guided LLM-as-a-judge framework, summaries were scored across five domains: Factual Accuracy, Completeness, Chronological Order, Clinical Relevance, and Organization. Product 1 achieved the highest overall performance, with a median average score of 4.61 (IQR: 0.73), compared to 2.55 (IQR: 0.78) for Product 2 and 2.45 (IQR: 0.92) for Product 3. It also received perfect median scores in Factual Accuracy and Chronological Order. To assess the internal consistency of the grading framework itself, we repeated the evaluation across three independent runs. The LLM grader demonstrated high reproducibility, with Average Score standard deviations of 0.015 (Product 1), 0.088 (Product 2), and 0.034 (Product 3). These findings highlight the importance of veterinary-specific commercial LLM tools and demonstrate that LLM-as-a-judge evaluation is a scalable and reproducible method for assessing clinical NLP summarization in veterinary medicine.

María Cerezo-Magaña, Alberto Olivares, Ernesto Staffetti

In this article, the formation mission design problem for commercial aircraft is studied. Given the departure times and the departure and arrival locations of several commercial flights, the relevant weather forecast, and the expected fuel savings during formation flight, the problem consists in establishing how to organize them in formation or solo flights and in finding the trajectories that minimize the overall direct operating cost of the flights. Each aircraft can fly solo or in different positions inside a formation. Therefore, the mission is modeled as a switched dynamical system, in which the discrete state describes the combination of flight modes of the individual aircraft and logical constraints in disjunctive form establish the switching logic among the discrete states of the system. The formation mission design problem has been formulated as an optimal control problem of a switched dynamical system and solved using an embedding approach, which allows switching decision among discrete states to be modeled without relying on binary variables. The resulting problem is a classical optimal control problem which has been solved using a knotting pseudospectral method. Several numerical experiments have been conducted to demonstrate the effectiveness of this approach. The obtained results show that formation flight has great potential to reduce fuel consumption and emissions.

Divine Grace C. Domingo, Maria Theresa M. Talavera, Angelina Rosario Bustos et al.

Background The study focused on understanding infant and young child feeding practices (IYCF) among Muslim mothers in the Bangsamoro Autonomous Region in Muslim Mindanao (BARMM), Philippines. Objective Recognizing the cultural and religious sensitivities associated with these practices, the research aimed to identify influencing factors and assess the influence of advertisements on maternal decisions regarding infants' and children's diets. Methods A total of 74 Muslim mothers with infants 6-23 months old were recruited and participated in the focus group discussions (FGD). Ten FGD sessions were conducted in Maguindanao Province, Philippines from July to August 2021. Verbatim transcriptions of audio-recorded discussions were transcribed into Microsoft Word files and QSR NVivo version 12 was used in the coding and analysis of the transcripts. Results Mothers exhibited limited awareness of such important complementary feeding issues as preferring fruits and vegetables while avoiding junk food as chips. IYCF information came primarily from health workers and other mothers - their own mothers, mothers-in-law, and midwives. Television commercials were identified as particularly influential in shaping maternal feeding decisions. Conclusions There was a diversity of breastfeeding practices and limited knowledge, especially of complementary feeding among these Muslim mothers. Both traditional beliefs and marketing were said to influence feeding choices. This underscores the need for culturally-sensitive interventions and targeted educational initiatives to enhance maternal knowledge and advocate for optimal infant feeding practices within Muslim communities, as well as regulation of the marketing of commercial infant foods.

Ritu Birla

In Stages of Capital , Ritu Birla brings research on nonwestern capitalisms into conversation with postcolonial studies to illuminate the historical roots of India’s market society. Between 1870 and 1930, the British regime in India implemented a barrage of commercial and contract laws directed at the “free” circulation of capital, including measures regulating companies, income tax, charitable gifting, and pension funds, and procedures distinguishing gambling from speculation and futures trading. Birla argues that this understudied legal infrastructure institutionalized a new object of sovereign management, the market, and along with it, a colonial concept of the public. In jurisprudence, case law, and statutes, colonial market governance enforced an abstract vision of modern society as a public of exchanging, contracting actors free from the anachronistic constraints of indigenous culture. Birla reveals how the categories of public and private infiltrated colonial commercial law, establishing distinct worlds for economic and cultural practice. This bifurcation was especially apparent in legal dilemmas concerning indigenous or “vernacular” capitalists, crucial engines of credit and production that operated through networks of extended kinship. Focusing on the story of the Marwaris, a powerful business group renowned as a key sector of India’s capitalist class, Birla demonstrates how colonial law governed vernacular capitalists as rarefied cultural actors, so rendering them illegitimate as economic agents. Birla’s innovative attention to the negotiations between vernacular and colonial systems of valuation illustrates how kinship-based commercial groups asserted their legitimacy by challenging and inhabiting the public/private mapping. Highlighting the cultural politics of market governance, Stages of Capital is an unprecedented history of colonial commercial law, its legal fictions, and the formation of the modern economic subject in India.

A. Morales

Paolo Branchini, Andrea Fabbri, Sacha Cormenier et al.

This paper presents the results of the irradiation, performed with atmospheric-like neutrons and heavy-ions, of Commercial Off-the Shelf Components (COTS), which can be used in space missions. In such cases, it is crucial to perform tests in a radiation environment that emulates the environment of different orbits around Earth. In our study we used atmosphericlike neutrons with fluences up to 1011 neutrons/cm-2 and Kr ions of fluences up to 107 ions/cm-2. These intensities are augmented with respect to the atmospheric one in order to shorten the irradiation time while simulating a long-time exposure during a possible mission in Low Earth Orbit (LEO). A similar radiation environment to LEO can also be present during High-Energy Physics experiments. Therefore, the study herby reported can also be helpful for accelerator physics. In this paper we show in detail procedures, setup and results we have obtained on a commercial device normally exploited in automotive environments.

Md Shah Naoaj

This study investigates the factors that influence the capital adequacy of commercial banks in Bangladesh using panel data from 28 banks over the period of 2013-2019. Three analytical methods, including the Fixed Effect model, Random Effect model, and Pooled Ordinary Least Square (POLS) method, are employed to analyze two versions of the capital adequacy ratio, namely the Capital Adequacy Ratio (CAR) and Tier 1 Capital Ratio. The study reveals that capital adequacy is significantly affected by several independent variables, with leverage and liquidity risk having a negative and positive relationship, respectively. Additionally, the study finds a positive correlation between real GDP and net profit and capital adequacy, while inflation has a negative correlation. For the Tier 1 Ratio, the study shows no significant relationship betweenleverage and liquidity risk, but a positive correlation with the number of employees, net profit, and real GDP, while a negative correlation with size and GDP deflator. Pooled OLS analysis reveals a negative correlation with leverage, size, and inflation for both CAR and Tier 1 Capital Ratio, and a positive correlation with liquidity risk, net profit, and real GDP. Based on the Hausman test, the Random Effect model is deemed moresuitable for this dataset. These findings have important implications for policymakers, investors, and bank managers in Bangladesh by providing insights into the factors that impact the capital ratios of commercial banks.

Alejandro Díaz Reyes, José Fernando Vázquez Avedillo

Esta investigación tiene como objeto analizar la infracción y el delito, que constituyen figuras jurídicas de naturaleza punitiva en el ámbito tributario, en las cuales su tipificación legal se da en ejercicio del derecho a castigar del Estado bajo la necesidad de protección de los ingresos fiscales del Estado que le permitan realizar sus finalidades. Este análisis parte del estudio de las distintas teorías que se disputan la titularidad del ius puniendi, para arribar a la teoría que propone a la entidad estatal como la única titular del derecho a castigar a través del derecho administrativo sancionador y del derecho penal, donde se regulan las conductas ilícitas consideradas como infracción o como delito. Dicha circunstancia permitirá examinar el ejercicio del ius puniendi por parte de las autoridades en el ámbito fiscal a la luz de los derechos humanos que limitan el ejercicio de esta potestad punitiva.

Marwan Zeggari, Renaud Lambiotte, Aydin Abadi et al.

While online interactions and exchanges have grown exponentially over the past decade, most commercial infrastructures still operate through centralized protocols, and their success essentially depends on trust between different economic actors. Digital advances such as blockchain technology has led to a massive wave of \textit{Decentralized Ledger Technology} (\textit{DLT}) initiatives, protocols and solutions. This advance makes it possible to implement trustless systems in the real world, which, combined with appropriate economic and participatory incentives, would foster the proper functioning and drive the adoption of a decentralized platform among different actors. This paper describes an alternative to current commercial structures and networks by introducing \textit{Lyzis Labs}, which is is an incentive-driven and democratic protocol designed to support a decentralized online marketplace, based on blockchain technology. The proposal, \textit{Lyzis Marketplace}, allows to connect two or more people in a decentralized and secure way without having to rely on a \textit{Trusted Third Party} (\textit{TTP}) in order to perform physical asset exchanges while mainly providing transparent and fully protected data storage. This approach can potentially lead to the creation of a permissionless, efficient, secure and transparent business environment where each user can gain purchasing and decision-making power by supporting the collective welfare while following their personal interests during their various interactions on the network.

Long Chen, Mao Ye, Alistair Milne et al.

This report, commissioned by the WTW research network, investigates the use of AI in property risk assessment. It (i) reviews existing work on risk assessment in commercial and industrial properties and automated information extraction from building blueprints; and (ii) presents an exploratory 'proof-of concept-solution' exploring the feasibility of using machine learning for the automated extraction of information from building blueprints to support insurance risk assessment.

Eva Wisse, Pietro Tedeschi, Savio Sciancalepore et al.

The recent worldwide introduction of RemoteID (RID) regulations forces all Unmanned Aircrafts (UAs), a.k.a. drones, to broadcast in plaintext on the wireless channel their identity and real-time location, for accounting and monitoring purposes. Although improving drones' monitoring and situational awareness, the RID rule also generates significant privacy concerns for UAs' operators, threatened by the ease of tracking of UAs and related confidentiality and privacy concerns connected with the broadcasting of plaintext identity information. In this paper, we propose $A^2RID$, a protocol suite for anonymous direct authentication and remote identification of heterogeneous commercial UAs. $A^2RID$ integrates and adapts protocols for anonymous message signing to work in the UA domain, coping with the constraints of commercial drones and the tight real-time requirements imposed by the RID regulation. Overall, the protocols in the $A^2RID$ suite allow a UA manufacturer to pick the configuration that best suits the capabilities and constraints of the drone, i.e., either a processing-intensive but memory-lightweight solution (namely, $CS-A^2RID$) or a computationally-friendly but memory-hungry approach (namely, $DS-A^2RID$). Besides formally defining the protocols and formally proving their security in our setting, we also implement and test them on real heterogeneous hardware platforms, i.e., the Holybro X-500 and the ESPcopter, releasing open-source the produced code. For all the protocols, we demonstrated experimentally the capability of generating anonymous RemoteID messages well below the time bound of $1$ second required by RID, while at the same time having quite a limited impact on the energy budget of the drone.

Dima Kagan, Mor Levy, Michael Fire et al.

In the last decades, global awareness towards the importance of diverse representation has been increasing. Lack of diversity and discrimination toward minorities did not skip the film industry. Here, we examine ethnic bias in the film industry through commercial posters, the industry's primary advertisement medium for decades. Movie posters are designed to establish the viewer's initial impression. We developed a novel approach for evaluating ethnic bias in the film industry by analyzing nearly 125,000 posters using state-of-the-art deep learning models. Our analysis shows that while ethnic biases still exist, there is a trend of reduction of bias, as seen by several parameters. Particularly in English-speaking movies, the ethnic distribution of characters on posters from the last couple of years is reaching numbers that are approaching the actual ethnic composition of US population. An automatic approach to monitor ethnic diversity in the film industry, potentially integrated with financial value, may be of significant use for producers and policymakers.

Georgy Kagramanov, Vladimir Gurkin, Elena Farnosova

The porous layer of composite and asymmetric hollow fiber membranes acts as a support and is exposed to strong mechanical stresses. The effect of external pressure on the polymer structure and, as a consequence, the separation characteristics of the membrane remains unsolved. Based on the solution of the Lamé approach to the calculation of the stress state of a hollow cylinder, a method of calculation was proposed for hollow fiber membranes. Calculations were based on the approximation of the isotropic nature of the physical and mechanical characteristics of the selective layer and substrate. Permissible deformation of the membrane’s selective layer was determined from the linear sector of strain-on-stress dependence, where Hooke’s law was performed. For these calculations, commercial polyethersulfone membranes were chosen with an inner and/or outer selective layer and with the following values of Young’s modulus of 2650 and 72 MPa for the selective and porous layers, respectively. The results obtained indicate that the dependence of the maximum allowable operating pressure on the substrate thickness asymptotically trends to a certain maximum value for a given membrane. Presented data showed that membranes with outer selective layer can be operated at higher working pressure. Optimal parameters for hollow fiber gas separation membrane systems should be realized, solving the optimization problem and taking into account the influence of operating, physicochemical and physicomechanical parameters on each other.

Tecle Hagos Bahta

Ethiopia’s ratification of the New York Convention for the recognition and enforcement of foreign arbitral awards and arbitration agreements is a welcome development. The Convention has been greatly facilitating cross-border mobility of arbitral awards and arbitration agreements in international commercial transactions. The entry into force of the New York Convention (as of 13 March 2020) and the enactment of the Arbitration and Conciliation Proclamation No.1237/2021 have ushered a relatively new era of modern arbitral regime in Ethiopia. In this regard, the necessary legal and formal infrastructure should be laid down for the proper implementation of the New York Convention. This article examines the ramifications of the three reservations registered by Ethiopia under the Convention; namely, the reciprocity, commercial and the non-retroactive application of the Convention. Furthermore, the multiplicity of enforcement regimes in the Ethiopian arbitral system related to these reservations are expounded. The formality requirements enunciated under the New York Convention are elaborated and the need for setting out the legal and institutional framework for contextualization thereof are dealt with. The possibility for award-creditors to resort to the more favourable local law or treaty other than the New York Convention and the recent trend of recognizing and enforcing arbitral awards, which are set aside or annulled in the place of arbitration are highlighted.

Liang Yu, Yi Sun, Zhanbo Xu et al.

In commercial buildings, about 40%-50% of the total electricity consumption is attributed to Heating, Ventilation, and Air Conditioning (HVAC) systems, which places an economic burden on building operators. In this paper, we intend to minimize the energy cost of an HVAC system in a multi-zone commercial building under dynamic pricing with the consideration of random zone occupancy, thermal comfort, and indoor air quality comfort. Due to the existence of unknown thermal dynamics models, parameter uncertainties (e.g., outdoor temperature, electricity price, and number of occupants), spatially and temporally coupled constraints associated with indoor temperature and CO2 concentration, a large discrete solution space, and a non-convex and non-separable objective function, it is very challenging to achieve the above aim. To this end, the above energy cost minimization problem is reformulated as a Markov game. Then, an HVAC control algorithm is proposed to solve the Markov game based on multi-agent deep reinforcement learning with attention mechanism. The proposed algorithm does not require any prior knowledge of uncertain parameters and can operate without knowing building thermal dynamics models. Simulation results based on real-world traces show the effectiveness, robustness and scalability of the proposed algorithm.

Mery López Nieves

La pandemia del covid-19 ha afectado de manera negativa la economía a nivel global, lo que ha llevado a que los contribuyentes no puedan asumir el pago de sus obligaciones tributarias como lo harían en condiciones normales; en este contexto, el artículo analiza los cambios normativos que Perú ha realizado en su modelo de facilitación del pago de los impuestos, a partir de las nuevas expectativas de recaudo tributario, en el marco de los efectos del covid-19, de modo comparativo con Colombia.