Hasil untuk "Public law"

Muhammad Javed, Sedigh Khademi Habibabadi, Christopher Palmer et al.

Vaccine hesitancy threatens public health, leading to delayed or rejected vaccines. Social media is a vital source for understanding public concerns, and traditional methods like topic modelling often struggle to capture nuanced opinions. Though trained for query answering, large Language Models (LLMs) often miss current events and community concerns. Additionally, hallucinations in LLMs can compromise public health communication. To address these limitations, we developed a tool (VaxPulse Query Corner) using the Retrieval Augmented Generation technique. It addresses complex queries about public vaccine concerns on various online platforms, aiding public health administrators and stakeholders in understanding public concerns and implementing targeted interventions to boost vaccine confidence. Analysing 35,103 Shingrix social media posts, it achieved answer faithfulness (0.96) and relevance (0.94).

Mark Edison Jim, Jan Benjamin Yap, Gian Chill Laolao et al.

Public speaking anxiety affects many individuals, yet opportunities for real-world practice remain limited. This study explores how augmented reality (AR) can provide an accessible training environment for public speaking. Drawing from literature on public speaking, VR-based training, self-efficacy, and behavioral feedback mechanisms, we designed SpeakAR, an AR-based tool that simulates audience interaction through virtual models. SpeakAR was evaluated with five participants of varying anxiety levels, each completing six speaking tasks. Results indicate that AR exposure can enhance confidence, with participants finding the system useful for practice. Feedback highlighted the importance of dynamic facial expressions and idle animations in virtual models to improve realism and engagement. Our findings contribute to the design of AR-based training tools for public speaking, offering insights into how immersive environments can support skill development and anxiety reduction.

Christian Kroer, Dominik Peters

Lindahl equilibrium is a solution concept for allocating a fixed budget across several divisible public goods. It always lies in the weak core, meaning that the equilibrium allocation satisfies desirable stability and proportional fairness properties. We consider a model where agents have separable linear utility functions over the public goods, and the output assigns to each good an amount of spending, summing to at most the available budget. In the uncapped setting, each of the public goods can absorb any amount of funding. In this case, it is known that Lindahl equilibrium is equivalent to maximizing Nash social welfare, and this allocation can be computed by a public-goods variant of the proportional response dynamics. We introduce a new convex programming formulation for computing this solution and show that it is related to Nash welfare maximization through double duality and reformulation. We then show that the proportional response dynamics is equivalent to running mirror descent on our new formulation. Our new formulation has similarities to Shmyrev's convex program for Fisher market equilibrium. In the capped setting, each public good has an upper bound on the amount of funding it can receive, which is a type of constraint that appears in fractional committee selection and participatory budgeting. In this setting, existence of Lindahl equilibrium was only known via fixed-point arguments. The existence of an efficient algorithm computing one has been a long-standing open question. We prove that our new convex program continues to work when the cap constraints are added, and its optimal solutions are Lindahl equilibria. Thus, we establish that approximate Lindahl equilibrium can be efficiently computed. Our result also implies that approximately core-stable allocations can be efficiently computed for the class of separable piecewise-linear concave (SPLC) utilities.

Jianhua Yang, Mir Seyedebrahimi, Margaret Low et al.

Programming is a crucial skill in today's world and being taught worldwide at different levels. However, in the literature there is little research investigating a formal approach to embedding public engagement into programming module design. This paper explores the integration of public engagement into an introductory programming module, at the University of Warwick, UK, as part of the Digital and Technology Solutions (DTS) degree apprenticeship. The module design follows a 'V' model, which integrates community engagement with traditional programming education, providing a holistic learning experience. The aim is to enhance learning by combining programming education with community engagement. Apprentices participate in outreach activities, teaching programming and Arduino hardware to local secondary school students. This hands-on approach aligns with Kolb's experiential learning model, improving communication skills and solidifying programming concepts through teaching. The module also includes training in safeguarding, presentation skills, and storytelling to prepare apprentices for public engagement. Pedagogical techniques in the module include live coding, group exercises, and Arduino kit usage, as well as peer education, allowing apprentices to learn from and teach each other. Degree apprentices, who balance part-time studies with full-time employment, bring diverse knowledge and motivations. The benefit of public engagement is that it helps bridge their skills gap, fostering teamwork and creating a positive learning environment. Embedding public engagement in programming education also enhances both technical and soft skills, providing apprentices with a deeper understanding of community issues and real-world applications. Our design supports their academic and professional growth, ensuring the module's ongoing success and impact.

Kevin KB Ng, Liyana Fauzi, Leon Leow et al.

The study on GitHub Copilot by GovTech Singapore's Engineering Productivity Programme (EPP) reveals significant potential for AI Code Assistant tools to boost developer productivity and improve application quality in the public sector. Highlighting the substantial benefits for the public sector, the study observed an increased productivity (coding / tasks speed increased by 21-28%), which translates into accelerated development, and quicker go-to-market, with a notable consensus (95%) that the tool increases developer satisfaction. Particularly, junior developers experienced considerable efficiency gains and reduced coding times, illustrating Copilot's capability to enhance job satisfaction by easing routine tasks. This advancement allows for a sharper focus on complex projects, faster learning, and improved code quality. Recognising the strategic importance of these tools, the study recommends the development of an AI Framework to maximise such benefits while cautioning against potential over-reliance without solid foundational programming skills. It also advises public sector developers to classify their code as "Open" to use Gen-AI Coding Assistant tools on the Cloud like GitHub Copilot and to consider self-hosted tools like Codeium or Code Llama for confidential code to leverage technology efficiently within the public sector framework. With up to 8,000 developers, comprising both public officers and vendors developing applications for the public sector and its customers, there is significant potential to enhance productivity.

Sadar Jaf, Basel Barakat

Despite the extensive communication benefits offered by social media platforms, numerous challenges must be addressed to ensure user safety. One of the most significant risks faced by users on these platforms is targeted hate speech. Social media platforms are widely utilised for generating datasets employed in training and evaluating machine learning algorithms for hate speech detection. However, existing public datasets exhibit numerous limitations, hindering the effective training of these algorithms and leading to inaccurate hate speech classification. This study provides a comprehensive empirical evaluation of several public datasets commonly used in automated hate speech classification. Through rigorous analysis, we present compelling evidence highlighting the limitations of current hate speech datasets. Additionally, we conduct a range of statistical analyses to elucidate the strengths and weaknesses inherent in these datasets. This work aims to advance the development of more accurate and reliable machine learning models for hate speech detection by addressing the dataset limitations identified.

Xinyan Yu, Yiyuan Wang, Tram Thi Minh Tran et al.

The increasing transition of human-robot interaction (HRI) context from controlled settings to dynamic, real-world public environments calls for enhanced adaptability in robotic systems. This can go beyond algorithmic navigation or traditional HRI strategies in structured settings, requiring the ability to navigate complex public urban systems containing multifaceted dynamics and various socio-technical needs. Therefore, our proposed workshop seeks to extend the boundaries of adaptive HRI research beyond predictable, semi-structured contexts and highlight opportunities for adaptable robot interactions in urban public environments. This half-day workshop aims to explore design opportunities and challenges in creating contextually-adaptive HRI within these spaces and establish a network of interested parties within the OzCHI research community. By fostering ongoing discussions, sharing of insights, and collaborations, we aim to catalyse future research that empowers robots to navigate the inherent uncertainties and complexities of real-world public interactions.

Giseli Rodrigues Wagner, Márcia Zampieri Grohmann

Abstract Law guarantees the entry of people with disabilities into the labor market. However, just making the vacancy possible does not guarantee the full inclusion and permanence of these people in the work environment. It is necessary that organizations be prepared and have in their culture the practice of accessibility actions that contribute to this process. This study aimed to propose accessibility actions according to the panorama of inclusion and permanence of servers with disabilities in a Federal University in the interior of Rio Grande do Sul. With a qualitative approach, of an exploratory nature, it was developed with content analysis of information from questionnaires with open questions, applied to 26 servers with disabilities at the Federal University of Santa Maria (UFSM). The results found indicate that UFSM is on the way to building an accessible University, but it still has barriers, mainly attitudinal, that can be minimized with proposed accessibility actions. In addition to understanding the panorama of inclusion and permanence of servers with disabilities in a Public University, the present study presents a proposal for accessibility actions that can provide better working conditions for people with disabilities. Also filling a gap in studies aimed at servers with disabilities and about actions that help in their real inclusion and permanence in the work environment.

Michael B. Law, Isaac M. Lopez, Daniel Santiago

We establish a weighted positive mass theorem which unifies and generalizes results of Baldauf--Ozuch and Chu--Zhu. Our result is in fact equivalent to the usual positive mass theorem, and can be regarded as a positive mass theorem for smooth metric measure spaces. We also study Dirac operators on certain warped product manifolds associated to smooth metric measure spaces. Applications of this include, among others, an alternative proof for a special case of our positive mass theorem, eigenvalue bounds for the Dirac operator on closed spin manifolds, and a new way to understand the weighted Dirac operator using warped products.

Bailey Flanigan, Ariel D. Procaccia, Sven Wang

A key promise of democratic voting is that, by accounting for all constituents' preferences, it produces decisions that benefit the constituency overall. It is alarming, then, that all deterministic voting rules have unbounded distortion: all such rules - even under reasonable conditions - will sometimes select outcomes that yield essentially no value for constituents. In this paper, we show that this problem is mitigated by voters being public-spirited: that is, when deciding how to rank alternatives, voters weigh the common good in addition to their own interests. We first generalize the standard voting model to capture this public-spirited voting behavior. In this model, we show that public-spirited voting can substantially - and in some senses, monotonically - reduce the distortion of several voting rules. Notably, these results include the finding that if voters are at all public-spirited, some voting rules have constant distortion in the number of alternatives. Further, we demonstrate that these benefits are robust to adversarial conditions likely to exist in practice. Taken together, our results suggest an implementable approach to improving the welfare outcomes of elections: democratic deliberation, an already-mainstream practice that is believed to increase voters' public spirit.

Koudai Hatakeyama, Daisuke Kotani, Yasuo Okabe

Public key authentication (PKA) has been deployed in various services to provide stronger authentication to users. In PKA, a user manages private keys on her devices called authenticators, and services bind the corresponding public keys to her account. To protect private keys, a user uses authenticators which never export private keys outside. On the other hand, a user regularly uses multiple authenticators like PCs and smartphones. She replaces some of her authenticators according to their lifecycle, such as purchasing new devices and losing devices. It is a burden for a user to register, update and revoke public keys in many services every time she registers new accounts with services and replaces some of her authenticators. To ease the burden, we propose a mechanism where users and services manage public keys based on the owner of authenticators and users can access services with PKA using any of their authenticators. We introduce a key pair called an Ownership Verification Key (OVK), which consists of the private key (OVSK) and the corresponding public key (OVPK). All authenticators owned by a user derive the same OVSK from the pre-shared secret called the seed. Services verify the ownership of the authenticators using the corresponding OVPK to determine whether binding the requested public key to her account. To protect user privacy while maintaining convenience, authenticators generate a different OVK for each service from the seed independently. We demonstrate the feasibility through the Proof of Concept implementation, show that our proposed mechanism achieves some security goals, and discuss how the mechanism mitigates threats not completely handled.

Jinkui Zhao

Growth patterns of complex systems predict how they change in sizes, numbers, masses, etc. Understanding growth is important, especially for many biological, ecological, urban, and socioeconomic systems. One noteworthy growth behavior is the 3/4- or and 2/3-power scaling law. It's observed in worldwide aquatic and land biomass productions, eukaryote growth, mammalian brain sizes, and city public facility distributions. Here, I show that these complex systems belong to a new universality class whose system dimensionality determines its growth scaling. The model uses producer-consumer dynamics to derive the n/(n+1) power scaling law for an n-dimensional system. Its predictions are validated with real-world two- and three-dimensional data. Dimensionality analysis thus provides a new paradigm for understanding growth and growth-related problems in a wide range of complex systems.

Deepak Sharma, Naveen Krishan Goel

Background: Exposure to Second-hand tobacco smoke (SHS) harms health. It is a risk factor for various diseases like asthma, hypertension, diabetes, heart disease and lung cancer. This study aimed to determine the prevalence and predictors of second-hand tobacco smoke among adult never-smokers. Methods: A cross-sectional study was conducted among 220 participants aged 18 years and above. A pre-tested questionnaire was used to elicit information regarding exposure to second-hand smoke at the home, workplace and various public places. The data was analysed using the Epi Info software for windows. Results: The second-hand smoke exposure at home and workplace was 11.4% and 19.1%, respectively. The SHS exposure at bus stops, public transport, government buildings and health care facilities were 33.3%, 13.0%, 7.6% and 3%, respectively. The in-home study participants with a current tobacco smoker, family member and/or friend had comparatively higher exposure to second-hand tobacco smoke. In the workplace and or public places, male study participants and illiterate individuals had higher exposure to second-hand tobacco smoke. Conclusion: The observed level of SHS exposure among non-smokers is a public health concern. Family members should not allow anyone to smoke in their home environment. The public health law prohibiting tobacco smoking in workplaces and public places needs further strengthening.

Lac Nguyen, Jeevanandha Ramanathan, Michelle Mei Wang et al.

Quantum random number (QRNG) beacons distinguish themselves from classical counterparts by providing intrinsic unpredictability originating from the fundamental laws of quantum mechanics. Most demonstrations have focused on certifiable randomness generators to guarantee the public that their genuineness is independent from imperfect implementations. These efforts however do not benefit applications where multiple distrusted users need a common set of random numbers, as they must rely on the honesty of beacon owners. In this paper, we formally introduce a design and proof-of-principle experiment of the first consensus protocol producing QRNs in a decentralized environment (dQRNG). Such protocol allows N number of participants contribute in the generation process and publicly verify numbers they collect. Security of the protocol is guaranteed given(N-1) dishonest participants. Our method is thus suited for distribute systems that requires a bias-resistant, highly secure, and public-verifiable random beacon.

Luciana Oliveira, Arminda Sequeira, Adriana Oliveira et al.

The outburst and proliferation of the COVID-19 pandemic, together with the subsequent social distancing measures, have raised massive challenges in almost all domains of public and private life around the globe. The stay-at-home movement has pushed the news audiences into social networks, which, in turn, has become the most prolific field for receiving and sharing news updates, as well as for public expression of opinions, concerns and feelings about the pandemic. Public opinion is a critical aspect in analysing how the information and events impact peoples lives, and research has shown that social media data may be promising in understanding how people respond to health risks and social crisis, which are the feelings they tend to share and how they are adapting to unforeseen circumstances that threaten almost all societal spheres. This paper presents results from a social media analysis of 61532 news headlines posted by the major daily news outlet in Portugal, Sic Noticias, on Facebook, from January to December 2020, focusing on the issues attention cycle and audiences emotional response to the COVID news outburst. This work adds to the emergent body of studies examining public response to the coronavirus pandemic on social media data.

Przemysław Dąbrowski

Doctor of Law Degree in the Interwar Period in Poland – Legal Regulations and Postulates of the Faculties of Law Several periods can be distinguished in the creation of legal regulations regarding the doctoral degree, including the doctor of laws. The first one, until 1924, was of a transitional nature, the years 1924-1933 were used to develop general, procedural guidelines, and the period after 1933 was to adapt the existing regulations to the new Act on Academic Schools. It should be noted that all legal acts relating to the doctoral degree were consulted with law faculties, and their opinions had a direct impact on the introduced changes.

Mohammad Roesli

Corruption shows a serious challenge to development. In the world of politics, corruption complicates democracy and good governance by destroying the formal process. Corruption in elections and in the legislature reduces accountability and representation in policy making; corruption in the court system stops law order; and corruption in public government results in an imbalance in community service. In general, corruption erodes the institutional capacity of the government, due to the neglect of procedures, suctioning of resources, and officials appointed or elevated positions not because of achievement. At the same time, corruption complicates the legitimacy of government and democratic values such as trust and tolerance. It takes the existence of local wisdom and religious values to minimize corruption.

Erico Wulf Betancourt

La interacción entre el medio ambiente, el crecimiento y el desarrollo económico, ha sido un tema de interés creciente para la investigación académica. El presente artículo, propone un modelo teórico de decisión endógena de la eficiencia en la empresa, para comprender la interrelación entre energía, producción, y crecimiento. Se revisan la literatura y la evidencia empírica de las variables consideradas. Se asume que agentes económicos motivados por la maximización de sus utilidades y beneficios, toman decisiones de gestión desde una función CES, para lograr un mix eficiente de producción. El modelo propuesto y la hipótesis de maximización de la utilidad derivada del capital humano, se ajusta con la evidencia de las economías del sudeste asiático (1950-1990).Más investigación es necesaria, acerca de la función de gestión de producción CES, y la relación entre energía y crecimiento. Una limitación, es la carencia de un formato inclusivo de las variables macro y microeconómicas, que influyen el crecimiento económico.Finalmente, la omisión del rol de la gestión, tiene un impacto sesgado en las recomendaciones de política respecto de la interacción energía - crecimiento.Palabras claves: Racionalidad acotada, Globalización, Capital Humano, Organización de la empresa, gestión, crecimiento económico.

Alvaro Corral, Isabel Serra

An important body of quantitative linguistics is constituted by a series of statistical laws about language usage. Despite the importance of these linguistic laws, some of them are poorly formulated, and, more importantly, there is no unified framework that encompasses all them. This paper presents a new perspective to establish a connection between different statistical linguistic laws. Characterizing each word type by two random variables, length (in number of characters) and absolute frequency, we show that the corresponding bivariate joint probability distribution shows a rich and precise phenomenology, with the type-length and the type-frequency distributions as its two marginals, and the conditional distribution of frequency at fixed length providing a clear formulation for the brevity-frequency phenomenon. The type-length distribution turns out to be well fitted by a gamma distribution (much better than with the previously proposed lognormal), and the conditional frequency distributions at fixed length display power-law-decay behavior with a fixed exponent $α\simeq 1.4$ and a characteristic-frequency crossover that scales as an inverse power $δ\simeq 2.8$ of length, which implies the fulfilment of a scaling law analogous to those found in the thermodynamics of critical phenomena. As a by-product, we find a possible model-free explanation for the origin of Zipf's law, which should arise as a mixture of conditional frequency distributions governed by the crossover length-dependent frequency.

Jason D. Eastman, Joseph E. Rodriguez, Eric Agol et al.

We present the next generation public exoplanet fitting software, EXOFASTv2. It is capable of fitting an arbitrary number of planets, radial velocity data sets, astrometric data sets, and/or transits observed with any combination of wavelengths. We model the star simultaneously in the fit and provide several state-of-the-art ways to constrain its properties, including taking advantage of the now-ubiquitous all-sky catalog photometry and Gaia parallaxes. EXOFASTv2 can model the star by itself, too. Multi-planet systems are modeled self-consistently with the same underlying stellar mass that defines their semi-major axes through Kepler's law and the planetary period. Transit timing, duration, and depth variations can be modeled with a simple command line option. We explain our methodology and rationale as well as provide an improved version of the core transit model that is both 25\% faster and more accurate. We highlight several potential pitfalls in exoplanet modeling, including the handling of eccentricity in transit-only fits, that the standard exoplanet convention for $ω$ uses a left-handed coordinate system, contrary to most modern textbooks, how to avoid an important degeneracy when allowing negative companion masses, and a widely unappreciated, potential 10-minute ambiguity in the reported transit times. EXOFASTv2 is available at https://github.com/jdeast/EXOFASTv2 . The code is written in IDL, and includes an executable that can be run freely and legally without an IDL license or any knowledge of the language. Extensive documentation and tutorials are included in the distribution for a variety of example fits. Advanced amateurs and undergrads have successfully performed sophisticated global fits of complex planetary systems with EXOFASTv2. It is therefore a powerful tool for education and outreach as well as the broader professional community.