Numerical Rules Research Articles

Digital Marketing in Hotels of Uttarakhand: A Review

The internet is the most significant element in the economy of the twenty-first century since it provides us with instant access to regional or worldwide audiences, generates millions of jobs, and 100,000 enterprises. Social media, which encompasses numerous rules and includes sites like Facebook, YouTube, Twitter, and LinkedIn, is managed by tiny groups with institutionally unified retail ideals. These regulations contain a promotion associate, a general connection, and their trading advancement to foster a client-focused culture. The hotel sector can benefit from the use of digital marketing. Media outlets including radio, television, and newspapers have developed over the past few decades into a connected marketing pathway that hotels can plan for. The allocation of actual hotel reservations, according to Amit Vyas (2018), is evidence that a digital marketing approach was successful. A framework with a strong foundation is provided by the digital marketing strategy model, which aids in projecting important growth activities and carrying out operations as required.

A DISCUSSÃO SOBRE A INCLUSÃO NO POLO PASSIVO DE SÓCIOS OU EMPRESAS COM ATIVIDADE DIVERSA DO MESMO GRUPO ECONÔMICO NA FASE EXECUTÓRIA

Given the cancellation of TST Precedent 205, which addressed the inclusion of companies within the same economic group at the enforcement stage of labor proceedings, there have been numerous rulings regarding whether or not to include companies that did not participate in the initial phase of recognition in the case. Over time, the judiciary has faced instances of execution fraud in proceedings, and to address these abusive practices, judicial mechanisms have been applied to recover executions. Eventually, the Supreme Federal Court recognized this as a matter of legislative repercussion in Extraordinary Appeal (RE) No. 1387795/MG, leading to a legal debate among the courts regarding the issue. This research is qualitative, using bibliographic and documentary methods. The research system allows for analysis from a general to a specific format, based on doctrines and decisions of Brazilian courts. The study analyzes the joint liability between companies within an economic group, including those that did not directly participate in the case from the initial stage. It highlights issues such as hidden partners and companies with different activities, examining whether the current legislation allows for the inclusion of service-recipient companies. Ultimately, it evaluates whether execution is feasible under this type of liability. The research concludes by examining these discussions and highlighting the study's importance in bringing benefits to labor law and labor process.

An evaluation of the performance of stopping rules in AI-aided screening for psychological meta-analytical research.

Several AI-aided screening tools have emerged to tackle the ever-expanding body of literature. These tools employ active learning, where algorithms sort abstracts based on human feedback. However, researchers using these tools face a crucial dilemma: When should they stop screening without knowing the proportion of relevant studies? Although numerous stopping rules have been proposed to guide users in this decision, they have yet to undergo comprehensive evaluation. In this study, we evaluated the performance of three stopping rules: the knee method, a data-driven heuristic, and a prevalence estimation technique. We measured performance via sensitivity, specificity, and screening cost and explored the influence of the prevalence of relevant studies and the choice of the learning algorithm. We curated a dataset of abstract collections from meta-analyses across five psychological research domains. Our findings revealed performance differences between stopping rules regarding all performance measures and variations in the performance of stopping rules across different prevalence ratios. Moreover, despite the relatively minor impact of the learning algorithm, we found that specific combinations of stopping rules and learning algorithms were most effective for certain prevalence ratios of relevant abstracts. Based on these results, we derived practical recommendations for users of AI-aided screening tools. Furthermore, we discuss possible implications and offer suggestions for future research.

A Comprehensive Survey on the Role of Law in Different Applications in Computer Science

One significant tool for addressing the concerns associated with the use of one of the applications in computer science is the law. Numerous laws and rules governing the use of computer science are designed to safeguard users, customers, and society at large. Law uses norms created by governmental and social institutions to control behavior. Programming is used to explore digital information in computer science. Computers got more potent and smaller as they evolved through generations, utilizing various technologies such as integrated circuits. Cyber law regulates online behavior and deals with matters pertaining to intellectual property, privacy, domain names, and other legal concerns. A few of the many concerns that the law must address in order to mitigate the electronic crimes are protecting privacy and security, upholding justice, limiting civil and criminal liability, ensuring safety, and controlling the application of AI in the workplace. Guidelines that people and organizations have to follow when utilizing computer science applications, making sure that these requirements are met in full. Additionally, as companies must commit to recording AI usage procedures and making clear the use of data and algorithms, the regulation fosters accountability and openness. By doing this, the possibility of prejudice and mistakes when utilizing AI is decreased. This survey provides a self-contained introduction to cybercrimes and types of cybercrimes. We also present ways to combat cybercrime and limit its spread.

Isospin sum rules for the nonleptonic B decays

Isospin symmetry, as the most precise flavor symmetry, can be used to extract information about hadronic dynamics. The effective Hamiltonian for bottom quark weak decay is zero under the isospin lowering operators I-n\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$I_-^n$$\\end{document}, which allows us to generate isospin sum rules through several master formulas. In this work, we derive the master formulas of isospin sum rules for the two- and three-body non-leptonic decays of B mesons. Numerous new isospin sum rules, especially those involving three or more decay channels, are proposed. The isospin sum rules can be used to test isospin symmetry and provide hints the isospin partners of exotic hadrons in B decays. It is found ten percent isospin breaking only in decay modes involving two vector mesons, indicating the complex dynamics of vector mesons. Besides, the isospin analysis suggests the charm tetraquark resonances might be observed in the B-→J/Ψπ-K¯0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ B^- \\rightarrow J/\\Psi \\pi ^-\\overline{K}^0$$\\end{document}, B¯0→J/ΨK¯0ϕ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\overline{B}^0 \\rightarrow J/\\Psi \\overline{K}^0\\phi $$\\end{document}, and B¯0→D0D¯0K¯0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\overline{B}^0\\rightarrow D^0\\overline{D}^0\\overline{K}^0$$\\end{document} modes.

Procedural constraints and regulatory ossification in the US states

AbstractScholars of the US regulatory process routinely assert that rulemaking is “ossified”—that it has become so encumbered with procedural constraints that it is difficult for agencies to issue socially desirable regulations. Yet, this claim has rarely been subject to empirical testing, and this is particularly true at the sub‐federal (i.e., US state) level. But the same factors that allegedly cause ossification in federal agencies also exist in the states. Using original survey data from 1460 agency leaders from across all 50 states, we present evidence suggesting that state agencies issue numerous rules and appear to do so quickly. We then focus on the procedural constraints that supposedly drive ossification and present some of the first evidence questioning the argument at the state level. We conclude that fears about the supposed tendency of procedural oversight mechanisms on the ability to regulate may be exaggerated.

Real-time integrated water availability – Salt intrusion modelling and management during droughts

Climate change and population increase are major challenges when guaranteeing a sustainable water supply in densely populated river basins worldwide, where different water users such as industry, drinking water production and agriculture typically come into conflict. During dry periods, real time monitoring and short term forecasting of the water availability are crucial to prepare and take appropriate action. Integrated water quantity and water quality models of complex surface water systems are indispensable to achieve this. However, existing model techniques often focus on a single aspect of the water system, are computationally too demanding and are hard to integrate with other sub models. This paper proposes a framework for developing efficient, integrated water quantity/quality models in support of real-time management and forecasting of complex surface water systems. Its three main components are: a low-flow prediction for the supplying river(s) during dry periods, a conceptual water quantity-quality model with semi-automated retrieval of necessary boundary conditions and input data, and classification models to predict the water quality state of the considered system during forecasts or scenario analyses. The novelty of the methodology lies in the use of parsimonious, computationally efficient sub-models that still allow to consider numerous operational rules, competing water users and water supply and quality constraints. The framework was tested in the context of water availability and salt intrusion management during droughts in the Campine Canals in the Scheldt-Meuse-Rhine delta, considering boundary conditions of shipping traffic, pumping at locks, hydropower stations, level regulation, and water abstractions for drinking water supply, industry, agriculture and nature reserves. Despite the complexity of the considered system, the model is able to describe the state of the water system in terms of water levels, discharges and salt intrusion impacts on water production with an acceptable accuracy. The research shows that the Campine Canal network is susceptible to water scarcity due to the increased risk of low flows in summer as a consequence of climate change. Local decision makers should adopt both effective adaptation strategies as well as real-time forecasts in acute drought situations to increase the region’s defence and resiliency against water shortages.

Old tools for the new economy? Counterfactual causation in foreclosure assessment and choice of remedies on data-driven markets

Abstract Under the Digital Markets Act, gatekeeper platforms abide by numerous ex-ante rules, including narrow data-sharing obligations that address data-driven market tipping. Gatekeepers also remain subject to ex-post competition interventions. While interventions under both ex-ante and ex-post (antitrust) mandates are not novel, they must be approached with extra care in data-driven digital markets, where uncertainty and error costs are high. Therefore, we argue that post-DMA competition enforcement against gatekeepers requires rigorous ex-post economic effects analysis at two levels: foreclosure assessment and devising appropriate remedies. Regarding foreclosure assessment, we propose a ‘multiple-counterfactual-causation-test’ for establishing anticompetitive effects, which should ensure a nuanced analysis of the competitive landscape on data-driven digital markets in the post-DMA world. Regarding remedies, a fine-grained, proportionality-driven assessment of the need for ex-post data-related obligations is vital.

Identifying diseases symptoms and general rules using supervised and unsupervised machine learning

The symptoms of diseases can vary among individuals and may remain undetected in the early stages. Detecting these symptoms is crucial in the initial stage to effectively manage and treat cases of varying severity. Machine learning has made major advances in recent years, proving its effectiveness in various healthcare applications. This study aims to identify patterns of symptoms and general rules regarding symptoms among patients using supervised and unsupervised machine learning. The integration of a rule-based machine learning technique and classification methods is utilized to extend a prediction model. This study analyzes patient data that was available online through the Kaggle repository. After preprocessing the data and exploring descriptive statistics, the Apriori algorithm was applied to identify frequent symptoms and patterns in the discovered rules. Additionally, the study applied several machine learning models for predicting diseases, including stepwise regression, support vector machine, bootstrap forest, boosted trees, and neural-boosted methods. Several predictive machine learning models were applied to the dataset to predict diseases. It was discovered that the stepwise method for fitting outperformed all competitors in this study, as determined through cross-validation conducted for each model based on established criteria. Moreover, numerous significant decision rules were extracted in the study, which can streamline clinical applications without the need for additional expertise. These rules enable the prediction of relationships between symptoms and diseases, as well as between different diseases. Therefore, the results obtained in this study have the potential to improve the performance of prediction models. We can discover diseases symptoms and general rules using supervised and unsupervised machine learning for the dataset. Overall, the proposed algorithm can support not only healthcare professionals but also patients who face cost and time constraints in diagnosing and treating these diseases.

Nature-Inspired Intelligent Computing: A Comprehensive Survey.

Nature, with its numerous surprising rules, serves as a rich source of creativity for the development of artificial intelligence, inspiring researchers to create several nature-inspired intelligent computing paradigms based on natural mechanisms. Over the past decades, these paradigms have revealed effective and flexible solutions to practical and complex problems. This paper summarizes the natural mechanisms of diverse advanced nature-inspired intelligent computing paradigms, which provide valuable lessons for building general-purpose machines capable of adapting to the environment autonomously. According to the natural mechanisms, we classify nature-inspired intelligent computing paradigms into 4 types: evolutionary-based, biological-based, social-cultural-based, and science-based. Moreover, this paper also illustrates the interrelationship between these paradigms and natural mechanisms, as well as their real-world applications, offering a comprehensive algorithmic foundation for mitigating unreasonable metaphors. Finally, based on the detailed analysis of natural mechanisms, the challenges of current nature-inspired paradigms and promising future research directions are presented.

Navigating fairness and boundaries: parental rule strategies and indicators of adolescents’ media overuse

ABSTRACT Balancing adolescents’ growing desire for independence with the establishment of effective media-related rules presents a complex challenge for many parents. Our study, utilising a diverse nationwide sample of 1,480 adolescents aged 13-17, investigates how adolescents’ perceptions of rule restrictiveness might explain the relationship between parental rule strategies and adolescents’ overuse of media. Indicators of overuse include dysregulated media engagement, interference of media use with other activities, and media-related physical symptoms. Structural equation modelling reveals that a higher number of rules and more frequent enforcement are associated with increased perceptions of restrictiveness among adolescents. However, adolescents tend to view rules as more reasonable when parents consistently adhere to these rules themselves, particularly in situations with numerous rules and strict enforcement. Notably, a curvilinear relationship emerges between adolescents’ perceptions of rule restrictiveness and media overuse indicators. Adolescents who perceive rules as reasonable, rather than overly restrictive or lenient, report lower levels of media overuse indicators. Our findings highlight the importance of parents establishing media use expectations that are balanced, reasonable, and that they themselves are committed to following.

Influence of In-Cylinder Turbulence Kinetic Energy on the Mixing Uniformity within Gaseous-Fuel Engines under Various Intake Pressure Conditions

To explore the potential for further enhancing the gas mixing uniformity of natural gas (NG) engines, this paper identifies turbulent kinetic energy (TKE), which has an essential impact on gas mixing, as the entry point of the research. After establishing a computational fluid dynamics (CFD) model for NG engines’ direct injection and mixing processes, the inlet pressure is selected as the experimental variable to investigate the influence of TKE on gas mixing uniformity. In particular, by proposing the theoretical concept of the core mixing stage, the numerical variation rule between the best mixture concentration region (BMCR) percentage and the mean turbulent kinetic energy (MTKE) of the core mixing stage is analyzed under certain injection timing conditions. The results indicate that, with identical intake pressures, an advanced gas injection timing elevates the total turbulence kinetic energy (TTKE) during the core mixing stage, thereby amplifying the uniformity of the gas mixture at the ignition. In specific scenarios, as the intake pressure increases, the decreasing trend in the BMCR proportion closely resembles the diminishing trend in the MTKE during the core mixing stage. Scrutinizing the variation trend in either parameter allows for an approximate prediction of the variation trend in the other parameter. When the intake pressure is gradually raised from the naturally aspirated state, the adequacy of the gas jet development is progressively reduced by the increasing back pressure in the cylinder.

Evidence of Giving Priority to the Hadith Associated with Mentioning the Reason over Other Hadiths: An Empirical Study

The study thoroughly examined the presumption of giving precedence to hadiths that mention their reasons over other hadiths. The primary objective of the study was to elucidate the underlying concepts, jurisprudential rulings, and practical applications pertinent to the topic. To fulfill the study's aims, the researchers utilized a combination of inductive and deductive methodologies to explore the assumptions underlying the prioritization process and to analyze the relevant texts. The study was geared toward achieving a comprehensive understanding of the results within the context of the examined topic. The study yielded several findings, one of which is that the presumption of prioritizing hadiths that cite a reason over those that do not is categorized within the domain of generality and specificity. Nevertheless, the principle is broad and is applicable to all individuals encompassed by the rationale stated within the rule. Numerous jurisprudential applications and rulings are derived from this principle, which are founded on hadiths that are tied to specific reasons.

Fiscal Rules in the European Union: Less Is More

AbstractIn this article, we examine the non‐linear relationship between the number of fiscal rules in place and compliance with the European Union's (EU) numerical fiscal targets included in the Stability and Growth Pact (SGP). Using a sample composed of 27 EU Member States for a period spanning 2000 to 2021, we document that countries' compliance with fiscal rules is positively associated with the number of numerical fiscal targets. However, this association only holds up to a specific threshold. Once this threshold is achieved, the relationship becomes negative, implying that the multiplication of numerical fiscal rules may undermine compliance, thereby reducing their effectiveness. In addition, we find that general elections and frequent changes in government reduce compliance, whereas economic adjustment programmes contribute positively to countries' compliance with fiscal targets. The findings bear critical policy implications against the backdrop of the current review of the European fiscal framework.

Tricks under Trade: How International Trade Both Facilitates and is Facilitated by Corporate Environmental Crime in the Waste and Hydrocarbon Sectors

Abstract Legal scholarship in the realm of international economic law has a blind spot: the practice of international trade. Cargo and container shipping is the blood and guts of international trade, and it is fuelled by bunker oil – a hydrocarbon mixture of the dirtiest petroleum-based products. Worryingly, there is empirical evidence of bunkers being intentionally contaminated with waste oils. This fraudulent contamination violates numerous international, national, and EU rules on waste management and poses immense risks to the health of planet and people alike. These same acts of fraud are also extremely profitable, and they facilitate the smooth functioning of our global economy. The fraud is itself not just incentivised in the tight-margins reality of international trade, but it is facilitated by the lack of proper legislation and the vulnerability of the existing means of enforcement in the areas where there is legislation to comply with. Economic operators often use falsified documents to market fuel oil that should be considered as waste. Systematic wrongdoing of this kind is detrimental to the environment and risks eroding the rule of law in both its formal and substantive conceptualisations.

Numerical integration rules based on B-spline bases

In this work, we present some new integration formulas for any order of accuracy as an application of the B-spline relations obtained in Amat et al. (2022). The resulting rules are defined as a perturbation of the trapezoidal integration method. We prove the order of approximation and extend the results to several dimensions. Finally, some numerical experiments are performed in order to check the theoretical results.

Mismatched Luneburg Lenses: Numerical Analysis and Design Rules

Mismatched Luneburg Lenses: Numerical Analysis and Design Rules

2023년 형법 중요 판례 평석

In 2023, there were fewer en banc decisions compared to 2022. While there were 7 en banc decisions related to criminal law in 2022, with 6 focusing on criminal law issues, the number decreased to 3 in 2023. However, the significance of this change should not be underestimated. Among these cases, a notable en banc decision redefined the meaning of assault and intimidation in the context of forcible molestation, representing an effort to align the legal decisions with contemporary societal trends.
 Additionally, there was a noticeable increase in en banc decisions related to stalking crimes and special criminal laws, shedding light on issues and challenges prevalent in these areas beyond basic criminal law. In the context of criminal law, there were numerous significant rulings pertaining to the co-perpetrators of negligent crimes and infringements on self-defense, specifically addressing the contemporaneity of self-defense (meaning not determined solely based on the formal completion of the criminal act but extending until the situation of harm to one's own or others' legal interests has ceased).
 In 2023, in terms of the legitimate exercise of the state's right to punish, there were many efforts to modify en banc decisions that extended beyond the literal interpretation of the law or to provide clarification on the meaning of legal provisions. While the ideal resolution for legal shortcomings would be through legislative measures, the impracticality of enacting legislation to address every situation necessitates the application of the law through judges' reasonable interpretation. Therefore, the positive aspect lies in not rendering outcome-oriented judgments based on the principle of proportionality. However, it is necessary to consider criticism that calls for clearer and more comprehensible improvements to the Supreme Court's en banc decisions, which currently restrict legal principles through their power of authoritative interpretation.
 Furthermore, it is noteworthy that many elements, which are not explicitly stipulated in the basic criminal law but are present in various special criminal laws, can be evaluated as serious crimes. To enhance the effectiveness of crime regulation and the general preventive impact, systematic legislative adjustments within the criminal law framework for these crime elements are essential.

A new discrete-time repetitive motion planning scheme based on pseudoinverse formulation for redundant robot manipulators with joint constrains

Recently, a repetitive motion planning (RMP) scheme with guaranteed precision has been developed for redundant robot manipulators. However, the RMP scheme does not consider joint constrains. As a result, such a scheme may not perform effectively when the joint configuration exceeds its physical limit. In this paper, we provide a further study by proposing a new discrete-time RMP (DTRMP) scheme based on the pseudoinverse formulation for redundant robot manipulators with joint constrains. Specifically, by using the direct derivation and by introducing the feedback, the handling of joint physical limit is formulated as an implicit dynamic equation. Then, the combined kinematic equation of the constrained redundant robot manipulators is obtained, and the resultant continuous-time RMP (CTRMP) scheme with the pseudoinverse-based formulation is established. By utilizing a numerical difference rule to discretize the CTRMP scheme, the new DTRMP scheme is thus developed for redundant robot manipulators with joint constrains. Theoretical analysis and computer simulations under a constrained five-link robot manipulator validate the effectiveness and superiority of the proposed DTRMP scheme. The experiment results of implementing the proposed scheme on the constrained practical Panda robot manipulator further indicate the scheme applicability and feasibility.

Examining the Impact of Fiscal Rules on Fiscal Stability in EU Member States

Following the rapid escalation of budget deficits and public debt across many EU nations post-2008, fiscal policy has encountered a formidable challenge in devising suitable measures to fortify fiscal discipline and enhance the quality of public finance. Institutional mechanisms, including numerical fiscal rules, play a pivotal role in upholding fiscal discipline and bolstering the fiscal credibility of states. These rules typically entail permanent constraints on fiscal policy, delineated by indicators that set thresholds for specific fiscal aggregates such as budget deficits, public debt, public expenditure, or public revenue. The theoretical aim of this article is to scrutinize the institutional dimensions of numerical fiscal rules, encompassing their type, legal foundation, transparency, complexity, flexibility, adequacy, and coherence. The empirical objective, conversely, is to conduct statistical analysis and investigate the correlation between the fiscal rules index and the levels of budget deficit and public debt across the 28 Member States of the European Union. Evaluating the efficacy of implemented fiscal rules, both at the European and national levels, constitutes a crucial aspect of this analysis.