Analyzing eID Public Acceptance and User Preferences for Current Authentication Options in Estonia

Рассматривается проблема выбора оптимальных параметров интерфейса в информационных системах с целью его персонализации под предпочтения пользователя и возможности его оборудования. В настоящее время для ее решения используется алгоритмическое обеспечение и статистическая обработка предпочтений пользователей, что не обеспечивает достаточной гибкости и точности. Поэтому в данной работе предлагается применение разработанного метода адаптации параметров интерфейса, основанного на анализе и обработке пользовательской информации с помощью нейронных сетей. Научная новизна метода заключается в автоматизации сбора, анализа данных и настройки интерфейса за счет использования и интеграции нейронных сетей в информационную систему. Рассмотрена практическая реализация предлагаемого метода на Python. Экспертная оценка адаптивности интерфейса тестовой информационной системы после внедрения разработанного метода показала его перспективность и эффективность. Разработанный метод показывает лучшую точность и низкую сложность программной реализации относительно классического алгоритмического подхода. Полученные результаты могут использоваться для автоматизации процесса выбора компонентов интерфейса различных информационных систем. Дальнейшие исследования заключаются в развитии и интеграции разработанного метода в рамках фреймворка адаптации информационных систем Here we consider the problem of choosing the optimal parameters of the interface in information systems with the aim of personalizing it for the preferences of the user and the capabilities of his equipment. Currently, algorithmic support and statistical processing of user preferences are used to solve it, which does not provide sufficient flexibility and accuracy. Therefore, in this work, we propose the application of the developed method for adapting interface parameters based on the analysis and processing of user information using neural networks. The scientific novelty of the method is to automate the collection, analysis of data and interface settings through the use and integration of neural networks in the information system. We consider the practical implementation of the proposed method in Python. An expert assessment of the adaptability of the interface of the test information system after the implementation of the developed method showed its availability and efficiency. The developed method shows the best accuracy and low complexity of software implementation relative to the classical algorithmic approach. The results obtained can be used to automate the selection of interface components for various information systems. Further research consists in the development and integration of the developed method within the framework of the information systems adaptation framework

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What Drives Public Acceptance of Reforms? Longitudinal Evidence from the Run-Up of the Increase of the Dutch Retirement Age

SSRN Electronic Journal ◽

10.2139/ssrn.2712255 ◽

2015 ◽

Author(s):

Jante Parlevliet

Keyword(s):

Public Acceptance ◽

Retirement Age ◽

Run Up

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Market Share Contracts in B2B Procurement Settings with Heterogeneous User Preferences

SSRN Electronic Journal ◽

10.2139/ssrn.3439084 ◽

2020 ◽

Author(s):

Ravi Mantena ◽

Rajib Lochan Saha

Keyword(s):

Market Share ◽

User Preferences

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Water Recycling: Review and Background

Water Science & Technology ◽

10.2166/wst.1982.0173 ◽

1982 ◽

Vol 14 (9-11) ◽

pp. 1385-1392

Author(s):

K D Linstedt

Keyword(s):

Water Quality ◽

Water Resource ◽

Water Reuse ◽

Public Acceptance ◽

Institutional Constraints ◽

Water Recycling ◽

Quality Cost ◽

The World ◽

Resource Situation

A review is provided of the world water resource situation. Water reuse is discussed as a means of augmenting conventional supplies, with types of potential reuse applications identified. Considerations of water quality, cost, public acceptance, and institutional constraints are discussed for their impact on decisions regarding implementation of water reuse.

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Heuristic Algorithms for Waste Load Allocation in a River Basin

Water Science & Technology ◽

10.2166/wst.1989.0307 ◽

1989 ◽

Vol 21 (8-9) ◽

pp. 1057-1064 ◽

Cited By ~ 3

Author(s):

Vijay Joshi ◽

Prasad Modak

Keyword(s):

Dynamic Programming ◽

Heuristic Algorithms ◽

Water Quality Management ◽

User Preferences ◽

Theory And Practice ◽

Waste Load Allocation ◽

Practical Applications ◽

Waste Load ◽

On Line ◽

The One

Waste load allocation for rivers has been a topic of growing interest. Dynamic programming based algorithms are particularly attractive in this context and are widely reported in the literature. Codes developed for dynamic programming are however complex, require substantial computer resources and importantly do not allow interactions of the user. Further, there is always resistance to utilizing mathematical programming based algorithms for practical applications. There has been therefore always a gap between theory and practice in systems analysis in water quality management. This paper presents various heuristic algorithms to bridge this gap with supporting comparisons with dynamic programming based algorithms. These heuristics make a good use of the insight gained in the system's behaviour through experience, a process akin to the one adopted by field personnel and therefore can readily be understood by a user familiar with the system. Also they allow user preferences in decision making via on-line interaction. Experience has shown that these heuristics are indeed well founded and compare very favourably with the sophisticated dynamic programming algorithms. Two examples have been included which demonstrate such a success of the heuristic algorithms.

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