Health Adjusted GDP (HAGDP) Measures of the Relationship Between Economic Growth, Health Outcomes and Social Welfare

Welfare economic analysis of health issues and policies can provide well balanced orderings of the state of the economy. This paper provides an innovative framework for welfare economic analysis of the relationships between economic growth, health outcomes and social welfare for both a developing and a developed country. Economic growth can increase health outcomes and social welfare but its influence is limited by biological laws. Further, achieving economic growth may have negative externalities which reduce health outcomes (particularly when biological health limits are reached). A new health adjusted GDP indicator to investigate the relationship between economic growth, health outcomes and social welfare in both a developing and developed country using social choice perspectives is developed in this paper. This new approach to social welfare analysis is also based on cost-benefit analysis and systems analysis and is called the social choice approach. The importance of good health is crucial when determining social welfare. The major limitation of many health-based indicators is that they can fail to adequately consider social welfare issues, such as equity and efficiency. Social choice theory allows optimal health outcomes to be fully considered in terms of equity and efficiency when determining the impact of economic growth on social welfare. Social choice theory incorporates the various “social concerns” that are not adequately captured using individual preference satisfaction techniques. This paper analyses the health outcomes resulting from economic growth (costs and benefits) using Thailand and Australia as case studies, from 1975 to 1999. Two health adjusted gross domestic product (HAGDP) indices are prepared in this paper by adjusting GDP to reflect the social welfare impacts of achieving economic growth on health outcomes.

Variational Inference for a Recommendation System in IoT Networks Based on Stein’s Identity

The recommendation services are critical for IoT since they provide interconnection between various devices and services. In order to make Internet searching convenient and useful, algorithms must be developed that overcome the shortcomings of existing online recommendation systems. Therefore, a novel Stein Variational Recommendation System algorithm (SVRS) is proposed, developed, implemented and tested in this paper in order to address the long-standing recommendation problem. With Stein’s identity, SVRS is able to calculate the feature vectors of users and ratings it has generated, as well as infer the preference for users who have not rated certain items. It has the advantages of low complexity, scalability, as well as providing insights into the formation of ratings. A set of experimental results revealed that SVRS performed better than other types of recommendation methods in root mean square error (RMSE) and mean absolute error (MAE)

Modelling the efficiency of knowledge economies in the Asia Pacific: a DEA approach

This paper measures the performances of 12 selected Asia Pacific countries in developing knowledge-based economies (KE). The performances of the selected countries are evaluated using Data Envelopment Analysis (DEA). The results indicate that four of the emerging countries (India, Indonesia, Thailand and mainland China) are relatively inefficient in K-E development compared to the other eight which are equally efficient The main reason for their backwardness is due to the outflow of their human capital resource to the developed countries. This seriously undermines the level of their K-E development compared to their counterparts. The results also indicate that knowledge dissemination is generally not a serious problem, except for India. However, in terms of knowledge output, knowledge dissemination becomes the weakest point for all low-scoring countries except China. Both India and China however, encounter serious obstacles in knowledge innovation and external connection

Bifurcation analysis of phytoplankton-fish model through parametric control by fish mortality rate and food transfer efficiency

An Algae-zooplankton fish model is studied in this article. First the proposed model is evaluated for positive invariance and boundedness. Then,the Routh-Hurwitz parameters and the Lyapunov function are used to determine the presence of a positive interior steady state and the criteria for plankton model stability (both local and global). Taylor’s sequence is also used to discuss Hopf bifurcation and the stability of bifurcated periodic solutions. The model’s bifurcation analysis reveals that Hopf-bifurcation can occur when mortality rate and food transfer efficiency are used as bifurcation parameters. Finally, we use numerical simulation to validate the analytical results

Variational channel estimation with tempering: An artificial intelligence algorithm for wireless intelligent networks

This article belongs to the Special Issue Trends on Edge Computing and Artificial Intelligence for Next Generation Sensor Network

A Cyber Physical System Crowdsourcing Inference Method Based on Tempering: An Advancement in Artificial Intelligence Algorithms

Activity selection is critical for the smart environment and Cyber-Physical Systems (CPSs) that can provide timely and intelligent services, especially as the number of connected devices is increasing at an unprecedented speed. As it is important to collect labels by various agents in the CPSs, crowdsourcing inference algorithms are designed to help acquire accurate labels that involve high-level knowledge. However, there are some limitations in the algorithm in the existing literature such as incurring extra budget for the existing algorithms, inability to scale appropriately, requiring the knowledge of prior distribution, difficulties to implement these algorithms, or generating local optima. In this paper, we provide a crowdsourcing inference method with variational tempering that obtains ground truth as well as considers both the reliability of workers and the difficulty level of the tasks and ensure a local optimum. The numerical experiments of the real-world data indicate that our novel variational tempering inference algorithm performs better than the existing advancing algorithms. Therefore, this paper provides a new efficient algorithm in CPSs and machine learning, and thus, it makes a new contribution to the literature

An innovative blockchain-based secured logistics management architecture:utilizing an RSA asymmetric encryption method

Purpose: The recent development in logistics due to the dawn of Logistics 4.0 has made global logistics providers more dependent on intelligent technologies. In this era, these technologies assist in data collection and transmission of logistical data and pose many security and privacy threats in logistics management systems. The customer’s private information, which is shared among the logistics stakeholders for optimal operation, faces unauthorized access due to a lack of privacy. This, amongst others, is a critical problem that needs to be addressed with blockchain. Blockchain is a disruptive technology that is transforming different sectors, and it has the potential to provide a solution to the issues mentioned above, with its unique features such as immutability, transparency, and anonymity. Method: This study designed a blockchain-based logistics management architecture on a decentralized peer-2-peer network using Ethereum smart contracts. The proposed system deployed the Rivest–Shamir–Adleman (RSA) asymmetric encryption method to protect the logistics system from cyber-attacks and secure customers’ private information from unauthorized access. Findings: Furthermore, the security and privacy of the proposed system are evaluated based on the theorem. The proof shows that the system can provide security to the logistics system and privacy to customers’ private data. The performance evaluation is based on throughput and latency. It shows that the proposed system is better than the baseline system, and the comparatives analysis shows that the proposed system is more secure and efficient than the existing systems. Implication and Limitation: The proposed system offers a better solution to the security/privacy of the logistics management system and provides recommendations to key stakeholders involved in the logistics industry while adopting blockchain technology. Apart from the study’s methodological limitation, it is also limited by a lack of reference materials