Investors wish to obtain the best trade-off between the return and risk. In portfolio optimization, the mean-absolute deviation model has been used to achieve the target rate of return and minimize the risk. However, the maximization of entropy is not considered in the mean-absolute deviation model according to past studies. In fact, higher entropy values give higher portfolio diversifications, which can reduce portfolio risk. Therefore, this paper aims to propose a multi-objective optimization model, namely a mean-absolute deviation-entropy model for portfolio optimization by incorporating the maximization of entropy. In addition, the proposed model incorporates the optimal value of each objective function using a goal-programming approach. The objective functions of the proposed model are to maximize the mean return, minimize the absolute deviation and maximize the entropy of the portfolio. The proposed model is illustrated using returns of stocks of the Dow Jones Industrial Average that are listed in the New York Stock Exchange. This study will be of significant impact to investors because the results show that the proposed model outperforms the mean-absolute deviation model and the naive diversification strategy by giving higher a performance ratio. Furthermore, the proposed model generates higher portfolio mean returns than the MAD model and the naive diversification strategy. Investors will be able to generate a well-diversified portfolio in order to minimize unsystematic risk with the proposed model.
Chitosan is a biocompatible polymer with vast applications in pharmacology, medicine, paper making, agriculture, and the food industry due to its low toxicity. Chitosan also plays an important role in the sustainable environment since chitosan is able to absorb greenhouse gases, harmful organic matter, and heavy ions. Therefore, this paper conducts a bibliometric analysis of chitosan for sustainable development using the Scopus database from 1976 to 2023. A performance analysis on the 8002 documents was performed with Harzing's Publish or Perish. Science mapping was conducted using VOSviewer. The annual publication on chitosan for sustainable development showed an upward trend in recent years as the annual publication peaked in 2022 with 1178 documents with most of the documents being articles and published in journals. Material science, chemistry, and engineering are tightly related subject areas. China had the highest publication of 1560 total documents while the United States had the most impactful publication with 55,019 total citations, 68.77 citations per document, 77.6 citations per cited document, h-index 110, and g-index of 211. India had the largest international collaboration with 572 total link strength. "International Journal of Biological Macromolecules", "Carbohydrate Polymers", and "Polymers" have been identified as the top three source titles that publish the most documents on chitosan for sustainable development. The emerging trends in chitosan on sustainable development focus on the application of chitosan as an antibacterial agent and biosorbent for contaminants, especially in water treatment.
Gallium nitride (GaN) has a wide energy band gap and a high power density, efficiency, switching frequency, and electron carrier mobility, having broad applications in digitization. Because GaN has high potentials, this study performed a bibliometric analysis on the publications of GaN indexed in the Web of Science database from 1970 to 2023. A performance analysis of the 15,634 publications was performed using Harzing's Publish or Perish tool, while science mappings were performed with VOSviewer software. The results show that there has been an uptrend in the on-going research on GaN, especially in the past decade. Most of the documents are within the fields of physics, engineering, and materials science. The United States has the highest number of publications and the most impactful research. The United States is also actively collaborating with other countries to gain deeper insights into GaN. The analysis shows that the concentration of GaN research is slowly moving towards the development of high-voltage operations.
Granger causality provides a framework that uses predictability to identify causation between time series variables. This is important to policymakers for effective policy management and recommendations. Granger causality is recognized as the primary advance on the causation problem. The objective of this paper is to conduct a bibliometric analysis of Granger causality publications indexed in the Web of Science database. Harzing's Publish or Perish and VOSviewer were used for performance analysis and science mapping. The first paper indexed was published in 1981 and there has been an upward trend in the annual publication of Granger causality studies which are shifting towards the areas of environmental science, energy, and economics. Most of the publications are articles and proceeding papers under the areas of business economics, environmental science ecology, and neurosciences/neurology. China has the highest number of publications while the United States has the highest number of citations. England has the highest citation impact. This paper also constructed country co-authorship, co-analysis of cited references, cited sources, and cited authors, keyword co-occurrence, and keyword overlay visualization maps.
Statistical information theory is a method for quantifying the amount of stochastic uncertainty in a system. This theory originated in communication theory. The application of information theoretic approaches has been extended to different fields. This paper aims to perform a bibliometric analysis of information theoretic publications listed on the Scopus database. The data of 3701 documents were extracted from the Scopus database. The software used for analysis includes Harzing's Publish or Perish and VOSviewer. Results including publication growth, subject areas, geographical contributions, country co-authorship, most cited publications, keyword co-occurrence analysis, and citation metrics are presented in this paper. Publication growth has been steady since 2003. The United States has the highest number of publications and received more than half of the total citations from all 3701 publications. Most of the publications are in computer science, engineering, and mathematics. The United States, the United Kingdom, and China have the highest collaboration across countries. The focus on information theoretic is slowly shifting from mathematical models to technology-driven applications such as machine learning and robotics. This study highlights the trends and developments of information theoretic publications, which helps researchers to understand the state of the art of information theoretic approaches for future contributions in this research domain.
Biophotonics procures wide practicability in life sciences and medicines. The contribution of biophotonics is well recognized in various Nobel Prizes. Therefore, this paper aims to conduct a bibliometric analysis of biophotonics publications. The scientific database used is the Web of Science database. Harzing's Publish or Perish and VOSviewer are the bibliometric tools used in this analysis. This study found an increasing trend in the number of publications in recent years as the number of publications peaked at 347 publications in 2020. Most of the documents are articles (3361 publications) and proceeding papers (1632 publications). The top three subject areas are Optics (3206 publications), Engineering (1706 publications) and Radiology, Nuclear Medicine, and Medical Imaging (1346 publications). The United States has the highest number of publications (2041 publications) and citation impact (38.07 citations per publication; h-index: 125). The top three publication titles are Proceedings of SPIE (920 publications), Journal of Biomedical Optics (599 publications), and Proceedings of the Society of Photo Optical Instrumentation Engineers SPIE (245 publications). The potential areas for future research include to overcome the optical penetration depth issue and to develop publicly available biosensors for the detection of common diseases.