Portfolio System Research Articles

Journeying with the Dying—Lessons from Palliative Care Physicians

AbstractWitnessing suffering and death in palliative care can cause moral distress, emotional exhaustion and maladaptive coping strategies. How sense and meaning is made from these experiences influences how physicians think, feel and act as professionals (professional identity formation or PIF). It also determines how they cope with their roles, care for patients and interact with other professionals. Timely, personalised and appropriate support is key as shaping how these physicians develop and contend with sometimes competing beliefs and roles. The Ring Theory of Personhood (RToP) and the Krishna-Pisupati Model (KPM) offer a means of mapping PIF and thus moulding, coping and meaning making. This study uses the RToP and KPM to explore how caring for end-of-life patients impacts the personhood of palliative care physicians. Semi-structured interviews with a purposive sample of 13 palliative care physicians—eleven females and two males aged between 35 and 50 years—at a cancer specialist centre were conducted. Transcripts of the audio-recorded interviews underwent content and thematic analysis where complementary themes and categories identified were combined to form domains that highlighted the physicians’ key experience of providing end-of-life care. The domains identified were (1) identity formation, (2) conflicts, (3) KPM elements and (4) support systems. Together, results revealed that palliative care physicians are driven by Innate, Individual, Relational and Societal belief systems that create an intertwined professional and personal identity, enabling them to find meaning in their experiences and adapt to present contexts within cultural norms and professional expectations. However, their failure to recognise their need for support when hampered by evolving personal, existential and clinical factors underlines the exigency for ongoing surveillance and a potential role for a RToP-based tool and portfolio system that can detect and direct timely, appropriate support to in-need physicians.

Application of Intelligent Portfolio Management System in Financial Field: Comprehensive Analysis Based on Accounting and Financial Knowledge

In the current digital financial environment, portfolio management is highly valued, but traditional approaches face challenges. This study aims to explore the application of intelligent portfolio management systems in the financial field and design the system through accounting and financial knowledge to improve the efficiency of decision-making. Comprehensive research methods were adopted to collect financial and market data, and tools such as machine learning and data mining were used for in-depth analysis. Finally, an intelligent portfolio management system was designed and constructed, and its application effect was verified through empirical research. The research objects are financial market participants, and the data comes from the real market. This study chooses JPMorgan Chase and BlackRock as the research objects. These two well-known financial institutions have rich experience and resources in portfolio management, which will provide in-depth case analysis and data support for this study. The results show that the intelligent system can improve the decision-making efficiency, and put forward the technical challenges and countermeasures to promote the further development of the system.

1161 Fostering International Surgical Trainee Collaboration: The UK-Iceland Trainee Collaborative

Abstract The Foundation In 2019, the UK Iceland Trainee Collaborative emerged in response to Iceland’s adoption of the Intercollegiate Surgical Curriculum Programme (ISCP), aligning training portfolios with the UK’s practices. A collaboration between core surgical trainees, this new initiative aimed to champion the transition of Icelandic trainees to a new portfolio system, as well as foster a new relationship to encourage combined research and projects between the two nations. The Progression Beyond portfolio alignment, the collaboration expanded into a multifaceted educational platform. Monthly seminars and an annual conference, initially delivered online, provided a forum for knowledge exchange, featuring research showcases, consultant talks, and insights into portfolio optimization and program developments. The Impact The collaborative facilitated seamless integration of ISCP into Icelandic trainees’ competency progression, mirroring UK practices. The annual conference, delivered in person in its 3rd edition in Reykjavik, Iceland, in October 2023, received overwhelmingly positive feedback, with high delegate satisfaction rates, highlighting the leadership skills honed by core surgical trainees leading this initiative. The Future The collaborative now aims to intensify research partnerships between UK and Icelandic trainees, deepening knowledge exchange and advancing collective understanding. The trajectory for 2024 involves strengthening bonds and knowledge sharing among trainees from both nations through collaborative research initiatives. We hope the annual conference will continue to grow and will alternate between the two nations, strengthening the relationship.

Using an electronic portfolio system to create simulated electronic medical records for pharmacy student skills application

Using an electronic portfolio system to create simulated electronic medical records for pharmacy student skills application

Deep Reinforcement Learning Model for Stock Portfolio Management Based on Data Fusion

Deep reinforcement learning (DRL) can be used to extract deep features that can be incorporated into reinforcement learning systems to enable improved decision-making; DRL can therefore also be used for managing stock portfolios. Traditional methods cannot fully exploit the advantages of DRL because they are generally based on real-time stock quotes, which do not have sufficient features for making comprehensive decisions. In this study, in addition to stock quotes, we introduced stock financial indices as additional stock features. Moreover, we used Markowitz mean-variance theory for determining stock correlation. A three-agent deep reinforcement learning model called Collaborative Multi-agent reinforcement learning-based stock Portfolio management System (CMPS) was designed and trained based on fused data. In CMPS, each agent was implemented with a deep Q-network to obtain the features of time-series stock data, and a self-attention network was used to combine the output of each agent. We added a risk-free asset strategy to CMPS to prevent risks and referred to this model as CMPS-Risk Free (CMPS-RF). We conducted experiments under different market conditions using the stock data of China Shanghai Stock Exchange 50 and compared our model with the state-of-the-art models. The results showed that CMPS could obtain better profits than the compared benchmark models, and CMPS-RF was able to accurately recognize the market risk and achieved the best Sharpe and Calmar ratios. The study findings are expected to aid in the development of an efficient investment-trading strategy.

E-Portfolio and E-Catalog Integration System as Learning Media and Promotion of Broadcasting Study Program

This article discusses the design of a web-based portfolio and catalog integration system as a medium for learning and promoting the work of Polymedia Broadcasting Study Program students. The systems entitled ’Nakula’ and ’Sadewa’ are designed in an integrated manner to meet the needs of the distribution and promotion process of student work. There are three main needs in managing audio-visual works in the broadcasting study program: (1) The need for a work archive system. (2) Open access to works for students as a learning medium. (3) Showcase student work so that it can be accessed on a limited basis by stakeholders or sponsors. These findings can complement the findings of previous studies which have been able to use the E-portfolio system as a promotional medium and the E-Catalog as a student learning medium. These two systems are then combined into an integrated system that can answer the three main needs for the distribution and archiving of works in the broadcasting study program. The method used in this research is the development research method (DRM). This method tries to map the problem at a locus and find a solution based on the problem found. Apart from that DRM also prioritizes the involvement of each actor in these activities so that it can maximize the role of each actor. The findings in this article are a platform called Nakula-Sadewa, which has features including a showcase of student assignments that can be accessed in full version for polymedia students so that it can be maximized as a learning medium, limited access by sponsors or external parties, work archive facilities, and writing practice for students.
 Keywords: Nakula-Sadewa, promotion, learing, media, platform

Final Project Portfolio Information System [Sistem Informasi Portofolio Tugas Akhir

The final project portfolio information system, developed in the form of a website built using the codeignter4 framework. This research aims to introduce the final project work of students in the form of a simple display with clear and structured content or information accompanied by a presentation video about the student's final project. This research has a research flow as a basis for managing and writing in this study. The result of this research is an information system that is web-based and can be accessed by all circles both from within the university or from outside the university, with features that can be used by users. with the increasing recognition of the work of students can be a value for students or for universities, making student final assignments as reference information is also a value in itself.

Dynamic integrated simulative layout planning and production control for matrix production in a semiconductor environment

Increasing complexity, emerging manufacturing objectives and rising costs of manufacturing equipment result in the needs for faster product development and for a more effectively use manufacturing equipment through flexible and reconfigurable operations. Semiconductor manufacturing constitutes a prime example and is prone to frequent breakdowns and changes in product portfolio and manufacturing system. Matrix production offers adaptable routing and modular configurations, thereby enhancing flexibility and adaptability in streamlining material and process flows. While both planning the layout and the production control through scheduling and dispatching of such systems has been extensively studied, there remains a need for more thorough exploration of integrated optimization strategies encompassing both manufacturing layout planning and production control. The proposed approach optimizes multiple criteria through layout planning and production control of a matrix production by formulating a multi-objective optimization approach and using the NSGA-II for optimization to identify the balanced solutions. To confirm the efficacy of the proposed method, we applied it to both a generalized matrix production simulation and a real-world semiconductor use case. Our results, visualized in Pareto fronts, illuminate the inherent trade-offs within manufacturing objectives.

Analysis of the application of game theory methods in financial markets and opportunities for creating automatic exchange trading systems

This discussion delves into the application of game theory principles, particularly Nash equilibrium, in the design of automated systems within financial markets. It explores various instances, including oligopolistic competition using the Cournot model, the impact of cooperation and competition among companies, and the dynamics of financial markets influenced by investor behaviors. Additionally, the narrative unfolds the integration of game theory in analyzing investment decisions, risk management, and the development of automated trading systems, such as High-Frequency Trading (HFT) algorithms. The concept of Nash equilibrium is further extended to portfolio management systems, illustrating how automated systems optimize asset allocation based on strategic interactions. The discussion highlights the adaptability of these systems to changing market conditions and the continuous assessment of risks and potential returns. The development of automated trading systems, based on the principles of game theory, facilitates the construction of systems that adapt to changes in the market environment, quickly react to changes and make accurate decisions based on a thorough analysis of data and actions of market participants.

Developing Electronic Portfolios to Align with Diverse National Standards to Showcase Students’ and Teachers’ Performance: A Design Approach

Traditional methods of documenting and assessing educational performance and achievements have often been limited in scope and accessibility. Addressing these limitations is to leverage the potential of technology to create a comprehensive and user-friendly electronic portfolio (e-portfolio) system. This study aimed to investigate the required national standard and functionalities of e-portfolios for showcasing students’ and teachers’ performance. This study adopted qualitative research methods to investigate the context under study. Interviews, documents, and reports with and from students, lecturers, administrators, and educational experts provided insights into the specific requirements and expectations for an effective electronic portfolio system. One hundred twenty-five participants were randomly sampled for the study in the Abuja metropolis of Nigeria. Data were collected using a semi-structured interview and case study approach. A deductive approach was employed for the coding and analysis of the transcribed data. The findings identified several key features and functionalities required in an electronic portfolio system: Customizability and Flexibility, Alignment with Standards, Multimedia Capabilities, Reflection, and Goal-Setting Tools. Both students and teachers generally perceived the use of electronic portfolios positively. The respondents highlighted technological barriers, such as lack of necessary skills, limited access to devices or reliable internet connectivity; time constraints; and resistance to change as challenges in using e-portfolios to showcase their performance. Based on a systematic analysis of interview data from the respondents, the qualitative study offers a framework for exploring, understanding, and discussing the standard for and the impact of developing electronic portfolios for student and teacher performance.

The design and implementation of a deep reinforcement learning and quantum finance theory-inspired portfolio investment management system

Deep Learning (DL) and Reinforcement Learning (RL) are common machine learning techniques used in automatic trading, notwithstanding, RL is deficient in portfolio investment in terms of funds distribution, potential loss control, profit maximization, and examine undetected environment. This paper proposed an intelligent Quantum Finance-based portfolio investment system (QFPIS), which is a combination of Deep Reinforcement Learning (DRL) with Quantum Finance Theory (QFT) to improve these conditions. There are two major agents embodied in the system: 1) a trading agent based on Deep Deterministic Policy Gradient algorithm to determine investment weighting for different financial products by generating continuous actions; 2) an intelligent agent based on Policy Gradient (PG) algorithm to enact risk control and determine whether to hold current orders by producing discrete actions depend on daily Quantum Price Levels (QPLs). The advantages of incorporating a two-agents system design are to devise stable and realistic fund allocation for different products in portfolio. Experiment results had shown robustness, flexibility, and profitability on a series of forex products and the U.S. stocks in the back-testing phase as compared to other RL trading systems.

Risk Analysis of the Chinese Financial Market with the Application of a Novel Hybrid Volatility Prediction Model

This paper endeavors to enhance the prediction of volatility in financial markets by developing a novel hybrid model that integrates generalized autoregressive conditional heteroskedasticity (GARCH) models and long short-term memory (LSTM) neural networks. Using high-frequency data, we first estimate realized volatility as a robust measure of volatility. We then feed the outputs of multiple GARCH models into an LSTM network, creating a hybrid model that leverages the strengths of both approaches. The predicted volatility from the hybrid model is used to generate trading strategy signals, which are subsequently used to build an investment strategy. Empirical analysis using the China Securities Index 300 (CSI300) dataset demonstrates that the hybrid model significantly improves value-at-risk (VaR) prediction performance compared to traditional GARCH models. This study’s findings have broad implications for risk management in financial markets, suggesting that hybrid models incorporating mathematical models and economic mechanisms can enhance derivative pricing, portfolio risk management, hedging transactions, and systemic risk early-warning systems.

Computing cardinality constrained portfolio selection efficient frontiers via closest correlation matrices

In this paper, we demonstrate a completely new approach for computing cardinality constrained mean-variance efficient frontiers. By cardinality constrained, it is meant that if there is to be investment in a security, it is to be of at least some minimum amount (a buyin threshold), and that there is also a specification on the number of securities to be held in a portfolio (called a cardinality constraint). Whereas the usual strategy, as such problems are NP-hard, is to take the original exact problem and apply heuristics to solve, in this paper the strategy is to perturb the original problem and then apply exact procedures to solve. The advantages of the approach are that the perturbations are tiny, they are only applied to the problem’s correlation matrix, and they allow for the accurate computation of cardinality constrained efficient frontiers in problems with up to at least 1000 securities in remarkably little time. Moreover, the simplicity of the approach is such that it can be inserted into existing portfolio management systems without requiring any re-training beyond what a typical portfolio analyst would already know.11The authors have benefited from associations with Markus Hirschberger and Sebastian Utz in this research.

Investment Portfolio Management System: A Survey

Abstract: An investment portfolio management system is a highly sophisticated software application meticulously crafted to assist investors in the management of their investment portfolios. This innovative system provides investors with a centralized platform that empowers them to track their investments meticulously, closely monitor their performance, and judiciously make informed investment decisions. The system encompasses several advanced features such as portfolio analysis, risk management tools, asset allocation strategies, and performance reporting, that provide investors with a comprehensive overview of their portfolio's performance. Additionally, this cutting-edge platform offers investors the opportunity to diversify their portfolio by investing across multiple asset classes such as stocks, bonds, and mutual funds. This paper delves into the various techniques and methods employed to identify the optimal strategy to maximize gains from the investment. The fusion of algorithms and investments has revolutionized the investment landscape, enabling investors to obtain insightful data and make data-driven decisions. Several research studies have been conducted in the investment field, bolstered by machine learning models and algorithms, resulting in exceptional gains for investors.

Evaluation of a modular all-in-one high-resolution PET detector and readout electronics setup

Objective. The all-in-one solution and modularity of the C13500 series TOF-PET detector modules (Hamamatsu Photonics K.K., Hamamatsu, Japan) make them a highly attractive candidate for the development of positron emission tomography (PET) systems. However, the commercially available portfolio targets clinical whole-body PET systems with a scintillation crystal cross area of 3.1 × 3.1 mm2. To extend the modules for high resolution (preclinical or organ specific) systems, the support for smaller scintillation crystals is required. Approach. In this work, a PET detector was developed based on the TOF-PET modules using a light sharing approach, 16 × 16 lutetium oxyorthosilicate (LSO) scintillation crystals with a size of 1.51 × 1.51 × 10.00 mm3 readout with 8 × 8 photosensor channels of size 3.0 × 3.0 mm2. In addition to hardware and software development, the optimized parameter settings for the adapted configuration were evaluated. Main Results. A factor of two in amplification of the analog signal compared to the minimum gain setting was necessary for an accurate crystal identification (peak-to-valley ratio 14.9 ± 5.9). A further increase to a factor of three was not determined as optimum as the time over threshold duration, thus pile-up probability, increased from 1032.1 ± 109.5 to 1789.5 ± 218.5 ns (photopeak position). With this amplification a full width at half maximum (FWHM) energy resolution of 14.1 ± 2.0% and a high linearity of the energy detection was obtained. A FWHM coincidence resolving time (CRT) of 313 ps was achieved by using a low timing threshold, increasing the bandwidth of the front-end circuit and using a narrow ± 1σ energy window. To approximately double the sensitivity and reduce the power consumption, the timing parameters were adjusted resulting in a FWHM CRT of 354 ps (±2σ). Significance. Based on the results obtained with the proof-of-concept detector setup, we confirm the modularity and flexibility of the all-in-one TOF-PET detector modules for the future development of application-specific high-resolution PET systems.

Utilizing Natural Language Processing of Narrative Feedback to Develop a Predictive Model of Pre-Clerkship Performance: Lessons Learned.

Natural language processing is a promising technique that can be used to create efficiencies in the review of narrative feedback to learners. The Feinberg School of Medicine has implemented formal review of pre-clerkship narrative feedback since 2014 through its portfolio assessment system but this process requires considerable time and effort. This article describes how natural language processing was used to build a predictive model of pre-clerkship student performance that can be utilized to assist competency committee reviews. The authors took an iterative and inductive approach to the analysis, which allowed them to identify characteristics of narrative feedback that are both predictive of performance and useful to faculty reviewers. Words and phrases were manually grouped into topics that represented concepts illustrating student performance. Topics were reviewed by experienced reviewers, tested for consistency across time, and checked to ensure they did not demonstrate bias. Sixteen topic groups of words and phrases were found to be predictive of performance. The best-fitting model used a combination of topic groups, word counts, and categorical ratings. The model had an AUC value of 0.92 on the training data and 0.88 on the test data. A thoughtful, careful approach to using natural language processing was essential. Given the idiosyncrasies of narrative feedback in medical education, standard natural language processing packages were not adequate for predicting student outcomes. Rather, employing qualitative techniques including repeated member checking and iterative revision resulted in a useful and salient predictive model.

First steps of learning analytics in a blended learning general practice curriculum at Saarland University - a quantitative approach.

Medical education has been revolutionized by the growing importance of digital learning. Little is known about students' online study behaviour and its relationship with exam performance. This quantitative study analyses and describes students' digital learning behaviours in a blended learning curriculum for General practice at Saarland University, Germany. It also examines the relationship between digital learning behaviour and exam performance. Cohort and individualized AMBOSS® user data from 195 students at Saarland University was analysed quantitatively. Performance in course-specific multiple-choice question sessions and user data of the integrated online learning activities were correlated with each other and with General practice exam grades. Anonymized data from 10,534 students from 35 other German universities served as the reference cohort. Differences in digital learning behaviour between the groups were calculated using Mann-Whitney-U-Test for non-normally distributed data. Students in the blended learning course used integrated content more frequently than the reference cohort (U=48777, p<0.001). The number of digital learning cards read correlated moderately with digital formative assessment performance (ρ=0.331, p=0.005 and ρ=0.217, p=0.034). Formative assessment scores and exam results correlated strongly in the summer semester cohort (ρ=0.505, p<0.001), and moderately in the winter semester cohort (ρ=0.381, p<0.001). There is a difference in the usage of online learning activities when they are purposefully integrated into a curriculum. Digital learning activities including formative assessment may serve as valuable, constructively aligned exam preparation. This is relevant for medical educators when planning future blended learning curricula and portfolio systems, as it may save financial and human resources.

Teacher Perceptions of the Tennessee Student Growth Measures in Physical Education

Few states have implemented an evaluation system to measure teacher efficiency through the use of student growth measures within physical education. Evaluation procedures can be extensive and have the potential for reduced active student learning time in addition to reduced teacher discernment. Therefore, the purpose of this research was to analyze teacher perceptions of a current state evaluation system that measures teacher efficiency within physical education. The overarching goal of this research was to help improve overall physical education instruction through high-quality evaluation systems. This study employed a mixed-methods design due to the collection of survey data, which included quantitative results and responses to open-ended questions during the focus group (qualitative). Forty-five (26 male, 19 female) teacher participants completed the online survey questionnaire (Phase 1), and 17 (6 male, 11 female) teachers volunteered to participate in follow-up focus group interviews (Phase 2). An electronic survey designed to obtain feedback regarding the student growth measures system was sent to all participants. Once surveys were collected, two focus group sessions occurred during an in-service for all physical education teachers. Survey data and interviews were analyzed. Results show that teachers believe the intent of the Tennessee Student Growth Measures portfolio is good and can provide potential benefits to teachers. However, adjustments that better support teachers, students, and the physical education program should occur. It is the duty of state leaders to improve the portfolio system to help maintain high-quality PE teachers.

STUDENTS’ ACCEPTANCE OF PORTOFOLIO ASSESSMENT IN AN ENGLISH FOR SPECIFIC ACADEMIC PURPOSE (ESAP) COURSE AT A POLYTECHNIC IN CHINA-REFLECTION ON LECTURERS’ BEST PRACTICES

Learning portfolio records the dynamic learning process of individual learners as a form of formative assessment. Portfolio evaluation system has attracted great interest from language educators as it could train learners and improve their language proficiency. This paper set out to explore the potential benefits that could be gained in language learning via the implementation of learning portfolio assessment. This paper uses a case study of the teaching and learning of a course in the major of business English in a vocational college to show the significance of portfolio evaluation system in increasing students’ interest and their learning autonomy. The students showed positive response via survey questionnaires that registered a mean of 3.90 with all items being recorded above 3.50 and via the structured interviews where the students expressed strong receptiveness to the range of benefits that they could gradually gain via such a dynamic teaching, learning and assessing process. Recorded observations by the author also showed positive signs of development in key areas like learners’ autonomy, self-confidence, critical thinking and self- reflection abilities. This study has positive implications for the teaching and learning in vocational college and will be useful for educators to take up as a dynamic teaching and learning approach.

A Reflective reading of the general secondary school 2022 results and the indicators of admission to Egyptian universities

High school is an important transitional stage in the life of the student and his family together, as it charts the course of the student's professional life when he graduates from the university or from higher education institutions. Because of the importance of the high school, efforts are exerted by all segments of society, students, parents, teachers, administrators, examination, and control committees, and ... etc. There is no doubt that these efforts are financially and morally costly, especially since the high school system has been unstable in recent years. It often changes with the change of the minister, once the portfolio system, and once the tablet system, and finally the Babylon chit system and perhaps other systems will come in the future. The state has expanded the number of universities with their three types: governmental, private, and private, and this may be in pursuit of future plans and a feasibility study of the needs of the labor markets globally, Arab, and locally, which casts doubts about the feasibility of the unstudied expansion in university education. Hence, the importance of this study appears to reveal the reality of the secondary school result 2022 and the trends and indicators of university admission to university education. In addition to this, the study seeks to answer a broad question. Where is Egyptian university education heading, does it support class, for example? Is it education for the elite and another for the poor? Is it based on a specific philosophy, and what? Is the state gradually abandoning support for education in general and higher education in particular.