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1 – 10 of 19Maedeh Gholamazad, Jafar Pourmahmoud, Alireza Atashi, Mehdi Farhoudi and Reza Deljavan Anvari
A stroke is a serious, life-threatening condition that occurs when the blood supply to a part of the brain is cut off. The earlier a stroke is treated, the less damage is likely…
Abstract
Purpose
A stroke is a serious, life-threatening condition that occurs when the blood supply to a part of the brain is cut off. The earlier a stroke is treated, the less damage is likely to occur. One of the methods that can lead to faster treatment is timely and accurate prediction and diagnosis. This paper aims to compare the binary integer programming-data envelopment analysis (BIP-DEA) model and the logistic regression (LR) model for diagnosing and predicting the occurrence of stroke in Iran.
Design/methodology/approach
In this study, two algorithms of the BIP-DEA and LR methods were introduced and key risk factors leading to stroke were extracted.
Findings
The study population consisted of 2,100 samples (patients) divided into six subsamples of different sizes. The classification table of each algorithm showed that the BIP-DEA model had more reliable results than the LR for the small data size. After running each algorithm, the BIP-DEA and LR algorithms identified eight and five factors as more effective risk factors and causes of stroke, respectively. Finally, predictive models using the important risk factors were proposed.
Originality/value
The main objective of this study is to provide the integrated BIP-DEA algorithm as a fast, easy and suitable tool for evaluation and prediction. In fact, the BIP-DEA algorithm can be used as an alternative tool to the LR model when the sample size is small. These algorithms can be used in various fields, including the health-care industry, to predict and prevent various diseases before the patient’s condition becomes more dangerous.
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Fatemeh Yazdani, Mehdi Khashei and Seyed Reza Hejazi
This paper aims to detect the most profitable, i.e. optimal turning points (TPs), from the history of time series using a binary integer programming (BIP) model. TPs prediction…
Abstract
Purpose
This paper aims to detect the most profitable, i.e. optimal turning points (TPs), from the history of time series using a binary integer programming (BIP) model. TPs prediction problem is one of the most popular yet challenging topics in financial planning. Predicting profitable TPs results in earning profit by offering the opportunity to buy at low and selling at high. TPs detected from the history of time series will be used as the prediction model’s input. According to the literature, the predicted TPs’ profitability depends on the detected TPs’ profitability. Therefore, research for improving the profitability of detection methods has been never given up. Nevertheless, to the best of our knowledge, none of the existing methods can detect the optimal TPs.
Design/methodology/approach
The objective function of our model maximizes the profit of adopting all the trading strategies. The decision variables represent whether or not to detect the breakpoints as TPs. The assumptions of the model are as follows. Short-selling is possible. The time value for the money is not considered. Detection of consecutive buying (selling) TPs is not possible.
Findings
Empirical results with 20 data sets from Shanghai Stock Exchange indicate that the model detects the optimal TPs.
Originality/value
The proposed model, in contrast to the other methods, can detect the optimal TPs. Additionally, the proposed model, in contrast to the other methods, requires transaction cost as its only input parameter. This advantage reduces the process’ calculations.
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Doris Ochterbeck, Colleen M. Berryessa and Sarah Forberger
Neuroscientific research on addictions has prompted a paradigm shift from a moral to a medical understanding – with substantial implications for legal professionals’ interactions…
Abstract
Purpose
Neuroscientific research on addictions has prompted a paradigm shift from a moral to a medical understanding – with substantial implications for legal professionals’ interactions with and decision-making surrounding individuals with addiction. This study complements prior work on US defense attorney’s understandings of addiction by investigating two further perspectives: the potential “next generation” of legal professionals in the USA (criminal justice undergraduates) and legal professionals from another system (Germany). This paper aims to assess their views on the brain disease model of addiction, dominance and relevance of this model, the responsibility of affected persons and preferred sources of information.
Design/methodology/approach
Views of 74 US criminal justice undergraduate students and 74 German legal professionals were assessed using Likert scales and open-ended questions in an online survey.
Findings
Neuroscientific research findings on addictions and views that addiction is a brain disease were rated as significantly more relevant by American students to their potential future work than by German legal professionals. However, a majority of both samples agreed that addiction is a brain disease and that those affected are responsible for their condition and actions. Sources of information most frequently used by both groups were publications in legal academic journals.
Practical implications
In the USA, information for legal professionals needs to be expanded and integrated into the education of its “next generation,” while in Germany it needs to be developed and promoted. Legal academic journals appear to play a primary role in the transfer of research on addiction into legal practice.
Originality/value
This study complements prior work on US defense attorney’s understandings of addiction by investigating two further perspectives.
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Katherine A. Graves, Lindsey Mirielli and Chad A. Rose
This chapter explores the complex intersection between students with disabilities and bullying prevention within educational settings. While bullying impacts all students, those…
Abstract
This chapter explores the complex intersection between students with disabilities and bullying prevention within educational settings. While bullying impacts all students, those with disabilities face unique challenges that make them more vulnerable to such experiences (Rose & Gage, 2016; Rose et al., 2011). By examining the underlying factors contributing to the heightened risk of bullying among students with disabilities, this chapter aims to provide a more comprehensive understanding of the issue. It delves into the specific ways in which students with disabilities are targeted and engage in bullying behaviors, such as through verbal, relational, or physical, and highlights the negative consequences on their overall well-being and academic performance. Moreover, this chapter examines existing interventions and strategies employed to prevent bullying among students with disabilities. It critically evaluates the effectiveness of individual, classroom, and school-wide interventions, highlighting the need for a comprehensive approach that addresses the unique needs and challenges faced by this subset of students. The importance of collaboration between educators, parents, and other stakeholders in implementing evidence-based practices is also emphasized. By promoting awareness, fostering inclusive school environments, and implementing targeted interventions, we can strive toward creating a safe and supportive atmosphere that enables students with disabilities to thrive academically and socially, free from bullying involvement.
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Julia Anamaria Sisu, Andrei Constantin Tirnovanu, Cristina-Claudia Patriche, Marian Nastase and George Cristian Schin
This study explores the enablers of students “entrepreneurial intentions by identifying the factors that raise students” interest in embracing an entrepreneurial career.
Abstract
Purpose
This study explores the enablers of students “entrepreneurial intentions by identifying the factors that raise students” interest in embracing an entrepreneurial career.
Design/methodology/approach
Entrepreneurship education is increasingly attracting attention as a means of fostering entrepreneurial activity and creating a culture of innovation. Developing students' entrepreneurial intentions is critical to promote entrepreneurship. This research is built on a mixed method approach of partial least squares structural equation modelling and fuzzy-set qualitative comparative analysis.
Findings
The factors that influence students ‘entrepreneurial intentions are identified: business incubation programmes, non-reimbursable grants for entrepreneurial students, networking events to promote entrepreneurship, mentoring services, innovation labs for business idea validation and entrepreneurship courses. This knowledge can help develop effective entrepreneurship education programmes. The study also provides actionable insights for educational institutions and policymakers. It underscores the need for innovative educational platforms such as entrepreneurial bootcamps. It also highlights the value of advanced learning environments such as decision theatres to foster a culture of entrepreneurship and innovation.
Originality/value
The study contributes to the body of knowledge on entrepreneurship education. It highlights the need for a multidisciplinary approach to understand the factors that shape students’ entrepreneurial intentions.
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Shahid Rasool, Hasan Aydin and Jingshun Zhang
The purpose of this quantitative study was to fill the knowledge gap and to investigate relationships between cultural background and various demographic factors influencing…
Abstract
Purpose
The purpose of this quantitative study was to fill the knowledge gap and to investigate relationships between cultural background and various demographic factors influencing parental involvement behaviors that prompt them to engage in their children's academic activities.
Design/methodology/approach
A quantitative research method was used to collect data to answer research questions and explore relationships between variables (Fraenkel et al., 2015). The researchers created the survey on Qualtrics and conducted a pilot study to improve the survey based on the recommendations of the pilot study's participants. Some items were reworded suggested by an expert committee to finalize the instrument. This survey mainly consisted of two sections to collect data on participants' demographics and cultural background. The participants used multiple-choice options to answer items pertaining to family demographics. They were asked to use a 5-point Likert scale: very often = 5, often = 4, sometimes = 3, rarely = 2 and never = 1 to respond to survey items regarding cultural background and parental involvement behaviors.
Findings
The correlation coefficient showed a statistically significant relationship between parents' expectations, educational level and their involvement behaviors in children's academic achievement. However, parents' income and cultural background had no statistically significant relationships with parental involvement in their children's academic achievement.
Research limitations/implications
The results of this study have potentially broad implications for educational leaders, policymakers, educators and parents to develop policies for diverse students to enhance their educational achievements.
Originality/value
The researchers reviewed extensive literature and found the gap in regional studies particularly related to one of the fastest-growing, financially stable and highly educated ethnic groups in the country. The researchers developed a brand new instrument on Qualtrics and distributed a survey via online and direct administration to collect primary data from 200 participants.
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Diane M. Holben and Perry A. Zirkel
According to national surveys, every year approximately 20% of school-age students report bullying victimization. The risk of victimization is even higher for students with…
Abstract
According to national surveys, every year approximately 20% of school-age students report bullying victimization. The risk of victimization is even higher for students with disabilities, particularly those whose disabilities are characterized by social–emotional or behavioral traits. To address public concern over bullying, states passed anti-bullying laws and schools implemented bullying prevention programs, with little effect on the frequency of bullying. Consequently, parents of students with disabilities increasingly filed lawsuits to address the harm caused by bullying. Previous research established an increasing trajectory for the frequency of these lawsuits, although the outcomes remained largely favorable to the district defendants. To determine whether these trends continue, this study examined bullying-related court decisions over a 2.5 year period to determine the frequency of cases and claim basis rulings, the representation of disability categories among student plaintiffs, and the outcomes distribution for the claim rulings and cases. The findings noted a continued increasing trajectory for the frequency of cases with an overrepresentation of plaintiffs with ADHD, mental health diagnoses, and autism. Most commonly cited legal bases were Section 504/ADA and negligence, with the overall outcomes distribution more parent plaintiff-favorable than the previous research. To prevent potential liability, educators should strengthen efforts to both comply with reporting and investigation requirements as well as establishing a school culture that accepts differences among students.
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Robert T. F. Ah King and Samiah Mohangee
To operate with high efficiency and minimise the risks of power failures, power systems require careful monitoring. The availability of real-time data is crucial for assessing the…
Abstract
To operate with high efficiency and minimise the risks of power failures, power systems require careful monitoring. The availability of real-time data is crucial for assessing the performance of the grid and assisting operators in gauging the present security of the grid. Traditional supervisory control and data acquisition (SCADA)-based systems actually employed provides steady-state measurement values which are the calculation premise of State Estimation. More often, however, the power grid operates under dynamic state and SCADA measurements can lead to erroneous and inaccurate calculation results. The introduction of the phasor measurement unit (PMU) which provides real-time synchronised voltage and current phasors with very high accuracy is universally recognised as an important aspect of delivering a secure and sustainable power system. PMUs are a relatively new technology and because of their high procurement and installation costs, it is imperative to develop appropriate methodologies to determine the minimum number of PMUs as well as their strategic placements to guarantee full observability of a power system. Thus, the problem of the optimal PMU placement (OPP) is formulated as an optimisation problem subject to various constraints to minimise the number of PMUs while ensuring complete observability of the grid. In this chapter, integer linear programming (ILP), genetic algorithm (GA) and non-linear programming (NLP) constrained models of the OPP problem are presented. A new methodology is proposed to incorporate several constraints using the NLP. The optimisation methods have been written in Matlab software and verified on the standard Institute of Electrical and Electronics Engineers (IEEE) 14-bus test system to authenticate their effectiveness. This chapter targets United Nations Sustainable Development Goal 7.
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Polish agriculture is one of the main sectors of the national economy that, under the influence of political transformations and European integration, is subject to measures…
Abstract
Research Background
Polish agriculture is one of the main sectors of the national economy that, under the influence of political transformations and European integration, is subject to measures stimulating its development. The instruments of the Common Agricultural Policy (CAP) have been an important supporting stimulus.
Purpose of the Chapter
This chapter aims to evaluate the significance of the common agricultural policy to the growth and development of agriculture and to structural transformations therein triggered primarily by the influx of additional CAP funds.
Methodology
The agricultural sector was examined together with its selected characteristics in the context of CAP instruments' impact after 2004. Data included the streams of funding for Polish agriculture and indicators illustrating changes in structural features, economic performance and productivity of production factors. The indicators included changes in the number, structure and potential of farmsteads, changes in the level of employment in agriculture, this sector's share in total gross value added, profitability of farmsteads, capital expenditure level and changes in labour and land profitability compared with changes in the level of employment and agricultural production intensity. They were calculated based on data from EUROSTAT, Statistics Poland and Farm Accountancy Data Network (FADN).
Findings
The outcomes confirm that common agricultural policy has contributed to create development processes in Polish agriculture. Changes in the sector affected structural characteristics, production factors productivity and the income of agricultural producers. Since Poland joined the European Union (EU), the percentage of agricultural workers declined by 8.4 p.p. and the number of farms decreased by nearly 30%. These changes were accompanied by a nearly twofold increase in agricultural labour productivity, 50% increase in land productivity and the profitability of land increased by 43%.
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Łukasz Wiechetek and Arkadiusz Gola
This chapter describes the present state and the trends in the Polish information and communications technology (ICT) sector, which today is considered to be one of the most…
Abstract
Background
This chapter describes the present state and the trends in the Polish information and communications technology (ICT) sector, which today is considered to be one of the most progressively developing part of the national economy. Special attention is given to economic background, ICT employment and governmental policy. Some forecasts for future development were also proposed.
Purpose of the Chapter
The purpose of this chapter is to present the background, dynamics and future trends in the Polish ICT sector.
Methodology
The statistical data (Statistics Poland, Eurostat), market reports and scientific articles were analysed. Microsoft Excel and QGIS software was used to analyse the data and visualise the results.
Findings
Polish ICT market has stable fundaments, good infrastructure, qualified workers and a good location. Despite the developed infrastructure, e-commerce and e-administration usage is relatively low compared to the average level of EU27. The Polish ICT market specialises in software implementation, IT outsourcing and computer game development. The Polish ICT market development is associated with cloud computing, outsourcing, e-commerce, cybersecurity, big data, artificial intelligence (AI) and Industry 4.0. Poland is also in the top 10 countries for IT outsourcing worldwide, with the leading ICT centers in Warsaw, Cracow and Wrocław.
The growth of the ICT sector was (is) supported also by central programmes and government strategies: Operational Programme Digital Poland, Digital Competence Development Program and Cybersecurity Strategy. In the last 2 years, the development of ICT was also boosted by the COVID-19 pandemic. Market reports and forecasts show that the sector's future development will be related to artificial intelligence, Industry 4.0 and data analytics and financed by private business and central government contracts. The increase in remote work will also be significant.
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