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The purpose of this paper is to predict the daily accuracy improvement for the Jakarta Islamic Index (JKII) prices using deep learning (DL) with small and big data of symmetric volatility information.

This paper uses the nonlinear autoregressive exogenous (NARX) neural network as the optimal DL approach for predicting daily accuracy improvement through small and big data of symmetric volatility information of the JKII based on the criteria of the highest accuracy score of testing and training. To train the neural network, this paper employs the three DL techniques, namely Levenberg–Marquardt (LM), Bayesian regularization (BR) and scaled conjugate gradient (SCG).

The experimental results show that the optimal DL technique for predicting daily accuracy improvement of the JKII prices is the LM training algorithm based on using small data which provide superior prediction accuracy to big data of symmetric volatility information. The LM technique develops the optimal network solution for the prediction process with 24 neurons in the hidden layer across a delay parameter equal to 20, which affords the best predicting accuracy based on the criteria of mean squared error (MSE) and correlation coefficient.

This research would fill a literature gap by offering new operative techniques of DL to predict daily accuracy improvement and reduce the trading risk for the JKII prices based on symmetric volatility information.

This research is the first that predicts the daily accuracy improvement for JKII prices using DL with symmetric volatility information.

For policymakers and participants of financial markets, predictions of trading volumes of financial indices are important issues. This study aims to address such a prediction problem based on the CSI300 nearby futures by using high-frequency data recorded each minute from the launch date of the futures to roughly two years after constituent stocks of the futures all becoming shortable, a time period witnessing significantly increased trading activities.

In order to answer questions as follows, this study adopts the neural network for modeling the irregular trading volume series of the CSI300 nearby futures: are the research able to utilize the lags of the trading volume series to make predictions; if this is the case, how far can the predictions go and how accurate can the predictions be; can this research use predictive information from trading volumes of the CSI300 spot and first distant futures for improving prediction accuracy and what is the corresponding magnitude; how sophisticated is the model; and how robust are its predictions?

The results of this study show that a simple neural network model could be constructed with 10 hidden neurons to robustly predict the trading volume of the CSI300 nearby futures using 1–20 min ahead trading volume data. The model leads to the root mean square error of about 955 contracts. Utilizing additional predictive information from trading volumes of the CSI300 spot and first distant futures could further benefit prediction accuracy and the magnitude of improvements is about 1–2%. This benefit is particularly significant when the trading volume of the CSI300 nearby futures is close to be zero. Another benefit, at the cost of the model becoming slightly more sophisticated with more hidden neurons, is that predictions could be generated through 1–30 min ahead trading volume data.

The results of this study could be used for multiple purposes, including designing financial index trading systems and platforms, monitoring systematic financial risks and building financial index price forecasting.

A significant number of studies have been conducted to analyze and understand the relationship between gas emissions and global temperature using conventional statistical approaches. However, these techniques follow assumptions of probabilistic modeling, where results can be associated with large errors. Furthermore, such traditional techniques cannot be applied to imprecise data. The purpose of this paper is to avoid strict assumptions when studying the complex relationships between variables by using the three innovative, up-to-date, statistical modeling tools: adaptive neuro-fuzzy inference systems (ANFIS), artificial neural networks (ANNs) and fuzzy time series models.

These three approaches enabled us to effectively represent the relationship between global carbon dioxide (CO₂) emissions from the energy sector (oil, gas and coal) and the average global temperature increase. Temperature was used in this study (1900-2012). Investigations were conducted into the predictive power and performance of different fuzzy techniques against conventional methods and among the fuzzy techniques themselves.

A performance comparison of the ANFIS model against conventional techniques showed that the root means square error (RMSE) of ANFIS and conventional techniques were found to be 0.1157 and 0.1915, respectively. On the other hand, the correlation coefficients of ANN and the conventional technique were computed to be 0.93 and 0.69, respectively. Furthermore, the fuzzy-based time series analysis of CO₂ emissions and average global temperature using three fuzzy time series modeling techniques (Singh, Abbasov–Mamedova and NFTS) showed that the RMSE of fuzzy and conventional time series models were 110.51 and 1237.10, respectively.

The paper provides more awareness about fuzzy techniques application in CO₂ emissions studies.

These techniques can be extended to other models to assess the impact of CO₂ emission from other sectors.

This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.

I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.

This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.

The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.

This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.

The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

The purpose of this paper is to understand the dynamic and power-laden nature of university–society collaboration from the individual academic's point of view.

This paper applies an autoethnographic approach in following a specific collaboration process through detailed fieldnotes and continuous reflections.

This research presents university–society collaboration as an emergent, volatile and fairly unpredictable process, involving a multitude of actors on both sides. The interactions among actors shape the emerging process and power relationships. The academic's situation could be understood in terms of multiple and shifting subject positions that could be embraced, accepted, resisted or surrendered to by the academic.

These findings may help academics with own experiences of collaboration to shed light on their observations. Novice academics, interested in collaborating with society, should be aware of the possibility of tensions and exercise of power in interactions with societal actors. When setting up collaboration agreements, academic and societal actors are advised to openly discuss potential problems and how to handle those.

This unique, in-depth testimony of a single collaboration process from the individual academic's point of view uncovers previously unobserved dynamic and political attributes of the process.

Using financial incentives has been criticised for putting too much focus on things that can be measured. Value-based reimbursement may better align professional values with financial incentives. However, professional values may differ between actor groups. In this article, the authors identify institutional logics within healthcare-providing organisations. Further, the authors analyse how the centrality and compatibility of the identified logics affect the institutionalisation of external demands.

41 semi-structured interviews were conducted with representatives from healthcare providers within spine surgery in Sweden, where a value-based reimbursement programme was introduced. Data were analysed using thematic content analysis with an abductive approach, and a conceptual framework based on neo-institutional theory.

After the introduction of the value-based reimbursement programme, the centrality and compatibility of the institutional logics within healthcare-providing organisations changed. The logic of spine surgeons was dominating whereas physiotherapists struggled to motivate a higher cost for high quality physiotherapy. The institutional logic of nurses was aligned with spine surgeons, however as a peripheral logic facilitating spine surgery. To attain holistic and interdisciplinary healthcare, dominating institutional logics within healthcare-providing organisations need to allow peripheral institutional logics to attain a higher centrality for higher compatibility. Thus, allowing other occupations to take responsibility for quality and attain the feeling of professional pride.

Interviewing spine surgeons, physiotherapists, nurses, managers and administrators allows us to deepen the understanding of micro-level behaviour as a reaction (or lack thereof) to macro-level decisions.

Maintaining infrastructures such as roads, bridges, railways and other civil constructions requires long term documentation that ideally should comprise a reliable reflection of the physical structures. However, the Swedish Transport Administration (TRA) states that its documentation is currently inadequate and that new working method are needed. The purpose of this paper is to study how the agency is working to improve their recordkeeping, by taking a closer look at two new positions that now coordinate the delivery of documentation from the building process teams to the agency. What is their role and what challenges do they face with regard to creating, sharing and preserving records with other areas across the TRA? The study’s purpose is also to discuss the concept of the archive in the current environment and how existing archival theory can be applied to long term documentation.

The study used a case study method, as the aim was to explore and understand recordkeeping practices and theoretical implications, without seeking to generalize the findings outside the Swedish Government. Two positions – the delivering coordinator and the receiving coordinator – were chosen as relevant focuses, due to their function as links between departments in which it was previously indicated that creating and maintaining reliable recordkeeping was difficult and where organizational structure might challenge the traditional archival theory. Documents and reports from the agency were used as research material through documentary analysis and a questionnaire consisting of 10 questions was used to conduct semi-structured interviews with 10 coordinators at the agency.

Obtaining the correct documentation at the right time and of appropriate quality from contractors and entrepreneurs was difficult, despite detailed contractual rules and regulations identifying what should be delivered. The work of the coordinators was formally connected to the important tasks of creating, sharing and preserving records with other areas within the TRA, but in reality, the coordinators faced several difficulties due to expectations of their professional role, practices in information management between different departments and archives creation at the entire agency. The interviewees therefore had differing perceptions of what was meant by TRA’s “archive”: it was variously perceived as only including the registry; comprising only the records preserved by the archives department or encompassing only those records in the registry or in the agency’s business system/s. Findings indicate that the concepts of multiple provenances and the recordkeeping “single mind” might provide insights to better inform the recordkeeping principles needed to improve the current environment.

The study was limited to the 10 interviewees in 2 roles, although there are more positions involved in handling records. Future studies may solidify or contest the different themes identified in the present paper, through interviews of those additional roles at the agency. This paper uses the Swedish concept of the archive as a point of departure in its analysis.

By increasing the knowledge about positions that are responsible for handling records at an agency, this paper can get a better understanding of how they affect the ultimate creation of archives. This will give Swedish public agencies and other organizations, better results when they are creating strategies to preserve reliable records for the future.

This study aims to determine whether, by means of the application of genetic algorithms (GA) through the traditional technical analysis (TA) using moving average convergence/divergence (MACD), is possible to achieve higher yields than those that would be obtained using technical analysis investment strategies following a traditional approach (TA) and the buy and hold (B&H) strategy.

The study was carried out based on the daily price records of the NASDAQ financial asset during 2013–2017. TA approach was carried out under graphical analysis applying the standard MACD. GA approach took place by chromosome encoding, fitness evaluation and genetic operators. Traditional genetic operators (i.e. crossover and mutation) were adopted as based on the chromosome customization and fitness evaluation. The chromosome encoding stage used MACD to represent the genes of each chromosome to encode the parameters of MACD in a chromosome. For each chromosome, buy and sell indexes of the strategy were considered. Fitness evaluation served to defining the evaluation strategy of the chromosomes in the population according to the fitness function using the returns gained in each chromosome.

The paper provides empirical-theoretical insights about the effectiveness of GA to overcome the investment strategies based on MACD and B&H by achieving 5 and 11% higher returns per year, respectively. GA-based approach was additionally capable of improving the return-to-risk ratio of the investment.

Limitations deal with the fact that the study was carried out on US markets conditions and data which hamper its application in some extend to markets with not as much development.

The findings suggest that not only skilled but also amateur investors may opt for investment strategies based on GA aiming at refining profitable financial signals to their advantage.

This paper looks at machine learning as an up-to-date tool with great potential for increasing effectiveness in profits when applied into TA investment approaches using MACD in well-developed stock markets.

Major gaps exist in the documented history of occupational therapy in Ireland. The purpose of this paper is to contribute to filling these gaps by providing an overview of three major transitions in Irish occupational therapy in the century preceding the opening of St. Joseph?s College of Occupational Therapy in 1963. Research on occupational therapy’s past is valuable not only for recording and commemorating key events and individuals but also for allowing reflection on and questioning of contemporary practice and assumptions.

This descriptive paper draws on multiple documentary sources to present an overview of the first 100 years of the use of occupation as therapy/occupational therapy in Ireland from 1863 to 1963.

Three major transitions in occupational therapy in Ireland are presented: from moral treatment and the use of occupation as therapy to medical patronage of occupational therapy, from medical patronage to the early/pre-professional era and finally from the pre-professional era to the era of professionally qualified occupational therapists. To illustrate these transitions, a small number of individuals and their contributions are discussed including Dr Eamon O’Sullivan, Dr Ada English, Donal Kelly, Olga Gale and Ann Beckett.

This paper charts the foundations upon which the currently thriving profession of occupational therapy are built. The Association of Occupational Therapists of Ireland recently celebrated their 50th anniversary (AOTI, 2015a), and in 2017, it is 100 years since occupational therapy was formalised in Clifton Springs, New York, USA. Occupational therapy is a relatively young profession, and great opportunities exist to research its history in Ireland to capture the memories and experiences of the pioneers who laid the foundation of the profession as well as to situate the development of the profession in the broader social, cultural and scientific contexts within which it developed.