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Independent component analysis (ICA) is a widely-used blind source separation technique. ICA has been applied to many applications. ICA is usually utilized as a black box, without understanding its internal details. Therefore, in this paper, the basics of ICA are provided to show how it works to serve as a comprehensive source for researchers who are interested in this field. This paper starts by introducing the definition and underlying principles of ICA. Additionally, different numerical examples in a step-by-step approach are demonstrated to explain the preprocessing steps of ICA and the mixing and unmixing processes in ICA. Moreover, different ICA algorithms, challenges, and applications are presented.

The paper is concerned with interpolatory proper orthogonal decomposition (IPOD) methods for nonlinear transmission line circuits. This paper aims to examine several factors that must be considered when applying such model reduction techniques to this kind of circuit.

Two types of POD will be implemented. In each case, the choice of the order of the reduced model and the order of the interpolation space shall be considered. The stability of the models shall be explored.

The results indicate that the order for the reduced model to obtain accurate results depends on the chosen method when considering nonlinear transmission lines. The results also indicate that the structure of the nonlinear transmission line is crucial for determining the stability of the reduced models.

The work compares two IPOD methods and discusses the issues involved in achieving an accurate and stable reduced-order model for a nonlinear transmission line.

Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time. However, storing and processing large and varied datasets (known as big data) is challenging to do in real time. In machine learning, streaming feature selection has always been considered a superior technique for selecting the relevant subset features from highly dimensional data and thus reducing learning complexity. In the relevant literature, streaming feature selection refers to the features that arrive consecutively over time; despite a lack of exact figure on the number of features, numbers of instances are well-established. Many scholars in the field have proposed streaming-feature-selection algorithms in attempts to find the proper solution to this problem. This paper presents an exhaustive and methodological introduction of these techniques. This study provides a review of the traditional feature-selection algorithms and then scrutinizes the current algorithms that use streaming feature selection to determine their strengths and weaknesses. The survey also sheds light on the ongoing challenges in big-data research.

The purpose of this paper is to draw a map of the general features of epistemological and critical concerns in contemporary Islamic philosophy. This study will not be confined to the domain of academic philosophy or to those who are professionals in the field of philosophy.

The paper adopted the critical rational approach in dealing with contemporary Islamic philosophy in the Arab world. The scope will include scholars from different fields of epistemology who tried to present a “vision” of the attitude that should be adopted in facing the challenges of the age and the problems of the nation on the epistemological level or the political, economic and social levels.

There is a need for a philosophy of action and progress rather than a philosophy that is based on abstract ideas and theories and of words/rhetoric. The ethics required to accomplish this ought to identify the attributes of the citizen who can reach self-actualization through legitimate means based on a progress agenda with theoretical and philosophical foundations.

Because a critical rational approach can be dealt with from different perspectives, this paper will adopt the classification of the principal intellectual trends: the reformist, secular and liberal.

This paper covers a long time span to determine whether the philosophical projects have been effective.

This paper, which criticizes the philosophic projects that are theoretically unsound and that do not address real social problems (like poverty), argues the need for a philosophy of progress and action. This will lead to devising an agenda that addresses the challenges the society is facing and to finding alternative and creative solutions resulting in development.

The purpose of this paper is to empirically test the economic convergence that operate between five selected Asian countries (namely Thailand, Singapore, Malaysia, the Philippines and Indonesia). In particular, it seeks to investigate how increased economic integration has impacted the inter-country income levels among the five founding members of ASEAN.

A new Machine Learning (ML) approach is applied along with a panel data analysis (GMM), and the application of KOF Globalization Index.

The Generalized Method of Moments (GMM) results highlight that the endogenous growth theory seems to be supported for the selected Asian countries, indicating evidence of diverging forces resulting from unequal growth and polarization dynamics. Overcoming the technical issues raised by the econometric approach, the new ML algorithm brings contrasted but interesting results. Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members.

Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members. As a matter of fact, the new LSTM algorithm has provided consistent evidence supporting the existence of converging forces. In fact, the results highlighted the effectiveness of the experiments and the algorithm we chose. The high predictability of the authors’ model and the absence of self-alignment in the values showed a convergence be-tween the economies.

Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.

The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.

The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.

Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.

This study aims to improve the availability of regenerative braking for urban metro vehicles by introducing a sensorless operational temperature estimation method for the braking resistor (BR) onboard the vehicle, which overcomes the vulnerability of having conventional temperature sensor.

In this study, the energy model based sensorless estimation method is developed. By analyzing the structure and the convection dissipation process of the BR onboard the vehicle, the energy-based operational temperature model of the BR and its cooling domain is established. By adopting Newton's law of cooling and the law of conservation of energy, the energy and temperature dynamic of the BR can be stated. To minimize the use of all kinds of sensors (including both thermal and electrical), a novel regenerative braking power calculation method is proposed, which involves only the voltage of DC traction network and the duty cycle of the chopping circuit; both of them are available for the traction control unit (TCU) of the vehicle. By utilizing a real-time iterative calculation and updating the parameter of the energy model, the operational temperature of the BR can be obtained and monitored in a sensorless manner.

In this study, a sensorless estimation/monitoring method of the operational temperature of BR is proposed. The results show that it is possible to utilize the existing electrical sensors that is mandatory for the traction unit’s operation to estimate the operational temperature of BR, instead of adding dedicated thermal sensors. The results also validate the effectiveness of the proposal is acceptable for the engineering practical.

The proposal of this study provides novel concepts for the sensorless operational temperature monitoring of BR onboard rolling stocks. The proposed method only involves quasi-global electrical variable and the internal control signal within the TCU.

The main purpose of this paper is to determine the discount function which better fits the individuals' preferences through the empirical analysis of the different functions used in the field of intertemporal choice.

After an in-depth revision of the existing literature and unlike most studies which only focus on exponential and hyperbolic discounting, this manuscript compares the adjustment of data to six different discount functions. To do this, the analysis is based on the usual statistical methods, and the non-linear least squares regression, through the algorithm of Gauss-Newton, in order to estimate the models' parameters; finally, the AICc method is used to compare the significance of the six proposed models.

This paper shows that the so-called q-exponential function deformed by the amount is the model which better explains the individuals' preferences on both delayed gains and losses. To the extent of the authors' knowledge, this is the first time that a function different from the general hyperbola fits better to the individuals' preferences.

This paper contributes to the search of an alternative model able to explain the individual behavior in a more realistic way.

This paper aims to shed light on how children's literature in Africa deserves to be studied because African writers “decolonize” the minds of African children and children and adults around the world.

This paper defines children's literature from an African perspective and the “decolonization of the mind.” This is done to examine how two African writers provide narratives for children inspired by their cultures. They deal with themes, characters and symbols that interest children and adults.

Achebe and Youssef crossed many borders: the world of children and adults, animals and humans, vice and virtue, supernatural and real. Their stories take the reader on journeys that involve enriching, engaging and inspiring adventures.

Youssef and Achebe are prolific writers. Providing a survey of what is available in Arabic and Nigerian literature for children, is beyond the scope of this paper.

This paper sends a message to those in charge of the curriculum in schools in Egypt, the Arab countries, Africa and the world at large: decolonize the syllabi in schools because the world is not black and white. Literature for children that encourages critical thinking is available by African writers in Egypt, Nigeria and elsewhere.

The works discussed show that African writers are creative, and their works inspire the African child with pride in his/her identity, culture and heritage.

To the best of the author’s knowledge, no one has compared Egyptian and Nigerian literature for children before. Youssef and Achebe provide evidence that “Good literature gives the child a place in the world … and the world a place in the child.” – Astrid Lindgren.

This study sheds light on the prediction of success using cutoff scores for student grades adopted for a required Physics pathway course for study in a health professions program at King Saud University in Saudi Arabia. Data on course grade and GPA for approximately 10,000 students enrolled in this course between 2008–2014, were analyzed. Receiver Operating Characteristic (ROC) curve analysis was used to determine cutoffs for course grades using ranges of GPA. This procedure has promise as a new method for quantitatively arriving at cutoff scores using an external criterion requiring less human judgment than most existing standard setting methods. The cutoff scores produced show that GPAs of students who complete the Physics course yield successive performance tiers that are lower than expected. In addition, the correlation between GPA and course grade for Physics is only 0.63 and therefore only 39% of the variation in GPA explains course grade. As a result of the findings of the study, the decision was made to maintain the existing standards thereby requiring higher grades in the Physics course for students seeking to enter a health professions course of study.

ﻧﺗﻟا ﺎﮭﺗردﻗو ﺔﯾدﺣﻟا تﺎﺟردﻟا ﻰﻠﻋ ءوﺿﻟا ﺔﯾﻟﺎﺣﻟا ﺔﺳاردﻟا طﻠﺳﺗ ﻲﻓ ﺔﺑﻠطﻟا حﺎﺟﻧ ﻰﻠﻋ ﺔﯾؤﺑﻲﻟوﻻا ءﺎﯾزﯾﻔﻟا ررﻘﻣ زﯾﻓ)145( ، دﻌﯾ يذﻟاوﻠﻋ ﺎﯾﺳﺎﺳا ﺎﺑﻠطﺗﻣكﻠﻣﻟا ﺔﻌﻣﺎﺟ ﻲﻓ ﺔﯾﺣﺻﻟا تﺎﺻﺻﺧﺗﻟا ﺔﺑﻠط ﻰ ﺔﻘﻠﻌﺗﻣﻟا تﺎﻧﺎﯾﺑﻟا ﻊﻣﺟ مﺗ دﻘﻓ ﺔﯾﻠﻋو ،ﺔﯾدوﻌﺳﻟا ﺔﯾﺑرﻌﻟا ﺔﻛﻠﻣﻣﻟﺎﺑ دوﻌﺳ نﻣ برﺎﻘﯾ ﺎﻣﻟ ررﻘﻣﻟا اذھ تﺎﺟردﺑ10000 ماوﻋﻻا نﯾﺑ ررﻘﻣﻟا اذﮭﺑ اوﻘﺣﺗﻟا نﯾذﻠﻟا ﺔﺑﻠطﻟا نﻣ2008 - 2014 .ﺔﯾﻣﻛارﺗﻟا مﮭﺗﻻدﻌﻣو ،م ﺗﻟو مادﺧﺗﺳا مﺗ دﻘﻓ ،تﺎﻧﺎﯾﺑﻟا هذھ لﯾﻠﺣ تﺎﯾﻠﻣﻌﻟا لﯾﻐﺷﺗ ﺔﯾﺻﺎﺧ ﻰﻧﺣﻧﻣReceiver Operating Characteristic (ROC) تﺎﺟردﻟا دﯾدﺣﺗﻟ نﻣ دﺣﻟاو ﺔﯾدﺣﻟا تﺎﺟردﻟا ﻰﻟا لوﺻوﻠﻟ ﺔﺛﯾدﺣﻟا ﺔﯾﻣﻛﻟا قرطﻟا نﻣ ﺔﻘﯾرطﻟا هذھ دﻌﺗ ثﯾﺣ ،ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نﻣ ﺔﻔﻠﺗﺧﻣ تﺎﻗﺎطﻧﻟ ﺔﯾدﺣﻟارﯾﺛﺄﺗﻟا .يرﺷﺑﻟا نﻣﺿ نﺎﻛ ررﻘﻣﻟا اذھ زﺎﺗﺟا نﻣﻟ ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نا ﻰﻟا ترﺎﺷا دﻗ ﺎﮭﯾﻠﻋ لوﺻﺣﻟا مﺗ ﻲﺗﻟا ﮫﯾدﺣﻟا تﺎﺟردﻟا نﺎﻓ ﺔﯾﻠﻋو تﻐﻠﺑ ﺔﺑﻠطﻟا تﺎﺟردو ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نﯾﺑ ﺔﯾطﺎﺑﺗرﻻا ﺔﻗﻼﻌﻟا نا ﺎﻣﻛ ،ﻊﻗوﺗﻣﻟا نﻣ لﻗا تﺎﻗﺎطﻧ0.63 ﻲﻧﻌﯾ ﺎﻣﻣ ، نا 39% نﻣتﺎﻧﯾﺎﺑﺗﻟا ﺔﯾﻣھا نﯾﺑﺗﯾ ﺞﺋﺎﺗﻧ نﻣ ﺔﯾﻠﻋ لوﺻﺣﻟا مﺗ ﺎﻣﻟ ﺎﻘﻓوو .رﻘﻣﻟا كﻟذ ﻲﻓ مﮭﺗﺎﺟرد رﯾﺳﻔﺗ ﻲﻓ مﮭﺳﺗ نا نﻛﻣﯾ ﺔﺑﻠطﻠﻟ ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا ﻲﻓﺔظﻓﺎﺣﻣﻟا ﻰﻠﻋ ررﻘﻣﻟا رﯾﯾﺎﻌﻣﺔﯾﻟﺎﺣﻟا ﻊﻣدﯾﻛﺄﺗ لوﺻﺣﺔﺑﻠطﻟا تﺎﺻﺻﺧﺗﻟﺎﺑ قﺎﺣﺗﻟﻼﻟ نﯾﺑﻏارﻟاﺔﯾﺣﺻﻟا تﺎﺟرد ﻰﻠﻋﺔﻌﻔﺗرﻣ .ءﺎﯾزﯾﻔﻟا ررﻘﻣ ﻲﻓ