Showing papers in "Journal of Southwest Jiaotong University in 2020"

Digital Content for Millennial Generations: Teaching the English Foreign Language Learner on COVID-19 Pandemic

Abstract: This article describes a method used in teaching English in the midst of the COVID-19 pandemic. Digital content media that can be sourced from YouTube, Facebook, and TV broadcasting, or teaching videos made by the teacher are expected to be utilized to enable students to learn effectively. The Mixed Method with Quan-Qual Approach used to analyse the research data not for teaching. They use questionnaires and interviews to examine the responses of students and teachers in Makassar.The purpose of these instruments is to determine how to use digital content and whether digital content can increase student motivation and interest in the material provided. Based on data analysis results, it was concluded that the use of digital content in teaching English is very helpful for students in understanding material during the pandemic, especially for the millennial generation. Upon using digital content, the learning process becomes easier because it can be directly integrated into various applications such as WhatsApp groups, Zoom, Google Meet, and so on. Further, the use of digital content in the learning process during the pandemic is one way to bypass direct contact (physical distancing) with other students; it is more flexible and can be accessed without constraints. The use of digital content also increases student motivation in learning because the material provided has been designed to evoke students’ interest. However, this mode of teaching has its weaknesses. The limitations of internet resources, both in terms of network and data packages, can restrict all students from using it.

Solid State Reaction Synthesis and Characterization of Aluminum Doped Titanium Dioxide Nanomaterials

Abstract: In this paper, aluminum doped titanium dioxide nanopowder with doping concentration of different weights were successfully prepared with a simple technique: the classic ceramic technique (or solid-state method). This technique permits the acquiring of powders as pellets with a small amount of the material. The best conditions for the prepared pellets are obtained. Titanium dioxide nanoparticles are mixed with different amounts of aluminum concentrations (0%, 3%, 5%, and 7%). The powders were then mixed and consolidated into pellets and sintered using a conventional furnace at 1100oC. The mechanical, thermal, structural, morphological (including roughness of the samples’ surfaces), and optical properties for those as-prepared samples are demonstrated by: Shore D hardness instrument, roughness test Instrument, Lee's Disc, X-ray diffraction, optical microscope, scanning electronic microscope, energy-dispersive X-ray spectroscopy and Fourier-transform infrared spectroscopy, respectively. The effect of aluminum doped concentrations on the characteristics of titanium dioxide nanoparticles depending on the above instruments are studied. The X-ray diffraction patterns appear to the crystallinity of these materials with a grain size between 20 nm and 30 nm. A roughness measurement indicates that the value of titanium dioxide nanoparticles decreases with the addition of aluminum weights according to the results of the hardness of the samples. Moreover, the results showed that the thermal conductivity increased with the increasing weight fraction of aluminum material. The main goal of the present paper is to investigate the annealing temperature-dependent behavior of the broadening parameter and the characteristics of aluminum doped titanium dioxide nanoparticles.

Consumers’ Behavioural Intention to Accept of the Mobile Wallet in Malaysia

Abstract: A mobile wallet is a part of financial technology products and it is still in the infant stage in Malaysia. This study applied 2 theories such as Theory of Reasoned Action and Theory of Acceptance Model. The research objectives of this paper are 1) to investigate the factors influencing consumers’ behavioural intention to accept of the mobile wallet in Malaysia, 2) to analyze the relationships between perceived usefulness, perceived ease of use, perceived security, social influence, price value, social media, brand image, and behavioural to accept the mobile wallet, and 3) to examine the relationship between the behavioural and intention to accept of the mobile wallet in Malaysia. Quantitative data analysis was employed in this study. The results implied that perceived usefulness, perceived ease of use, social influence, and brand image have a significant relationship on the consumers’ behavioural to accept of the mobile wallet, and also the consumers’ behavioural has a significant relationship on the intention to accept mobile wallet. Considerably, the mobile wallet companies can formulate appropriate marketing decisions in designing a more personalized mobile wallet to Malaysian consumers and protect the benefits of consumers’ secured digital payment to motivate mobile wallet acceptance.

Good Governance of Zakat Institutions: A Literature Review

Abstract: This study describes the characteristics of zakat institutions, which can be classified as institutions with good governance. This study summarizes the characteristics of good governance in zakat institutions that have been analyzed in previous research from various countries. Several studies were collected from Scopus-indexed journals with a Q1-Q4 range. This study used the “Charting the Field” method to sort the articles based on the topic, discussion, year, and source. We concluded that in order to for a zakat institution to be considered a good-governance institution, it must meet several criteria, such as distribution criteria, efficiency, and financial reporting. Following these characteristics, this study also provides the positive impacts in zakat institutions if the institutions can perform good governance. The positive impacts obtained from previous research are poverty alleviation, the impact toward the users of zakat institutions, and the life guarantee for muallaf.

An Optimal Algorithm for a Fuzzy Transportation Problem

Abstract: This paper deals with the optimal approximate solution to a special type of optimization problem called a fuzzy transportation problem using pentagonal fuzzy numbers. The values of the cost, supply, and demand for fuzzy transportation problems are taken as pentagonal fuzzy numbers. The pentagonal fuzzy numbers are converted into crisp values using a novel suggested ranking function. By comparing this with the conventional ranking methods, we can achieve better results with the aid of the proposed new ranking method. Vogel’s Approximation Method is then applied to obtain the solution. Several experiments have been conducted in order to investigate the suggested technique.

Twitter Sentiment Analysis Using an Ensemble Majority Vote Classifier

Abstract: Twitter social media data generally uses ambiguous text that can cause difficulty in identifying positive or negative sentiments. There are more than one billion social media messages that need to be stored in a proper database and processed correctly to analyze them. In this paper, an ensemble majority vote classifier to enhance sentiment classification performance and accuracy is proposed. The proposed classification model is combined with four classifiers, using varying techniques—naive Bayes, decision trees, multilayer perceptron and logistic regression—to form a single ensemble classifier. In addition to these, a comparison is drawn among the four classifiers to evaluate the performance of the individual classifiers. The result shows that in terms of an individual classifier, the naive Bayes classifier is optimal as compared to the others. However, for comparing the proposed ensemble majority vote classifier with the four individual classifiers, the result illustrates that the performance of the proposed classifier is better than the independent one.

The New Era of Financial Technology in Banking Industry

Abstract: The purpose of this research paper is to examine the impact of FinTech companies compared to the traditional banking industry. FinTech is a digitalized financial solution that is offered to small businesses and individuals to fulfill their banking needs. It is expected that FinTech companies will be able to offer the same banking products as existing banks, but the FinTech companies are predicted to grow at a faster pace in countries where digital technology is available. There has been mention that FinTech companies have already had a financial impact on the performance of traditional banks. This research paper undertakes to determine if there is enough empirical evidence to support these hypotheses. A study model has been designed that identifies the dependent and independent variables for each hypothesis. The research undertaken to validate this theory will be drawn from the previous literature by academic authors. The findings from the research indicate that FinTech company formations will grow faster in an environment where digital technology is available and mobile phone penetration is widespread. Results show that profitability does change for the traditional banks when there are FinTech companies present in a country and when the banks adopt their own financial technology into their business model. The results from statistical analysis show that the impact of financial technology on the banking sector’s profitability is statistically insignificant.

A New Boubaker Wavelets Operational Matrix of Integration

Abstract: Many fields of science and engineering have used wavelet functions. They are established from expansion of a single mother wavelet function. Boubaker wavelet functions are presented in this paper based on the important properties of Boubaker polynomials. The research goal of this article is to drive a Boubaker wavelets operation matrix of integration in general formulas. Then an approximate solution method for solving a singular initial value problem is presented using Boubaker wavelets along the obtained operational matrix of integration. The importance of this method is that it converts a singular initial value problem in order to solve algebraic examples as a system. The process is based on reducing by means of integration the original problem into integral equations using a Boubaker wavelets operation matrix of integration to predict the integral equation. Illustrative experiments are included. In addition, computational results obtained by a Boubaker wavelets operation matrix of integration are compared with the exact solutions and other existing methods.

Sustainability Concept Implementation in Higher Education Institutions of Indonesia

Abstract: The concept of sustainability has been widely implemented in various organizations. This research aims to develop a theory of implementing the concept of sustainability in non-business organizations, namely, institutes of higher education of Indonesia. The methods used in this research are literature review and content analysis of reports of universities that have implemented the concept of sustainability within their organizations. This research consists of two main parts in which the first part focuses on drafting concepts for implementing sustainability in higher education institutions, and the second part discusses ways to establish a sustainable university. The results of this research will aid in compiling and developing our motive. The resulting concept will consist of three main stages and it can be used as a guideline for universities that will implement the concept of sustainability. This research will frame the policy that can be applied to form a sustainable university and identify obstacles and challenges for the same.

Internal Instability as a Security Challenge for Vietnam

Abstract: National security is one of the most critical elements for Vietnam society, economy and political system, their stability, sustainability and prosperity. It is unconditionally the top priority for Vietnamese government, State, Communist Party and military forces. The article proposes a new research approach treating security and military science as interdisciplinary, but two of the branches of social science. Using empirical analysis and case study as research methods, the article is focused on internal instability as challenging security issue that could pose a real threat and danger to the current socio-economic and political system. Based on the obtained research results we can draw some implications and propose some viable solutions for the Vietnamese authority to guard the safety and security of the people, society and also its political existence.

Spatial Transformation of New City Area: Economic, Social, and Environmental Sustainability Perspective of Makassar City, Indonesia

Abstract: The spatial transformation of new urban areas into industrial urban areas impacts spatial structure, spatial patterns, and environmental degradation. This study aims to analyze the spatial transformation work as a determinant of the development of the new urban area of Metro Tanjung Bunga Makassar and analyze the relationship of spatial expansion, land use change and population increase for the growth of new city areas and the sustainable development of the Metro Tanjung Bunga area, Makassar city. The data for this study has been obtained through observation, surveys and documentation. The research approach used is a sequential explanation. According to the results, that excessive urbanization and maximum compaction led to spatial expansion towards the development of the new urban area of Metro Tanjung Bunga. Moreover, the increase in number has a dominant influence with a value of 32.3% on the growth of the new city area of Metro Tanjung Bunga, Makassar City. Spatial expansion, land use change, and population increase were determinants of growth factors in the new urban areas and they also had a significant impact on environmental quality degradation. This study recommends the importance of considering the impact of new urban spatial areas for the formulation of strategic policies on sustainable development as an effort to meet national development targets for the case of Metropolitan Cities in Indonesia.

Inhibition and Adsorption Using Thiazole-2-Carboxylic Acid as an Anti-Corrosive for Copper in HCl Media

Abstract: This research studied inhibition and adsorption using thiosol-2-carboxylic acid as an anti-corrosive for copper in an acidic environment. The aim of the study was to evaluate the inhibition efficiency of chemical inhibitors through two methods of weight loss, anode and cathode polarization, when concentrations of the inhibitor ranged from 100 to 250 ppm and at temperatures ranging from 40–60°C. The results showed that greater concentration of the inhibitor resulted in less corrosion and increased inhibition efficiency. This indicates the effectiveness of the inhibitor. By forming a layer on the copper surface and through the occurrence of adsorption due to the presence of nitrogen, sulfur and hydroxyl groups, the inhibitor transfers electrons from these groups to the surface of the metal, thus creating a protective layer that protects it from external influences.

The Role of Activating Electronic Training in Increasing Efficiency of Training Process

Abstract: The research deals with the reality of using electronic learning to teach the lessons prescribed for the training courses held at the Continuing Education Center of Middle Technical University, through a survey of the opinions of trainees in training courses held at the center. These trainees are considered the research sample as for the research, community is represented by all participants in the training courses using electronic classes through Google Classroom as a practical application for supporting electronic learning. The questionnaire tool was designed to collect information as a descriptive approach and a set of statistical methods was used to analyze the relationship between variables and test the research hypotheses. This included the simple correlation coefficient Pearson (r) and the significance tests (F, t) to test the significance of the hypotheses. Further more, in order to verify the hypothesis verification; simple linear regression (Regression Linear) was used, as well as interpretation factor (R2) to measure what the independent variable explains from the changes affected by the dependent variable in the research. The research results indicated the importance of using electronic learning in the training process, based on diligence and personal initiative. The research conclusions showed that members of the sample agreed on the importance of supportive (blended) electronic training to enhance the training process and also give them a skill in using electronic learning software.

Prediction of Indonesia Strategic Commodity Prices during the COVID-19 Pandemic based on a Simultaneous Comparison of Kernel and Fourier Series Estimator

Abstract: This study describes a new idea about comparing two new estimations in nonparametric regression for multiresponse cases or simultaneously model based on Fourier series and kernel estimators enabling the prediction of Indonesian strategic commodity prices during the COVID-19 pandemic. Based on the National Strategic Food Price Information Center in Indonesia, there are 10 strategic commodities in the agriculture, livestock, fishery, and horticultural sectors, which have had the biggest endowment to secure food supplies and the formation of inflation figures in Indonesia. These commodities include rice, chicken meat, beef, chicken, egg, onion, garlic, chili, cayenne, cooking oil, and sugar. Using the goodness estimator of criteria in nonparametric regression, such as the smaller Generalized Cross-Validation, the smaller Mean Square Error, and the larger determination coefficient (R2), the result of this study is Fourier series estimator to predict the prices of 10 food commodities, simultaneously. When compared with the kernel estimator, the Fourier series estimator meets the criteria of goodness with a smaller Mean Square Error value of 0.052 and a larger determination coefficient of 99.0472%. The selected estimator has very good performance to predict the prices of 10 food commodities, because the prediction result has very small Mean Absolute Percentage Error equaling 0.0443%. This prediction result can be used for the government to monitor and evaluate price fluctuations for 10 commodities so that the stability of national strategic commodities becomes daily consumption to be maintained, especially during the COVID-19 pandemic.

Energy Consumption, Income, Trading Openness, and Environmental Pollution: Testing Environmental Kuznets Curve Hypothesis

Abstract: The purpose of this study is to examine the effects of energy consumption, economic growth, and trade openness on environmental pollution in a developing country, especially in the case of Vietnam. The study was conducted on the basis of time-series data collected in the period of time between the years 1990 and 2014. By a method of autoregressive distributed lag and testing the hypothesis of the environmental Kuznets curve, our result demonstrated that environmental Kuznets curve could be found in both the long run and short run. There existed an inverted U-shaped relationship between different pollutants and per capita income. Further, energy consumption could positively affect carbon dioxide (CO2) emissions in the short run, but negatively could affect CO2 emissions in the long run because of transformation from non-renewable energy sources to renewable energy sources. In addition, environmental pollution converged on its long-run equilibrium by at least 29.4% with the speed adjustment via the channel of income, energy consumption, and trade openness. In terms of trade openness, the country has a positive and significant effect on CO2 emissions in both the long run and short run.

Urban Air Quality Assessment Using Integrated Artificial Intelligence Algorithms and Geographic Information System Modeling in a Highly Congested Area, Iraq

Abstract: Pollutant emissions are considered to be a major threat to air quality and human health in urban areas. Therefore, accurate modeling and assessment tools are required. In this study, a model was done by the integration of machine learning algorithms and a geographic information system model. This model included the optimization of the support vector regression model by using the principal component analysis algorithm. Then, the integration of the regression model with spatial analysis modeling via a grid (100 x 100 m) was done in order to generate prediction maps during holidays and workdays in the daytime and at nighttime in a highly congested area in Baghdad city, Iraq. The data used in this study categorized into two categories. The first category is the data acquired through field surveying that includes temperature, humidity, wind speed, wind direction, and traffic flow data (e.g., the number of light and heavy vehicles), as well as carbon monoxide samples by using mobile equipment. The second category is the information derived from geographic information system data, such as land use, road network, and building height. The accuracy of the proposed model is 81%, and the lowest value of root mean square error was 0.067 ppm. The integration between air pollution models and geographic information system techniques could be a promising tool for urban air quality assessment and urban planning. These tools effectively utilized by stakeholders and decision-makers to outline proper plans and strategies to mitigate air pollutants in urban areas.

Integrity and Security in Cloud Computing Environment: A Review

Abstract: Cloud computing is a newly developed concept that aims to provide computing resources in the most effective and economical manner. The fundamental idea of cloud computing is to share computing resources among a user group. Cloud computing security is a collection of control-based techniques and strategies that intends to comply with regulatory compliance rules and protect cloud computing-related information, data apps, and infrastructure. On the other hand, data integrity is a guarantee that the digital data are not corrupted, and that only those authorized people can access or modify them (i.e., maintain data consistency, accuracy, and confidence). This review presents an overview of cloud computing concepts, its importance in many applications, and tools that can be used for providing the integrity and security to the data located in the cloud environment.

EFL Learners’ Perceptions about the Use of Mobile Learning during COVID-19

Abstract: Mobile learning has recently emerged as a powerful and frequently used tool in the teaching-learning curriculum. Besides, it also attracted the attention of EFL teachers and learners across the globe. Its acceptance in EFL learning is mainly because of the two fundamental functions, i.e., anytime and anywhere. As a result, the pioneers and scholars who work in second or foreign language learning have largely recognized its impact and importance. Furthermore, since the outbreak of the COVID-19 pandemic, the regular traditional classes have been severely affected, and teaching has been carried out by online method. As a result, mobiles and tablets have primarily been used along with other electronic gadgets. Therefore, this paper aims to examine EFL learners' perceptions about m-learning for their learning activities during COVID-19 at Qassim University, Saudi Arabia. A questionnaire has been prepared by keeping the use of the mobile device in view that can benefit Saudi EFL learners, and distributed among 50 EFL male and female students. Later, a quantitative analysis of the responses has been done by using SPSS 26. The study identified healthy and positive perceptions of m-learning. The significant findings will be valuable for the teachers and administrators concerning m-learning in language teaching.

The Practice of Digital Learning (D-Learning) in the Study from Home (SFH) Policy: Teachers' Perceptions

Abstract: This article investigates the efficacy of Digital Learning implementation in SFH policy from teachers' viewpoints. The outbreak of the COVID-19 pandemic in Indonesia in mid-March 2020 required the Government to take a decisive step in the form of Study from Home (SFH). The policy was aimed at preserving the quality of students' mental and psychological learning while socially and physically distancing. In this descriptive qualitative study, the interviews were conducted online with four teachers in various high schools in Bulukumba Regency, Indonesia. It was also supported by documents. This research found that teachers prefer to use WhatsApp and Google Classroom as the platforms to organize D-Learning. These applications are more comfortable to use, easy to access, and more familiar in their environment. Teachers perceive that D-Learning modifies the learning process so that it becomes more flexible. It also results in more autonomous learners. However, teachers are aware they are not yet ready to provide good technology-based material. They face difficulties in assessing students' progress from home. Students were also found to lack enthusiasm in responding to the learning content. Besides, inadequate facilities and infrastructure limit the students' access to D-Learning. As a result, D-Learning in SFH policy has not been effective for the students' cognitive and affective development and learning goals cannot be maximally achieved. Thus, it is suggested that the government support all efforts to adjust quickly to the D-Learning system's practice, such as by broadcasting more educational content through electronic media and publishing materials of pedagogical specialists for working in D-Learning environments.

New Properties of Modified Second Kind Chebyshev Polynomials

Abstract: Modified second kind Chebyshev polynomials for solving higher order differential equations are presented in this paper. This technique, along with some new properties of such polynomials, will reduce the original differential equation problem to the solution of algebraic equations with a straightforward and computational digital computer. Some illustrative examples are included. The modified second kind Chebyshev polynomial is calculated using only a small number of the modified second kind Chebyshev polynomials, which leads to attractive results.

Boubaker Wavelet Functions for Solving Higher Order Integro-Differential Equations

Abstract: In the present paper, the properties of Boubaker orthonormal polynomials are used to construct new Boubaker wavelet orthonormal functions which are continuous on the interval [0, 1). Then, a Boubaker wavelet orthonormal operational matrix of the derivative is obtained with the new general procedure. The matrix elements can be expressed in a simple form that reduces the computational complexity. The collocation method of the Boubaker orthonormal wavelet functions together with the application of the derived operational matrix of the derivative are then utilized to transform the higher-order integro-differential equation into a solution of linear algebraic equations. As a result, the solution of the original problem reduces to the solution of a linear system of algebraic equations and can be sufficiently solved by an approximate technique. The main advantage of the suggested method is that the orthonormality property greatly simplifies the original problem and leads to easy calculation of the coefficients of expansion. Special attention is needed to perform the convergence analysis. The error is analyzed when a sufficiently smooth function is expanded in terms of the Boubaker orthonormal wavelet functions, then an estimation of the upper bound of the error is calculated. The results obtained by the technique in the current work are reported by solving some numerical examples and the accuracy is checked by comparing the results with the exact solution.

Automatic Leftover Weight Prediction in Tray Box Using Improved Image Segmentation Color Lighting Component

Abstract: The problem of food waste is experienced by many countries, including Indonesia. In the previous Comstock model, estimating food scraps required the expertise of the estimator, but this method has drawbacks because of subjective perspective of even skilled observers. Another weakness occurred when the observers were exhausted, which in turn negatively affected the measurement of leftover estimation. Therefore, in this paper, we propose an approach for automatic weight prediction using image processing in order to minimize the error forecasting caused by humans. Improved lighting component in image segmentation is also utilized. We apply this framework in the tray box images and estimate each compartment. Two types of tray box backgrounds are tested: gray and black backgrounds. The first part of the proposed method takes a lighting component from each color channel of LAB, HSV, YcbCr, YUV, and LUV. Each of those color channels are applied in contrast limited adaptive histogram equalization to adjust the contrast of each image. After that, the Otsu segmentation is applied, and some formulas to calculate leftover automatically are also presented. The result shows remarkable results when applied in the black background of the tray box with root mean square error around 6.67 using an L lighting component of LAB and Y lighting color component as well YcbCr and YUV. The proposed method is good for leftover forecasting since the estimation is not significantly different from one done by human observers.

Weights of Factors Contributing to Flood Formation in the Lam River Basin, Vietnam

Abstract: There are many factors that influence the formation and development of floods, such as rainfall, soil, slope, land cover, drainage, and density. Therefore, a quantitative assessment of their importance is necessary, especially in the determination of flood risk zones, using the Analytic Hierarchy Process algorithm and Geographic Information System. In comparison with other methodologies, an obvious advantage of Analytic Hierarchy Process is the ability to solve multi-variable qualitative and quantitative problems with precise and trustworthy results. This paper presents the application of the Analytic Hierarchy Process algorithm in analyzing and evaluating the level at which various criteria affect flood risk in the Lam River basin. Some of the flood-causative factors considered in this paper are annual rainfall, soil, slope, land cover, drainage density, and relative slope length. These factors were chosen based on the physical conditions of the study area. The research results are the weight of different criteria. The higher the weight, the higher the effect of that criterion on flood risk. The computed weights show that annual rainfall and slope are the factors that contribute the most to flooding, based on decision-makers’ judgement. The results of this article can be used to construct a flood risk zoning map and flood susceptibility map for flood warnings in the Lam River basin, using the Analytic Hierarchy Process method and Geographic Information System technology. New research shows that Analytic Hierarchy Process can be trustworthy when assessing the level of influence of the different factors on determining flood-prone areas in the Lam River basin, as well as other basins.

Bit Error Rate Evaluation in Atmospheric Blustery for Slant Path Spread of Super Lorentz Gaussian Beam

Abstract: The formula of the scintillation index fixated on bit error rate of Super Lorentz Gaussian beam in turbulent atmosphere is derivative by using the Huygens Fresnel Process to evaluate the average bit error rate. The scintillation index guides of a higher beam order engrossed Super Lorentz Gaussian beam flat and Cartesian coordinates are compared. The average signal-to-noise ratio is computed via the versus scintillation index and bit error rate by using the formula of log-normal dispersed intensity for the beam order and absorbed the Super Lorentz Gaussian beams (SLG) is propagated in the slant path, which display several factors such as source size, focal length and wavelength, for example, 0.8 and 1.55 μm. Absorbed beams are initiated to take significant compensations over higher order beams. According to the two desired wavelength distributions processed theoretically, the results of bit error rate estimation were started to the value of source size rises, the system is improved and scintillation index, bit error rate decreased, the quality of bit error rate was enhanced, and the elevation was decreased. Bit error rate quality estimation of full reference objective relay on the feedback by SLG22 beam has the better bit error rate.

Determining Factors Affecting the Interest in Investment in Bulukumba Area of South Sulawesi

Abstract: The natural resources in Bulukumba district are readily available, but they are not optimally managed. Thus, the current economic growth of 5.05% is not high compared to other areas in South Sulawesi. Therefore, there is a need to increase the regional economic growth investment from both domestic and overseas sources. The purpose of this research is to determine the potential of the area and decide how the policy for supporting investments and strategies can be done to improve investment in the region. This research, using qualitative descriptive research methods, is a study conducted to determine the value of self-variables, either one or more variables (independent) without making comparisons or linking them with other variables.Qualitative research is a systematic scientific study of the parts and phenomena. The research results are known to the potential area with high competitiveness consisting of the agricultural, fisheries, and tourism sectors. The tourism sector is one of the flagships owned by Bulukumba. There are some tourism products that are superior to the area that are not owned by other regions such as the craft of “Phinisi” boat making as a product of the community culture and the culture of \"amma toa\" in kajang that has not been well managed. Bulukumba can be developed with clear rules so investors can enter and cultivate potential there in order for it to increase regional economic growth to a rate of 7.5%. Moreover, investment development strategy is the provision of convenience in terms of business licenses and the promotion of the area’s potential using technology.

On the Properties of Two-Dimensional Normalized Boubaker Polynomials

Abstract: The aim of the present work deals with newly defined two-variable polynomials for normalized Boubaker . The operational matrices of derivatives with respect to the two variables are presented at first with explicit expression. Then, a normalized Boubaker polynomial approximation for the numerical solution of a class of partial differential equations is proposed, depending on a truncated, normalized Boubaker function series in the equation together with the operational matrices in the proposed partial differential equation. The original partial differential equation is reduced under consideration of a system of simply solvable algebraic equations. Due to the interesting derived properties of normalized Boubaker polynomials in two variables, the suggested method can achieve good results with few complexities. Using operational matrices of derivatives, one can save computation and more memory. Two-dimensional examples are listed to show the satisfactory level of the suggested method.

A Proposed Architectural Framework for Generating Personalized Users’ Query Response

Abstract: Personality mining is a vital approach which is currently been on focus for retaining customers as well as extending the customers’ segment. Data in its varied forms such as personal profile, social networks data, as well as transactional data could be considered as key for the success of industries. Therefore, successful data analysis by applying intelligent techniques, such as mining, natural language processing techniques, weighting methods, and others, drive competitiveness to a higher level and, further, to uniqueness. One of the main competitive advantages is the customer satisfaction, therefore, utilizing such successful techniques and successfully analyzing these sources of data with exploring their varieties of relationships lead to the successful personalization and consequently the user satisfaction. This research proposes an adaptive framework for documents’ personalization. The proposed framework builds the most suitable documents’ contents following user’s queries as well as the preferred style for content presentation with respect to users’ personality characteristics. On the other hand, the research highlights the importance of the Egyptian Knowledge Bank as a source of professional documents for replying to the users’ queries. A preliminary investigation has been applied to explore the importance of the proposed framework in the educational field through conducting a survey that included ten staff members and fifty students. The results revealed that the current research is a vital objective in the education field with 91% and 95% respectively.

A Collaborative Evaluation Metrics Approach for Classification Algorithms

Abstract: Evaluating Algorithms is one of the critical steps which should be strongly considered as this is the pillar of most of the decisions. This research proposes a novel method for accurate algorithms’ evaluation according to the metrics’ relationships and weight. The weight of the evaluation metrics is determined according to their invariance level. The proposed method validity is confirmed by applying and evaluating the most famous and well-populated classification techniques. The results have been considered according to the calculated weight of the evaluation measures to reveal the final algorithm evaluation. As a case study, the most suitable classification technique for Tinnitus data are explored. This research considered the Tinnitus data as Tinnitus symptoms are not clearly recognized which highlights the difficulty of the patients to have a direct and fast diagnosis which highlighted the motivation in investigating intelligent methods for fast Tinnitus diagnosing. The research applied the experiment on a real dataset that is gathered in Egypt and the results highlighted that the Support Vector Machine classification algorithm is the most suitable technique for Tinnitus data classification with an accuracy equal to 90.1%.

The Technology of Professional Teaching The Simulative Company as a Complex of Imitative Teaching Methods

Abstract: The characteristics of the competitive specialist and requirements for their training served the basis for the development of the generalized specialist model. A new imitative tutorial The Simulative Company, which is a systemized complex of operation teaching methods, is worked out and implemented. The research provides the algorithm of the teaching method The Simulative Company development realized and implemented by the authors in student groups on the specialties Management and Economy and Bookkeeping. The algorithm comprises the following stages: the launch of The Simulative Company (presenting The Simulative Company, the analysis of the environment); the functioning of The Simulative Company (recruitment, professional activity appraisals, partnering); the creation of an automated workplace. It is proved that in secondary professional educational institutions, active teaching methods should be given precedence to, which will increase the student's learning activity, facilitate the development of their initiative and personal potential, generate their creative approach, as well as will allow solving important teaching and organizational tasks. The established specifics of imitative teaching methods usage enable: to put into practice the models of the competitive specialist within the educational process; to realize the teacher’s potential in improving his/her pedagogical excellence; to implement the system of new imitative teaching methods which is presented by the new technology The Simulative Company.

An Efficient Model for Financial Risks Assessment Based on Artificial Neural Networks

Abstract: According to the developments in financial liberalization and banking innovation, the bank risks have been changed in their nature which leads to use new financial instruments. Thus banks increasingly adopt risk assessment to avoid it. Therefore, this article describes a new model to assist financial risk management based on artificial intelligence. This entails using artificial neural networks to forecast financial risks and support the decision-makers and the consumers in making better risk management decisions. A real-world case study based on the Iraqi banking sector is presented to guarantee the applicability, accuracy, and efficiency of our proposed model. The sample was selected from a data of 16 banks for the period (2004-2018), taken from Iraq Securities Commission, regular market (https://www.isc.gov.iq/). The data were examined with an initial analysis and then converted to the formula compatible with neural networks. The authors describe the results obtained and compare them with previous studies. It confirmed the effectiveness of the proposed model for risk assessment by the results obtained from the approved form on artificial intelligence.