Mathematical Intelligence Research Articles

A Novel Framework for Analysis of Road Traffic Information for Decision Support by Using Data Mining Techniques

As we know we want traffic data analysis, data mining measures are recommended to help manage and traffic information decision making. Such as this limit, the road type is added intelligence analysis and decision support are another gave. This model has a data collection system and the data warehouse at its heart, and works well mathematical intelligence techniques and the invention of decision support system. As the main part of this report, the main parts of the model, the main process and an implementation plan is developed. An intelligent urban traffic decision analysis system is a system designed to solve open road problems, improve road safety and quality, and improve road quality work. The application of big data mining technology can improve various capabilities types of analysis and processing of traffic information, spread rapidly and provide a decision reference for the application of intelligent transport systems, which will be carried out to ensure smooth and safe roads. This topic will introduce the concept of large data mining technology and intelligent transport systems, and review the architecture of smart city road systems based on big data technology and design implementation of the mining process.

The Relationship between Social Sciences High School and Science High School Students' Multiple Intelligence Levels and Learning Styles

This study which used survey model aims to examine the relationship between the multiple intelligence and learning styles of the Social Sciences High School and Science High School students. Multiple Intelligence Inventory and Learning Styles Inventory were used as data collection tools, which was conducted on 761 students from Social Sciences High School and Science High School. Mann Whitney–U test and point-biserial correlation analysis were used for data analysis. According to the findings, in the comparison of Social Sciences and Science High School types, it was found that mathematical and naturalist intelligence scores were more dominant in Science High School students. It was found that there is a statistically significant difference between the types of schools in which students attended the study in sensing/intuitive learning style. When the relationship between students' learning styles and their scores on multiple intelligence was examined, there were positive relationships, albeit low, in all four learning style dimensions. In line with these data, it is thought that the dimensions of learning style and multiple intelligence, in which individual differences manifest the most, will be considered, and it is thought that students will bring awareness of their own individual differences and individual success.

Kecerdasan Logika Matematika, Efikasi Diri dan Motivasi Berprestasi Terhadap Perilaku Inovatif

The purpose of this study is to get answers empirically: (1) The Effect of Mathematical Logic on Innovative Behavior, (2) The Effect of Self-Efficacy on Innovative Behavior. (3) The Effect of Achievement Motivation on Innovative Behavior. (4) The Joint Effect of Mathematical Logic Intelligence, Self-Efficacy and Achievement Motivation on Innovative Behavior. The method used in this research is a survey method with multiple linear regression approach. The research sample was 40 SMK students in Sawangan sub-district which was determined by random sampling technique. Based on the results of this study, it can be concluded that: (1) There is a partial positive and significant influence of the Mathematical Logic variable on the Innovative Behavior variable, (2) There is a partial positive and significant influence on the Self-Efficacy variable on the Innovative Behavior variable. (3) There is a positive and significant influence of the achievement motivation variable partially on the variable of innovative behavior. (4) There is a positive and significant influence on the variables of Mathematical Logical Intelligence, Self-Efficacy and Achievement Motivation simultaneously on Innovative Behavior. The higher the mathematical logic, the better the self-efficacy and the higher the achievement motivation, the higher the student's innovative behavior.

Students' Mathematical Problem Solving Ability in Elementary School

The purpose of this study was to describe the results of a literature study on mathematical problem solving abilities in elementary schools. This research uses a qualitative descriptive study approach with the type of literature study research. This research is a literature study or library research that describes descriptively the mathematical problem solving abilities of students in elementary schools. The subjects of this study were elementary school students related to their ability to solve mathematical problems. The data sources for this research are secondary data obtained from scientific journals or articles related to the problems discussed. The data will be analyzed using descriptive analysis techniques. The results showed that students' mathematical problem solving abilities still tended to be low. Students have not achieved all of the problem solving indicators. The factors that influence students' mathematical problem solving abilities include prior knowledge, appreciation of mathematics, logical mathematical intelligence, experience, motivation, skills, self-confidence and teachers.

THE EFFECT OF LABORATORY-BASED LEARNING STRATEGIES AND MATHEMATIC LOGICAL INTELLIGENCE ON LEARNING OUTCOMES OF LINEAR ALGEBRA COURSES

This study aims to: (1) analyze the difference in the mean difference that laboratory-based learning is better than the RME (Realistic Mathematics Education) learning strategy and DL (Direct Learning) learning strategy. Methods This research uses quantitative research with experimental methods is 3×2 factorial with three levels of qualification of independent variables: laboratory-based learning strategies, Realistic Mathematics Education (RME) learning strategies, and Direct Instruction (DI) strategies. The results of this research are Differences in learning outcomes for linear algebra courses between students who are taught using laboratory-based learning strategies and students who are trained using DL (Direct Learning) learning strategies, and those prepared using RME (Realistic Mathematics Education) learning strategies. The average difference value (mean difference) that laboratory-based learning is better than the RME (Realistic Mathematics Education) learning strategy and DL (Direct Learning) learning strategy. Linear Jabar on students with high and low mathematical and logical intelligence. This is in line with the explanation that knowledgeable people will more readily accept or understand lessons. There is an interaction between learning strategies and logical-mathematical intelligence on linear algebra learning outcomes. Based on the study results, it is explained that the collaboration between learning strategies and logical-mathematical intelligence is a form of interaction or influence of learning strategies on learning outcomes of linear algebra courses on mathematical, logical intelligence, or vice versa.

Neuro-Cybernetic System for Forecasting Electricity Consumption in the Bulgarian National Power System

Making forecasts for the development of a given process over time, which depends on many factors, is in some cases a difficult task. The choice of appropriate methods—mathematical, statistical, or artificial intelligence methods—is also not obvious, given their great variety. This paper presented a model of a forecasting system by comparing the errors in the use of time series on the one hand, and artificial neural networks on the other. The model aims at multifactor predictions based on forecast data on significant factors, which were obtained by automated testing of different methods and selection of the methods with the highest accuracy. Successful experiments were conducted to forecast energy consumption in Bulgaria, including for household consumption; industry consumption, the public sector and services; and total final energy consumption.

The Impact of Covid-19 on Online Final Exam Scores Among Computer Science Students

The main goal of this research is to identify the impact of COVID-19 on online final exam scores among Computer Science students. The correlation matrix we used indicates the interrelationships among learning outcomes and student profile, type of classes, and student online behaviour. Six courses were taken under consideration: Practical Algorithms, Discrete Mathematics, Software Engineering, Programming, Team Projects, and Artificial Intelligence. A total of 4,988 final exam results were examined. After a deep analysis of the literature on the topic, we expected two scenarios. The first scenario constituted a decline in passing grades due to challenges such as learning platform failures, poor internet connections, or poorer quality of lessons due to teachers’ lack of online competence. We hypothesized the second scenario as extraordinary student performance compared to their prior exams, but due to their dishonesty. The results of the study revealed that neither of the scenarios took place. It turned out that the challenges that seemed to be the most difficult ultimately did not matter. The present study finds that there is not a significant difference in the students’ final exam performance between their online and traditional courses. Our strategy as described in this article has demonstrated a smooth transition from traditional to online teaching and assessment in terms of the final assessment.

Identification of Encrypted Traffic Using Advanced Mathematical Modeling and Computational Intelligence

This paper proposed a hybrid approach for the identification of encrypted traffic based on advanced mathematical modeling and computational intelligence. Network traffic identification is the premise and foundation of improving network management, service quality, and application security. It is also the focus of network behavior analysis, network planning and construction, network anomaly detection, and network traffic model research. With the increase in user and service requirements, many applications use encryption algorithms to encrypt traffic during data transmission. As a result, traditional traffic classification methods classify encrypted traffic on the network, which brings great difficulties and challenges to network monitoring and data mining. In our article, a nonlinear modified DBN method is proposed and applied to encrypted traffic identification. Firstly, based on Deep Belief Networks (DBN), this paper introduces the proposed Eodified Elliott (ME)-DBN model, analyzes the function image, and presents the ME-DBN learning algorithm. Secondly, this article designs an encrypted traffic recognition model based on the ME-DBN model. Feature extraction is carried out by training the ME-DBN model, and finally, classification and recognition are carried out by the classifier. The experimental results on the ISCX VPN-non-VPN database show that the MEDBN method proposed in this article can enhance the classification and recognition rate and has better robustness to encrypt traffic recognition from different software.

Multiple Intelligences and Perceptual Learning Style Preferences of Education and Engineering Students

Effective learning varies based on the students’ different learning styles and intelligence across the curriculum. This research determines the learning styles and multiple intelligences of 250 second-year education students and 200 engineering students. It employed a stratified sampling technique in the data collection process. It reveals that individual, group, auditory, and visual learning are among engineering students’ most common learning styles, while auditory, visual, and kinesthetic learning were the most prevalent among education students. Furthermore, engineering students most commonly demonstrated interpersonal, mathematical, and kinesthetic intelligence. Moreover, visual, linguistic, interpersonal, and kinesthetic intelligence were education students’ most commonly exhibited intelligence. Most intelligence types and learning styles of education and engineering students show a moderate positive correlation. The results of this study suggest that employing teaching strategies based on learning styles and multiple intelligences may positively affect students’ achievement. Likewise, the academic institutions must also consider the multiple intelligences in admitting students for any specific courses.

The Development of the Educational Game to Improve Logical/ Mathematical Intelligence

The purpose of this study was to examine the educational games to improve logical/mathematical intelligence for early childhood education. In this study, logical/mathematical intelligence included the aspects of symbolic thinking, problem-solving, and logical thinking. The educational games were designed to stimulate children to think analytically or to have a higher-order thinking. This study used the ADDIE model. The results indicated that the games were valid and very feasible to use with an average score of 0.88. Additionally, the results of the practicality test of educational games were good. Also, the result indicated that the games had 87% for the effectiveness. Based on the results of the study on three aspects (symbolic thinking, problem-solving, and logical thinking), symbolic thinking and problem solving can be improved independently only with the help of audio, but for the logical thinking aspect, teacher assistance was needed to complete the game.

Multiple Intelligence Informed Resources for Addressing Sustainable Development Goals in Management Engineering

The competence-based model focuses on acquiring skills and abilities, yet each student’s individual circumstances condition the way in which they learn, develop, and implement them. Accordingly, there is a growing interest in defining learning activities that consider the diverse range of intelligences, abilities, and prevailing mindsets in each individual in order to promote inclusive education and sustainable development. This article seeks to design a methodology for the teaching–learning resources associated with the nature of the prevailing intelligence in the competence-based model. Thus, the “competence-intelligence-resource triangle” was proposed for promoting inclusive education in the degree in Management Engineering at the University of the Basque Country (UPV/EHU). A total of 99 teaching–learning resources, 11 competences, and 9 types of intelligence were combined. As far as the multiple intelligence approach is concerned, the 50 students surveyed prioritized logical–mathematical, interpersonal, intrapersonal, linguistic, and spatial intelligences. As a conclusion, the use of teaching–learning resources designed for promoting different types of intelligence in the competence-based model constitutes an adaptive strategy for the students to successfully acquire competences.

PENGARUH KECERDASAN LOGIS MATEMATIS DAN EFIKASI DIRI TERHADAP KEMAMPUAN PEMECAHAN MASALAH MATEMATIKA

The purpose of this study was to determine the effect of mathematical logical intelligence and self-efficacy on mathematical problem solving abilities. This research method uses a survey method. The population in this study were 277 students. The sample used was 74 students. This research was conducted using a questionnaire and a test with a sample of 30 students. The sampling technique used is random sampling technique. Measurement and data collection of students' mathematical problem solving abilities using a written test instrument in the form of an essay totaling 6 valid questions and taking data on mathematical logical intelligence and self-efficacy using a questionnaire totaling 22 questions and 24 valid questions. The results showed that the significant test was obtained Fℎ???????????????????? = 139.969 while F???????????????????? = 3, 13 which stated that was rejected and 1 was accepted, which means that there is a significant influence between mathematical logical intelligence and self-efficacy on mathematical problem solving abilities.

THE USE OF SNAKES AND LADDERS MATH TO THE DEVELOPMENT OF MULTIPLE INTELLEGENCES IN ELEMENTARY SCHOOL MATHEMATICS SUMMATION MATERIALS

Each student has a different level of intelligence, as a result their learning needs are also not aligned. Children have multiple intelligences so a strategy is needed to accommodate the intelligence possessed by children. This research was conducted at SD Islam Tepadu Permata Cendekia, Simalungun Regency, to be precise in third grade students. The aim is to see the effectiveness of the Multiple Intelligences Learning Strategy with the help of Snakes and Ladders Math media on addition material in Mathematics. The implementation of this research is in the form of quasi-experimental research with One group pretest posttest design. Data collection is done by applying tests as well as observations. The results of the study showed that there was an increase in the average score of students before and after being given treatment, namely (40 91). So that it can improve children's mathematical logical intelligence and verbal intelligence through tests. In addition, the physical and interpersonal intelligence of students is also seen when the traditional game media is applied. So it can be concluded that the application of Media Snakes and Ladders is effective in developing Multiple Intelligences in class III SDIT Permata Cendekia, Simalungun Regency.

Analisis kesulitan belajar peserta didik kelas IVB SDN 1 Gabusan pada materi FPB & KPK di masa pandemi Covid-19 berdasarkan kecerdasan logis matematis

<p><strong>Abstract</strong>. This research aims to describe the types and causes of learning difficulties for class IVB students at SDN 1 Gabusan on FPB and KPK materials during the Covid-19 pandemic based on logical mathematical intelligence. This research uses a qualitative descriptive research method with a case study approach. Determination of the subject in the research using purposive sampling technique. This research uses test data collection techniques and task-based interviews. The data validity technique used in this research is time triangulation. Data analysis techniques include identifying all data, reducing data, compiling data in units, validating data to making conclusions. Based on the results of the research, it can be concluded that the type of learning difficulty of students with high logical mathematical intelligence is difficulty in using correct mathematical procedures. The types of learning difficulties of students with moderate mathematical logical intelligence are difficulties in determining the right solution strategy and difficulties in using correct mathematical procedures. The types of learning difficulties of students with low logical mathematical intelligence are difficulties in understanding the given problem, difficulty in determining the right solution strategy, and difficulty in using correct mathematical procedures. The causes of learning difficulties for students with high logical mathematical intelligence are the limited learning time during the limited face-to-face implementation during the Covid-19 pandemic and the way teachers teach using the lecture learning method. The causes of learning difficulties for students with moderate mathematical logical intelligence are the limited learning time during the limited face-to-face implementation during the Covid-19 pandemic, the way teachers teach using the lecture learning method, and low interest in learning. The causes of learning difficulties in students with low logical mathematical intelligence are the limited learning time during the limited face-to-face implementation during the Covid-19 pandemic, the way teachers teach using the lecture learning method, low interest in learning, and an unsupportive family environment for learning. The level of logical mathematical intelligence of students is also one of the factors that affect learning difficulties.</p><strong>Keywords:</strong> learning difficulties, FPB & KPK, and mathematical logical intelligence

The Effect of Mathematical Logical Intelligence on Mathematical Problem Solving Ability through Contextual Approach

The purpose of this study was to prove that there is a correlation between mathematical logical intelligence and mathematical problem solving ability through a contextual approach and to prove that is a significant effect of mathematical logical intelligence on mathematical problem solving ability through a contextual approach. The sample used was 31 students of class VIII B MTs Tauhidiyah Sulang with the material used is polyhedron. The learning process in this study was based on lesson plans with a contextual approach, while the data were obtained through mathematical logical intelligence instruments and mathematical problem solving ability tests. After the data was collected and analyzed using two techniques, namely simple linear correlation and simple linear regression, the conclusions were: 1) There is a positive correlation and significant (r = 0.417) between mathematical logical intelligence and problem solving ability through a contextual approach. 2) There is a significant effect of mathematical logical intelligence on mathematical problem solving ability through a contextual approach of 17.4% which is explained by the regression line equation Y=3.360+0.265X, which means that the mathematical problem solving ability variable has a consistent value a 3.360 and it can be said that for every increase 1 unit of mathematical logical intelligence value increase 0.265 trought contextual approach.

Analytical, Dynamic, and Interactive Platform for Generation and Managing Predictive Models Focused on Energy Sector

Ensuring the supply of electricity in a reliable and safe way is not an easy task, especially when considering renewable and clean energy generated with wind turbines given the intermittency or variability of the wind; also considering different time horizons increases complexity. Mexico has great potential for wind energy in the Eastern region and, to meet this challenge, a platform capable of generating forecast models automatically through mathematical techniques and artificial intelligence and managing them is proposed aimed at providing support based on knowledge and presenting the information graphically through a flexible dashboard, which is customizable and accessible when and where required. In this investigation, components related to the generation of electrical energy in this area are identified and a centralized system is proposed, with information segmentation, management of 3 user profiles, 6 KPIs, 5 configurable parameters, 7 different forecast models using statistical techniques, support vector machines, and automatic and deep learning, with 2 ways of visualization, to carry out analyses at 3 different time horizons. It is built in a modular way with free and open-source software. The results in the energy sector show that it allows focusing on priority activities avoiding rework, ensures reliability and completeness, is scalable, avoids duplication, allows resources to be shared, responds quickly to hypotheses, and has a global and summarized view of relevant data according to the interested party for different periods of time in an agile way, reducing times and offering support to the decision maker.

Sensor based electromagnetic waves for unblocks clogged arteries

A significant advance has been made in medical diagnosis through introduction of mathematical theories and artificial intelligence (AI). The main theme of this research work is to presents a novel arteries unblocks sensor model based on the principle of the propagation electromagnetic waves. Sensor model based on an electromagnetic waves transmit shock waves through guide wires to specifically cross calcified and fibrotic tissues in the arterial vascular system while leaving intact the elastic wall of healthy vessels. This sensor model has been implemented in a designed system model in an electric circuit inside stockings. The observed results are presented to illustrate the performances of his ability to move strange objects which represents the suspended cholesterol. The results expressed by the distance traveled by the stone under the influence of electromagnetic waves transmitted in water showed that the application of this principle for a period of time allows the opening of blockage of the arteries which demonstrates the performance of the proposed sensor model and the entire system. For health state monitoring: severity and localization coordinates of the arteries unblocks by incorporating artificial intelligence tools are studied in detail in second part for better obstruction treatment.

Logical Intelligence and Mathematical Competence Are Determined by Physical Fitness in a Sample of School Children.

Previous research has shown positive relationships between fitness level and different cognitive abilities and academic performance. The purpose of this study was to explore the relationships between logical–mathematical intelligence and mathematical competence with physical fitness in a group of pre-adolescents. Sixty-three children (50.79% girls; 49.21% boys) from Castro del Río (Córdoba, Spain), aged between 11 and 12 years (M = 11.44, SD = 0.64), participated in this research. The Superior Logical Intelligence Test (SLIT) and the EVAMAT 1.0–5 battery were used. Physical fitness was evaluated by the horizontal jump test, the 4×10 meter speed–agility test, and the Course Navette test. The analyses showed positive relationships between physical fitness with logical–mathematical intelligence and mathematical competence. Specifically, linear regression analyzes indicated that the 4×10 speed–agility test significantly predicted mathematical competence (R2 = 0.16; β = −0.41) and the horizontal jump test significantly predicted logical–mathematical intelligence (R2 = 0.24; β = 0.50). These results are in agreement with previous research, highlighting the importance of improving physical fitness from an early age due to its benefits for intellectual and academic development.

On Theoretical Foundations of Human and Robot Vision

A set of cognitive, neurological, and mathematical theories for human and robot vision has been recognized that encompasses David Hubel’s hypercolumn vision theory (The Nobel Prize in Physiology or Medicine 1981 [1]) and Dennis Gabor’s wavelet filter theory (The Nobel Prize in Physics 1971 [2]). This keynote lecture presents a theoretical framework of the Cognitive Vision Theory (CVT) [3-6] and its neurological and mathematical foundations. A set of Intelligent Mathematics (IM) [7-13] and formal vision theories developed in my laboratory is introduced encompassing Image Frame Algebra (IFA) [3], Visual Semantic Algebra (VSA) [4], and the Spike Frequency Modulation (SFM) theory [5]. IM is created for enabling cognitive robots to gain autonomous vision cognition capability supported by Visual Knowledge Bases (VKBs). Paradigms and case studies of robot vision powered by CVTs and IM will be demonstrated. The basic research on CVTs has led to new perspectives to human and robot vision for developing novel image processing applications in AI, neural networks, image recognitions, sequence learning, computational intelligence, self-driving vehicles, unmanned systems, and robot navigations.

Emotional Intelligence Quotient and Mathematics Performance of Students in a State College

The descriptive-correlational research design was employed to determine the relationship between emotional intelligence quotient and the mathematics performance of first year students. The respondents of the study were the randomly selected first year students during the second semester of the academic year 2021- 2022at the Iloilo State College of Fisheries. The data-gathering instruments were Emotional Intelligence Quotient Questionnaire for emotional intelligence quotient, and Mathematics Performance Test for their performance in Mathematics. Data gathered were analyzed using mean, standard deviation, and Pearson’s r. The .05 alpha level was used as the criterion for the acceptance or rejection of the null hypotheses. Results revealed that first year students have average level of emotional intelligence. Students were high in handling relationships, self-regulation and self-motivation and average in empathy, and self-awareness. Generally, they had average performance in Mathematics. A significant and positive relationship was noted between students’ performance in Mathematics and emotional intelligence. It can be concluded therefore that students’ emotional intelligence played important role in enhancing students’ mathematics performance.