This study aims to describe the stress coping mechanism of the academic scholars from the College of Education (COEd) in one of the private higher education institutions in Cabanatuan City, Philippines. This is an action research that focuses on the assessment of the academic scholars’ stressors and their correlates. It involves systematic observations and data collection that enables the researchers to reflect, decide and develop a training plan for stress management. The findings show that monthly family income and economic-related stressors were highly correlated. This further explains that students with high family income are less likely to experience frequent stress. In contrary, students who belong to low-income families are more prone to experience frequent stress. In other words, students who belong to poor families are more vulnerable to stress. Likewise, monthly family income and physiological responses to stress had high interdependence, which means that students with higher socio-economic status are less likely to experience severe anxiety, while students belonging to low-income families tend to experience severe anxiety. The results of this quantitative analysis served as basis in designing or preparing the stress management plan for these students. 

On the Wechat platform, the current article push is mainly completed by the Wechat Public Account, but it is not perfect in the aspects of user information collection, user service, data storage and management. With economic development and progress of the times, people seek development in spiritual and cultural aspects. This program "One Thing One Story" uses Wechat Web Developer Tools as the medium and Wechat Small Program and Cloud Development as the platform. The purpose of push management platform is "use at any time". Small program cloud development has a relatively complete cloud background. It does not need to rebuild the server in the development cycle. Through the relevant interface, small program development can be started and time cost can be reduced. Using JavaScript, CSS style, JSON database and other technologies, we can realize user data collection, article push, push classification management, push data storage, user praise collection and other functions. This program is applied to article pushing, cultural dissemination and other aspects. Through the platform of Wechat applet, the dream of "accessible" can be realized. 

The impact of malicious software are getting worse day by day. Malicious software or malwares are programs that are created to harm, interrupt or damage computers, networks and other resources associated with it. Malwares are transferred in computers without the knowledge of its owner. Mostly the medium used to spread malwares are networks and portable devices. Malwares are always been a threat to digital world but with a rapid increase in the use of internet, the impacts of the malwares become severe and cannot be ignored. A lot of malware detectors have been created, the effectiveness of these detectors depend upon the techniques being used. Although researchers are developing latest technologies for the timely detection of malwares but still malware creators always stay one step ahead. In this paper, a detailed review of malwares types are provided, malware analysis and detection techniques are studied and compared. Furthermore, malware obfuscation techniques have also been presented.

The study examined the influence of classroom management strategies of Junior High School teachers on the academic performance of students in the Ashanti Akim North District. The descriptive survey design was used for the study. One hypothesis and two research questions were developed to guide the study. Multistage sampling technique was used to select 48 teachers and 297 year two students to respond to the Behaviour and Instructional Management Scale (BIMS). Test scores in English Language, Integrated Science, Mathematics and Social Studies were used to measure students’ academic performance. The statistical tools used to analyse the data collected were means, standard deviation, Pearson’s Product Moment Correlation Coefficient (PPMCC) and Multiple Regression. The findings revealed that both students and teachers identified good relationship and reinforcement as the mostly used classroom management strategies. It was found that a significant positive relationship existed between reinforcement and antecedent as classroom management schemes and students’ academic performance. However, good relationship and punishment as classroom management strategies did not have a positive relationship with the academic performance of students. It is recommended that teachers should use reinforcement and antecedent strategies frequently in their classrooms since they play a dual role of managing behaviour and predicting the academic performance of students. Good relationship as a classroom management strategy should be cautiously used because it could potentially be misinterpreted or abused and can lead to low academic performance. Using punishment as a classroom management strategy should be avoided as its use hinders academic performance of students.

Chemistry is very interesting, but it is often regarded as a difficult subject. Computer software can make chemistry teaching easier, and keeps the students active. This paper seeks to introduce some implications of computer softwares in chemistry classroom teaching. These softwares include Powerpoint, Chemoffice, computer simulation softwares, LabVIEW software, some computational chemistry softwares, and other chemistry softwares, such as ACD/ChemSketch, ChemDB software, Chemical Reagent Calculator, Atom Builder and Atoms, Symbols and Equations. We gave the simple directions of these softwares and presented some applicable examples.

The researchers conducted this study with the main purpose of helping the residents of the municipality to expedite the process of obtaining free medicine. In the current setup, an individual who needs to avail of free medicine from the barangay or municipal health center personally visits the place to request maintenance medicine. This motivated the researchers to make a research study focusing on converting the manual requisition system to something that people can access quickly and comfortably without necessarily going out of their households, especially during these challenging times – the pandemic. The researchers called it a “Medicine Management System”. The researchers aimed to speed up the requisition of medicine using this online system. The patients or qualified recipients need not consume time lining up to request medicine from the municipal health center. This system can be accessed over the internet anytime and anywhere. Users must register and upload a legit doctor’s prescription. Researchers have created this system using HTML for the system interface, XAMPP for maintaining database records, and PHP for other system functionalities.

The world has witnessed a sudden change in the teaching-learning processes due to the ongoing pandemic of COVID-19. The worldwide compulsive lockdown for ensuring the preventive measures to stop the spread of this infection has equally affected education sector as other business sectors. As all of us know that quality education is the only long-term rescue for all the challenges and therefore, the need to find out the alternative solution to the traditional classroom teaching-learning is the concern of all stakeholders and the only option found is online mode of teaching-learning, which was somehow already available and had attracted an intense attention during this period. The aim of the paper is to study the teacher’s perspective in India about this mode of learning, challenges and issues faced by them in migration to online platform, experience about online tools/platforms used for instructional delivery and their suggestions to improve the process for effective teaching. This study will help in gaining insight towards the possible improvements in the ongoing mode of online teaching and in future situations also. The results obtained based on sample collection through web based questionnaire clearly gives some information, which could be an eye opener for enhancing the implementation of the online teaching-learning among the learners especially teachers, who can further help in implementation of the large. Although, the online mode was already in place and was utilized in blended form to a substantial level in the developed countries, but in developing countries like India, where teachers are not familiar with online platforms/tools, lack of knowledge and skills to handle the online ICT infrastructure in a challenging situation. The results also give an impression about the need of professional development with special focus on digital literacy skills and awareness among the teacher community about the merits of online platforms for the teaching-learning process.

Teaching at the Right Level (henceforth, TaRL) is a new trending remedial educational approach being piloted in many countries. It basically matches pedagogical content to pupils’ educational needs through various adapted activities after segmentation of pupils’ depending on their actual difficulties and needs. In this respect, Morocco has been piloting this relatively new approach during the beginning of the school year 2022-23. Therefore, this study aimed at measuring the effectiveness of the TaRL approach on Moroccan pupils’ mathematics, Arabic, and French reading competencies. An experimental study took place involving 106 pupils from 4th grade to 6th grade during a one-month remedial course (half an hour per day, one subject per day) based on TaRL guidelines. After carefully examining the data through the Wilcoxon Signed Ranks Test by comparing the baseline and endline results in all three subjects. The results showed statistically high improvements with large effect sizes in the levels of the three subjects suggesting that TaRL was effective in raising the levels of numeracy and literacy and may be, safely, further adopted throughout Moroccan primary schools.

This paper reviews recent advancements in machine learning (ML) driven automated trading systems (ATS). ATS has progressed from simple rule-based systems to sophisticated ML models like deep reinforcement learning, deep learning, and Q-learning that can adapt to evolving markets. These techniques have been successfully applied across various financial instruments to optimize trading strategies, forecast prices, and enhance profits. The literature indicates that ML improves ATS performance over conventional methods by identifying intricate patterns and relationships in data. However, risks like overfitting, instability, and low interpretability exist. Techniques to mitigate these limitations include cross-validation, careful model management, and utilizing more transparent algorithms. Although challenges remain, ML creates valuable opportunities for ATS via alternative data sources, advanced feature engineering, optimized adaptive strategies, and holistic market modelling. While research shows ML improves market quality through increased liquidity and efficiency, heightened volatility needs further analysis. Promising future research directions include leveraging innovations in deep learning, reinforcement learning, sentiment analysis, and hybrid systems. More work is also needed on evaluating different techniques systematically. Overall, the progress in ML-driven ATS contributes significantly to the field, but judicious application and balanced regulations are required to address risks. Further advancements in ML will enable more capable, nuanced, and profitable algorithmic trading.

The present age is the age of information. The globalization has affected every sphere of the life including education. In spite of availability of ICT infrastructure in schools, their potential is underutilized because of digital incompetence of the teachers.  New digital technologies are acting as a catalyst towards improvement of learning outcome and enhancing quality of education, but only introduction of such technologies in schools for producing change and innovation is not enough, it requires digitally competent teachers to facilitate the use of ICT in education. These teachers will act as facilitators and mentors to students to lead them towards problem solving and innovation to meet the new challenges of globalization. Teachers must be able to create learning environments which are student centric and foster creativity, Meta cognition, meta-literacy, collaboration and communication in learners. Mere superficial use of ICT in teaching will not yield the required learning outcome, but the integration of ICT in pedagogy is important to enhance teaching, learning process. This can be done only when teachers are competent enough to use ICT tools and facilitate ICT integrated education. In this paper, we tried to assess the teacher’s perspective about the ICT and investigate the factors responsible for resistance of teachers in using ICT in schools and suggestive measures for successful integration of ICT in the teaching process by the teachers of Rajouri district (J&K, India). The ICT skills are very important for teachers to support alternative modes of teaching, learning, i.e. e-learning, mobile learning in the present outbreak of pandemic disease caused by Coronavirus-COVID19. 

On the Wechat platform, the current article push is mainly completed by the Wechat Public Account, but it is not perfect in the aspects of user information collection, user service, data storage and management. With economic development and progress of the times, people seek development in spiritual and cultural aspects. This program "One Thing One Story" uses Wechat Web Developer Tools as the medium and Wechat Small Program and Cloud Development as the platform. The purpose of push management platform is "use at any time". Small program cloud development has a relatively complete cloud background. It does not need to rebuild the server in the development cycle. Through the relevant interface, small program development can be started and time cost can be reduced. Using JavaScript, CSS style, JSON database and other technologies, we can realize user data collection, article push, push classification management, push data storage, user praise collection and other functions. This program is applied to article pushing, cultural dissemination and other aspects. Through the platform of Wechat applet, the dream of "accessible" can be realized. 

This study aims to describe the stress coping mechanism of the academic scholars from the College of Education (COEd) in one of the private higher education institutions in Cabanatuan City, Philippines. This is an action research that focuses on the assessment of the academic scholars’ stressors and their correlates. It involves systematic observations and data collection that enables the researchers to reflect, decide and develop a training plan for stress management. The findings show that monthly family income and economic-related stressors were highly correlated. This further explains that students with high family income are less likely to experience frequent stress. In contrary, students who belong to low-income families are more prone to experience frequent stress. In other words, students who belong to poor families are more vulnerable to stress. Likewise, monthly family income and physiological responses to stress had high interdependence, which means that students with higher socio-economic status are less likely to experience severe anxiety, while students belonging to low-income families tend to experience severe anxiety. The results of this quantitative analysis served as basis in designing or preparing the stress management plan for these students. 

The researchers conducted this study with the main purpose of helping the residents of the municipality to expedite the process of obtaining free medicine. In the current setup, an individual who needs to avail of free medicine from the barangay or municipal health center personally visits the place to request maintenance medicine. This motivated the researchers to make a research study focusing on converting the manual requisition system to something that people can access quickly and comfortably without necessarily going out of their households, especially during these challenging times – the pandemic. The researchers called it a “Medicine Management System”. The researchers aimed to speed up the requisition of medicine using this online system. The patients or qualified recipients need not consume time lining up to request medicine from the municipal health center. This system can be accessed over the internet anytime and anywhere. Users must register and upload a legit doctor’s prescription. Researchers have created this system using HTML for the system interface, XAMPP for maintaining database records, and PHP for other system functionalities.

The impact of malicious software are getting worse day by day. Malicious software or malwares are programs that are created to harm, interrupt or damage computers, networks and other resources associated with it. Malwares are transferred in computers without the knowledge of its owner. Mostly the medium used to spread malwares are networks and portable devices. Malwares are always been a threat to digital world but with a rapid increase in the use of internet, the impacts of the malwares become severe and cannot be ignored. A lot of malware detectors have been created, the effectiveness of these detectors depend upon the techniques being used. Although researchers are developing latest technologies for the timely detection of malwares but still malware creators always stay one step ahead. In this paper, a detailed review of malwares types are provided, malware analysis and detection techniques are studied and compared. Furthermore, malware obfuscation techniques have also been presented.

This paper reviews recent advancements in machine learning (ML) driven automated trading systems (ATS). ATS has progressed from simple rule-based systems to sophisticated ML models like deep reinforcement learning, deep learning, and Q-learning that can adapt to evolving markets. These techniques have been successfully applied across various financial instruments to optimize trading strategies, forecast prices, and enhance profits. The literature indicates that ML improves ATS performance over conventional methods by identifying intricate patterns and relationships in data. However, risks like overfitting, instability, and low interpretability exist. Techniques to mitigate these limitations include cross-validation, careful model management, and utilizing more transparent algorithms. Although challenges remain, ML creates valuable opportunities for ATS via alternative data sources, advanced feature engineering, optimized adaptive strategies, and holistic market modelling. While research shows ML improves market quality through increased liquidity and efficiency, heightened volatility needs further analysis. Promising future research directions include leveraging innovations in deep learning, reinforcement learning, sentiment analysis, and hybrid systems. More work is also needed on evaluating different techniques systematically. Overall, the progress in ML-driven ATS contributes significantly to the field, but judicious application and balanced regulations are required to address risks. Further advancements in ML will enable more capable, nuanced, and profitable algorithmic trading.

Teaching at the Right Level (henceforth, TaRL) is a new trending remedial educational approach being piloted in many countries. It basically matches pedagogical content to pupils’ educational needs through various adapted activities after segmentation of pupils’ depending on their actual difficulties and needs. In this respect, Morocco has been piloting this relatively new approach during the beginning of the school year 2022-23. Therefore, this study aimed at measuring the effectiveness of the TaRL approach on Moroccan pupils’ mathematics, Arabic, and French reading competencies. An experimental study took place involving 106 pupils from 4th grade to 6th grade during a one-month remedial course (half an hour per day, one subject per day) based on TaRL guidelines. After carefully examining the data through the Wilcoxon Signed Ranks Test by comparing the baseline and endline results in all three subjects. The results showed statistically high improvements with large effect sizes in the levels of the three subjects suggesting that TaRL was effective in raising the levels of numeracy and literacy and may be, safely, further adopted throughout Moroccan primary schools.

The study examined the influence of classroom management strategies of Junior High School teachers on the academic performance of students in the Ashanti Akim North District. The descriptive survey design was used for the study. One hypothesis and two research questions were developed to guide the study. Multistage sampling technique was used to select 48 teachers and 297 year two students to respond to the Behaviour and Instructional Management Scale (BIMS). Test scores in English Language, Integrated Science, Mathematics and Social Studies were used to measure students’ academic performance. The statistical tools used to analyse the data collected were means, standard deviation, Pearson’s Product Moment Correlation Coefficient (PPMCC) and Multiple Regression. The findings revealed that both students and teachers identified good relationship and reinforcement as the mostly used classroom management strategies. It was found that a significant positive relationship existed between reinforcement and antecedent as classroom management schemes and students’ academic performance. However, good relationship and punishment as classroom management strategies did not have a positive relationship with the academic performance of students. It is recommended that teachers should use reinforcement and antecedent strategies frequently in their classrooms since they play a dual role of managing behaviour and predicting the academic performance of students. Good relationship as a classroom management strategy should be cautiously used because it could potentially be misinterpreted or abused and can lead to low academic performance. Using punishment as a classroom management strategy should be avoided as its use hinders academic performance of students.

Developing nations like India have a huge potential for agricultural business and better cultivation. Because of the large size of cultivation land, improper water supply systems and lack of technology-based agricultural practices, there is a huge gap among expected and actual quantity and quality of agricultural products. Hence there is a need for significant revival in agribusiness using emerging technologies. The article proposes an intelligent water framework device called Agribot designed for the agricultural industry to minimize the water wastage and a better supply of cultivating materials using the Internet of Things (IoT). Our proposed IOT- Agribot will energize the water framework, improve the cost-effective water usage and reduce the labor force to achieve precision agriculture. The proposed IOT- Agribot has performed well for variable weather conditions, soli type, moisture content and crops.

Maintenance in any manufacturing organization is critical, given its significant role in ensuring business continuity. Maintenance plays a crucial role and has a significant impact on the results of industrial companies. Therefore, it is essential to manage maintenance, observe, understand, and improve actions by adopting well-chosen performance indicators according to the company's needs. These indicators are known as Maintenance KPIs or Key Performance Indicators, which allow for gathering knowledge and exploring the best means to achieve the organization's goals. Maintenance KPIs are critical to keeping track of the function, monitoring performance, and ensuring fulfillment of business expectations. In addition, KPIs drive reliability growth while guiding decisions to improve maintenance efficiency and performance. A helpful maintenance KPIs help to identify the problems causing the maintenance effect and help to select the right strategy to support or correct the actions that produced the results. They also allow to identify the causes of equipment failures (measure the influence of life cycle factors), direct what maintenance does with its time and resources (measure the efficiency and effectiveness of the maintenance group) and identify if maintenance removes failure causes ( measure the improved reliability and operational risk reduction results of maintenance effort) and help drive the business benefits provided by maintenance (measure the contribution to the business value of maintenance).

Essential maintenance KPIs are the most commonly used for maintenance management and are adopted by most industries; among these primary KPIs which are essential for maintenance management, we cite Mean Time Between Failure (MTBF), Mean Time To Repair (MTTR), and Overall Equipment (OEE). Nevertheless, it is crucial to continuously redefine and update KPIs to ensure they are appropriate for the organization's current environment, significantly when the constant market or research methodologies change. Hence, researchers and the industry propose several other maintenance KPIs outside the essential ones used in the industry according to the needs and within the performance improvement framework. These proposed KPIs aim to compensate for the lack of maintenance data, the absence of decision support, and the problems related to specific equipment, also in the context of improving the management strategy, the application of predictive maintenance, and the quality control of a maintenance process or the monitoring of systems reviews. Unfortunately, these indicators are not sufficiently known and are, therefore, not used by the industry. However, we believe that some of them should gain maturity and reach the status of widely used traditional indicators, such as the KPI of obsolescence management in maintenance operations and schedule compliance KPIs that aim to link maintenance planning with production. In addition, although not all proposed KPIs in the literature are generalizable, it has been identified that they can sometimes be specific to problematic situations, equipment categories, and even sectors of industry activity. Therefore, this work aims to inventory the most widely used maintenance KPIs and some of the KPIs proposed by researchers and the industry. In addition, we study the trends and challenges of selecting these KPIs and for what purposes they are used to help their understanding and usability. Indeed, Maintenance managers need to select relevant KPIs aligned with the maintenance strategy and the company objectives. 

The accuracy of population forecasts is one of the most important calculations in demography statistics. However, traditional demographic methods used in population projections are tend to produce biased results. The need for accurate prediction of future behavior in a number of areas require the application of reliable and efficient methods. Recently, machine learning (ML) models have emerged as a serious competitor to classical statistical models in the forecasting community. In this study, the performance and capacity of the four different ML models such as Random forest (RF), Decision tree (DT), Linear regression (LR) and K-nearest neighbors (KNN) to the prediction of population has been examined. The aim of the study is to find the best performing regression model among these machine learning algorithms for forecasting of population. The data were collected from the State Statistical Committee of the Republic of Azerbaijan website were used for the analysis. We used five metrics such as mean absolute percentage error (MAPE), mean absolute error (MAE), root mean squared error (RMSE), mean square error (MSE) and R-squared to compare the predictive ability of the models. As the result of the analysis, it has been known that the all ML models showed high results with correlation coefficient of 0.985 - 0.996. Also the KNN and RF prediction models showed the lowest root mean square deviation, means square error and mean absolute error values compared to other models. By effectively using the advantage of the ML algorithms, the forecast of population growth the near future can be observed objectively, and it can provide an objective reference to the strategic planning in the public and private sectors, particularly in education, health and social areas.