Asian Journal of Research in Computer Science

Acquiring knowledge, either individually or in a team, is known as learning. The mode of learning may be either supervised or unsupervised. Language learning develops communication ability in a second foreign language, such as the Malay language... Malaysia is among the countries that students around the globe visit for undergraduate and postgraduate studies. But, the international students faced communication challenges with both the local students and the academic staff due to language variations. The local students lack confidence in English, while the international students don’t understand the Malay language. The communication The Gap was pointed out as the major problem for the international students to carry out their academic activities as most lecturers deliver their classes using Bahasa Melayu (Malay language). It is expected for the international students to learn the Malay language, but the local students are communicatively shy due to their lack of confidence in English. The present study investigates the Malay language learning difficulties of the international students at Universiti Sultan Zainal Abidin and Universiti Malaysia Terengganu. The researcher adopted quantative analysis with a structured questionnaire as the research tool. The experiment was carried out with the IBM SPSS version tool, and hardware components such as the Intel Celeron quad core processor (2M cache, 2.0GHz), 4GHz RAM, and 500GHz HDD. One hundred and seventy (170) with eighty-five (85) of equal size between the two universities were considered as the sample size. Findings reveal that most of the respondents disagreed that it was easy to learn Malay with the traditional system that presented a frequency of 41.8%. In addition, 43.5% of the respondents believed that learning Malay with the traditional system was time-consuming. Finally, respondents disagreed that traditional learning systems are easy to read. As such, most of the respondents suggest a mobile application as a substitute to the traditional mode of Malay language learning that will enhance learning anywhere at any time, regardless of the location.

Two experiments to compare text-entry were carried out using Soft Keyboard Layouts. Paper mockups were used and we carried out manual timing in a relaxed situation, even though within a classroom environment. Volunteer students were paired and made to work in such groups, serving as participants and also helping out in the timing process. One set of students served as participants at first and the other timed them. They then switched roles halfway and exchanged the tasks of participation and timing. Participants tapped the phrase “the quick brown fox jumps over the lazy dog” on each keyboard layouts five times using stylus. The time for word entry was measured and used to determine the speeds; which were found to be 24.8 to 34.3 for QWERTY Keyboard Layout and 11.9 to 14.8 for Opti Layout. We discussed the advantages and shortfalls of the methods of evaluation.

In most educational institutions, the computerized selection system (CSS) consists of a collection of different hardware and software requiring disparate supporting infrastructures and offering little in the way of integration. However, university admission is no exception, but it is organized very differently throughout the world. Thus, the goal is to determine the challenges in the use of the computerized system for admission into colleges of education affiliated with the University of Cape Coast. The methodology for the study was a descriptive design with a quantitative method. The total population for the study was 255, with a sample size of 192 admission officers, quality assurance staff, and heads of departments. The results of the study show that one of the challenges of a computerized system for admission is that the system forces some candidates initially selected to grant their place in the list to others far behind. The study’s findings discovered a negative weak association between the challenges of using a computerized system for admission and its’ efficiency.

Artificial neural network (ANN) has the characteristics of self-adaptation, self-learning, parallel processing and strong nonlinear mapping ability. Compared with traditional experimental analysis modeling, ANN has obvious advantages in dealing with multivariable nonlinear complex relationships in the process of industrial catalyst design. In the face of the complex structure of catalyst, the unclear reaction mechanism and conditions, the use of neural network for small-scale experimental data analysis can save the time and energy invested in large-scale experimental research and obtain more perfect results in catalyst formulation optimization and condition selection. This paper summarizes the development of artificial neural network. The application principle, construction method and research progress of BP artificial neural network model in catalyst optimization design are summarized and analyzed. The development and innovation of artificial neural network in the future, as well as its continuous application and accumulation, will provide a powerful tool for the research of catalyst design and optimization in the future.

Deep learning (DL) is a kind of sophisticated data analysis and image processing technology, with good results and great potential. DL has been applied to many different fields, and it is also being applied to the agricultural field. This paper presents a wide-ranging review of research with regards to how DL is applied to agriculture. The analyzed works were categorized in yield prediction, weed detection, and disease detection. The articles presented here illustrate the benefits of DL to agriculture through filtering and categorization. Farm management systems are turning into real-time AI-enabled applications that give in-depth insights and suggestions for farmer's decision support by using the proper utilization of DL and sensor data.