Asian Journal of Research in Computer Science

We contemplate this article to help the teachers of programming in his aspiration for giving some appropriate and interesting examples. The work will be especially useful for students-future programmers, and for their lecturers.

Some of the strong sides of these programming languages C/C++ and Java are the possibilities of low-level programming. Some of the means for this possibility are the introduced standard bitwise operations, with the help of which, it is possible directly operate with every bit of an arbitrary variable situated in the computer’s memory.

In the current study, we are going to describe some methodical aspects for work with the bitwise operations and we will discuss the benefit of using bitwise operations in programming. The article shows some advantages of using bitwise operations, realising various operations with sets.

Project allocation is an annual challenge for lecturers and students. The process of allocating project involves matching preferences of students over project and with of staff over the student, and is thus an instance of stable marriage problem from theoretical computer science aspect. The aim is to find a stable allocation of project to students, such that it is impossible to find a project swap that would make all involved parties (both students, both staff) happier. This paper investigated efficacy of stable marriage algorithm and deployed basic Gale Sharply Algorithm into the process of allocating student project. A system was developed using ruby and MySQL to handle the task. The result showed that the algorithm was able to improve the process by enhancing the stability involved. 

Aims: The study aimed to determine the specific features responsible for the recognition of gestures, to design a computational model for the process and to implement the model and evaluate its performance.

Place and Duration of Study: Department of Computer Engineering, Federal Polytechnic, Ede, between August 2017 and February 2018.

Methodology: Samples of hand gesture were collected from the deaf school. In total, 40 samples containing 4 gestures for each numeral were collected and processed. The collected samples were pre-processed and rescaled from 340 × 512 pixels to 256 × 256 pixels. The samples were examined for the specific characteristics responsible for the recognition of gestures using edge detection and histogram of the oriented gradient as feature extraction techniques. The model was implemented in MATLAB using Support Vector Machine (SVM) as its classifier. The performance of the system was evaluated using precision, recall and accuracy as metrics.

Results: It was observed that the system showed a high classification rate for the considered hand gestures. For numerals 1, 3, 5 and 7, 100% accuracy were recorded, numerals 2 and 9 had 90% accuracy, numeral 4 had 85.67% accuracy, numeral 6 had 93.56%, numeral 8 had 88% while numeral 10 recorded 90.72% accuracy. An average recognition rate of 95% on tested data was recorded over a dataset of 40 hand gestures.

Conclusion: The study has successfully classified hand gesture for Yorùbá Sign Language (YSL). Thus, confirming that YSL could be incorporated into the deaf educational system. The developed system will enhance the communication skills between hearing and hearing impaired people.

Software engineering projects in Nigeria have been classified generally as a failure, challenged or successful with no proof that the projects fall into these categories. The main focus has been on cost and time overrun, and attention has not been given to check whether projects truly fall within the given categories. Discriminant analysis was employed to determine how the 30 selected projects in the public sector in Nigeria can be correctly classified. This study developed a method for determining the actual category of software engineering projects concerning the characteristics of projects as a failure, challenged, or successful. The developed model was used to reclassify the thirty (30) projects, and it was discovered that twenty- one (21) projects were correctly classified giving 70% of correctly classified projects while nine (9) were wrongly classified giving 30%. It is possible for projects to satisfy the established success criteria (requirements met on time and within budget) whereas the stigma of failure still exists in its result.

The global demand for translation and translation tools currently surpasses the capacity of available solutions. Besides, there is no one-solution-fits-all, off-the-shelf solution for all languages. Thus, the need and urgency to increase the scale of research for the development of translation tools and devices continue to grow, especially for languages suffering under the pressure of globalisation. This paper discusses our experiments on translation systems between English and two Nigerian languages: Igbo and Yorùbá. The study is setup to build parallel corpora, train and experiment English-to-Igbo, (), English-to-Yorùbá, () and Igbo-to-Yorùbá, () phrase-based statistical machine translation systems. The systems were trained on parallel corpora that were created for each language pair using text from the religious domain in the course of this research. A BLEU score of 30.04, 29.01 and 18.72 respectively was recorded for the English-to-Igbo, English-to-Yorùbá and Igbo-to-Yorùbá MT systems. An error analysis of the systems’ outputs was conducted using a linguistically motivated MT error analysis approach and it showed that errors occurred mostly at the lexical, grammatical and semantic levels. While the study reveals the potentials of our corpora, it also shows that the size of the corpora is yet an issue that requires further attention. Thus an important target in the immediate future is to increase the quantity and quality of the data.