Asian Journal of Research in Computer Science

Aims: This article reports the various application areas of the spoken dialogue system in the developing world to determine if the system could be used to bridge the digital divide prevalent in these regions of the world. The work also aims to identify in which developing nations is the system currently being put to use.

Study Design:  A survey of twenty articles on the subject matter was carried out and their domains of the application were identified. The different forms of the evaluation carried out on them were also identified towards determining their outcomes positivity for bridging the digital divide. Various comments made of the different evaluations were also considered in determining the suitability of spoken dialogue systems in bridging the digital divide.

Place and Duration of Study: Department of Computer Science and Information Technology, Bowen University, Iwo, Nigeria, between February 2013 and October 2019.

Methodology: The different domains of the works, the different forms of the evaluation carried out on the systems, the various comments consequent upon the testing of the systems by the participants and the developing countries where those works were carried out were identified. A position was now taken based on the results obtained.  

Results: Nine of the works are in the healthcare domain, three in agriculture, one in banking, one in aviation, one in secretarial work, one in the accuracy of recognition, one in education and three having multiple domains. The various comments and results from the evaluations all point towards the system’s suitability for bridging the digital divide. The spoken dialogue system is currently being used in only six developing nations of the world.

Conclusion: Consequent upon the results obtained, it is clear that spoken dialogue systems can be used to bridge the digital divide in the developing world and that other application areas not yet covered could be explored for the benefits of the citizens of these regions, especially the digitally disadvantaged ones.

Big Data is increasingly used on almost the entire planet, both online and offline. It is not related only to computers. It makes a new trend in the decision-making process and the analysis of this data will predict the results based on the explored knowledge of big data using Clustering algorithms. The response time of performance and speed presents an important challenge to classify this monstrous data. K-means and big k-mean algorithms solve this problem. In this paper, researcher find the best K value using the elbow method, then use two ways in the first sequential processing and the second is parallel processing, then apply the K-mean algorithm and the big K-mean on shared memory to make a comparative study find which one is the best in different data sizes. The analysis performed by R studio environment.

Today, common diseases like malaria, typhoid, cholera and others are becoming more dangerous problems for people living in this world. It is simple to use, portable, inexpensive and makes the diagnosis of typhoid faster, more efficient and more accurate, and helps doctors avoid wasting time on the diagnosis of typhoid and the publication of results. The objective is to know how to avoid the queue of patients in the hospital. In this article, the author proposed a model of expert systems using the knowledge of physicians and other health professionals. The expert system Xper Typh is useful for patients who suffer from typhoid fever. This system will give a response similar to that of a doctor or a medical expert. This system is also very useful in rural areas where we have young medical experts or no medical experts. Study cross-sectional between the Cabinda Provincial Hospital and the Center 1st of May Health in Cabinda during June 2015 and July 2018. We included 65 patients (22 men, 28 women and 15 children); age group from 5 to 75 years old. The patients examined presented different symptoms and signs. On 65 patients, 20 patients with confirmed fever, 25 patients without confirmed fever and 20 contraction patients between the expert system and the physician. The results between the doctor and the expert system are as follows: Sixty-five patients were diagnosed with XpertTyph. The XpertTyph correctly identified 20/65 (30%) of patients with typhoid fever and 25/65 (41%) of patients not suffering from typhoid fever. That is 71% concordance and 29% discrepancy. The criterion of validity of the model presented the best content for a certain level of average diagnosis for the diagnosis (k = 0.21 to 0.40) for typhoid fever which corresponds to 69% of confidence.

Skew detection and correction of a scanned document is a very important step in Optical Character Recognition because skew of scanned document is reducing the accuracy of text line approach for skew detection and correction to calculate the skew angle on multi-script scanned document using Radon transform, Hough transform, Harries corner, Wiener filter and smearing algorithm. In this paper, a proposed approach is compared existing skew detection and correction techniques for printed documents having different scripts: English, Tamil, Sinhala and mixed-script. A proposed hybrid method is tested on 160 documents. The overall testing results is 90.62% for skew detection and correction.

A key ingredient in the world of cloud computing is a database that can be used by a great number of users. Distributed storage mechanisms become the de-facto method for data storage used by companies for the new generation of web applications. In the world of data storage, NoSQL (usually interpreted as "not only SQL" by developers) database is a growing trend. It is said that NoSQL alternates with the most widely used relational databases for the data storage, but, as the name implies, it does not fully replace the SQL. In this paper we will discuss about SQL and NoSQL databases, comparison of traditional SQL with NoSQL databases for Big Data analytics, NoSQL data models, types of NoSQL data stores, characteristics and features of each data store, advantages and disadvantages of NoSQL and RDBMS.