Open Access Original Research Article

Video Ads in Digital Marketing and Sales: A Big Data Analytics Using Scrapy Web Crawler Mining Technique

Addo Prince Clement, Dorgbefu Jnr. Maxwell, Kulbo Nora Bakabbey, Akpatsa Samuel Kofi, Ohemeng Asare Andy, Dagadu Joshua Caleb, Boansi Kufuor Oliver, Kofi Frimpong Adasa Nkrumah

Asian Journal of Research in Computer Science, Page 52-71
DOI: 10.9734/ajrcos/2021/v11i430270

The survival of the global economy is rooted in the production of goods, rendering of valuable services, and formulation and implementation of favorable trade policies. These goods and services supported by related policies however, must reach prospective customers unblemished in good time, through planned advertisement strategies. Advertisement over the years has evolved from the traditional one-on-one to technology induced ones such as digital marketing and sales. Technological advancement has diversified advertisement into a multi-faceted and dynamic channel with enormous growth and prospects. In this paper, we made a significant effort to identify actual online data to justify why short video (SV) adoption is essential in e-commerce and digital marketing. A total of 23589 datasets were drawn from three global B2C and C2C websites using the scrappy web crawlers to investigate a resilience model in the relationship between SV advertising adoption, quality signals, customer satisfaction, price fairness, and sales in digital marketing. Whereas shop location is vital in traditional shopping, logistics service quality overrides its influence in online shopping settings.

Open Access Original Research Article

Approach to Kirana Store Product Arrangement Using Machine Learning

Ajita Patel, Krishna Kumar Tiwari

Asian Journal of Research in Computer Science, Page 72-83
DOI: 10.9734/ajrcos/2021/v11i430271

Market Basket Analysis (MBA) is a method for determining the association between entities, and it has often been used to study the association between products in a shopping basket. Trained Computer vision models are able to recognize objects in photos so accurately that it can even outperform humans in some instances. This study shows that combining objective detection techniques with market basket analysis can assist Stores/Kirana in organizing the products effectively. With the use of MBA and Object detection, we formulated recommendations for store arrangements along with putting a recommendation engine on top to help shoppers. After deploying this to local Kirana stores, the Kirana store was able to see an increase of 7% in the sale. The recommendation engine performed better than just the domain knowledge of the kirana store.

Open Access Review Article

A Survey of Data Mining Activities in Distributed Systems

Waleed A. Mohammad, Hajar Maseeh Yasin, Azar Abid Salih, Adel AL-Zebari, Naaman Omar, Karwan Jameel Merceedi, Abdulraheem Jamil Ahmed, Nareen O. M. Salim, Sheren Sadiq Hasan, Shakir Fattah Kak, Ibrahim Mahmood Ibrahim

Asian Journal of Research in Computer Science, Page 1-18
DOI: 10.9734/ajrcos/2021/v11i430267

Distributed systems, which may be utilized to do computations, are being developed as a result of the fast growth of sharing resources. Data mining, which has a huge range of real applications, provides significant techniques for extracting meaningful and usable information from massive amounts of data. Traditional data mining methods, on the other hand, suppose that the data is gathered centrally, stored in memory, and is static. Managing massive amounts of data and processing them with limited resources is difficult. Large volumes of data, for instance, are swiftly generated and stored in many locations. This becomes increasingly costly to centralize them at a single location. Furthermore, traditional data mining methods typically have several issues and limitations, such as memory restrictions, limited processing ability, and insufficient hard drive space, among others. To overcome the following issues, distributed data mining's have emerged as a beneficial option in several applications According to several authors, this research provides a study of state-of-the-art distributed data mining methods, such as distributed common item-set mining, distributed frequent sequence mining, technical difficulties with distributed systems, distributed clustering, as well as privacy-protection distributed data mining. Furthermore, each work is evaluated and compared to the others.

Open Access Review Article

State of Art Survey for Fault Tolerance Feasibility in Distributed Systems

Arshad A. Hussein, Adel AL-zebari, Naaman Omar, Karwan Jameel Merceedi, Abdulraheem Jamil Ahmed, Nareen O. M. Salim, Sheren Sadiq Hasan, Shakir Fattah Kak, Ibrahim Mahmood Ibrahim, Hajar Maseeh Yasin, Azar Abid Salih

Asian Journal of Research in Computer Science, Page 19-34
DOI: 10.9734/ajrcos/2021/v11i430268

The use of technology has grown dramatically, and computer systems are now interconnected via various communication mediums. The use of distributed systems (DS) in our daily activities has only gotten better with data distributions. This is due to the fact that distributed systems allow nodes to arrange and share their resources across linked systems or devices, allowing humans to be integrated with geographically spread computer capacity. Due to multiple system failures at multiple failure points, distributed systems may result in a lack of service availability. to avoid multiple system failures at multiple failure points by using fault tolerance (FT) techniques in distributed systems to ensure replication, high redundancy, and high availability of distributed services. In this paper shows ease fault tolerance systems, its requirements, and explain about distributed system. Also, discuss distributed system architecture; furthermore, explain used techniques of fault tolerance, in additional that review some recent literature on fault tolerance in distributed systems and finally, discuss and compare the fault tolerance literature.

Open Access Review Article

Scheduling Algorithms Implementation for Real Time Operating Systems: A Review

Gulistan Ahmead Ismael, Azar Abid Salih, Adel AL-Zebari, Naaman Omar, Karwan Jameel Merceedi, Abdulraheem Jamil Ahmed, Nareen O. M. Salim, Sheren Sadiq Hasan, Shakir Fattah Kak, Ibrahim Mahmood Ibrahim, Hajar Maseeh Yasin

Asian Journal of Research in Computer Science, Page 35-51
DOI: 10.9734/ajrcos/2021/v11i430269

The term "Real-Time Operating System (RTOS)" refers to systems wherein the time component is critical. For example, one or more of a computer's peripheral devices send a signal, and the computer must respond appropriately within a specified period of time. Examples include: the monitoring system in a hospital care unit, the autopilot in the aircraft, and the safety control system in the nuclear reactor. Scheduling is a method that ensures that jobs are performed at certain times. In the real-time systems, accuracy does not only rely on the outcomes of calculation, and also on the time it takes to provide the results. It must be completed within the specified time frame. The scheduling strategy is crucial in any real-time system, which is required to prevent overlapping execution in the system. The paper review classifies several previews works on many characteristics. Also, strategies utilized for scheduling in real time are examined and their features compared.