International Journal of Applied Sciences: Current and Future Research Trends

The Impact of Social Networks on E-Commerce

Soma Gholamveisy, Seyedamirmasoud Homayooni, Mohammad sekhavat — Mon, 03 Jul 2023 00:00:00 +0000

Today, with the expansion of e-commerce, businesses have gone out of the traditional mode, and the use of social networks by the public and their positive and tremendous impact on e-commerce and businesses has caused the success of businesses. Hence, Investigating social media advertising and the effective factors in them that affect e-commerce is of great importance. This study was conducted with the aim of investigating the factors that can increase the effectiveness of social media advertising on the customer's online purchase. In this study, these results have found that 6 factors in social media advertising, including interactivity, seductiveness, enjoyment, functional expectation, perceived connection, and habit, have had an effect on the customer's online shopping behavior. In addition, it has been determined that the trust factor Created in e-commerce websites and advertising in social networks is very important.

Role of Interpersonal Communication Channels in the Uptake of Cervical Cancer Screening among Women in Uasin Gishu County, Kenya

Chepngeno Judy B, Anyonje Lydia, Anyonje Lydia — Mon, 11 Sep 2023 00:00:00 +0000

Cervical cancer remains a serious health challenge in the developing world due to various reasons. Among these reasons are low uptake of screening services owing to poor access to reliable information about cervical cancer, role of screening and treatment options. This paper examines the role of interpersonal communication channels in the uptake of cervical cancers screening services among women in Uasin Gishu County. The study was guided by Diffusion of Innovations (DOI) theory. It utilized mixed methods research design. The target population of the study was all women within the reproductive age of 18-65 years seeking maternal child health services and family planning (MCH-FP) at Moi Teaching and Referral Hospital in Uasin Gishu County, Kenya. The study used systematic random sampling method to obtain a sample of 308 from the population. Purposive sampling was used for the key informants, namely 4 health workers and 2 County officers from the Ministry of Health. Two focus group discussions (FGDs) were conducted among women with each group composed of 10 women. Data from the FGDs and key informant interviews were used to generate qualitative data. For quantitative data, the study utilized questionnaires for data collection. Quantitative data was analysed using descriptive statistics with the aid of SPSS, version 29. Qualitative data was analysed thematically. The study found that women rely on several channels of communication to access and disseminate cervical cancer information. The most common channels of communication used are friends, health care workers and media channels. From the study findings, it is also concluded that interpersonal communication channels play a key role in the uptake of cervical cancer screening. As such, it is recommended that the major stakeholders, namely the national and county governments, together with non-governmental organizations working in the health sector in Kenya, should make deliberate efforts to formulate policies to guide effective dissemination of cervical cancer messages for prevention, early detection and treatment of cervical cancer.

Reynolds Number and Drag Influences on Large Horizontal Axis Wind Turbine Design

Imane ECHJIJEM, Abdelouahed DJEBLI , Mfedel AKDI — Mon, 24 Jul 2023 00:00:00 +0000

The aerodynamic design of large wind turbines involves many factors, the most important of which are Reynolds number, drag and air density. This paper discusses the influence of these factors on the aerodynamic performance of a large horizontal axis wind turbine covering the drag term in the theoretical analysis. The drag term complicates the system of resolution for the axial and tangential induction factors. Previous work (Mingwei Ge) simplified this system by taking approximations for the axial and tangential induction factors. To make the analysis more general, the nonlinear equation system with the axial and tangential induction factors is solved. In the first step, the effect of Reynolds numberis studied for the DU00-W-350 blade profile though three values,,.Increasing the Reynolds number improves both the torque in the outer section of the blade and the power coefficient along the blade. In the next step, the effect of drag is examined using a comparison between the blade without drag and the blade with drag for the DU00-W-350 and NACA64618 profiles. It is found that a blade profile with lower drag gives higher torque and power coefficient than a blade profile with higher drag. In addition, the air density affects the torque and power coefficient of the NACA64618 blade profile. The simulation of this work is compared to previous work in the literature.

Minimizing Schedule Risk of Supply Chain

Thu, 22 Jun 2023 00:00:00 +0000

The supply chain management sector in Bangladesh faces so many challenges in minimizing schedule risk, this research paper targets to identify strategies that can help organizations to overcome this situation. The study includes a review of the literature, data collecting through surveys and interviews, and statistical data analysis. The findings demonstrate that companies in Bangladesh can reduce schedule risk by putting into practice strategies like enhancing stakeholder collaboration and communication, investing in technology to improve supply chain visibility, diversifying suppliers to lessen reliance on a single source, and creating backup plans for unforeseen disruptions. The study's conclusions offer useful advice for companies working in Bangladesh, particularly those in the industrial and retail industries, on how to manage their supply chains more effectively and lower the likelihood of schedule delays. The research adds to the sparse body of knowledge in academia about supply chain management in Bangladesh.

Detection of the Fake News Using Machine Learning Algorithms and Data Analysis Techniques

Mirza Niksic, Dzelila Mehanovic — Mon, 11 Sep 2023 00:00:00 +0000

Due to the rapid advancement of online social networks in recent years, the prevalence of fake news has increased significantly. Fake news is deliberately created to deceive users by imitating real news, making it challenging to identify early on. So, we need to explore the accompanying information to improve its disclosure such as the publisher. This study focuses on analyzing and investigating various traditional machine learning models to determine the most effective one. The goal is to develop a supervised machine learning algorithm that can classify news articles as either true or fake, utilizing tools like Python’s scikitlearn and NLP for text analysis. The proposed approach involves feature extraction and vectorization. To accomplish this, the
scikit-learn library in Python is utilized, which offers helpful tools like CountVectorizer and TfidfVectorizer. The experiment involved implementing well-known algorithms: Logistic regression, Neural networks and SVM, and comparing their performance to determine the most suitable one. Each of the three algorithms
performed well, but SVM demonstrated superior outcomes across nearly all categories.

The Impact of Digital Platform Satisfaction on Continued Utilization of Digital Health Information

Philomina Pomaah Ofori — Mon, 24 Jul 2023 00:00:00 +0000

Expectant mothers have increasingly turned to digital platforms as a supplementary source of information for managing their health during pregnancy. This article aims to investigate the impact of platform satisfaction on the continued usage of healthcare information and explore the role of trust in social media on digital platforms in shaping information usage. The data used in this study were from 580 expectant mothers in five hospitals in Ghana. The data were subjected to rigorous analysis using the SmartPLS statistical technique. The findings reveal that satisfaction with social media (SATSM) significantly influences social media health information continuance usage (SMHIC). Moreover, trust in social media (TRSM) exhibits a positive and significant effect on SMHIC. SATSM positively influences TRSM. Furthermore, the results suggest that trust in social media partially mediates the relationship between satisfaction and information continuance usage. These findings contribute to a deeper understanding of expectant mothers’ expectations of digital platforms and health. Digital health providers can use this to improve their activities on digital platforms.

Investigation of a Suspected Case of Adverse Events Post Immunization (AEFI) In the Health District of Commune VI, Bamako (Mali), June 2021

Sun, 20 Aug 2023 00:00:00 +0000

Introduction: A post-immunization adverse event (AEFI) is any adverse medical event following vaccination that is not necessarily causally related to vaccine use. Reporting and investigating AEFIs is useful to identify and avoid reactions related to vaccination error and to distinguish between an inconsistent concomitant event and a vaccine reaction or other vaccine-related event. Our objective was to investigate a case of AEFI in Commune VI of Bamako, June 2021.

Methods: This was a descriptive case study that took place in June 2021 following the notification of a case of severe AEFI with necrosis of the left arm in Commune 6 of Bamako.

Results: This is the case of Ms. YD, 44 years old, with no known history of having received a dose of Astra Zeneca's Covishild vaccine administered by the mobile vaccination team at a community health center in Bamako. The onset of symptomatology dates back to 2 hours after vaccination, marked by pain and redness at the injection site. The addition of swelling of the left arm on Day 1 post-vaccination followed by self-medication based on anti-inflammatory which leads to an accentuation of symptoms with the appearance of fluctenes and fistulization complicated by necrosis.

Conclusion: This investigation allowed us to report a case of severe AEFI whose most likely hypothesis would be ERYSIPELE in a lady whose course was marked by a total recovery with preservation of the sensory and motor function of the arm.