Echogenic bubbles: An new avenue for cancer therapy

The development of micro and nanobubbles as theranostics is been an emerging trend in the 21st century. Ultrasound molecular imaging is a real-time non-invasive, cost-effective, promising non-viral tool, which is been widely used in the recent times. These micro and nanobubbles are marked as ultrasound agents for both diagnosis and targeting therapeutic agents. These are designed in order to obtain efficient drug delivery. Micro and nanobubbles are very much used for targeting drug and achieving site specific release. These are stable and have longer residence time in systemic circulation, finally shows efficient and promising drug delivery [1]. These echogenic bubbles are helpful for disease diagnosis and therapy more prominently when compared with other novel drug delivery systems. This review describes about functioning of micro and nanobubbles along with mechanism, preparation and studies which describes the works on micro and nanobubbles.

An intelligent web-based point of sales management system for small and medium scale businesses

The increase in population globally has caused organisations and businesses to move from square rooms, table-top and containers into supermarkets, malls and more. With this expansion in businesses, the traditional pen and paperwork system for keeping records are becoming more difficult for salespersons and shop owners everywhere. However, the introduction of the point-of-sales management system and advancement in technologies have elevated the challenges facing shop owners in managing their daily sales and balance sheet. Despite the overwhelming number of POS systems available, wholesalers and retailers' in low-income counties such as Ghana see some challenges with the existing POS, cost-effectiveness, and user-friendliness. Thus, the cultural difference makes it difficult for easy adaptation of shop owners to off-the-shell POS system. Hence, the current study sought to design and develop a user-friendly, low-cost intelligent web-based point of sales management system for small and medium scale business in the Bono region of Ghana, based on a user-centred approach. Using a waterfall model, we implement a POS system based on XAMP server and MySQL database as backend and PHP for server-side scripting. At the same time, HTML and CSS were used for front end development. Our experimental setup with ten students shows that the proposed system is easy to use and robust. Thus, it has a user-friendly interface for even novice to learn it with ease.

Extraction of Metadata from Images

Metadata is defined as the information providing data about one or more faces of the data. It is used to abridge basic indication about data which can make pursuing and working with specific data easier. The idea of metadata is often prolonged to involve words or phrases that stand for objects or “objects” in the world, leading to the notion of unit extraction. In this paper, I am proposing extracting the metadata of the files user inputs to the system, this can be achieved using Flask as the web platform and Python programming language, our goal is to make a free and lightweight metadata extractor which is more efficient and user friendly.

A proposed conceptual framework based on machine learning techniques and IoT services for smart farming in developing countries

Farming in low and medium countries such as Ghana is seen as one of the pillars that support the economy. However, most smallholder farms within these countries face several challenges such as irregular rain pattern, access to adequate information, inadequate agricultural extension agents, bush fires destroying crops pest and diseases, and more, which affect low productive and food security. These challenges encountered by small scale farmers (SSF) in these counties make it impossible to achieve the millennium development goals (MDGs) of diminishing hunger, and food security is rooted in increasing agricultural productivity, especially from the crop farming. In a way to overcome these challenges facing SSF, this paper proposed a theoretical Framework for Smart Farming based on IoT and Machine Learning Techniques. It is anticipated that the successful implementation of the proposed framework will increase productivity in crop farming, hence help achieve the MDGs.