Malicious code detection in android: the role of sequence characteristics and disassembling methods

The acceptance and widespread use of the Android operating system drew the attention of both legitimate developers and malware authors, which resulted in a significant number of benign and malicious applications available on various online markets. Since the signature-based methods fall short for detecting malicious software effectively considering the vast number of applications, machine learning techniques in this field have also become widespread. In this context, stating the acquired accuracy values in the contingency tables in malware detection studies has become a popular and efficient method and enabled researchers to evaluate their methodologies comparatively. In this study, we wanted to investigate and emphasize the factors that may affect the accuracy values of the models managed by researchers, particularly the disassembly method and the input data characteristics. Firstly, we developed a model that tackles the malware detection problem from a Natural Language Processing (NLP) perspective using Long Short-Term Memory (LSTM). Then, we experimented with different base units (instruction, basic block, method, and class) and representations of source code obtained from three commonly used disassembling tools (JEB, IDA, and Apktool) and examined the results. Our findings exhibit that the disassembly method and different input representations affect the model results. More specifically, the datasets collected by the Apktool achieved better results compared to the other two disassemblers.

     

The Effect of the Binding Agents on the Friability and Compressibility of Granules

The friability of granule is one of the most important parameters which effects the properties of compressed tablet and several factors play an important role. In this study the effects of the molecular weights and types of the binding agents on friabilityand conpressibility of granules were investigated. Possesing various molecular weigths of Polyvinylpyrrolidone and Methylcellulose were used for the preparation of granules and their physico-pharmaceutic properties were evaluated.     

Reducing the spatial distance between printed and online information sources by means of mobile technology enhances learning: Using 2D barcodes

Online information sources, such as pictures and animations on web pages are frequently used for complementing printed course material in educational contexts. The concurrent use of online and printed information sources by students, however, requires going back and forth between physically separated course material, such as a course book and a computer screen, thus leading to suboptimal learning outcomes. Compatible with the principles identified by the recent theoretical frameworks for multimedia learning, mobile technology provides learners with the opportunity to bring online and printed course material close together. Mobile phones make online information available within a small desktop space, in close proximity to printed course material. The challenges that are relevant to text input methods can be overcome by the 2D barcode technology. This study investigates the use of camera-equipped mobile phone and 2D barcode technology as an alternative to the use of computer screen for complementing printed course material. The results of the experimental investigation suggest that, by facilitating the access to online information sources by 2D barcode tags on course books, mobile phones have the potential to enhance learning.