Malware clustering using suffix trees

Clustering is an important problem in malware research, as the number of malicious samples that appear every day makes manual analysis impractical. Although these samples belong to a limited number of malware families, it is difficult to categorize them automatically as obfuscation is involved. By extracting relevant features we can apply clustering algorithms, then only analyze a couple of representatives from each cluster. However, classic clustering algorithms that compute the similarity between each pair of samples are slow when a large collection is involved. In this paper, the features will be strings of operation codes extracted from the binary code of each sample. With a modified suffix tree data structure we can find long enough substrings that correspond to portions of a program’s code. These substrings must be filtered against a database of known substrings so that common library code will be ignored. The items that have common substrings above a certain threshold will be grouped into the same cluster. Our algorithm was tested with data extracted from real-world malware and constructed quality clusters.     

Formulation studies for mirtazapine orally disintegrating tablets

Abstract

Objective: Orally disintegrating tablets (ODTs) recently have gained much attention to fulfill the needs for pediatric, geriatric, and psychiatric patients with dysphagia. Aim of this study was to develop new ODT formulations containing mirtazapine, an antidepressant drug molecule having bitter taste, by using simple and inexpensive preparation methods such as coacervation, direct compression and to compare their characteristics with those of reference product (Remereon SolTab).

Materials and methods: Coacervation method was chosen for taste masking of mirtazapine. In vitro characterization studies such as diameter and thickness, weight variation, tablet hardness, tablet friability and disintegration time were performed on tablet formulations. Wetting time and in vitro dissolution tests of developed ODTs also studied using 900?mL 0.1?N HCl medium, 900?mL pH 6.8 phosphate buffer or 900?mL pH 4.5 acetate buffer at 37?±?0.2?°C as dissolution medium.

Results: Ratio of Eudragit® E-100 was chosen as 6% (w/w) since the dissolution profile of A1 (6% Eudragit® E-100) was found closer to the reference product than A2 (4% Eudragit® E-100) and A3 (8% Eudragit® E-100). Group D, E and F formulations were presented better results in terms of disintegration time. Dissolution results indicated that Group E and F formulations showed optimum properties in all three dissolution media.

Discussion: Formulations D1, D4, D5, E3, E4, F1 and F5 found suitable as ODT formulations due to their favorable disintegration times and dissolution profiles.

Conclusion: Developed mirtazapine ODTs were found promising in terms of showing the similar characteristics to the original formulation.     

基于直方图熵的体数据分类算法研究

体数据的分类用于确定体素的可见性,在三维体绘制中起着重要的作用。提出一种基于熵的体数据分类算法。首先根据累计直方图将体数据的直方图进行分段,然后根据熵判别式在每个分段中计算一个阈值作为阻光度传递函数的分段点,再根据阻光度传递函数计算出体素的阻光度值,完成体数据的分类。以工业CT体数据为对象进行实验,其结果表明,所提出的算法较好地实现了体数据的分类,体绘制结果清晰,且能够实现试件的模拟拆卸。     

多用户MIMO系统低复杂度收发联合波束成形方案

基于多用户多输入多输出(MIMO)有限反馈系统提出了一种收发联合波束成形方法。该方法在发送端采用每个用户酉速率控制(PU2RC)波束成形技术,在接收端采用基于信干噪比(SINR)最大化的天线合并算法。天线合并算法利用用户SINR的广义Rayleigh熵特性寻找最佳的天线合并矢量。仿真结果表明,该方法能充分利用信道信息,不仅改善了传统PU2RC系统的和速率性能,相对于已有的迫零(ZF)联合波束成形方法,对信道状态信息的量化误差的敏感性更低,用户选择算法的复杂度更低,且低速率反馈条件下和速率性能更优。     

Multilevel optimization algorithms in computer aided production control in process industry

The use of optimization techniques in production control is discussed. Two optimization problems in relation to typical process industry complexes are formulated. A modified version of Tamura's algorithm is reviewed. The promising performance of the computerised algorithms is illustrated by numerical results. DISPATCHER, a practical operative decision support system, is described.     

A new deep convolutional neural network model for classifying breast cancer histopathological images and the hyperparameter optimisation of the proposed model

The Journal of Supercomputing - Deep learning algorithms have yielded remarkable results in medical diagnosis and image analysis, besides their contribution to improvements in a number of fields...     

Functional Diversity,Absorptive Capability and Product Success: The Moderating Role of Project Complexity in New Product Development Teams

Absorptive capability appears to be an appealing concept in the technology and innovation management literature. Though absorptive capability attracts researchers from a variety of disciplines, team‐level empirical research on it is scant. In this study, we operationalized team absorptive capability as a multidimensional construct involving knowledge acquisition, assimilation and exploitation. This study also explores the moderating effect of project complexity between team absorptive capability and new product success. In studying the data from 239 new product development projects using partial least squares structural equation modelling, we found that team functional diversity is a significant determinant of team absorptive capability. Moreover, regarding the relationships between team absorptive capability and new product success, we uncovered that (i) new product success is dependent on the ability to understand the acquired knowledge, and (ii) the teams appear to be more cautious in putting the assimilated knowledge into practice to the extent that project complexity increases.