R2-D2: ColoR-inspired Convolutional NeuRal Network (CNN)-based AndroiD Malware Detections

The influence of Deep Learning on image identification and natural language processing has attracted enormous attention globally. The convolution neural network that can learn without prior extraction of features fits well in response to the rapid iteration of Android malware. The traditional solution for detecting Android malware requires continuous learning through pre-extracted features to maintain high performance of identifying the malware. In order to reduce the manpower of feature engineering prior to the condition of not to extract pre-selected features, we have developed a coloR-inspired convolutional neuRal networks (CNN)-based AndroiD malware Detection (R2-D2) system. The system can convert the bytecode of classes.dex from Android archive file to rgb color code and store it as a color image with fixed size. The color image is input to the convolutional neural network for automatic feature extraction and training. The data was collected from Jan. 2017 to Aug 2017. During the period of time, we have collected approximately 2 million of benign and malicious Android apps for our experiments with the help from our research partner Leopard Mobile Inc. Our experiment results demonstrate that the proposed system has accurate security analysis on contracts. Furthermore, we keep our research results and experiment materials on http://R2D2.TWMAN.ORG.Comment: Verison 2018/11/15, IEEE BigData 2018, Seattle, WA, USA, Dec 10-13, 2018. (Accepted

Data-Driven and Deep Learning Methodology for Deceptive Advertising and Phone Scams Detection

The advance of smartphones and cellular networks boosts the need of mobile advertising and targeted marketing. However, it also triggers the unseen security threats. We found that the phone scams with fake calling numbers of very short lifetime are increasingly popular and have been used to trick the users. The harm is worldwide. On the other hand, deceptive advertising (deceptive ads), the fake ads that tricks users to install unnecessary apps via either alluring or daunting texts and pictures, is an emerging threat that seriously harms the reputation of the advertiser. To counter against these two new threats, the conventional blacklist (or whitelist) approach and the machine learning approach with predefined features have been proven useless. Nevertheless, due to the success of deep learning in developing the highly intelligent program, our system can efficiently and effectively detect phone scams and deceptive ads by taking advantage of our unified framework on deep neural network (DNN) and convolutional neural network (CNN). The proposed system has been deployed for operational use and the experimental results proved the effectiveness of our proposed system. Furthermore, we keep our research results and release experiment material on http://DeceptiveAds.TWMAN.ORG and http://PhoneScams.TWMAN.ORG if there is any update.Comment: 6 pages, TAAI 2017 versio

THE EFFECT OF EIGHT WEEKS TRAINING WITH EXTRA WEIGHT ON STANDING LONG JUMP PERFORMANCE

The purpose of this study was to investigate the effect of eight weeks training with extra weight in the hands on standing long jump performance. Fifteen junior high school male students participated in the study. Vicon motion system (10 cameras, 200Hz) and two Kistler force plates (1000 Hz) were used to collect the kinematics and kinetic data of pretraining and post-training tests. The results found the jumping distance increased 18 % after extra weight training. The horizontal velocity of center of mass (CM) at takeoff, flight distance, landing distance, the CM difference at takeoff, the horizontal positive impulse and the peak horizontal ground reaction force were all significantly enhanced. It was concluded that eight weeks of extra weight in the hands jump training increased the high school male standing long jump performance

‘Drop, Cover and Hold On’ or ‘Triangle of Life’ Attributes of Information Sources Influencing Earthquake Protective Actions

A well-known fact is that an earthquake or earth shaking does not cause injuries and deaths. Rather, buildings and infrastructure systems collapsing on people do. Hence, reputable government organizations from countries prone to high earthquake risks are heavily invested in advising their populations on immediate lifesaving protective actions (PAs). One such action is the ‘Drop, Cover and Hold on’ strategy proven to have saved countless lives. Unfortunately, in recent years another action known as the ‘Triangle of Life’ has been trolled through internet sites and hearsay. It is believed that adopting such an unsubstantiated erroneous action is likely to put people at greater risk during an earthquake. Thus, there is a need to extend studies to understand factors that influence people’s decisions to take certain PAs over another for earthquakes. This research does that through an empirical study of 647 residents from Mianyang City in the Sichuan province of China. The results indicate that if a PA is easy to understand, mentioned often by multiple sources and easy to access, then people will adopt it. But a striking finding is that people are also likely to be influenced by wrong information, depending on who is providing such information and through which medium (e.g. social media). These findings suggest that the Chinese government needs to provide gate keepers who are dedicated, trained personnel who can monitor misinformation on various Internet sites and address them. In parallel they can provide regular, up to date public advisories on immediate PA through multiple legitimate government, private and non-profit sector sources and channels

High expression FUT1 and B3GALT5 is an independent predictor of postoperative recurrence and survival in hepatocellular carcinoma.

Cancer may arise from dedifferentiation of mature cells or maturation-arrested stem cells. Previously we reported that definitive endoderm from which liver was derived, expressed Globo H, SSEA-3 and SSEA-4. In this study, we examined the expression of their biosynthetic enzymes, FUT1, FUT2, B3GALT5 and ST3GAL2, in 135 hepatocellular carcinoma (HCC) tissues by qRT-PCR. High expression of either FUT1 or B3GALT5 was significantly associated with advanced stages and poor outcome. Kaplan Meier survival analysis showed significantly shorter relapse-free survival (RFS) for those with high expression of either FUT1 or B3GALT5 (P = 0.024 and 0.001, respectively) and shorter overall survival (OS) for those with high expression of B3GALT5 (P = 0.017). Combination of FUT1 and B3GALT5 revealed that high expression of both genes had poorer RFS and OS than the others (P < 0.001). Moreover, multivariable Cox regression analysis identified the combination of B3GALT5 and FUT1 as an independent predictor for RFS (HR: 2.370, 95% CI: 1.505-3.731, P < 0.001) and OS (HR: 2.153, 95% CI: 1.188-3.902, P = 0.012) in HCC. In addition, the presence of Globo H, SSEA-3 and SSEA-4 in some HCC tissues and their absence in normal liver was established by immunohistochemistry staining and mass spectrometric analysis

Local Residents’ Risk Perceptions in Response to Shale Gas Exploitation: Evidence from China

In 2014, China became the world’s third country to accomplish shale gas commercial development, following the United States and Canada. China still however lacks a comprehensive analysis of its public’s concerns about potential environmental risks of shale gas exploration, particularly those of local residents near extraction sites. This paper specifically aims to explore risks perceived as associated with shale gas development in the Changning-Weiyuan area of Sichuan Basin, by conducting a face-to-face household survey with 730 participants interviewed. Some 86% of respondents reported their belief that shale gas exploitation causes more than three types of negative impacts, the most commonly perceived being noise, underground water contamination and geological disruption. Associated variables that were statistically significant predictors of risk perception include demographic characteristics (age, gender, education), environmental awareness level, landslide experience, awareness of past shale gas accidents, information sources, general knowledge about shale gas, and perspectives on whether negative impacts can be observed and controlled, along with trust in the central government and the petroleum company. Our findings implications are discussed, with the goal of informing both central and local authorities’ policy development in protecting local residents from risks of shale gas exploitation and better communicating risks to residents

i-Genome: A database to summarize oligonucleotide data in genomes

BACKGROUND: Information on the occurrence of sequence features in genomes is crucial to comparative genomics, evolutionary analysis, the analyses of regulatory sequences and the quantitative evaluation of sequences. Computing the frequencies and the occurrences of a pattern in complete genomes is time-consuming. RESULTS: The proposed database provides information about sequence features generated by exhaustively computing the sequences of the complete genome. The repetitive elements in the eukaryotic genomes, such as LINEs, SINEs, Alu and LTR, are obtained from Repbase. The database supports various complete genomes including human, yeast, worm, and 128 microbial genomes. CONCLUSIONS: This investigation presents and implements an efficiently computational approach to accumulate the occurrences of the oligonucleotides or patterns in complete genomes. A database is established to maintain the information of the sequence features, including the distributions of oligonucleotide, the gene distribution, the distribution of repetitive elements in genomes and the occurrences of the oligonucleotides. The database can provide more effective and efficient way to access the repetitive features in genomes