Detecting Android Malware and Classifying Its Families in Large-scale Datasets

To relieve the burden of security analysts, Android malware detection and its family classification need to be automated. There are many previous works focusing on using machine (or deep) learning technology to tackle these two important issues, but as the number of mobile applications has increased in recent years, developing a scalable and precise solution is a new challenge that needs to be addressed in the security field. Accordingly, in this article, we propose a novel approach that not only enhances the performance of both Android malware and its family classification, but also reduces the running time of the analysis process. Using large-scale datasets obtained from different sources, we demonstrate that our method is able to output a high F-measure of 99.71% with a low FPR of 0.37%. Meanwhile, the computation time for processing a 300K dataset is reduced to nearly 3.3 hours. In addition, in classification evaluation, we demonstrate that the F-measure, precision, and recall are 97.5%, 96.55%, 98.64%, respectively, when classifying 28 malware families. Finally, we compare our method with previous studies in both detection and classification evaluation. We observe that our method produces better performance in terms of its effectiveness and efficiency.

Analysis about Planning and Modification of the Upper and Lower Structures of the 38 Floor Apartment SkyHouse Project with Equivalent Static Analysis

The modeled building structure is a regular building, with the number of levels being varied. The structural model is divided into 38-level portals. This research uses the help of the SAP2000 v21 program to facilitate the earthquake analysis process. The results of the study that will be compared are displacements between levels and base shear that occur due to earthquake forces. The results of the analysis have shown that static analysis produces greater results for the structural models compared to dynamic analysis. The difference in displacement between levels produced by the two methods in the three structural models is still included in the displacement limits between levels of permission required in SNI 1726-2012, so that the three models can still be analyzed by static analysis and dynamic analysis. Because the results of displacement and base shear in static analysis are greater than dynamic analysis, static analysis is safer if used for earthquake force loading in general structural calculations. Although in earthquake analysis, dynamic analysis is a more accurate analysis because the analysis process is closer to the actual situation.

Research on Dynamic Assessment Method of Earthquake Scene Rescue Performance Based on AHP and Cloud Model

In view of the ambiguity and randomness of the assessment of earthquake scene rescue performance, this paper proposes an integrated assessment method considering quantitative and qualitative influencing factors from three levels: search, rescue and medical treatment. Firstly, this study constructs an assessment index system of rescue performance at the earthquake scene based on the International Search and Rescue Advisory Group (INSARAG) guidelines set by International Search and Response. Secondly, the subjective weights and objective weights of each index were calculated using the hierarchical analysis process (AHP) and cloud model, respectively. The comprehensive weights were calculated using weighted analysis, and the performance assessment results were visually expressed by cloud model images. Finally, the study was applied to an earthquake rescue case with an initial assessment of 4.0065, and its performance was improved by 4.36% when the rescue process was optimized. The assessment results show that earthquake rescue performance can be estimated, and the rationality and effectiveness of the method was validated.

Characterization of Groundwater Zones and Salinity Assessment in Aquifers of the Campo District, South Cameroon Using the GIS, AHP and PCA Approach.

In the Campo region, groundwater is critical for human consumption and social activity. Groundwater potential is influenced by a region's geological, geophysical, and hydrogeological factors. The major goals of this research are to determine which regions are ideal for productive groundwater drilling and to assess the source of salinity in the study area's coastal aquifers. The groundwater potential map was created using Geographic Information Systems (GIS) and the Hierarchical Analysis Process (AHP). The process of groundwater mineralization was studied using principal component analysis (PCA). Six variables were taken into account, and weights were assigned to them based on their impact on groundwater recharge. In a GIS environment, spatial integration and a combination of theme layers were conducted. Campo's groundwater potential map was divided into four zones: low 14.4% (389.6 km²), moderate 53.3% (1484.5 km²), high 28.3% (783.3 km²), and extremely high 4.1% (110.9 km²). The results of the PCA reveal a mechanism of water-rock interaction, as a result of geological alteration and a salinization process caused by the intrusion of seawater and human activity The source of salinity in groundwater is manmade (agricultural and residential activities) rather than seawater intrusion. Seawater infiltration is not greatly aided by the low lineament density found near the beaches.

Grey Relational Analysis (GRA) as an Effective Method of Research into Social Preferences in Urban Space Planning

The appearance of urban space is most often determined by planners, urbanists, and officials who fail to consider social preferences in the planning process. According to recent scientific research, spatial design should take into account people’s preferences with regard to its shape, as it is they who are the target audience. Moreover, legal regulations in many countries require the public’s inclusion into the space planning process. This paper outlines the legal status of the issue of social participation in spatial planning and provides an overview of the methods and techniques applied in the research into preferences. The aim of the article is to determine the strength of the relationship between the features adopted for the study using the grey system theory and to investigate the model’s behaviour for varied input data. It also presents the results of a study into the effect of geospatial features on the perception of the sense of security within urban space. The features were extracted using a heuristic method for solving research problems (i.e., brainstorming) and the survey was conducted by the point-scoring method. The survey results were processed by the grey system method according to the grey system theory (GST) of the grey relational analysis (GRA) type to yield a sequence of the strength of dependence between the analysed features. The study was conducted five times, with the order of entering the survey results being changed. The conducted analyses indicated that a change in the order of data from particular surveys applied for calculations resulted in the order of the epsilon coefficients in the significance sequences being changed. The analysis process was modified in order to obtain a stable significance sequence irrespective of the order of entering survey results in the analysis process. The analysis results in the form of a geospatial feature significance sequence provide information as to which of them have the greatest impact on the phenomenon under consideration. The research method can be applied to solve practical problems related to social participation.

Estimating herbaceous aboveground biomass in Sahelian rangelands using structure from motion data collected on the ground and by UAV

1.Herbaceous aboveground biomass (HAB) is a key indicator of grassland vegetation and indirect estimation tools, such as remote sensing imagery, increase the potential for covering larger areas in a timely and cost-efficient way. Structure from motion (SfM) is an image analysis process that can create a 3D model from a set of images. 2: Computed from UAV and ground camera measurements, the SfM potential to estimate the herbaceous aboveground biomass in Sahelian rangelands was tested in this study. Both UAV and ground camera recordings were used at three different scales: temporal, landscape and national (across Senegal). All images were processed using PIX4D software and were used to extract vegetation indices and heights. 3: A random forest algorithm was used to estimate the HAB and the average estimation errors were around 150 g.m-² for fresh mass (20% relative error) and 60 g.m-² for dry mass (around 25% error). A comparison between different datasets revealed that the estimates based on camera data were slightly more accurate than those from UAV data. 4:It was also found that combining datasets across scales for the same type of tool (UAV or camera) could be a useful option for monitoring HAB in Sahelian rangelands or in other grassy ecosystem.

A Simple Route for the Preparation of Gold Nanofilms and Their Application in SERS Detection of Pyrene in Water

Design and preparation of various rational gold nanostructures has been recognized as a promising solution for the surface-enhanced Raman scattering (SERS) signal amplification. Here, a simple fabrication method was reported for the synthesis of highly sensitive gold nanofilms for SERS detection through covering ginger-liked gold nanoparticles on the stainless steel sheet. The prepared gold nanofilms were then tested by a dip-SPME-SERS method for detecting pyrene. The limit of detection for pyrene standard solution was 0.1ppb, while the limit of detection for pyrene in tap water and lake water without any pretreatment was 5 ppb, respectively. The whole analysis process takes less than 15 minutes. Our method may be a potential alternative way to the chromatography method. The fabricated gold nanfilms are expected to be used for the rapid and sensitive detection of other pollutants such as organic pesticides and polycyclic aromatic hydrocarbon.

Understanding the Concept of Data Warehousing and Challenges in Its Implementation

The aim of this paper is to understand the concept of Data ware housing and how it is implemented. It is related to the data analysis of the data in an organisation. It facilitates and makes the analysis process easy for the workers of the organisation. The paper will also explain two approaches that are followed in data ware housing. The process of implementation of data ware house will also discussed further in this paper. There are certain challenges to create data ware house.

Types of smart systems and their application in power grids

With the development of modern technologies, opportunities for an exchange of the increasing amount of information at ever higher speeds are created. The use of smart systems in electric power engineering creates conditions for improving the systems for monitoring, archiving, analysis and management. It is necessary to collect the basic information about the emergency modes automatically for analysis of the operation of the equipment and the parameters of the regimes in the power grids. The main questions to be decided are: what type of information is needed, how to use this information and at what are the different access levels, what should be the systems - local or global, how to exchange data. Smart systems for power grids and switchgears have been developed on a modular basis by almost all global manufacturers, as well as by many companies on individual assignments. The publication discusses the existing types of smart systems and the data they process. Suggestions have been made for the volume and structure of data that are needed for the analysis process.

Reliability Engineering Techniques Applied to the Human Failure Analysis Process

Human reliability and human error are factors that are present in all areas: industrial, economic, social, etc. All these areas require to a greater or lesser extent a physical and mental effort to satisfy their own needs, those of others, or established requirements that, depending on the circumstances and the nature of the person, can lead to errors. Certainly, it is not possible to find a single human reliability method that can meet all the expectations and technical demands related to the analysis of human errors. However, it is important to note that the orientation of all human reliability methods is focused on the study and analysis of the risk factor (frequency by consequences). In other words, as can be observed throughout this chapter, all human reliability methodologies seek to help us reduce the uncertainty in the process of evaluating the frequencies of unforeseen events (human errors) and the consequences that such human errors can bring to safety, the environment, and the operations within the framework of an industrial production process.