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.

     

Estimation of optimum design of structural systems via machine learning

Three different structural engineering designs were investigated to determine optimum design variables, and then to estimate design parameters and the main objective function of designs directly, speedily, and effectively. Two different optimization operations were carried out: One used the harmony search (HS) algorithm, combining different ranges of both HS parameters and iteration with population numbers. The other used an estimation application that was done via artificial neural networks (ANN) to find out the estimated values of parameters. To explore the estimation success of ANN models, different test cases were proposed for the three structural designs. Outcomes of the study suggest that ANN estimation for structures is an effective, successful, and speedy tool to forecast and determine the real optimum results for any design model.     

Children’s interactions with water in city centres: a case study from Sheffield,UK

Children’s experiences of outdoor environments have been studied now for more than 40 years yet no research has specifically focussed on children’s experiences of water play in constructed spaces of city centres. This article discusses the development of an observational mapping tool, called TOWEC, to record the interaction of children with water. It then reports findings and analysis from observations over a year-long period of 3,399 children interacting with water in the award winning public open space of the Peace Gardens in the centre of the City of Sheffield, UK. The findings reveal that children undertake both active and passive activities associated with the constructed water features and that these activities are influenced by gender, age and temperature, but not ethnicity. The water features were not designed for children to play in but the children realise the potential affordance that the water features provide.     

The optimum support design selection by using AHP method for the main haulage road in WLC Tuncbilek colliery

The engineers can frequently encounter with the situation to select the optimum option among the alternatives related with mining operations. The optimum choice can be selected by the experienced engineers taking into consideration their judgement and intuition. However, decision-making methods can offer to the engineers to support their optimum selection for a particular application in the scientific way. The Analytical Hierarchy Process (AHP) is one of the multi attribute decision-making (MADM) methods utilizing structured pair-wise comparisons. This paper presents an application of the AHP method to the selection of the optimum support design for the main transport road, which has been planned for deep coal seam panels of Western Lignite Corporation (WLC) Tuncbilek in Turkiye. The methodology considers eight main objectives, namely: four different displacement values for determined history locations, factor of safety (FOS), cost, labour and applicability factor for the selection of support design. The displacements and stress values were obtained by using the finite difference program FLAC^3D as the numerical studies have been widely used by the engineers examining the response of any opening in underground, in advance. After carrying out several numerical models for different support design, the AHP method was incorporated to evaluate these support designs according to the pre-determined criteria. The result of this study shows that such AHP application can assist the engineers to effectively evaluate the support system alternatives for an underground mine.     

Generalized pointwise bias error bounds for response surface approximations

This paper proposes a generalized pointwise bias error bounds estimation method for polynomial‐based response surface approximations when bias errors are substantial. A relaxation parameter is introduced to account for inconsistencies between the data and the assumed true model. The method is demonstrated with a polynomial example where the model is a quadratic polynomial while the true function is assumed to be cubic polynomial. The effect of relaxation parameter is studied. It is demonstrated that when bias errors dominate, the bias error bounds characterize the actual error field better than the standard error. The bias error bound estimates also help to identify regions in the design space where the accuracy of the response surface approximations is inadequate. It is demonstrated that this information can be utilized for adaptive sampling in order to improve accuracy in such regions. Copyright © 2005 John Wiley & Sons, Ltd.     

Experimental investigation of performance and emissions of the SICAI-hybrid engine systems

The use of hybrid electrical engines can provide more efficiency by reducing fuel consumption and emissions. In the research, the experimental studies on the created hybrid electric engine were presented. The hybrid engine combines an electric motor with the internal combustion engine (ICE) which is operated under spark assisted controlled auto-ignition (SICAI) combustion mode with the alternative fuels consisting of different ratios of methane–hydrogen blends. In order to establish the hybrid engine, firstly, efficiency graphs of the electrical motor were obtained experimentally. The battery charge status was also checked. The operating range of the SICAI engine in the hybrid system was identified considering performance and efficiency parameters. Based on these parameters, a hybrid algorithm was established to control the operating of the created hybrid engine system. Thus, the experimental studies were carried out for 100% methane, 90% methane-10% hydrogen, 80% methane-20% hydrogen and, 70% methane-30% hydrogen blends (by volume) at wide opening throttle (WOT) and, 50% WOT positions. Consequently, the results were discussed in terms of efficiency and emissions.     

Optimization of seismic isolation systems via harmony search

In this article, the optimization of isolation system parameters via the harmony search (HS) optimization method is proposed for seismically isolated buildings subjected to both near-fault and far-fault earthquakes. To obtain optimum values of isolation system parameters, an optimization program was developed in Matlab/Simulink employing the HS algorithm. The objective was to obtain a set of isolation system parameters within a defined range that minimizes the acceleration response of a seismically isolated structure subjected to various earthquakes without exceeding a peak isolation system displacement limit. Several cases were investigated for different isolation system damping ratios and peak displacement limitations of seismic isolation devices. Time history analyses were repeated for the neighbouring parameters of optimum values and the results proved that the parameters determined via HS were true optima. The performance of the optimum isolation system was tested under a second set of earthquakes that was different from the first set used in the optimization process. The proposed optimization approach is applicable to linear isolation systems. Isolation systems composed of isolation elements that are inherently nonlinear are the subject of a future study. Investigation of the optimum isolation system parameters has been considered in parametric studies. However, obtaining the best performance of a seismic isolation system requires a true optimization by taking the possibility of both near-fault and far-fault earthquakes into account. HS optimization is proposed here as a viable solution to this problem.     

An augmented reality interface to contextual information

In this paper, we report on a prototype augmented reality (AR) platform for accessing abstract information in real-world pervasive computing environments. Using this platform, objects, people, and the environment serve as contextual channels to more information. The user??s interest with respect to the environment is inferred from eye movement patterns, speech, and other implicit feedback signals, and these data are used for information filtering. The results of proactive context-sensitive information retrieval are augmented onto the view of a handheld or head-mounted display or uttered as synthetic speech. The augmented information becomes part of the user??s context, and if the user shows interest in the AR content, the system detects this and provides progressively more information. In this paper, we describe the first use of the platform to develop a pilot application, Virtual Laboratory Guide, and early evaluation results of this application.     

Service Life Assessment of Existing Highway Bridges with No Planned Regular Inspections

Safety of a highway infrastructure system depends very much on the proper maintenance of bridges. The level of required maintenance is, typically, determined through a series of regular field inspections with the guidance of safety–economy trade-off. In Turkey, bridge maintenance, repair, and rehabilitation are currently performed on an as-needed basis. Time-dependent reliability analysis cannot be utilized for Turkish bridges for the time being since the majority of the bridges are either not regularly inspected or not inspected at all. The purpose of this paper is to propose a simple method to assess the remaining service life of a bridge by defining a relationship between its current condition rating and its age by evaluating a set of bridges at different ages. In a case study, 28 bridges were inspected for the first time to assess the average life expectancy. The average life of a bridge was predicted to be 80?years, and for this set of bridges, the main body components were found to deteriorate more than earth retaining and serviceability components.