Identification of rockfall source areas using the seed cell concept and bivariate susceptibility modelling

The objective of this research was to prepare a rockfall susceptibility map. Explorations were conducted in the Dubra?ina River basin (Croatia). The input data included a geological map, an orthophoto and a 1-m digital terrain model (DTM). After a talus inventory was prepared, the seed cell concept was applied to define the rockfall source areas. The contributing factors (predictors) of rockfalls were evaluated by the chi-squared test. The analysis confirmed the following predictors: CORINE land cover, lithology, slope, aspect, distance from a spring, distance from a road, distance from a fault, distance from a stream, and distance from the rock-soil geological boundary. A matrix pairwise comparison of the predictor ratings was used to define the most significant contributing factors. The predictors that affected the susceptibility map in the share of 86.3% were the slope (61.6%), lithology (13.4%), CORINE land cover (6.2%), and distance from the rock-soil geological boundary (5.1%). Two susceptibility maps were prepared: one using all nine contributing factors and another using the four most significant factors. The analysis showed that both maps were good, with the same areas under the receiver operating characteristic (ROC) curves. The map prepared with only four contributing factors can be considered a better map due to its more precise spatial definition of critical areas. It can be concluded that geological map, 1-m DTM and orthophoto provide enough data to prepare reliable rockfall susceptibility map. The application of the bivariate statistical zonation method called the “frequency ratio method” was proven to be successful. This research demonstrates that the application of the seed cell concept can be useful to speed up the process of rockfall source area detections in large research regions.

     

Development of protease nanobiocatalysts and their application in hydrolysis of sunflower meal protein isolate

In this study, the suitability of fumed silica nanoparticles (FNS) and its derivatives (amino-modified FNS (AFNS), cyanuric chloride-activated AFNS (CCAFNS) and epoxy-modified FNS (GFNS)), for covalent immobilisation of two commercial protease preparations Alcalase^® and Flavourzyme^® was investigated. The highest hydrolytic activities of immobilised preparations were 25 IU g⁻¹ support (Alcalase-GFNS) and 2.95 IU g⁻¹ support (Flavourzyme-CCAFNS). Furthermore, the immobilised preparations showed 43% and 20% of initial specific activities of commercial protease preparations, respectively. Flavourzyme-CCAFNS also exhibited the highest exopeptidase activity of 22.83 L-pNAU g⁻¹ support. Finally, these two nanobiocatalysts were successfully applied for hydrolysis of sunflower meal protein isolate (SMPI), providing two times higher hydrolysis yields in comparison to free enzymes, justifying the applied immobilisation process. Namely, the highest hydrolysis yield (30%) was gained by the sequential hydrolysis with Alcalase-GFNS and Flavourzyme-CCAFNS, which resulted in the formation of small hydrophobic and hydrophilic peptides, ≤5 kDa, confirmed by HPLC analysis and electrophoretic separation.     

A Proposal for Addressing Security Issues Related to Dynamic Code Loading on Android Platform

One of the constant challenges faced by the Android community, when it comes to the safety of the end users, is the ability of applications to load code dynamically. This mechanism may be used for both legitimate and malicious purposes. A particular problem is the fact that remote code is not analyzed during the verification process because it doesn’t have to be present in the application package at the publishing time. Previous research has shown that using this concept in an insecure way can cause serious consequences for the user and his device. Solving this problem has proved to be a big challenge that many have tried to address in different ways. This paper deals with the problem of dynamic code loading on Android platform. For the purpose of this paper, an application that demonstrates the abuse of the dynamic code loading concept has been developed and published in the Google Play Store. Also, a proposal of the modified Android ecosystem that should address this problem and improve the security of the whole platform is given.     

Hungarian algorithm for subcarrier assignment problem using GPU and CUDA

General purpose graphics processing units (GPGPUs) have gained much popularity in scientific computing to speedup computational intensive workloads. Resource allocation in terms of power and subcarriers assignment, in current wireless standards, is one of the challenging problems due to its high computational complexity requirement. The Hungarian algorithm (HA), which has been extensively applied to linear assignment problems (LAPs), has been seen to provide encouraging result in resource allocation for wireless communication systems. This paper presents a compute unified device architecture (CUDA) implementation of the HA on graphics processing unit (GPU) for this problem. HA has been implemented on a parallel architecture to solve the subcarrier assignment problem and maximize spectral efficiency. The proposed implementation is achieved by using the “Kuhn‐Munkres” algorithm with effective modifications, in order to fully exploit the capabilities of modern GPU devices. A cost matrix for maximum assignment has been defined leading to a low complexity matrix compression along with highly optimized CUDA reduction and parallel alternating path search process. All these optimizations lead to an efficient implementation with superior performance when compared with existing parallel implementations.     

Analyzing XACML policies using answer set programming

International Journal of Information Security - With the tremendous growth of Web applications and services, eXtensible Access Control Markup Language (XACML) has been broadly adopted to specify...     

New access modes of parallel memory subsystem for sub-pixel motion estimation

Accessing pixels in memory is a well-known bottleneck of SIMD (single instruction multiple data) processors in video/imaging. To tackle it, we propose new block and row access modes of parallel on-chip memory subsystem, which enable a higher processing throughput and lower energy consumption than the access modes of the state-of-the-art subsystems. The new access modes significantly reduce the number of on-chip memory accesses, and thereby accelerate one of key video/imaging kernels: sub-pixel block-matching motion estimation. The main idea is to exploit spatial overlaps of blocks/rows accessed for pixel interpolation, which are known at the subsystem design-time, and merge multiple accesses into a single one by accessing somewhat more pixels at a time than with other parallel memories. To avoid the need for a wider, and, therefore, more costly SIMD datapath, we propose new memory read operations that split all pixels accessed at a time into multiple SIMD-wide blocks/rows, in a convenient way for further processing. As a proof of concept, we describe a parametric, scalable, and cost-efficient architecture that supports the new access modes. The architecture is based on a previously proposed set of memory banks with multiple pixels per bank word, and a previously proposed shifted scheme for arranging pixels in the banks. We analytically and experimentally demonstrate advantages of this work on a case study of sub-pixel motion estimation for video frame-rate conversion. The implemented motion estimator processes 2160p video at 60 fps in real time, while clocked at 600 MHz. Compared to the implementations based on the state-of-the-art subsystems, this work enables 40–70 % higher throughput, consumes 17–44 % less energy and has similar silicon area and off-chip memory bandwidth costs. That is 1.8–2.9 times more efficient than the prior art, considering the throughput and all costs, i.e., consumption, area, and off-chip bandwidth. Such a higher efficiency is the result of the new access modes, which reduced the number of on-chip memory accesses by 1.6–2.1 times, and the cost-efficient architecture.     

An Approximation Framework for Solvers and Decision Procedures

We consider the problem of automatically and efficiently computing models of constraints, in the presence of complex background theories such as floating-point arithmetic. Constructing models, or proving that a constraint is unsatisfiable, has various applications, for instance for automatic generation of test inputs. It is well-known that a naïve encoding of constraints into simpler theories (for instance, bit-vectors or propositional logic) often leads to a drastic increase in size, or that it is unsatisfactory in terms of the resulting space and runtime demands. We define a framework for systematic application of approximations in order to improve performance. Our method is more general than previous techniques in the sense that approximations that are neither under- nor over-approximations can be used, and it shows promising performance on practically relevant benchmark problems.     

Thermodynamic modeling of vapor-liquid equilibria and excess properties of the binary systems containing diethers and n-alkanes by cubic equation of state

A comparison of the performances of two different approaches of cubic equations of state models, based on a classical van der Waals and mixing rules incorporating theG ^E equation, was carried out for correlation of Vapor-Liquid Equilibria (VLE), H^E and C _P ^E data alone, and simultaneous correlation of VLE+H^E, VLE+C _P ^E , H^E +C _P ^E and VLE+H^E +C _P ^E data for the diethers (1,4-dioxane or 1,3-dioxolane) with n-alkane systems. For all calculations the Peng-Robinson-Stryjek-Vera cubic equation of state (PRSV CEOS) was used. A family of mixing rules for the PRSV CEOS based on the Modified van der Waals one-fluid mixing rule (MvdW1) and two well-known CEOS/G^E mixing rules (MHV1 and MHV2), was considered. The NRTL equation, as the G^E model with linear or reciprocal temperature dependent parameters, was incorporated in the CEOS/G^E models. The results obtained by the CEOS/G^E models exhibit significant improvement in comparison to the MvdW1 models.     

A new method in designing compatibility and adhesion of EVA/PMMA blend by using EVA-<Emphasis Type="Italic">g</Emphasis>-PMMA with controlled graft chain length

Atom transfer free radical polymerization (ATRP) was employed in a synthesis of graft polymer EVA-g-PMMA with controlled length of side PMMA chains. Three steps of synthesis: partial hydrolysis of EVA, esterification with chloroacetyl chloride and ATRP grafting were performed to produce EVAOH, macroinitiator EVACl and grafted polymers G8020 (EVA/PMMA?=?80/20 wt%) and G6040 (EVA/PMMA?=?60/40 wt%). FTIR, Raman and NMR spectroscopy were used in the determination of the chemical structure and modification of EVA. Transmitted light and dark field microscopy showed higher affinity for coil formation of EVA-g-PMMA with longer PMMA side chains, i.e. G6040 compatibilizer. Morphological, thermal and adhesive properties of optical fiber adhesives of graft polymers and polymer blends poly(ethylene-co-vinyl acetate)-blend-poly(methyl methacrylate) (EVA/PMMA) compatibilized with 1 wt% of EVA-g-PMMA, were studied. Image analysis of SEM micrographs showed effective compatibilization with short grafted chains (G8020) that was indicated by lower porosity characteristics. TG/DTG analysis enabled determination of degree of hydrolysis and amount of chloro-functionalized groups. DSC analysis showed higher thermal stability of G8020 polymer. Single lap joint of adhesives/optical fibers were subjected to adhesive testing and obtained results for maximal force applied and adhesive failure suggested the visible influence of the length of graft chains on adhesion.