Multidimensional Software Research Articles

Detecting and Classifying Problematic Behavior: A Method Based on Multi-Dimensional Software Modeling Behavioral Characteristics

Detecting and Classifying Problematic Behavior: A Method Based on Multi-Dimensional Software Modeling Behavioral Characteristics

VMD: A Visualizable Malware Detection Scheme Based on Multi-dimensional Dynamic Behavior Information

Enormous traditional malware detection methods have been proposed and they are efficient in detecting known malware, however, these methods usually either are ineffective or have high false positive rate in detecting unknown malware. To improve the performance in unknown malware detection, many novel methods are presented by introducing and employing software behavior visualization, Artificial Intelligence, and other popular technologies. Unfortunately, they are still facing the inadequate data utilization and benchmark dataset lack problems. Therefore, in this paper, we propose an effective malware detection method by utilizing multi-dimensional software dynamic behavior information. To construct the concrete scheme, we combine a mapping mechanism from key parameters of software operation to grayscale images with a malware prediction model. In addition, to our knowledge, we constructed the first publicly accessible software dynamic behavior dataset containing over 800 malicious and 600 non-malicious software behavior images. Finally, the experiment results show that our method can effectively detect unknow malware and outperforms the existing comparative baseline schemes in terms of accuracy, precision, and recall.

Estimation of the shape factor (m) in Wiebe function at different operating conditions for a SI engine

The burning process is one of the most important periods, which affects thermal efficiency and exhaust gas emissions, in internal combustion engines. The combustion process in internal combustion engines is modeled with one-dimensional or multi-dimensional software because it is cheaper, faster, and more practical than experiment. One of these methods, which is used to model the combustion period, is the Wiebe function. The Wiebe equation is an approach used in calculating the mass fraction burned and the heat release rate. The selection of Wiebe parameters is one of the most important factors affecting the accuracy of the mass fraction burned. In this study, the measured cylinder pressure of a spark ignition engine was directly used to calculate the heat released rate. The experiments were conducted at different brake mean effective pressures, engine speeds and relative air/fuel ratios, which were called independent variables. The shape factor (m) was determined by fitting the Wiebe equation to the heat release rate curves, which were extracted from the experimental results. The relationship between determined shape factor and independent variables was analyzed with a statistical approach. Eventually, a linear regression model, which explains 80% of the change in the shape factor, was created.

Application of Software Data Analysis Model Based on K-Means Clustering Algorithm

In order to improve the anomaly detection ability of portable multidimensional control software test data, a software test data anomaly detection method based on K-means clustering is proposed. The abnormal data distribution structure model of portable multidimensional control software testing is constructed. The fuzzy semantic feature reconstruction method is adopted to identify the fuzzy parameters of portable multidimensional control software and extract the feature quantity of associated information. According to the evolution distribution of associated features, the joint combination feature analysis method is adopted to realize the fuzzy clustering center detection of abnormal data of portable multidimensional control software test, and the fusion of abnormal feature distribution is carried out to complete the joint multidimensional feature detection. The K-means clustering method is used for effective data combination control in portable multidimensional control software to extract and detect abnormal features of test data in portable multidimensional control software. Experimental results show that the accuracy of anomaly detection of software test data by the proposed method is always greater than 0.8. Conclusion. Using this method to detect abnormal data of portable multidimensional control software test has higher accuracy and better detection performance.

EmbrASD: Android Mobile Application for Children with Autism as a Supplemental Tool for Therapy

Autism has a very wide range that influences people, specifically children in general. Usually, it affects a child’s social interaction, communication, behaviors, and interests. Providing a complete device for treatment which is planned to be used by kids with autism needs to be taken into consideration. There is no software available that will adhere to the main areas of autism. The development a multidimensional software that focuses the main areas of kids with autism was a specific goal that the paper is being addressed. It is planned from the viewpoint of several specialists: more particularly speech therapist, occupational therapist, Special Education (SPED) educator and an Applied Behavior Analysis (ABA) specialist. The specialists’ focused objectives were lengthily included into the planning of the software. The development of an application for the young with autism that would completely attend to all the main areas that are initiated by autism and serves as an addendum to treatment is the primary goal of the study. Interviews from, speech therapist, occupational therapist, SPED teacher, ABA therapist and a SPED therapist will serve as a basis and the prototyping methodology for system development. With the implemented system, the intended users gave an approval on the application to be integrated in the teaching of children with autism. Suggestions on the improvement of the application comprises of including video recording for API 22, implementing the system in the iOS environment, and concentration on older autism cases were recommended.

One Tube 24 Color Full Spectral Flow Cytometry and Multi-Dimensional Software to Study the Maturation Pattern and Antigen Expression of the Myeloid

Introduction Flow cytometry(FC) plays an important role in the diagnosis of hematologic diseases and the study of cell maturation. Spectral multicolor flow cytometry(SMFC) has shown an advantage over traditional FC that more fluorescent markers could be detected simultaneously, more antigen combinations could be made, and the expression of cells could be scrutinized. However, published studies focused on lymphocyte subsets and the differentiation between hematogones and B-acute lymphoblastic leukaemia/lymphoma(ALL/LBL) minimal residual disease(MRD) detection, and there are few studies on myeloid development and expression. Besides, more powerful and cutting-edge software are needed for complicated combinations from SMFC because traditional dot plots are unable to meet the demand of analysis. Here we design a one-tube 24-color panel combining with the multidimensional data analysis software to study the expression and maturation of normal and malignant myeloid cells including minus subgroups. We hope to improve the sensitivity of MRD by FC and explore more information about myeloid diseases, finally promote the development of artificial intelligence(AI) in clinical FC diagnosis. Methods: the one-tube 24-color panel was designed according to our experience and Euroflow recommendation. it is composed of backbones including CD45 and myeloblast markers CD34, CD117 and HLA-DR, adding myeloid markers CD33, CD13, CD371, CD15, CD64, CD11c,CD14, CD36 and CD11b, routine leukaemia associated immunophenotyping(LAIP) or different from normal(DFN) markers CD4, CD19, CD7, CD2, CD56,CD96,CD123, CD38, CD200, CD71 and CD9. The control database consisted of 20 normal bone marrow(BM) specimens, including 8 healthy donors and 12 patients with other diseases that were in complete remission(CR) after treatment. To verify the effectiveness of the panel, 4 BM samples from acute myeloblastic leukaemia(AML) patients with MRD positive or relapsed status were selected, with malignant myeloblasts of 0.23% (sample A1), 4.3%, 30.31% (and 6.47% abnormal mast cells, sample A3), 0.29% (16.49% basophils) (sample A4), respectively. The data was acquired by a 3 laser 38-color Cytek spectral FC, and analyzed by Kaluza and Flowjo software. The results were compared with those of conventional 3 - laser 8 - color Canto FC. Results when analyzing the common antibodies acquired by two kinds of FCs and software, the similarities and good correlations were shown about the percentage of myeloid subsets and expression pattern of antigens, no matter in normal or abnormal specimen. However, SMFC can analyze subsets of myeloid cells more clearly and detailedly, especially in minus subgroups like mast cells or basophils. Abnormal expression of tumor cells could be clearly observed in both FCs, and more abnormalities could be found with 24 color analysis, especially mast cell abnormalities. The t-SNE plug-in in Flowjo was used to conduct dimension-reduction analysis on 20 samples (see figure), with hundreds of dot plots being merged into one multi-dimensional picture. The normal samples were similar, but the abnormal samples were different from the normal ones. However, the t-SNE pictures were same only for the specimens that malignant myeloblasts were the only abnormality. The other two samples with abnormal mast cells or basophils showed different t-SNE figures. In the process of automatic clustering, CD117 and CD34 positive myeloblasts, basophils and mast cells were classified as three clusters according to the proportion of cells, surface antigen expression, and of fluorescence intensity of antigen expression. A more obvious aggregation was formed by malignant cells than normal cells, and was positively related to tumor burden. Since mast cells and basophils were low percentages in normal specimens, the abnormal clusters were more obvious when the proportion of these two types of cells increased. Conclusion Combined with cutting-edge software(BD FlowJO), SMFC can offer more cellular information that is unmatched by traditional FC. This study is only the preliminary attempt of our laboratory. With detailed data from more samples and longer-termed clinical trials, it would be a promising method to explore and study the myeloid maturation, improve the sensitivity of MRD, and promote the application of AI. Disclosures No relevant conflicts of interest to declare.

The appisation of television: TV apps, discoverability and the software, device and platform ecologies of the internet era

This article examines the appisation of television: the emergence of apps as a mainstream means of delivering television services/content through smart TVs, connected devices, smartphones and tablets. Exploring the interrelationships between TV content, discovery and aggregator apps, the article demonstrates how content/software providers, device manufacturers and infrastructural platforms vie to control our access to, and experience of, television in a market underpinned by datafication, commodification and selection. This control is enacted within a multidimensional software, device and platform ecology where discoverability is central because it determines which content, services and apps are most prominent, accessible and easy to find.

A machine learning approach to software model refactoring

Good software quality is a consequence of good design. Model refactoring counteracts erosion of the software design at an early stage in the software development project complying with the model-driven engineering paradigm. Traditional model refactoring approaches work at the surface level by using threshold values of model metrics as indicators of suboptimal design and carry out localized corrections. Through this paper, it is proposed that identifying design flaws at a higher level of granularity will save from the vicious cycle of small refactoring operations and their cascaded side-effects. The notion of functional decomposition, as an anomalous design tendency and a dominant cause of design, smells in object-oriented software, is introduced. It is suggested that refactoring operations targeted at signs of functional decomposition instead of atomic smells achieve substantial improvement in design within a concise quality assurance procedure. The idea is realized using a deep neural network that learns to recognize the presence of functional decomposition in UML models of object-oriented software. The presented approach uses data science methods to gain insight into multidimensional software design features and uses the experience gained to generalize subtle relationships among architectural components.

Multi-Dimensional Software Tool for OSS Project Management Considering Cloud with Big Data

We discuss a method of software dependability assessment based on stochastic differential equation modeling in order to consider the interesting factors of the numbers of components, cloud applications and users. Then, we consider the determination of an optimum software maintenance time, minimizing the total expected software cost. In particular, we develop the three-dimensional AIR application for reliability and cost optimization analyses based on the proposed method. Moreover, the three-dimensional application based on NW.js, known as the latest technology, is developed in this paper. Furthermore, we show several numerical examples of the developed application software to evaluate the performance of software optimization and reliability assessment tools for the big data on cloud computing.

Effects of hydrogen blending mode on combustion process of a rotary engine fueled with natural gas/hydrogen blends

The highly advanced wankel rotary engine is a promising energy system because of its favorable energy to weight ratio, multi-fuel capability and large specific power output. This work aims to numerically study the performance, combustion and emission characteristics of a side-ported rotary engine fueled with natural gas/hydrogen blends under different hydrogen blending modes. Simulations were performed using multi-dimensional software FLUENT 14.0. On the basis of the software, a three-dimensional dynamic simulation model was established by writing dynamic mesh programs, choosing the RNG k-ε turbulent model, the eddy-dissipation concept (EDC) combustion model and a reduced reaction mechanism. The three-dimensional dynamic simulation model based on the chemical reaction kinetics was also validated by the experimental data. Meanwhile, further simulations were then conducted to investigate how to impact the combustion process by the coupling function between hydrogen distribution and the flow field inside the cylinder. Simulation results showed that in order to improve the combustion efficiency, the low-pressure early injection should be used as the hydrogen blending mode. The low-pressure early injection, not only allowed the hydrogen in the combustion chamber to be distributed evenly, but also resulted in the high concentration areas of hydrogen located at the front of the trialing spark plug, which can be used to increase the combustion rate. For the hydrogen low-pressure early injection, the improved combustion rate made in-cylinder pressure and the intermediate OH increase significantly. Compared with no hydrogen induction, it shows a 29% increase in the peak pressures. Meanwhile, the drawback is the increase in NO emissions.

A Mathematical Model for the Exhaust Gas Temperature Profile of a Diesel Engine

This work presents a heat transfer model for the exhaust gas of a diesel power generator to determine the gas temperature profile in the exhaust pipe. The numerical methodology to solve the mathematical model was developed using a finite difference method approach for energy equation resolution and determination of temperature profiles considering turbulent fluid flow and variable fluid properties. The simulation was carried out for engine operation under loads from 0 kW to 40 kW. The model was compared with results obtained using the multidimensional Ansys CFX software, which was applied to solve the governor equations of turbulent fluid flow. The results for the temperature profiles in the exhaust pipe show a good proximity between the mathematical model developed and the multidimensional software.

Effects of ignition parameters on combustion process of a rotary engine fueled with natural gas

The side-ported rotary engine fueled with natural gas is anew,clean,efficientenergy system. This work aims to numerically study the performance, combustion and emission characteristics of a side-ported rotary engine fueled with natural gas under different ignition positions andignition timings. Simulations were performed using multi-dimensional software ANASYS Fluent. Onthebasisof the software, a three-dimensional dynamic simulation model was established by writing dynamic mesh programs and choosing a detailed reaction mechanism. The three-dimensional dynamic simulation model, based on the chemical reaction kinetics, was also validated by the experimental data. Meanwhile, further simulations were then conducted to investigate how to impact the combustion process by the couplingfunction between ignitionoperating parameter and the flow field inside the cylinder. Simulation results showed that in order to improve the combustion efficiency, the trailing spark plugshould be located at the rear of the tumble zone and the ignition timing should be advanced properly. This was mainly caused by the trailing spark plug being located at the rear of the tumble zone, as it not only allowed the fuel in the rear of combustion chamber to be burnt without delay, but also permitted the acceleration of the flame propagation by the tumble. Meanwhile, with advanced ignition timing, the time between ignitiontiming and the timing of the tumble disappearance increased, which led to an increase of the tumble effect time used to improve the combustion rate. However, the drawback of this improved combustion was the slight increase in NO emissions. Under thecomputationalcondition, when the trailing spark plug scheme of case C coupled with an ignition timing of 50°CA (BTDC) was compared with the spark plug location and the ignition timing of theoriginalengine, it showed a27.4% increasein thepeak pressure. Taking the limited increaseof NO exhaust into consideration it was thebest ignitionallocation scheme under thecomputational condition. This study provided a theoretical foundation for the determination of best ignition position and ignition timing under different working conditions.

Effects of pocket shape and ignition slot locations on the combustion processes of a rotary engine fueled with natural gas

This work aims to numerically study the performance, combustion and emission characteristics of a side-ported natural-gas-fueled rotary engine under different pocket shapes and ignition slot positions. Simulations were performed using multi-dimensional software FLUENT 14.0. On the basis of the software, a three-dimensional dynamic simulation model was established by writing dynamic mesh programs and choosing a detailed reaction mechanism. The three-dimensional dynamic simulation model, based on the chemical reaction kinetics, was also validated by the experimental data. Simulation results showed that a bigger intensity of the tumble, a larger area of the high speed oblique flow and a higher average flow speed in the middle of the combustion chamber can make the flame propagation speed increase. When the combustion chamber configuration had a middling pocket coupled with an ignition slot located at the middle of the width direction of rotor surface, the combustion rate is the highest. As a result, the cylinder pressure and the intermediate OH increased significantly. Compared with the combustion chamber configuration, which had a flat-top pocket without ignition slot, it showed a 10 percent increase in the peak pressures, but a certain increase in NO emissions.

Data Checking and Econometric Software Development: A Technique of Traceability by Fictive Data Encoding

In this paper, we have exposed the data checking problem in the context of the econometric software development. We have based our presentation on the development of our SIMUL multidimensional econometric software. We have shown that this problem is particularly important when one develops multi-dimensional econometric software. Then, we have briefly recalled the principle of the main arithmetical and managerial techniques available to deal with this problem. Finally, we have presented the data checking procedures we have conceived based on a fictive data encoding technique.

3-DIMENSIONAL NUMERICAL MODELING ON THE COMBUSTION AND EMISSION CHARACTERISTICS OF BIODIESEL IN DIESEL ENGINES

A 3-dimensional computational fluid dynamics modeling is conducted on a direct injection diesel engine fueled by biodiesel using multi-dimensional software KIVA4 coupled with CHEMKIN. To accurately predict the oxidation of saturated and unsaturated agents of the biodiesel fuel, a multicomponent advanced combustion model consisting of 69 species and 204 reactions combined with detailed oxidation pathways of methyl decenoate (C11H22O2), methyl-9-decenoate (C11H20O2) and n-heptane (C7H16) is employed in this work. In order to better represent the real fuel properties, the detailed chemical and thermo-physical properties of biodiesel such as vapor pressure, latent heat of vaporization, liquid viscosity and surface tension were calculated and compiled into the KIVA4 fuel library. The nitrogen monoxide (NO) and carbon monoxide (CO) formation mechanisms were also embedded. After validating the numerical simulation model by comparing the in-cylinder pressure and heat release rate curves with experimental results, further studies have been carried out to investigate the effect of combustion chamber design on flow field, subsequently on the combustion process and performance of diesel engine fueled by biodiesel. Research has also been done to investigate the impact of fuel injector location on the performance and emissions formation of diesel engine.

Standardizing the analysis of conditioned fear in rodents: a multidimensional software approach

Data comparability between different laboratories strongly depends on the individually applied analysis method. This factor is often a critical source of variation in rodent phenotyping and has never been systematically investigated in Pavlovian fear conditioning paradigms. In rodents, fear is typically quantified in terms of freezing duration via manual observation or automated systems. While manual analysis includes biases such as tiredness or inter-personal scoring variability, computer-assisted systems are unable to distinguish between freezing and immobility. Consequently, the novel software called MOVE follows a semi-automatized approach that prefilters video sequences of interest for the final human judgment. Furthermore, MOVE allows integrating additional data sources (e.g. force-sensitive platform, EEG) to reach the most accurate and precise results. MOVE directly supports multi-angle video recordings with webcams or standard laboratory equipment. The integrated manual key logger and internal video player complement this all-in-one software solution. Calculating the interlaboratory variability of manual freezing evaluation revealed significantly different freezing scores in two out of six laboratories. This difference was minimized when all experiments were analyzed with MOVE. Applied to a genetically modified mouse model, MOVE revealed higher fear responses of CB1 deficient mice compared to their wild-type littermates after foreground context fear conditioning. Multi-angle video analysis compared to the single-camera approach reached up to 15% higher accuracy and two fold higher precision. Multidimensional analysis provided by integration of additional data sources further improved the overall result. We conclude that the widespread usage of MOVE could substantially improve the comparability of results from different laboratories.

Editorial for CollaborateCom 2011 Special Issue

Editorial: Collaboration is an essential cornerstone of modern computing. Enabled by cloud computing, new wireless networks, ubiquitous mobile devices – to name just a few – the new collaborative ecosystem promises a potential that far exceeds our current capabilities. And as the world heads towards unlimited connectivity and global mobile computing, future collaboration solutions that fully realize this potential will require advances in networking, technology and systems, user interfaces and interaction paradigms, and interoperation with application-specific components and tools. As a nexus for collaborative computing, the Seventh International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2011) serves as a premier international forum for discussion among academic and industrial researchers, practitioners, and students interested in collaborative networking, technology and systems, and applications. In total, we received 62 submissions to CollaborateCom 2011. After a rigorous review and follow-up discussions, the Program Committee selected 19 papers for acceptance (a rate of 30 %). Following the completion of the conference, the Program Committee selected three of the best papers from the conference that best exemplify the themes of CollaborateCom and mobile computing for special invited submission to this issue. These three papers underwent a series of new reviews and revisions before appearing as you will find them here. In the first paper titled “Data Replication in Cooperative Mobile Ad-Hoc Networks: A game theoretic replication algorithm using volunteers' dilemma,” Hirsch and Madria propose a new replication scheme to strategically balance the constrained resources inherent in a mobile computing environment through a cooperative game theoretic approach. Nodes within the network collaborate via cooperative replica caching decisions to achieve overall improved query response times while reducing the query error rate and energy utilization. The second paper titled “Combining Mobile XMPP Entities and Cloud Services for Collaborative Post-Disaster Management in Hybrid Network Environments,” by Klauck and Kirsche presents a new system design that integrates portable devices and autonomous sensors through XMPP with the flexibility of cloud services to support post-disaster management. Through implementation and evaluation of two prototypes, they derive new insights into the practical application of XMPP and potential enhancements in hybrid (ad hoc and infrastructure) network scenarios. In the third paper titled “ChameleonSoft: Software Behavior Encryption For Moving Target Defense,” Azab and Elotweissy propose a biologically-inspired defense system that employs multidimensional software diversity to overcome the vulnerability of the persistent software monoculture. The system – ChameleonSoft – is built over a celloriented architecture, applying a multidimensional spatiotemporal diversity and hot shuffling of variants, hence effecting software execution behavior encryption, as well as adjusting its system policies at runtime to meet the continual change in the operational environment. As you read this issue, we believe you'll find that the selected papers make significant contributions to J. Caverlee (*) Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA e-mail: caverlee@cse.tamu.edu

A numerical study on a hydrogen assisted diesel engine

This work aims to numerically study the performance, combustion and emission characteristics of a hydrogen assisted diesel engine under various operating conditions. Simulations were performed using multi-dimensional software KIVA4 coupled with CHEMKIN. The Kelvin–Helmholtz and Rayleigh–Taylor hybrid break up model was implemented to accurately model the spray development. A detailed reaction mechanism was constructed to take into account the chemical kinetics of diesel and hydrogen, and it was validated against the experimental results with 0% of hydrogen induction. Simulation results showed that at low engine speeds, the indicated thermal efficiency, in-cylinder pressure and apparent heat release rate increased significantly with the induction of hydrogen. On the other hand, at high engine speed and high load conditions, no tangible changes on the engine performance, combustion characteristics were observed. In terms of emissions, CO and soot emissions were shown to be reduced under most of the engine operating conditions. Whereas for NOx emissions, a slight increase was observed at low engine speed of 1600 rpm.

ChameleonSoft: Software Behavior Encryption for Moving Target Defense

Ubiquitous cyber systems and their supporting infrastructure impact productivity and quality of life immensely. Their penetration in our daily life increases the need for their enhanced resilience and for means to secure and protect them. One major threat is the contemporary software monoculture. Recent research illustrated the vulnerability of the software monoculture and proposed diversity to reduce the attack surface. In this paper, we propose a biologically-inspired defense system, ChameleonSoft, that employs multidimensional software diversity to, in effect, induce spatiotemporal "software behavior encryption" for moving target defense. The key principles of ChameleonSoft are decoupling functional roles from runtime role players; devising intrinsically-resilient composable online-programmable building blocks; separating logic, state and physical resources; and employing functionally-equivalent, behaviorally-different code variants. ChameleonSoft is also equipped with an autonomic failure recovery mechanism for enhanced resilience. Nodes employing ChameleonSoft autonomously and cooperatively change their recovery and encryption policies both proactively and reactively according to the continual changes in context and environment. Using analysis and simulation, our results show that chameleonsoft can encrypt the execution behavior by confusion and diffusion induction at a reasonable overhead.

A Multidimensional Software Cache for Scratchpad-Based Systems

In many kernels of multimedia applications, the working set is predictable, making it possible to schedule the data transfers before the computation. Many other kernels, however, process data that is known just before it is needed or have working sets that do not fit in the scratchpad memory. Furthermore, multimedia kernels often access two or higher dimensional data structures and conventional software caches have difficulties to exploit the data locality exhibited by these kernels. For such kernels, the authors present a Multidimensional Software Cache (MDSC), which stores 1- 4 dimensional blocks to mimic in cache the organization of the data structure. Furthermore, it indexes the cache using the matrix indices rather than linear memory addresses. MDSC also makes use of the lower overhead of Direct Memory Access (DMA) list transfers and allows exploiting known data access patterns to reduce the number of accesses to the cache. The MDSC is evaluated using GLCM, providing an 8% performance improvement compared to the IBM software cache. For MC, several optimizations are presented that reduce the number of accesses to the MDSC.