Abstract: The aim of information systems integration is to make all the data sources, applications and business flows integrated into the new environment so that unwanted redundancies are reduced and bottlenecks and mismatches are eliminated. Two issues have to be dealt with to meet such requirements: the software architecture that supports resource integration, and the adaptor development tool that help integration and migration of legacy applications. In this paper, a service-enabled dependable integration environment (SDIE), is presented, which has two key components, i.e., a dependable service integration platform and a legacy application integration tool. For the dependable platform for service integration, the service integration bus, the service management framework, the dependable engine for service composition, and the service registry and discovery components are described. For the legacy application integration tool, its basic organization, functionalities and dependable measures taken are presented. Due to its service-oriented integration model, the light-weight extensible container, the service component combination-oriented p-lattice structure, and other features, SDIE has advantages in openness, flexibility, performance-price ratio and feature support over commercial products, is better than most of the open source integration software in functionality, performance and dependability support.
Abstract: This paper describes a part of the integrating work between assembly design and assembly process planning domains (APP). The work is based, in its first stage, on modelling assembly features to support APP. A multi-layer architecture, based on feature-based modelling, is proposed to establish a dynamic and adaptable link between product design using CAD tools and APP. The proposed approach is based on deriving “specific function” features from the “generic” assembly and form features extracted from the CAD tools. A hierarchal structure from “generic” to “specific” and from “high level geometrical entities” to “low level geometrical entities” is proposed in order to integrate geometrical and assembly data extracted from geometrical and assembly modelers to the required processes and resources in APP. The feature concept, feature-based modelling, and feature recognition techniques are reviewed.
Abstract: Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.
Abstract: Deformable part models achieve high precision in
pedestrian recognition, but all publicly available implementations are
too slow for real-time applications. We implemented a deformable
part model algorithm fast enough for real-time use by exploiting
information about the camera position and orientation. This
implementation is both faster and more precise than alternative
DPM implementations. These results are obtained by computing
convolutions in the frequency domain and using lookup tables to
speed up feature computation. This approach is almost an order of
magnitude faster than the reference DPM implementation, with no
loss in precision. Knowing the position of the camera with respect to
horizon it is also possible prune many hypotheses based on their
size and location. The range of acceptable sizes and positions is
set by looking at the statistical distribution of bounding boxes in
labelled images. With this approach it is not needed to compute the
entire feature pyramid: for example higher resolution features are
only needed near the horizon. This results in an increase in mean
average precision of 5% and an increase in speed by a factor of
two. Furthermore, to reduce misdetections involving small pedestrians
near the horizon, input images are supersampled near the horizon.
Supersampling the image at 1.5 times the original scale, results in
an increase in precision of about 4%. The implementation was tested
against the public KITTI dataset, obtaining an 8% improvement in
mean average precision over the best performing DPM-based method.
By allowing for a small loss in precision computational time can be
easily brought down to our target of 100ms per image, reaching a
solution that is faster and still more precise than all publicly available
DPM implementations.
Abstract: Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.
Abstract: The subject of this abstract is related to the notion of 'popular music', a notion that should be treated with extreme care, particularly when applied to Frederic Chopin, one of the greatest composers of Romanticism. By ‘popular music’, we mean a category of everyday music, set against the more intellectual kind, referred to as ‘classical’. We only need to look back to the culture of the nineteenth century to realize that this ‘popular music’ refers to the ‘music of the low’. It can be studied from a sociological viewpoint, or as sociological aesthetics. However, we cannot ignore the fact that, very quickly, this music spread to the wealthiest strata of the European society of the nineteenth century, while likewise the lowest classes often listen to the intellectual classical music, so pleasant to listen to. Further, we can observe that a sort of ‘sacralisation of kitsch’ occurs at the intersection between the classical and popular music. This process is the topic of this contribution. We will start by investigating the notion of kitsch through the study of Chopin’s popular compositions. However, before considering the popularisation of this music in today’s culture, we will have to focus on the use of the word kitsch in Chopin’s times, through his own musical aesthetics. Finally, the objective here will be to negate the theory that art is simply the intellectual definition of aesthetics. A kitsch can, obviously, only work on the emotivity of the masses, as it represents one of the features of culture-language (the words which the masses identify with). All art is transformed, becoming something outdated or even outmoded. Here, we are truly within a process of mythologization of art, through the study of the aesthetic reception of the musical work.
Abstract: Manufacturing technologies are becoming continuously
more diversified over the years. The increasing use of robots for
various applications such as assembling, painting, welding has also
affected the field of machining. Machining robots can deal with
larger workspaces than conventional machine-tools at a lower cost
and thus represent a very promising alternative for machining
applications. Furthermore, their inherent structure ensures them a
great flexibility of motion to reach any location on the workpiece with
the desired orientation. Nevertheless, machining robots suffer from
a lack of stiffness at their joints restricting their use to applications
involving low cutting forces especially finishing operations. Vibratory
instabilities may also happen while machining and deteriorate the
precision leading to scrap parts. Some researchers are therefore
concerned with the identification of optimal parameters in robotic
machining. This paper continues the development of a virtual robotic
machining simulator in order to find optimized cutting parameters in
terms of depth of cut or feed per tooth for example. The simulation
environment combines an in-house milling routine (DyStaMill)
achieving the computation of cutting forces and material removal
with an in-house multibody library (EasyDyn) which is used to
build a dynamic model of a 3-DOF planar robot with flexible links.
The position of the robot end-effector submitted to milling forces is
controlled through an inverse kinematics scheme while controlling
the position of its joints separately. Each joint is actuated through
a servomotor for which the transfer function has been computed
in order to tune the corresponding controller. The output results
feature the evolution of the cutting forces when the robot structure
is deformable or not and the tracking errors of the end-effector.
Illustrations of the resulting machined surfaces are also presented.
The consideration of the links flexibility has highlighted an increase
of the cutting forces magnitude. This proof of concept will aim
to enrich the database of results in robotic machining for potential
improvements in production.
Abstract: The following paper describes the video database tool used by the Fédération Internationale de Football Association (FIFA) as part of the research project developed in collaboration with the Carlos III University of Madrid. The database project began in 2012, with the aim of creating an educational tool for the training of instructors, referees and assistant referees, and it has been used in all FUTURO III courses since 2013. The platform now contains 3,135 video clips of different match situations from FIFA competitions. It has 1,835 users (FIFA instructors, referees and assistant referees). In this work, the main features of the database are described, such as the use of a search tool and the creation of multimedia presentations and video quizzes. The database has been developed in MySQL, ActionScript, Ruby on Rails and HTML. This tool has been rated by users as "very good" in all courses, which prompt us to introduce it as an ideal tool for any other sport that requires the use of video analysis.
Abstract: Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.
Abstract: A strategy of fault diagnosis and tolerance for
asynchronous sequential machines is discussed in this paper. With
no synchronizing clock, it is difficult to diagnose an occurrence
of permanent or stuck-in faults in the operation of asynchronous
machines. In this paper, we present a fault detector comprised of
a timer and a set of static functions to determine the occurrence
of faults. In order to realize immediate fault tolerance, corrective
control theory is applied to designing a dynamic feedback controller.
Existence conditions for an appropriate controller and its construction
algorithm are presented in terms of reachability of the machine and
the feature of fault occurrences.
Abstract: The triple diffusive boundary layer flow of nanofluid under the action of constant magnetic field over a non-linear stretching sheet has been investigated numerically. The model includes the effect of Brownian motion, thermophoresis, and cross-diffusion; slip mechanisms which are primarily responsible for the enhancement of the convective features of nanofluid. The governing partial differential equations are transformed into a system of ordinary differential equations (by using group theory transformations) and solved numerically by using variational finite element method. The effects of various controlling parameters, such as the magnetic influence number, thermophoresis parameter, Brownian motion parameter, modified Dufour parameter, and Dufour solutal Lewis number, on the fluid flow as well as on heat and mass transfer coefficients (both of solute and nanofluid) are presented graphically and discussed quantitatively. The present study has industrial applications in aerodynamic extrusion of plastic sheets, coating and suspensions, melt spinning, hot rolling, wire drawing, glass-fibre production, and manufacture of polymer and rubber sheets, where the quality of the desired product depends on the stretching rate as well as external field including magnetic effects.
Abstract: The paper describes conceptual design, control strategies, and partial simulation for a new fully autonomous lower limb wearable exoskeleton system for human motion enhancement that can support its weight and increase strength and endurance. Various problems still remain to be solved where the most important is the creation of a power and cost efficient system that will allow an exoskeleton to operate for extended period without batteries being frequently recharged. The designed exoskeleton is enabling to decouple the weight/mass carrying function of the system from the forward motion function which reduces the power and size of propulsion motors and thus the overall weight, cost of the system. The decoupling takes place by blocking the motion at knee joint by placing passive air cylinder across the joint. The cylinder is actuated when the knee angle has reached the minimum allowed value to bend. The value of the minimum bending angle depends on usual walk style of the subject. The mechanism of the exoskeleton features a seat to rest the subject’s body weight at the moment of blocking the knee joint motion. The mechanical structure of each leg has six degrees of freedom: four at the hip, one at the knee, and one at the ankle. Exoskeleton legs are attached to subject legs by using flexible cuffs. The operation of all actuators depends on the amount of pressure felt by the feet pressure sensors and knee angle sensor. The sensor readings depend on actual posture of the subject and can be classified in three distinct cases: subject stands on one leg, subject stands still on both legs and subject stands on both legs but transit its weight from one leg to other. This exoskeleton is power efficient because electrical motors are smaller in size and did not participate in supporting the weight like in all other existing exoskeleton designs.
Abstract: In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.
Abstract: Epoxy composites are broadly used as an electrical insulation for the high voltage applications since only such materials can fulfill particular mechanical, thermal, and dielectric requirements. However, properties of the final product are strongly dependent on proper manufacturing process with minimized material failures, as too large shrinkage, voids and cracks. Therefore, application of proper materials (epoxy, hardener, and filler) and process parameters (mold temperature, filling time, filling velocity, initial temperature of internal parts, gelation time), as well as design and geometric parameters are essential features for final quality of the produced components. In this paper, an approach for three-dimensional modeling of all molding stages, namely filling, curing and post-curing is presented. The reactive molding simulation tool is based on a commercial CFD package, and include dedicated models describing viscosity and reaction kinetics that have been successfully implemented to simulate the reactive nature of the system with exothermic effect. Also a dedicated simulation procedure for stress and shrinkage calculations, as well as simulation results are presented in the paper. Second part of the paper is dedicated to recent developments on formulations of functional composites for electrical insulation applications, focusing on thermally conductive materials. Concepts based on filler modifications for epoxy electrical composites have been presented, including the results of the obtained properties. Finally, having in mind tough environmental regulations, in addition to current process and design aspects, an approach for product re-design has been presented focusing on replacement of epoxy material with the thermoplastic one. Such “design-for-recycling” method is one of new directions associated with development of new material and processing concepts of electrical products and brings a lot of additional research challenges. For that, one of the successful products has been presented to illustrate the presented methodology.
Abstract: Regional earthquake early warning (EEW) systems are not suitable for Taiwan, as most destructive seismic hazards arise due to in-land earthquakes. These likely cause the lead-time provided by regional EEW systems before a destructive earthquake wave arrives to become null. On the other hand, an on-site EEW system can provide more lead-time at a region closer to an epicenter, since only seismic information of the target site is required. Instead of leveraging the information of several stations, the on-site system extracts some P-wave features from the first few seconds of vertical ground acceleration of a single station and performs a prediction of the oncoming earthquake intensity at the same station according to these features. Since seismometers could be triggered by non-earthquake events such as a passing of a truck or other human activities, to reduce the likelihood of false alarms, a seismometer was installed at three different locations on the same site and the performance of the EEW system for these three sensor locations were discussed. The results show that the location on the ground of the first floor of a school building maybe a good choice, since the false alarms could be reduced and the cost for installation and maintenance is the lowest.
Abstract: Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.
Abstract: This research focused on the dimensions of brand personality of the Ice Hockey World Championship sporting event. The authors compared the elements in relation to different demographic groups including gender, age, level of education and student status of the population of Prague. Moreover, the differences of opinions of respondents who had experience of visiting a sports event and those who had not were assessed. In the research, the modified brand personality scale was used. This modified scale consists of five dimensions: responsibility, activity, toughness, individuality and emotionality, none of which was previously tested. The authors had an intentional sample of 291 respondents from Prague available, ranging in age from 18 years to 75 years, with either a high school or university education. The respondents rated the characteristic features in a seven-point Likert Scale and the data was collected in November 2012. The results suggest that the Ice Hockey World Championship is most identified with these dimensions: responsibility, emotionality and activity. Men had higher mean scores (4.93) on the Likert Scale in the emotionality dimension, while women had higher mean scores (4.91) in the activity dimension. Those respondents with experience visiting an Ice Hockey World Championship match had the highest mean score (5.10) in the emotionality dimension. This research had expected to show more pronounced mean values (above six) on the Likert scale in the emotionality and activity dimensions that more strongly characterize the brand personality of the Ice Hockey World Championship, however this expectation was not confirmed.
Abstract: Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.
Abstract: This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.
Abstract: In this day and age, extremism in various forms of its manifestation is a real threat to the world community, the national security of a state and its territorial integrity, as well as to the constitutional rights and freedoms of citizens. Extremism, as it is known, in general terms described as a commitment to extreme views and actions, radically denying the existing social norms and rules. Supporters of extremism in the ideological and political struggles often adopt methods and means of psychological warfare, appeal not to reason and logical arguments, but to emotions and instincts of the people, to prejudices, biases, and a variety of mythological designs. They are dissatisfied with the established order and aim at increasing this dissatisfaction among the masses. Youth extremism holds a specific place among the existing forms and types of extremism. In this context in 2015, we conducted a survey among Moscow college and high school students. The aim of this study was to determine how great or small is the difference in understanding and attitudes towards extremism manifestations, inclination and readiness to take part in extremist activities and what causes this predisposition, if it exists. We performed multivariate analysis and found the Russian college and high school students' opinion about the extremism and terrorism situation in our country and also their cognition on these topics. Among other things, we showed, that the level of aggressiveness of young people were not above the average for the whole population. The survey was conducted using the questionnaire method. The sample included college and high school students in Moscow (642 and 382, respectively) by method of random selection. The questionnaire was developed by specialists of RUDN University Sociological Laboratory and included both original questions (projective questions, the technique of incomplete sentences), and the standard test Dayhoff S. to determine the level of internal aggressiveness. It is also used as an experiment, the technique of study option using of FACS and SPAFF to determine the psychotypes and determination of non-verbal manifestations of emotions. The study confirmed the hypothesis that in respondents’ opinion, the level of aggression is higher today than a few years ago. Differences were found in the understanding of and respect for such social phenomena as extremism, terrorism, and their danger and appeal for the two age groups of young people. Theory of psychotypes, SPAFF (specific affect cording system) and FACS (facial action cording system) are considered as additional techniques for the diagnosis of a tendency to extreme views. Thus, it is established that diagnostics of acceptance of extreme views among young people is possible thanks to simultaneous use of knowledge from the different fields of socio-humanistic sciences. The results of the research can be used in a comparative context with other countries and as a starting point for further research in the field, taking into account its extreme relevance.