scispace - formally typeset
Search or ask a question

Showing papers in "Advances in intelligent systems and computing in 2016"


Book ChapterDOI
TL;DR: The results show that GAR-forest performs better when compared with random forest, C4.5, naive Bayes and multilayer perceptron for binary and multi-class classification problem achieving 82.3989 and 77.2622 % accuracy, respectively, while classifying test data.
Abstract: Intrusion detection systems (IDS) are designed to detect malicious activities in a large-scale infrastructure. Many classification methods have been proposed to improve the classification accuracy of IDS. In this paper, we have applied greedy randomized adaptive search procedure with annealed randomness—Forest (GAR-Forest), a novel tree ensemble technique, with feature selection to improve classification accuracy of IDS. GAR-forest uses metaheuristic GRASP with annealed randomness to increase the diversity of ensemble. We used NSL-KDD datasets to study the classification accuracy of GAR-forest for both binary and multi-class classification problems. The results show that GAR-forest performs better when compared with random forest, C4.5, naive Bayes and multilayer perceptron for binary and multi-class classification problem achieving 82.3989 and 77.2622 % accuracy, respectively, while classifying test data. We have also applied feature selection procedures, such as information gain, symmetrical uncertainty and correlation-based feature subset, to select relevant features for improving the accuracy of GAR-forest. GAR-forest with symmetrical uncertainty yields 85.0559 % accuracy using 32 features for binary classification problem and information gain yields accuracy of 78.9035 % using 10 features for multi-class classification problem. GAR-forest is found to be relatively much faster than multilayer perceptron though it is slower than naive Bayes, random forest and C4.5 algorithm. The metaheuristic GRASP procedure enables GAR-forest to reach the global optimal solution which greedy deterministic approaches fail to reach.

53 citations


Book ChapterDOI
TL;DR: This work introduces solution based on an agent to protect DDoS attack on IoT, which is the attack penetrated from compromised systems that result in poor network performance, bandwidth consumptions, and resource consumptions.
Abstract: Internet of Things is an interconnected network where physical things become digital objects with the capability of communication via internet. World is moving speedily toward the era of IoT with increasing use of digital things, from smart home to smart city, smart street to smart industry, where all human-required information is either under surveillance or monitored through it via internet medium. By such a large-scale application of IoT, it becomes essential and important to secure the network, prevent it form unwanted attack. IoT is still evolving, but there are certain issues related to security like confidentiality, integrity, and availability. Here, we try to solve Distributed Denial of Service issue against IoT network. DDoS is the attack penetrated from compromised systems that result in poor network performance, bandwidth consumptions, and resource consumptions; as IoT have small processing unit, we must provide solution to restrict such attacks. We introduce solution based on an agent to protect DDoS attack on IoT.

38 citations


Book ChapterDOI
TL;DR: Five 3D sensors, including the structured light sensors Microsoft Kinect and ASUS Xtion Pro Live, and the time of flight sensors Fotonic E70P, IFM O3D200 and Nippon Signal FX6 are compared and it is found that structured light sensor are very accurate for close ranges.
Abstract: 3D sensors are used for many different applications, e.g., scene reconstruction, object detection, and mobile robots, etc. Several studies on usability and accuracy have been done for different sensors. However, all these studies have used different settings for the different sensors. For this reason we compare five 3D sensors, including the structured light sensors Microsoft Kinect and ASUS Xtion Pro Live, and the time of flight sensors Fotonic E70P, IFM O3D200 and Nippon Signal FX6, using the same settings. The sensor noise, absolute error, and point detection rates are compared for different depth values, environmental illumination, and different surfaces. Also, simple models of the noise depending on the measured depth are proposed. It is found that structured light sensors are very accurate for close ranges. The time of flight sensors have more noise, but the noise does not increase as strongly with the measured distance. Further, it is found that these sensors can be used for outdoor applications.

27 citations


Book ChapterDOI
TL;DR: In this article, the authors examined how AR tools can be integrated into informal learning experiences in ways that support children's engagement in science in their communities and found that AR tools could trigger and maintain children's situational interest and science learning outcomes during context-sensitive informal mobile learning.
Abstract: This research examines how augmented reality (AR) tools can be integrating into informal learning experiences in ways that support children’s engagement in science in their communities. We conducted a series of video-based studies over 4 years in an arboretum and a nature center with families and children. In this study (the four iteration of the Tree Investigators design-based research project), 1-hour sessions were conducted at a summer camp for 6 weeks at Shaver’s Creek Environmental Center. The sessions supported children to learn about the life cycle of trees with iPad computer tablets. Data collected included pre- and post-assessments and video records of children engaged in the science practice of observation. Analysis included the Wilcoxon signed-rank test of 42 paired assessments, the microethnographic analysis of transcripts of dyads and triads engaged with AR tools, and the creation of one case study of a pair of boys, who were representative of others in the dataset. Across the dataset, we found three sociotechnical interactions that contributed to triggering situational interests during the summer camp learning experience: (a) discoveries in the environment related to nature, (b) prior experiences that led to anticipation or expectation about what would happen, and (c) hands-on experiences with natural phenomenon. Implications of the study include that AR tools can trigger and maintain children’s situational interest and science learning outcomes during context-sensitive informal mobile learning.

26 citations


Book ChapterDOI
TL;DR: This study has been done in the perspective of enabling the selection of a segmentation method for MRI brain images, and has been categorized based on the techniques used in segmentation.
Abstract: This paper presents a survey on the existing methods for segmentation of brain MRI images. Segmentation of brain MRI images has been widely used as a preprocessing, for projects that involve analysis and automation, in the field of medical image processing. MRI image segmentation is a challenging task because of the similarity between different tissue structures in the brain image. Also the number of homogeneous regions present in an image varies with the image slice and orientation. The selection of an appropriate method for segmentation therefore depends on the image characteristics. This study has been done in the perspective of enabling the selection of a segmentation method for MRI brain images. The survey has been categorized based on the techniques used in segmentation.

23 citations


Book ChapterDOI
TL;DR: In this paper, the direction of values in processing is considered and a new algorithm for the inference operation for fuzzy rule constructed with the Kosinski's Fuzzy Number (KFN) is proposed.
Abstract: The Kosinski’s Fuzzy Number (KFN) model (former name the Ordered Fuzzy Number) is a tool for processing an imprecise information interpreted in a similar way as the classical convex fuzzy numbers. The specificity of KFNs is an additional property for the fuzzy number—the direction. Thanks to that, the calculations can be done as flexibly as with real numbers. Especially, we are not doomed to get the more fuzzy results after many arithmetical operations. Apart good calculations, the direction also has additional potential in the interpretation of fuzzy data. It can be treated as a direction of process, not only the value. For example “an income is high and process is growing” is a different situation than “an income is high, but process is lowering”. The direction of KFN can be used to represent difference between these sentences. Since we deal with an additional information, there is need for the new methods which let benefit a full potential of KFNs in the modeling of linguistic data. This paper introduces algorithm of the inference operation for fuzzy rule constructed with the KFNs. Presented proposal consider the direction of values in processing. It bases on the ideas presented in previous studies on this subject—the Direction Determinant. It was proposed as the general basic tool for defining methods, where we need sensitivity for the direction.

22 citations


Book ChapterDOI
TL;DR: This paper introduces a model-driven approach for the analysis of IoT applications via simulation, and standard modeling languages, code generation, and network simulation and visualization are combined into an integrated development environment for rapid and automated analysis.
Abstract: The Internet of Things (IoT) refers to the networked interconnection of objects equipped with ubiquitous intelligence, or simply “smart objects”. The “smart” part is often followed by words like grid, home, parking, etc., to identify the application domain, and it is provided by software applications and/or services running on top of these large-scale distributed communication infrastructures. Heterogeneity and distribution scale speak for the complexity of such systems and call for a careful analysis prior to any deployment on target environments. In this paper we introduce a model-driven approach for the analysis of IoT applications via simulation. Standard modeling languages, code generation, and network simulation and visualization are combined into an integrated development environment for rapid and automated analysis.

21 citations


Book ChapterDOI
TL;DR: The paper presents the present state-of-the-art of a component importance analysis for complex technical systems, using a sea vessel as an example of the complex technical system and described some factors influencing importance of the technical system components.
Abstract: The paper presents the present state-of-the-art of a component importance analysis for complex technical systems. We used a sea vessel as an example of the complex technical system. We showed selected statistics of ship operation losses. We highlighted a necessity of further development of importance analysis methods for machinery operation. We presented a description and diagrams of qualitative and quantitative importance analysis. We pointed out the most significant problems of complex technical systems modelling. We introduced a multi-criteria system component importance analysis. Basic criteria for a system component quality evaluation have been presented. We described some factors influencing importance of the technical system components.

19 citations


Book ChapterDOI
TL;DR: The goal of this survey is to present a comprehensive review of the recent literature on the various possible energy harvesting technologies from ambient environment for WSNs.
Abstract: In recent years, wireless sensor networks (WSNs) have grown dramatically and made a great progress in many applications. But having limited life, batteries, as the power sources of wireless sensor nodes, have restricted the development and application of WSNs which often requires a very long lifespan for better performance. In order to make the WSNs prevalent in our lives, an alternative energy source is required. Environmental energy is an attractive power source, and it provides an approach to make the sensor nodes self-powered with the possibility of an almost infinite lifetime. The goal of this survey is to present a comprehensive review of the recent literature on the various possible energy harvesting technologies from ambient environment for WSNs.

19 citations


Book ChapterDOI
TL;DR: This research investigated the possible internal traffic flow pattern and evaluated network performance of each pattern on OpenStack cloud computing environment to estimate parameter related to network performance such as throughput, package loss, time and delay of data transmission.
Abstract: Cloud computing has become popular in IT technology because of advantages that focus on flexible, scaling, resources and services which help customers easy to build their own on-demand IT system. Cloud computing also has ability to balance, share, and manage IT resources between customers to get better performance. OpenStack, a new open source cloud computing framework which was a built-in modular architecture and focus on IaaS. OpenStack also focuses on NaaS by using network virtualization technology and OpenStack has been used popular in business. This paper does a research on network performance on OpenStack network module code name Neutron. The parameter related to network performance such as throughput, package loss, time and delay of data transmission are estimated through UDP protocol. Our research investigated the possible internal traffic flow pattern and evaluated network performance of each pattern on OpenStack cloud computing environment.

17 citations


Book ChapterDOI
TL;DR: A robust cover content extraction andembedding technique that trades off between visual quality and embedding capacity is proposed and demonstrates that the proposed technique is better than the exiting techniques.
Abstract: A robust cover content extraction and embedding technique that trades off between visual quality and embedding capacity is proposed in this paper. In addition, adaptive quantization is used to achieve higher capacity of embedding with good visual quality. In this technique we are using Discrete Wavelet Transform (DWT) plus adaptive quantization to reduce noise over modification. Here, secret data is embedded into Non-zero quantized coefficients. By using this technique, we achieve approximately 0.99 Normalization Cross Coefficient (NCC) and Peak Signal-to-Noise Ratio (PSNR ≈ 60–70 dB). Comparison of results demonstrates that the proposed technique is better than the exiting techniques.

Book ChapterDOI
TL;DR: In this paper, the authors used the data from Indiastat.com from all states and Union Territories of India for the years 2001 and 2011 to establish the relationship between infant mortality rate and some of the above mentioned factors along with a few healthcare infrastructure related variables.
Abstract: While there are enough efforts by the governments to reduce the infant mortality rate in developing countries, the results are not as desired. India is no exception to the case. Identifying the factors that affect the infant mortality rates would help in better targeting of the programs leading to enhanced efficiency of such programs. Earlier studies have shown the influence of socio economic factors on infant mortality rates at a global level and found that variables like fertility rate, national income, women in labour force, expenditure on health care and female literacy rates influence the infant mortality rates. The current study using the data from Indiastat.com from all states and Union Territories of India for the years 2001 and 2011 tries to establish the relationship between infant mortality rate and some of the above mentioned factors along with a few healthcare infrastructure related variables. Using a regression analysis method we not only identify the influence of the variables on infant mortality, we went a step further in identifying the performance of states and union territories in reducing IMR. The performance was measured using ‘technical efficiency’ analysis. We then compared the performance and growth rate of IMR to classify the states as good performers and laggards. Our results suggest that most of the major states are on track on their performance on IMR. However, a few small states and union territories like Andaman and Nicobar Island, Mizoram, Arunachal Pradesh as well as Jammu & Kashmir need special attention and targeting to reduce IMR.

Book ChapterDOI
TL;DR: Software Defined Networking (SDN) based continuous time modeling techniques are introduced to perform virtual machine migration and MTD techniques while maintaining high service availability and system security.
Abstract: Moving Target Defense (MTD) has emerged as a good solution to deal with dynamic attack surface. The goal is to make it difficult for an attacker to exploit network resources. But it is challenging to provide zero downtime guarantees when performing network rearrangement or when a physical host acts as a single point of failure for virtual servers. In this paper, we introduce Software Defined Networking (SDN) based continuous time modeling techniques to perform virtual machine migration and MTD techniques while maintaining high service availability and system security. This solution will not only increase attackers uncertainty but will also provide low downtime and high availability guarantee for the network.

Book ChapterDOI
TL;DR: The proposed method to use aerial images, which are already available from online databases such as GoogleMaps™, as reference map and to match images taken with a downward looking camera with this map to make it invariant to lighting/weather changes as well as seasonal variations or minor changes in the environment.
Abstract: In this paper we investigate the benefit of terrain classification for self-localization of a flying robot. The key idea is to use aerial images, which are already available from online databases such as GoogleMaps™, as reference map and to match images taken with a downward looking camera with this map. Using different terrain classes as features, we can make sure that our method is invariant to lighting/weather changes as well as seasonal variations or minor changes in the environment. A particle filter is used to register the query image with parts of the map. The proposed method has shown to work on image data from both simulated and real flights.

Book ChapterDOI
TL;DR: A survey of literature on the offline handwritten writer identification/verification with the type of data, features and classification approaches attempted till date in different languages and scripts is presented.
Abstract: In forensic science different unique bio-metric information of humans are being used to analyses forensic evidence like finger print, signature, retina scan etc The same can be used applied on handwriting analysis The Automatic Writer Identification and Verification (AWIV) is a study which combines forensic analysis field and computer vision and pattern recognition field This paper presents a survey of literature on the offline handwritten writer identification/verification with the type of data, features and classification approaches attempted till date in different languages and scripts The analysis of the approaches has been described for further enhancement and adaptation of these techniques in different languages and scripts

Book ChapterDOI
TL;DR: A description of the mobile, ubiquitous, and pervasive learning (MUP-Learning) arena is presented through the selection of a sample of recent and transcendent works that offer from a conceptual contribution, such as models and frameworks, even empirical approaches oriented to specific domains of study.
Abstract: This chapter tailors a perspective of the work fulfilled in three learning research lines, which besides holding many common attributes also tend to converge to shape mobile, ubiquitous, and pervasive sceneries. Such a junction pursues to spread the traditional classroom and distance settings to open environments, as well as use the surrounding physical and digital objects as learning content that is available to learners at anytime, anywhere, and in any way. In sum, a complete learning environment is recreated to provide formal and informal learning to support academic studies, professional training, and lifelong learning. Thus, in this chapter a description of the mobile, ubiquitous, and pervasive learning (MUP-Learning) arena is presented through the selection of a sample of recent and transcendent works that offer from a conceptual contribution, such as models and frameworks, even empirical approaches oriented to specific domains of study. The sample of works is characterized according to a proposed pattern, as well as organized according to a suggested taxonomy. A profile to describe each work is also stated and a series of statistics are presented, as well as an analysis of the arena is provided to understand the potential and challenges related to the MUP-Learning field.

Book ChapterDOI
TL;DR: This paper attempts to employ dynamic energy management on a Grid-Connected Smart Microgrid energized by a Micro Hydro Power Plant sans governor control to accomplishing the frequency control without perturbing the controlling facility in the conventional grid.
Abstract: Penetration of renewable energy-based microgrids onto the legacy grid is in demand to solve the global energy problems and the environmental issues. This paper attempts to employ dynamic energy management on a Grid-Connected Smart Microgrid (GCSMG) energized by a Micro Hydro Power Plant (MHPP) sans governor control. Frequency control of such SMGs poses a challenge as the latter is distributed. The concept of Dynamic Energy Management (DEM) plays a significant role in accomplishing the frequency control without perturbing the controlling facility in the conventional grid. DEM is a concept of controlling the charge–discharge transactions on the energy storage modules to oppose the frequency excursions on the grid. Support Vector Machine (SVM) algorithm is employed to automate DEM operation. The Dynamic Energy Management System (DEMS) is implemented on a Field Programmable Gate Array (FPGA) as the response time is critical for this application. The DEM scheme is validated on the SMG simulator in the Renewable Energy Laboratory of Amrita Vishwa Vidyapeetham University, Coimbatore.

Book ChapterDOI
TL;DR: Experimental results show the multilayer feedforward perceptron discriminates and detects faces from non-face patterns irrespective of the illumination changes.
Abstract: The paper proposes a face detection system that locates and extracts faces from the background using the multilayer feedforward perceptron. Facial features are extracted from the local image using filters. In this approach, feature vector from Gabor filter acts as an input for the multilayer feedforward perceptron. The points holding high information on face image are used for extraction of feature vectors. Since Gabor filter extracts features from varying scales and orientations, the feature points are extracted with high accuracy. Experimental results show the multilayer feedforward perceptron discriminates and detects faces from non-face patterns irrespective of the illumination changes.

Book ChapterDOI
TL;DR: A new 2-level hierarchical dictionary structure for classification such that the dictionary at the higher level is utilized to classify the K classes of documents and the results show around an 85% recall during the classification phase.
Abstract: Classification, clustering of documents, detecting novel documents, detecting emerging topics etc in a fast and efficient way, is of high relevance these days with the volume of online generated documents increasing rapidly. Experiments have resulted in innovative algorithms, methods and frameworks to address these problems. One such method is Dictionary Learning. We introduce a new 2-level hierarchical dictionary structure for classification such that the dictionary at the higher level is utilized to classify the K classes of documents. The results show around an 85% recall during the classification phase. This model can be extended to distributed environment where the higher level dictionary should be maintained at the master node and the lower level ones should be kept at worker nodes.

Book ChapterDOI
TL;DR: The main aim of this research is to do sequential tagging for Indian languages based on the unsupervised features and distributional information of a word with its neighboring words.
Abstract: Indian languages have very less linguistic resources, though they have a large speaker base They are very rich in morphology, making it very difficult to do sequential tagging or any type of language analysis In natural language processing, parts-of-speech (POS) tagging is the basic tool with which it is possible to extract terminology using linguistic patterns The main aim of this research is to do sequential tagging for Indian languages based on the unsupervised features and distributional information of a word with its neighboring words The results of the machine learning algorithms depend on the data representation Not all the data contribute to creation of the model, leading a few in vain and it depends on the descriptive factors of data disparity Data representations are designed by using domain-specific knowledge but the aim of Artificial Intelligence is to reduce these domain-dependent representations, so that it can be applied to the domains which are new to one Recently, deep learning algorithms have acquired a substantial interest in reducing the dimension of features or extracting the latent features Recent development and applications of deep learning algorithms are giving impressive results in several areas mostly in image and text applications

Book ChapterDOI
TL;DR: The work done in this paper provides a Proof of Concept (POC) for the better throughput of SDN-based routing.
Abstract: Network is growing day by day. New devices are getting added into the network making it very difficult for an IT administrator to configure the ACLs and the other network parameters in the devices. Flexibility and programmability are the key factors in the present day scenario. Software Defined Networks (SDN) is the evolving network technology which provides the two factors mentioned. The latency in the packet delivery is less compared to the legacy Hardware Defined Networks (HDN) and in turn the throughput is also high. The work done in this paper provides a Proof of Concept (POC) for the better throughput of SDN-based routing.

Book ChapterDOI
TL;DR: The various security mechanisms and protocols are discussed in both VANET and MANET for secure data transmission and their exploitation in various layers are analyzed.
Abstract: Ad hoc wireless communication is an infrastructure-less network and adaptable to all environments. It is characterized by self-organizing, dynamic topology, and self-healing. These characteristics are most common for both MANET and VANET. In these networks, security is a major concern for data transmission. Ad hoc security is violated by various security attacks. In this paper, we are analyzing the common security attacks and their exploitation in various layers. The various security mechanisms and protocols are discussed in both VANET and MANET for secure data transmission.

Book ChapterDOI
TL;DR: In this article, a generic algorithm for peg-in-hole assembly tasks is suggested, which is applied in the project GINKO were the aim is to connect electric vehicles with charging stations automatically.
Abstract: In this paper, a generic algorithm for peg-in-hole assembly tasks is suggested. It is applied in the project GINKO were the aim is to connect electric vehicles with charging stations automatically. This paper explains an algorithm applicable for peg-in-hole tasks by means of Cartesian impedance controlled robots. The plugging task is a specialized peg-in-hole task for which 7 pins have to be aligned simultaneously and the peg and the hole have asymmetric shapes. In addition significant forces are required for complete insertion. The initial position is inaccurately estimated by a vision system. Hence, there are translational and rotational uncertainties between the plug, carried by the robot and the socket, situated on the E-car. To compensate these errors three different steps of Cartesian impedance control are performed. To verify our approach we evaluated the algorithm from many different start positions.

Book ChapterDOI
TL;DR: An efficient wireless charging system based on resonant magnetic coupling that contains single-stage boost rectifier at receiver that is analyzed for different coupling factors of the inductive links and for different loads.
Abstract: Advancements in power electronics have aided in the development of inductive power transfer technologies by providing transmitter coil drivers and converters for conditioning the power received at the receiver coil. But the use of traditional two-stage circuit with half wave or full wave rectifiers and boost converter at the receiver side may be inefficient, as it reduces the total power delivered to the load. As an alternative, single-stage boost rectifier can be used, which is compact and more efficient. This paper introduces an efficient wireless charging system based on resonant magnetic coupling that contains single-stage boost rectifier at receiver. Single-stage rectification and boosting is made possible by the bidirectional conduction capability of MOSFETs. The system is designed and simulated in PSIM software. The overall power transfer efficiency of the system is analyzed for different coupling factors of the inductive links and for different loads.

Journal Article
TL;DR: The main contribution of the work presented in this paper is to attempt to fill this void by presenting a survey of some existing scientific contributions dealing with time in information systems.
Abstract: In existing literature, many proposals have concerned the modeling or handling of imperfection in time in information systems. However, although reviews, surveys and overviews about either imperfection or time in information systems exist, no reviews, surveys or overviews about imperfection in time in information systems seem to exist. The main contribution of the work presented in this paper is to attempt to fill this void by presenting a survey of some existing scientific contributions dealing with time in information systems. A more modest contribution is an attempt at identifying some open research challenges or opportunities concerning imperfection in time in information systems.

Book ChapterDOI
TL;DR: The goal is to propose an archi-tecture that measures the level of attentiveness in real scenario, and detect patterns of behavior in different attention levels among different students.
Abstract: In this article we focus on a new field of application of ICT techniques and technologies in learning activities. With these activities with computer platforms, attention allows us to break down the problem of understanding a speculative scenario into a series of computationally less demanding and localized lack of attention. The system considers the students’ attention level while performing a task in learning activities. The goal is to propose an archi-tecture that measures the level of attentiveness in real scenario, and detect patterns of behavior in different attention levels among different students. Measurements of attention level are obtained by a proposed model, and user for training a decision support system that in a real scenario makes recommendations for the teachers so as to prevent undesirable behavior.

Book ChapterDOI
TL;DR: This paper proposes a new approach by integrating UML and Z notation, a formal specification language for capturing both the syntax and semantics of a system, particularly for safety critical system.
Abstract: The two most critical phases of SDLC are the specification and the designing phase as they involve the transformation of the semantics from real world domain to computer software systems. Unified Modelling Language (UML) has been accepted as blue print for design and specification of software critical systems. But, UML structures have the weakness in preciously defining the semantics of a system. Any misinterpretation in safety critical system’s specification may risks loss of lives. Formal methods are mathematical tools and techniques which are proven very adequate, principally, at requirement specification and design level. However, formal methods are not welcomed because of rigorous use of mathematics. Therefore, a bridge is required between UML and formal methods to overcome the above insufficiencies. The endeavour of this paper is to propose a new approach by integrating UML and Z notation, a formal specification language. The main focus of this paper is on transforming the UML diagram: use case diagram, class diagram and sequence diagram to Z Schema for capturing both the syntax and semantics, particularly for safety critical system. The resultant formal model of the approach are analyzed and verified by using Z/Eves tool.

Book ChapterDOI
TL;DR: This work applies effective reasoning methods to make inferences over a Learning Process Knowledge-Base that leads to automated discovery of learning patterns/behaviour.
Abstract: Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respond by making decision based on adaptive rules centred on captured user profiles. The method applies semantic rules and description logic queries to build ontology model capable of automatically computing the various learning activities within a Learning Knowledge-Base, and to check the consistency of learning object/data types. The approach is grounded on inductive and deductive logic descriptions that allows the use of a Reasoner to check that all definitions within the learning model are consistent and can also recognise which concepts that fit within each defined class. Inductive reasoning is practically applied in order to discover sets of inferred learner categories, while deductive approach is used to prove and enhance the discovered rules and logic expressions. Thus, this work applies effective reasoning methods to make inferences over a Learning Process Knowledge-Base that leads to automated discovery of learning patterns/behaviour.

Book ChapterDOI
TL;DR: The algorithm discussed in this paper uses a combination of Dynamic Time Warping (DTW) and prosody manipulation to inter-convert emotions among one another and compares with neutral to emotion conversion using objective and subjective performance indices.
Abstract: The objective of this work is to explore the importance of parameters contributing to synthesis of expression in vocal communication. The algorithm discussed in this paper uses a combination of Dynamic Time Warping (DTW) and prosody manipulation to inter-convert emotions among one another and compares with neutral to emotion conversion using objective and subjective performance indices. Existing explicit control methods are based on prosody modification using neutral speech as starting point and have not explored the possibility of conversion between inter-related emotions. Also, most of the previous work relies entirely on perception tests for evaluation of speech quality post synthesis. In this paper, the objective comparison in terms of error percentage is verified with forced choice perception test results. Both indicate the effectiveness of inter-emotion conversion by speech with better quality. The same is also depicted by synthesis results and spectrograms.

Book ChapterDOI
TL;DR: It was identified that Mobile Sandbox tool is the best when time factor is not considered because it possess the capability of both a static and dynamic analysis, native API call tracking and web accessibility.
Abstract: The expeditious growth of Android malwares has posed a serious challenge in front of researchers. The researchers are continuously proposing countermeasures and developing tools to mitigate against such attacks. In this paper, widely used techniques that have been proposed recently by researchers have been explored. The key contributions of each of these techniques along with their limitations have been analyzed. All these techniques were compared based on nine parameters and it was identified that Mobile Sandbox tool is the best when time factor is not considered because it possess the capability of both a static and dynamic analysis, native API call tracking and web accessibility. If time factor is considered, then Dendroid performs best among all. This is due to the reason that it applies text mining to get the signature of malware and it can also classify unknown malware sample through 1-NN classifier.