Query: Cartesian Cubical Computational Type Theory: Constructive Reasoning with Paths and Equalities

Relevant passages:
Computational higher-dimensional type theory <=SEP=> Formal constructive type theory has proved to be an effective language for mechanized proof. By avoiding non-constructive principles, such as the law of the excluded middle, type theory admits sharper proofs and broader interpretations of results. From a computer science perspective, interest in type theory arises from its applications to programming languages. Standard constructive type theories used in mechanization admit computational interpretations based on meta-mathematical normalization theorems. These proofs are notoriously brittle; any change to the theory potentially invalidates its computational meaning. As a case in point, Voevodsky's univalence axiom raises questions about the computational meaning of proofs. 
 We consider the question: Can higher-dimensional type theory be construed as a programming language? We answer this question affirmatively by providing a direct, deterministic operational interpretation for a representative higher-dimensional dependent type theory with higher inductive types and an instance of univalence. Rather than being a formal type theory defined by rules, it is instead a computational type theory in the sense of Martin-Löf's meaning explanations and of the NuPRL semantics. The definition of the type theory starts with programs; types are specifications of program behavior. The main result is a canonicity theorem stating that closed programs of boolean type evaluate to true or false.

Computational Higher Type Theory IV: Inductive Types <=SEP=> This is the fourth in a series of papers extending Martin-Löf’s meaning explanation of dependent type theory to higher-dimensional types. In this installment, we show how to define cubical type systems supporting a general schema of indexed cubical inductive types whose constructors may take dimension parameters and have a specified boundary. Using this schema, we are able to specify and implement many of the higher inductive types which have been postulated in homotopy type theory, including homotopy pushouts, the torus, W-quotients, truncations, arbitrary localizations. By including indexed inductive types, we enable the definition of identity types. The addition of higher inductive types makes computational higher type theory a model of homotopy type theory, capable of interpreting almost all of the constructions in the HoTT Book [40] (with the exception of inductive-inductive types). This is the first such model with an explicit canonicity theorem, which specifies the canonical values of higher inductive types and confirms that every term in an inductive type evaluates to such a value.

A Model of Type Theory in Cubical Sets <=SEP=> We present a model of type theory with dependent product, sum, and identity, in cubical sets. We describe a universe and explain how to transform an equivalence between two types in an equality. We also explain how to model propositional truncation and the circle. While not expressed internally in type theory, the model is expressed in a constructive metalogic. Thus it is a step towards a computational interpretation of Voevodsky’s Univalence Axiom.

Cubical Type Theory: A Constructive Interpretation of the Univalence Axiom <=SEP=> This paper presents a type theory in which it is possible to directly manipulate n-dimensional cubes (points, lines, squares, cubes, etc.) based on an interpretation of dependent type theory in a cubical set model. This enables new ways to reason about identity types, for instance, function extensionality is directly provable in the system. Further, Voevodsky’s univalence axiom is provable in this system. We also explain an extension with some higher inductive types like the circle and propositional truncation. Finally we provide semantics for this cubical type theory in a constructive meta-theory. 1998 ACM Subject Classification F.3.2 Logics and Meanings of Programs: Semantics of Programming Languages, F.4.1 Mathematical Logic and Formal Languages: Mathematical Logic

A Monolithic CMOS-MEMS 3-Axis Accelerometer With a Low-Noise, Low-Power Dual-Chopper Amplifier <=SEP=> This paper reports a monolithically integrated CMOS-MEMS three-axis capacitive accelerometer with a single proof mass. An improved DRIE post-CMOS MEMS process has been developed, which provides robust single-crystal silicon (SCS) structures in all three axes and greatly reduces undercut of comb fingers. The sensing electrodes are also composed of the thick SCS layer, resulting in high resolution and large sensing capacitance. Due to the high wiring flexibility provided by the fabrication process, fully differential capacitive sensing and common-centroid configurations are realized in all three axes. A low-noise, low- power dual-chopper amplifier is designed for each axis, which consumes only 1 mW power. With 44.5 dB on-chip amplification, the measured sensitivities of x-, y-, and z-axis accelerometers are 520 mV/g, 460 mV/g, and 320 mV/g, respectively, which can be tuned by simply changing the amplitude of the modulation signal. Accordingly, the overall noise floors of the x-, y-, and z-axis are 12 mug/radicHz , 14 mug/radicHz, and 110 mug/radicHz, respectively, when tested at around 200 Hz.

Cyber security of smart grids modeled through epidemic models in cellular automata <=SEP=> Due to their distributed management, smart grids can be vulnerable to malicious attacks that undermine their cyber security. An adversary can take control of few nodes in the network and spread digital attacks like an infection, whose diffusion is facilitated by the lack of centralized supervision within the smart grid. In this paper, we propose to investigate these phenomena by means of epidemic models applied to cellular automata. We show that the common key parameters of epidemic models, such as the basic reproductive ratio, are also useful in this context to understand the extent of the grid portion that can be compromised. At the same time, the lack of mobility of individuals limits the spreading of the infection. In particular, we evaluate the role of the grid connectivity degree in both containing the epidemics and avoiding its spreading on the entire network, and also increasing the number of nodes that do not get any contact with the cyber attacks.

A review of overview+detail, zooming, and focus+context interfaces <=SEP=> There are many interface schemes that allow users to work at, and move between, focused and contextual views of a dataset. We review and categorize these schemes according to the interface mechanisms used to separate and blend views. The four approaches are overview+detail, which uses a spatial separation between focused and contextual views; zooming, which uses a temporal separation; focus+context, which minimizes the seam between views by displaying the focus within the context; and cue-based techniques which selectively highlight or suppress items within the information space. Critical features of these categories, and empirical evidence of their success, are discussed. The aim is to provide a succinct summary of the state-of-the-art, to illuminate both successful and unsuccessful interface strategies, and to identify potentially fruitful areas for further work.

An Experiment of Influences of Facebook Posts in Other Users <=SEP=> People usually present similar behavior of their friends due to the social influence that is produced by group pressure. This factor is also present in online social networks such as Facebook. In this paper, we make a study on social influence produced by the contents published on Facebook. First, we have executed a systematic literature review of the previous works to understand better this field of research. Then, by executing the Asch experiment, we have illustrated how such social influence can change the behavior of users in Facebook. Through this experiment, we could identify how the social influence type called “conformity” is present in online social network platforms and how this influence can make changes in the behavior of people.

Use of the stair vision library within the ISPRS 2D semantic labeling benchmark (Vaihingen) <=SEP=> This report describes experiments conducted using the multi-class image classification framework implemented in the stair vision library (SVL, (Gould et al., 2008)) in the context of the ISPRS 2D semantic labeling benchmark. The motivation was to get results from a well-established and public available software (Gould, 2014), as a kind of baseline. Besides the use of features implemented in the SVL which makes use of three channel images, assuming RGB, we also included features derived from the height model and the NDVI which is specific here, because the benchmark dataset provides surface models and CIR images. Another point of interest concerned the impact the segmentation had on the overall result. To this end a pre-study was performed where different parameters for the graph-based segmentation method introduced by Felzenszwalb and Huttelocher (2004) have been tested, in addition we only applied a simple chessboard segmentation. Other experiments focused on the question whether the conditional random field classification approach helps to enhance the overall performance. The official evaluation of all experiments described here is available at http://www2.isprs.org/vaihingen-2d-semantic-labeling-contest.html (SVL_1 to SVL_6). The normalized height models are available through the ReseachGate profile of the author (http://www.researchgate.net/profile/Markus_Gerke)

Rollable Multisegment Dielectric Elastomer Minimum Energy Structures for a Deployable Microsatellite Gripper <=SEP=> Debris in space presents an ever-increasing problem for spacecraft in Earth orbit. As a step in the mitigation of this issue, the CleanSpace One (CSO) microsatellite has been proposed. Its mission is to perform active debris removal of a decommissioned nanosatellite (the CubeSat SwissCube). An important aspect of this project is the development of the gripper system that will entrap the capture target. We present the development of rollable dielectric elastomer minimum energy structures (DEMES) as the main component of CSO's deployable gripper. DEMES consist of a prestretched dielectric elastomer actuator membrane bonded to a flexible frame. The actuator finds equilibrium in bending when the prestretch is released and the bending angle can be changed by the application of a voltage bias. The inherent flexibility and lightweight nature of the DEMES enables the gripper to be stored in a rolled-up state prior to deployment. We fabricated proof-of-concept actuators of three different geometries using a robust and repeatable fabrication methodology. The resulting actuators were mechanically resilient to external deformation, and display conformability to objects of varying shapes and sizes. Actuator mass is less than 0.65 g and all the actuators presented survived the rolling-up and subsequent deployment process. Our devices demonstrate a maximum change of bending angle of more than 60° and a maximum gripping (reaction) force of 2.2 mN for a single actuator.

MSc THESIS Hardware Acceleration of BWA-MEM Genome Mapping Application <=SEP=> Faculty of Electrical Engineering, Mathematics and Computer Science CE-MS-2014 Next Generation Sequencing technologies have had a tremendous impact on our understanding of DNA and its role in living organisms. The cost of DNA sequencing has decreased drastically over the past decade, leading the way for personalised genomics. Sequencers provide millions of fragments of DNA (termed short reads), which have to be aligned aginst a reference genome to reconstruct the full information of the DNA molecule under study. Processing short reads requires large computational resources, with many specialised computing platforms now being used to accelerate software aligners. We take up the challenge of accelerating a well know sequence alignment tool called Burrows Wheeler aligner on the Convey Hybrid Computing platform, which has FPGAs as co-processors. The focus of the research is to accelerate the BWA-MEM algorithm of the Burrows Wheeler aligner on the Convey HC-2 platform. The implementation was carried out using the Vivado HLS tool. The architectures proposed are targeted to overcome the memory bottleneck of the application. Two architectures are proposed, the Base architecture and the Batch architecture meant to address the memory bottleneck. Simulations were performed for the intended platform and it was found that, the Batch architecture is 18% faster than the Base architecture for reads with similar run time characteristics. The architectures provide possibilities of further pipelining and implementation of more cores, which is expected to provide better performance than the current implementation. Hardware Acceleration of BWA-MEM Genome Mapping Application

Performance Gaps between OpenMP and OpenCL for Multi-core CPUs <=SEP=> OpenCL and OpenMP are the most commonly used programming models for multi-core processors. They are also fundamentally different in their approach to parallelization. In this paper, we focus on comparing the performance of OpenCL and OpenMP. We select three applications from the Rodinia benchmark suite (which provides equivalent OpenMP and OpenCL implementations), and carry out experiments with different datasets on three multi-core platforms. We see that the incorrect usage of the multi-core CPUs, the inherent OpenCL fine-grained parallelism, and the immature OpenCL compilers are the main reasons that lead to the OpenCL poorer performance. After tuning the OpenCL versions to be more CPU-friendly, we show that OpenCL either outperforms or achieves similar performance in more than 80% of the cases. Therefore, we believe that OpenCL is a good alternative for multi-core CPU programming.

Alternative placement of bispectral index electrode for monitoring depth of anesthesia during neurosurgery. <=SEP=> In neurosurgery in particular, the recommended placement of electrodes for monitoring depth of anesthesia during surgery sometimes conflicts with the surgical site or patient positioning. Therefore, we proposed this study to evaluate the agreement and correlation of bispectral index values recorded from the usual frontal area and the alternate, post-auricular areas in neurosurgery patients. Thirty-four patients scheduled for neurosurgery under general anesthesia were included. Bispectral index (BIS) sensors were placed at both the frontal and post-auricular areas. The anesthesia given was clinically adjusted according to the frontal (standard) BIS reading. The BIS values and impedance were recorded;Pearson's correlation and Bland-Altman plots were analyzed. The bias±2SD for the electrode placement before, during, and post-anesthesia were 0±23.32, 1.5±10.69, and 2.1±13.52, while the limits of agreement were -23.3 to 23.3, -12.2 to 9.2, and -17.7 to 13.5, respectively. The correlation coefficient between frontal- and post-auricular-area electrodes was 0.74 with a p-value<0.001.The post-auricular placement of a BIS electrode is a practical alternative to frontal lobe placement. Nevertheless, proper electrode location is important to minimize error.

A survey on virtual machine migration and server consolidation frameworks for cloud data centers <=SEP=> Modern Cloud Data Centers exploit virtualization for efficient resource management to reduce cloud computational cost and energy budget. Virtualization empowered by virtual machine (VM) migration meets the ever increasing demands of dynamic workload by relocating VMs within Cloud Data Centers. VM migration helps successfully achieve various resource management objectives such as load balancing, power management, fault tolerance, and system maintenance. However, being resourceintensive, the VM migration process rigorously affects application performance unless attended by smart optimization methods. Furthermore, a Cloud Data Centre exploits server consolidation and DVFS methods to optimize energy consumption. This paper reviews state-of-the-art bandwidth optimization schemes, server consolidation frameworks, DVFS-enabled power optimization, and storage optimization methods over WAN links. Through a meticulous literature review of state-of-the-art live VM migration schemes, thematic taxonomies are proposed to categorize the reported literature. The critical aspects of virtual machine migration schemes are investigated through a comprehensive analysis of the existing schemes. The commonalties and differences among existing VM migration schemes are highlighted through a set of parameters derived from the literature. Finally, open research issues and trends in the VM migration domain that necessitate further consideration to develop optimal VM migration schemes

Assessing SMS and PJD Schemes of Anti-Islanding with Varying Quality Factor <=SEP=> When a particular zone of the distribution network containing an embedded generator is disconnected from the main supply grid, yet the generator continues to operate with normal voltage and frequency to feed power to the isolated section, islanding is said to occur. In a distributed power system, islanding may occur at different possible zones consisting of distribution feeders, substations and voltage levels as long as the isolated zone is found to operate independently of the main grid but remained energized by the distributed generation unit. To ensure safety and reliability, it is necessary to detect islanding condition as quickly as possible by using anti-islanding algorithms. Among the available islanding prevention methods, slip mode frequency shift (SMS) and phase jump detection (PJD) schemes are very common and have numerous advantages over others. This paper presents detailed discussion and comparison of the characteristics of the various anti-islanding schemes. Both SMS and PJD techniques are examined in detail through design and simulation. In the islanding situation with quality factor range (0.1les Qf les10), load voltage waveforms are analyzed and plotted. Both the methods are assessed in terms of detection times with different Qf's. The results are complying with IEEE standard specifications and show that the two developed algorithms could prevent islanding more consistently.

Adaptive Image Registration via Hierarchical Voronoi Subdivision <=SEP=> Advances in image acquisition systems have made it possible to capture high-resolution images of a scene, recording considerable scene details. With increased resolution comes increased image size and geometric difference between multiview images, complicating image registration. Through Voronoi subdivision, we subdivide large images into small corresponding regions, and by registering small regions, we register the images in a piecewise manner. Image subdivision reduces the geometric difference between regions that are registered and simplifies the correspondence process. The proposed method is a hierarchical one. While previous methods use the same block size and shape at a hierarchy, the proposed method adapts the block size and shape to the local image details and geometric difference between the images. This adaptation makes it possible to keep geometric difference between corresponding regions small and simplifies the correspondence process. Implementational details of the proposed image registration method are provided, and experimental results on various types of images are presented and analyzed.

Augmented Human: Augmented Reality and Beyond <=SEP=> Will Augmented Reality (AR) allow us to access digital information, experience others' stories, and thus explore alternate realities? AR has recently attracted attention again due to the rapid advances in related multimedia technologies as well as various glass-type AR display devices. However, in order to widely adopt AR in alternated realities, it is necessary to improve various core technologies and integrate them into an AR platform. Especially, there are several remaining technical challenges such as 1) real-time recognition and tracking of multiple objects while generating an environment map, 2) organic user interface with awareness of user's implicit needs, intentions or emotion as well as explicit requests, 3) immersive multimodal content augmentation and just-in-time information visualization, 4) multimodal interaction and collaboration during augmented telecommunication, etc. In addition, in order to encourage user engagement and enable an AR ecosystem, AR standards should be established that support creating AR content, capturing user experiences, and sharing the captured experiences.

Result Diversification in Automatic Citation Recommendation <=SEP=> The increase in the number of published papers each year makes manual literature search inefficient and furthermore insufficient. Hence, automatized reference/citation recommendation have been of interest in the last 3-4 decades. Unfortunately, some of the developed approaches, such as keyword-based ones, are prone to ambiguity and synonymy. On the other hand, using the citation information does not suffer from the same problems since they do not consider textual similarity. Today, obtaining the desired information is as hard as looking for a needle in a haystack. And sometimes, we want that small haystack, e.g., a small result set containing only a few recommendations, cover all the important and relevant parts of the literature. That is, the set should be diversified enough. Here, we investigate the problem of result diversification in automatic citation recommendation. We enhance existing techniques, which were designed to recommend a set of citations with satisfactory quality and diversity, with direction-awareness to allow the users to reach either old, well-cited, well-known research papers or recent, less-known ones. We also propose some novel techniques for a better result diversification. Experimental results show that our techniques are very useful in automatic citation recommendation.

Hull-form optimization in calm and rough water <=SEP=> The paper presents a formal methodology for the hull form optimization in calm and rough water using wash waves and selected dynamic responses, respectively. Parametric hull form modeling is used to generate the variant hull forms with some of the form parameters modified, which are evaluated in the optimization scheme based on evolutionary strategies. Rankine-source panel method and strip theories are used for the hydrodynamic evaluation. The methodology is implemented in the optimization of a double-chine, planing hull form. Furthermore, a dual-stage optimization strategy is applied on a modern fast displacement ferry. The effect of the selected optimization parameters is presented and discussed. Crown Copyright© 2009 Published by Elsevier Ltd. All rights reserved.

NewsVallum: Semantics-Aware Text and Image Processing for Fake News Detection system <=SEP=> As a consequence of the social revolution we faced on the Web, news and information we daily enjoy may come from different and diverse sources which are not necessarily the traditional ones such as newspapers, either in their paper or online version, television, radio, etc. Everyone on the Web is allowed to produce and share news which can soon become viral if they follow the new media channels represented by social networks. This freedom in producing and sharing news comes with a counter-effect: the proliferation of fake news. Unfortunately, they can be very effective and may influence people and, more generally, the public opinion. We propose a combined approach of natural language and image processing that takes into account the semantics encoded within both text and images coming with news together with contextual information that may help in the classification of a news as fake or not.

Supply chain risk management in French companies <=SEP=> Available online 22 November 2011

Bringing contextual information to google speech recognition <=SEP=> In automatic speech recognition on mobile devices, very often what a user says strongly depends on the particular context he or she is in. The n-grams relevant to the context are often not known in advance. The context can depend on, for example, particular dialog state, options presented to the user, conversation topic, location, etc. Speech recognition of sentences that include these n-grams can be challenging, as they are often not well represented in a language model (LM) or even include out-of-vocabulary (OOV) words. In this paper, we propose a solution for using contextual information to improve speech recognition accuracy. We utilize an on-the-fly rescoring mechanism to adjust the LM weights of a small set of n-grams relevant to the particular context during speech decoding. Our solution handles out of vocabulary words. It also addresses efficient combination of multiple sources of context and it even allows biasing class based language models. We show significant speech recognition accuracy improvements on several datasets, using various types of contexts, without negatively impacting the overall system. The improvements are obtained in both offline and live experiments.

SOFIA: An automated security oracle for black-box testing of SQL-injection vulnerabilities <=SEP=> Security testing is a pivotal activity in engineering secure software. It consists of two phases: generating attack inputs to test the system, and assessing whether test executions expose any vulnerabilities. The latter phase is known as the security oracle problem. 
 In this work, we present SOFIA, a Security Oracle for SQL-Injection Vulnerabilities. SOFIA is programming-language and source-code independent, and can be used with various attack generation tools. Moreover, because it does not rely on known attacks for learning, SOFIA is meant to also detect types of SQLi attacks that might be unknown at learning time. The oracle challenge is recast as a one-class classification problem where we learn to characterise legitimate SQL statements to accurately distinguish them from SQLi attack statements. 
 We have carried out an experimental validation on six applications, among which two are large and widely-used. SOFIA was used to detect real SQLi vulnerabilities with inputs generated by three attack generation tools. The obtained results show that SOFIA is computationally fast and achieves a recall rate of 100% (i.e., missing no attacks) with a low false positive rate (0.6%).

Crisis prevention: how to gear up your board. <=SEP=> Today's critics of corporate boardrooms have plenty of ammunition. The two crucial responsibilities of boards-oversight of long-term company strategy and the selection, evaluation, and compensation of top management--were reduced to damage control during the 1980s. Walter Salmon, a longtime director, notes that while boards have improved since he began serving on them in 1961, they haven't kept pace with the need for real change. Based on over 30 years of boardroom experience, Salmon recommends against government reform of board practices. But he does prescribe a series of incremental changes as a remedy. To begin with, he suggests limiting the size of boards and increasing the number of outside directors on them. In fact, according to Salmon, only three insiders belong on a board: the CEO, the COO, and the CFO. Changing how committees function is also necessary for gearing up today's boards. The audit committee, for example, can periodically review "high-exposure areas" of a business, perhaps helping to prevent embarrassing drops in future profits. Compensation committees can structure incentive compensation for executives to emphasize long-term rather than short-term performance. And nominating committees should be responsible for finding new, independent directors--not the CEO. In general, boards as a whole must spot problems early and blow the whistle, exercising what Salmon calls, "constructive dissatisfaction." On a revitalized board, directors have enough confidence in the process to vigorously challenge one another, including the company's chief executive.

Integrated CMOS transmit-receive switch using LC-tuned substrate bias for 2.4-GHz and 5.2-GHz applications <=SEP=> CMOS transmit-receive (T/R) switches have been integrated in a 0.18-/spl mu/m standard CMOS technology for wireless applications at 2.4 and 5.2 GHz. This switch design achieves low loss and high linearity by increasing the substrate impedance of a MOSFET at the frequency of operation using a properly tuned LC tank. The switch design is asymmetric to accommodate the different linearity and isolation requirements in the transmit and receive modes. In the transmit mode, the switch exhibits 1.5-dB insertion loss, 28-dBm power, 1-dB compression point (P/sub 1dB/), and 30-dB isolation, at 2.4 and 5.2 GHz. In the receive mode, the switch achieves 1.6-dB insertion loss, 11.5-dBm P/sub 1dB/, and 15-dB isolation, at 2.4 and 5.2 GHz. The linearity obtained in the transmit mode is the highest reported to date in a standard CMOS process. The switch passes the 4-kV Human Body Model electrostatic discharge test. These results show that the switch design is suitable for narrow-band applications requiring a moderate-high transmitter power level (<1 W).

Computational analysis of the safe zone for the antegrade lag screw in posterior column fixation with the anterior approach in acetabular fracture: A cadaveric study. <=SEP=> OBJECTIVE
The fluoroscopically-guided procedure of antegrade posterior lag screw in posterior column fixation through anterior approach is technique-dependent and requires an experienced surgeon. The purpose of this study was to establish the safe zone for the antegrade posterior lag screw by using computational analysis.


METHOD
The virtual three-dimensional model of 178 hemi-pelvises was created from the CT data (DICOM format) by using Mimics® program, and were used to measure the safe zone of antegrade lag screw fixation on the inner table of the iliac wing, and the largest diameter of cylindrical implant inside safe zone. The central point (point A) of the cylinder was assessed and was compared with the intersection point (point B) between the linea terminalis and the anterior border of the sacroiliac articulation.


RESULTS
The safe zone was triangular with an average area of 670.4mm2 (range, 374.8-1084.5mm2). The largest diameter of the cylinder was a mean 7.4mm (range, 5.0-10.0mm). When height was under 156.3cm, the diameter of the cylindrical implant was smaller than 7.0mm (p<0.001, regression coefficient=0.09). The linear distance between points A and B was 32.5mm (range, 19.2-49.3mm). Point A was far enough away from the well-positioned anterior column plate to prevent collision between the two.


CONCLUSION
The safe zone was shaped like a triangle, and was large enough for multiple screws. Considering the straight-line distance between points A and B, the central screw can be fixed without overlapping with the well-positioned anterior column plate at the point between holes 2 and 3.

Flexible capacitive sensors for high resolution pressure measurement <=SEP=> Thin, flexible, robust capacitive pressure sensors have been the subject of research in many fields where axial strain sensing with high spatial resolution and pressure resolution is desirable for small loads, such as tactile robotics and biomechanics. Simple capacitive pressure sensors have been designed and implemented on flexible substrates in general agreement with performance predicted by an analytical model. Two designs are demonstrated for comparison. The first design uses standard flex circuit technology, and the second design uses photolithography techniques to fabricate capacitive sensors with higher spatial and higher pressure resolution. Sensor arrays of varying sensor size and spacing are tested with applied loads from 0 to 1 MPa. Pressure resolution and linearity of the sensors are significantly improved with the miniaturized, custom fabricated sensor array compared to standard flexible circuit technology.

On optimal fuzzy c-means clustering for energy efficient cooperative spectrum sensing in cognitive radio networks <=SEP=> This work explores the scope of Fuzzy C-Means (FCM) clustering on energy detection based cooperative spectrum sensing (CSS) in single primary user (PU) cognitive radio network (CRN). PU signal energy sensed at secondary users (SUs) are forwarded to the fusion center (FC). Two different combining schemes, namely selection combining (SC) and optimal gain combining are performed at FC to address the sensing reliability problem on two different optimization frameworks. In the first work, optimal cluster center points are searched for using differential evolution (DE) algorithm to maximize the probability of detection under the constraint of meeting the probability of false alarm below a predefined threshold. Simulation results highlight the improved sensing reliability compared to the existing works. In the second one, the problem is extended to the energy efficient design of CRN. The SUs act here as amplifyand-forward (AF) relays and PU energy content is measured at the FC over the combined signal from all the SUs. The objective is to minimize the average energy consumption of all SUs while maintaining the predefined sensing ∗. Santi P. Maity . Email addresses: santipmaity@it.iiests.ac.in (Santi P. Maity ), subhankar.ece@gmail.com (Subhankar Chatterjee), t_acharya@telecom.iiests.ac.in (Tamaghna Acharya) Preprint submitted to Elsevier October 28, 2015 constraints. Optimal FCM clustering using DE determines the optimal SU amplifying gain and the optimal number of PU samples. Simulation results shed a light on the performance gain of the proposed approach compared to the existing energy efficient CSS schemes.

Exploiting semantic web knowledge graphs in data mining <=SEP=> Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in that field are knowledge intensive and can often benefit from using additional knowledge from various sources. Therefore, many approaches have been proposed in this area that combine Semantic Web data with the data mining and knowledge discovery process. Semantic Web knowledge graphs are a backbone of many information systems that require access to structured knowledge. Such knowledge graphs contain factual knowledge about real word entities and the relations between them, which can be utilized in various natural language processing, information retrieval, and any data mining applications. Following the principles of the Semantic Web, Semantic Web knowledge graphs are publicly available as Linked Open Data. Linked Open Data is an open, interlinked collection of datasets in machine-interpretable form, covering most of the real world domains. In this thesis, we investigate the hypothesis if Semantic Web knowledge graphs can be exploited as background knowledge in different steps of the knowledge discovery process, and different data mining tasks. More precisely, we aim to show that Semantic Web knowledge graphs can be utilized for generating valuable data mining features that can be used in various data mining tasks. Identifying, collecting and integrating useful background knowledge for a given data mining application can be a tedious and time consuming task. Furthermore, most data mining tools require features in propositional form, i.e., binary, nominal or numerical features associated with an instance, while Linked Open Data sources are usually graphs by nature. Therefore, in Part I, we evaluate unsupervised feature generation strategies from types and relations in knowledge graphs, which are used in different data mining tasks, i.e., classification, regression, and outlier detection. As the number of generated features grows rapidly with the number of instances in the dataset, we provide a strategy for feature selection in hierarchical feature space, in order to select only the most informative and most representative features for a given dataset. Furthermore, we provide an end-to-end tool for mining the Web of Linked Data, which provides functionalities for each step of the knowledge discovery process, i.e., linking local data to a Semantic Web knowledge graph, integrating features from multiple knowledge graphs, feature generation and selection, and building machine learning models. However, we show that such feature generation strategies often lead to high dimensional feature vectors even after