Miracle-dz/UniFAR-FTUs huggingface dataset:
Domain decomposition FDTD algorithm combined with numerical TL calibration technique and its application in parameter extraction of substrate integrated circuits

An efficient hybrid algorithm, known as the "domain decomposition finite-difference time-domain" (DD-FDTD) method combined with a numerical thru-line (TL) calibration technique, is proposed and developed for the accurate parameter extraction of microwave circuits and structures. By means of a TL technique, the developed FDTD algorithm not only greatly increases the accuracy of numerical simulations but it also saves computation time and memory space. Moreover, the hybrid algorithm can be used for the parameter extraction of arbitrary complex circuits and structures, such as substrate integrated circuits (SICs). The SICs that are studied in this work are based on substrate integrated waveguides, which are useful for the design of millimeter-wave planar circuits such as filters, resonators, and antennas. On the basis of the characteristic features of numerical calibration process, an idea of domain decomposition is introduced to simplify the procedure of programming and simulation and to increase the simulation's reliability. Simulation and measurement results have verified this hybrid algorithm
An intent inference based dynamic obstacle avoidance method for intelligent vehicle in structured environment

In this paper, a novel intent inference based dynamic obstacle avoidance method is described that is effective for both normal moving obstacles and maneuvering obstacles, therefore taking advantages of information from different sensors and electronic map. Unlike many of the methods discussed in literature our approach is based on inferring the intent of moving obstacles. It avoids the prediction of accurate maneuvering trajectories which usually fails as the motion is nonlinear and difficult to be modeled. With this method, the performance of dynamic obstacle avoidance is improved which enables the intelligent vehicle to navigate autonomously among moving obstacles. A linear model is used when no maneuver intent is detected and, otherwise, the intent of changing lane is inferred by combing its dynamic features and the road structure when the obstacle is maneuvering. Then a potential collision point will be worked out and avoided to ensure the intelligent vehicle collision free. Experiments show that our method bears significant performance.
DREAR - Towards Infrastructure-Free Indoor Localization via Dead-Reckoning Enhanced with Activity Recognition

The recent indoor localization techniques use inertial sensors for position estimations in order to obtain a certain degree of freedom from infrastructure based solutions. Unfortunately, this dependency cannot be completely eliminated due to the cumulative errors induced in the localization process. While many methods are designed to reduce the required number of reference points or try to offer unsupervised maintenance, completely infrastructure independent solutions are still missing. In this paper we propose a novel approach for mobile-based indoor localization and navigation services by introducing a context-aware localization framework. We exploit the ability to recognize certain human motion patterns with a smartphone, representing activities related to walking, climbing stairs, taking escalators, etc. This allows the detection of corridors, staircases and escalators, knowledge which can be used to create building interior related reference points. Based on these a scenario specific context interpreter controls the localization process and provides position refinement for the elimination of the cumulated errors. Using our solution the auxiliary reference points can be omitted, thus, a completely infrastructure-free localization system is formed. The proposed solution is evaluated in a subway scenario and its performance is analysed focusing on the influence of dead-reckoning error on path reconstruction, the effect of activity detection quality on localization performance, respectively the benefits of using additional context-related information. The results are promising, our solution presents good localization and path reconstruction performance, showing potential for real-world scenarios, where the deployment of auxiliary localization infrastructure is unfeasible.
Comparison of neural network based fingerprint classification techniques

The primary task of this work is to compare classification techniques to decrease the matching time in fingerprint identification. For classification, four different artificial neural networks are tested, as well as a non-linear support vector machine. All classifiers are compared and discussed to find the most suitable one. Automatic fingerprint identification systems (AFIS) are today widely used, but for use in embedded systems with less computational power, it is necessary to create less time-consuming systems. The classifiers splits a fingerprint database into four different subclasses. A multi-layer perceptron network using a backpropagation algorithm has shown to suit this problem best, outperforming both BAM, Hopfleld, Kohonen and just barely SVM, with a correct classification rate of 88.8%. This classification decreases the average matching time with a factor of 3.7.
Autonomous Vehicle Simulation Model to Assess Potential Collisions to Reduce Severity of Impacts

Autonomous vehicle safety has received much attention in recent years. Autonomous vehicles will improve road safety by eliminating human errors. However, not all automotive collisions can be avoided. A strategy needs to be developed in the event when an autonomous vehicle encounters an unavoidable collision. Furthermore, the vehicle will need to take responsibility for the safety of its occupants, as well as any other individuals, who may be affected by the vehicle’s behaviour. This paper proposes a control system to assist an autonomous vehicle to make a decision to reduce the risks to occupants potentially involved in highway motorway collisions. Before any decision can be made, the potential collisions need to be assessed for their effects. A quick and numerical method for evaluation of impact of potential collisions was developed. Assessing the Kinetic Energy of the vehicles before and after collisions is proposed as a method to assess the severity of collisions. A simulation model developed calculates the kinetic energy values and recommends an autonomous vehicle the motorway lane to drive into to cause the least severe collision impact. Different scenarios are defined and used to test the simulation model. The results obtained are promising and in line with the decision made by the subject expert.
Crowdsourced System to Report Traffic Violations - RoadCop: Bi-Modular System

With increasing demand of transportation, implementation of the traffic regulations has become a major challenge for the developing countries. Most of the traffic accidents occur due to violation of traffic rules, thus, resulting in loss of human lives and property. The developed countries have addressed the situation by deploying surveillance systems at intersection, but the solution can be expensive; therefore, due to the cost factor the solution is out of reach for many underdeveloped countries. In order to overcome the situation, a framework is proposed that is based on crowdsourced model to report violations supplemented by the video evidence. The user reports are evaluated in multiple phases. In the first stage, spam is eliminated through evaluation, and associated user profiles are blocked. In the second stage, traffic law experts evaluate the report and on every valid report the users are rewarded with incentive points while ensuring the anonymity. The system is evaluated for usability, advantages to authorities, citizen involvement, skills and resources required and transparency. The results of functional testing indicate that the participants appreciated the purpose of the application and found it quite easy to use. With a large-scale deployment and an effective mechanism to identify offender, this system can lead to much improved implementation of traffic regulations.
Robust Movement Policies for Physics-based Characters in 2-d

This course project outlines an approach for constructing simple, relatively robust control strategies for a simple, physics-based biped character. A simple, articulated character was first built from links in the BOX2D simulator, and tested during each phase of creation. These phases consisted of specifying torques for each joint of the character, creating Proportional Derivative (PD) controllers to actuate or move these links about their joints, defining Finite State Machine (FSM) biped locomotion movement routine controllers and a basic balance strategy for the character's movements, and employing a Reinforcement Learning (RL) technique to select among three, defined control strategies when the character is being pushed or perturbed by the outside world. The character was able to learn simple control strategies for staying upright when being pushed around by an external force by intelligently selecting from three, simple prede-fined controllers – a " Walk-in-Place " controller, a " Walk Forwards Controller " and a " Walk Backwards " controller.
AR-SMT: Coarse-Grain Time Redundancy for High Performance General Purpose Processors

Time redundancy is a fault tolerance technique in which a task -either computation or communication -is performed multiple times on the same hardware. This technique is cheaper than other fault tolerance solutions that require some form of hardware redundancy, because it does not require replicated hardware. However, fault coverage may be lower with time redundancy as it only captures certain classes of faults, and furthermore performance is degraded due to the repetition of tasks.
A Riddle, Wrapped in a Mystery, Inside an Enigma … or Just Multidimensional? Testing the Multidimensional Structure of Boredom

Abstract The multidimensional structure of boredom poses unique measurement challenges related to scale length and statistical modeling. We systematically address these concerns in two studies. In Study 1, we use item response theory to shorten the 29-item Multidimensional State Boredom Scale (MSBS) (Fahlman et al., 2013). In Study 2, we use structural equation modeling to compare two theoretically consistent multidimensional structures of boredom (superordinate and multivariate) with the most commonly used, yet theoretically inconsistent, structure in boredom research (unidimensional parallel model). Our findings provide support for modeling boredom as multidimensional and demonstrate the impact of model selection on effect sizes and significance.
Variation in surface energy and reduction drive of a metal oxide lithium-ion anode with stoichiometry: a DFT study of lithium titanate spinel surfaces

Li4Ti5O12 is a “zero-strain” lithium-ion anode material that shows excellent stability over repeated lithium insertion–extraction cycles. Although lithium (de)intercalation in the bulk material has been well characterised, our understanding of surface atomic-scale-structure and the relationship with electrochemical behaviour is incomplete. To address this, we have modelled the Li4Ti5O12 (111), Li7Ti5O12 (111) and α-Li2TiO3 (100), (110), and (111) surfaces using Hubbard-corrected density-functional theory (GGA+U), screening more than 600 stoichiometric Li4Ti5O12 and Li7Ti5O12 (111) surfaces. For Li4Ti5O12 and Li7Ti5O12 we find Li-terminated surfaces are more stable than mixed Li/Ti-terminated surfaces, which typically reconstruct. For α-Li2TiO3, the (100) surface energy is significantly lower than for the (110) and (111) surfaces, and is competitive with the pristine Li7Ti5O12 (111) surface. Using these stoichiometric surfaces as reference, we also model variation in Li surface coverage as a function of lithium chemical potential. For Li4Ti5O12, the stoichiometric surface is most stable across the full chemical potential range of thermodynamic stability, whereas for Li7Ti5O12, Li deficient surfaces are stabilised at low Li chemical potentials. The highest occupied electronic state for Li7Ti5O12 (111) is 2.56 eV below the vacuum energy. This is 0.3 eV smaller than the work function for metallic lithium, indicating an extreme thermodynamic drive for reduction. In contrast, the highest occupied state for the α-Li2TiO3 (100) surface is 4.71 eV below the vacuum level, indicating a substantially lower reduction drive. This result demonstrates how stoichiometry can strongly affect the thermodynamic drive for reduction at metal-oxide-electrode surfaces. In this context, we conclude by discussing the design of highly-reducible metal-oxide electrode coatings, with the potential for controlled solid-electrolyte-interphase formation via equilibrium chemistry, by electrode wetting in the absence of any applied bias.
The distribution and chemical composition of ultracentrifugally separated lipoproteins in human serum.

In the past few years several methods have been developed for the analysis of serum lipoproteins. Lindgren, Elliott, and Gofman (1) have utilized the relatively low density of the lipoproteins to separate them from the other serum proteins by ultracentrifugal flotation. Quantitation was subsequently performed by refractometric methods in the analytical ultracentrifuge. Separations of lipoproteins have also been made by Cohn fractionation in cold ethanol, and the quantities of lipoprotein have been estimated from the lipid. content of the fractions (2, 3). Widely used at the present time is the method of zone electrophoresis with quantitation either by staining (4) or by chemical analysis of eluates from the support
Emergent Thought Automated Agent Design Mini-project Report

The following report presents the preliminary results and theoretical backgrounds of a multi-layer evolutionary mechanism. The project aims at developing a mechanism for automated agent design within a pre-designed multi-layer architecture. The core mechanism used in the experiments is a Genetic Programming algorithm working in a specially designed condition-action rules system. There is described an extension to Genetic Programming, which is based on a multi-layer evolution paradigm, inspired by notion of the niche & design spaces. The multi-layer GP algorithm is distributed across a number of workstations and works in parallel. There are presented plans for experiments with the multi-layer co-evolutionary mechanism for parallel distributed search within restrained search space. Attention is paid to evolutionary mechanisms in general, with no commitments to any particular problem. In theory the multi-layer evolutionary process can be applied to a number of systems and problems, e.g. to Genetic Programming. The experiments are based on simple Artiicial Life scenario in which agents act in a continuous 3D environment. The simulation is 2D online and 3D oo-line (as a movie). The use of agents in entertainment as a perfect environment for agent research is stressed.
SURVEY ON CONTENT BASED IMAGE RETRIEVAL USING COLOR AND TEXTURE FEATURES

Content based image retrieval is a research topic since last decade and it is used to solve different problems such as construction of feature vectors, multidimensional indexing, and design of user interface and data visualization. The main problem of content based image retrieval system is with retrieval accuracy and the computational complexity (or retrieval time). This paper provides information about color features such as color space, color moment and also texture features such as Gabor filters, Wavelets. The CBIR system is useful in many applications such as medical imaging, data mining, weather forecasting, crime prevention, education etc. This paper mainly concentrated on the color and texture feature of content based image retrieval techniques.
Porting the Arla file system to Windows NT

This paper describes how we ported the Arla filesystem to Windows NT/2000. Windows is very different from the platforms (different flavors of Unix) that Arla was written for before. Arla consists of a complex userland daemon (arlad) and a rather simple kernel-module (xfs). Arlad needed very little work to be able to work on Windows because we used Cygwin. The Windows kernel-module was written from scratch under influence from the earlier Unix kernel-modules. Since everthing was different it took very long time to complete the work with xfs. A problem is that there is little example code available to be used as reference and inspiration.
Types of Creativity and Visualization in Teams of Different Educational Specialization

This research is the first to examine different types of creativity dimensions in relation to different types of visualization on a team level, by comparing adolescences’ teams of different specialization (visual artist, scientists, and humanities) during a complex creative task in an ecologically valid educational setting First, the difference between all teams’ creative outputs (drawings) was compared in terms of their visual characteristics and represented content based on parameters derived from the content analysis of visual media. Second, the teams’ creative performance was compared using evaluations of experts from different professional domains. Based on the evidence from examination of teams’ creative products (final drawings) and their evaluations by professionals, this research suggests that object visualization is related to artistic creativity and spatial visualization is related to scientific creativity on the team-level. Furthermore, the findings provide a clear indication that assessing general creativity independently of the domain, as it has been done so far in most team creativity literature, might be somewhat limited.
Color Local Texture Features Based Face Recognition

For the purpose of face recognition (FR), the new color local texture features, i.e., color local Gabor wavelets (CLGWs) and color local binary pattern (CLBP), are being proposed. The proposed color local texture features are able to exploit the discriminative information derived from spatiochromatic texture patterns of different spectral channels within a certain local face region. This method encodes the discriminative features by combining both color and texture information as well as its fusion approach. To make full use of both color and texture information, the opponent color texture features are used. The opponent features capture the spatial correlation between spectral bands and taken into the generation of CLGW and CLBP. In addition, to perform the final classification, multiple color local texture features (each corresponding to the associated color band) are combined within a feature-level fusion framework. Particularly, compared with gray scale texture features, the proposed color local texture features are able to provide excellent recognition rates for face images taken under severe variation in illumination, as well as some variations in face images.
Modelling the time variation of the surface differential rotation in AB Doradus and LQ Hydrae

Sequences of Doppler images of the young, rapidly rotating late-type stars AB Dor and LQ Hya show that their equatorial angular velocity and the amplitude of their surface differential rotation vary versus time. Such variations can be modelled to obtain information on the intensity of the azimuthal magnetic stresses within stellar convection zones. We introduce a simple model in the framework of the mean-field theory and discuss briefly the results of its application to those solar-like stars.
Deterministic k-set structure

A k-set structure over data streams is a bounded-space data structure that supports stream insertion and deletion operations and returns the set of (item, frequency) pairs in the stream, provided, the number of distinct items in the stream does not exceed k; and returns nil otherwise. This is a fundamental problem with applications in data streaming [14], data reconciliation in distributed systems [12] and mobile computing [16], etc. In this paper, we present a deterministic algorithm for the k-set problem that matches the space lower bound to within a logarithmic factor.
What You Write Is What You Get: A Novel Mixed Reality Interface

Kids develop their understanding of the world by interacting with diﬀerent objects. This cognitive development process can be further enriched through the use of interactive multimedia technology. This paper presents a novel application that combines the ﬂexibility of the virtual world with a handwriting recognition engine to create a tangible mixed reality learning environment
An improved ACO algorithm for vehicle scheduling problem in military material distribution

The “distribution” mode for material support is the trend of military logistics evolution, and scheduling of vehicle is crucial to achieve this target. The mathematical model for the vehicle scheduling problem of military material distribution was formulated, in which the minimization of the armies' waiting time was used as the objective, and an improved ant colony optimization algorithm was utilized to solve the model. In the proposed algorithm, the transition rule in ant colony optimization algorithm was improved, and the local search heuristics were integrated into the algorithm. The vehicle routing problem with time windows (VRPTW) benchmark instances were solved under different parameter settings, and the experimental results showed that our improved transition rule can significantly enhance the algorithm's performance.
Assessing Software Design Skills and their Relation with Reasoning Skills

Lecturers see students struggle learning software design. In order to create educational interventions it is needed to know which reasoning skills are related to students’ software design performance. We introduce an online test for measuring students’ software design skills and relate those with abstract reasoning. Two student groups of two different European universities participated in an experiment in which we were able to relate students’ visual and verbal reasoning skills to students’ software design skills and measured learning improvement. In the future proper interventions can be chosen while using the test as a diagnostic tool.
Reprints Available Directly from the Publisher Photocopying Permitted by License Only Expression of Gata-3 during Lymphocyte Differentiation and Mouse Embryogenesis

The GATA family of C4 zinc-finger transcription factors has been implicated in tissue-specific gene regulation in birds and mammals. One of the members of this family, GATA-3, is reportedly expressed specifically in the T-cell lineage, where it interacts with GATA motifs in the TCR-c, TCR-]/, and TCR-enhancers, thereby controlling the T-cell phenotype. To evaluate the differentiation control properties of GATA-3, we have now documented its expression pattern during lymphoid differentiation and murine embryogenesis.
Active learning for adaptive brain machine interface based on Software Agent

Brain Machine Interface (BMI) and Software Agent (SA) can provide some new adaptive strategies for robust BMI implementations. In this work, a non-invasive Adaptive BMI is introduced, which has been designed to discriminate four mental tasks. The SA allows tracking features to contribute for an adaptive process, while the user's engagement state provides a feedback between BMI and the environment. The Silhouette's width is the performance measurement used for the active learning process. The results show that the implemented system allows high accuracy (75%) in the classification process.