Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Automated Music Genre Classification

This report explores the classification and clustering of audio files. The classification is based on Feature extraction using the MARSYAS tool. The performance of both the Logistic Regression and Support Vector Machine models is evaluated. Within Logistic Regression, information is produced based on the probabilities of classification that may be useful to the end-user. The clustering is based on the use of the Normalised Compression Distance, and the use of an agglomerative hierarchical clustering technique. The results show that SVMs work the best out of all considered techniques. The report suggests why this might be so, and offers suggestions on improving both clustering and classification techniques.
BM³E : Discriminative Density Propagation for Visual Tracking

We introduce BM3E, a conditional Bayesian mixture of experts Markov model, that achieves consistent probabilistic estimates for discriminative visual tracking. The model applies to problems of temporal and uncertain inference and represents the unexplored bottom-up counterpart of pervasive generative models estimated with Kalman filtering or particle filtering. Instead of inverting a nonlinear generative observation model at runtime, we learn to cooperatively predict complex state distributions directly from descriptors that encode image observations (typically, bag-of-feature global image histograms or descriptors computed over regular spatial grids). These are integrated in a conditional graphical model in order to enforce temporal smoothness constraints and allow a principled management of uncertainty. The algorithms combine sparsity, mixture modeling, and nonlinear dimensionality reduction for efficient computation in high-dimensional continuous state spaces. The combined system automatically self-initializes and recovers from failure. The research has three contributions: (1) we establish the density propagation rules for discriminative inference in continuous, temporal chain models, (2) we propose flexible supervised and unsupervised algorithms to learn feed-forward, multivalued contextual mappings (multimodal state distributions) based on compact, conditional Bayesian mixture of experts models, and (3) we validate the framework empirically for the reconstruction of 3D human motion in monocular video sequences. Our tests on both real and motion-capture-based sequences show significant performance gains with respect to competing nearest neighbor, regression, and structured prediction methods.
Adaptive two-loop Voltage-mode control of DC-DC switching converters

A new two-loop control scheme for voltage-mode control (VMC) of dc-dc switching converters is presented. The proposed method adds a high-gain robust loop with two controllers to the conventional VMC loop, achieving an analog "adaptive" loop in which the "equivalent voltage regulator" varies with the changing power stage parameters given as follows: 1) input voltage; 2) load; and 3) component tolerances. The loop significantly improves the disturbance rejection of the control system, i.e., closed-loop output impedance and audiosusceptibility while preserving the stability and the loop gain crossover frequency to a significant extent. Both the small-signal analysis and the experimental results carried out on a buck converter demonstrate the superiority of the proposed scheme with respect to the conventional single loop.
A virtually 1H‐free birdcage coil for zero echo time MRI without background signal

MRI of tissues with rapid transverse relaxation can be performed efficiently using the zero echo time (ZTE) technique. At high bandwidths leading to large relative initial radiofrequency (RF) dead times, the method becomes increasingly sensitive to artifacts related to signal stemming from outside the field of view, particularly from the RF coils. Therefore, in this work, a birdcage coil was designed that is virtually free of 1H signal.
Disappearing formal methods*

In his book The Invisible Computer [ 111, Donald Norman describes how most technological innovations begin as very complex products that require highly skilled operators, and become widely accepted and generally useful only as the products manage more of their own functions and present a simple interface to their operators. Early radios, for example, had dozens of controls to adjust such arcane features as regeneration and filter bandwidth, and operators were expected to understand “the fundamentals of radio reception. ” A modern radio, on the other hand, is trivial to operate. Most current formal methods are like those early radios: they are difficult to use and fit awkwardly into traditional software engineering processes. For example, formal methods generally require a formal specification or model that is quite different to the other documents and descriptions produced during design and whose construction is an additional burden for the developers. Formal analysis requires mastery of the recondite skills needed to guide theorem provers and model checkers-skills that that are more concerned with the formal methods technology employed than with the design being analyzed. There are those who believe that the benefits of formal specification outweigh the cost of their introduction and that the best way forward is to develop a workforce for whom formal specifications are the primary means of documentation and communication-rather in the way that mathematical notation and analysis underlie every other engineering discipline. This is certainly a worthwhile goal, and may be necessary for critical systems that require the highest levels of assurance, but the path to reach that goal from current practice is difficult, and it is hard to persuade practitioners to undertake it if there are few intermediate rewards along the way. So the topic I want to consider is how to make formal methods invisible in Norman’s sense: how to make them “disappear” into the familiar fabric of software engineering
Enhanced Use of Mattes for Easy Image Composition

Existing matting methods focus on improving matte quality to produce high-quality composites. This generally requires significant manual interaction, a tedious task for the user. Despite these efforts, the composites may still exhibit evident artifacts, especially in the case of transparent and complicated objects as their related pixels always contain percentage of the background. In this paper, we focus on the enhanced use of mattes to produce satisfactory composites by suppressing the discrepancies around objects of interest. This approach is motivated by cloning methods but overcomes their shortcoming of ineffective treatment of the over-included regions around objects of interest. For this, we present an enhanced matting function by including a term to smooth the local contrasts for seamless composition, and meanwhile, we develop a novel algorithm to generate mattes with reduced user interaction and improved usability. As a result, we reduce the composite's dependence on the user's input and only require the user to drag a box to enclose the objects of interest. As shown in the user studies and the experimental results, our method requires many times less user interaction than the existing matting methods and cloning methods. Our method is more effective in producing good composites in a simple interactive manner, especially when treating transparent and complicated objects, thereby providing a superior approach for image composition.
Representation methods for recognizing and grasping object of robots

Recognizing and grasping object of robots are two crucial issues for robots accomplishing complicated tasks in unstructured environments, where object representation is a key premise problem. In this paper, we study the representation methods for (1) object recognition, SHOT descriptor is further described by using Tsallis entropy, which greatly reduces the storage and the computation time; (2) grasp part selection, a hierarchical grid representation method is proposed, which retrieves the abrupt concave area layer by layer for segmentation and builds layer minimum bounding cubes referring to the principal axis of point set for orientation changeable representation. Simulations and experiments have verified the effectiveness of the proposed methods.
Variable Pitch Reconstruction Using John's Equation

We present an algorithm to reconstruct helical cone beam computed tomography (CT) data acquired at variable pitch. The algorithm extracts a halfscan segment of projections using an extended version of the advanced single slice rebinning (ASSR) algorithm. ASSR rebins constant pitch cone beam data to fan beam projections that approximately lie on a plane that is tilted to optimally fit the source helix. For variable pitch, the error between the tilted plane chosen by ASSR and the source helix increases, resulting in increased image artifacts. To reduce the artifacts, we choose a reconstruction plane, which is tilted and shifted relative to the source trajectory. We then correct rebinned fan beam data using John's equation to virtually move the source into the tilted and shifted reconstruction plane. Results obtained from simulated phantom images and scanner images demonstrate the applicability of the proposed algorithm.
Being visible in public space: The normalisation of asymmetrical visibility

Over recent decades, cities have been radically transformed by information and communication technologies (ICTs) that modify people’s daily lives by reorganising mobility, infrastructure systems and physical spaces. However, in addition to the role that technology plays in the development of the infrastructure in our cities, it is also being used ‘as a means of control’. This view of technology as a disciplinary tool that restructures space, time and the relations among activities has been promoted by scholars who have shown that technology is also a means of saturating and sustaining contemporary capitalist societies and deepening inequalities. However, the situation is far more complex than that. Technology is not only used top-down but also bottom-up, with individuals using technological devices to share and enhance their visibility in space. This bidirectional paradigm – of vertical surveillance and horizontal sharing – contributes to a sense of ‘being exposed’ in public space that normalises practices of sharing personal data by individuals and thus results in diminished privacy. This argument is supported by an experiment conducted on smartphone users that includes personal interviews and the use of a smartphone Android application that combines online tracking with experience sampling. The findings show a convergence between the online and offline worlds (a ‘public’ situation in the offline world is also considered as such in the online world), which is a condition that contributes to the normalisation of ‘asymmetrical visibility’. Based on these results, the paper ends with a discussion of the contemporary meaning of public space.
From human instructions to robot actions: Formulation of goals, affordances and probabilistic planning

This paper addresses the problem of having a robot executing motor tasks requested by a human through spoken language. Verbal instructions do not typically have a one-to-one mapping to robot actions, due to various reasons: economy of spoken language, e.g., one short instruction might indeed correspond to a complex sequence of robot actions, and details about action execution might be omitted; grounding, e.g., some actions might need to be added or adapted due to environmental contingencies; embodiment, e.g., a robot might have different means than the human ones to obtain the goals that the instruction refers to. We propose a general cognitive architecture to deal with these issues, based on three steps: i) language-based semantic reasoning on the instruction (high-level), ii) formulation of goals in robot symbols and probabilistic planning to achieve them (mid-level), iii) action execution (low-level). The description of the mid-level is the main focus of this paper. The robot plans are adapted to the current scenario, perceived in real-time and continuously updated, taking in consideration the robot capabilities, modeled through the concept of affordances: this allows for flexibility and creativity in the task execution. We showcase the performance of the proposed architecture with real world experiments using the iCub humanoid robot, also in the presence of unexpected events and action failures.
EMI Coupling Paths and Mitigation in a Board-to-Board Connector

Cage connectors for optical subassembly I/O modules have been identified as one of the main coupling paths in an optical link at the front-end of switches and routers. In the study presented herein, the simulation model used to study electromagnetic interference coupling physics and mitigation of the optical cage connector was corroborated by comparing the measured and simulated results for the total radiated power (TRP). Currents on the adjacent ground references to the differential signal conductors caused half-wave resonant peaks in the TRP response in the frequency range of 4-18 GHz. At frequencies from 18 to 28 GHz, both full-wave simulation and analytical formulas indicate that the radiation results primarily from the currents on the signal traces. The radiation from the optical cage connector was suppressed with absorbing materials, and the coupling path was verified, together with the optical cage and module enclosure.
Magnetic Nanocomposite Cilia Sensors

Magnetic Nanocomposite Cilia Sensors Ahmed Alfadhel Recent progress in the development of artificial skin concepts is a result of the increased demand for providing environment perception such as touch and flow sensing to robots, prosthetics and surgical tools. Tactile sensors are the essential components of artificial skins and attracted considerable attention that led to the development of different technologies for mimicking the complex sense of touch in humans. This dissertation work is devoted to the development of a bioinspired tactile sensing technology that imitates the extremely sensitive hair-like cilia receptors found in nature. The artificial cilia are fabricated from permanent magnetic, biocompatible and highly elastic nanocomposite material, and integrated on a giant magneto-impedance magnetic sensor to measure the stray field. A force that bends the cilia changes the stray field and is therefore detected with the magnetic sensor, providing high performance in terms of sensitivity, power consumption and versatility. The nanocomposite is made of Fe nanowires (NWs) incorporated into polydimethylsiloxane (PDMS). Fe NWs have a high remanent magnetization, due the shape anisotropy; thus, they are acting as permanent nano-magnets. This allows remote device operation and avoids the need for a magnetic field to magnetize the NWs, benefiting miniaturization and the possible range of applications. The magnetic properties of the nanocomposite can be easily tuned by modifying the NWs concentration or by aligning the NWs to define a magnetic anisotropy. Tactile sensors are realized on flexible 3 and rigid substrates that can detect flow, vertical and shear forces statically and dynamically, with a high resolution and wide operating range. The advantage to operate the sensors in liquids and air has been utilized to measure flows in different fluids in a microfluidic channel. Various dynamic studies were conducted with the tactile sensor demonstrating the detection of moving objects or the texture of objects. Overall, the results confirm the possibility to easily control the sensors’ performance with the cilia arrangement and dimensions. The cost effective mold-based microfabrication process and magnetic operation enable a high degree of integration, which together with the extremely low power consumption make the artificial cilia sensor reported in this dissertation an attractive solution for many applications.
A New Scalable, Distributed, Fuzzy C-Means Algorithm-Based Mobile Agents Scheme for HPC: SPMD Application

The aim of this paper is to present a mobile agents model for distributed classification of Big Data. The great challenge is to optimize the communication costs between the processing elements (PEs) in the parallel and distributed computational models by the way to ensure the scalability and the efficiency of this method. Additionally, the proposed distributed method integrates a new communication mechanism to ensure HPC (High Performance Computing) of parallel programs as distributed one, by means of cooperative mobile agents team that uses its asynchronous communication ability to achieve that. This mobile agents team implements the distributed method of the Fuzzy C-Means Algorithm (DFCM) and performs the Big Data classification in the distributed system. The paper shows the proposed scheme and its assigned DFCM algorithm and presents some experimental results that illustrate the scalability and the efficiency of this distributed method.
Tokenized Interaction Architecture

Out-of-Home (OOH) advertising is currently advancing into a new era: “pervasive advertising” is one of the buzz words describing a soft change from the traditional push-only media to an interactive and bi-directional advertisement experience. While ambient media solutions try to conquer each and every piece of potential advertisement surfaces by various sorts of print media, another trend can be observed as well: OOH advertising is becoming smarter (at least from an electronics point of view). Digital signage products, SMS, Bluetooth interaction in city lights and talking billboards that react on the feedback of motion sensors—pervasive advertising is on its way. However, the development of a pervasive advertisement platform is beyond the scope of any single engineering or art discipline; instead it is a multidisciplinary effort including electronic engineering, computer science, art, cognitive psychology and even social sciences. Therefore, we introduce a tokenized interaction architecture; a foundation on top of low level issues that simplifies sub sequent implementation efforts by addressing interaction, context awareness and hardware heterogeneity, so to release designers of pervasive advertising campaigns from computer related challenges.
Hot Rectangular Extrusion Textures of Six Mg‐Alloys Via Neutron Diffraction

Due to the high quality and statistics utilizing neutron diffraction for texture analyses, the crystallographic texture variation of six Mg‐alloys is described in detail (AM20–AZ31–AZ61–AZ91–ZC71–WE43). More or less in all cases, the crystallographic texture is composed of some ideal texture components such as {0001} <10–10> and {10–10} <11–20> and fiber components such as <0001> // ND and <10–10> // ED. There is a dependency of the existence and texture sharpness of texture components with alloying elements such as the amount of Al. ZC71 is special with one dominating texture component {10–10} <11–20>. WE43 shows the split of the central pole in the basal pole figure but texture components are identical to other alloys without the tilt.
Cultivation of an obligate acidophilic ammonia oxidizer from a nitrifying acid soil

Nitrification is a fundamental component of the global nitrogen cycle and leads to significant fertilizer loss and atmospheric and groundwater pollution. Nitrification rates in acidic soils (pH < 5.5), which comprise 30% of the world's soils, equal or exceed those of neutral soils. Paradoxically, autotrophic ammonia oxidizing bacteria and archaea, which perform the first stage in nitrification, demonstrate little or no growth in suspended liquid culture below pH 6.5, at which ammonia availability is reduced by ionization. Here we report the discovery and cultivation of a chemolithotrophic, obligately acidophilic thaumarchaeal ammonia oxidizer, “Candidatus Nitrosotalea devanaterra,” from an acidic agricultural soil. Phylogenetic analysis places the organism within a previously uncultivated thaumarchaeal lineage that has been observed in acidic soils. Growth of the organism is optimal in the pH range 4 to 5 and is restricted to the pH range 4 to 5.5, unlike all previously cultivated ammonia oxidizers. Growth of this organism and associated ammonia oxidation and autotrophy also occur during nitrification in soil at pH 4.5. The discovery of Nitrosotalea devanaterra provides a previously unsuspected explanation for high rates of nitrification in acidic soils, and confirms the vital role that thaumarchaea play in terrestrial nitrogen cycling. Growth at extremely low ammonia concentration (0.18 nM) also challenges accepted views on ammonia uptake and metabolism and indicates novel mechanisms for ammonia oxidation at low pH.
Review of tissue simulating phantoms with controllable optical, mechanical and structural properties for use in optical coherence tomography

We review the development of phantoms for optical coherence tomography (OCT) designed to replicate the optical, mechanical and structural properties of a range of tissues. Such phantoms are a key requirement for the continued development of OCT techniques and applications. We focus on phantoms based on silicone, fibrin and poly(vinyl alcohol) cryogels (PVA-C), as we believe these materials hold the most promise for durable and accurate replication of tissue properties.
Joint-Torque Control of Character Motions

—We want to go beyond “passive rag-doll like” simulated characters towards more “active” intelligent self-driven solutions. The “puppet on strings” approach lacks dynamic interactive properties for engaging realistic and immersive virtual environments. This paper focuses on physics-based “self-driven characters” (e.g., character’s own joint-torques to control and move the limbs to accomplish speciﬁc tasks, such as walking) that can react in a life-like manner using physical properties (e.g., limb-strength, ground contacts, and mass). We start by explaining the kinematic principles of motion-control of articulated ﬁgures. The two types of motion-control for virtual characters are ‘position-based’ and ‘torque-based’. The position-based approach focuses on the linear inverse kinematic model, while the force-based approach extends the principle to generalized joint-torques. Primarily, the relationship between end-effectors (e.g., ﬁngers and feet) current and desired targets to joint orientations and torques. We exploit the highly complex and ambiguous nature of an articulated character to produce primary and secondary cases. For example, projecting joint-torques onto the null-space transformation. This discusses and explains the principles and advantages of active torque controlled character animation solutions, including their dynamics and limitations.