Miracle-dz/UniFAR-FTUs huggingface dataset:
User Pairing, Link Selection, and Power Allocation for Cooperative NOMA Hybrid VLC/RF Systems

Despite the promising high-data rate features of visible light communications (VLC), they still suffer from unbalanced services due to blockages and channel fluctuation among users. This paper introduces and evaluates a new transmission scheme which adopts cooperative non-orthogonal multiple access (Co-NOMA) in hybrid VLC/radio-frequency (RF) systems, so as to improve both system sum-rate and fairness. Consider a network consisting of one VLC access point (AP) and multiple strong and weak users, where each weak user is paired with a strong user. Each weak user can be served either directly by the VLC AP, or via the strong user which converts light information received through the VLC link, and forwards the information to the weak user via the RF link. The paper then maximizes a network-wide weighted sum-rate, so as to jointly determine the strong-weak user-pairs, the serving link of each weak user (i.e., either direct VLC or hybrid VLC/RF), and the power of each user message, subject to user connectivity and transmit power constraints. The paper tackles such a mixed-integer non-convex optimization problem using an iterative approach. Simulations show that the proposed scheme significantly improves the VLC network performance (i.e., sum-rate and fairness) as compared to the conventional NOMA scheme.
A Semantic Schema for Data Quality Management in a Multi-Tenant Data Platform

Schibsted Media Group is a global marketplace company with presence in more than 20 countries. It is undergoing a digital transformation to convert data silos to a multi-tenant system based on a common data platform. Good data quality based on a common schema on the semantic level is essential for building successful data-driven products across marketplaces. To solve this challenge, we developed the data quality tooling based on a semantic schema management system to support schema evolution with versioning, testing and transformation. It can monitor the data quality requirements for different applications and handle incoming data consisting of multiple schema versions. Today the system is operating in production and processes over one billion events per day for over 100 applications.
Automated Architecture Design for Deep Neural Networks

Machine learning has made tremendous progress in recent years and received large amounts of public attention. Though we are still far from designing a full artificially intelligent agent, machine learning has brought us many applications in which computers solve human learning tasks remarkably well. Much of this progress comes from a recent trend within machine learning, called deep learning. Deep learning models are responsible for many state-of-the-art applications of machine learning. Despite their success, deep learning models are hard to train, very difficult to understand, and often times so complex that training is only possible on very large GPU clusters. Lots of work has been done on enabling neural networks to learn efficiently. However, the design and architecture of such neural networks is often done manually through trial and error and expert knowledge. This thesis inspects different approaches, existing and novel, to automate the design of deep feedforward neural networks in an attempt to create less complex models with good performance that take away the burden of deciding on an architecture and make it more efficient to design and train such deep networks.
Mechanism of generation of a Josephson phase shift by an Abrikosov vortex

Abrikosov vortex contains magnetic ﬁeld and circulating currents that decay at a short range λ ∼ 100 nm. However, the vortex can induce a long range Josephson phase shift at distances r ∼ µ m (cid:29) λ . The mechanism of this puzzling phenomenon is not clearly understood. Here we present a systematic study of vortex-induced phase shift in planar Josephson junctions. We make two key observations: (i) The cuto ﬀ e ﬀ ect: although vortex-induce phase shift is a long-range phenomenon, it is terminated by the junction and does not persists beyond it. (ii) A crossover from linear to superlinear dependence of the phase shift on the vortex polar angle occurs upon approaching of the vortex to the junction. The crossover occurs at a distance comparable with the penetration depth. This, together with theoretical and numerical analysis of the problem, allows unambiguous identiﬁcation of two distinct and independent mechanisms. The short range mechanism is due to circulating vortex currents inside superconducting electrodes without involvement of magnetic ﬁeld. The long range mechanism is due to stray magnetic ﬁelds outside electrodes without circulating vortex currents. We argue that understanding of controlling parameters of vortex-induced Josephson phase shift can be used for development of compact and fast electronic devices with low dissipation power.
Forward-Mode Differentiation of Maxwell's Equations

We present a previously unexplored forward-mode differentiation method for Maxwell's equations, with applications in the field of sensitivity analysis. This approach yields exact gradients and is similar to the popular adjoint variable method, but provides a significant improvement in both memory and speed scaling for problems involving several output parameters, as we analyze in the context of finite-difference time-domain (FDTD) simulations. Furthermore, it provides an exact alternative to numerical derivative methods, based on finite-difference approximations. To demonstrate the usefulness of the method, we perform sensitivity analysis of two problems. First we compute how the spatial near-field intensity distribution of a scatterer changes with respect to its dielectric constant. Then, we compute how the spectral power and coupling efficiency of a surface grating coupler changes with respect to its fill factor.
EOG signal Modeling using Double Exponential Smoothing for Robot Arm Control System

This paper present a novel way of modeling EOG signal to use in a robot arm control system, two procedures implemented, offline procedure to measure and modeling EOG for building a pattern reference model ,and online procedure used to Control the robot arm. By comparing online measured EOG and the EOG pattern in reference model suitable manipulation instruction generated by the micro controller. The double exponential smoothing method used for building the pattern reference model, the accuracy of the reference model tested with main squire error (MSE) and main absolute error (MAPE) measures. Auto correlation analysis applied to study the existing pattern and linearity of EOG signal with eye movements. EOG signal measurement for this research classified in to five kinds: EOG horizontal (left and right) Vertical (up and down), and blinking. The EOG signal models of this research saved and used as a reference model file to classify the eye movements. a measurement and robot arm control system constructed by using arduino olimix 328, olimix sensor shield, and robot arm driving circuit, arduino C used as a programming environment, Minitab software used to build the model and correlation analysis ,Brain Bay software used to control and signal processing.
Quantum scattering by a disordered target - The mean cross section

We study the variation of the mean cross section with the density of the samples in the quantum scattering of a particle by a disordered target. The particular target we consider is modelled by a set of pointlike scatterers, each having an equal probability of being anywhere inside a sphere whose radius may be modified. We first prove that the scattering by a pointlike scatterer is characterized by a single phase shift δ which may take on any value in ]0 , π/2[ and that the scattering by N pointlike scatterers is described by a system of only N equations. We then show with the help of numerical calculations that there are two stages in the variation of the mean cross section when the density of the samples (the radius of the target) increases (decreases). The mean cross section first either increases or decreases, depending on whether the value of δ is less or greater than π/4 respectively, each one of the two behaviours being originated by double scattering; it always decreases as the density increases further, a behaviour which results from multiple scattering and which follows that of the cross section for diffusion by a hard sphere potential of decreasing radius. The exact expression of the mean cross section is derived for an unlimited number of contributions of successive scatterings.
Gap Effect on Taylor Vortex Size Between Rotating Conical Cylinders

The present paper is concerned with an experimental study of the occurrence of Taylor vortices between conical cylinders, the inner one rotating and the outer one at rest. Gap effect on the non-uniqueness of the Taylor vortex flow mode is investigated. Six different flow modes are observed according to the gap width, the acceleration of the inner rotating conical cylinder and Reynolds number. In one of the observed flow modes very large Taylor vortices are obtained with a wavelength up to 3.5 times the gap width. This kind of Taylor vortices has not been observed before in our knowledge.
Lightweight cryptography methods

ABSTRACT While our conventional cryptography methods, such for AES (encryption), SHA-256 (hashing) and RSA/Elliptic Curve (signing), work well on systems which have reasonable processing power and memory capabilities, these do not scale well into a world with embedded systems and sensor networks. Thus, lightweight cryptography methods are proposed to overcome many of the problems of conventional cryptography. This includes constraints related to physical size, processing requirements, memory limitation and energy drain. This paper outlines many of the techniques that are defined as replacements for conventional cryptography within an Internet of things space and discuss some trends in the design of lightweight algorithms.
Classifying windows ransomware based on runtime behavior using machine learning algorithms

Ransomware is defined as a type of malware program that infects, locks or takes control of the users system and demands ransom from the user to undo the damage. Ransomware detection is an important factor in security of computer systems. However, Zero-day attacks and polymorphic viruses are not easily detected by signature-based methods. As a result, need for machine learning based detection arises. The purpose of this work is to determine result of feature selection on classification methods when used on top of cuckoo sandbox. Classification algorithms like k-Nearest-Neighnours, Naive Bayes, Support Vector Machines and Random Forest were evaluated. The dataset for this study consisted over 1584 ransomware samples of 11 different ransomware families. Cuckoo sandbox is used to run these samples and see their real time behavior. This work demonstrated the improvement in accuracy obtained using mutual information criteria for feature selection. Index words: Security, Computer Security, Ransomware, Ransomware Classification, Windows Ransomware Classifying Windows Ransomware Based On Runtime Behavior Using Machine Learning Algorithms
KnobSlider: Design of a Shape-Changing Parameter Control UI and Study of User Preferences on Its Speed and Tangibility

Professionals such as sound engineers or aircraft pilots heavily use physical knobs and sliders on their interfaces. The interfaces have advantages over touchscreen interfaces, especially when the users need to quickly and eyes-freely respond to changing situations such as when musicians are improvising, or there is smoke in a cockpit. However, unlike touchscreen interfaces, the physical interfaces are often bulky and crowded and lack of adaptability to user preferences or small spaces. To have advantages from both physical and touchscreen control interfaces, we explore design space of control interfaces and suggest design guidelines in the following steps. We first conduct a formative study with eight professionals who use knobs and sliders. Based on their feedback, we propose design requirements for future parameter control interfaces. We then introduce the design of the KnobSlider, a shape-changing device that combines the advantages of a physical knob and a slider in a time- and space-multiplexing way. To increase users' acceptance on shape-changing control interfaces, we investigate subjective preference on speed of shape-changes by using pairwise comparison with different maximum speeds. We also investigate how tangibility—showing KnobSlider on a video or showing it in the physical world—affects users preference and suggest speed design guidelines for future studies.
Supporting Book Search: A Comprehensive Comparison of Tags vs. Controlled Vocabulary Metadata

Abstract Book search is far from a solved problem. Complex information needs often go beyond bibliographic facts and cover a combination of different aspects, such as specific genres or plot elements, engagement or novelty. Conventional book metadata may not be sufficient to address these kinds of information needs. In this paper, we present a large-scale empirical comparison of the effectiveness of book metadata elements for searching complex information needs. Using a test collection of over 2 million book records and over 330 real-world book search requests, we perform a highly controlled and in-depth analysis of topical metadata, comparing controlled vocabularies with social tags. Tags perform better overall in this setting, but controlled vocabulary terms provide complementary information, which will improve a search. We analyze potential underlying factors that contribute to search performance, such as the relevance aspect(s) mentioned in a request or the type of book. In addition, we investigate the possible causes of search failure. We conclude that neither tags nor controlled vocabularies are wholly suited to handling the complex information needs in book search, which means that different approaches to describe topical information in books are needed.
Personal Database Security and Trusted Execution Environments: A Tutorial at the Crossroads

Smart disclosure initiatives and new regulations such as GDPR in the EU increase the interest for Personal Data Management Systems (PDMS) being provided to individuals to preserve their entire digital life. Consequently, the thorny issue of data security becomes more and more prominent, but highly differs from traditional privacy issues in outsourced corporate databases. Concurrently, the emergence of Trusted Execution Environments (TEE) changes the game in privacy-preserving data management with novel security models. This tutorial offers a global perspective of the current state of work at the confluence of these two rapidly growing areas. The goal is threefold: (1) review and categorize PDMS solutions and identify existing privacy threats and countermeasures; (2) review new security models capitalizing on TEEs and related privacy-preserving data management solutions relevant to the personal context; (3) discuss new challenges at the intersection of PDMS security and TEE-based data management.
Simulation of Transient Diffusion Enhancement of Boron with VICTORY Process in 3D, with the Plus-One Implantation Damage Model and the Five-Stream Diffusion Model

During thermal treatment the motion of the doping atoms is assisted by point-defects in semiconductor material. When the point-defects are in thermal equilibrium and hence the point-defect concentrations are rather low, the effective diffusivity of the doping atoms is also low. In this case a significant redistribution of doping atoms can only be observed after annealing for several minutes and only when the annealing temperature is high. On the other hand, in the presence of high point-defect concentrations, the effective diffusivity of the doping atoms can be dramatically enhanced so that a significant redistribution of doping atoms can be observed after just a few seconds of annealing and at relatively low annealing temperatures. Diffusion enhancement caused by the presence of high concentrations of point-defects can only be simulated by means of diffusion models which take point-defects into account in the problem formulation [1][2][3].
Self-Parametrizing System-Focused Atomistic Models.

Computational studies of chemical reactions in complex environments such as proteins, nanostructures, or on surfaces require accurate and efficient atomistic models applicable to the nanometer scale. In general, an accurate parametrization of the atomistic entities will not be available for arbitrary system classes, but demands a fast automated system-focused parametrization procedure to be quickly applicable, reliable, flexible, and reproducible. Here, we develop and combine an automatically parametrizable quantum chemically derived molecular mechanics model with machine-learned corrections under autonomous uncertainty quantification and refinement. Our approach first generates an accurate, physically motivated model from a minimum energy structure and its corresponding Hessian matrix by a partial Hessian fitting procedure of the force constants. This model is then the starting point to generate a large number of configurations for which additional off-minimum reference data can be evaluated on the fly. A Delta-machine learning model is trained on these data to provide a correction to energies and forces including uncertainty estimates. During the procedure, the flexibility of the machine learning model is tailored to the amount of available training data. The parametrization of large systems is enabled by a fragmentation approach. Due to their modular nature, all model construction steps allow for model improvement in a rolling fashion. Our approach may also be employed for the generation of system-focused electrostatic molecular mechanics embedding environments in a quantum mechanical molecular-mechanical hybrid model for arbitrary atomistic structures at the nanoscale.
Evaluation of safety, effectiveness and reproducibility of telemedicine for neurosurgical screening

ABSTRACT Objective: To ascertain the safety, effectiveness and reproducibility of screening potential neurosurgical patients by means of smartphones. Methods: This is a retrospective and multicentric study. Data were collected from the medical records of patients subjected to real emergency neurosurgical evaluations and compared with assessments by neurosurgeons using smartphones to determine the feasibility of identifying changes in cranial computed tomography scans, potentially serious conditions of patients, and the need for transfer to reference centers. Results: We analyzed 232 cases. The main diagnosis was traumatic brain injury, with 119 cases (51.3%). Of this, 105 (45.3%) patients were discharged immediately after the assessment. The telemedicine evaluators presented 95.69% accuracy in the identification of changes in computed tomography scans, with 0.858 concordance. Accuracy in the identification of severity was 95.26%, with 0.858 concordance. As for procedure, the concordance among evaluators was 0.672, increasing to 100% in cases that required surgical treatment. Conclusion: Our study indicated that the use of telemedicine for screening patients with acute neurological disorders was safe, effective and reproducible. Implementation of the method shows a promising potential to improve the patient's outcome by reducing unnecessary transfers and decreasing the time elapsed until a specialist can be consulted.
Effect of Salt Stress on Antioxidant Activity and Seedling Growth of Canola ( Brassica Napus L . ) Cultivars

This research was carried out in order to evolution effect of salt stress on seedling growth and antioxidant activity of three canola (Brassica napus ) cultivars Consul, Zarfam (new Iranian cultivar) and Okapi, in Islamic Azad University, Shoushtar branch. Salt stress treatments were applied using salt solutions with EC values of 0 (control), 4, 8 and 12 ds/m. All experiments were carried out under a dual factorial (cultivar × salinity level) completely randomized design at four replications. Results showed salt stress decreased root length, shoot length and seedling dry weight but increased seedling electrolyte leakage and catalase (CAT) and peroxidase (POD) activity. Cultivar Okapi seems to be a salt tolerant canola cultivar since it showed the highest seedling dry weight, highest CAT and POD activity and the lowest electrolyte leakage at 12ds/m level compared other cultivars.
Three-dimensional testicular organoids as novel in vitro models of testicular biology and toxicology

Abstract Organoids are three dimensional structures consisting of multiple cell types that recapitulate the cellular architecture and functionality of native organs. Over the last decade, the advent of organoid research has opened up many avenues for basic and translational studies. Following suit of other disciplines, research groups working in the field of male reproductive biology have started establishing and characterizing testicular organoids. The three-dimensional architectural and functional similarities of organoids to their tissue of origin facilitate study of complex cell interactions, tissue development and establishment of representative, scalable models for drug and toxicity screening. In this review, we discuss the current state of testicular organoid research, their advantages over conventional monolayer culture and their potential applications in the field of reproductive biology and toxicology.
Survey of ribose ring pucker of signaling nucleosides and nucleotides

Abstract The ribose of protein-bound nucleosides and nucleotides displays preferred conformations (usually either North or South), which can be exploited to design enhanced analogs having chemically fixed conformations. We introduce a computational protocol for assembling data from the protein database (PDB) on the ribose and ribose-like conformation of small molecule ligands when complexed with purinergic signaling proteins (including receptors, enzymes and transporters, and related intracellular pathways). Some targets prefer exclusively North (adenosine and P2Y1 receptors, CD73, adenosine kinase ATP/ADP-binding site, adenosine deaminase), others prefer South (P2Y12 receptor, E-NTPDase2) or East (adenosine kinase substrates), while others (P2XRs) allow various conformations.
Uso de saliências do contorno via esqueletização para recuperação de imagens

Image retrieval is an offshoot of information retrieval, which has received growing attention. Within this new offshoot the area of shape-based retrieval has shown itself to be one of the most difficult tasks to perform successfully. It is therefore the purpose of this work to explore the main aspects of shape-based retrieval: the representation and the description of shapes, which aim at extracting the main shape forms, as well as the similarity measurements which are used in the comparison between two characteristic vectors which are the result of characteristic extraction. Various descriptors of different classes are covered giving a general view of how shape based retrieval can be carried out. When given further consideration these descriptors are able to point out some desirable aspects, with the invariance to geometric transformations being one of the principal ones. Therefore the descriptors are analyzed to their degree of invariance to transformations, also normalizations in the sense of making the descriptors invariant are analyzed. One new descriptor, contour saliences, in particular shows promising results as it is invariant to such transformations. For this reason the subject is widely discussed in this work, its retrieval is carried out through the use of skeletons being that each saliency is associated to an adjoining extremity, and this is obtained through the use of the image forest transform. A CBIR based on shape that uses salience is implemented and the final results are discussed.