Miracle-dz/UniFAR-FTUs huggingface dataset:
Duties Family in The Prevention of Acute Respiratory Infectious Disease ( ARI ) in Children in Society based on Leinenger Theory Approach

Introduction: Infectious diseases are the second highest cause of infant mortality in the world. In Indonesia acute respiratory infection (ARI) is one of infectious diseases which causes many deaths, especially in infants and toddlers. Efforts to overcome these, nurses are expected to have a role to perform five tasks assessment families with adopted culture. Understanding of the culture can be carried through nursing transcultural approach that explains awareness and appreciation of cultural differences. This study aims to describe the family experience in the implementation of tasks in the family health and disease prevention of infectious diseases due to lifestyle based on Leininger's theory. Methodology: This study used the method of qualitative with phenomenological study approach. In this study consist of six participants who met the inclusion criteria. Data were analyzed using Collaizi method. Results: The results obtained consist of five themes. Theme 1 is a familiar problem. Theme 2 is how to make decisions. Theme 3 is caring for a sick member. Theme 4 is modification of the physical environment and compliance. Theme 5 is the use of existing health facilities. Discussion: Family has implemented five family duties in the prevention of infectious diseases in children with relatively simple home treatment for prevention of transmission, utilizing the nearby health facilities such as health centers, doctors clinique, and hospitals beside utilizing alternative treatments such as massage and treatment to the traditional healer as the influence of cultural values Java. Application of their family duties largely influenced by economic conditions and lower-middle education and the influence of Javanese culture. The results of this study recommends that community empowerment in the prevention of infectious diseases in children with operational research methods is essential.
Cosmological tensor perturbations in the Randall-Sundrum model: Evolution in the near-brane limit

We discuss the evolution of cosmological tensor perturbations in the Randall-Sundrum model with one brane. In Gaussian normal coordinates the wave equation is nonseparable, so we use the near-brane limit to perform the separation and study the evolution of perturbations. Massive excitations, which may also mix, decay outside the horizon, which could lead to some novel cosmological signatures.
Low-cost rapid prototyping of flexible plastic paper based microfluidic devices

This research presents a novel rapid prototyping method for paper-based flexible microfluidic devices. The microchannels were fabricated using laser ablation on a piece of plastic paper (permanent paper), the dimensions of the microchannels was carefully studied for various laser powers and scanning speeds. After laser ablation of the microchannels on the plastic paper, a transparent poly (methyl methacrylate)(PMMA) film was thermally bonded to the plastic paper to enclose the channels. After connection of tubing, the device was ready to use. An example microfluidic device (droplet generator) was also fabricated using this technique. Due to the flexibility of the fabricated device, this technique can be used to fabricate 3D microfluidic devices. The fabrication process was simple and rapid without any requirement of cleanroom facilities.
The Application of Phosphogypsum in Agriculture

Phosphogypsum (PG) is a by-product of phosphoric acid production and according to the Waste Management Strategy of the Republic of Croatia for 2007 – 2015 (Official Gazette 85/07, 126/10, 31/11, 46/15) it is classified under the waste code 06 09 01. Phosphogypsum has a significant impact on the environment by its effects, admixtures (impurities) and amount. One of its possible applications is in agriculture. Many positive effects on soil and plants were noted, but there is also a growing concern regarding the effect of residues of heavy metals and natural radioactivity of radionuclides. In order to obtain a better understanding of this subject, this study provides a general overview of the available literature regarding the application of phosphogypsum in agriculture.
A proposed voltage technique for inverter open fault-circuit detection based on SVM strategy

The present paper is dedicated to open-circuit faults diagnosis in a three-phase two-level voltage source inverter fed induction motor using SVM control strategy as a part of diagnosis techniques associated with power electronics. The paper proposes a new voltage-based approach by using the SVM voltage vectors (usually used as a strategy for the inverter-motor control) to detect the inverter open-circuit faults. The paper also presents a comparative study to assess this proposed approach with respect to the Park's current vectors approach. The merits and effectiveness of the proposed approach is verified and illustrated by simulation results which are then validated by experimental work.
Active singly and dual polarised interwoven spiral frequency selective surfaces

Reconfigurable bi-state interwoven spiral FSSs are explored in this work. Their switching capability is realized by pin diodes that enable the change of the electromagnetic response between transparent and reflecting modes at the specified frequencies in both singly and dual polarised unit cell configurations. The proposed topologies are single layer FSS with their elements acting also as dc current carrying conductors supplying the bias signal for switching pin diodes between the on and off states, thus avoiding the need of external bias lines that can cause parasitic resonances and affect the response at oblique incidence. The presented simulation results show that such active FSSs have potentially good isolation between the transmission and reflection states, while retaining the substantially subwavelength response of the unit cell with large fractional bandwidths (FBWs) inherent to the original passive FSSs.
Rare Sound Event Detection Using 1D Convolutional Recurrent Neural Networks

Rare sound event detection is a newly proposed task in IEEE DCASE 2017 to identify the presence of monophonic sound event that is classified as an emergency and to detect the onset time of the event. In this paper, we introduce a rare sound event detection system using combination of 1D convolutional neural network (1D ConvNet) and recurrent neural network (RNN) with long shortterm memory units (LSTM). A log-amplitude mel-spectrogram is used as an input acoustic feature and the 1D ConvNet is applied in each time-frequency frame to convert the spectral feature. Then the RNN-LSTM is utilized to incorporate the temporal dependency of the extracted features. The system is evaluated using DCASE 2017 Challenge Task 2 Dataset. Our best result on the test set of the development dataset shows 0.07 and 96.26 of error rate and F-score on the event-based metric, respectively. The proposed system has achieved the 1st place in the challenge with an error rate of 0.13 and an F-Score of 93.1 on the evaluation dataset.
Controlling the coupling ratio of the plasmonic directional couplers by SPM and XPM nonlinear effects

In this paper, we have shown that by increasing the input power in a Kerr-type nonlinear plasmonic directional coupler (PDC), the bar coupling ratio can be controlled. In 3dB performance of the directional coupler, it has been shown that by utilizing the cross phase modulation (XPM) nonlinear effect the required pump power has been reduced significantly compared to the signal power with self phase modulation (SPM) effect.
EVIDENCE FOR A WEAK WIND FROM THE YOUNG SUN

The early history of the solar wind has remained largely a mystery due to the difficulty of detecting winds around young stars that can serve as analogs for the young Sun. Here we report on the detection of a wind from the 500 Myr old solar analog π1 UMa (G1.5 V), using spectroscopic observations from the Hubble Space Telescope. We detect H i Lyα absorption from the interaction region between the stellar wind and interstellar medium, i.e., the stellar astrosphere. With the assistance of hydrodynamic models of the π1 UMa astrosphere, we infer a wind only half as strong as the solar wind for this star. This suggests that the Sun and solar-like stars do not have particularly strong coronal winds in their youth.
Classification of mass and non-mass mammography based on Tsallis entropy

Breast cancer is a neoplasia that affects a high number of women in the world every year and it is the second on ranking of the diseases that more affects women. Mammography is the most important exam to aid in early detection and diagnosis of breast cancer. Computational methods have been developed to assist the radiologist in diagnosis and to improve the perception of the results. Feature extraction of mammography images has been allowed good results in classification of these mass. This paper presents a new approach of texture descriptors using multilevel decomposition and extracting Tsallis entropy from this new images and the best result for a vector of 24 features was 84.21% of accuracy.
A Multiplexed Microfluidic Platform for Bone Marker Measurement: A Proof-of-Concept

In this work, we report a microfluidic platform that can be easily translated into a biomarker diagnostic. This platform integrates microfluidic technology with electrochemical sensing and embodies a reaction/detection chamber to measure serum levels of different biomarkers. Microfabricated Au electrodes encased in a microfluidic chamber are functionalized to immobilize the antibodies, which can selectively capture the corresponding antigen. An oxidative peak is obtained using the chronoamperometry technique at room temperature. The magnitude of the response current varies linearly with the logarithmic concentration of the relative biomarker and, thus, is used to quantify the concentration of the relative biomarker in serum samples. We demonstrated the implementation, feasibility and specificity of this platform (Osteokit) in assaying serum levels of bone turnover markers (BTMs) using osteocalcin (limits of detection (LOD) = 1.94 ng/mL) and collagen type 1 cross-linked C-telopeptide (CTX) (LOD = 1.39 pg/mL). To our knowledge, this is the first such device fabricated to measure BTMs. Our results also showed that the sensitivity of Osteokit is comparable with the current states of art, electrochemiluminescence (ECLIA).
Advanced semiconductor on insulator substrates for LP and HP digital CMOS applications

To meet HP and LP circuit requirements, increasing channel mobility is required to boost transistor performance and/or reduce Vdd for lower power dissipation without performance penalty. The ultra-thin body (UTB) devices with undoped and strained channels can be used to control the SCE and reduce the sub-threshold leakage for scaling and low power dissipation. Implementing strained-silicon is not just a substrate change; strained- Si will require much more extensive work as transistor scaling continues.
Canopy level estimations of chlorophyll and LAI for two tropical species (teak and bamboo) from Hyperion (EO1) data

Current economic development in tropical regions (especially in India, China, and Brazil) is putting tremendous pressure on tropical forest cover. Some of the dominant and economically important species are planted at large scale in these countries. Teak and bamboo are two important species of tropical regions because of their commercial and conservation values. Accurate estimates of foliar chemistry can help in evaluating the health status of vegetation in these regions. An attempt has been made to derive canopy level estimation of chlorophyll and leaf area index (LAI) for these species utilizing Hyperion data. Partial least square (PLS) regression analysis was carried out to identify the correlation between measured parameters (chlorophyll and LAI) and Hyperion reflectance spectra. PLS regression identified 600–750 nm as a sensitive spectral region for chlorophyll and 1000–1507 nm for LAI. The PLS regression model tested in this study worked well for the estimation of chlorophyll (R 2 = 0.90, root mean square error (RMSE) = 0.182 for teak and R 2 = 0.84, RMSE = 0.113 for bamboo) and for the estimation of LAI (R 2 = 0.87, RMSE = 0.425). The lower predictive error obtained indicates the robustness of the data set and also of the applicability of the PLS regression analysis. Wavelengths recognized by the PLS regression model were utilized for the development of vegetation indices for estimating chlorophyll and LAI. Predictive performances of the developed simple ratios (SRs) were evaluated using the cross-validation method. SR 743/692 gave the best results for the prediction of chlorophyll with the leave-one-out cross-validation (LOO-CV) method (R 2 = 0.73, RMSE = 0.28 for teak and R 2 = 0.71, RMSE = 0.15 for bamboo). The normalized difference ratio (ND 1457/1084) gave the best results for the prediction of LAI with LOO-CV (R 2 = 0.66, RMSE = 0.57). Ratios developed here can be tested for teak and bamboo cover spread in tropical regions with similar environmental conditions.
HARMONIC DECOMPOSITION OF TRANSIENT DISTURBANCES USING THE LS PRONY AND ESPRIT-BASED METHODS

The modeling and analysis of electric power disturbances affecting power quality has emerged as an important field in the changing electric power industry. These disturbances differ in characteristics, and their occurrence can be attributed to various reasons. Tools capable of classifying these disturbances have been investigated and many are under development. This paper illustrates the harmonic decomposition of disturbances, focusing on transient disturbances. The approaches presented are based on modeling the disturbance as a series of damped exponentials, extracting waveform descriptors unique to each disturbance. The two processing methods used are the Least-Squares Prony method and an ESPRIT- based approach (Estimation of Signal Parameters via Rotational Invariance Techniques). The approaches are compared by processing transient disturbances corrupted with measurement noise, which is modeled as zero-mean white Gaussian noise, at different voltage deviation levels. Results indicate that the ESPRIT-based method outperforms the Least-Squares Prony method in estimating the waveform descriptors in the presence of measurement noise. The transient disturbances used were created at the Center for Electric Power Engineering (CEPE), Drexel University.
Isolation improvement of two-port multiple-input-multiple-output antenna using slits and split ring resonators on the ground plane

In this paper, a multiple-input-multiple-output (MIMO) for dual frequency band is proposed. Each antenna consists of two folded planar inverted F structure with slits and split ring resonator (SRR) cells on a ground plane. It is designed on a FR-4 substrate (relative permittivity = 4.4, height = 0.8 mm) using micro-strip technology. The size of the ground plane and each chip type planar inverted F antenna (PIFA) is 50 mm × 100 mm and 35 mm × 5 mm, respectively. For the isolation improvement between two antennas, a quarter-wavelength open slit is designed for long term evolution (LTE) band and five SRR cells is designed for united state personal communication services (USPCS) band. The measured isolation between two antennas has been enhanced to be near −20 dB by using slits and SRR cells on the ground plane.
Rigorous Design of Truncated Cylindrical Cavity for Dual Mode Dielectric Resonator Filters Applying the Finite Element Method

A novel dielectric resonator filter with truncated cylindrical cavity is proposed in order to realize dual mode narrow band filters without tuning and coupling elements. A full electromagnetic optimization method using the three dimensional finite element method permits rigorous prediction of a two pole filter. A representative prototype of dual mode dielectric resonator filter using truncated metallic cavity is built and tested. The favorable comparison between experimental and theoretical results validates our coupling technique and the accuracy of our computations. At last, the design of an elliptic four pole dual mode DR filter with truncated cavities and original tuning iris is proposed.
Automated Deduction : Decidability , Complexity , Tractability ( ADDCT ) 18 Ju ly 2014

Abduction can be de ned as the process of inferring plausible explanations (or hypotheses) from observed facts (conclusions). This form of reasoning has the potential of playing a central role in system veri cation, particularly for identifying bugs and providing hints to correct them. We describe an approach to perform abductive reasoning that is based on the superposition calculus. The formulas we consider are sets of rst-order clauses with equality, and the explanations that are allowed to be inferred are boolean combinations of equations constructed over a given nite set of ground terms. By duality, abduction can be reduced to a consequencending problem. We show how the inference rules of the superposition calculus can be adapted to obtain a calculus that is deductive complete for ground clauses built on the considered sets of ground terms, thus guaranteeing that all required explanations can be generated. This calculus enjoys the same termination properties as the superposition calculus: in particular, it is terminating on ground extensions of decidable theories of interest in software veri cation. The number of implicates of a given equational formula is usually huge. We describe techniques for storing sets of abduced clauses e ciently, and show how usual trie-based approaches for representing sets of propositional clauses in a compact way can be adapted and extended in order to denote equational clauses up to equivalence (modulo the axioms of equality). We provide algorithms for performing redundancy pruning in an e cient way on such representations. We also identify hints for improvements and provide lines of on-going and future research.
Online filtering and uncertainty management techniques for rfid data processing

RFID is one of the emerging technologies for a wide-range of applications, including supply chain and asset management, healthcare and intruder localization. However, the nature of an RFID data stream is noisy, redundant and unreliable, making it unsuitable for direct use in applications. In this paper, we propose specific RFID Online Filtering and Uncertainty Management techniques that operate on unreliable and imprecise data streams in order to transform them into reliable probabilistic data that can be meaningful to the applications. Our proposal makes use of an Hidden Markov Model (HMM) that continuously infers hidden variables (locations, in case of above example) based on sensor readings. The resulting data can be directly stored in a probabilistic database table for further analysis. All the techniques presented in this paper are implemented in a complete framework and succesfully evaluated in real-world object tracking scenarios. Key–Words: RFID data streams, Hidden Markov Model, Probabilistic Data Management, Object tracking
Fingertip detection approach on depth image sequences for interactive projection system

This study presents a vision-based approach for fingertip tracking on multi-touch tabletop which combines infrared and depth image processing. This approach intends to tackle two main issues on tabletop interaction: improve the performance for real-time applications and increase fingertip detection accuracy. A prototype using this fingertip tracking method was implemented with a depth and infrared camera. This approach processes the user's arm, hands and fingertips images using depth-space constraints, as well as clustering. Fingertip positions are accurately corrected using additional infrared information. Quantitative results show high accuracy of fingertip detection, with lower error rates compared to previous studies. Also, increased capabilities for real-time multi-user interaction are further demonstrated through a set of response time tests.
A novel implementation for FastSLAM 2.0 algorithm based on cloud robotics

In this paper, an extremely efficient architecture for the Simultaneous Localization and Mapping (SLAM) problem is proposed. This architecture depends on distributing of heavy computational tasks and large data sets among remote servers and frees the robots from any computational loads. Thus, the most widely used FastSLAM2.0 approach is parallelized as Map/Reduce tasks via the Hadoop framework. The experiments show the real-time performance for a single robot navigation in two scenarios: the traditional method as sequential algorithm and the presented scheme which is used to estimate fast a parallel algorithm. Also, the contribution of this paper is segmentation of the FastSLAM 2.0 algorithm to execute concurrently the localization and the mapping tasks on the cloud for overcoming strong real-time constraints of the localization task.
Dynamic fault tree analysis based on pivotal decomposition of the structure function

Many fault-tolerant systems in real life are involved in sequence- and function-dependent failure behaviors, in which the failure of these systems depends not only on the combination of basic events, but also on their failure orders. Dynamic fault tree (DFT) as an extension of the conventional static fault tree is widely used to model such systems. The existing analytical approaches for reliability evaluation of DFT are mainly Markov-based, Inclusion-exclusion-based and sequential-BDD - based methods. Those approaches either suffer from the problem of state-space explosion or are subjected to combinatorial explosion knot or have small flaws. To overcome the shortcomings of the existing methods, a pivotal decomposition scheme upon the structure function of a given DFT is proposed in this paper. The proposed approach rewrites the structure function into equivalent sum-of-disjoint products based on Shannon decomposition theorem and exactly calculates the unreliability of non-repairable dynamic systems modeled by DFT. In addition, the proposed method is efficient compared with existing approaches. The application and advantages of the proposed method are demonstrated by analysis of a case study.
Real-time, continuous large particle monitoring for CMP slurry quality control

With each new technology node, the cost of scratches during chemical-mechanical planarization (CMP) becomes higher in terms of tool downtime, process yield, and device reliability. Large particles (LPC) in the slurry are known to increase the likelihood of scratching; therefore, considerable resources are spent to quantify their number [1-4] and improve methods for detection [5, 6]. This paper explores a relatively new technology for large particle counting, the SlurryScope from Vantage Technology Corporation, as a potential means for more advanced processing and control of slurry supplied to the CMP line.
Newton-Kantorovich and Modified Gradient - Inversion Algorithms Applied to Ipswich Data

The present paper considers the application of the Newton-Kantorovich and modified-gradient methods to the Ipswich data. The object is assumed to be an inhomogeneous lossy dielectric cylinder of arbitrary cross section. Both inverse-scattering methods are based on electric-field integral representations. The Newton-Kantorovich technique builds up the solution by solving successively the forward problem and a linear inverse problem. This method needs regularization, and we use either the identity operator or a gradient operator for regularization. The modified-gradient method is iterative, as is the Newton algorithm, but does not involve a linearization at each step of the nonlinear inverse problem. Results of inversions with both methods, on two known impenetrable targets, are discussed.