Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling of Periodic Array of Cut-Through Slits With Sinusoidal Surface Conductivity at the Interfaces of an Anisotropic Medium

A periodic arrangement of 1-D slits carved in a perfect electric conductor is investigated, and an equivalent model which features sinusoidal surface conductivity on its upper and lower interfaces is derived. Therefore, and in sheer contrast to all the previous attempts that were successful in mimicking only the zeroth-order diffracted waves, it is capable of emulating both specular and nonspecular diffraction orders. The accuracy of the model is verified by the full-wave simulations. The proposed model is used to study the sharp Fano-type extraordinary transmission resonances arising in the structure. The transmission spectrum near these resonances is derived in terms of Fano resonance parameters. Furthermore, our model is used to explain the plasma-like behavior of the cut-through metallic slits in terms of the band bending caused by the periodicity of the surface conductivity. The analysis and design of applications which are devised based on the characteristics of higher Bloch orders can also be facilitated by this model.
Multi-UAVs Cooperative Path Planning Method based on Improved RRT Algorithm

This paper presents a cooperative path planning algorithm using improved Rapidly-exploring Random Trees (RRTs) to generate paths for multiple unmanned air vehicles (UAVs) in real time, from given starting locations to goal locations in the presence of unknown pop-up obstacles. Generating no conflicting paths in obstacle environments for a group of DAVs within a short time is a challenging task. Firstly, we propose an improved RRT by taking the maneuvering constraints of the DAVs into account and a simple and efficient path pruning method is designed to delete redundant nodes on the path. Secondly, a cooperative path planning method is developed that generate a low cost path to avoid collision when DAVs detect a dynamic teammate or pop-up obstacles. Simulation studies are carried out to show the performance of the proposed algorithm.
DESIGN OF MICRO PHOTON SIEVE ARRAYS FOR HIGH RESOLUTION LIGHT-FIELD CAPTURE IN PLENOPTIC CAMERAS

The design of micro photon sieve arrays (PSAs) is investigated for light-field capture with high spatial resolution in plenoptic cameras. A commercial very high-resolution full-frame camera with a manual lens is converted into a plenoptic camera for high-resolution depth image acquisition by using the designed PSA as an add-on diffractive optical element in place of an ordinary refractive microlens array or a diffractive micro Fresnel Zone Plate (FZP) array, which is used in integral imaging applications. The noise introduced by the diffractive nature of the optical element is reduced by standard image processing tools. The light-field data is also used for computational refocusing of the 3D scene with wave propagation tools.
Scaling a Fluorescent Detection System by Polymer-Assisted 3-D Integration of Heterogeneous Dies

Scaling by 3-D integration of various heterogeneous components enables miniaturized systems. However, the heterogeneous system integration is challenging due to the dissimilarities in materials and process used in fabrication of individual components. In this paper, we demonstrate a simple 3-D integration method for miniaturization of systems. Various components of the system were stacked using SU-8-based planarization and epoxy-based bonding. Spacer dielectric (SU-8) was patterned using photolithography for the formation of interconnect vias. Electrical interconnects over the large topography between the layers was formed by the screen printing of silver nanoparticle epoxy. Using this integration technique, we demonstrate a fluorescence-sensing platform consisting of a silicon photodetector, plastic optical filters, commercial LED, and a glass microheater chip. This paper resolves several fabrication challenges of planarization, stacking, and interconnection of these divergent chips. For example, the process incompatibility of the plastic optical filters was resolved by additional passivation using parylene-C. The functionality of the demonstrated system is verified by detecting the fluorescence property of Rhodamine B and Rhodamine 6G dyes. Rhodamine B’s sensitivity to temperature was also demonstrated using the on-chip microheater. This process flow can be scaled to stack a larger number of layers for demonstrations of more complicated systems with enhanced functionality and applications. [2018–0064]
Borsa İstanbul Gıda, İçecek Endeksine Kote İşletmelerin Finansal Performanslarının Veri Zarflama Analizi ile Ölçümü ve Malmquist Endeksine Göre Karşılaştırılması

Borsa Istanbul Gida, Icecek Endeksinde islem goren isletmelerin verimliliklerinin karsilastirilmasi amaciyla endeksten secilen isletmelerin finansal verimlilik degerleri 2010- 2012 donemine ait her bir yil icin finansal oranlari uzerinden Veri Zarflama Analizi ile olculmustur. Uygulanan analizler neticesinde hem verimli hem de verimsiz isletmeler tespit edilmis ayrica verimsiz olanlarin potansiyel iyilestirme oranlari hesaplanmistir. Calismanin sonunda ise her bir isletmeye ait verimlilik degerleri soz konusu donem icin Malmquist Endeksine gore karsilastirilmistir. Yapilan degerlendirmeler neticesinde ULKER hem her bir yilda verimli bulunan hem de verimlilik degerleri surekli artis gosteren tek isletme olarak tespit edilmistir.
Towards Cognitive Assisted Living 3.0

Considerable effort to manually set up the user’s context and too coarse-grained activity recognition results often make it difficult to set up active assisted living systems. In this paper we join our cognitive assistance system HBMS with the semantic web to (1) simplify the construction of user’s context model and to (2) improve the system’s activity recognition capability. We present how to describe non-smart resources like domestic appliances semantically to make their handling understandable for HBMS-System and interoperable with its environmental context model. Benefits of this semantic markup approach beyond the use for HBMS are discussed. Moreover, we show how personalized and adaptive HBMS user clients and the power of the HBMS environmental context model can be used to bridge an existing activity recognition gap.
Study of Exhaust Air Treatment From a Ship Building Factory Painting Facility Using Pulse Plasma Technology

Ship building companies are exposed to increasingly strict regulations on exhaust air from painting facilities, which current exhaust air treatment methods cannot adequately meet. We propose the use of a plasma system using a pulsed-power supply, which we constructed and tested at the painting facility of a ship building factory. Through gas chromatography and facility efficiency analysis, we found flexibility in design of the plasma system. We demonstrate the efficiency and safety of our plasma system, and emphasize the importance of posttreatment facilities for the secondary pollutant treatment.
MapReduce and Spark-based architecture for bi-class classification using SVM

Support Vector Machine (SVM) is a classifier widely used in machine learning because of its high generalization capacity. The sequential minimal optimization (SMO) its most popular implementation, scales somewhere between linear and quadratic in the training set size for various test problems. This fact makes using SVM to train large data sets have a high computational cost. SVM implementations on distributed systems such as MapReduce and Spark have shown efficiency to improve computational cost; this paper analyzes how data subset size and number of mapping tasks affects SVM performance on MapReduce and Spark. Also, a cost model as a useful tool for setting data subset size according to available hardware and data to be processed is proposed.
Output Agreement of a Class of Nonlinear Multi-Agent Systems with Switching Topologies

In this paper, output agreement problem of a class of nonlinear multi-agent systems with switching topologies is studied. By employing a new type of dynamic control law to the controlled agents, the switching and directed information flow topology is handled and by a state transformation the distributed control problem is successfully converted into network control problem with each subsystem has input-to-output stability (IOS) and unboundedness observability (UO) properties. Then, the cyclic-small-gain theorem is applied to conclude the conclusion that the output agreement objective is achieved.
Seamless Parametrization with Arbitrarily Prescribed Cones

Seamless global parametrization of surfaces is a key operation in geometry processing, e.g. for high-quality quad mesh generation. A common approach is to prescribe the parametric domain structure, in particular the locations of parametrization singularities (cones), and solve a non-convex optimization problem minimizing a distortion measure, with local injectivity imposed through either constraints or barrier terms. In both cases, an initial valid parametrization is essential to serve as feasible starting point for obtaining an optimized solution. While convexified versions of the constraints eliminate this initialization requirement, they narrow the range of solutions, causing some problem instances that actually do have a solution to become infeasible. We demonstrate that for arbitrary given sets of topologically admissible parametric cones with prescribed curvature, a global seamless parametrization always exists (with the exception of one well-known case). Importantly, our proof is constructive and directly leads to a general algorithm for computing such parametrizations. Most distinctively, this algorithm is bootstrapped with a convex optimization problem (solving for a conformal map), in tandem with a simple linear equation system (determining a seamless modification of this map). This initial map can then serve as valid starting point and be optimized with respect to application specific distortion measures using existing injectivity preserving methods.
The Noise Exposure Structured Interview (NESI): An Instrument for the Comprehensive Estimation of Lifetime Noise Exposure

Lifetime noise exposure is generally quantified by self-report. The accuracy of retrospective self-report is limited by respondent recall but is also bound to be influenced by reporting procedures. Such procedures are of variable quality in current measures of lifetime noise exposure, and off-the-shelf instruments are not readily available. The Noise Exposure Structured Interview (NESI) represents an attempt to draw together some of the stronger elements of existing procedures and to provide solutions to their outstanding limitations. Reporting is not restricted to prespecified exposure activities and instead encompasses all activities that the respondent has experienced as noisy (defined based on sound level estimated from vocal effort). Changing exposure habits over time are reported by dividing the lifespan into discrete periods in which exposure habits were approximately stable, with life milestones used to aid recall. Exposure duration, sound level, and use of hearing protection are reported for each life period separately. Simple-to-follow methods are provided for the estimation of free-field sound level, the sound level emitted by personal listening devices, and the attenuation provided by hearing protective equipment. An energy-based means of combining the resulting data is supplied, along with a primarily energy-based method for incorporating firearm-noise exposure. Finally, the NESI acknowledges the need of some users to tailor the procedures; this flexibility is afforded, and reasonable modifications are described. Competency needs of new users are addressed through detailed interview instructions (including troubleshooting tips) and a demonstration video. Limited evaluation data are available, and future efforts at evaluation are proposed.
Platinum (Pt) doped Nb2O5 for Enhancing Ultraviolet Photodetector

This work presents the development of Ultraviolet (UV) Photodetector based on platinum doped niobium oxide (Nb2O5) for enhancing UV Photodetector performance. The anodization duration was varied by using Ethylene Glycol and Ammonium Fluoride and observed by UV radiation with different voltage supply. The morphology of Nb2O5nanoporous was characterized by using FESEM. Metal contact with 30 nm thickness of platinum was used using Thermal Evaporator process. Different duration of anodized produces different sizes of nanoporous diameter that affected UV performance. Lastly, I-V characteristic was used to record the reading of UV performance for every sample substrate. The thinner the thickness of the substrate, the higher the performance of UV characterized.
Remaining Useful Life Prediction for Lithium-Ion Battery: A Deep Learning Approach

Accurate prediction of remaining useful life (RUL) of lithium-ion battery plays an increasingly crucial role in the intelligent battery health management systems. The advances in deep learning introduce new data-driven approaches to this problem. This paper proposes an integrated deep learning approach for RUL prediction of lithium-ion battery by integrating autoencoder with deep neural network (DNN). First, we present a multi-dimensional feature extraction method with autoencoder model to represent battery health degradation. Then, the RUL prediction model-based DNN is trained for multi-battery remaining cycle life estimation. The proposed approach is applied to the real data set of lithium-ion battery cycle life from NASA, and the experiment results show that the proposed approach can improve the accuracy of RUL prediction.
Evaluating the Benefits of the TimeSlips Creative Storytelling Program for Persons With Varying Degrees of Dementia Severity

Objectives: To evaluate the benefits of TimeSlips, a group creative storytelling intervention used in residential care settings, on quality of life (QOL), interactions with caregivers, and Mini-Mental State Examination (MMSE) scores for persons with varying degrees of dementia severity. Design: A mixed-methods approach was used weekly over a 6-month period to measure QOL and resident–caregiver relationships. Setting: A dementia care unit in Pennsylvania. Participants: Twenty-two residents with mild-to-severe dementia. Measurements: Dementia severity and QOL were assessed using the MMSE and Greater Cincinnati Chapter Well-Being Observational Tool. Resident–caregiver interactions were analyzed using a modified version of the Quality of Interactions Schedule. Semistructured interviews were conducted upon the study’s conclusion. Results: Quantitatively, participants initially classified with mild–moderate dementia were significantly more likely to experience positive benefits compared to those initially classified with severe dementia. There were no significant changes in dementia severity over time. There was also no change in QOL or resident–caregiver relationships for those with mild–moderate dementia over time, although there was a decrease in certain measures of QOL and resident–caregiver relationships for those with severe dementia. Qualitative analysis identified consistent benefits for residents with both mild–moderate and severe dementia over time. Conclusions: Mixed-methods analyses helped identify benefits of TimeSlips for persons at all levels of dementia severity, but particularly for those with milder dementia. Such an observation helps demonstrate how arts-based programs like TimeSlips can uniquely benefit people with advanced memory impairments and thereby support QOL.
The Thief Orienteering Problem: Formulation and Heuristic Approaches

This paper introduces the Thief Orienteering Problem (ThOP), a multi-component problem that combines two classic combinatorial problems: Orienteering Problem (OP) and Knapsack Problem (KP). In this problem, a person (called the thief) carries a capacitated knapsack and has a time limit to collect items distributed in a set of cities. The thief has fixed start and end points, begins his journey with the knapsack empty, and travels with speed inversely proportional to the knapsack weight. While there is time, the thief may visit the cities and collect items. The aim of the problem is to determine the thief's route and items to collect in order to maximize the knapsack profit. We formally describe the ThOP by a mixed integer non-linear programming formulation and present two heuristic approaches based on Iterated Local Search (ILS) and Biased Random-Key Genetic Algorithm (BRKGA) metaheuristics. Our results showed that BRKGA outperformed ILS for a large majority of instances.
Brain Tumor Segmentation Techniques in MRI images-An Analysis

Segmentation of complex images like that of medical background is very important for clinical research and diagnosis, and hence for treatment leading to a requirement for robust methods. Accurate measurements in brain tumor diagnosis is hard for there are diverse shapes, sizes and appearances of tumors. Tumors can grow suddenly and bluntly causing defects in surrounding tissues also, which gives an abnormal edge for healthy tissues as well. This paper presents major segmentation techniques for Tumor in brain MRI images. Preprocessing is inevitable step, artefacts otherwise lead to wrong diagnosis and mistreatment of the medical condition.
Optimal Trajectory Design of Flying by a Target Spacecraft

To fulfill fast inspection of a target spacecraft, a novel observation method based on fly-by is presented. The model of relative motion between the target and the observer is established first, and the practical detection requirements are taken into account in terms of some dynamic constraints. Thereafter, the problem of fly-by trajectory design is formalized as a dynamic optimization problem with the performance index of scanning angle within finite time. Furthermore, with the purpose of reducing computational difficulty, we introduce an approximating algorithm to simplify the original problem to be a static optimization problem, which can be solved by the SQP algorithm. Finally, the numerical simulations are performed to verify the fly-by observation can increase the speed of target inspection comparing with the traditional fly-around observation.
Throughput Analysis of Cooperative Spectrum Sensing with Hard-decision Fusion over Generalized κ – μ Fading Channel

In this paper, a cooperative spectrum sensing system (CSSS) based on energy detection method and hard-decision fusion is proposed. The performance through complementary receiver operating characteristics (CROC), total error rate (TER), and throughput is analytically investigated under the influence of noise and generalized κ – μ fading. More precisely, each cognitive radio (CR) senses the PU through erroneous sensing (S) channels and reports the sensing information in the form of binary-decision obtained using energy detector (ED) to fusion center (FC) through erroneous reporting (R) channels. Next, the hard-decision is performed at FC to obtain a global decision on the status (active or inactive) of the PU. Towards that, we derive a novel-analytic expression of detection probability subject to noise and κ – μ fading is derived. The analytical frame works based on derived expression for evaluating TER and throughput performance for any network and channel conditions are developed. Further, the CSSS performance for differen network parameters such as channel error probability, time bandwidth product, signal to noise ratio (SNR), number of CRs, detection threshold under various fusion rules is investigated. Finally, an optimal detection threshold, an optimal number of CRs, and maximum throughput for several network parameters subject fusion rule are also determined.
Mutual Regulation of TLR/NLR and CEACAM1 in the Intestinal Microvasculature: Implications for IBD Pathogenesis and Therapy.

Background Carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) displays multiple activities, among which pathogen binding and angiogenesis are particularly prominent. These same functions are also exerted by Toll- and NOD-like receptors (TLRs and NLRs), which are critical mediators of innate immune responses. We investigated whether a functional inter-relationship exists between CEACAM1 and TLRs and NLRs and its potential impact on induction of intestinal angiogenesis. Methods This hypothesis was tested using human intestinal microvascular endothelial cells, a unique cell population exposed to microbial products under physiological and pathological conditions. Results The results show that activation of TLR2/4, TLR4, NOD1, and NOD2 by specific bacterial ligands selectively and differentially upregulates the levels of cellular and soluble CEACAM1 produced by intestinal microvascular endothelial cells. The results also show that CEACAM1 regulates the migration, transmigration, and tube formation of these endothelial cells and mediates vessel sprouting induced by specific TLR and NLR bacterial ligands. Combined, these results demonstrate a close and reciprocal regulatory interaction between CEACAM1 and bacterial products in mediating multiple functions essential to new vessel formation in the gut mucosa. Conclusions A coordinated and reciprocal interaction of CEACAM1 and microbiota-derived factors is necessary to optimize angiogenesis in the gut mucosa. This suggests that a coordination of endogenous and exogenous innate immune responses is necessary to promote intestinal angiogenesis under physiological and inflammatory conditions such as inflammatory bowel disease.
A Ka-Band High Efficiency Doherty Power Amplifier MMIC using GaN-HEMT for 5G Application

This paper has reported a Ka-band (27-40GHz) high efficiency doherty power amplifier (DPA) MMIC (Monolithic Microwave Integrated Circuit) using GaN-HEMT for 5G application. To realize a high power and high efficiency DPA in Ka-band, a parasitic output capacitance (Cds) is compensated by shunt inductor through resonance using high accuracy large-signal model. As a result, the fabricated 2-stage DPA using GaN-HEMT achieves a measured saturation output power of 35.6dBm (3.6W) and peak PAE of 25.5%. PAE of 22.7% and 19.5% are obtained at 6dB and 8dB back-off, respectively. In addition, the measured ACLR is −25/−27dBc and PAE is 20.5% at average output power of 27.6dBm under 100MHz 64QAM modulated signal. To the best of author’s knowledge, the developed DPA is state-of-the art 5G amplifier at Ka-band.
A low-pass filter made up of the cylindrical through-silicon-via

the concept of three-dimensional integrated circuits has been widely practiced in many fields such as SoC (system on chip) DSP (image signal processor). It is well-known that through-silicon-via (TSV) has not only been used as interconnection between vertical layers but been applied to more fields like radio frequency (RF). In this paper, a low-pass filter (LPF) based on the cylindrical TSV consists of two planar spiral inductors and one TSV capacitor. The simulation result shows that the cutoff frequency is about 20GHz and the area is only 10850 um2.
Application of Ag/graphene composites in flexible electrical conductive adhesives

Flexible electrical conductive adhesives (FECAs) was developed using Ag microflakes (AgMFs), Ag nanodendrites/reduced graphene oxide (AgNDs/rGO) nanocomposites and thermoplastic polyurethane (TPU). In this work, AgNDs/rGO was synthesized via facile replacement reaction. Scanning electron microscopy (SEM) has been used to characterize the as-synthesized nanocomposites. The synthesized AgMFs/AgNDs/rGO/TPU flexible electrical conductive adhesives exhibited not only great flexibility but also excellent conductivity and stretchable. The resistivity of AgMFs and AgNDs/rGO filled conductive composites can reach 6.92×10-5 Ω•cm. In addition, the resistance is almost constant upon bending, twisting and stretching when the hybrids of AgMFs-AgNDs/rGO were employed. Importantly, AgMFs/AgNDs/rGO/TPU flexible electrical conductive adhesives can be used in flexible circuits which exhibit excellent electrical properties at different mechanical deformation.