Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative investigation of reflection and band gap properties of finite periodic wideband artificial magnetic conductor surfaces for microwave circuits applications in X‐band

In this study, novel designs of artificial magnetic conductors (AMCs) for wideband operation are introduced. By using two techniques of the planar parasitic patches and stacked elements, AMC unit cells are achieved. The first design of the AMC unit cell is composed of four symmetric patches with two arms, which are coupled to a rhombic patch at the center. The second AMC design is configured of two stacked patches, which are connected together through the air spacing. The first and second AMC designs operate at the frequencies of 10.15 and 10.65 GHz with ±90° reflection phase bandwidths of 8 to 12.38 GHz (43.15%) and 8 to 12.90 GHz (46%), respectively, for X‐band operation. The proposed AMC unit cells present prominent features such as symmetric structures and wide bandwidths with distinct capabilities. To achieve an accurate evaluation of AMC performance, the reflection and band gap properties of the finite periodic AMC surfaces are investigated. The finite periodic arrays of the AMC reflectors are implemented and tested. The measured results show that they can be applied for wideband applications in microwave circuits and low profile antennas. The 15 × 15 AMC planar and stacked arrays under normal incidence operate at the frequencies of 9.89 and 10.25 GHz with the measured bandwidths of 7.85 to 12.02 GHz and 7.77 to 12.58 GHz, respectively. In addition, to identify the band gap properties of the finite periodic planar and stacked AMC arrays, the method of the suspended microstrip line is applied. For this purpose, the measured band gaps of the planar and stacked arrays include the ranges of 8.12 to 12.63 GHz and 7.81 to 12.10 GHz below −20 dB, respectively.
Low-Temperature $p$-Type Microcrystalline Silicon as Carrier Selective Contact for Silicon Heterojunction Solar Cells

Silicon heterojunction (SHJ) solar cells have reached record efficiency, particularly in all-back contacted architectures. Despite this, two-side contacted SHJ cells still suffer from parasitic absorption and series resistance losses in the amorphous silicon contacts. An alternative to the doped amorphous silicon layer is microcrystalline silicon, which exhibits improved transparency and charge transport, while maintaining the superior passivation quality of all-silicon contact stacks. However, depositing thin, highly crystalline films has remained a challenge until recently. In this work, we use deposition temperatures <200 °C to improve the performance of <inline-formula><tex-math notation="LaTeX">$p$</tex-math></inline-formula>-type <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>c-Si:H contact layers. With these layers, we demonstrate <inline-formula><tex-math notation="LaTeX">$J_{\text{sc}}$</tex-math></inline-formula> gains of 1 mA/cm<inline-formula><tex-math notation="LaTeX">$^2$</tex-math></inline-formula>, while reducing series resistance below 1 <inline-formula><tex-math notation="LaTeX">$\Omega$</tex-math></inline-formula>cm<inline-formula><tex-math notation="LaTeX">$^2$</tex-math></inline-formula>, leading to screen printed 4 cm<inline-formula><tex-math notation="LaTeX">$^2$</tex-math></inline-formula> cells with certified <inline-formula><tex-math notation="LaTeX">$\eta =\text{23.45}\%$</tex-math></inline-formula>. Using a suite of device and material characterization techniques, we show that reduced deposition temperature leads to an increase in crystalline volume fraction from 35% to 55% for <inline-formula><tex-math notation="LaTeX">$p$</tex-math></inline-formula>-type films, which mitigates parasitic absorption in the front contact and facilitates hole extraction. These improvements are explained as resulting from higher transparency in the <inline-formula><tex-math notation="LaTeX">$p$</tex-math></inline-formula>-type layer accompanied by higher band bending in the c-Si wafer. These findings provide a method to improve SHJ solar cells performance, while offering insight into the importance of band bending considerations when optimizing heterojunction designs.
Copper micro-electrode fabrication using laser printing and laser sintering processes for on-chip antennas on flexible integrated circuits

Recent advances in flexible electronics have highlighted the importance of high throughput, digital additive microfabrication techniques. In this work, we demonstrate the combination of laser printing and laser sintering of a novel copper nanoparticle ink onto flexible substrates in order to produce oxide free conductive copper patterns in ambient atmospheric conditions. The printed patterns exhibit high reproducibility, very low resistivity (about 2x bulk), and negligible oxidation according to Raman spectroscopy. The process has been employed for the fabrication of an on-chip antenna on a flexible substrate for use in combination with a flexible circuit, in applications where a small form factor and simplicity of integration are required alongside ultra-low cost, e.g. consumable tagging.
Deep learning versus classical neural approach to mammogram recognition

Bull. Pol. Ac. : Tech. 66(6) 2018 Abstract. Automatic recognition of mammographic images in breast cancer is a complex issue due to the confusing appearance of some perfectly normal tissues which look like masses. The existing computer-aided systems suffer from non-satisfactory accuracy of cancer detection. This paper addresses this problem and proposes two alternative techniques of mammogram recognition: the application of a variety of methods for definition of numerical image descriptors in combination with an efficient SVM classifier (so-called classical approach) and application of deep learning in the form of convolutional neural networks, enhanced with additional transformations of input mammographic images. The key point of the first approach is defining the proper numerical image descriptors and selecting the set which is the most class discriminative. To achieve better performance of the classifier, many image descriptors were defined by means of applying different characterization of the images: Hilbert curve representation, Kolmogorov-Smirnov statistics, the maximum subregion principle, percolation theory, fractal texture descriptors as well as application of wavelet and wavelet packets. Thanks to them, better description of the basic image properties has been obtained. In the case of deep learning, the features are automatically extracted as part of convolutional neural network learning. To get better quality of results, additional representations of mammograms, in the form of nonnegative matrix factorization and the self-similarity principle, have been proposed. The methods applied were evaluated based on a large database composed of 10,168 regions of interest in mammographic images taken from the DDSM database. Experimental results prove the advantage of deep learning over traditional approach to image recognition. Our best average accuracy in recognizing abnormal cases (malignant plus benign versus healthy) was 85.83%, with sensitivity of 82.82%, specificity of 86.59% and AUC = 0.919. These results are among the best for this massive database.
Potential applications of nanoshell bow-tie antennas for biological imaging and hyperthermia therapy

Abstract. Silver nanoshell bow-tie antennas, two separate triangular dielectric cores covered by thin silver shells, have the potential of being used in different absorption- and scattering-based applications. The fields are highly localized in the gap region between the two components of the antenna. The dependence of the near-field and far-field spectra of silica-core silver nanoshells on antenna geometrical parameters, such as length, bow angle, gap width, and shell thickness, are investigated by applying the finite element method. Also, the effect of the dielectric permittivity of the antenna core is theoretically studied. The results show how the position and intensity of the electric field, absorption, scattering, and extinction resonance peak can be tuned within visible and near-infrared regions. By investigating the absorption and scattering spectra, we have designed appropriate silver nanoshell bow-tie antennas for the absorption- and scattering-based applications, such as hyperthermia therapy and biological imaging. The introduced nanoshells have high potential to be used as effective contrast and therapeutic agents.
Bottleneck focused heuristic algorithm for flow shop scheduling problem

To solve flow shop scheduling problem with the makespan minimization criterion,a bottleneck focused heuristic algorithm was proposed a ccording to the characteristics of workpiece time.Different machines generally had different load,to construct initial workpiece sequence,this characteristic was fully used.The workpieces with shorter processing time before bottleneck s tage and with longer processing time after bottleneck stage were processed prior ity.At every stage before or after bottleneck,the workpiece sequence was adjus ted according to features of workpiece processing time before or after bottlenec k if there were workpieces waiting to be processed.Finally,workpiece adjacent pairwise interchanges and insertion operation were used to improve the initial s cheduling.The proposed heuristic algorithm was performed well when bottleneck t ends to middle stage or workpiece processing time at bottleneck tends to increas e.The data experimental results indicated the effectiveness of the proposed app roach.
Design of auto-marking software framework for Java programming questions

After analyzing the characteristics of object-oriented programming and its marking rules,an auto-marking technology based on reflection mechanism for Java programming questions is presented.In this technology,class file is judged object,marking item is judged unit.With the technology,the shortcomings of the current auto-marking technology are overcome,the inherent features of object-oriented programming are followed.Then an auto-marking software framework is designed and implemented.With the software framework,an auto-marking system or exercise evaluation system related to Java programming can be build quickly.Finally,effectiveness of the software framework is demonstrated by practical application.
Response anomalies in discrete choice experiments for environmental valuation

The use of discrete choice experiments (DCEs) to value environmental goods and services has been rapidly increasing over the last years. However, many studies call into question the validity of this approach. Biases in welfare estimates derived from DCEs may arise from response behavior which is not fully consistent with one or more of the assumptions underlying stated preference approaches. Since preferences are elicited in surveys, the central question is whether anomalous response behavior is triggered by the survey design. This cumulative dissertation analyzes response anomalies in DCEs for environmental valuation. By designing and evaluating two large-scale, nation-wide online surveys each time implementing a split sample approach, the influence of choice task complexity, attribute thresholds and survey consequentiality is investigated systematically. First, the impact of choice task complexity on survey drop-outs, choice consistency, the attendance to attributes and the status quo effect is studied by systematically varying the design dimensions of the DCE following a design plan originally introduced in transportation research. It is shown that the complexity of the DCE impacts marginal as well as non-marginal welfare estimates. With respect to each individual design dimension, survey drop-outs are found to be positively related to the number of choice sets, alternatives and attributes. Choices tend to become more consistent the more choice sets are presented as well as with a narrow level range. While the attendance to attributes is negatively affected by the number of choice sets and alternatives, status quo choices are observed to decrease with the number of alternatives and increase with the number of choice sets, the level range and the similarity between alternatives. Second, stated information on attribute cut-offs is used to study threshold-based decision making. Results suggest that prior cut-off elicitation influences willingness to pay estimates. Moreover, respondents are observed to employ cut-offs, which they are, however, in many cases willing to violate when having to make trade-offs in the DCE. Third, it is investigated whether information on how survey results would be used as well as perceived survey consequentiality affect preferences. It is observed that neither the information about, nor the perception of survey consequentiality impact preferences. Overall, the results of this dissertation suggest the design of the survey, in general, and the complexity of the DCE, in particular, might influence preferences. This emphasizes the need to further identify and accommodate heterogeneous decision making in DCEs and discrete choice models.
Synchronized adaptive control for coordinating manipulators with time‐varying actuator constraint and uncertain dynamics

This paper addresses the control issue for cooperative visual servoing manipulators on strongly connected graph with communication delays, in which case that the uncertain robot dynamics and kinematics, uncalibrated camera model, and actuator constraint are simultaneously considered. An adaptive cooperative image‐based approach is established to overcome the control difficulty arising from nonlinear coupling between visual model and robot agents. To estimate the coupled camera‐robot parameters, a novel adaptive strategy is developed and its superiority mainly lies in the containment of both individual image‐space errors and the synchronous errors among networked robots; thus, the cooperative performance is significantly strengthened. Moreover, the proposed cooperative controller with a Nussbaum‐type gain is implemented to both globally stabilize the closed‐loop systems and realize the synchronization control objective under the existence of unknown and time‐varying actuator constraint. Finally, simulations are carried out to validate the developed approach.
Clustering Based Steganographic Approach for Secure Data Transfer

Providing security for the message during transmission is a thought-provoking task. To accomplish this goal many cryptographic and steganographic algorithms are being used. Cryptographic algorithms transform the original message into a cipher text before transmission, whereas the basic idea used in Steganography is to hide the existence of the message in a media. This enables the existence of secret data to be known only to the authorized sender and the receiver. In this paper a newfangled method based on clustering and noise addition is proposed to enhance the security of the hidden data. The proposed method consist of two steps. In the first step the pixels of the cover image are grouped into different clusters using k-means clustering algorithm which is followed by the embedding process. In the Second step a random noise is added to each pixel in all the clusters. Experimental results are compared with existing steganography techniques, which shows the proposed algorithm not only achieves same embedding capacity but also enhances the PSNR of the stego image.
Generalized full matching and extrapolation of the results from a large-scale voter mobilization experiment.

Matching is an important tool in causal inference. The method provides a conceptually straightforward way to make groups of units comparable on observed characteristics. The use of the method is, however, limited to situations where the study design is fairly simple and the sample is moderately sized. We illustrate the issue by revisiting a large-scale voter mobilization experiment that took place in Michigan for the 2006 election. We ask what the causal effects would have been if the treatments in the experiment were scaled up to the full population. Matching could help us answer this question, but no existing matching method can accommodate the six treatment arms and the 6,762,701 observations involved in the study. To offer a solution this and similar empirical problems, we introduce a generalization of the full matching method and an associated algorithm. The method can be used with any number of treatment conditions, and it is shown to produce near-optimal matchings. The worst case maximum within-group dissimilarity is no worse than four times the optimal solution, and simulation results indicate that its performance is considerably closer to the optimal solution on average. Despite its performance, the algorithm is fast and uses little memory. It terminates, on average, in linearithmic time using linear space. This enables investigators to construct well-performing matchings within minutes even in complex studies with samples of several million units.
Comparison of Microseismic Events Concurrently Acquired with Geophones and hDVS

The fibre-optic distributed vibration sensor (hDVS) is considered a disruptive technology for geophysical measurements. Previous works have demonstrated the use of the hDVS for a number of applications, such as vertical seismic profiling (VSP), pressure measurement and flow monitoring. We present results of monitoring a stimulation treatment with both downhole geophones and hDVS. This work compares the microseismic activity acquired with both systems and gives an insight on the maturity of the technology for hydraulic-fracturing monitoring. In particular, a direct comparison between traces validates the hDVS as a single component measurement and permits study of the system’s frequency response. Analysis of the entire monitoring job shows that 3.5% of the events recorded on the downhole array are visible in the fibre data.
Ciphertext Query Method Based on Multi-Attribute Keywords

— Following the widespread application of cloud computing, many users outsource local data to cloud server. Users encrypt their data before outsourcing makes the traditional query method failure. Aiming at the problem of slow query speed and low accuracy of ciphertext query, an improved ciphertext query method based on multi-attribute keywords is proposed through the research of existing ciphertext query technique. The method establishes security index through multi-attribute characteristic vector, it conducts correlation calculation according to the sort order selected by users and multi-keyword, and returns the most relevant sorted query result. Research result shows that the method improves query speed and accuracy of the query result.
Penyalahgunaan Narkoba pada Warga Binaaan di Rutan Klas I A Surakarta

Penyalahgunaan narkoba di Indonesia sebanyak 4,2 juta jiwa danberusia 10-59 tahun. Di wilayah Solo Raya pada tahun 2016 jumlahpengguna narkoba sebanyak 360 orang dan pada bulan Januari-April 2017 pengguna narkoba dengan rentang usia penggunanarkoba berkisar antara 20-40 tahunsebanyak 170 orang. Tujuandari penelitian ini adalah mendeskripsikan penyalahgunaan narkobapada warga binaan di Rutan Klas I A Surakarta. Metode yangdigunakan pada penelitian ini adalah deskriptif dengan jenispenelitian kualitatif dengan menggunakan pendekatan studi kasus.Informan penelitian ini terdiri dari 10 informan utama dan I infomantriangulasi dengan teknik purposive sampling. Hasil penelitian iniadalah proses penyalahgunaan narkoba yang terjadi pada wargabinaan diawali dengan mengetahui narkoba, coba-coba, memakainarkoba pada situasi tertentu, penggunaan secara intensif, dansakaw. Penyebab penyalahgunaan narkoba yaitu rasa ingin tahu,pengetahuan yang kurang tentang narkoba, persepsi tentang manfaatnarkoba yang dapat meningkatkan semangat, pengaruh sosial,pekerjaan dengan aktivitas yang padat, dan keluarga yang kurangharmonis. Simpulan pada penelitian ini adalah penggunaan narkobayang terjadi pada usia produktif dan pekerja dikarenakan narkobatersebut dapat menambah semangat untuk melakukan aktifitas yangberat. Oleh karena itu, Dinas Kesehatan dan BNN seharusnyamelakukan pengecekan penggunaan narkoba tidak hanya pada usiaremaja tetapi juga para pekerja baik sektor formal maupun nonformal.
Routing Algorithms for Mobile Ad Hoc Networks

In this chapter, we will introduce mobile ad hoc networks and issues related to routing data in such networks. Mobile ad hoc networks (MANET) are multi-hop networks made up of mobile nodes cooperating together to maintain the network connectivity. These kinds of network are very useful in situations where a temporary network is needed, such as military area, disaster area, and so on. MANET routing protocols are divided into two categories: proactive (table driven routing) and reactive (on-demand routing) routing. In conventional routing algorithms, if information is to be sent between two nodes, then the shortest path connecting these two nodes is found and used. However this approach does not take into consideration the fact that these devices are battery-operated, so the energy consumed is very important. A number of energy aware algorithms will be presented and their advantages and disadvantages will be discussed in this chapter. Also we will present and discuss the different metrics considered when designing a power aware routing algorithm
PD-Impedance Control of Docking Mechanism Composed of Intelligent Adaptive Structure

A docking mechanism and its control scheme are discussed for high per formance autonomous docking systems. A problem is to achieve soft docking of the system to a satellite approaching the docking mechanism with relative velocity and to absorb the shock of collision. To solve the problem an intelligent adaptive structure is examined to use as the docking mechanism. Control strategy for the docking mechanism is discussed and a PD-impedance control, i.e., impedance control combined with PD-control, is pro posed. The docking mechanism is controlled along an appropriate trajectory by using the PD-impedance control and the soft docking is achieved. Feasibility and advantage of the proposed scheme are verified by numerical simulations.
Evaluation of the Effectiveness of Cosine Similarity in Predicting Relevance between Paired Citing and Cited Sentences.

Citation analysis has a long history in Information Science. We examined the potential of cosine similarity to predict relevance between citing sentences and the articles they cite. An expert evaluated 22,697 pairs of cited and citing sentences, and marked 544 as relevant to one another. Cosine similarity gave 8386 of these pairs a similarity score over zero, which included 339 relevant pairs. (4% precision, 65% recall). Under 0.01% of each cited article was relevant to the citing sentence, making precise retrieval challenging. We performed a detailed error analysis. Cosine similarity performance was reduced by insufficient window size, affixes, hyphenation, acronyms and abbreviations. The following preprocessing steps would improve retrieval performance: using a stemming algorithm that accounts for prefixes, expanding the window of comparison from sentences to paragraphs, identifying synonyms and expanding abbreviations. Further investigation of the possibilities of cosine similarity is necessary, but such investigation is worth pursuit.