Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of hydrogen plasma for spherical Si solar cells fabricated by high speed dropping method

The effects of hydrogen passivation on spherical Si solar cells are investigated. The spherical Si solar cells fabricated from Si spheres produced by a dropping method are multicrystalline Si including dislocations and grain boundaries. In order to inactivate the defects, H-passivation was done by R.F. plasma. The short circuit current density and the open circuit voltage of spherical Si solar cells increased after H-passivation, consequently, the conversion efficiency was enhanced. Current voltage characteristics and external quantum efficiency indicated the bulk passivation effect of recombination centers. Laser beam induced current analysis indicated that the crystal defects such as dislocations and grain boundaries were electrically inactive by H-passivation.
FastMap: a fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets

A very promising idea for fast searching in traditional and multimedia databases is to map objects into points in k-d space, using k feature-extraction functions, provided by a domain expert [25]. Thus, we can subsequently use highly fine-tuned spatial access methods (SAMs), to answer several types of queries, including the 'Query By Example' type (which translates to a range query); the 'all pairs' query (which translates to a spatial join [8]); the nearest-neighbor or best-match query, etc.However, designing feature extraction functions can be hard. It is relatively easier for a domain expert to assess the similarity/distance of two objects. Given only the distance information though, it is not obvious how to map objects into points.This is exactly the topic of this paper. We describe a fast algorithm to map objects into points in some k-dimensional space (k is user-defined), such that the dis-similarities are preserved. There are two benefits from this mapping: (a) efficient retrieval, in conjunction with a SAM, as discussed before and (b) visualization and data-mining: the objects can now be plotted as points in 2-d or 3-d space, revealing potential clusters, correlations among attributes and other regularities that data-mining is looking for.We introduce an older method from pattern recognition, namely, Multi-Dimensional Scaling (MDS) [51]; although unsuitable for indexing, we use it as yardstick for our method. Then, we propose a much faster algorithm to solve the problem in hand, while in addition it allows for indexing. Experiments on real and synthetic data indeed show that the proposed algorithm is significantly faster than MDS, (being linear, as opposed to quadratic, on the database size N), while it manages to preserve distances and the overall structure of the data-set.
Cell design and comparative evaluation of a novel 1T memristor-based memory

CMOS is expected to soon meet the end of the Semiconductor Industry Technology Roadmap. This paper investigates the memristor as a post-CMOS component for memory design. The proposed cell requires one transistor and one memristor (i.e. 1T1M); this cell employs novel read and write mechanisms for improved performance. Initially, it is shown that differently from previous designs, the proposed scheme accomplishes a read operation that does not affect the memory state; this cell is assessed with respect to different parameters as related to its design (such as applied write voltage, memristor range and size). It is shown that at array-level, the write operation may still incur in a state change due to voltage degradation. A detailed assessment of the relationship between a linear array size (as dimension of a square memory array) and the cell parameters, is pursued. Moreover, a comparison with a DRAM cell (i.e. 1T1C) in CMOS is pursued; the advantages and disadvantages of DRAM versus memristor based arrays are then presented.
Virtual Machine Communication for the Implementation of Decision Support Systems

This paper presents the use of the virtual machine concept as a software engineering tool. The focus is on techniques that allow the rapid integration and assimilation of existing data, models, analytical facilities, report generation facilities, and data base management systems. Since many of these models, programs, and facilities run under different operating systems, they often are incompatible with each other. By combining multiple virtual machines in a particular configuration, and allowing for communication among them, it has been possible to overcome these difficulties. The result is a set of software engineering tools that seem particularly useful in decision support systems. We present the application of these tools along with the software techniques used to implement them, and quantify some of their costs and benefits.
Image Steganalysis with Binary Similarity Measures

We present a novel technique for steganalysis of images that have been subjected to embedding by steganographic algorithms. The seventh and eighth bit planes in an image are used for the computation of several binary similarity measures. The basic idea is that the correlation between the bit planes as well as the binary texture characteristics within the bit planes will differ between a stego image and a cover image. These telltale marks are used to construct a classifier that can distinguish between stego and cover images. We also provide experimental results using some of the latest steganographic algorithms. The proposed scheme is found to have complementary performance vis-à-vis Farid's scheme in that they outperform each other in alternate embedding techniques.
Notice of RetractionMoving average effect of the stock market in China: An analysis based on the textile section

This article study the theory and technology of the stock price's formation. One theory on the technical analysis theory of moving average is tested by using the 4 years'dates seclected from the 20 stocks on clothing section in the stock price. The results show that the combination of short and medium term combinations are valid, and the stock investment analysis has certain significance.
A Study on the Effect of Process Parameters on Surface Topography of Al Thin Films on Various Substrates Using AFM

Al thin films were prepared over different substrates at various process conditions using DC sputtering. The surface topography of all prepared films was examined using AFM technique. Very smooth, uniform and dense surface were observed for Al films coated over Glass substrates. The observed particle size was nano scale (20 -70 nm) for Glass substrates. Sputtering power showed immense effect on surface roughness with respective to Ar gas flow rate. Noticeable change on surface with large particles was observed in Copper substrates at various sputtering power and gas flow rate.
Algorithms for the Bregman k-Median problem

In this thesis, we study the k-median problem with respect to a dissimilarity measure Dφ from the family of Bregman divergences: Given a finite set P of size n from R, our goal is to find a set C of size k such that the sum of error cost(P,C) = ∑ p∈P minc∈C { Dφ(p, c) } is minimized. This problem plays an important role in applications from many different areas of computer science, such as information theory, statistics, data mining, and speech processing. Our main contribution is the development of a general framework of algorithms and techniques that is applicable to (almost) all Bregman divergences. In particular, we give a randomized approximation algorithm for the Bregman k-median problem that computes a (1 + e)-approximate solution using at most 2O(k/e)n arithmetic operations, including evaluations of Bregman divergence Dφ. In doing so, we give the first approximation algorithm known for this problem that provides any provable approximation guarantee. We also give a fast, practical, randomized approximation algorithm that computes an O(log k)-approximate solution for arbitrary input instances, or even an O(1)-approximate solution for certain, well separated input instances. In addition to that, we study the use of coresets in the context of Bregman k-median clusterings. In a nutshell, a coreset is a small (weighted) set that features the same clustering behavior as the original input set. We show how classical coreset constructions for the Euclidean k-means problem can be adapted to a special subfamily of the Bregman divergences, namely the class of Mahalanobis distances. We also give a new, randomized coreset construction for the Mahalanobis k-median problem in low dimensional spaces that has several practical advantages. Furthermore, by introducing the notion of weak coresets, we give the first coreset construction applicable to (almost) all Bregman k-median clustering problems. Using these weak coresets, we are able to give the currently asymptotically fastest (1 + e)-approximation algorithm known for the Bregman k-median problem. This algorithm uses at most O(kn)+2O(k/e) log(n) arithmetic operations, including evaluations of Bregman divergence Dφ.
Overscoping: Reasons and consequences — A case study on decision making in software product management

Efficient scope management is a core part of software release management and often a key factor in releasing successful software products to the market. In a case when not all the requirements for the next software product release are known ‘a priori’ and when new requirements are issued throughout the project, the risk of overscoping by including more functionality than can be implemented increases. In this paper, we report on findings from an empirical interview study about understanding the causes and effects of overscoping in a large-scale industrial set up. Six main causes of overscoping have been identified in this work, complemented by root cause analysis of the causes and concluded by effects of overscoping. The results provide an increased understanding of the scoping activity as a continuous activity and outline risks and issues that can lead to a situation of overscoping.
Partial Paging for Real-Time NoC Systems

In multiprocessor Network-on-Chip (NoC) architectures it is common that CPU local memory space is limited, with external memory accessed across the NoC infrastructure. Clearly it is imperative for real-time performance that local memory is used effectively, with code and data moved from external memory when required. One common approach is for the local memory to be comprised of two levels, ie. cache and memory. Software mechanisms are used to move code and data between local memory and external memory, eg. scratchpad mechanisms. In this paper we explore the issue of using paging to supplement this approach, ie. a hardware mechanism to automate movement of code and data between external memory and perCPU local memory within the NoC. This has wide-ranging potential benefits in from efficiency and real-time performance, through application programmability (ie. potential support of logical address spaces). However, the limited amounts of local memory raise the problem of thrashing. Therefore, we examine the effect of limiting thrashing effects by only loading the parts of pages that are referenced (rather than the entire page). The approach is assessed against a real-time video application, considering different page replacement policies.
Astrocytes refine cortical connectivity at dendritic spines

During cortical synaptic development, thalamic axons must establish synaptic connections despite the presence of the more abundant intracortical projections. How thalamocortical synapses are formed and maintained in this competitive environment is unknown. Here, we show that astrocyte-secreted protein hevin is required for normal thalamocortical synaptic connectivity in the mouse cortex. Absence of hevin results in a profound, long-lasting reduction in thalamocortical synapses accompanied by a transient increase in intracortical excitatory connections. Three-dimensional reconstructions of cortical neurons from serial section electron microscopy (ssEM) revealed that, during early postnatal development, dendritic spines often receive multiple excitatory inputs. Immuno-EM and confocal analyses revealed that majority of the spines with multiple excitatory contacts (SMECs) receive simultaneous thalamic and cortical inputs. Proportion of SMECs diminishes as the brain develops, but SMECs remain abundant in Hevin-null mice. These findings reveal that, through secretion of hevin, astrocytes control an important developmental synaptic refinement process at dendritic spines. DOI: http://dx.doi. org/10.7554/eLife.04047. 001
SE-CDA: A scalable and efficient community detection algorithm

Detecting communities is of great importance in various disciplines such as social media, biology and telephone networks, where systems are often represented as graphs. Community is formed by individuals such that those within a group interact with each other more frequently than with those outside the group. The communities have different properties such as node degree, betweenness, centrality, cluster coefficient and modularity. Discovering communities from social networks of big data scale on a single se quential machine is a tedious task. In this paper, we present a Scalable Community Detection Algorithm which relaxes the performance issues due to many I/Os. We adopt Girvan-Newman's modularity based hierarchical community detection algorithm in bottom u p a pproach an d proposed an approximation algorithm for community detection in a distributed environment. We developed our approach using MapReduce and Giraph computing platforms. Experimental results demonstrate that the proposed approach is more efficient than standard MapReduce approach and easily scaled to graph of any size.
HMMER web server: interactive sequence similarity searching

HMMER is a software suite for protein sequence similarity searches using probabilistic methods. Previously, HMMER has mainly been available only as a computationally intensive UNIX command-line tool, restricting its use. Recent advances in the software, HMMER3, have resulted in a 100-fold speed gain relative to previous versions. It is now feasible to make efficient profile hidden Markov model (profile HMM) searches via the web. A HMMER web server (http://hmmer.janelia.org) has been designed and implemented such that most protein database searches return within a few seconds. Methods are available for searching either a single protein sequence, multiple protein sequence alignment or profile HMM against a target sequence database, and for searching a protein sequence against Pfam. The web server is designed to cater to a range of different user expertise and accepts batch uploading of multiple queries at once. All search methods are also available as RESTful web services, thereby allowing them to be readily integrated as remotely executed tasks in locally scripted workflows. We have focused on minimizing search times and the ability to rapidly display tabular results, regardless of the number of matches found, developing graphical summaries of the search results to provide quick, intuitive appraisement of them.
Joint sensor registration and track-to-track fusion for distributed trackers

Sensor registration deals with the correction of registration errors and is an inherent problem in all multisensor tracking systems. Traditionally, it is viewed as a least squares or a maximum likelihood problem independent of the fusion problem. We formulate it as a Bayesian estimation problem where sensor registration and track-to-track fusion are treated as joint problems and provide solutions in cases 1) when sensor outputs (i.e., raw data) are available, and 2) when tracker outputs (i.e., tracks) are available. The solution to the latter problem is of particular significance in practical systems as band limited communication links render the transmission of raw data impractical and most of the practical fusion systems have to depend on tracker outputs rather than sensor outputs for fusion. We then show that, under linear Gaussian assumptions, the Bayesian approach leads to a registration solution based on equivalent measurements generated by geographically separated radar trackers. In addition, we show that equivalent measurements are a very effective way of handling sensor registration problem in clutter. Simulation results show that the proposed algorithm adequately estimates the biases, and the resulting central-level trucks are free of registration errors.
Faulty successive cancellation decoding of polar codes for the binary erasure channel

We study faulty successive cancellation decoding of polar codes for the binary erasure channel. To this end, we introduce a simple erasure-based fault model and we show that, under this model, polarization does not happen, meaning that fully reliable communication is not possible at any rate. Moreover, we provide numerical results for the frame erasure rate and bit erasure rate and we study an unequal error protection scheme that can significantly improve the performance of the faulty successive cancellation decoder with negligible overhead.
A GPU-based real-time traffic sign detection and recognition system

This paper presents a GPU-based system for real-time traffic sign detection and recognition which can classify 48 different traffic signs included in the library. The proposed design implementation has three stages: pre-processing, feature extraction and classification. For high-speed processing, we propose a window-based histogram of gradient algorithm that is highly optimized for parallel processing on a GPU. For detecting signs in various sizes, the processing was applied at 32 scale levels. For more accurate recognition, multiple levels of supported vector machines are employed to classify the traffic signs. The proposed system can process 27.9 frames per second video with active pixels of 1,628 × 1,236 resolution. Evaluating using the BelgiumTS dataset, the experimental results show the detection rate is about 91.69% with false positives per window of 3.39 × 10-5 and the recognition rate is about 93.77%.
Variation and inheritance of the Xanthomonas gene cluster required for activation of XA21-mediated immunity

The rice XA21-mediated immune response is activated upon recognition of the RaxX peptide produced by the bacterium Xanthomonas oryzae pv. oryzae (Xoo). The 60 residue RaxX precursor is posttranslationally modified to form a sulfated tyrosine peptide that shares sequence and functional similarity with the plant sulfated tyrosine (PSY) peptide hormones. The five kb raxX-raxSTAB gene cluster of Xoo encodes RaxX, the RaxST tyrosylprotein sulfotransferase, and the RaxA and RaxB components of a predicted type one secretion system. The identified the complete raxX-raxSTAB gene cluster is present only in Xanthomonas spp. , in five distinct lineages in addition to X. oryzae. The phylogenetic distribution of the raxX-raxSTAB gene cluster is consistent with the occurrence of multiple lateral transfer events during Xanthomonas speciation. RaxX variants representing each of the five lineages, and three Xoo RaxX variants, fail to activate the XA21-mediated immune response yet retain peptide hormone activity. These RaxX variants contain a restricted set of missense mutations, consistent with the hypothesis that selection acts to maintain peptide hormone-like function. These observations are also consistent with the hypothesis that the XA21 receptor evolved specifically to recognize Xoo RaxX.
Domain Adaptive Subspace Clustering

We propose domain adaptive extensions of the recently introduced sparse subspace clustering and low-rank representation-based subspace clustering algorithms for clustering data lying in a union of subspaces. We propose a general method that learns the projections of data in a space where the sparsity or low-rankness of data is maintained. We propose an efﬁcient iterative procedure for solving the proposed optimization problems. Various experiments on face, object and handwritten digits datasets show that the proposed methods can perform better than many competitive subspace clustering meth-ods.
EUVL mask substrate defect print study

Mask substrate defects continue to be one of the critical issues for EUV technology development. Current specifications call for allowable defects in the 25nm height range for production masks blanks. Simulations seem to indicate that defects as small as 3nm high will cause printable defects on the wafer. To study the effects of small aspect defects on the printed image we undertook a study to look at 10nm height (mask substrate size) defects. A mask was fabricated with 12nm height defects in arrays based on area. Defects of 110nm, 190nm, 300nm, and 1000nm were fabricated. Multi-layers were then deposited and the mask was patterned with line/space patterns with pitches (mask size) of 600nm, 800nm, and 1000nm. Wafers were then exposed using a well characterized resist and the results were analyzed. All sizes of defects printed at least once. The largest defect size (1000nm mask) caused multiple bridges to form while even the smallest defect size (110nm mask) could cause a bridge on the 600nm (mask size) pitch.
Purely Corpus-based Automatic Conversation Authoring

This paper presents an automatic corpus-based process to author an open-domain conversational strategy usable both in chatterbot systems and as a fallback strategy for out-of-domain human utterances. Our approach is implemented on a corpus of television drama subtitles. This system is used as a chatterbot system to collect a corpus of 41 open-domain textual dialogues with 27 human participants. The general capabilities of the system are studied through objective measures and subjective self-reports in terms of understandability, repetition and coherence of the system responses selected in reaction to human utterances. Subjective evaluations of the collected dialogues are presented with respect to amusement, engagement and enjoyability. The main factors influencing those dimensions in our chatterbot experiment are discussed.
Both Foot-and-Mouth Disease Virus and Bovine Viral Diarrhea Virus Replication are Inhibited by Mx1 Protein Originated from Porcine

Mx1 protein is I type interferons (IFNs)-induced 76-kDa guanosine triphosphatases (GTPases) that belong to the dynamin superfamily of large GTPases. Mx1 proteins have attracted attention because some display antiviral activity against pathogenic RNA and DNA viruses. Meanwhile, Mx1 gene generally exists in organisms or cells of mammalian, fish and chicken. Blocking a wide range of RNA virus replication by inhibiting nuclear viral mRNA synthesis is a unique property of Mx1 protein. In order to investigate a novel prevention measure against foot-and-mouth disease virus (FMDV) and bovine viral diarrhea virus (BVDV), which frequently break out in Xinjiang Uygur Autonomous Region of China, we investigated the effects of porcine Mx1 protein on FMDV and BVDV replication by measuring viral reverse transcriptase activity at various time intervals. In our study, Mx1 protein was overexpressed in BHK-21 and MDBK cells mediated by lentivirus prior to infect with FMDV and BVDV. FMDV and BVDV replication levels were monitored by quantitative real-Time PCR. The results showed porcine Mx1 overexpression significantly inhibited both FMDV and BVDV replication within 12 and 36 hours post-infection (pi). The finding may provide a new therapeutic approach for preventing from FDMV and BVDV infection.