Miracle-dz/UniFAR-FTUs huggingface dataset:
Removing Shadows using Flash/Noflash Image Edges

Flash/noflash pairs have been used for noise-reduction in ambient-light images. But not explicitly studied is the problem of shadows in the ambient images. While shadows are lessened in a flash image, other problems arise, and other shadows are produced. It is known that we can in fact produce a flash-only (no ambient) image by subtracting the two images, but the result is not as pleasant as the ambient image, because of several artifacts due to the flash. Here, we use the pure-flash image to detect the ambient shadows. We argue that first going to a "spectrally sharpened" color space, and then focusing on the difference in a log domain of the flash image minus the ambient image, gives a very simple feature space consisting of two components-one in an illuminant-change 3-vector direction, and one along the gray axis. This space provides excellent separation of the shadow and nonshadow areas. Inserting edges from the flash image within the ambient-shadow region into the ambient image edge map and inverting Poisson's equation fills in the shadow. In this way, we arrive at an image with the advantages of the ambient-only image-warmth, no flash effects such as disturbing illumination dropoff with distance, pixel saturation etc.-but no shadows
Harmonic Frequency Estimation Algorithm based on ESPRIT and MSWFin Power System

The paper points out the deficiency in the current harmonic frequency estimation algorithm in power system. In order to improve the detection accuracy and reduce the computational complexity, it combines the ESPRIT algorithm with multistage Wiener filter (MSWF) recurrence to achieve fast estimation of harmonic frequency. Theoretical analysis and simulation experiment show that the algorithm has relatively low requirement for data amount, has good frequency resolution characteristics and anti-jamming capability, and thus ideally suited for harmonic analysis in power system.
E‐learning and retention: key factors influencing student withdrawal

This study examines the causes for student withdrawals experienced in the E‐College Wales BA Enterprise programme. These key causes, identified by interview with former students are contrasted against the existing literature. The study found that successful e‐learners were typically female, non‐HE qualified, self employed and aged between 31 and 50. Eight prime causes of withdrawal were identified including technical problems, pressure of work and lack of time, which where categorised as extrinsic or intrinsic. Intrinsic factors were identified as internal course related barriers, which could be influenced by the course team. Extrinsic factors are barriers to e‐learning, which are external to the University such as employment issues and personal problems. This study contributes to knowledge in providing a conceptual framework for managing withdrawals and retentions illustrating key bodies and their interactions and identifying key strategies to overcome their negative influence. This paper will assist e‐learning providers in identifying and differentiating between causes of student withdrawal and creating strategies and systems to monitor and improve student retention.
Web-based progressive geometry transmission using subdivision-surface wavelets

Web-based geometry transmission profits from a transmission system, which is both progressive and compressive. For this application, the wavelet transform has emerged as a suitable tool. We present a new zerotree coding scheme for compressing coefficients resulting from the wavelet transform of B-spline and Catmull-Clark surfaces. It results from a generalization of the original zerotree coding algorithm for image compression. The main idea is the construction of a suitable forest-structure of wavelet coefficients. Furthermore we present a system architecture for web-based progressive geometry transmission. Its main features are the separation of the transmission algorithms from the implementation of several geometry types, a set of parameters for regulating transmission properties, and a thread system for concurrent receiving and visualizing a scene. The power of the zerotree coding scheme is demonstrated by some numerical examples.
Deregulated FGF and homeotic gene expression underlies cerebellar vermis hypoplasia in CHARGE syndrome

Mutations in CHD7 are the major cause of CHARGE syndrome, an autosomal dominant disorder with an estimated prevalence of 1/15,000. We have little understanding of the disruptions in the developmental programme that underpin brain defects associated with this syndrome. Using mouse models, we show that Chd7 haploinsufficiency results in reduced Fgf8 expression in the isthmus organiser (IsO), an embryonic signalling centre that directs early cerebellar development. Consistent with this observation, Chd7 and Fgf8 loss-of-function alleles interact during cerebellar development. CHD7 associates with Otx2 and Gbx2 regulatory elements and altered expression of these homeobox genes implicates CHD7 in the maintenance of cerebellar identity during embryogenesis. Finally, we report cerebellar vermis hypoplasia in 35% of CHARGE syndrome patients with a proven CHD7 mutation. These observations provide key insights into the molecular aetiology of cerebellar defects in CHARGE syndrome and link reduced FGF signalling to cerebellar vermis hypoplasia in a human syndrome. DOI: http://dx.doi. org/10.7554/eLife.01305. 001
Automatic Addressee Identification Based on Participants' Head Orientation and Utterances for Multiparty Conversations

We propose a method that uses the participants' head orientation and utterances for automatically identifying the addressee of each utterance in face-to-face multiparty conversations, such as meetings. First, each participant's head orientation is determined through vision-based detection and the presence/absence of utterances is extracted using the power of voices captured by microphones. Second, gaze direction (whom each participant is looking at) is estimated from just detected head orientation using the support vector machine. Third, several related features such as amount and frequency of gaze and eye contact are calculated in each utterance interval. Finally, a Bayesian Network is used to classify each utterance into one of two types of utterances: (a) the speaker is addressing a single participant and (b) the speaker is addressing all participants. Experiments on addressee estimation with 3-person conversations confirm the usefulness of our method
Enriched Environment Increases the Myelinated Nerve Fibers of Aged Rat Corpus Callosum

In this study, the effect of enriched environment (EE) on the spatial learning of aged rats was examined, and then the effects of EE on the aged corpus callosum (CC) were investigated by means of the modern stereological methods. We found that EE significantly improved the spatial learning of aged rats. The CC volume, the total volume of the myelinated fibers and total volume of the myelin sheaths in the CC, the total length of the myelinated fibers in the CC of enriched rats were significantly increased when compared to standard rats. The increase of the myelinated fibers in enriched rat CC might provide one of the structural bases for the enrichment‐related improvement of the spatial learning. This study provided, to the best of our knowledge, the first evidence of environmental enrichment‐induced increases of the CC and the myelinated fibers in the CC of aged rats. Anat Rec, , 2012. © 2012 Wiley Periodicals Inc.
Calibration Approach and Results of the COCOMO II Post- Architecture Model

The COCOMO II model was created to meet the need for a cost model that accounted for future software development practices. This paper describes some of the experiences learned in calibrating the COCOMO II Post-Architecture model from the 1997 dataset of 83 observations. The results of the multiple regression analysis, their implications, and the future calibration strategy of Bayesian analysis are discussed. TITLE OF PAPER: Calibration Approach and Results of the COCOMO II Post-Architecture Model
Interpreting CNN knowledge via an Explanatory Graph

This paper learns a graphical model, namely an explanatory graph, which reveals the knowledge hierarchy hidden inside a pre-trained CNN. Considering that each filter in a conv-layer of a pre-trained CNN usually represents a mixture of object parts, we propose a simple yet efficient method to automatically disentangles different part patterns from each filter, and construct an explanatory graph. In the explanatory graph, each node represents a part pattern, and each edge encodes co-activation relationships and spatial relationships between patterns. More importantly, we learn the explanatory graph for a pre-trained CNN in an unsupervised manner, i.e., without a need of annotating object parts. Experiments show that each graph node consistently represents the same object part through different images. We transfer part patterns in the explanatory graph to the task of part localization, and our method significantly outperforms other approaches.
Topic and topic-comment constructions in Mandarin Chinese

This article attempts to provide a precise definition for topic and to derive most of the properties of topic from this definition. The main assumption is that the topic-comment construction is a syntactic device employed to fulfill certain discourse functions. Topic is always related to a position inside the comment. Since topic has no independent thematic role but always depends on an element inside the comment for its thematic role, it has no syntactic function of its own. This dependence relationship is subject to locality constraints.
Performance evaluation of cluster-based homogeneous multiprocessor system-on-chip using FPGA device

the cluster-based multiprocessor system-on-chip (MPSoC), which adopts the hybrid interconnection composed of both bus-based and NoC architecture, is a new infrastructure for MPSoC. For obtaining the fast exploration of multiple hardware (HW) and software (SW) implementation alternatives with accurate estimations of performance to tune the MPSoC architecture in an early stage of the design process, this paper use the FPGA device to prototype the cluster-based MPSoC with 17 processing cores. And, a suite of benchmarks, including several parallel applications with different characteristic of parallelism, workload and communication pattern, are designed and presented in this paper. The experiment results show that, the highest speedup ratio is up to 15.850.
AIS Electronic Library (AISeL)

Many studies show that named entities are closely related to users' search behaviors, which brings increasing interest in studying named entities in search logs recently. This paper addresses the problem of forming fine grained semantic clusters of named entities within a broad domain such as “company”, and generating keywords for each cluster, which help users to interpret the embedded semantic information in the cluster. By exploring contexts, URLs and session IDs as features of named entities, a three-phase approach proposed in this paper first disambiguates named entities according to the features. Then it properly weights the features with a novel measurement, calculates the semantic similarity between named entities with the weighted feature space, and clusters named entities accordingly. After that, keywords for the clusters are generated using a text-oriented graph ranking algorithm. Each phase of the proposed approach solves problems that are not addressed in existing works
Dual Mechanisms of sHA 14-1 in Inducing Cell Death through Endoplasmic Reticulum and Mitochondria

HA 14-1 is a small-molecule Bcl-2 antagonist that promotes apoptosis in malignant cells, but its mechanism of action is not well defined. We recently reported that HA 14-1 has a half-life of only 15 min in vitro, which led us to develop a stable analog of HA 14-1 (sHA 14-1). The current study characterizes its mode of action. Because of the antiapoptotic function of Bcl-2 family proteins on the endoplasmic reticulum (ER) and mitochondria, the effect of sHA 14-1 on both organelles was evaluated. sHA 14-1 induced ER calcium release in human leukemic cells within 1 min, followed by induction of the ER stress-inducible transcription factor ATF4. Similar kinetics and stronger intensity of ER calcium release were induced by the sarcoendoplasmic reticulum Ca2+-ATPase (SERCA) inhibitor thapsigargin, accompanied by similar kinetics and intensity of ATF4 induction. sHA 14-1 directly inhibited SERCA enzymatic activity but had no effect on the inositol triphosphate receptor. Evaluation of the mitochondrial pathway showed that sHA 14-1 triggered a loss of mitochondrial transmembrane potential (Δψm) and weak caspase-9 activation, whereas thapsigargin had no effect. (R)-4-(3-Dimethylamino-1-phenylsulfanylmethyl-propylamino)-N-{4-[4-(4′-chloro-biphenyl-2-ylmethyl)-piperazin-1-yl]-benzoyl}-3-nitrobenzenesulfonamide (ABT-737), a well established small-molecule Bcl-2 antagonist, rapidly induced loss of Δψm and caspase-9 activation but had no effect on the ER. The pan-caspase inhibitor N-benzyloxycarbonyl-Val-Ala-Asp-fluoromethyl ketone had some protective effect on sHA 14-1-induced cell death. These collective results suggest a unique dual targeting mechanism of sHA 14-1 on the apoptotic resistance machinery of tumor cells that includes antiapoptotic Bcl-2 family proteins and SERCA proteins.
Blind Speech Separation with GCC-NMF

We introduce a blind source separation algorithm named GCCNMF that combines unsupervised dictionary learning via nonnegative matrix factorization (NMF) with spatial localization via the generalized cross correlation (GCC) method. Dictionary learning is performed on the mixture signal, with separation subsequently achieved by grouping dictionary atoms, over time, according to their spatial origins. Separation quality is evaluated using publicly available data from the SiSEC signal separation evaluation campaign consisting of stereo recordings of 3 and 4 concurrent speakers in reverberant environments. Performance is quantified using perceptual and SNRbased measures with the PEASS and BSS Eval toolkits, respectively. We compare our approach with other NMF-based speech separation algorithms including unsupervised and semisupervised approaches. GCC-NMF outperforms the unsupervised model-based approach that combines NMF with spatial covariance mixture models, and compares favourably to semisupervised approaches that leverage prior knowledge and information, despite being purely unsupervised itself.
An improved random decision trees algorithm with application to land cover classification

Random decision trees algorithm, which is no need to count images and has good portability, is a great prospective method for land cover remote sensing classification at present. An improved random decision trees algorithm with application to land cover remote sensing classification was proposed in this paper. Firstly, in accordance with the low operation efficiency of random decision trees algorithm, an improved random decision trees algorithm was presented by adding tree balance factor, setting node impurity and distinguishing sample types. Secondly, by taking the ALOS images of Longmen city of Guangdong Province in China as study object, the remote sensing classification was conducted using the improved random decision trees algorithm. Finally, a comparison study was proceeded to compare the improved random decision trees algorithm with maximum likelihood classification method. The results indicate that the classification precision is improved from 81.46% to 87.53% and Kappa coefficient is up to 0.8524. By taking extreme imbalanced decision trees, node impurity and distinguishing sample types into consideration, the improved random decision trees algorithm can improve the efficiency and accuracy of land cover remote sensing classification.
STFT Phase Reconstruction in Voiced Speech for an Improved Single-Channel Speech Enhancement

The enhancement of speech which is corrupted by noise is commonly performed in the short-time discrete Fourier transform domain. In case only a single microphone signal is available, typically only the spectral amplitude is modified. However, it has recently been shown that an improved spectral phase can as well be utilized for speech enhancement, e.g., for phase-sensitive amplitude estimation. In this paper, we therefore present a method to reconstruct the spectral phase of voiced speech from only the fundamental frequency and the noisy observation. The importance of the spectral phase is highlighted and we elaborate on the reason why noise reduction can be achieved by modifications of the spectral phase. We show that, when the noisy phase is enhanced using the proposed phase reconstruction, instrumental measures predict an increase of speech quality over a range of signal to noise ratios, even without explicit amplitude enhancement.
Epsilon Equitable Partition: On Scheduling Data Loading and View Maintenance in Soft Real-time Data Warehouses

Data warehouses contain historic data providing information for analytical processing, decision making and data mining tools. However, several business intelligence applications nowadays require access to real-time data to make sound decisions. As a consequence, there is a great demand to incorporate new data from sources to the data warehouse as fast as possible. That motivates the construction of real-time data warehouse. Despite high demand, moving from a traditional data warehouse to a real-time one is not straightforward since we have to deal with the problem of e‐ciently scheduling various activities, viz., updates, view maintenances and OLAP transactions in a timely manner. In addition, OLAP transactions are now associated with deadlines (transaction timeliness) and data freshness requirement (data timeliness). Balancing between these two requirements poses another challenge in real-time data warehousing context. In this paper, we present an e‐cient technique aimed at updating data and performing view maintenance for real-time data warehouses while still enforcing these two timing requirements for the OLAP transactions. Our proposed approach aims at addressing the issues of applying updates and performing view maintenance while still efiectively serving user OLAP queries in real-time data warehouse environment. Through extensive empirical studies, we demonstrate the e‐ciency of ORAD in achieving the goal of building a real-time data warehouse.
Cloning of a catabolite repression control (crc) gene from Pseudomonas aeruginosa, expression of the gene in Escherichia coli, and identification of the gene product in Pseudomonas aeruginosa

Mutants which are defective in catabolite repression control (CRC) of multiple independently regulated catabolic pathways have been previously described. The mutations were mapped at 11 min on the Pseudomonas aeruginosa chromosome and designated crc. This report describes the cloning of a gene which restores normal CRC to these Crc- mutants in trans. The gene expressing this CRC activity was subcloned on a 2-kb piece of DNA. When this 2-kb fragment was placed in a plasmid behind a phage T7 promoter and transcribed by T7 RNA polymerase, a soluble protein with a molecular weight (MW) of about 30,000 was produced in Escherichia coli. A soluble protein of identical size was overproduced in a Crc- mutant when it contained the 2-kb fragment on a multicopy plasmid. This protein could not be detected in the mutant containing the vector without the 2-kb insert or with no plasmid. When a 0.3-kb AccI fragment was removed from the crc gene and replaced with a kanamycin resistance cassette, the interrupted crc gene no longer restored CRC to the mutant, and the mutant containing the interrupted gene no longer overproduced the 30,000-MW protein. Pools of intracellular cyclic AMP and the activities of adenylate cyclase and phosphodiesterase were measured in mutant and wild-type strains with and without a plasmid containing the crc gene. No consistent differences between any strains were found in any case. These results provide original evidence for a 30,000-MW protein encoded by crc+ that is required for wild-type CRC in P. aeruginosa and confirms earlier reports that the mode of CRC is cyclic AMP independent in this bacterium.
Software Maintenance

The term maintenance, when accompanied to software, assumes a meaning profoundly different from the meaning it assumes in any other engineering discipline. In fact, many engineering disciplines intend maintenance as the process of keeping something in working order, in repair. The key concept is the deterioration of an engineering artifact due to the use and the passing of time; the aim of maintenance is therefore to keep the artifact’s functionality in line with that defined and registered at the time of release.
Regulation of cell division and expansion by sugar and auxin signaling

Plant growth and development are modulated by concerted actions of a variety of signaling molecules. In recent years, evidence has emerged on the roles of sugar and auxin signals network in diverse aspects of plant growth and development. Here, based on recent progress of genetic analyses and gene expression profiling studies, we summarize the functional similarities, diversities, and their interactions of sugar and auxin signals in regulating two major processes of plant development: cell division and cell expansion. We focus on roles of sugar and auxin signaling in both vegetative and reproductive tissues including developing seed.
Possible application of MPW effect for sensitive acceleration measurements

This paper examines the "magnetic potential well" effect by the example of two ring-shaped superconductive coils. This effect allows us to create a noncontact magnetic suspension of one coil and to define its movements by measuring the current in the stationary coil. It is shown that the system of these two coils is unstable with respect to the tilt angle. The new construction of the levitated coil, which allows us to create the completely stable suspension is examined. The solution of the equation of test mass motion and the acceleration-to-current transfer function for low-frequency acceleration are found. The other type of superconducting accelerometer is briefly described for comparison.
Improved Extend Kalman particle filter based on Markov chain Monte Carlo for nonlinear state estimation

Considering the problem of poor tracking accuracy and particle degradation in the traditional particle filter algorithm, a new improved particle filter algorithm with the Markov chain Monte Carlo (MCMC) and extended particle filter is discussed. The algorithm uses Extend Kalman filter to generate a proposal distribution, which can integrate latest observation information to get the posterior probability distribution that is more in line with the true state. Meanwhile, the algorithm is optimized by MCMC sampling method, which makes the particles more diverse. The simulation results show that the improved extend Kalman particle filter solves particle degradation effectively and improves tracking accuracy.