Miracle-dz/UniFAR-FTUs huggingface dataset:
Classifying imbalanced dataset based on minority detection

Classifying imbalanced dataset has recently become an important problem in many industrial and financial applications. In this paper, a novel method for combing minority detection algorithm and solving optimization problem to classify imbalanced dataset was presented. We empirically evaluate the proposed approach using a number of UCI datasets, and experiment results show that our novel method is superior to the state-of-the-art methods in the literature and scales well to large, high dimensional databases.
Molecular characterization of patients with pathologic complete response or early failure after neoadjuvant chemotherapy for locally advanced breast cancer using next generation sequencing and nCounter assay

Neoadjuvant chemotherapy (NAC) has the added advantage of increasing breast conservation rates with equivalent survival outcomes compared with adjuvant chemotherapy. A subset of breast cancer patients who received NAC experienced early failure (EF) during the course of therapy or within a short period after curative breast surgery. In contrast, patients with pathological complete response (pCR) were reported to have markedly favorable outcomes. This study was performed to identify actionable mutation(s) and to explain refractoriness and responsiveness to NAC. Included in this analysis were 76 patients among 397 with locally advanced breast cancer for whom a preoperative fresh-frozen paraffin-embedded tumor block was available for next-generation sequencing using AmpliSeq. The incidence of missense mutations in KRAS was much higher in patients with EF than in other groups (p < 0.01). In contrast, polymorphisms of the cMET gene were found in patients with pCR exclusively (p < 0.01).
A High Throughput and Data Reuse Architecture for H.264/AVC Deblocking Filter

In this paper, we propose a high throughput and data reuse architecture for de-blocking filter in H.264/AVC. There are two SRAMs exploited in the design. One is 144times32 bits single-port SRAM, and the other is 16times32 bits two-port SRAM. We use the group-of-pixel access method to store the pixels in SRAMs instead of the column-of-pixel or row-of-pixel approach. In the algorithm level, we modify the filtering order in the de-blocking filter without violating the H.264/AVC standard. Therefore, we efficiently use the data reuse skill to reduce the access frequency of SRAMs. We implement this architecture with UMC 0.18 mum cell library, and the maximum clock frequency we can achieve is 100 MHz. The simulation results show that the total number of logic gate counts is 16.6k. When the clock frequency equals 100 MHz, it can process 14619 macroblocks in 1/30 second. In other words, we achieve 4XGA (2048times1536) @30 frames/sec when we set the clock frequency to 85 MHz
Fault Diagnosis of Blast Furnace Based on DAGSVM

For achieving high efficiency of artificial intelligence applied in decision-making system of blast furnace, and reducing high technique demands to operators, a new multi-classification method based on support vector machines (SVMs) is proposed. In order to avoid dimension disaster and solve multi-classification problem, use decision directed acyclic graph (DDAG) algorithm combined with each kernel function, and map the training samples into high dimension space utilizing the statistic learning theory. Then compare different performance of each kernel function referring to the actual process data, and select the proper one to construct diagnosis classifier. Through tested different multi-classification strategies, simulation results show that DAGSVM model is superior to the others on testing accuracy and has efficient classification ability
Application of neural networks in talent management

Study of talent management is getting more attentions in the recent years. It was found that there are no easy classification methods for verifying talents. This paper discusses the application of neural networks for a talent matrix based talent classification process. The proposed method is easy to implement, and free from biasing and nepotism.
Feature Extraction Technique for Human Face Recognition - A Hybrid Approach

This paper presents a new feature extraction technique for recognizing human faces. The proposed method uses hybrid feature extraction techniques such as Principal Component Analysis and Gabor Wavelet are combined together. The classifier k-Nearest Neighbor is used for classification. For experimentation JAFEE and YALE face databases are used to test and achieved better performance of proposed method. The performance of proposed method on JAFFE and Yale face database are compared with known other methods.
Multi-Resolution Analysis Based MRI Image Quality Analysisusing DT-CWT Based Preprocessing Techniques

— The main objective of this paper is to improve the image quality by de-noising and resolution enhancement Techniques. The medical image quality parameters are mainly noise and resolution. This paper targets the average, median and wiener filters for image denoising and Discrete Wavelet Transform (DWT) and Dual tree Complex Wavelet Transform (DT-CWT) techniques for resolution enhancement, and it shows the results comparisons between DWT and DT-CWT. The performance of these techniques is evaluated using Peak Signal to Noise Ratio (PSNR).
Load flow analysis of low voltage dc networks with photovoltaic

Even though the power systems for the last century have been running on ac, with the emerging dc technologies such as solar photovoltaic (PV), LED lights, electric vehicles (EVs) and so on the interest for dc networks are also increasing. Rather than the traditional practice of inverting the dc power output of PVs to ac, it would be efficient if the dc power is used without inverting. With the development of the low voltage dc (LVdc) networks, it is essential to develop tools to analyze these networks. In this paper, a load flow program was developed to analyze LVdc networks that incorporate PV generation modules. The PV modules were modeled with its dc/dc converter in Simulink. The load flow study has been carried out on LVdc network using three different methods and the results were compared.
Study of AIS application for Vessel Traffic Service

This paper analyzed the performance of AIS (Automatic Identification System) application in Vessel Traffic Service (VTS), and simulated the time slot occupied schedule of SOTDMA (Self-Organized TDMA) communication protocol of AIS. By the result of simulation the measures of how to increase the capacity of the AIS network in different conditions and how to avoid the network congestion in crowded VTS area were discussed. The study of this paper is available for the vessel traffic management and is meaningful for keeping the AIS network more stably.
Construction of Pancreatic Cancer Classifier Based on SVM Optimized by Improved FOA

A novel method is proposed to establish the pancreatic cancer classifier. Firstly, the concept of quantum and fruit fly optimal algorithm (FOA) are introduced, respectively. Then FOA is improved by quantum coding and quantum operation, and a new smell concentration determination function is defined. Finally, the improved FOA is used to optimize the parameters of support vector machine (SVM) and the classifier is established by optimized SVM. In order to verify the effectiveness of the proposed method, SVM and other classification methods have been chosen as the comparing methods. The experimental results show that the proposed method can improve the classifier performance and cost less time.
K-Subspaces Quantization for Approximate Nearest Neighbor Search

Approximate Nearest Neighbor (ANN) search has become a popular approach for performing fast and efficient retrieval on very large-scale datasets in recent years, as the size and dimension of data grow continuously. In this paper, we propose a novel vector quantization method for ANN search which enables faster and more accurate retrieval on publicly available datasets. We define vector quantization as a multiple affine subspace learning problem and explore the quantization centroids on multiple affine subspaces. We propose an iterative approach to minimize the quantization error in order to create a novel quantization scheme, which outperforms the state-of-the-art algorithms. The computational cost of our method is also comparable to that of the competing methods.
RPSGAe – Reduced Pareto Set Genetic Algorithm : A Multiobjective Genetic Algorithm with Elitism

In this paper a Multiobjective Optimization Genetic Algorithm, named Reduced Pareto Set Genetic Algorithm with Elitism (RPSGAe), is presented and its performance assessed. The algorithm is compared with other MOEA ́s using three difficult problems from the literature and a sophisticated statistical comparison technique. The preliminary results obtained showed that the RPSGAe outperform the other algorithms tested.
LEGO® Bricks as Building Blocks for Centimeter-Scale Biological Environments: The Case of Plants

LEGO bricks are commercially available interlocking pieces of plastic that are conventionally used as toys. We describe their use to build engineered environments for cm-scale biological systems, in particular plant roots. Specifically, we take advantage of the unique modularity of these building blocks to create inexpensive, transparent, reconfigurable, and highly scalable environments for plant growth in which structural obstacles and chemical gradients can be precisely engineered to mimic soil.
Maximizing reserve capacity for a signalized road network design problem

For an area traffic control road network with expansions of link capacity, the maximum possible increase in travel demands is considered while total delays for travelers are minimized with respect to the common cycle time, the starts and durations of green times and the offsets. Using the concept of reserve capacity of signal-controlled junctions, the problem of finding the maximum possible increase in traffic demands and determining optimal link capacity expansions can be formulated as a mathematical program with equilibrium constraints (MPEC). In this paper, we present a new solution approach for simultaneously solving the maximum increase in travel demands and minimizing link capacity expansion investment together with total delays of travelers on the basis of TRANSYT model. Subject to strict complementary slackness, we propose two MPEC problems where the equilibrium constraints are of KKT conditions. A projected quasi-Newton method is proposed to effectively solve this problem to the KKT points. Numerical computations are made on a real data signal-controlled network where good results are obtained
The Semblance of Truth: The Development of Dialogue in Computer-Based Characters

Using a play written by the author as a case study this paper examines the development of computer characters in a theatrical production. In particular, it examines the use of interaction, audio and visual interfaces, and variation in prosody to generate 'a semblance of truth' that Coleridge argued is a requirement of the 'willing suspension of disbelief'. Further, the paper argues, following the logic of the "Media Equation" by Reeves and Nass, that it is belief, not disbelief, that is automatic. From this stand point, the paper argues that an audience would accept computer characters in the same manner as they would accept human characters.
Sensitivity analysis for a forest growth model: A statistical and time-dependent point of view

Increasing number of computer models are being used to simulate and predict the state of certain systems, in which parameter calibration and model output uncertainties co-exist due to the incomplete understanding of the system under simulation and biased model structure. In this paper, we demonstrated the ability of using sensitivity analysis, which include both screening and variance-based methods, to explore model structure and behavior. A forest growth model 3-PG2 and 141 plots of Corymbia maculata and Eucalyptus cladocalyx are used. Two model outputs, leaf area index and root biomass, were evaluated. Comparability between screening and variance-based methods and the change in sensitivities over time were assessed. High consistency was found and the variance-based method exhibited excellent convergence and stable sensitivity rankings. The results show that for each model output, the methods presented here can effectively identify the relative sensitivities of each input parameter. The results present some instructive hints about the model structure and underlying model behavior evolution features as simulation period becoming longer. This study shows that the sensitivity analysis methods are effective tools in model calibration and identification.
Salivary gland diseases in children

Salivary gland diseases in children are rare, apart from viral-induced diseases. Nevertheless, it is essential for the otolaryngologist to recognize these uncommon findings in children and adolescents and to diagnose and initiate the proper treatment. The present work provides an overview of the entire spectrum of congenital and acquired diseases of the salivary glands in childhood and adolescence. The current literature was reviewed and the results discussed and summarized. Besides congenital diseases of the salivary glands in children, the main etiologies of viral and bacterial infections, autoimmune diseases and tumors of the salivary glands were considered. In addition to the known facts, new developments in diagnostics, imaging and therapy, including sialendoscopy in obstructive diseases and chronic recurrent juvenile sialadenitis were taken into account. In addition, systemic causes of salivary gland swelling and the treatment of sialorrhoea were discussed. Although salivary gland diseases in children are usually included in the pathology of the adult, they differ in their incidence and sometimes in their symptoms. Clinical diagnostics and especially the surgical treatment are influenced by a stringent indications and a less invasive strategy. Due to the rarity of tumors of the salivary glands in children, it is recommended to treat them in a specialized center with greater surgical experience. Altogether the knowledge of the differential diagnoses in salivary gland diseases in children is important for otolaryngologists, to indicate the proper therapeutic approach.
Image Quality in Helical Cone-Beam CT 3 D Reconstructions of Low Contrast Objects

— This paper concerns image reconstruction for helical x-ray transmission tomography (CT) with multi-row detectors. The aim of this work was (i) to perform numerical studies (simulation) on Katsevich and FDK-type algorithms for helical CBCT (using a flat panel detector) and (ii) to assess image quality of these reconstructions (visually and using objective image characteristics). It is observed that the two algorithms produce similar quality if the cone angle is not large and/or there is no sharp density change along the z-direction. Feldkamp-type algorithm runs faster, is less sensitive to noise, more sensitive to motion, and produces more artifacts than the Katsevich-type algorithm, which is preferred due to its exactness nature.
DirectShow Application in LED Panel Display System

A new DirectShow application in the field of LED Panel display system is shown in this paper. It realizes video processing functions with DirectShow architecture on computer. Source Filter and many Transform Filters, which provided by Microsoft Co., transform source video into RGB24 format. Then, the video data are scaled up/down to LED panel resolution by Fixformat Filter which inherite CTramsformfilter baseclass. After that, the R/G/B values of video data are adjusted in CCorrect Filter to adapt LED Panel display. Finally, the processed video is shown on LED Wall through DVI or VGA interface. Our experimental results demonstrate that this system makes a good performance. It is greatly simplify the functions of Sending-Board, Receiving-Board, and Control-Scanning-Board in display system of the LED Wall. The total cost will be cut down observably, if we can transplant the filters into the embedded platform, to build a special video processing system for LED Panel display.
Energy, the Heckscher-Ohlin theorem, and U. S. international trade

An empirical model of U.S./foreign transactions shows the U.S. to have a comparative advantage in labor-intensive output and a disadvantage in an energy-capital input. The labor-intensive advantage is apparent when traded goods are defined to include intra-industry trade and when sectors are identified by their net trade balance. The findings of Leontief and Baldwin that import-competing production is relatively labor-intensive is substantiated. The model used incorporates energy as a third input to determine the outcome of energy conservation. The export of labor and capital during the 1960s is shown to balance the import of energy, although complimentarity can be demonstrated for energy-labor only. 25 references.
How to reach ‘hard-to-reach’ older people for research: The TIBaR model of recruitment

Recruiting older persons with diverse health statuses as participants in research projects is a challenge for health researchers, particularly because persons with health impairments and in socially disadvantaged living conditions are difficult to reach. This article presents a step model for gaining access to older people who are difficult to contact. The step model is based on the literature and a qualitative analysis of documentation, field notes and memos that stem from the recruitment processes of two studies from the German research consortium ‘Autonomy despite multimorbidity in old age’, both of which also included older persons who would qualify as ‘hard-to-reach’. The analysis followed the method of Grounded Theory and aimed to understand the social process of ‘recruitment’. Four steps of the recruitment process were identified that had been applied – intentionally or unintentionally – in both of the projects, i.e., the qualitative as well as the quantitative projects: 1. build up Trust, 2. offer Incentives, 3. identify individual Barriers and 4. be Responsive (TIBaR). The step model provides information for facilitating access to various target groups for qualitative as well as quantitative research designs. However, its implementation requires time, financial resources, flexibility and appropriately qualified staff members.
Interaction in creative tasks

The design of tools for creative activities affects the creative processes and output of users. In this paper we consider how an understanding of creative interaction can inform the design of support tools in a creative domain, and where creative needs cross domain boundaries. Using observations of musical composers we analyse the theoretical approaches to understanding creativity and their use to HCI. Cycles of ideation and evaluation are suggested as atomic elements of creative interactions, with the representation of ideas a central activity for individual and collaborating composers. A model of collaborative composition was developed, along with an analysis of the representational types used in the domain. This led to the design and evaluation of a prototype Sonic Sketchpad for musical idea representation.
Guaranteed Performance Routing of Unpredictable Traffic With Fast Path Restoration

Two-phase routing, where traffic is first distributed to intermediate nodes before being routed to the final destination, has been recently proposed for handling widely fluctuating traffic without the need to adapt network routing to changing traffic. Preconfiguring the network in a traffic-independent manner using two-phase routing simplifies network operation considerably. In this paper, we extend this routing scheme by providing resiliency against link failures through fast path restoration along disjoint end-to-end backup paths. We view this as important progress toward adding carrier-class reliability to the robustness of the scheme so as to facilitate its future deployment in Internet service provider (ISP) networks. On the theoretical side, the main contribution of the paper is the development of linear-programming-based and fast combinatorial algorithms for two-phase routing with fast path restoration so as to minimize the maximum utilization of any link in the network, or equivalently, maximize the throughput. The algorithms developed are fully polynomial time approximation schemes (FPTAS)-for any given epsiv > 0, an FPTAS guarantees a solution that is within a (1+epsiv)-factor of the optimum and runs in time polynomial in the input size and [ 1/(\relax epsiv)]. To the best of our knowledge, this is the first work in the literature that considers making the scheme resilient to link failures through preprovisioned fast restoration mechanisms. We evaluate the performance of fast path restoration (in terms of throughput) and compare it to that of unprotected routing. For our experiments, we use actual ISP network topologies collected for the Rocketfuel project and three research network topologies.
Magnetic Fields in Star-forming Molecular Clouds. IV. Polarimetry of the Filamentary NGC 2068 Cloud in Orion B

We present submillimeter polarimetry at 850 μm toward the filamentary star-forming region associated with the reflection nebulosity NGC 2068 in Orion B. These data were obtained using the James Clerk Maxwell Telescope's Submillimeter Common-User Bolometric Array polarimeter. The polarization pattern observed is not consistent with that expected for a field geometry defined by a single mean field direction. There are three distinct distributions of polarization angle, which could represent regions of differing inclination and/or field geometry within the filamentary gas. In general, the polarization pattern does not correlate with the underlying total dust emission. The presence of varying inclinations against the plane of the sky is consistent with the comparison of the 850 μm continuum emission to the optical emission from the Palomar Observatory Sky Survey, which shows that the western dust emission lies in the foreground of the optical nebula, while the eastern dust emission originates in the background. Percentage polarizations are high, particularly toward the northeast region of the cloud. The mean polarization percentage in the region is 5.0% with a standard deviation of 3.1%. Depolarization toward high intensities is identified in all parts of the filament.