Miracle-dz/UniFAR-FTUs huggingface dataset:
On the fly best view detection using graphics hardware

Selection of good camera positions has many applications in Computer Graphics. It can be used to compute a walkthrough inside a scene that shows a higher amount of information or to select a minimal set of views for Image- Based Rendering. However, the selection of a good view is costly, even when using OpenGL for fast rendering, as it is necessary to analyze a high amount of camera positions. In this paper we show how histograms, an OpenGL extension available in current graphics hardware, may be used together with an adaptive algorithm in order to obtain on the fly best views for objects of moderate complexity (several thousands of polygons).
Optimizing estradiol level for gonadotrophin-releasing hormone antagonist initiation among patients with simple tubal factor infertility

Objective The aim of this study is to investigate the optimal estradiol (E2) level on the day of gonadotropin-releasing hormone antagonist (GnRH-ant) initiation to maximize the clinical pregnancy rate (CPR) after fresh embryo transfer among patients with simple tubal factor infertility. Methods A retrospective cohort study was conducted in the Reproductive Medicine Center, the Second Hospital of Hebei Medical University. A total of 1,493 IVF-ET cycles of patients diagnosed with single tubal factor infertility from August 2016 to August 2021 were included and equally allocated into five distinct groups according to the quintile serum E2 levels on the day of GnRH-ant initiation. The five groups had similar baseline data except for antral follicle count. Result(s) The serum E 2 level on GnRH-ant initiation day was determined as an independent predictor of clinical pregnancy after adjusting for confounding factors such as age, infertility duration, body mass index, cycle number, antral follicle count, and the number of transferred embryos. Through smooth curve fitting, we found that, with the increase of serum E2 levels on the day of GnRH-ant initiation, CPR showed a trend of slight increase and then slight decrease. The maximal CPR was achieved when the serum E2 level on GnRH-ant initiation day was 498 pg/ml. When E2 was less than 498 pg/ml, the odds ratio (OR) of clinical pregnancy was 1.05 (95% CI: 1.00, 1.11, P = 0.0583). When E2 was greater than 498 pg/ml, the OR of clinical pregnancy was 0.97 (95% CI: 0.95, 0.98, P = 0.0003). Furthermore, CPR remained high when E2 was 436.8–658.6 pg/ml but declined significantly by more than 40% when E2 was ≥ 894.4 pg/ml (P < 0.05). Conclusion(s) The serum E2 level should be considered as an adjuvant parameter for GnRH-ant initiation. The best E2 value was 498 pg/ml, and GnRH-ant administration could be recommended to initiate when serum E2 was 436.8–658.6 pg/ml. If GnRH-ant was initiated when serum E2 was above 894.4 pg/ml, then the CPR after fresh embryo transfer may decline dramatically, and thus, cancellation of fresh embryo transfer and earlier initiation of GnRH-ant in future cycles should be considered.
Authentic leadership, perceived insider status, error management climate, and employee resilience: A cross-level study

Employee resilience is of great significance for organizations to resist pressures, overcome crises, and achieve sustainable development. However, existing research has largely failed to explore its situational triggers. Drawing on social information processing theory and social exchange theory, a cross-level study was conducted to theorize the underlying mechanisms through which authentic leadership facilitates employee resilience. Based on a two-wave time-lagged design, the data were obtained from 85 team leaders and 417 employees in China. The results of the cross-level model showed that authentic leadership was positively related to employee resilience. Perceived insider status and error management climate both played a partial mediating role in linking authentic leadership and employee resilience. Error management climate positively moderated the relationship between perceived insider status and employee resilience. This paper not only contributes to revealing the cross-level effect of authentic leadership on employee resilience but also provides some managerial practices.
M-DCF: a MAC protocol supporting QoS in ad hoc network

M-DCF, modified distribution coordination function, is proposed based on the characteristics of the IP frame network, which is applied to the WLAN ad hoc. Computer simulation shows that M-DCF can decrease the total frame dropping probability, voice frame dropping probability, voice frame contention delay, as well as data frame contention delay.
A General Explanation-Based Learning Mechanism and Its Application to Narrative Understanding

Explanation-based learning (EBL) is a learning method which uses existing knowledge of the domain to construct an explanation for why a specific example is a member of a concept or why a specific combination of actions achieves a goal. This explanation is then generalized in an analytical manner in order to produce a general concept description or plan schema. Although a number of exploratory EBL systems which operate in particular domains have previously been constructed, recent research in this area has led to the development of general mechanisms which can perform explanation-based learning in a wide variety of domains. This thesis describes a general EBL mechanism, EGGS, which can make use of declarative knowledge stored in the form of horn clauses, rewrite rules, or STRIPS operators. Numerous examples are presented illustrating its application to a wide variety of domains, including "blocks world" planning, logic circuit design, artifact recognition, and various forms of mathematical problem solving. The system is shown to improve its performance in each of these domains. EGGS has been most thoroughly tested as a component of a narrative understanding system, GENESIS, which improves its own performance through learning. GENESIS processes short English narratives and constructs explanations for characters' intentional behavior. When the system detects that a character has achieved an important goal by combining actions in an unfamiliar way, EGGS is used to generalize the specific explanation for how the goal was achieved into a general plan schema. The resulting schema is then retained by the system and indexed into its existing knowledge-base. This schema can then be used to process narratives which were previously beyond the system's capabilities. The thesis also discusses GENESIS' ability to learn meanings for words related to its learned schemata and reviews several recent psychological experiments which demonstrate that GENESIS can be productively interpreted as a cognitive model of certain types of human learning.
Security in Wireless Sensor Network: A Survey

-This paper present, detail discussion on Security in Wireless Sensor Network (WSN). Wireless sensor networks are generally set up for storing records from insecure environment. In the l ast decade, many advances in field of electronics and wireless communication technologies, have enabled the development of wireless sensor networks on larg e scale that consist of many thing as like that, low power, low-cost, and small-size sensor nodes. Senso r networks hold the facilitating, large-scale and rea ltime data processing in complex environments. Current applications of wireless sensor networks ar e in the fields of medical, battlefield monitoring, environment monitoring, surveillance and disaster prevention. To provide security and privacy to smal l sensor nodes is challenging issues, due to the limi ted capabilities of sensor nodes in terms of computatio n, communication, memory or storage, & energy supply. In this paper, Also focus on the security in different situation in wireless sensor network. KeywordsWireless Sensor Network, Node, Security, Attack, Communication, Attacker, Layering-Based Attacks, Synchronization, Self-Organization.
Identification of cuproptosis-associated IncRNAs signature and establishment of a novel nomogram for prognosis of stomach adenocarcinoma

Purpose: Stomach adenocarcinoma (STAD) is one of the common cancers globally. Cuproptosis is a newly identified cell death pattern. The role of cuproptosis-associated lncRNAs in STAD is unknown. Methods: STAD patient data from TCGA were used to identify prognostic lncRNAs by Cox regression and LASSO. A nomogram was constructed to predict patient survival. The biological profiles were evaluated through GO and KEGG. Results: We identified 298 cuproptosis-related lncRNAs and 13 survival-related lncRNAs. Patients could be categorized into either high risk group or low risk group with 9-lncRNA risk model with significantly different survival time (p < 0.001). ROC curve and nomogram confirmed the 9-lncRNA risk mode had good prediction capability. Patients in the lower risk score had high gene mutation burden. We also found that patients in the two groups might respond differently to immune checkpoint inhibitors and some anti-tumor compounds. Conclusion: The nomogram with 9-lncRNA may help guide treatment of STAD. Future clinical studies are necessary to verify the nomogram.
A Detailed Simulation Model of the HP 97560 Disk Drive

We implemented a detailed model of the HP 97560 disk drive, to replicate a model devised by Ruemmler and Wilkes (both of Hewlett-Packard, HP). Our model simulates one or more disk drives attached to one or more SCSI buses. The design is broken into three components: a test driver, the disk model itself, and the discrete-event simulation support. Thus, the disk model can be easily extracted and used in other simulation environments. We validated our model using traces obtained from HP, using the same "demerit" measure as Ruemmler and Wilkes. We obtained a demerit percentage of 3.9%, indicating that our model was extremely accurate. This paper describes our implementation, and is meant for those wishing to use our model, see our validation, or understand our code.
Analyzing Message Passing Programs on the Cray T3E with PAT and VAMPIR

Writing efficient parallel programs for a massively parallel system like the CRAY T3E is still a difficult task because such programs are typically very large and complex, not trivially parallelizable and their dynamic behavior is difficult to understand or predict. Therefore, runtime performance analysis tools are needed on such systems in addition to the normal programming environment tools like editors and debuggers. For the CRAY T3E, Silicon Graphics/Cray Research implemented and provides two performance analysis tools, Apprentice and PAT. Apprentice is a profiling tool which uses source code instrumentation through compiler switches and provides statistics on the level of functions and basic blocks. PAT, the Performance Analysis Tool, is actually several tools in one. It provides profiling through sampling and access to hardware performance information. It also includes an object code instrumenter which can be used for detailed call site profiling and gathering of function level hardware performance statistics. In a collaboration between Silicon Graphics/Cray Research and Forschungszentrum Julich, PAT was extended to also support event tracing. In this paper, we describe how the new extended PAT and VAMPIR, an event trace browser developed by Forschungszentrum Julich, can be used to analyze message passing programs on the CRAY T3E. The powerful trace browsing features of VAMPIR make it a perfect extension to PAT’s object instrumentation and tracing functionality. First, the features of PAT are described in detail. In order to analyze message passing programs, the message passing libraries of the CRAY T3E (MPI, PVM, and SHMEM) needed to be instrumented. This feature is described next. We then give an overview of VAMPIR and it’s functionality. With two small examples, we show how the combination of PAT’s object instrumentation features, the new message passing function wrapper library, and VAMPIR’s trace displays can be used to analyze message passing programs on the CRAY T3E to any detail.
Issues in routing for large and dynamic networks

The routing function is necessary in computer communication networks in order to create the appearance of complete connectivity in an environment of sparse physical links. The purpose of this dissertation is to examine ways of providing the routing function in large networks or networks which are characterized by frequent topological changes or both. The focus is on distributed routing algorithms because of their failsafe property. Two new event driven distributed route table update algorithms, A and B, are introduced and proven correct. Algorithm A requires less buffer space to store route tables than other event driven algorithms. Algorithm B, a variation of algorithm A, allows each node to maintain a source tree, i.e. a tree rooted at the node and containing the shortest path to all possible destinations in the network. The source tree may be used to implement source routing, i.e. the whole path from source to destination is determined at the source. Transient route table looping is also studied for algorithms A, B, as well as other algorithms in the literature. Hierarchical routing has been suggested in the literature as a means to reduce the size of the route tables when networks become very large. Reduction of the table size may also reduce the communication cost incurred during the update of the route tables. A possible effect of the shrinking of the route tables is that the resulting paths are not optimal. A classification of hierarchical routing schemes is introduced. The trade-off between between route table reduction and path length increase is studied in detail for two classes of schemes. Alternate policies for routing in the absence of necessary information are suggested and evaluated. In order to implement hierarchical routing it is necessary to partition the network into clusters. The network partitioning problem is abstracted to a graph partitioning problem which is shown to be NP complete. A new heuristic procedure, V3.2, is developed which is compared to the agglomerative method, a procedure suggested in the literature. V3.2 is shown to perform considerably better computationally as well as in terms of desired properties of the partitions. The comparison is performed by simulation experiments. An algorithm is developed to randomly generate connected networks suitable to be used in the simulations.
Bayesian State-Space Modelling on High-Performance Hardware Using LibBi

LibBi is a software package for state space modelling and Bayesian inference on modern computer hardware, including multi-core central processing units, many-core graphics processing units, and distributed-memory clusters of such devices. The software parses a domain-specific language for model specification, then optimizes, generates, compiles and runs code for the given model, inference method and hardware platform. In presenting the software, this work serves as an introduction to state space models and the specialized methods developed for Bayesian inference with them. The focus is on sequential Monte Carlo (SMC) methods such as the particle filter for state estimation, and the particle Markov chain Monte Carlo and SMC2 methods for parameter estimation. All are well-suited to current computer hardware. Two examples are given and developed throughout, one a linear three-element windkessel model of the human arterial system, the other a nonlinear Lorenz '96 model. These are specified in the prescribed modelling language, and LibBi demonstrated by performing inference with them. Empirical results are presented, including a performance comparison of the software with different hardware configurations.
Design of Fixed-Width Multiplier Using Baugh-Wooley Algorithm

This paper focuses on the design of fixed-width multipliers with Baugh-Wooley algorithm. The fixed width multipliers derived from Baugh-Wooley algorithm produce n-bit output product with n-bit multiplier and n-bit multiplicand. In previous papers the fixed-width signed multipliers are designed by using both half-adders and full-adders. In this paper we have designed the fixed width Baugh-Wooley multiplier by using only an array of full-adders and the final Ripple Carry Adder (RCA). We have implemented the Multiply and Accumulate (MAC) unit using fixed width signed multiplier and fixed width Baugh-Woolley multiplier. The main contribution of the proposed work is to reduce the area and power by designing the fixedwidth Baugh-Wooley multiplier. We also present the comparison results of parameters like power, area, gates and delay.
Fuzzy filter based on neural network and its application to image restoration

A novel fuzzy filter based on a neural network is proposed in order to remove salt and pepper noise on images. The filter proposed here is obtained as the sum of the input signal and non-linear transform on the output of fuzzy reasoning filter, and the non-linear transform is obtained by a trained neural network. Examples of processing actual images with salt and pepper noise are shown to verify the high performance of this filter. Moreover, the influence of the training signal on the filter performance is shown to be helpful for selecting the training signal.
Real‐time up‐converter from HDTV to 4K with super‐resolution: Breaking the Nyquist frequency barrier

This real‐time up‐converter from high‐definition television (HDTV) to 4K with a novel super‐resolution (SR) creates 4K video with frequency elements higher than the Nyquist frequency of the original HDTV video. The novel SR uses non‐linear signal processing to overcome the theoretical limitation of the Nyquist frequency.
Voicing detection in DAP-STC

Sinusoidal transform coding (STC) requires an all-pole representation of spectra derived periodically from the short-term speech spectral envelope and a "voicing probability" frequency f/sub v/ to divide each spectrum into two sub-bands: voiced below f/sub v/ and unvoiced above f/sub v/. Discrete all-pole (DAP) modeling may be applied to STC to improve the accuracy of the short-term spectral envelope for voiced speech with modifications to accommodate unvoiced speech and spectra which do not conform well to an all-pole model. This paper presents a novel approach to the determination of f/sub v/ which is appropriate when DAP is employed. It is a frequency-domain algorithm with an analysis-by-synthesis optimisation process. This approach improves the accuracy of DAP-STC modeled speech.
A General Technique For Inter-study Registration Of Multi-function And Multi-modality Images

A technique that can register anatomic/structural brain images (eg., MRI) with various functional images (eg., PET-FDG and PET-FDOPA) of the same subject has been developed. The procedure of this technique includes the following steps : (1) segmentation of MRI brain images into gray matter (GM), white matter (WM), cerebral spinal fluid (CSF), and Muscle (MS) components, (2) assignment of appropriate radiotracer concentrations to various components depending on the kind of functional image that is being registered, (3) generation of simulated functional images to have a spatial resolution that is comparable to that of the measured ones, (4) alignment of the measured functional images to the simulated ones that are based on MRI images. A self-organization clustering method is used to segment the MRI images. The image alignment is based on the criterion of least squares between the two sets of images that are being matched and on the Powell's algorithm for minimization. The technique was applied successfully for registerring the MRI, PET-FDG, and PET-FDOPA images. This technique offers a general solution to the registration of structural images to functional images and to the registration of different functional images of markly different distributions.
iGRT : A Generic Interface for GRoundTram

Bidirectional transformation plays an important role in maintaining the consistency of two models, and it has many potential applications, such as model synchronization, software evolution, etc. Currently we have a powerful tool called GRoundTram, which is designed for compositional development of well-behaved and efficient bidirectional graph transformations. However, as the graph representation in GRoundTram is a directed edge-labelled graph, it is quite difficult to apply it to real-world graphs directly, as graphs have more sophisticated representations usually. In this paper, we present iGRT, a generic interface for GRoundTram. It serves as the connection between the graphs in real world and GRoundTram system. We have designed the representation for real world graphs, and provided traceable transformations between realworld graph representation and GRoundTram representation without losing any information. By using iGRT, we can easily shuttle between the different representations and maintain the synchronization as well. We have implemented iGRT and offered a friendly user interface based on the eclipse framework. Experiment result shows that iGRT enhances GRoundTram’s application work to a large extent.
Short-term Load Forecasting Based on VPSO-Elman Neural Network

Because of the shortcomings which Elman neural network in the short-term load forecasting of power system is easy to fall into local minimum, slow convergence, Use VPSO(Variance Particle Swarm Optimization)to train Elman neural network in order to get optimal weights and thresholds. The optimized Elman network can avoid the convergence speed and getting into local minimum solution and other defects to the full. So it possesses best potential application in the field of short-term load forecasting.
SatelliteLab: Adding Heterogeneity to Planetary-Scale Testbeds

We extended PlanetLab with 32 diverse edge nodes Composed of desktops, laptops, and handhelds They connect using cable, DSL, Wi-Fi, and cellular networks They are distributed across 4 countries in Europe, 10 states in the United States, and Canada We significantly increased PlanetLab’s path diversity A SatelliteLab path has similar characteristics as the direct path The paths share the access links of the edge nodes, which are often their bottlenecks The bottlenecks determine path capacity, jitter, and loss rate
Audio Enancement using Nonlinear Time-Frequency Filtering

Forensic audio recordings may contain undesired noise that can impair source identification, speech recognition, and other audio processing requirements. In this paper several custom analysis/synthesis algorithms are presented based on a time-varying spectral representation of the noisy signal. The enhancement process adapts to the instantaneous signal behavior and alters the noisy signal so that the enhanced output signal is higher in quality than the unprocessed noisy input signal. Nonlinear and time-varying filters operate on the spectral representation in order to retain features that are attributable to the desired signal, such as human speech, while removing the features that are more likely to be due to the noise contamination.
Multi-rate wideband speech/channel codec based on MPEG-4/CELP for ETSI/GSM full-rate channel

This paper proposes a wideband multi-rate speech and channel codec based on the MPEG-4/CELP for the ETSI/GSM full-rate channel. In order to improve coding performance under mobile environments, such as channel error and background noise, the proposed codec operates at three bit allocations between speech and channel coding with a constant gross bit-rate of 22.8 kbit/s. The speech coding bit-rates are 10.9, 12.1 and 15.9 kbit/s. It achieves high speech quality under any channel condition by switching the bit allocations and also for noisy speech by using the highest bit-rate. The preliminary subjective evaluation tests show the speech quality is improved by switching the bit allocation under error conditions. It is also comparable of superior to ITU-T Recommendation G.722 48 kbit/s for carrier-to-interference ratios (C/I) higher than 10 dB. The codec at 15.9 kbit/s also gives comparable speech quality to G.722 at 48 kbit/s under background noise conditions.