Miracle-dz/UniFAR-FTUs huggingface dataset:
Chaotic bee swarm optimization algorithm for path planning of mobile robots

This paper is based on swarm intelligence and chaotic dynamics for learning. We address this issue by considering the problem of path planning for mobile robots. Autonomous systems assume intelligent behavior with ability of dealing in complex and changing environments. Path planning problem, which can be studied as an optimization problem, seems to be of high importance for arising of intelligent behavior for different real-world problem domains. In recent years, swarm intelligence has gained increasingly high interest among the researchers from different domains such as commerce, science and engineering. Bees' warming about their hive is an example of swarm intelligence. It's particularly fitting apply methods inspired by swarm intelligence to sundry optimization problems, and chiefly if the space to be explored is large and complex. In this paper, we propose a new approach to the problem of path planning for mobile robots based on an improved artificial bee colony optimization combined with chaos. In artificial bee colony optimization, chaos is hybridized to form a chaotic bee swarm optimization, which reasonably combines the population-based evolutionary searching ability of artificial bee colony optimization and chaotic searching behavior. The track of chaotic variable can travel ergodically over the whole search space. In general, the chaotic variable has special characters, i.e., ergodicity, pseudo-randomness and irregularity. Generally, the parameters of the artificial bee colony optimization are the key factors to affect the convergence of the artificial bee colony optimization. In fact, however, it cannot ensure the optimization's ergodicity entirely in phase space because they are absolutely random in the traditional artificial bee colony optimization. Therefore, this paper provides a new method that introduces chaotic mapping with certainty, ergodicity and the stochastic property into artificial bee colony optimization so as to improve the global convergence.
Rule Mining Framework for Students Performance Evaluation

: Academic Data Mining used many techniques such as Decision Trees, Neural Networks, Naïve Bayes, K-Nearest neighbor, and many others. Using these techniques many kinds of knowledge can be discovered such as association rules, classifications and clustering. The discovered knowledge can be used for prediction and analysis purposes of student patterns. Prior approaches used decision tree classifications optimized with ID3 algorithms to obtain such patterns. Among sets of items in transaction databases, Association Rules aims at discovering implicative tendencies that can be valuable information for the decision-maker which is absent in tree based classifications. So we propose a new interactive approach to prune and filter discovered rules. First, we propose to integrate user knowledge in the post processing task. Second, we propose a Rule Schema formalism extending the specifications to obtain association rules from knowledge base. Furthermore, an interactive framework is designed to assist the user throughout the analyzing task. Applying our new approach to discover the likelihood of students deviations / requiring special attention is organized and efficient providing more insight by considering more information. Compared to tree based classifications the results are better to understand and can be applied to real time use. An implementation of the proposed system validates our claim.
Explicit Surface Remeshing

We present a new remeshing scheme based on the idea of improving mesh quality by a series of local modifications of the mesh geometry and connectivity. Our contribution to the family of local modification techniques is an area-based smoothing technique. Area-based smoothing allows the control of both triangle quality and vertex sampling over the mesh, as a function of some criteria, e.g. the mesh curvature. To perform local modifications of arbitrary genus meshes we use dynamic patch-wise parameterization. The parameterization is constructed and updated on-the-fly as the algorithm progresses with local updates. As a post-processing stage, we introduce a new algorithm to improve the regularity of the mesh connectivity. The algorithm is able to create an unstructured mesh with a very small number of irregular vertices. Our remeshing scheme is robust, runs at interactive speeds and can be applied to arbitrary complex meshes.
Support Recovery for Sparse Deconvolution of Positive Measures

We study sparse spikes deconvolution over the space of Radon measures on $\mathbb{R}$ or $\mathbb{T}$ when the input measure is a finite sum of positive Dirac masses using the BLASSO convex program. We focus on the recovery properties of the support and the amplitudes of the initial measure in the presence of noise as a function of the minimum separation $t$ of the input measure (the minimum distance between two spikes). We show that when ${w}/\lambda$, ${w}/t^{2N-1}$ and $\lambda/t^{2N-1}$ are small enough (where $\lambda$ is the regularization parameter, $w$ the noise and $N$ the number of spikes), which corresponds roughly to a sufficient signal-to-noise ratio and a noise level small enough with respect to the minimum separation, there exists a unique solution to the BLASSO program with exactly the same number of spikes as the original measure. We show that the amplitudes and positions of the spikes of the solution both converge toward those of the input measure when the noise and the regularization parameter drops to zero faster than $t^{2N-1}$.
ASHG : Automatic Semantic Header Generator

Indexing file systems is a powerful means of helping users locate documents, software, and other types of data among large repositories. In environments that contain many different types of data, content indexing requires type-specific processing to extract information effectively. Cover page (or Semantic Header) is a portion of each document which should contain information useful in searching for a document based on a number of commonly used criteria. The information from the semantic header could be used by various indexing schemes to help locate appropriate documents with minimum effort. In this paper, we present a model that automatically extracts the secondary or meta-information, and stores it in a Semantic Header which will be used as an index for the document, which will help users in accessing and searching for it.
Trade‐Offs in Thermal Adaptation: The Need for a Molecular to Ecological Integration*

Through functional analyses, integrative physiology is able to link molecular biology with ecology as well as evolutionary biology and is thereby expected to provide access to the evolution of molecular, cellular, and organismic functions; the genetic basis of adaptability; and the shaping of ecological patterns. This paper compiles several exemplary studies of thermal physiology and ecology, carried out at various levels of biological organization from single genes (proteins) to ecosystems. In each of those examples, trade‐offs and constraints in thermal adaptation are addressed; these trade‐offs and constraints may limit species' distribution and define their level of fitness. For a more comprehensive understanding, the paper sets out to elaborate the functional and conceptual connections among these independent studies and the various organizational levels addressed. This effort illustrates the need for an overarching concept of thermal adaptation that encompasses molecular, organellar, cellular, and whole‐organism information as well as the mechanistic links between fitness, ecological success, and organismal physiology. For this data, the hypothesis of oxygen‐ and capacity‐limited thermal tolerance in animals provides such a conceptual framework and allows interpreting the mechanisms of thermal limitation of animals as relevant at the ecological level. While, ideally, evolutionary studies over multiple generations, illustrated by an example study in bacteria, are necessary to test the validity of such complex concepts and underlying hypotheses, animal physiology frequently is constrained to functional studies within one generation. Comparisons of populations in a latitudinal cline, closely related species from different climates, and ontogenetic stages from riverine clines illustrate how evolutionary information can still be gained. An understanding of temperature‐dependent shifts in energy turnover, associated with adjustments in aerobic scope and performance, will result. This understanding builds on a mechanistic analysis of the width and location of thermal windows on the temperature scale and also on study of the functional properties of relevant proteins and associated gene expression mechanisms.
Radiation-induced mammary carcinogenesis in virgin, pregnant, lactating, and postlactating rats.

Little attention has been paid to the influence of the reproductive condition of the rat at the time of irradiation upon X-ray-induced mammary carcinogenesis. At 12 weeks of age, 160 virgin female Sprague-Dawley rats were mated, and another 140 were maintained as virgins. On Days 14 to 16 of pregnancy, 36 mated females and 40 virgins were whole-body irradiated with 200 R of X-rays. On Days 2 to 5 postpartum, 40 additional mated females and 40 additional virgins were irradiated. At this time, all pups were removed from their mothers; 2 weeks later, 40 additional parous females and 40 virgins were irradiated. The remaining animals: parous females; virgins; and mated, but nonparous females were kept as unirradiated controls. Breast tissue biopsies were taken from 25% of the animals in each irradiated group on the day of irradiation, and the biopsies were examined microscopically for mammary tissue development. The experiment was terminated 10 months after irradiation. Despite marked differences in mammary tissue development among the groups at the time of irradiation, there were no significant differences among the irradiated groups for the incidence of rats with mammary adenocarcinomas or the number of mammary adenocarcinomas per rat. There were no significant differences among the irradiated groups for the incidence of rats with mammary fibroadenomas. There was an increase in the number of fibroadenomas per rat which was associated with increased age at the time of death. In contrast to mammary carcinogenesis produced by polycyclic aromatic hydrocarbons in previous studies, in the current investigation the physiological status of the host at the time of irradiation had little effect on: ( a ) the final incidence of mammary neoplasia; ( b ) the number of mammary adenocarcinomas produced; or ( c ) the type of mammary neoplasms produced.
A 1.2-V 0.09-µm high-gain buffered amplifier for 14.2-GHz satellite applications

Employing a 90-nm CMOS process, this article presents a high-gain, low-power (9.2 mW), highly-linearized (IIP3: 8.5 dBm), buffered amplifier for satellite applications near the lower edge of Ku-band (14.2 GHz). Over the frequencyband of interest (13.2-15.4 GHz), the amplifier achieves low noise contribution (<;3.41 dB) and excellent port-matching (<;-10 dB) simultaneously. With an effective 3-dB bandwidth of 2.2 GHz, the circuit demonstrates a small-signal forward gain of 24 dB and a noise figure (NF) of 3.25 dB at 14.2 GHz while maintaining a minimum input return-loss of -35 dB. Effect of impedance mismatch and process parasites are included in the design to facilitate a layout-sensitive RF analysis. When compared with simulated results of published amplifiers, the proposed design fares better in terms of linearity, forward gain and watt-per-decibel requirements.
Variation in Nutrient Utilization by Poultry and Ingredient Composition

Introduction This fact sheet has been developed to support the implementation of the Natural Resources Conservation Service Feed Management 592 Practice Standard. The Feed Management 592 Practice Standard was adopted by NRCS in 2003 as another tool to assist with addressing resource concerns on livestock and poultry operations. Feed management can assist with reducing the import of nutrients to the farm and reduce the excretion of nutrients in manure.
NTOU Chinese Spelling Check System in Sighan-8 Bake-off

This paper describes details of NTOU Chinese spelling check system in SIGHAN-8 Bakeoff. Besides the basic architecture of the previous system participating in last two CSC tasks, three new preference rules were proposed to deal with Simplified Chinese characters, variants, sentence-final particles, and DE-particles. A new sentence likelihood function was proposed based on frequencies of space-removed version of Google n-gram datasets. Two formal runs were submitted where the best one was created by the system using Google n-gram frequency information.
The capacity of discrete-time memoryless Rayleigh-fading channels

We consider transmission over a discrete-time Rayleigh fading channel, in which successive symbols face independent fading, and where neither the transmitter nor the receiver has channel state information. Subject to an average power constraint, we study the capacity-achieving distribution of this channel and prove it to be discrete with a finite number of mass points, one of them located at the origin. We numerically compute the capacity and the corresponding optimal distribution as a function of the signal-to-noise ratio (SNR). The behavior of the channel at low SNR is studied and finally a comparison is drawn with the ideal additive white Gaussian noise channel.
Subtle shifts in the ratio between pro‐ and antiapoptotic molecules after activation of corticosteroid receptors decide neuronal fate

Glucocorticoid receptor (GR) activation induces apoptosis of granule cells in the hippocampus. In contrast, neuroprotection is seen after mineralocor‐ticoid receptor (MR) activation. To date there is no in vivo evidence for direct interactions between corticosteroids and any of the key regulatory molecules of programmed cell death. In this report, we show that the opposing actions of MR and GR on neuronal survival result from their ability to differentially influence the expression of members of the bcl‐2 gene family; specifically, in the rat hippocampus, activation of GR induces cell death by increasing the ratio of the pro‐apoptotic molecule Bax relative to the antiapoptotic molecules Bcl‐2 or Bcl‐xL; the opposite effect is observed after stimulation of MR. The same results were obtained in both young and aged animals; however, older subjects (which were more susceptible to GR‐mediated apoptosis) tended to express the antiapoptotic genes more robustly. Using a loss‐of‐function mouse model, we corroborated the observations made in the rat, demonstrating Bax to be essential in the GR‐mediated cell death‐signaling cascade. In addition, we show that GR activation increases and MR activation decreases levels of the tumor suppressor protein p53 (a direct transcriptional regulator of bax and bcl‐2 genes), thus providing new information on the early genetic events linking corticosteroid receptors with apoptosis in the nervous system. —Almeida, O. F. X. , Condé, G. L. , Crochemore, C. , Demeneix, B. A. , Fischer, D. , Hassan, A. H. S. , Meyer, M. , Holsboer, F. , Michaelidis, T. M. Subtle shifts in the ratio between pro‐ and antiapoptotic molecules after activation of corticosteroid receptors decide neuronal fate. FASEB J. 14, 779–790 (2000)
DISTRIBUTED SPEECH RECOGNITION BY WIRA GUNAWAN

Speech is a natural mode of communication for human beings and speech recognition is an application that enables the interaction between human and machine via voice. As the cost of software and hardware needed to do recognition decreases, automatic speech recognition (ASR) has entered the consumer product mainstream. A particularly interesting application is wireless speech recognition, which is the integration of ASR technology into wireless applications. Utilizing an ASR system, people can interact via their cell phone using voice, thereby freeing their hands and eyes for other tasks. One aspect of speech recognition useful for wireless applications is digit recognition. In this paper, we perform speaker–independent isolated digit recognition using PLP (perceptual linear predictive) analysis and a DTW (dynamic time warping) algorithm. The effect of quantization of speech recognition features on recognition accuracy is examined to determine the lowest bit rate possible while maintaining high quality performance. iv To my family. Without their love and support, none of this would have happened. v ACKNOWLEDGMENTS I would like to thank Professor Mark Hasegawa-Johnson for giving me the opportunity to do research in speech recognition and for his guidance in developing this thesis.
Desiccation of Porous Media : Intermediate-Scale Flow Cell Experiments and Numerical Simulations

Soil desiccation is recognized as a potentially robust remediation process for the deep vadose zone. Before this technique can be deployed, several techniques issues need to addressed. In this paper, two experiments are described addressing the issue of potential energy limitations to reduce soil moisture. The experiments are conducted in wedge-shaped, intermediate-scale flow cells. The experiment in the homogeneous porous medium showed a maximum evaporative cooling of ~10 C and a rapid decrease in relative humidity when the drying front passed. In the heterogeneous experiments, the fine-grained sand dried considerably slower than the medium-grained sand and showed two local minima. The first minimum is associated with cooling due to evaporation in the adjacent medium grained sand and the second minimum with cooling the find-grained sand itself. The STOMP simulator was able to simulate desiccation and the associated thermal behavior well in both experiments. The good match for both temperature and relative humidity data shows that the STOMP simulator is using appropriate conservation equations and constitutive relations to describe the experimental observations.
Transoral Laser Microsurgery for Early Glottic Cancer

Objectives. To assess the outcome of transoral laser-assisted microsurgery (TLM) with regards to local and distant tumour control, quality of voice and swallowing. Design. Retrospective review of patients with five-year follow-up period. Setting. Royal Derby Hospital Head and Neck Department. Participants. All patients undergoing TLM with a diagnosis of Tis, T1, or T2 glottic tumour following endoscopic biopsy. Main Outcome Measures. Speech, swallowing, cancer-free survival, laryngectomy-free survival, and mortality rate. Results. 22 patients were treated for early glottic carcinoma with TLM. The 5-year local control rate for T1 tumours is 89% and 56% for T2 tumours. The laryngectomy rate was 4.5%. The mortality rate from local and distant disease was 4.5% with an overall mortality rate of 22% from all causes. 40% of patients had normal voices and a further 45% had only mild or moderate voice change. At their last followup, no patients assessed had any difficulty swallowing relating to their treatment for glottic cancer. Conclusion. Transoral Endoscopic CO2 laser microsurgery is a valid technique for treating early glottic tumours.
Classification of vowel sounds using MFCC and feed forward Neural Network

The English language as spoken by Malaysians varies from place to place and differs from one ethnic community and its sub-group to another. Hence, it is necessary to develop an exclusive Speech to text translation system for understanding the English pronunciation as spoken by Malaysians. Speech translation is a process of both speech recognition and equivalent phonemic to word translation. Speech recognition is a process of identifying phonemes from the speech segment. In this paper, the initial step for speech recognition by identifying the phoneme features is proposed. In order to classify the phoneme features, Mel-frequency cepstral coefficients (MFCC) are computed in this paper. A simple feed forward Neural Network (FFNN) trained by back propagation procedure is proposed for identifying the phonemes features. The extracted MFCC coefficients are used as input to a neural network classifier for associating it to one of the 11 classes.
Curated MicroRNAs in Urine and Blood Fail to Validate as Predictive Biomarkers for High-Risk Prostate Cancer

Purpose The purpose of this study was to determine if microRNA profiling of urine and plasma at radical prostatectomy can distinguish potentially lethal from indolent prostate cancer. Materials and Methods A panel of microRNAs was profiled in the plasma of 70 patients and the urine of 33 patients collected prior to radical prostatectomy. Expression of microRNAs was correlated to the clinical endpoints at a follow-up time of 3.9 years to identify microRNAs that may predict clinical response after radical prostatectomy. A machine learning approach was applied to test the predictive ability of all microRNAs profiled in urine, plasma, and a combination of both, and global performance assessed using the area under the receiver operator characteristic curve (AUC). Validation of urinary expression of miRNAs was performed on a further independent cohort of 36 patients. Results The best predictor in plasma using eight miRs yielded only moderate predictive performance (AUC = 0.62). The best predictor of high-risk disease was achieved using miR-16, miR-21 and miR-222 measured in urine (AUC = 0.75). This combination of three microRNAs in urine was a better predictor of high-risk disease than any individual microRNA. Using a different methodology we found that this set of miRNAs was unable to predict high-volume, high-grade disease. Conclusions Our initial findings suggested that plasma and urinary profiling of microRNAs at radical prostatectomy may allow prognostication of prostate cancer behaviour. However we found that the microRNA expression signature failed to validate in an independent cohort of patients using a different platform for PCR. This highlights the need for independent validation patient cohorts and suggests that urinary microRNA signatures at radical prostatectomy may not be a robust way to predict the course of clinical disease after definitive treatment for prostate cancer.
Linkages between reach-scale physical habitat and invertebrate assemblages in upland streams

Determining the influence of physical habitat on biological structure in minimally disturbed settings is important if the effects of alterations to physical habitat are to be understood. This study tested whether reach-scale differences in physical habitat influence macroinvertebrate community composition at 24 sites in the Cairngorm Mountains, Scotland. Stream reaches were classified into channel types based on a geomorphic typology (i.e. step-pool, bedrock, plane-bed and pool-riffle). PERMANOVA indicated an overall significant relationship between the geomorphic typology and macroinvertebrate species-level composition, and among all combinations of channel types (such as step-pool and pool-riffle, step-pool and bedrock). Most channel types were dominated by high abundances of Baetis rhodani, Rhithrogena semicolorata and Leuctra inermis, which are ubiquitous in unpolluted gravel-bedded Scottish streams. However, reflecting significant differences in abundance of commoner taxa between types, indicator value (IndVal) analysis revealed that pool-riffle reaches were characterised by elmids (Limnius sp. and Oulimnius sp.) and Caenis rivulorum, and step-pool reaches by Alainites muticus, B. rhodani, L. inermis and Brachyptera risi. Geomorphic typing of rivers provides a useful basis for the initial assessment of ecological status whereas abundance-based biological data processed at the appropriate taxonomic resolution should be sensitive to physical-habitat modifications.