Miracle-dz/UniFAR-FTUs huggingface dataset:
Speech Emotion Recognition using non-linear Teager energy based features in noisy environments

In this study, Teager-energy based Mel-frequency cepstral coefficients (TEMFCCs) are proposed for Automatic Speech Emotion Recognition (ASER) in noisy environments. TEMFCCs are obtained by taking the absolute value of the Teager-energy operator (TEO) of the short-time Fourier transform of the signal (STFT), warping it to a Mel-frequency scale, and taking the discrete cosine transform (DCT) of the log-Mel Teager-energy spectrum. Experiments on classification of discrete emotion categories show that TEMFCCs are more robust than MFCCs in noisy conditions, while TEMFCCs and MFCCs perform similarly for clean conditions.
Identifying Definitions in Text Collections for Question Answering

One particular type of question which was made the focus of its own subtask within the TREC2003 QA track was the definition question (“What is X? ” or “Who is X? ”). One of the main problems with this type of question is how to discriminate in vast text collections between definitional and non-definitional text passages about a particular definiendum (i.e., the term to be defined). A method will be presented that uses definition patterns and terms that co-occurr with the definiendum in on-line sources for both passage selection and definition extraction.
Receptor-Mediated and Fluid-Phase Transcytosis of Horseradish Peroxidase across Rat Hepatocytes

Horseradish peroxidase (HRP) is often used as a fluid-phase marker to characterize endocytic and transcytotic processes. Likewise, it has been applied to investigate the mechanisms of biliary secretion of fluid in rat liver hepatocytes. However, HRP contains mannose residues and thus binds to mannose receptors (MRs) on liver cells, including hepatocytes. To study the role of MR-mediated endocytosis of HRP transport in hepatocytes, we determined the influence of the oligosaccharid mannan on HRP biliary secretion in the isolated perfused rat liver. A 1-minute pulse of HRP was applied followed by marker-free perfusion. HRP appeared in bile with biphasic kinetics: a first peak at 7 minutes and a second peak at 15 minutes after labeling. Perfusion with 0.8 mg/mL HRP in the presence of a twofold excess of mannan reduced the first peak by 41% without effect on the second one. Together with recently published data on MR expression in rat hepatocytes this demonstrates two different mechanisms for HRP transcytosis: a rapid, receptor-mediated transport and a slower fluid-phase transport.
Validation of Expressive XML Keys with XML Schema and XQuery

The eXtensible Markup Language (XML) is the defacto industry standard for exchanging data on the Web and elsewhere. While the relational model of data enjoys a well-accepted denition of a key, several competing notions of keys exist in XML. These have complementary properties and therefore serve dierent applications domains. In a nutshell, XML keys allow us to capture important domain semantics in XML documents and thereby advance data processing in most applications. In this paper we propose how to validate XML documents against an expressive class of XML keys using XML Schema and XQuery, respectively. It is somewhat surprising how simple it is to express sophisticated notions of XML keys in these o-the-shelf tools. Experiments show that our simple validation technique works well for real-world data of reasonable size. For large-scale data, however, dedicated tools must be developed.
Complexity of Bondage and Reinforcement

Let $G=(V,E)$ be a graph. A subset $D\subseteq V$ is a dominating set if every vertex not in $D$ is adjacent to a vertex in $D$. A dominating set $D$ is called a total dominating set if every vertex in $D$ is adjacent to a vertex in $D$. The domination (resp. total domination) number of $G$ is the smallest cardinality of a dominating (resp. total dominating) set of $G$. The bondage (resp. total bondage) number of a nonempty graph $G$ is the smallest number of edges whose removal from $G$ results in a graph with larger domination (resp. total domination) number of $G$. The reinforcement number of $G$ is the smallest number of edges whose addition to $G$ results in a graph with smaller domination number. This paper shows that the decision problems for bondage, total bondage and reinforcement are all NP-hard.
cellular neural network based medical image segmentation using artificial bee colony algorithm

Magnetic Resonance Imaging (MRI) has become an efficient instrument for clinical diagnoses and research in recent years. It has become a very useful medical modality for the detection of various diseases through segmentation methods. In this paper, we have presented an effective CNN based segmentation method with lung and brain MRI images. This approach hits the target with the aid of the following major steps, which includes, 1) Preprocessing of the brain and lung images, 2) Segmentation using cellular neural network. Initially, the MRI image is pre-processed to make it fit for segmentation. Here, in the pre-processing step, image de-noising is done using the linear smoothing filters, such as Gaussian Filter. Then, the pre-processed image is segmented according to our proposed technique, CNN-based image segmentation. Finally, the different MRI images (brain and lung) are given to the proposed approach to evaluate the performance of the proposed approach in segmentation process. The Comparative analysis is carried out Fuzzy C-means (FCM) and K-means classification. From the comparative analysis, the accuracy of proposed segmentation approach produces better results (83.7% for lung and 93% for brain images) than that of existing Fuzzy C-means (FCM) and K-means classification.
Development of a multi-objective optimization tool for the selection and placement of BMPs for nonpoint source pollution control

Nonpoint source (NPS) pollution from agricultural areas can be minimized by the implementation of best management practices (BMPs) at the source (farm), by controlling the movement of pollutants from the agricultural areas into the receiving bodies. However, selection and implementation of BMPs in every farm, to achieve cost effective NPS pollution reduction in a watershed may be a daunting task. This typically requires obtaining an optimal solution, from the many million solutions that are possible, that is ecologically effective and economically feasible for the placement of BMPs. The previous works done to solve this problem have used genetic algorithms (GA) for optimizing the two objectives of : 1) pollution reduction and 2) cost increase. But most of the works have considered the two objectives individually during the optimization process by introducing a constraint on the other objective. This approach of finding an optimal solution is not practical as the constrained objective results in a decrease in the degree of freedom in the solution space. In the present work the optimization is performed by considering the two objectives simultaneously. A multi-objective genetic algorithm (NSGA-II) was used to optimize the two objectives which gave a tradeoff between the two objectives for a range of optimal pollution reduction alternatives and their corresponding cost for implementation of BMPs. The model was used for the selection and placement of BMPs in L’Anguille River Watershed, Arkansas, USA for total phosphorus (TP) reduction. The most ecologically effective solution from the model had a TP reduction of 33% from the base scenario for a BMP implementation cost of $14 million. The tradeoff was obtained between the two optimized objective functions which can be used to achieve desired water quality goals with the minimum BMP implementation cost for the watershed.
Enhanced De Novo Assembly of High Throughput Pyrosequencing Data Using Whole Genome Mapping

Despite major advances in next-generation sequencing, assembly of sequencing data, especially data from novel microorganisms or re-emerging pathogens, remains constrained by the lack of suitable reference sequences. De novo assembly is the best approach to achieve an accurate finished sequence, but multiple sequencing platforms or paired-end libraries are often required to achieve full genome coverage. In this study, we demonstrated a method to assemble complete bacterial genome sequences by integrating shotgun Roche 454 pyrosequencing with optical whole genome mapping (WGM). The whole genome restriction map (WGRM) was used as the reference to scaffold de novo assembled sequence contigs through a stepwise process. Large de novo contigs were placed in the correct order and orientation through alignment to the WGRM. De novo contigs that were not aligned to WGRM were merged into scaffolds using contig branching structure information. These extended scaffolds were then aligned to the WGRM to identify the overlaps to be eliminated and the gaps and mismatches to be resolved with unused contigs. The process was repeated until a sequence with full coverage and alignment with the whole genome map was achieved. Using this method we were able to achieved 100% WGRM coverage without a paired-end library. We assembled complete sequences for three distinct genetic components of a clinical isolate of Providencia stuartii: a bacterial chromosome, a novel bla NDM-1 plasmid, and a novel bacteriophage, without separately purifying them to homogeneity.
Probabilistic Classification Vector Machine at large scale

Probabilistic kernel classiﬁers are effective approaches to solve classi-ﬁcation problems but only few of them can be applied to indeﬁnite kernels as typically observed in life science problems and are often limited to rather small scale problems. We provide a novel batch formulation of the Probabilistic Classiﬁcation Vector Machine for large scale metric and non-metric data.
Subclasses of the separable permutations

The separable permutations are those that can be obtained from the trivial permutation by two operations called direct sum and skew sum. This class of permutations contains the class of stack sortable permutations, Av(231), which are enumerated by the Catalan numbers. We prove that all subclasses of the separable permutations which do not contain Av(231) or a symmetry of this class have rational generating functions. Our principal tools include partial well‐order (the lack of an infinite antichain), atomicity (the joint embedding property), and the theory of strongly rational permutation classes which is introduced here for the first time.
A Fast Bilinear Structure from Motion Algorithm Using a Video Sequence and Inertial Sensors

In this paper, we study the benefits of the availability of a specific form of additional information-the vertical direction (gravity) and the height of the camera, both of which can be conveniently measured using inertial sensors and a monocular video sequence for 3D urban modeling. We show that in the presence of this information, the SfM equations can be rewritten in a bilinear form. This allows us to derive a fast, robust, and scalable SfM algorithm for large scale applications. The SfM algorithm developed in this paper is experimentally demonstrated to have favorable properties compared to the sparse bundle adjustment algorithm. We provide experimental evidence indicating that the proposed algorithm converges in many cases to solutions with lower error than state-of-art implementations of bundle adjustment. We also demonstrate that for the case of large reconstruction problems, the proposed algorithm takes lesser time to reach its solution compared to bundle adjustment. We also present SfM results using our algorithm on the Google StreetView research data set.
Comparative study of interactive seed generation for growcut-based fast 3D MRI segmentation

This paper proposes a speed-enhanced growcut method and presents comparative study of seed setting methods for fast 3D medical image (MRI) segmentation. The processing time tends to be larger in 3D image segmentation because of the large number of neighboring voxels as well as the number of voxels themselves. In this paper, two seed setting methods are proposed for our fast growcut-based segmentation algorithm: sphere-based bounding box method and label transfer based method using SIFT flow. Experimental results demonstrate that the tumor segmentation for each patient can be done very quickly as compared to the previous works. The segmentation accuracy can also be made very high with only a few user interactions.
PATTERN FORMATION IN A MIXED LOCAL AND NONLOCAL REACTION-DIFFUSION SYSTEM

Local and nonlocal reaction-diffusion models have been shown to demonstrate nontrivial steady state patterns known as Turing patterns. That is, solutions which are initially nearly homogeneous form non-homogeneous patterns. This paper examines the pattern selection mechanism in systems which contain nonlocal terms. In particular, we analyze a mixed reactiondiffusion system with Turing instabilities on rectangular domains with periodic boundary conditions. This mixed system contains a homotopy parameter β to vary the effect of both local (β = 1) and nonlocal (β = 0) diffusion. The diffusion interaction length relative to the size of the domain is given by a parameter . We associate the nonlocal diffusion with a convolution kernel, such that the kernel is of order −θ in the limit as → 0. We prove that as long as 0 ≤ θ < 1, in the singular limit as → 0, the selection of patterns is determined by the linearized equation. In contrast, if θ = 1 and β is small, our numerics show that pattern selection is a fundamentally nonlinear process.
On-line estimation of IGBT junction temperature using on-state voltage drop

In this paper, a noninvasive and accurate on-line estimation method for IGBT junction temperature is proposed. To optimize the heat management of IGBTs, it provides accurate information about junction temperature. The proposed method requires a few additional passive circuit components for the estimation and it can be easily incorporated into the conventional gate driver circuit. The proposed method consists of two processes, one is off-line characterization of the IGBT under test and the other one is on-line estimation of junction temperature based on the characterized data. The simulation and experimental results confirm the validity of the proposed estimation method.
A robust position control for induction motors using a load torque observer

The design of a robust position control scheme for an induction motor drive using the field oriented control theory is proposed. The proposed sliding-mode control law incorporates an adaptive sliding gain in order to adjust the sliding gain to the system uncertainties. Moreover, the sliding gain adaptation avoids having to calculate the upper limit for the system uncertainties. The design also incorporates a load torque observer in order to obtain the load torque applied to the induction motor without the use of the load torque sensor. The proposed observer is based on the system dynamical equation and uses the rotor speed and the stator current in order to obtain the load torque. The stability analysis of the proposed controller under parameter uncertainties and load torque variations is provided using the Lyapunov stability theory. Finally experimental results show that the proposed controller with the proposed observer provides high-performance dynamic characteristics and that this scheme is robust with respect to plant parameter uncertainties and load torque variations.
C-E Tourism Translation Principles and Techniques Based on Relevance Theory——In the Case of the Three Scenic Spots in Qufu

As a cognitive theory, relevance theory is also a theory for communication. It provides scientific pragmatics analysis approach for translation. Tourism translation, a communicative activity between languages and cultures, is the envoy for cultural communication. Based on relevance theory, this paper analyses the tourism translation with the examples of the scenic spots in Qufu. With the guidance of Relevance Principals we can choose appropriate translation strategies: domestication strategy is supposed to be chosen to reduce cognitive inferential efforts when language structure differences are concerned; while foreignization strategy should be used for cultural image differences so as to bring out maximum contextual effects.
Recommending Products using Preference Based Modeling

Common approaches to product recommendations are oer level propensity models and collaborative ltering. These methods are typically used for respectively a low or a high number of products, and come with specic limitations. In this paper we introduce preference based approaches to product recommendations, aimed at lling the gap between these methods. This approach can be used for any expected value decision problem, with choices across alternatives with common sets of attributes.
Housekeeping with Multiple Autonomous Robots: Representation, Reasoning and Execution

We consider a housekeeping domain with static or movable objects, where the goal is for multiple autonomous robots to tidy a house collaboratively in a given amount of time. This domain is challenging in the following ways: commonsense knowledge (e.g., expected locations of objects in the house) is required for intelligent behavior of robots; geometric constraints are required to find feasible plans (e.g., to avoid collisions); in case of plan failure while execution (e.g., due to a collision with movable objects whose presence and location are not known in advance or due to heavy objects that cannot be lifted by a single robot), recovery is required depending on the cause of failure; and collaboration of robots is required to complete some tasks (e.g., carrying heavy objects). We introduce a formal planning, execution and monitoring framework to address the challenges of this domain, by embedding knowledge representation and automated reasoning in each level of decision-making (that consists of discrete task planning, continuous motion planning, and plan execution), in such a way as to tightly integrate these levels. At the high-level, we represent not only actions and change but also commonsense knowledge in a logicbased formalism. Geometric reasoning is lifted to the high-level by embedding motion planning in the domain description. Then a discrete plan is computed for each robot using an automated reasoner. At the mid-level, if a continuous trajectory cannot be computed by a motion planner because the discrete plan is not feasible at the continuous-level, then a different plan is computed by the automated reasoner subject to some (temporal) conditions represented as formulas. At the low-level, if the plan execution fails, then a new continuous trajectory is computed by a motion planner at the mid-level or a new discrete plan is computed using an automated reasoner at the high-level. We illustrate the applicability of this formal framework with a simulation of a housekeeping domain.
End User Response to Web-Server Access - Calibration Method

One cannot think of living in this world without Internet which one has to visit everyday for e-mail checking, booking air ticket, purchasing items from online stores etc. A client server environment can be compared to Internet access by users. Where the services are hosted on web server and users are considered as clients. Anyone who visits a web site wants a reasonably good response time. But due to increasing number of users and changing scenario in Internet environment the traffic situation changes and is going from bad to worst. In this paper an effort is made to study the end user feeling of web server access via emulated Internet like environment. Load tests are used to simulate virtual users accessing the web pages called static pages of known sizes to make a deterministic study of their response behavior. To collect various logs and study them to build up a model and predict the end-user response time. Focus is particularly given to the network packets that flow between the client and the server computer, so as to get an idea about end user response of web server access.
The geography of climate change: implications for conservation biogeography

Aim Climate change poses significant threats to biodiversity, including impacts on species distributions, abundance and ecological interactions. At a landscape scale, these impacts, and biotic responses such as adaptation and migration, will be mediated by spatial heterogeneity in climate and climate change. We examine several aspects of the geography of climate change and their significance for biodiversity conservation.
A System for Locating Mobile Terminals with Tunable Privacy

A number of approaches for capturing and processing location information of mobile users have been proposed in the past; however, only with the latest advances in the handset technology, a terminal-based positioning approach, using overlay SIP signaling on top of a packet switched bearer and area notification as basic functionality becomes feasible for mass applications. Especially in electronic commerce scenarios, in which users often interact with non-trusted services and shops, any location-based solution has to consider privacy aspects as well. The terminal-centric model presented in the paper leads to a simple and efficient way to achieve tunable privacy: mobile users define own "zones" and selectively disclose them to their buddies and to external services. As a result, localization can be performed only in the allowed places and by the allowed watchers, both parameters being configured by the user herself on her mobile terminal. We describe the system architecture, protocols and present representative technical scenarios.
Antipsychotic drugs reverse the AMPA receptor‐stimulated release of 5‐HT in the medial prefrontal cortex

The prefrontal cortex (PFC) is involved in the pathophysiology of schizophrenia. PFC neuronal activity is modulated by monoaminergic receptors for which antipsychotic drugs display moderate‐high affinity, such as 5‐HT2A and α1‐adrenoceptors. Conversely, PFC pyramidal neurons project to and modulate the activity of raphe serotonergic neurons and serotonin (5‐HT) release. Under the working hypothesis that atypical antipsychotic drugs may partly exert their action in PFC, we assessed their action on the in vivo 5‐HT release evoked by increasing glutamatergic transmission in rat medial PFC (mPFC). This was achieved by applying S‐AMPA in mPFC (reverse dialysis) or by disinhibiting thalamic excitatory afferents to mPFC with bicuculline. The application of haloperidol, chlorpromazine, clozapine and olanzapine in mPFC by reverse dialysis (but not reboxetine or diazepam) reversed the S‐AMPA‐evoked local 5‐HT release. Likewise, the local (in mPFC) or systemic administration of these antipsychotic drugs reversed the increased prefrontal 5‐HT release produced by thalamic disinhibition. These effects were shared by the 5‐HT2A receptor antagonist M100907 and the α1‐adrenoceptor antagonist prazosin. However, raclopride (DA D2 antagonist) had very modest effects. These results suggest that, besides their action in limbic striatum, antipsychotic drugs may attenuate glutamatergic transmission in PFC, possibly by interacting with 5‐HT2A and/or α1‐adrenoceptors.