Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Time Series Autoregressive Model for prediction of rainfall and runoff in Kelo Watershed Chhattisgarh

1 23 Department of Soil & Water Conservation Engineerin g M.Tech ( Soil and Water conservation engineering) 2 Professor 3 Associate Professor 1 Email:shaonleec@gmail.com Abstract: A study was conducted to develop a stocha stic time series model, capable of prediction of r ainfall and runoff in Kelo watershed . The Kelo watershed of Mahanadi river bas in situated in Raigarh region of Chhattisgarh state . Raigarh is in the North–Central part of Chhattisgarh state. The catchment area of the watershed is 1175 sq km. It is si tuated 21°53’00’’ latitude and longitude 83°24 ́00 ́ ́. The rainfall and runoff data of the watershed from the year (2001-2006) was collected and used for the development of model. Autoregressive (AR) models of rder 0,1 and 2 were tried.The goodness of fit and adequacy of models were tested by BoxPierce Portmanteau test, Akaike info rmation Criterion and by comparison of historical and generated data correlogram The graphical representation between h istorical and generated correlogram , where in both the cases of rainfall and runoff there was a very close agreement between th em. The comparison between the measured and predict ed rainfall and runoff by AR(1) model clearly shows that the developed mod el can be used efficiently for the future prediction o rainfall and runoff in Kelo watershed.
Reparametrization Invariance and the Schrödinger Equation

In the present work we consider a time-dependent Schr\"odinger equation for systems invariant under the reparametrization of time. We develop the two-stage procedure of construction such systems from a given initial ones, which is not invariant under the time reparametrization. One of the first-class constraints of the systems in such description becomes the time-dependent Schr\"odinger equation. The procedure is applicable in the supersymmetric theories as well. The $n=2$ supersymmetric quantum mechanics is coupled to world-line supergravity, and the local supersymmetric action is constructed leading to the square root representation of the time-dependent Schr\"odinger equation.
Real-Time Inverse Dynamics Learning for Musculoskeletal Robots based on Echo State Gaussian Process Regression

A challenging topic in articulated robots is the control of redundantly many degrees of freedom with artificial muscles. Actuation with these devices is difficult to solve because of nonlinearities, delays and unknown parameters such as friction. Machine learning methods can be used to learn control of these systems, but are faced with the additional problem that the size of the search space prohibits full exploration in reasonable time. We propose a novel method that is able to learn control of redundant robot arms with artificial muscles online from scratch using only the position of the end effector, without using any joint positions, accelerations or an analytical model of the system or the environment. To learn in real time, we use the so called online “goal babbling” method to effectively reduce the search space, a recurrent neural network to represent the state of the robot arm, and novel online Gaussian processes for regression. With our approach, we achieve good performance on trajectory tracking tasks for the end effector of two very challenging systems: a simulated 6 DOF redundant arm with artificial muscles, and a 7 DOF robot arm with McKibben pneumatic artificial muscles. We also show that the combination of techniques we propose results in significantly improved performance over using the individual techniques alone.
Reversible and permanent effects of the carbon sources and various antibiotics on the morphology and metabolic properties of Ustilago cynodontis cells

The effects of various carbon sources and of antibiotics on the morphology of hypha cells of the fungus Ustilago cynodontis is described. Nonfermentable substrates promote readily reversible yeastlike colonies from hypha cells: all the hypha cells spread on these substrates give rise to yeastlike colonies that revert to the mycelial phenotype when transferred to glucose medium. Among the antibiotics tested, chloramphenicol (CAP) is found to promote, under certain circumstances, a long-lasting, even permanent modification on the morphology of the colonies: the colonies developed on CAP-glucose media are yeastlike, and a percentage of them give rise to colonies whose morphology remains yeastlike even on drug-free media: this effect is also obtained with cells cultivated in liquid medium. This permanent morphological modification is accompanied by a change of metabolic properties. Similar permanent effects are obtained with ethidium bromide, suggesting that mitochondrial functioning is involved in these modifications.
Individual Differences in True and False Memory Retrieval Are Related to White Matter Brain Microstructure

We sometimes vividly remember things that did not happen, a phenomenon with general relevance, not only in the courtroom. It is unclear to what extent individual differences in false memories are driven by anatomical differences in memory-relevant brain regions. Here we show in humans that microstructural properties of different white matter tracts as quantified using diffusion tensor imaging are strongly correlated with true and false memory retrieval. To investigate these hypotheses, we tested a large group of participants in a version of the Deese–Roediger–McDermott paradigm (recall and recognition) and subsequently obtained diffusion tensor images. A voxel-based whole-brain level linear regression analysis was performed to relate fractional anisotropy to indices of true and false memory recall and recognition. True memory was correlated to diffusion anisotropy in the inferior longitudinal fascicle, the major connective pathway of the medial temporal lobe, whereas a greater proneness to retrieve false items was related to the superior longitudinal fascicle connecting frontoparietal structures. Our results show that individual differences in white matter microstructure underlie true and false memory performance.
Robust and cost-effective architecture design for smart grid communications: A multi-stage middleware deployment approach

Wide-area monitoring, protection and control (WAMPAC) plays a critical role in smart grid, for protection against possible contingencies, by using the Supervisory Control and Data Acquisition (SCADA) system. However, a general consensus is that such a hierarchical system can be highly vulnerable to component (i.e., nodes and links) failures, calling for a robust and cost-effective communication system for smart grid. To this end, we consider a middleware approach to leverage the existing commercial communication infrastructure with abundant connectivity. In this approach, a natural question is how to use the middleware to cohesively “glue” the power grid and the commercial communication infrastructure together, in order to enhance robustness and cost-effectiveness. We tackle this problem while taking into consideration the multi-stage deployment of power devices and their redundant connections. We show that this problem can be cast as a minimum-cost middleware design under incremental deployment-an “online” problem where the input is provided gradually due to the incremental deployment. We design a randomized “online” algorithm, and show that it achieves the order-optimal average competitive ratio. Simulation results demonstrate the performance of our proposed algorithm, compared to the optimal offline solution.
Contact-induced language alternation in Tanzanian Ngoni – an empirical study of frequency and patterns

ABSTRACT The codeswitching pattern is different in rural Tanzania compared to urban agglomerations around the world. Even in very rural areas people in Tanzania are bilingual in Swahili, the national and local lingua franca, and their own first language. The result of this language contact is understudied and has only recently been focused on. This paper presents quantitative and qualitative results of a study of the language Ngoni in contact with Swahili. The study is based on photo elicitations about traditional artefacts and their use in one semi-urban and one remote rural village in Songea District, Ruvuma Region. Codeswitching is the unmarked choice among the Ngoni subsistence farmers in the area, even for old persons living in remote villages. The quantitative results are summed in relation to socio-demographic factors. Additionally, possible social and psycholinguistic factors, such as triggering, are discussed. The results give reason to concern regarding the future of Ngoni.
Robust airplane detection in satellite images

Automatic target detection in satellite images remains a challenging problem. The main difficulties lie in the cooccurrence of variations of target type, pose, and size in huge satellite image. In this paper, we propose a new airplane detection approach based on visual saliency computation and symmetry detection. The advantages are twofold. First, saliency and symmetry detection perform stably in obtaining target location and orientation information. Second, independent of target type, pose and size, saliency map and symmetry detection are computed only once. This saves a large amount of computational time but does not miss any targets. Experiments show that our method provides a promising way to detect airplanes in complex airport scenes.
Adaptive Fault-Tolerant CORBA Components

Component-based software development allows developers to compose applications using software parts, called components. This approach represents an important step towards reducing development cost and time, and allows the creation of automated tools for software development. However, current applications have quality of service (QoS) requirements, and the existing component-based technologies provide limited support for QoS. In particular, fault tolerance is provided only in the form of persistence services, which enable the recovery of faulty components without loss of state information. This paper presents AFT-CCM (Adaptive Fault-Tolerance in the CORBA Component Model) – a model for building component-based applications with QoS requirements related to fault tolerance. AFT-CCM is based on CCM (CORBA Component Model), proposed by the OMG (Object Management Group), which extends the CORBA object model in order to introduce a new abstraction – the component. The AFT-CCM model allows the application user to specify QoS requirements that will be interpreted in order to adapt the configuration of replicated components. Characteristics such as the number of replicas and the replication technique will be defined aiming to fulfill the fault tolerance requirements specified by the user. This process is accomplished at execution time employing a set of CCM components that deal with the non-functional aspects of the application. The characteristics of this model, a prototype implementation, and an analysis of its functionality in the face of other proposals found in the literature are described along this paper.
A New General Topology for Cascaded Multilevel Inverters With Reduced Number of Components Based on Developed H-Bridge

In this paper, a new general cascaded multilevel inverter using developed H-bridges is proposed. The proposed topology requires a lesser number of dc voltage sources and power switches and consists of lower blocking voltage on switches, which results in decreased complexity and total cost of the inverter. These abilities obtained within comparing the proposed topology with the conventional topologies from aforementioned points of view. Moreover, a new algorithm to determine the magnitude of dc voltage sources is proposed. The performance and functional accuracy of the proposed topology using the new algorithm in generating all voltage levels for a 31-level inverter are confirmed by simulation and experimental results.
Query-driven Frequent Co-occurring Term Extraction over Relational Data using MapReduce

In this paper we study how to efficiently compute \textit{frequent co-occurring terms} (FCT) in the results of a keyword query in parallel using the popular MapReduce framework. Taking as input a keyword query q and an integer k, an FCT query reports the k terms that are not in q, but appear most frequently in the results of the keyword query q over multiple joined relations. The returned terms of FCT search can be used to do query expansion and query refinement for traditional keyword search. Different from the method of FCT search in a single platform, our proposed approach can efficiently answer a FCT query using the MapReduce Paradigm without pre-computing the results of the original keyword query, which is run in parallel platform. In this work, we can output the final FCT search results by two MapReduce jobs: the first is to extract the statistical information of the data; and the second is to calculate the total frequency of each term based on the output of the first job. At the two MapReduce jobs, we would guarantee the load balance of mappers and the computational balance of reducers as much as possible. Analytical and experimental evaluations demonstrate the efficiency and scalability of our proposed approach using TPC-H benchmark datasets with different sizes.
Performance of MIMO-IDMA system with imperfect channel state information

In this article, we consider the performance of multiple-input multiple-output (MIMO) interleave division multiple access (IDMA) system based on double space-time transmit diversity (DSTTD) considering imperfect channel state information(CSI) for downlink(DL) communication. DSTTD system employs four transmit antennas at the base station which multiplex two STTD block units. At the receiver, we realize the decoder based on low-complexity layered space-time interference cancellation technique by considering four receive antennas. Further, we acquire the CSI by estimating at the receiver using pilot assisted channel estimation (PACE) technique. In IDMA, users specific interleaving patterns are employed to distinguish the different users in contrast to the conventional code division multiple access where orthogonal spreading sequence are used. Furthermore in our considered work, random interleavers are used to differentiate multi-users. Particularly, we evaluate the performance of DSTTD assisted MIMO-IDMA system based on Stanford University Interim (SUI) channel models. Our simulation study shows that our DSTTD-IDMA system provides better error rate performance while retaining higher throughput with fewer computation in the frequency-selective channels.
Bumblebees are not deterred by ecologically relevant concentrations of nectar toxins

Bees visit flowers to collect nectar and pollen that contain nutrients and simultaneously facilitate plant sexual reproduction. Paradoxically, nectar produced to attract pollinators often contains deterrent or toxic plant compounds associated with herbivore defence. The functional significance of these nectar toxins is not fully understood, but they may have a negative impact on pollinator behaviour and health, and, ultimately, plant pollination. This study investigates whether a generalist bumblebee, Bombus terrestris, can detect naturally occurring concentrations of nectar toxins. Using paired-choice experiments, we identified deterrence thresholds for five compounds found in the nectar of bee-pollinated plants: quinine, caffeine, nicotine, amygdalin and grayanotoxin. The deterrence threshold was determined when bumblebees significantly preferred a sucrose solution over a sucrose solution containing the compound. Bumblebees had the lowest deterrence threshold for the alkaloid quinine (0.01 mmol l−1); all other compounds had higher deterrence thresholds, above the natural concentration range in floral nectar. Our data, combined with previous work using honeybees, suggest that generalist bee species have poor acuity for the detection of nectar toxins. The fact that bees do not avoid nectar-relevant concentrations of these compounds likely indicates that it is difficult for them to learn to associate floral traits with the presence of toxins, thus maintaining this trait in plant populations.
Hybrid Clustered Peer-Assisted DASH-SVC System

Dynamic Adaptive Streaming over HTTP (DASH) standard was designed to improve quality of experience (QoE) by enabling video distribution at different quality levels according to the clients' network conditions. Moreover, DASH is compatible with the H.264 Scalable Video Coding (SVC) technology. In Content Delivery Networks (CDNs)-P2P hybrid approach, users can fetch contents from the CDN edge network, the P2P network, or from both networks. In this paper, we present a Hybrid CDN-P2P-SVC-DASH system, mainly to improve user quality of experience. Our system is based on clustering the peers to improve the user download time. The simulation results show that the clusters improve the QoE, reduce the start-time and reduce the load on the tracker. We also found that relatively small clusters can achieve most of the potential benefits engrained in the CDN-P2P hybrid approach.
Implementation of a Wireless Haptic Controller for Humanoid Robot Walking

Humanoid robots are the most proper type of robots for providing humans with various intelligent services, since it has a human-like body structure and high mobility. Despite this prosperity, operation of the humanoid robot requires complicated techniques for performing biped walking and various motions. Thus, the technical advancement concerning humanoid motion is somewhat sluggish. For attracting more engineering interest to humanoids, it is necessary that one should be able to manipulate a humanoid with such easiness as driving an remote control(RC) car by a wireless controller. In doing so, they will watch the motion and learn intrinsic principles naturally. Actually, however, only a few well-trained experts can deal with a humanoid robot of their own assembling as often seen in robot shows. This limitation may be due to the lack of unified and systemized principles on kinematics, dynamics, and trajectory generation for a humanoid. For biped walking, modeling of the humanoid for deriving kinematics and dynamics is to be constructed first. Humanoid modeling can be roughly classified into two categories; the inverted pendulum model (Park et al., 1998; Kajita et al., 2001; Kajita et al., 2003) and the joint-link model (Huang et al., 2001; Lim et al., 2002; Jeon et al., 2004; Park et al., 2006). The former approach is such that a humanoid is simplified as an inverted pendulum which connects the supporting foot and the center of mass (CoM) of the whole body. Owing to the limited knowledge in dynamics, this approach considerably relies on feedback control in walking. On the contrary, the latter approach requires the precise knowledge of robot specification concerning each link including mass, moment of inertia, and the position of CoM. This complexity in modeling, however, leads to an inevitable intricateness of deriving dynamics. We have been building the humanoid walking technologies by constructing the unique three-dimensional model, deriving its dynamics, generating motor trajectories that satisfy both stability and performance in biped walking and upstairs walking since 2007 (Kim & Kim, 2007; Kim et al., 2008a; Kim et al., 2009a; Kim et al. 2009b). All the computer simulations were validated through implementation of walking with a small humanoid robot. 6
An impact of ridgelet transform in handwritten recognition: A study on very large dataset of Kannada script

Handwritten character recognition is a difficult problem due to the great variations on writing styles, different size and orientation angle of the characters. In this paper, we propose an unconstrained handwritten Kannada character recognition based on the ridgelet transforms. Ridglets are a powerful instrument in catching and representing mono-dimensional singularities in bi dimensional space [7]. Ridgelet transforms is used to extracts low pass energy of character image and is then fed to PCA for feature extraction. We conducted experiment on very large database of handwritten Kannada character. The size of the class was 200 and encouraging results are obtained.
Detection of selected face areas on thermograms with elimination of typical problems

The paper presents an algorithm enabling a fully automatic detection of characteristic areas on thermograms containing patients’ faces in a front projection. A resolution of problems occurring at the segmentation of face images, such as a change of position, orientation and scale, has been proposed. In addition, attempts to eliminate the effect of the background and of disturbances caused by the haircut and the hairline were made. The algorithm may be used to detect selected points and areas of a face or as a preliminary component in the face recognition, as a development of optical analysis methods or in the quantitative analysis of face on thermograms.
Trilepton production at the CERN LHC: SUSY Signals and Standard Model Backgrounds

Events with isolated leptons and missing energy in the final state are known to be signatures of new physics phenomena at high energy collider physics facilities. Standard model (SM) sources of isolated trilepton final states include gauge boson pair production such as W Z and Wg , and tproduction. Symbol g represents a virtual photon. Our new contribution is the demonstration that bottom and charm meson decays, b! lX and c! lX, produce isolated lepton events that can overwhelm the effects of other processes. We compute contributions from a wide range of SM heavy flavor processes including bZ=g , cZ=g , b¯ bZ=g , c ¯ cZ=g . We also include contributions from processes in which a W is produced in association with one or more heavy flavors such as tW , b¯ bW , c ¯ cW . In all these cases, one or more of the final observed isolated leptons comes from a heavy flavor decay. We propose new cuts to control the heavy flavor backgrounds in the specific case of chargino plus neutralino pair production in supersymmetric models. PACS: 13.85. Qk, 13.85. Rm, 12.60. Jv
SNPper: retrieval and analysis of human SNPs

MOTIVATION Single Nucleotide Polymorphisms (SNPs) are an increasingly important tool for the study of the human genome. SNPs can be used as markers to create high-density genetic maps, as causal candidates for diseases, or to reconstruct the history of our genome. SNP-based studies rely on the availability of large numbers of validated, high-frequency SNPs whose position on the chromosomes is known with precision. Although large collections of SNPs exist in public databases, researchers need tools to effectively retrieve and manipulate them. RESULTS We describe the implementation and usage of SNPper, a web-based application to automate the tasks of extracting SNPs from public databases, analyzing them and exporting them in formats suitable for subsequent use. Our application is oriented toward the needs of candidate-gene, whole-genome and fine-mapping studies, and provides several flexible ways to present and export the data. The application has been publicly available for over a year, and has received positive user feedback and high usage levels.