Miracle-dz/UniFAR-FTUs huggingface dataset:
Transfer in Photography Composition

In this paper, we propose novel photography recomposition method, which aims at transferring the photography composition of a reference image to an input image automatically. Without any user interaction, our approach first identifies the salient foreground objects or image regions of interest, and the recomposition is performed by solving a graph-matching based optimization task. With additional post-processing step to preserve the locality and boundary information of the recomposed visual components, we can solve the task of photography recomposition without the uses of any prior knowledge on photography or predetermined image aesthetics rules. Experiments on a variety of images, including transferring the photography composition from real photos, sketches or even paintings, would confirm the effectiveness of our proposed method.
MMSE Equalizer for MIMO-ISI Channel With Shorten Guard Period

A finite-impulse-response minimum mean-square error equalizer (FIR-MMSEE) for block-based transmission over a multiple-input multiple-output (MIMO) intersymbol interference (ISI) channels is proposed in this correspondence. The proposed MMSE equalizer can avoid interblock interference (IBI) without requiring a guard period to be larger than or equal to the channel order. By reducing the number of redundant symbols in the transmitted signals, the spectral efficiency of the communication system with long channel dispersion can be greatly improved. We further investigated the parallel FIR-MMSEE equalization structure and proposed a group successive interference cancellation MMSE equalizer (GSIC-MMSEE). A group of elements in the output of the FIR-MMSEE will be used to successively cancel their own effect in the received signals after the signal detection in GSIC-MMSEE. Since the cancellation process eliminates some interference sources, the error performance of the subsequent equalization will be improved. Moreover, the interference cancellation is performed in a group-by-group basis. As a result, the computational complexity of the proposed equalizer can be controlled by adjusting the number of groups in the GSIC. Simulation results are presented to compare the performance of the proposed FIR-MMSEE and GSIC-MMSEE
Synaptic Plasticity Defect Following Visual Deprivation in Alzheimer's Disease Model Transgenic Mice

Amyloid-β (Aβ)-induced changes in synaptic function in experimental models of Alzheimer's disease (AD) suggest that Aβ generation and accumulation may affect fundamental mechanisms of synaptic plasticity. To test this hypothesis, we examined the effect of APP overexpression on a well characterized, in vivo, developmental model of systems-level plasticity, ocular dominance plasticity. Following monocular visual deprivation during the critical period, mice that express mutant alleles of amyloid precursor protein (APPswe) and Presenilin1 (PS1dE9), as well as mice that express APPswe alone, lack ocular dominance plasticity in visual cortex. Defects in the spatial extent and magnitude of the plastic response are evident using two complementary approaches, Arc induction and optical imaging of intrinsic signals in awake mice. This defect in a classic paradigm of systems level synaptic plasticity shows that Aβ overexpression, even early in postnatal life, can perturb plasticity in cerebral cortex, and supports the idea that decreased synaptic plasticity due to elevated Aβ exposure contributes to cognitive impairment in AD.
Parenting styles and sociodramatic play

This exploratory study investigated the relationship of parenting styles to sociodramatic play in preschool-aged children. The sample included 31 threeto five-year-old girls (M= 4 yrs. 1 mo.) and their mothers. Mothers completed a 91-item questionnaire on child-rearing values and practices. Children were observed for two 15-minute sessions during their preschool's regular indoor free-play periods to determine their level of sociodramatic play. Although it was hypothesized that parents who exhibited qualities of authoritative parenting (i.e., high warmth/responsiveness and high demandingness/control) would facilitate higher levels of sociodramatic play in children, the results indicated that maternal control only> and not authoritative parenting per se influenced childrens' level of sociodramatic play. These results suggest that by exerting firm control, a mother may be setting the framework by which a child is more self-confident, explores more, is friendly and cooperative, and self-assertiye, all of which are characteristics that may facilitate sociodramatic play.
CS 6332 : Fall 2008 Systems for Large Data Review

MapReduce [10] gives us an appropriate model for distributed parallel computing. There are several features which are proved useful: 1) centralized job distribution. 2) Fault tolerance mechanism for both masters and workers. Although there is controversies about MapReduce capability to replace standard RDBMS [12, 13], it is reasonable that existing proposals to use MapReduce in relational data processing [39] do not manipulate very well for complicated queries. Besides, MapReduce itself is not really user-friendly for most programmers and therefore may need some additional specific language or systems for its easy usage [30].
Diagnostic Problem Solving via Planning with Ontic and Epistemic Goals

Diagnostic problem solving involves a myriad of reasoning tasks associated with the determination of diagnoses, the generation and execution of tests to discriminate diagnoses, and the determination and execution of actions to alleviate symptoms and/or their root causes. Fundamental to diagnostic problem solving is the need to reason about action and change. In this work we explore these myriad of reasoning tasks through the lens of artificial intelligence (AI) automated planning. We characterize a diversity of reasoning tasks associated with diagnostic problem solving, prove properties of these characterizations, and define correspondences with established automated planning tasks and existing state-of-the-art planning systems. In doing so, we characterize a class of planning tasks with epistemic and ontic goals which we show can be compiled into non-epistemic planning, allowing state-of-the-art planners to compute plans for such tasks. Furthermore, we explore the effectiveness of using the conditional planner Contingent-FF with a number of diagnostic planning tasks.
Microtubule dynamics in interphase cells

The sites of microtubule growth and the kinetics of elongation have been studied in vivo by microinjection of biotin-labeled tubulin and subsequent visualization with immunocytochemical probes. Immunofluorescence and immunoelectron microscopy demonstrate that injected biotin-labeled subunits are incorporated into new segments of growth which are contiguous with unlabeled microtubules. Rapid incorporation occurs by elongation of existing microtubules and new nucleation off the centrosome. The growth rate is 3.6 micron/min and is independent of the concentration of injected labeled tubulin. This rate of incorporation together with turnover of existing microtubules leads to approximately 80% exchange in 15 min. The observed kinetics and pattern of microtubule turnover allow for an evaluation of the relevance of several in vitro models for steady-state dynamics to the in vivo situation. We have also observed a substantial population of quasi-stable microtubules that does not exchange subunits as rapidly as the majority of microtubules and may have specialized functions in the cell.
Secure Dot Product of Outsourced Encrypted Vectors and its Application to SVM

It is getting popular for users to outsource their data to a cloud system as well as leverage the high-speed computing power of this third-party platform to process the data. For the sake of data privacy, outsourced data from different users is usually encrypted under different keys. To enable users to run data mining algorithms collaboratively in the cloud, we need an efficient scheme to process the encrypted data under multiple keys. Dot product is one of the most important building blocks of data mining algorithms. In this paper, we show how to give the cloud the permission to decrypt the encrypted dot product of two encrypted vectors without compromising the privacy of the data owners. We propose the first feasible scheme that trains a SVM (Support Vector Machine) classifier for both horizontally and vertically partitioned datasets using only one server. Existing schemes either can only handle a much simpler classifier (linear mean classifier) with two non-colluding servers or can only be applied to vertically partitioned dataset. We also show that our scheme not only preserves data privacy but also runs faster than existing schemes.
Implementation of Automatic Generation Control of Hydrothermal System Employing Hybrid Genetic-Neural Approach

This paper presents the design of controller based on the combined principle of Genetic Algorithm and Neural networks. The concept of artificial intelligent techniques greatly helps in overcoming the disadvantages posed by the conventional controllers. A hierarchical architecture of three layer feed forward neural network (NN) is proposed for controller design based on back propagation algorithm (BPA). Area Control Error (ACE) is considered as input to the neural network controller and the output of the controller is provided to the governor in each area. The main advantage of neural network is that it can adapt itself from the training data. In order to reduce the complexity of having more training data, Genetic Algorithm (GA) has been incorporated into the neural network in order to obtain optimal values of weights and bias. The proposed controller is tested for a two area hydrothermal system. Simulation results show that the limitations of conventional controller can be overcome by including Hybrid Genetic-Neural concept and thereby the dynamic response of the system with respect to peak time, overshoot and settling time can be improved drastically.
Effects of the duration of expressions on the recognition of microexpressions

ObjectiveThe purpose of this study was to investigate the effects of the duration of expressions on the recognition of microexpressions, which are closely related to deception.MethodsIn two experiments, participants were briefly (from 20 to 300 ms) shown one of six basic expressions and then were asked to identify the expression.ResultsThe results showed that the participants’ performance in recognition of microexpressions increased with the duration of the expressions, reaching a turning point at 200 ms before levelling off. The results also indicated that practice could improve the participants’ performance.ConclusionsThe results of this study suggest that the proper upper limit of the duration of microexpressions might be around 1/5 of a second and confirmed that the ability to recognize microexpressions can be enhanced with practice.
Comparison of Diagnosed vs Predicted Condensate in CCM3 1 A comparison of the CCM3 model climate using diagnosed and predicted condensate parameterizations

We introduce a parameterization for the prediction of cloud water into the NCAR CCM3. The new parameterization makes a much closer connection between the meteorological processes which determine condensate formation, and the condensate amount. The parameterization removes some constraints from the simulation, by allowing a substantially wider range of variation in condensate amount than in the standard CCM3, and tieing the condensate amount to local physical processes. The parameterization also allows cloud drops to form prior to the onset of grid-box saturation, and can require a signiicant length of time to convert condensate to a precipitable form, or to remove the condensate. The free parameters of the scheme were adjusted to provide reasonable agreement with top of atmosphere and surface uxes of energy. The parameterization was evaluated by a comparison with satellite and in-situ measures of liquid and ice cloud amounts. The eeect of the parameterization on the model simulation was then examined by comparing long model simulations to a similar run with the standard CCM, and through comparison with climatologies based upon meteorological observations. Global ice and liquid water burdens are higher in the revised model than in the CONTROL simulation, with an accompanying increase in height of the center of mass of cloud water. Zonal averages of cloud water contents were 20 to 50% lower near the surface, and much higher above. The range of variation of cloud water contents is much broader in the new parameterization but was still not as large as measurements suggest. Diierences in the simulation were generally small. The largest signiicant changes found to the simulation were seen in polar regions (winter in the arctic, and all seasons in the antarctic). The new parameterization signiicantly changes the northern hemisphere winter distribution of cloud water and improves the simulation of temperature and cloud amount there. Small changes were introduced in the cloud fraction to improve consistency of the meteorological parameterizations, and to attempt to alleviate problems in the model (in particular, in the marine stratocumulus regime). The small changes did not make any appreciable improvement to the model simulation. The new parameterization adds signiicantly to the exibility in the model, and the scope of problems which can be attacked. Such a scheme is needed for a reasonable treatment of scavenging of atmospheric trace constituents, and cloud aqueous or surface chemistry. The addition of a more realistic condensate parameterization provides opportunities for a closer connection …
Cognitive distortions in an acutely traumatized sample: an investigation of predictive power and neural correlates

Background Current theories of post-traumatic stress disorder (PTSD) place considerable emphasis on the role cognitive distortions such as self-blame, hopelessness or preoccupation with danger play in the etiology and maintenance of the disorder. Previous studies have shown that cognitive distortions in the early aftermath of traumatic events can predict future PTSD severity but, to date, no studies have investigated the neural correlates of this association. Method We conducted a prospective study with 106 acutely traumatized subjects, assessing symptom severity at three time points within the first 3 months post-trauma. A subsample of 20 subjects additionally underwent a functional 4-T magnetic resonance imaging (MRI) scan at 2 to 4 months post-trauma. Results Cognitive distortions proved to be a significant predictor of concurrent symptom severity in addition to diagnostic status, but did not predict future symptom severity or diagnostic status over and above the initial symptom severity. Cognitive distortions were correlated with blood oxygen level-dependent (BOLD) signal strength in brain regions previously implicated in visual processing, imagery and autobiographic memory recall. Intrusion characteristics accounted for most of these correlations. Conclusions This investigation revealed significant predictive value of cognitive distortions concerning concurrent PTSD severity and also established a significant relationship between cognitive distortions and neural activations during trauma recall in an acutely traumatized sample. These data indicate a direct link between the extent of cognitive distortions and the intrusive nature of trauma memories.
Evaluation of smart electric wheelchair operation based on directional input from user and mobile robot navigation

This paper presents a smart electric wheelchair used as a personal mobility tool (PMT), which integrates autonomous mobile robot navigation and human operation input. This PMT is implemented using an actual electric wheelchair. An experiment is conducted to evaluate the usability of the input interface and movement efficiency of the PMT; its performance is compared to that of a normal electric wheelchair operated using a joystick.
Self-Organized Disjoint Service Placement in Future Mobile Communication Networks

Future mobile communication networks will offer many ubiquitous services to its clients such as voice and video communication, access to data and files, use of virtual resources in cloud, etc. The provision of these services will have to face the different challenges posed by future wireless networks such as changing network topology, variable load conditions, clients’ distribution, QoS requirements etc. is a very difficult task and requires a high degree of self-organization in network operations. One important problem in this context is the self-organized service placement which refers to the problem of finding optimal nodes in the network that are most suitable for hosting a particular service type. An optimal placement of a service and its instances (replicas) not only minimizes the service costs but also reduces the overall network traffic and improves connectivity between clients and servers. This paper proposes a novel network service called Self-Organized Disjoint Service Placement (SO-DSP) service which manages other network services and their instances in order to achieve overall network optimization while keeping the individual service’s quality at the same level for its clients. The clients of SO-DSP are not the end-users of the network but the offered network services
Approximate dynamic programming using model-free Bellman Residual Elimination

This paper presents an modification to the method of Bellman Residual Elimination (BRE) for approximate dynamic programming. While prior work on BRE has focused on learning an approximate policy for an underlying Markov Decision Process (MDP) when the state transition model of the MDP is known, this work proposes a model-free variant of BRE that does not require knowledge of the state transition model. Instead, state trajectories of the system, generated using simulation and/or observations of the real system in operation, are used to build stochastic approximations of the quantities needed to carry out the BRE algorithm. The resulting algorithm can be shown to converge to the policy produced by the nominal, model-based BRE algorithm in the limit of observing an infinite number of trajectories. To validate the performance of the approach, we compare model-based and model-free BRE against LSPI, a well-known approximate dynamic programming algorithm. Measuring performance in terms of both computational complexity and policy quality, we present results showing that BRE performs at least as well as, and sometimes significantly better than, LSPI on a standard benchmark problem.
Challenges in distributed leadership: evidence from the perspective of headteachers

Purpose – The purpose of this paper is to investigate the issues and challenges faced by headteachers in practicing the suggested distributed leadership (DL) approach in three primary schools to their middle layer leaders. Design/methodology/approach – The study employed a case study design and data were collected through semi-structured interviews. A total of three headteachers were interviewed in examining and exploring challenges within the DL practices. The transcripts from the semi-structured interviews formed the basis of the findings. Findings – The findings suggest that senior teachers lack confidence in making decisions and rely on the consent from headteachers even though they are empowered to make their own decisions. Another significant issue faced by headteachers when distributing their leadership is the ability, expertise, experience, and willingness of teachers to hold leadership roles and responsibilities. Originality/value – The results are important since there have been few empirical studies on the issues and challenges faced by headteachers in practising DL approach in primary schools in the context of Malaysia. This initiative sidelines the traditional school leadership approach which emphasises on the accountability of headteachers as the sole school leader.
Guidance Law Design Based on Finite Time Convergence

Traditional guidance laws are designed based on Lyapunov theorem. They will guide the line of sight (LOS) angular rate to converge to zero when time approaches infinity. In this paper, guidance laws with finite time convergence are proposed in terms of finite time stability theory of nonlinear control systems. It is proved that the LOS angular rate will converge to zero before the final guidance ends with the designed guidance laws. Simulation results show that the guidance laws are highly effective.
Presynaptic NMDA Receptors Modulate Glutamate Release from Primary Sensory Neurons in Rat Spinal Cord Dorsal Horn

NMDA receptors have the potential to produce complex activity-dependent regulation of transmitter release when localized presynaptically. In the somatosensory system, NMDA receptors have been immunocytochemically detected on presynaptic terminals of primary afferents, and these have been proposed to drive release of substance P from central terminals of a subset of nociceptors in the spinal cord dorsal horn. Here we report that functional NMDA receptors are indeed present at or near the central terminals of primary afferent fibers. Furthermore, we show that activation of these presynaptic receptors results in an inhibition of glutamate release from the terminals. Some of these NMDA receptors may be expressed in the preterminal axon and regulate the extent to which action potentials invade the extensive central arborizations of primary sensory neurons.
Agenda Diversity in Social Media Discourse: A Study of the 2012 Korean General Election

The diversity of agendas in the media plays a critical role in shaping the scope of public discourse. Due to the increasing impact of social media, it is important and necessary to examine if it is circulating a wide range of issue and extending the realm of public discussion. In this paper, we put forward agenda diversity as a core value for evaluation of social media discourse and examine the current diversity status. Our study provides a firm basis for understanding the topics, quantity, diversity, and relative salience of the agendas offered by the social media. We further look into the information diffusion process from the diversity viewpoint, and explore the potential to increase diversity.
Analysis of security algorithms towards secured communication in wireless networks

Wireless sensor networks are now widely used in military surveillance, industrial applications and civilian uses such as pollution control, forest fire detection, farming etc. The design of wireless network varies from application to application. These networks are vulnerable to external threats that may try to gain unauthorized access with malicious intent. The wireless network also has design similarities with adhoc network. In this paper deals with the different security algorithms that exist in wireless network. It also provides analysis for conclusions of the selection of appropriate security algorithm towards improving the trust among users in wireless network. Security issues exist at node level, network level and user level. The security algorithms have been analyzed for wireless networks in different directions and research directions of the analysis has been presented.