Miracle-dz/UniFAR-FTUs huggingface dataset:
Student and Parent IEP Collaboration: A Comparison across School Settings

The purpose of this study was to determine if differences existed across rural, urban, and suburban environments when special education teachers reported perceived levels of student and parent involvement and participation during IEP meetings. The investigators surveyed special education teachers (N = 159) across a Southwest state and applied log linear analyses to show possible differences in groups. Special education teachers in rural environments reported significantly higher rates of parent and student involvement and participation in IEP meetings than their counterparts in urban and suburban environments. Results are discussed and suggestions and implications for practitioners are provided.
Safeguard: User Reauthentication on Smartphones via Behavioral Biometrics

With the emergence of smartphones as an essential part of daily life, the demand for user reauthentication has increased manifolds. The effective and widely practiced biometric schemes are based upon the principle of “who you are” which utilizes inherent and unique characteristics of the user. In this context, the behavioral biometrics such as sliding dynamics and pressure intensity make use of on-screen sliding movements to infer the user's patterns. In this paper, we present Safeguard, an accurate and efficient smartphone user reauthentication (verification) system based upon on-screen finger movements. The computation and processing is performed at back-end which is transparent to the users. The key feature of the proposed system lies in fine-grained on-screen biometric metrics, i.e., sliding dynamics and pressure intensity, which are unique to each user under diverse scenarios. We first implement our scheme through five machine learning approaches and finally select the support vector machine (SVM)-based approach due to its high accuracy. We further analyze Safeguard to be robust against adversary imitation. We validate the efficacy of our approach through implementation on off-the-shelf smartphone followed by practical evaluation under different scenarios. We process a set of more than 50 000 effective samples derived from a raw dataset of over 10 000 slides collected from each of the 60 volunteers over a period of one month. The experimental results show that Safeguard can verify a user with 0.03% false acceptance rate (FAR) and 0.05% false rejection rate (FRR) within 0.3 s with 15 to 20 slides by the user. The FRR of our system adequately meets the European Standard for Access Control Systems, whereas FAR differs by 0.029%. Our future works aim to integrate multitouch sliding movements in existing scheme.
Constructing abstract maps from spatial descriptions for goal-directed exploration

This paper describes ongoing work on a system using spatial descriptions to construct abstract maps that can be used for goal-directed exploration in an unfamiliar office environment. Abstract maps contain membership, connectivity, and spatial layout information extracted from symbolic spatial information. In goal-directed exploration, the robot would then link this information with observed symbolic information and its grounded world representation. We demonstrate the ability of the system to extract and represent membership, connectivity, and spatial layout information from spatial descriptions of an office environment. In the planned study, the robot will navigate to the goal location using the abstract map to inform the best direction to explore in.
MULTI-PLAN RETRIEVAL AND ADAPTATION IN AN EXPERIENCE-BASED AGENT

To address these issues, we propose a theory of experience-based agency which specifies how an agent with the ability to richly represent and store its experiences could remember those experiences with a context-sensitive, asynchronous memory, incorporate the relevant portions of those experiences into its reasoning on demand w ith integration mechanisms, and direct memory and reasoning through the use of a utility-based control mechanism. We have implemented this theory in the NICOLE multistrategy reasoning system and are currently using it to explore the problem of merging multiple past planning experiences. N ICOLE’S control system allows memory and reasoning to proceed in parallel; the asyn chronous and context-sensitive nature of that memory system allows NICOLE to return a “best guess” retrie val immediately and then to update that retrieval whenever new cues become available. But solving the problem of merging planning experiences requires more than just memory and control. We need mechanisms to integrate new retrieved plans into the planner’s current reasoning context whenever they are found; to en sure that those new retr ieved plans are useful, we need ways to use the planner’s current context to generate new cues that can help guide the memory system’s search. To solve these subproblems, we have developed the Multi-Plan Adaptor (MPA) algorithm, a novel method for merging partial-order plans in the context of casebased least-commitment planning. MPA allows the merging of arbitrary numbers of plans at any point during the adaptation process; it achieves this by dynamically extracting relevant case subparts and splicing those subpart s into partially completed plan s. MPA can also help guide retrieval by extracting intermediate goal statements from partial plans. In this chapter, we briefly review the properties of the real world that present challenges for the design of intelligent agents, examining in particular the need to combine past planning experiences. We then review our theory of experience-based agency and its implementation in the NICOLE system. We present the MPA algorithm, illustrate how it supports the merging of plans at any point during the adaptation pro cess, and describe its foundations in leastcommitment case-based planning. We then discuss how MPA can be integrated into various
Simulation of MRAC based speed control of brushless DC motor with low-resolution hall-effect sensors

2 Abstract: A novel speed estimation approach with control system based on model reference adaptive control (MRAC) is presented for low cost brushless dc motor drives with low-resolution hall sensors. The back EMF is usually used to estimate speed. But the estimation result is not accurate enough at low speeds because of the divided voltage of stator resistors and too small back EMF. Moreover, the stator resistor is always varying with the motor"s temperature. A speed estimation algorithm based on MRAC was proposed to correct the speed error estimated by using back EMF. The proposed algorithm"s most innovative feature is its adaptability to the entire speed range including low speeds and high speeds and temperature and different motors do not affect the accuracy of the estimation result. The effectiveness of the algorithm was verified through simulations and experiments.
Building efficient partial plans using Markov decision processes

Markov decision processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given goal, accounting for actuator uncertainties. But algorithms classically used to solve MDPs are intractable for problems requiring a large state space. Plans are computed considering the whole state space, without using any knowledge about the initial state of the problem. We propose a new technique to build partial plans for a mobile robot, considering only a restricted MDP which contains a small set of states composing a path between the initial state and the goal state. To ensure good quality of the solution, the path has to be very similar to the one which would have been computed on the whole environment. We present a new method to compute partial plans, showing that representing the environment as a directed graph can be very helpful to find near-optimal paths. Partial plans obtained using this method are very similar to complete plans, and computing times are considerably reduced.
The Semantics of Intermediate CPTs in Variable Elimination

Variable elimination (VE), a central component of Bayesian network inference, starts and ends with clear structure and semantics, yet all intermediate distributions, whether normalized or unnormalized, are denoted as potentials. In this paper, a condition is given stating when intermediate distributions are defined with respect to the joint distribution. Theoretical and practical advantages of these new semantics are given.
Intra Detrusor Botulinum Toxin and Lower Limbs Motor Deficit: About 2 Clinical Cases

Objective: To demonstrate how a single intra detrusor botulinum toxin injection could be responsible for lower limbs proximal motor deficit. Results: Two women-37 and 38 years old-presenting with secondary progressive multiple sclerosis, having received intra detrusor botulinum toxin injections (400 BOTOX® U and 750 DYSPORT® U) due to major neurogenic detrusor over activity with high-pressure and risks of uro-nephrologic complications despite an efficient-dose anticholinergic bi-therapy (DITROPAN®/CERIS®). Few days in post-injection they present heavy tiredness, instability of the pelvis, and a major reduction of the walking distance. Those symptoms last for several months. During the emergency neurology consultation set up in the event of a new relapse, an aggravation of the paraparesis at the proximal level is observed. This deficit accounts for the realization of a corticosteroids bolus, the effectiveness of which is questioned by the patient. A cerebral and medullary MRI is performed in order to certify the appearance of new lesions. The MRI doesn’t objectify any new lesions or any pathological contrast enhancement. Discussion: Ramirez-Castaneda et al. describe three means of dissemination of the BoNT: migration by systemic or neuronal transport, propagation/spread and diffusion. Conclusion: The retrograde migration of the botulinum toxin via hypo-gastric nerves seems to prevail. It could be followed by axonal anterograde transport causing a deficit on the hip flexors via the L2 nerve root.
Extending Filter-based Structure from Motion to Large Baselines

Filter-based Structure from Motion (SfM) approaches work usually in two steps: prediction and update. Prediction is the process of determining a prior distribution of the state vector at time t + 1 from the previous distribution at time t. Update is the process of adjusting the predicted distribution so it complies with the new received measurements at time t + 1. A key issue in those two steps is that the prediction and update should use statistically independent data and hence the same data can not be used in both of them. In Bayesian SfM filters that maintain a state vector composed of a set of 3D features and of the camera motion, and that use the projections of the 3D features in the images as measurements for the filter, this two step process faces a serious problem in the case where the baseline between successive frames (i.e. the displacement between the camera centers) is wide. This is because the previous estimate of the state vector at time t does not allow to solely determine an estimate of the motion at t+1 accurate enough for the filtering as there would be a significant change of motion between t and t + 1. In this paper, we provide a probabilistic solution to this problem by using features that are matched in the last three frames only. We show that this solution provides reliable prediction of the motion across large baselines.
First detection of a frequency multiplet in the line-profile variations of RR Lyrae : towards an understanding of the Blazhko effect

All present models for explaining the Blazhko ef- fect are based on the presence of non-radial components. Up to now, however, these components have not been found explicitly in the observational studies, which were all based on photoelec- tric data. We provide the first detection of a frequency multiplet in the line-profile variations of RR Lyrae. Performing a period analysis on 669 high resolution line profiles obtained with the spectrograph ELODIE at OHP, we clearly detect a multiplet structure, with a separation equal to the Blazhko frequency, around the main frequency and its harmonics. Additional obser- vations are needed to decide about the existence of a quintuplet. The presence of the harmonics of the main frequency in the line profiles indicates the importance of non-linear effects in the pulsation. The complete understanding of the origin of the Blazhko effect still needs further theoretical modelling and better new observations. Our detection of the frequency multiplet in the line-profile variations is a first essential step towards a decisive confrontation between the theoretical models and the observa- tions.
Structured Intelligent Search Engine for effective information retrieval using query clustering technique and Semantic Web

In this paper we present Structured Intelligent Search Engine (SISE), personalized search engine architecture catering the interest each user. In SISE, query clustering technique is used along with web semantics is used to produce much efficient and precise search results than current existing search systems. This claim is supported by the experimental results carried out on the NASA and FIRE data set. At present a vast majority of the popular search engines majorly depend upon the term frequency of the query issued by the users i.e., how many times the query has been repeatedly used in the article. Despite the rapid advancement in the field of information retrieval and especially in the advancement in the field of search engine there is still a lot of scope for development of personalized search engine. Apart from the problems of scaling traditional search techniques to deal with the ambiguous query, there are new technical challenges involved with using the additional information present in user search history to produce better search results. This paper addresses this question of how to build a personalised search system which can exploit the context of the query by using users search history to gather additional information present in user history.
EVENT-BASED TEXTUAL DOCUMENT RETRIEVAL BY USING SEMANTIC ROLE LABELING AND COREFERENCE RESOLUTION

Conventional keyword-based indexing and retrieval techniques for textual documents lack of precision when a long query string is employed in order to discover documents containing a specific “event”, such as “Einstein discovered relativity”. This paper proposes a framework to resolve such a problem. In our proposal, we apply semantic role labeling and coreference techniques in order to parse each sentence within textual documents into three elements: subject, object and predicates. These elements can subsequently be used for indexing and retrieval. Our primitive evaluation experiments have shown that this promising methodology raises the retrieval precision if we compared it to conventional literal termmatching techniques.
Multiple resources scheduling for diverse workloads in heterogeneous datacenter

Multiple resources allocation in large scale datacenter has been widely studied and used in recent years. However, the existing scheduling methods have some shortcomings in the heterogeneous environment, such as starving certain jobs, leaving some important resources unallocated, and decreasing system throughput. In this paper, we generalize the most popular multi-resource scheduling algorithm, Dominant Resource Fairness (DRF), to the heterogeneous datacenter, and propose the Heterogeneous DRF (H-DRF) algorithm. In H-DRF, we first introduce the parameter of weight for coprocessors to avoid job starvation and important resources unallocated. Second, we consider the factors of running tasks and average executing time of each job to ensure the fairness and throughput of the system. Finally, we implement H-DRF algorithm in the YARN resource manager for scheduling diverse workloads. The experimental results show that our proposed algorithm, H-DRF, leads to higher resources utilization and better throughput than DRF sharing scheme in heterogeneous datacenter.
Zebrafish sex: a complicated affair

In this review, we provide a detailed overview of studies on the elusive sex determination (SD) and gonad differentiation mechanisms of zebrafish (Danio rerio). We show that the data obtained from most studies are compatible with polygenic sex determination (PSD), where the decision is made by the allelic combinations of several loci. These loci are typically dispersed throughout the genome, but in some teleost species a few of them might be located on a preferential pair of (sex) chromosomes. The PSD system has a much higher level of variation of SD genotypes both at the level of gametes and the sexual genotype of individuals, than that of the chromosomal sex determination systems. The early sexual development of zebrafish males is a complicated process, as they first develop a ‘juvenile ovary’, that later undergoes a transformation to give way to a testis. To date, three major developmental pathways were shown to be involved with gonad differentiation through the modulation of programmed cell death. In our opinion, there are more pathways participating in the regulation of zebrafish gonad differentiation/transformation. Introduction of additional powerful large-scale genomic approaches into the analysis of zebrafish reproduction will result in further deepening of our knowledge as well as identification of additional pathways and genes associated with these processes in the near future.
Cheiracanthium ilicis sp. n. (Araneae, Eutichuridae), a novel spider species associated with Holm Oaks (Quercus ilex)

Abstract We describe a novel species Cheiracanthium ilicis sp. n. (Araneae, Eutichuridae) collected in the province of Toledo (Central Spain). It was found during a systematic sampling campaign carried out in an agricultural landscape with isolated Holm oaks Quercus ilex and small forest patches. Its morphology and affinities with other species of the genus are discussed. Furthermore, one mitochondrial gene was sequenced to confirm species membership and its differentiation from other Cheiracanthium species. The molecular phylogenies based on mitochondrial and nuclear genes showed a close relationship of Cheiracanthium ilicis sp. n. with Cheiracanthium inclusum and Cheiracanthium mildei, with which it also shares morphological similarities. Nonetheless, the sparse sampling of the phylogeny, due to the low number of sequences available, impedes drawing any definitive conclusion about these relationships; it is first necessary to perform an extensive review of the genus worldwide and more thorough phylogenies. Cheiracanthium ilicis sp. n. also shares certain ecological and phenological characteristics with Cheiracanthium inclusum and Cheiracanthium mildei. Like them, Cheiracanthium ilicis sp. n. is an obligate tree dweller that prefers a tree canopy habitat and reproduces primarily in late spring and summer. From a conservation perspective, the present study suggests the need to preserve isolated trees in agricultural landscapes. They are not only the refuge of common forest organisms but also of novel species yet to be discovered.
A Framework of Modified Adaptive Fuzzy Inference Engine (MAFIE) and Its Application

This paper introduces a complete framework of Modified Adaptive Fuzzy Inference Engine (MAFIE) and its application. The fuzzy with hybridization schemes has become of research interest in versatile applications over the past decade. The fuzzy hybridizations models are quite popular among practitioners or researchers in various advanced promising fields to help solve problems with a small number of inputs. However, there are limitations faced by all popular fuzzy systems when they are applied to systems with a large number of inputs. A modified apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input - output dataset. A TSK type fuzzy inference system is constructed by the automatic generation of membership functions and fuzzy rules by the hybrid fuzzy clustering (Fuzzy C-Means and Subtractive Clustering) and apriori algorithms techniques, respectively. The generated adaptive fuzzy inference engine is adjusted by the least - square estimator and a conjugate gradient descent algorithm towards better performance with a minimal set of fuzzy rules. The proposed MAFIE is able to reduce the number of fuzzy rules which increases exponentially when large input dimensions are involved. The performance of the proposed MAFIE is compared with other existing models when applied to pattern classification schemes using Fisher’s Iris and Wisconsin Breast Cancer benchmark datasets. The results are shown to be very competitive and MAFIE is ready for high dimension practical applications.
Clinical Features and Polysomnographic Findings in Greek Male Patients with Obstructive Sleep Apnea Syndrome: Differences Regarding the Age

Background-Aim. Although sleep disturbance is a common complaint among patients of all ages, research suggests that older adults are particularly vulnerable. The aim of this retrospective study was to elucidate the influence of age on clinical characteristics and polysomnographic findings of obstructive sleep apnea syndrome (OSAS) between elderly and younger male patients in a Greek population. Methods. 697 male patients with OSAS were examined from December 2001 to August 2011. All subjects underwent an attended overnight polysomnography (PSG). They were divided into two groups: young and middle-aged (<65 years old) and elderly (≥65 years old). We evaluated the severity of OSAS, based on apnea-hypopnea index (AHI), and the duration of apnea-hypopnea events, the duration of hypoxemia during total sleep time (TST) and during REM and NREM sleep, and the oxygen saturation in REM and in NREM sleep. Results. PSG studies showed that elderly group had significant higher duration of apnea-hypopnea events, longer hypoxemia in TST and in NREM sleep, as well as lower oxygen saturation in REM and NREM sleep than the younger group. Otherwise, significant correlation between BMI and neck circumference with AHI was observed in both groups. Conclusions. The higher percentages of hypoxemia during sleep and longer duration of apnea-hypopnea events that were observed in the elderly group might be explained by increased propensity for pharyngeal collapse and increased deposition of parapharyngeal fat, which are associated with aging. Another factor that could explain these findings might be a decreased partial arterial pressure of oxygen (PaO2) due to age-related changes in the respiratory system.
Pastry Based Sensor Data Sharing

With research effort of Ubiquitous computing development, Wireless Sensor Networks have also been studied and deployed in many places. Recently various works for sharing the existing sensor data have been tried. In this paper we propose a P2P based system for sharing sensor data. It uses a structured P2P - Pastry to provide DHT based routing without server and has been deployed in KOREN. We classify the sensor data into real-time data and past data, and Scribe in Pastry is applied to multicast the real-time data and PAST in Pastry is used to store and provide the past data. Also as Pastry itself does not provide the search function, we propose to use PAST for providing search function using keywords.