Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of remote sensing technologies to time series analyses of surface temperatures in Daegu city

This study intended to develop a new method for the analysis and assessment of city surface temperatures (ST). Landsat data from 1994 to 2003 were used, and Daegu, Korea, was selected as the study region. Surface temperature difference(STD) distribution diagrams were prepared and verified, based on the surface temperatures of wide and flat playgrounds of schools. The surface temperatures of the entire city were rearranged as an axis to enable temporal and spatial analysis of surface temperatures. STD distributions in relation to land-cover could be seen. The reason why the STD of rice paddies existed was the differences in water states before and after rice-planting. In addition, yearly changes in STD distributions in industrial regions and downtown regions could be seen. Diverse aspects of STD analysis methods were described to verify the methods.
Stair Climbing using a compliant modular robot

Stair Climbing is a key functionality desired for robots deployed in Urban Search and Rescue (USAR) scenarios. A novel compliant modular robot was proposed earlier to climb steep and big obstacles. This work extends the functionality of this robot to ascend and descend stairs of dimensions that are also typical of an urban setting. Stair Climbing is realized by equipping the robot's link joints with optimally designed passive spring pairs that resist clockwise and counter clockwise moments generated by the ground during the climbing motion. This 3-module robot is only propelled by wheel actuators. Desirable stair climbing configurations are estimated a-priori and used to obtain the optimal stiffness for springs. Extensive numerical simulation results over different stair configurations are shown. The numerical simulations are corroborated by experimentation using the prototype and its performance is tabulated for different types of surfaces.
A New Algorithm for Stable Communication in Wireless Emergency Network

Emergency communication has been intensively investigated for solving suddenly-occurred events of public safety. Wireless network can play an important role of information acquisition and command decision-making in disaster areas, so a new Wireless Emergency Communication (WEC) algorithm is proposed in this paper. This algorithm possesses the characteristics of quick, stability, low energy and high reliability. The test results show that wireless emergency network adopting this algorithm can achieve the optimal stable communication.
“Please Draw Me a Face…” Atypical Face Mental Concept in Autism

Autism is a severe neurodevelopmental disorder characterized by early manifestations of social difficulties and atypical sensory-based behaviors. As faces are essential for social interaction, they have been widely investigated in autism, revealing disruptions in face processing. Cognitive theories argue that people with autism process the world differently, showing a processing bias for local information. However, the literature currently neglects the mental representation of faces, or face concept, in people with ASD. The current study sought to establish how young children with ASD “see” a human face. A key question is whether this face concept is a function of cognitive style and/or sensory impairment. By comparing simple face drawings in young children with ASD, with those of deaf children and controls, we highlight an atypical face concept in ASD that does not show, however, global processing deficits: face drawing presents a preserved overall configuration. The atypical face drawings in children with ASD showed similarities with those of deaf children: eyes were not an essential feature, whereas a marked interest for ears and non-facial external features (accessories, body parts) was shown. These findings suggest that the face mental concept in ASD may be impacted by sensory processing deficits.
Symmetric Cipher Design Using Recurrent Neural Networks

In this paper, a neural network-based symmetric cipher design methodology is proposed to provide high performance data encryption. The proposed approach is a novel attempt to apply the parallel processing capability of neural networks for cryptography purposes. By incorporating neural networks approach, the proposed cipher releases the constraint on the length of the secret key. The proposed cipher is robust in resisting different cryptanalysis attacks and provides efficient data integrity and authentication services. The design of the symmetric cipher is presented and its security is analyzed. Simulation results are presented to validate the effectiveness of the proposed cipher design.
Relationship of Students' Spelling Gains to Teacher Knowledge and Teacher Practice

Relationship of Students’ Spelling Gains to Teacher Knowledge and Teacher Practice by Alison Puliatte Advisor: Professor Linnea C. Ehri This study examined the impact of classroom teachers’ linguistic knowledge and spelling instructional practices on Grade 2 and 3 students’ spelling gains over the course of one school year. The purpose of this study was to identify teacher level variables that impact student spelling gains. This study employed a correlational research design aimed at finding relationships between two independent variables and one dependent variable. The two independent variables were teacher instructional practices and teacher linguistic knowledge. Teacher level variables were identified through two measures, an Instructional Practices Questionnaire and a Linguistic Knowledge Survey. The dependent variable was the student spelling gain score which was measured by calculating gains made from a beginning of the year spelling pretest to an end of the year spelling posttest. Gains were measured in terms of the number of words spelled correctly. In addition, relationships between teacher knowledge and practices were examined. The participants included 32 classroom teachers (16 Grade 2 and 16 Grade 3), and 636 students (331 Grade 2 and 305 Grade 3). Correlational analyses revealed a significant positive relationship between teacher total knowledge and classroom practices. In addition, significant and positive relationships were found between student gain scores and teacher phoneme knowledge, time spent in weekly spelling instruction, and teaching of spelling strategies. These results were found on a subsample
Real-time navigation and obstacle avoidance from optical flow on a space-variant map

Navigation and obstacle avoidance belong to the basic behavioral repertoire of any biological or technical autonomous agent. A moving observer equipped with a monocular visual sensor can gain information pertinent for the performance of these tasks from the optical flow field induced by its own motion. In the periphery of the visual field image flow can be evaluated for speed and direction control, whereas the central flow indicates imminent collisions. We show that a space-variant mapping augmented with a purposive representation of the environment allows a robot to take into account these structural properties of the flow field and to navigate in real-time in an unknown environment. We implemented an extended simulation environment, and verified reliability, speed, control and robustness of our proposed scheme.
Practical resource scheduling in massive-cell deployment for 5G mobile communications systems

This paper proposes the first practical resource scheduling that increases system throughput in massive-cell deployment for 5G mobile communications systems. In 5G systems, the best combination of a huge number of antennas and user equipment for communications should be decided in the scheduling. The proposed scheme searches for the suitable combination without exhaustive search and accelerates calculation of system throughput for each combination. The scheme quickly obtains the combination for which the scheduling achieves higher system throughput, and thus the scheduling can be done within the required period. Simulation and experimental measurements show that the system throughput obtained is about seven times higher than for the conventional scheme. The proposed scheme enables a future practical 5G system.
Adaptive 3D Reconstruction system with improved recovery of miscoded region to automatically adjust projected light patterns

The paper proposes an adaptive system for 3D object reconstruction which analyzes the shape and colours of the object and automatically designs suitable projection patterns for more effective reconstruction. The system is also able to detect regions with details and adaptively provides higher resolution reconstructions for such regions. A method that interpolates the ambiguous or miscoded regions based on the monotonicity of camera-projector correspondence relationship is also proposed to improve the accuracy of the system. Experiments have been performed to demonstrate the effectiveness of the proposed approaches and to show that the proposed system is able to overcome inflexibilities in traditional structured lighting approaches.
Algebraic Reasoning for Probabilistic Concurrent Systems

We extend Milner's SCCS to obtain a calculus, PCCS, for reasoning about communicating probabilistic processes. In particular, the nondeterministic process summation operator of SCCS is replaced with a probabilistic one, in which the probability of behaving like a particular summand is given explicitly. The operational semantics for PCCS is based on the notion of probabilistic derivation, and is given structurally as a set of inference rules. We then present an equational theory for PCCS based on probabilistic bisimulation, an extension of Milner's bisimulation proposed by Larsen and Skou. We provide the rst axiomatization of probabilistic bisimulation, a subset of which is relatively complete for nite-state probabilistic processes. In the probabilistic case, a notion of processes with almost identical behavior (i.e., with probability 1 ? , for suuciently small) appears to be more useful in practice than a notion of equivalence, since the latter is often too restrictive. We weaken probabilistic bisimulation to obtain a metric space for \deterministic" PCCS processes, and show that in most contexts the eeect of expression replacement on distance is isometric. Finally, we use PCCS to model and analyze the performance of the AUY communication protocol for deletion errors.
Visualization of Large Nested Graphs in 3D: Navigation and Interaction

Abstract Most systems for visualizing large information structures use 2D graphics to view networks of nodes and arcs that represent data. To understand large structures it is often necessary to show both small-scale and large-scale structures. This has been called the problem of focus and context. Distortion, rapid zooming, elision and multiple windows are all techniques that have been developed to provide both focus and context within single representations. We review these techniques and argue that 3D visualization has a number of advantages. A system called NestedVision3D (NV3D) will be presented that has been developed to investigate the use of 3D visualization for understanding the structure of large computer programs. NV3D is a system for visualizing large nested graphs using interactive 3D graphics. It has been tested with graphs containing more than 35,000 nodes and 100,000 relationships. We describe NV3D and its design philosophy. Basic navigation is facilitated by a set of 3D widgets, rapid scaling and interactive elision. More experimental features include animations called snakes, which are used to trace dynamic software behavior.
Utility-proportional fairness in wireless networks

Current communication networks support a variety of applications with different quality of service (QoS) requirements which compete for its resources. This continuously increasing competition highlights the necessity for more efficient and fair resource allocation. Current Network Utility Maximization (NUM) framework fails to achieve this target and alternative approaches cannot operate in networks that consist of wireless links. This paper presents a NUM framework for wireless networks that shares resources according to the utility proportional fairness policy. This policy is shown to prevent rate oscillations in the resource allocation process, allocate resources in a more fair manner among different types of applications and lead to the calculation of closed form solutions for the optimal rate allocation function. Based on this policy, a distributed rate and power allocation algorithm is proposed that gives priority to applications with greater need of resources. Finally, numerical results on the performance of the proposed algorithm are presented and compared against other approaches in the literature.
Mapping the tourism mobile applications: what, how and where

Today's growing interest in mobile technologies and applications creates curiosity to examine the conditions (what, how and where) under which they can be especially applied in the tourism sector. This paper focuses on mapping the mobile tourism applications regarding specific dimensions of proposed business models resulting by extended literature review. Fourteen tourism services are analyzed as case studies through a content analysis selection taking into consideration the proposed dimensions. Furthermore, the specific focus of these services is mainly on their value proposition, the role of their technology delivery channels, the initiators of the services and their revenue model. The results showed that the most popular mobile tourism applications are for navigating and disseminating information to end-users/travellers using their smart phones as a channel.
TWO TIME-SCALE FEASIBLE DIRECTION METHOD

Abstract Stochastic constrained optimization problems with non-convex objective and convex feasible domain are considered for the case where the objective and constraint functions are available only throuth noisy observations. A general algorithm of the two time-scale stochastic approximation type is proposed for these problems. The proposed algorithm is applied to Markov decision problems with average cost, average constraints and parameterized randomized policy. The asymptotic behavior of the proposed algorithm is analyzed for the case where the algorithm step-sizes are constant and the noise in the observations of the objective and constraint functions depends on the algorithm iterates.
Stimuli Evoking Positive Emotions in Infants in the First Months of Life

The development of positive emotions in children is a significant objective of communist upbringing. This goal is particularly important in raising very young children, at the time when positive emotions are just being formed. Under favorable conditions of upbringing, such emotions first appear at the end of the first and the beginning of the second month of life. In the course of the second and third months, the corresponding expressive movements come to establish what is termed the "animation complex" [kompleks ozhivleniia]. (16) This reaction complex includes smiling, quick and animated generalized movements with repeated straightening and bending of hands and feet, rapid breathing, vocal reactions, eyeblink, etc. All of practical experience in child rearing shows that a timely appearance of these responses is of much significance to the neuro-mental and physical development of children. Therefore it is important to know what conditions are essential for early formation of this positive emotional compl.
Clearing an Orthogonal Polygon Using Sliding Robots

In a multi-robot system, a number of autonomous robots would sense, communicate, and decide to move within a given domain to achieve a common goal. In this paper, we consider a new variant of the pursuit-evasion problem in which the robots (pursuers) each move back and forth along an orthogonal line segment inside a simple orthogonal polygon $P$. A point $p$ can be covered by a sliding robot that moves along a line segment s, if there exists a point $q\in s$ such that $\overline{pq}$ is a line segment perpendicular to $s$. In the pursuit-evasion problem, a polygonal region is given and a robot called a pursuer tries to find some mobile targets called evaders. The goal of this problem is to design a motion strategy for the pursuer such that it can detect all the evaders. We assume that $P$ includes unpredictable, moving evaders that have unbounded speed. We propose a motion-planning algorithm for a group of sliding robots, assuming that they move along the pre-located line segments with a constant speed to detect all the evaders with unbounded speed.
Characterization of Supersaturatable Formulations for Improved Absorption of Poorly Soluble Drugs

With the increasing number of poorly water-soluble compounds in contemporary drug discovery pipelines, the concept of supersaturation as an effective formulation approach for enhancing bioavailability is gaining momentum. This is intended to design the formulation to yield significantly high intraluminal concentrations of the drug than the thermodynamic equilibrium solubility through achieving supersaturation and thus to enhance the intestinal absorption. The major challenges faced by scientists developing supersaturatable formulations include controlling the rate and degree of supersaturation with the application of polymeric precipitation inhibitor and maintenance of post-administration supersaturation. This review is intended to cover publications on this topic since April 2009. Scientific publications associated with characterization of supersaturatable systems and related preclinical and clinical pharmacokinetics (PK) studies are reviewed. Specifically, this review will address issues related to assessing the performance of supersaturatable systems including: (1) Diversified approaches for developing supersaturatable formulations, (2) meaningful in vitro test methods to evaluate supersaturatable formulations, and (3) in vivo PK study cases which have demonstrated direct relevance between the supersaturation state and the exposure observed in animal models and human subjects.
Do Insecure Systems Increase Global Digital Divide

Without doubt information and communication technologies (ICTs) continue to change the world to varying degrees from one place to another, depending on a number of technological and socio-economical factors such as: physical access to technology, education, geographical locations, language and gender (Warschauer, 2002; Chen & Wellman, 2003; Nahon, 2006). As a result of these factors the rates of adopting ICTs are different between countries. Accordingly, this creates a disparity between communities, or a gap commonly known as Global Digital Divide. The term digital divide is claimed to have been first used a decade ago by US Department of Commerce’s National Telecommunication and Information Administration (NITA, 1999). Since then, the term has been extensively discussed by scholars and politicians in order to propose strategies and recommendation for bridging the aBstract
Growth and Its Discontents

Fragmented marketing debates concerning the role of alternative economies are attributable to the lack of a meaningful macromarketing dimension to which alternative economic practices can be anchored. This research frames an evaluation of existing macromarketing developments aimed at reformulating the mindless pursuit of economic growth. Raising concerns with the treadmill dynamics of marketing systems, three different approaches - green growth, a-growth and degrowth - are critically evaluated to: (a) introduce degrowth as a widely overlooked concept in the macromarketing literature; (b) expose how each perspective entails a specific organization of provisioning activities; and (c) foreground the role of alternative economic practices beyond the growth paradigm. We conclude that socially sustainable degrowth is the missing voice within macromarketing debates that lie central to elucidating the future direction of alternative economic practices.
Optimizing an Approximation of ROUGE - a Problem-Reduction Approach to Extractive Multi-Document Summarization

This paper presents a problem-reduction approach to extractive multi-document summarization: we propose a reduction to the problem of scoring individual sentences with their ROUGE scores based on supervised learning. For the summarization, we solve an optimization problem where the ROUGE score of the selected summary sentences is maximized. To this end, we derive an approximation of the ROUGE-N score of a set of sentences, and define a principled discrete optimization problem for sentence selection. Mathematical and empirical evidence suggests that the sentence selection step is solved almost exactly, thus reducing the problem to the sentence scoring task. We perform a detailed experimental evaluation on two DUC datasets to demonstrate the validity of our approach.
Semiparametric Bayesian Analysis of Selection Models

Selection models are appropriate when a datum x enters the sample only with probability or weight w(x). It is typically assumed that the weight function w is monotone, but the precise functional form of the weight function is often unknown. In this article, the Dirichlet process prior, centered on a parametric form, is used as a prior distribution on the weight function. This allows for incorporation of knowledge about the weight function, without restricting it to be of some particular functional form. By introducing latent variables related to the selection mechanism, computation via Gibbs sampling can be implemented in the case where the total number of selected and unselected observations, N, is known. When N is unknown, a reversible jump Markov chain sampler is needed to carry out the computations. An important difficulty that can be thought of as “practical nonidentifiability” is revealed, even for selection models in which the weight functions are theoretically identifiable. The proposed solution to this problem depends on the existence of prior knowledge concerning the effective range of the weight function.
Automatic Detection of Beta-barrel from Medium Resolution Cryo-EM Density Maps

Cryo-electron microscopy (Cryo-EM) has become central to the study of large-scale molecular interactions and has produced three-dimensional (3D) density maps at various resolutions. Secondary structure element (SSE) identification from volumetric protein density maps is critical for de novo backbone structure derivation in cryo-EM. Multiple methods have been developed to detect helix and β-sheet from density maps at medium resolutions (~5-10Å). β-barrel as a special β-sheet structure has been found in many proteins. However, currently there are no methods aimed to automatically and accurately extract the β-barrel as a complete chunk of density from cryo-EM map of β-barrel protein. We present an effective approach, BarrelMiner, to automatically extract the β-barrel region from cryo-EM density maps based on the conspicuous cylindrical shape of β-barrel. BarrelMiner has been tested using ten simulated density maps at 10Å resolution and seven experimental cryo-EM maps between 5. 5Å and 8. 25Å resolution. The result suggests that BarrelMiner can be used for the detection of β-barrel from medium resolution cryo-EM density maps of β-barrel proteins.