Miracle-dz/UniFAR-FTUs huggingface dataset:
Episodic Memory in a Cognitive Model

The ability to remember events plays an important role in human life. People can replay past events in their heads and often make decisions based on the retrieved information. In this paper, we describe a novel extension to a cognitive architecture, ICARUS, that enables it to store, organize, generalize, and retrieve episodic cases that can help the agent in a variety of manners. After briefly discussing previous work on the related topic, we explain the new extension to the architecture. Then we discuss three architectural implications of the new capability and list some future work before we conclude.
Author Verification Using Common N-Gram Profiles of Text Documents

Authorship verification is the problem of answering the question whether or not a sample text document was written by a specific person, given a few other documents known to be authored by them. We propose a proximity based method for one-class classification that applies the Common N-Gram (CNG) dissimilarity measure. The CNG dissimilarity (Keet al., 2003) is based on the differences in the frequencies of n-grams of tokens (characters, words) that are most common in the considered documents. Our method utilizes the pairs of most dissimilar documents among documents of known authorship. We evaluate various variants of the method in the setting of a single classifier or an ensemble of classifiers, on a multilingual authorship verification corpus of the PAN 2013 Author Identification evaluation framework. Our method yields competitive results when compared to the results achieved by the participants of the PAN 2013 competition on the entire set, as well as separately on two subsets — English and Spanish ones — out of the three language subsets of the corpus.
Lessons Learned about Coaching from Reading First in Georgia.

Reading First, the largest and most ambitious beginning reading initiative funded by the United States Department of Education, is entering its sixth and final year in Georgia. I currently serve as a coordinator for the project as well as serve as a Regional Consultant to six schools near my home in South Georgia. I am one of fourteen consultants who are responsible for supporting as many as ten schools. In my role with the schools, I visit each one at least one time a month, meet with coaches and administrators, visit classrooms, provide support, and monitor progress. This part of my job has been a joy because of the close personal relationships that it has allowed me to form as I work together with others to create the best possible situation for the teachers and students in their schools.
Predicting Memory Activity Using Spatial Correlation Doctor of Philosophy

The memory wall continues to pose a performance bottleneck for computer systems—studies show that modern servers spend up to two-thirds of execution time stalled on memory accesses. Although recent trends forecast growth in processor clock frequencies to be minimal, improvements to memory access latencies are correspondingly slow. Traditional approaches, such as large on-chip caches, hardware multithreading, and out-of-order processing, demonstrate some success at mitigating the impact of high memory latencies, but offer little hope of completely overcoming the memory wall. Prefetching/streaming techniques have been proposed for predicting and eliminating misses in desktop, scientific, and engineering applications, but are less effective across commercial workloads, which exhibit data dependent and irregular memory behaviors. Though complex, commercial server applications nevertheless organize their data in a structured manner and at large granularity. In this thesis, we explore spatial correlation of access patterns that span page-sized regions of memory. We develop mechanisms for accurately observing and predicting repetitive spatial layouts, which lead us to propose Spatial Memory Streaming (SMS), a hardware prefetcher that exploits spatial correlation to predict cache misses in server workloads. Although SMS is practical and effective, it loses significant opportunity for performance improvement because it predicts spatial layouts in isolation. To overcome this fundamental limitation, we adapt temporal correlation to predict order across spatial layouts. We exploit the repetitive temporal characteristics of spatial accesses in Spatio-Temporal Memory Streaming (STeMS), a hardware prefetching technique that combines spatial and temporal predictions into a single total predicted miss sequence. Across our suite of commercial workloads, we demonstrate that STeMS achieves equal or better prediction coverage and application speedup than either temporal or spatial memory streaming alone.
Investigation of galactic alignment in Local Supercluster galaxy clusters

We investigate the orientations of the galactic axes within 18 selected clusters, substructures of the Local Supercluster. For every cluster we map the parameter Δ11 describing the alignment of the galactic axes with respect to a chosen cluster pole, divided by its formal error σ (Δ11) [s ≡Δ11 / σ (Δ11)]. The cluster pole coordinates change along the entire celestial sphere. The resulting maps are analysed for correlations of their maxima with directions from the cluster centre to (i) the derived `physical' cluster poles, (ii) the Local Supercluster centre, (iii) the Virgo A centre and (iv) the Earth, i.e. along the line of sight (≡ LOS). The strong maxima -- with one exception -- exist only for non-spiral (NS) subsamples, with the maximum well correlated with the LOS direction. Another of the studied directions may occur close to the maximum only if these directions are close to the LOS and they do not correlate with other features visible on the maps. For clusters with a clearly defined maximum of s below 3.0 the conclusion generally does not change. For the spiral (S) subsamples the maps are usually at the random noise level. In these cases a weaker, but still existing correlation with the LOS is observed and no other evident correlations are noted. We conclude that a strong systematic effect, generated by the process of deprojection of a galactic axis from its optical image, is present in the catalogue data. It can mask any weak alignment existing in the analysed clusters. With the use of a simple model for the systematic effect we are able to reproduce the main characteristic features of the maps for non-spiral galaxies. We note, however, that a few clusters show significant differences with respect to this model.
Efficient Non-domination Level Update Approach for Steady-State Evolutionary Multiobjective Optimization

Non-dominated sorting, dividing the population into several non-domination levels, is a basic step for many Pareto-based evolutionary multiobjective optimization (EMO) algorithms. Different from the generational scheme, where the selection of next parents is conducted after the generation of a population of offspring, the steady-state scheme updates the parent population whenever a new candidate solution is reproduced. As a consequence, non-dominated sorting can be a computationally expensive part in steady-state EMO algorithm when the population size or number of objectives becomes large. In fact, before introducing a new candidate solution, the non-domination level structure of the parent population is already known from the last environmental selection. Thus, conducting non-dominated sorting from scratch, each time, obviously does not take advantages of the existing knowledge and results in a severe waste of computational resources. In view of this, we propose an efficient non-domination level update (ENLU) mechanism for steady-state EMO algorithm. By extracting the knowledge of the non-domination level structure of the parent population, ENLU mechanism only updates the nondomination levels of necessary solutions during the update procedure, including the addition of a new candidate solution into the parent popualtion and the elimination of an inferior solution. Theoretical analysis show the time complexity of ENLU mechanism is O(mN √ N) in the worst-case and O(m) in the best case. Extensive experiments empirically demonstrate that ENLU mechanism is more computationally efficient than the fast non-dominated sorting procedure, as it saves 103 to 104 magnitude of unnecessary dominance comparisons.
Suboptimal Paths in the Problem of a Planar Motion With Bounded Derivative of the Curvature

We consider the planar motion of a car-like robot with a bounded derivative of the curvature, with given initial and final configuration (i.e. positions, tangent angles and curvatures). The tangent angle and the curvature of the path are assumed to be continuous. When the distance between the initial and the final point is much greater than the initial and final curvatures and the curvature's derivative, we show how to construct a suboptimal path (the cost is the path length). We admit a finite number of cusps in the path.
Evolution by reticulation: European dogroses originated by multiple hybridization across the genus rosa.

The European dogroses (Rosa sect. Caninae (DC.) Ser. ) are characterized by a unique meiosis system ("canina-meiosis"), which controls the heterogamous development of tetraploid egg cells and haploid pollen grains resulting in a pentaploid somatic status. This permanent anorthoploidy is supposed to have originated by a hybridization event in the postglacial period. In this study we present molecular evidence by an analysis of nuclear ribosomal DNA data that dogroses are complex allopolyploids resulting from multiple hybridization events. As previously described, the nrITS-1 region does not undergo concerted evolution in dogroses. Thus, different ITS-1 sequences persist within single individuals. Secondary structure predictions do not point to the existence of pseudogenes within these ITS-1 types. Our data suggest that the pentaploid Caninae genome originated from different members of nondogroses and the now extinct Protocaninae.
Direct Observation of α-Synuclein Amyloid Aggregates in Endocytic Vesicles of Neuroblastoma Cells

Aggregation of α-synuclein has been linked to both familial and sporadic Parkinson’s disease. Recent studies suggest that α-synuclein aggregates may spread from cell to cell and raise questions about the propagation of neurodegeneration. While continuous progress has been made characterizing α-synuclein aggregates in vitro, there is a lack of information regarding the structure of these species inside the cells. Here, we use confocal fluorescence microscopy in combination with direct stochastic optical reconstruction microscopy, dSTORM, to investigate α-synuclein uptake when added exogenously to SH-SY5Y neuroblastoma cells, and to probe in situ morphological features of α-synuclein aggregates with near nanometer resolution. We demonstrate that using dSTORM, it is possible to follow noninvasively the uptake of extracellularly added α-synuclein aggregates by the cells. Once the aggregates are internalized, they move through the endosomal pathway and accumulate in lysosomes to be degraded. Our dSTORM data show that α-synuclein aggregates remain assembled after internalization and they are shortened as they move through the endosomal pathway. No further aggregation was observed inside the lysosomes as speculated in the literature, nor in the cytoplasm of the cells. Our study thus highlights the super-resolution capability of dSTORM to follow directly the endocytotic uptake of extracellularly added amyloid aggregates and to probe the morphology of in situ protein aggregates even when they accumulate in small vesicular compartments.
Path planning of free-flying space robot based on artificial bee colony algorithm

The artificial bee colony algorithm is a novel simulated evolutionary algorithm. The artificial bee colony algorithm has distributed computation, positive feedback and a constructive greedy heuristic convergence. Obstacle avoidance path planning of free-flying space robot is realized by the use of artificial bee colony algorithm. The artificial bee colony algorithm is a class of population based bionic algorithm, which provides new methods for complex combinatorial optimization problems. The artificial bee colony algorithm is improved appropriately so that it is applicable to path planning of free-flying space robot. Then, the algorithm is implemented with computer simulation and preferable results are obtained.
Analyzing the structure of parent-moderated narratives from children with ASD using an entity-based approach

Storytelling is a commonly used technique for rating linguistic and communicative abilities of children with Autism Spectrum Disorders (ASD). It highlights their language use beyond sentence-level production, and their ability to cohesively link events into a plot, including incorporating social context. A key scenario of interest we consider is spoken narrative creation in interactive settings, where confederates such as parents can offer scaffolding to their children’s narratives by eliciting answers with appropriate questions, shaping the structure of the resulting narrative. We analyze the structure of children’s stories narrated with the help of their parents using entity-based feature-level patterns in order to see how there are influenced by the parents’ narrative elicitation techniques. The frequency distribution and evolution of entities -meaning the co-referent people, objects and ideas- can capture the main axis of the story plot. Our results indicate that the type of questions the parents ask can be reflected in the entity-based features of a narrative, affecting its underlying structure and coherence. Index Terms: Narrative Structure, Coherence, Text Entities, Autism Spectrum Disorders
AUGMENTED LEARNING: AN E-LEARNING ENVIRONMENT IN AUGMENTED REALITY FOR OLDER ADULTS

Studies on topics such as active ageing or health and wellbeing show that older adults want to remain healthy and active as they age. Nowadays, new technologies guarantee older adults longer and healthier lives, but do not really facilitate more social aspects of their lives. In a world where social relationships, public and private activities, or entertainment are based on the use of technology, older adults lacking technological knowledge risk social isolation. They will find it progressively more difficult to use all the public and private e-services necessary to maintain an active and socially integrated life. The goal of our research is to help older adults to cope with their technological illiteracy. In this paper we present our work on an innovative learning environment specifically tailored for older adults, easily accessible without any previous knowledge of technology, and capable of delivering educational material on technology and, particularly, on e-services. We use the technology available in the field of augmented reality, so that the learning environment an immersive, 3-D and fully interactive environment, capable of providing older adults with the knowledge on ICTs and ICT tools they need to become active and integrated citizens of our technological society.
Macrotasking the singluar value decomposition of block circulant matrices on the Cray-2

A parallel algorithm to compute the singular value decomposition (SVD) of block circulant matrices on the Cray-2 is described. For a block circulant form described by M blocks with m x n elements in each block, the computation time using an SVD algorithm for general matrices has a lower bound (M3min(m, n)mn). Using a combination of fast Fourier transform (FFT) and SVD steps, the computation time for block circulant singular value decomposition (BCSVD) has a lower bound (Mmin(m, n)mn); a relative savings of ~ M2. Memory usage bounds are reduced from (M2mn) to (Mmn); a relative savings of ~ M. For M = m = n = 64, this decreases the computation time from approximately 12 hours to 30 seconds and memory usage is reduced from 768 megabytes to 12 megabytes. The BCSVD algorithm partitions well into n macrotasks with a granularity of (mM log M) for the FFT portion of the algorithm. The SVD portion of the algorithm partitions into M macrotasks with a granularity of (min(m, n)mn). Again, for the case where M = m = n = 64, the FFT granularity is 29ms and the SVD granularity is 428ms. A speedup of 3.06 was achieved by using a prescheduled partitioning of tasks. The process creation overhead was 2.63ms. Using a more elaborate self-scheduling method with four synchronizing server processes, a speedup of 3.25 was observed with four processors available. The server synchronization overhead was 0.32ms. Relative memory overhead in both cases was about 4% for data space and 40% for code space.
Synopsis of Rational Approaches to Learning and Development

In this dissertation, I study decision-making mechanisms in young children and non-human primates across multiple domains—including visual attention and overt choice—in order to discover the efficacy and limitations of rational cognitive theories. Rational cognitive theories posit that intelligent organisms should choose actions that maximize utility (e. Effective utility maximization requires an agent to generate accurate expectations about what will happen in the future—which, in turn, requires the agent to mentally model the world. Adults have a substantial amount of world experience upon which they can base such models. Very young children, however, have far less world experience, and thus—at least initially— possess no such advantage. They must sample observations from their environments in order to overcome their naïveté concerning the structure of those environments. They gradually infer complex representations and form abstract theories about the world through the sampling process. Sample by sample, they continuously build upon, update, and revise their theories. My dissertation investigates young children's choice behavior throughout development in order to understand the decision-making mechanisms that guide knowledge acquisition. The included studies test the efficacy and limitations of rational cognitive theories in order to better understand the decision-making mechanisms that guide early learning and behavior in children and monkeys. The studies span across multiple domains—including visual attention and overt choice. The results provide empirical evidence that learners rely on utility maximization both to build complex models of the world starting from very little knowledge and, more generally, to guide their decisions and behavior. Five experiments were conducted on infants, young children, and monkeys using visual and auditory stimuli presented in sequences of events. These experiments show that children are capable of rational decisions that optimize future utility and exhibit a U-shaped relationship between stimulus complexity and attention. Similarly, monkeys' attentional patterns are also guided by stimulus complexity. The dissertation opens by applying a rational cognitive approach to perhaps the most classic example of seemingly irrational behavior in young children—their poor track record in delay-of-gratification tasks, such as in the Stanford Marshmallow experiments (e.g., Mischel & Ebbesen, 1970). Though children apparently fail to maximize utility in such delay-of-gratification tasks, the cause of these apparent failures was not well understood (Chapter 2, " Rational Snacking: Young children's decision-making on the marshmallow task is moderated byyear-olds choose an immediately available low-value reward (e.g., one marshmallow) over one of high-value (e.g., two marshmallows) after a temporal delay (Mischel & Ebbesen, 1970). …
Global cross-over dynamics of single semiflexible polymers

We present a mean-field dynamical theory for single semiflexible polymers which can precisely capture, without fitting parameters, recent fluorescence correlation spectroscopy results on single-monomer kinetics of DNA strands in solution. Our approach works globally, covering three decades of strand length and five decades of time: it includes the complex cross-overs occurring between stiffness-dominated and flexible bending modes, along with larger-scale rotational and center-of-mass motion. The accuracy of the theory stems in part from long-range hydrodynamic coupling between the monomers, which makes a mean-field description more realistic. Its validity extends even to short, stiff fragments, where we also test the theory through Brownian hydrodynamics simulations.
Automatic slope streak detection on Mars

An algorithm to detect slope streaks on Mars is presented in this paper. It is mainly based on morphological operators and consists of three steps: `pre-processing' with connected operators to filter small structures and shadows, `detection' with top-hat, Otsu binarisation and thinning/pruning-reconstruction operations and by a `post-processing' to remove non-elongated objects. The algorithm is successfully tested on very high resolution images (0.25-6.5 m/pixel) of HiRISE and MOC cameras on different locations of Mars.
From Boolean Network Model to Continuous Model Helps in Design of Functional Circuits

Computational circuit design with desired functions in a living cell is a challenging task in synthetic biology. To achieve this task, numerous methods that either focus on small scale networks or use evolutionary algorithms have been developed. Here, we propose a two-step approach to facilitate the design of functional circuits. In the first step, the search space of possible topologies for target functions is reduced by reverse engineering using a Boolean network model. In the second step, continuous simulation is applied to evaluate the performance of these topologies. We demonstrate the usefulness of this method by designing an example biological function: the SOS response of E. coli. Our numerical results show that the desired function can be faithfully reproduced by candidate networks with different parameters and initial conditions. Possible circuits are ranked according to their robustness against perturbations in parameter and gene expressions. The biological network is among the candidate networks, yet novel designs can be generated. Our method provides a scalable way to design robust circuits that can achieve complex functions, and makes it possible to uncover design principles of biological networks.
The state of the art in locally distributed Web-server systems

The overall increase in traffic on the World Wide Web is augmenting user-perceived response times from popular Web sites, especially in conjunction with special events. System platforms that do not replicate information content cannot provide the needed scalability to handle large traffic volumes and to match rapid and dramatic changes in the number of clients. The need to improve the performance of Web-based services has produced a variety of novel content delivery architectures. This article will focus on Web system architectures that consist of multiple server nodes distributed on a local area, with one or more mechanisms to spread client requests among the nodes. After years of continual proposals of new system solutions, routing mechanisms, and policies (the first dated back to 1994 when the NCSA Web site had to face the first million of requests per day), many problems concerning multiple server architectures for Web sites have been solved. Other issues remain to be addressed, especially at the network application layer, but the main techniques and methodologies for building scalable Web content delivery architectures placed in a single location are settled now. This article classifies and describes main mechanisms to split the traffic load among the server nodes, discussing both the alternative architectures and the load sharing policies. To this purpose, it focuses on architectures, internal routing mechanisms, and dispatching request algorithms for designing and implementing scalable Web-server systems under the control of one content provider. It identifies also some of the open research issues associated with the use of distributed systems for highly accessed Web sites.