Miracle-dz/UniFAR-FTUs huggingface dataset:
Coverage Path Planning and Room Segmentation in Indoor Environments using the Constriction Decomposition Method

The task of complete coverage path planning in complex 2D environments is a classic NPHard problem that has been an active research topic for well over 30 years. A common approach to solving coverage problem in such environments is to partition, or segment, the target environment into a set of cells that have some property that allows any given cell to be covered in an optimal or near optimal manner. If each cell of an environment is visited and covered by some agent, then the entire environment is said to be covered. This work proposes a novel segmentation method, called the Constriction Decomposition Method (CDM), that works by locating constriction points in indoor, 2D environment and then partitioning the environment based on the constriction points. When the CDM is applied to 2D maps of office or laboratory environments, the CDM produces a segmentation that closely resembles a room based decomposition. Once the environment has been decomposed into regions, this work demonstrates that each room can be covered using a simple coverage path planning algorithm that exploits the fact that the resulting cells do not contain any constriction points. The lack of constriction points in each region means that each region, or room, can be completely covered using a series of contour following paths followed by a series of back and forth motions. Once a set of coverage paths are produced for each cell, a tour between all path is found using a heuristic Traveling Salesman Problem (TSP) solver. The proposed segmentation and coverage path planning methods are tested on a set of 15 indoor environments that are derived from a set of floor plans corresponding to five office and seven laboratory environments. The quality of the segmentation produced by the CDM is directly compared to existing methods on a qualitative and quantitative basis using a series of metrics proposed by other authors. The set of coverage paths for each environment are compared to existing work based on the ratio between the total path length and the ratio between the inter-sector path and the total coverage path length. Based on these metrics it is demonstrated that the CDM and the CDM coverage path planner produces both superior segmentations and coverage plans in 2D indoor environments.
How sensory ecology affects the utility of planning

Prior to the vertebrate invasion of land, aquatic vision provided short range sensing with low contrast scenes. Once on land, aerial vision provided a 100-fold increase in range with high contrast scenes. This change in sensory ecology due to emergence onto land may have provided a selective advantage to those animals that were able to imagine alternative action sequences toward distant goals. To explore the relationship between sensory ecology and the utility of planning, we developed a simulation of predator-prey dynamics where we controlled visual range, planning depth, and environmental complexity. Simulations show that for prey with short visual range, increased planning results in a negligible change in survival rate with increased environmental complexity. However, at longer visual ranges, survival rate is strongly correlated with planning depth and environmental complexity, with peak survival rate occurring at high complexity and planning depth. These data suggest that planning is an adaptation to long range sensing enabled by terrestrial habitats 385 million years ago. Our results point to future research into the limitations on our temporal and spatial range of prospective cognition, a possible result of environments in which we have evolved, to raise awareness and create circumventions for looming existential threats.
FASTER: An Embedded Concurrent Key-Value Store for State Management

Over the last decade, there has been a tremendous growth in data-intensive applications and services in the cloud. Data is created on a variety of edge sources such as devices, and is processed by cloud applications to gain insights or make decisions. These applications are typically update intensive and involve a large amount of state beyond what can fit in main memory. However, they display significant temporal locality in their access pattern. We demonstrate F aster , a new key-value store that combines a latch-free concurrent hash index with a hybrid log : a concurrent log-structured record store that spans main memory and storage, while supporting fast in-place updates in memory. F aster achieves up to orders-of-magnitude better throughput than systems deployed widely today. It is built as an embedded high-level language component using dynamic code generation, and can work with any storage back-end such as local SSD or cloud storage. Our demonstration focuses on: (1) the ease with which cloud applications and state stores can deeply integrate state management into their high-level language logic at low overhead; and (2) the innovative system design and the resulting high performance, adaptability to varying memory capacities, durability, and natural caching properties of our system.
Hierarchical Incident Clustering for Security Operation Centers

In security operation centers (SOCs) of large organizations, triaging and remediating security incidents is a tedious and error-prone job. Incidents are generated by correlating security-related events that may indicate attack (e.g., unblocked end-point alerts on the same machine). In many cases, several incidents consist mainly of the same sets of events, and they can be traced back to the same root cause. Rather than requiring analysts to triage incidents individually or scan incident lists one by one to identify related incidents, in our demo we provide hierarchical clustering of incidents so that analysts can quickly identify all similar incidents and perform joint remediation actions. The hierarchical aspect of the clustering algo-rithm enables analysts to navigate a cluster tree, allowing them to find the right granularity at which incidents should be grouped so that a single remediation action can dispatch the largest possible number of related incidents. Our user interface simultaneously provides insight into the nature of attacks on an organization, and is also an efficient mechanism to automate response. This is a demo paper. Our demo can be viewed at https://vimeo.com/250453752 with password svp3267b . Should this paper be accepted we will make the demo video public.
Detection , correction and minimization of segmentation errors in volumetric medical images

Fuzzy boundaries of anatomical structures in medical images make segmentation a challenging task. We present a new segmentation method that addresses the fuzzy boundaries problem. Our method maps the lengths of 3D rays cast from a seed point to the unit sphere, estimates the fuzzy boundaries location by thresholding the gradient magnitude of the rays lengths, and derives the true boundaries by Laplacian interpolation on the sphere. Its advantages are that it does not require a global shape prior or curvature based constraints, that it has an automatic stopping criteria, and that it is robust to anatomical variability, noise, and parameters values settings. Our experimental evaluation on 23 segmentations of kidneys and on 16 segmentations of abdominal aortic aneurysms (AAA) from CT scans yielded an average volume overlap error of 12.6% with respect to the ground-truth. These results are comparable to those of other segmentation methods without their underlying assumptions.
Morphology and molecular phylogeny of Phaeostrophion irregulare ( Phaeophyceae ) with a proposal for Phaeostrophiaceae fam . nov . , and a review of

Phaeostrophion irregulare, which is distributed along the Pacific coast of northwestern America, has been placed in the family Punctariaceae, order Dictyosiphonales (or Ectocarpales sensu lato), because of anatomical resemblances. On the basis of a previous culture study, the species was assumed to have a direct type of life history, with erect thalli forming unilocular or plurilocular zooidangia. However, the occurrence of a perennial prostrate system (holdfast), the presence of marginal meristematic cells on the holdfast and the lack of pyrenoids in chloroplasts suggest that this taxonomic assignment is questionable. Transmission electron microscopy observation confirmed the absence of pyrenoids in the chloroplasts. Molecular phylogenetic studies using rbcL (chloroplast) and partial 18S and 26S ribosomal RNA (nuclear) gene sequences revealed that Phaeostrophion is not included in the clade of Ectocarpales s.l. , but forms a clade with Sphacelariales which diverged relatively early in the evolution of Phaeophyceae and shares an apical or marginal meristematic manner of growth with them. Members of Ishigeaceae were also shown to have a distant phylogenetic relationship with Chordariales (or Ectocarpales s.l.) and diverged early in the phaeophycean lineage. We propose a new family Phaeostrophiaceae to accommodate Phaeostrophion, although we suspend taxonomic treatment at the ordinal level.
Real-time Prediction of User Performance based on Pupillary Assessment via Eye Tracking

We propose a method to predict user performance based on eye-tracking. The method uses eye-tracking-based pupillometry to capture pupil diameter data and calculates—based on a Random Forest algorithm—user performance expectations. We conducted a large-scale experimental evaluation (125 participants aged from 21 to 61 years) and found promising results that pave the way for a dynamic real-time adaption of IT to a user’s mental effort and expected user performance. We have already achieved a good classification accuracy of user performance after only 40 seconds (5% of the mean total trial time that our participants took to complete our experiment). The non-invasive contact-free method can be applied cost-efficiently both in research and practical environments.
742 CISST ’ 02 International Conference PREPROCESSING FOR SKELETON-BASED FINGERPRINT MINUTIAE EXTRACTION

In this paper, we propose to use the fingerprint valley instead of ridge for the binarization-thinning process to extract fingerprint minutiae. We first use several preprocessing steps on the binary image in order to eliminate the spurious lakes and dots, and to reduce the spurious islands, bridges, and spurs in the skeleton image. Finally, by removing all the bug pixels introduced at the thinning stage, our algorithm can detect a maximum number of minutiae from the fingerprint skeleton using the Rutovitz Crossing Number.
COMPARISON OF HUMANS AND ROBOTS EMOTION EVALUATION PERCEPTION BASED ON HUMAN SOUND

In human-to-human interaction emotion perception is the perception on the emotion of the other people, which, due to the nature of emotions is not so precise. On the other hand, perception on emotions in human-computer interaction is still an open problem. A lot of work is done in direction of finding suitable model for perceiving emotions based on different input signals and classification models. Here, only sound signals are considered. Emotion perception is being used in human-robot interaction among others. Robots are machines that can partially act like humans, and today some robots can even perceive emotions. Here a custom build emotion aware robot that perceives emotion evaluation is used to investigate the similarity and differences of the robot's perception with human's perception. This paper presents a discussion about the future of robots that can perceive human emotions and their usage.
HYDRA: A Dynamic Big Data Regenerator

A core requirement of database engine testing is the ability to create synthetic versions of the customer's data warehouse at the vendor site. Prior work on synthetic data regeneration suffers from critical limitations with regard to (a) scaling to large data volumes, (b) handling complex query workloads, and (c) producing data on demand. In this demo, we present HYDRA , a workload-dependent dynamic data regenerator, that materially addresses these limitations. It introduces the concept of dynamic regeneration by constructing a minuscule memory-resident database summary that can on-the-fly regenerate databases of arbitrary size during query execution. Further, since the data is generated in memory, the velocity of generation can be closely regulated. Finally, to complement dynamic regeneration, Hydra also ensures that the process of summary construction is data-scale-free.
How does the robot feel ? Annotation of emotional expressions generated by a humanoid robot with affective quantifiers

Human-robot interaction could be greatly enhanced if we understand and improve the reliability and impact of robot emotional expressions. Using a pre-designed set of robot animations as our starting point, we seek to increase its usability by annotating it with valence and arousal quantifiers. An initial experiment is described that aims to provide such an annotation by evaluating the quality and consistency of human emotional interpretation of the robot animations.
No-Reference Image Quality Assessment Based on SIFT Feature Points

Image quality assessment is an important research field of image application. A no-reference image assessment method is proposed based on SIFT feature points and the collection of statistical features from a space domain Natural Scene Statistic (NSS) model. The proposed method extracts feature points by the SIFT method, and the feature regions are extracted by K means clustering algorithm. Then features are computed in the feature regions which can reflect the image quality. The quality of the distorted image is expressed as the distance between the quality aware NSS feature model and the MVG fit to the features extracted from the distorted image. The experimental results show that the proposed method is consistent with human subjective perception Keywords-SIFT; feature points; K means clustering algorithm; feature regions;no reference; objective assessment; image quality
Compositional Morpheme Embeddings with Affixes as Functions and Stems as Arguments

This work introduces a novel, linguistically motivated architecture for composing morphemes to derive word embeddings. The principal novelty in the work is to treat stems as vectors and affixes as functions over vectors. In this way, our model’s architecture more closely resembles the compositionality of morphemes in natural language. Such a model stands in opposition to models which treat morphemes uniformly, making no distinction between stem and affix. We run this new architecture on a dependency parsing task in Korean—a language rich in derivational morphology—and compare it against a lexical baseline,along with other sub-word architectures. StAffNet, the name of our architecture, shows competitive performance with the state-of-the-art on this task.
Effect of Blending Doum (Hyphaene thebaica) Powder with Wheat Flour on the Nutritional Value and Quality of Cake

Pastry is an essential part of food stuff people like, especially preferring those made of wheat flour: cakes, biscuits, pancakes, etc. The nutritive value of the products mentioned above is not high. Therefore, there is a need to increase it by adding something like doum fruit (Hyphaene thebaica L.), which is a widespread in Upper Egypt. Doum fruit is a rich source of fibers and antioxidants, also other valuable substances such as carbohydrates and minerals especially potassium (K for people suffering from blood pressure problems). This investigation was carried out to study the possibility of utilization doum fruit powder in cake production. Five levels of wheat flour substitution were used 0%, 5%, 10%, 15% and 20% to produce cake. Also, the effects of blends on farinograph parameters were studied. Results indicated that substitution of doum powder (D.P) led to increase the water absorption (%) and dough weakening (B.U), whereas dough stability (min) was decreased. The water holding capacity of blends increased with increasing the level of substitution. The chemical, physical and sensory characteristics of the prepared cakes were studied. Results showed that increasing the levels of substitution increased the total fat, crude fiber and ash contents in produced cake compared with control. Minerals of the produced cake showed an increment in K and Mg, while slightly increment in Ca, Fe and Zn with increasing the level of substitution. Total phenol and antioxidant activity (AO) increased in substituted cake. Physical attributes of the produced cakes were evaluated and results showed that volume of substituted cakes decreased with increasing the level of replacement except for 10% level it increased. Results of textural analysis showed that D.P fiber decreased all the parameters. Concerning cake color, as the percentage of D.P increased, the color of the cake became darker and had high a and b values. The sensory evaluation results showed an insignificantly decrease in the acceptability by increasing the doum powder substitution comparing with control.
Experimental and theoretical investigation of nucleation from wall-bounded nuclei in a laminar flow

April 10-15, 2016 Abstract Even though theories and models on free nuclei and wall-bounded nuclei are part of cavitation standard literature, the process of nucleation from wall-bounded nucleation sites has hardly been explored. In this work we present new experimental results and give new insights into the physics of nucleation. High-speed visualizations show that nucleation from wall-bounded nuclei is a self excited cyclic process, triggered by the bubble detachment. The detachment itself is a consequence of a Plateau-Rayleigh instability and thus strongly depends on the geometry of the nuclei. Measurements of the nucleation rate show that frequencies of up to 1000Hz are easily achievable. The size of the detaching bubbles is in the order of magnitude of 0.01 to 1mm.
Multi-glance Reading Model for Text Understanding

In recent years, a variety of recurrent neural networks have been proposed, e.g LSTM. However, existing models only read the text once, it cannot describe the situation of repeated reading in reading comprehension. In fact, when reading or analyzing a text, we may read the text several times rather than once if we couldn’t well understand it. So, how to model this kind of the reading behavior? To address the issue, we propose a multi-glance mechanism (MGM) for modeling the habit of reading behavior. In the proposed framework, the actual reading process can be fully simulated, and then the obtained information can be consistent with the task. Based on the multi-glance mechanism, we design two types of recurrent neural network models for repeated reading: Glance Cell Model (GCM) and Glance Gate Model (GGM). Visualization analysis of the GCM and the GGM demonstrates the effectiveness of multi-glance mechanisms. Experiments results on the large-scale datasets show that the proposed methods can achieve better performance.
Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation

The author used ATLAS.ti to conduct a systematic review of the literature on leadership competencies in fields undergoing rapid change to complete his dissertation. Studies were imported to ATLAS.ti for first, second and third stage analysis which led to the creation of final themes and concepts. The use of ATLAS.ti for coding encouraged a cyclical and iterative approach to data analysis that would have been difficult to accomplish through note cards, word processing, or spreadsheet applications. ATLAS.ti assisted with using meta-ethnography as the means of synthesizing both qualitative and quantitative research. ATLAS.ti provided the ability to make chains of multiple codes and linking of quotations to create networks, which was vital to third stage coding. These network diagrams were qualitative visual representations of the data and greatly assisted with third stage coding. Concepts, themes, and patterns emerged from the network diagrams. Also useful at this stage for identifying patterns in the data was mapping of co-occurring codes. ATLAS.ti allows co-occurring codes to be retrieved and visualized through network and mapping tools. Finally, ATLAS.ti was used to create hyperlinked maps of quotations which assisted with the analysis of proposition three of this dissertation.
Noise allocation for industrial plant acoustic design

Due to industrial plant customer's awareness and legislator's attention about aspects connected with environmental noise, engineering companies developing new settlements are often required to accurately design sound reduction measures from the time when the project development begins, or even before, during its proposal. The outdated method to deal with industrial plant noise control during the equipment procurement or, worst, during construction, by means of retrofitting, is going to be left as it leads to poor acoustic performance and high costs. Besides, especially for plant engineering purposes from the authorization point of view, the environmental noise limitations to be respected is also set in terms of maximum allowed sound power level. This vision represents the state of art approach to industrial plants design; it requires the plant constructor to supply low noise equipment and noise reduction systems at source in order to comply with the goal. Presently noise predictions using sound pressure levels are more prevalent in industry than those provided by means of the more flexible to use sound power levels, due to lack of manufacturers data and because plant customers and equipment suppliers usually deal with pressure levels, easier to measure.
Literatura y práctica: una revisión crítica acerca de los MOOC Literature and Practice: A Critical Review of MOOCs

This article focuses on a review of both literature and practical experiences concerning MOOCs. The literature analyzed was published in peer-reviewed journals between 2007 and 2013. 268 items were selected for this study, of which 100 were analyzed in detail. The issues raised by this analysis were used as the criteria for the analysis of 10 current empirical MOOC experiences. The literature study highlighted the rapid growth in interest in understanding MOOCs and seeking to understand the pedagogic frameworks most relevant to their adoption and the importance of the concept of openness embodied within them. More recently a new emphasis has been emerging where institutional factors, particularly those concerned with financial viability, certification and retention have been highlighted. The analysis of current practice showed that many of the concerns in the academic literature were absent from not only the practices embodied in current MOOC-based learning experiences but seem to have been ignored in the conceptual phase of implementing a MOOC-based teaching model. In practice therefore, most of the current MOOC offer is only a pale reflection of the conceptualization that gave them rise and has been shown to be significant in the literature. In particular the true essence encapsulated in the concept described as Openness has been largely lost in practice.