Escherization with Large Deformations Based on As-Rigid-As-Possible Shape Modeling

Escher tiling is well known as a tiling that consists of one or a few recognizable figures, such as animals. The Escherization problem involves finding the most similar shape to a given goal figure that can tile the plane. However, it is easy to imagine that there is no similar tile shape for complex goal shapes. This article devises a method for finding a satisfactory tile shape in such a situation. To obtain a satisfactory tile shape, the tile shape is generated by deforming the goal shape to a considerable extent while retaining the characteristics of the original shape. To achieve this, both goal and tile shapes are represented as triangular meshes to consider not only the contours but also the internal similarity of the shapes. To measure the naturalness of the deformation, energy functions based on traditional as-rigid-as-possible shape modeling are incorporated into a recently developed framework of the exhaustive search of the templates for the Escherization problem. The developed algorithms find satisfactory tile shapes with natural deformations for fairly complex goal shapes.

Alternation emerges as a multi-modal strategy for turbulent odor navigation

Foraging mammals exhibit a familiar yet poorly characterized phenomenon, "alternation", a momentary pause to sniff in the air often preceded by the animal rearing on its hind legs or raising its head. Intriguingly, rodents executing an olfactory search task spontaneously exhibit alternation in the presence of airflow, suggesting that alternation may serve an important role during turbulent plume-tracking. To test this hypothesis, we combine fully-resolved numerical simulations of turbulent odor transport and Bellman optimization methods for decision-making under partial observability. We show that an agent trained to minimize search time in a realistic odor plume exhibits extensive alternation together with the characteristic cast-and-surge behavior commonly observed in flying insects. Alternation is tightly linked with casting and occurs more frequently when the agent is far downwind of the source, where the likelihood of detecting airborne cues is higher relative to cues close to the ground. Casting and alternation emerge as complementary tools for effective exploration when cues are sparse. We develop a model based on marginal value theory to capture the interplay between casting, surging and alternation. More generally, we show how multiple sensorimotor modalities can be fruitfully integrated during complex goal-directed behavior.

Precision Landing for Low-Maintenance Remote Operations with UAVs

This work proposes a fully integrated ecosystem composed of three main components with a complex goal: to implement an autonomous system with a UAV requiring little to no maintenance and capable of flying autonomously. For this goal, was developed an autonomous UAV, an online platform capable of its management and a landing platform to enclose and charge the UAV after flights. Furthermore, a precision landing algorithm ensures no need for human intervention for long-term operations.

Comparison of Three Physical—Cognitive Training Programs in Healthy Older Adults: A Study Protocol for a Monocentric Randomized Trial

(1) Combining aerobic, coordination and cognitive training allows for more improved physical and cognitive performance than when performed separately. A Nordic walking (NW) and two cognitive-motor circuit training programs (CT-c and CT-fit) are compared. CT-c and CT-fit stimulate cognition differently: CT-c, is through conventional complex coordination training performed in single and dual-task conditions; CT-fit, incorporates it into complex goal-directed actions, implemented by fitness gaming technology (2) The aim is to determine whether CT-fit brings additional benefits to cognition compared to more traditional training. (3) Forty-five healthy independent living community dwellers participants (65–80 years) will be included after a general medical examination. The main exclusion criteria are signs of cognitive impairments (Mini–Mental State Examination < 26/30) and physical impairments. Pre and post-tests will be performed to assess: cognitive functions (Montreal Cognitive Assessment; Trail Making Test; Stroop task, working memory test, Rey Complex Figure copy task, Oral Trail Making Test, and dual-task); motor fitness (Bipedal and unipedal balance test, gait assessments, Time Up and Go, chair sit and reach test and four-square stepping test); and physical fitness (10 m incremental shuttle walking test, maximal handgrip force, Timed-Stands test). (4) Incorporating cognitive demands into complex, goal-directed actions using fitness gaming technology should be the best solution to optimize training benefits.

Radical schemes for representing objects of observation and restrictions in the operation of the spacecraft target equipment for the task of forming its working program

The paper considers the problem of generating a list of objects for space survey. To solve the problem it is proposed to use mathematical objects — schemes of radicals, aimed at eliminating critical weaknesses related to the use of mathematical models and corresponding software and hardware in the problem area of complex goal-oriented systems. Also mathematical standardization of complex goal-oriented systems based on the use of radical schemes seems to be necessary. The paper substantiates the need for using radical schemes for the standard representation of objects of observation and restrictions in the operation of the spacecraft target equipment for the task of designing its working program.

On vocabulary learning strategies among students of foreign languages

Adequate and purposeful use of vocabulary is one of the primary goals of the process of learning and teaching a foreign language, given that the success in building language competence largely depends on it. Vocabulary learning strategies, as a diverse set of techniques focused on overcoming the various problems that arise when learning words, can help students to achieve this complex goal in the easiest and fastest way possible. While some strategies can be applied spontaneously, teaching practice and research (Oxford, 1990; Gu and Johnson, 1996; Schmitt, 1997; Fan, 2003; Šikmanović, 2013) indicate that students are often unaware of the breadth of the range of strategies at their disposal. The main goal of the research presented in this paper is to provide an insight into the attitudes of students of foreign languages towards the use of vocabulary learning strategies, as well as to examine the interrelationships between their attitudes and the perceived use of the strategies. The research was conducted by using a questionnaire on a sample of 47 respondents, and the results showed a significantly developed awareness of students about the usefulness of vocabulary learning strategies, which does not fully correspond to the recorded patterns of using the strategies. It was observed that students use social strategies the least, while they most often use determination and memorisation strategies, but they consider the cognitive and metacognitive types of strategies to be the most useful.

Modernization of managerial approaches to combating corruption in the context of ensuring the European integration of Ukraine

The article investigates the phenomenon of corruption as a systemic possibility of forbidden actions and violation of established norms in public administration. Corruption is drawn here as a dangerous social and political phenomenon that emerges as one of the key threats and impediments to the successful development and reconstruction of a country on the way of its European integration. It emerges due to such reasons as blurred authority, insufficient publicity and transparency of the public institution and its’ representatives activity, low index of accountability, which leads to the emergence of personal incentives for officials and, above all, the absence of penalties for violations of rules. Accordingly, the fight against corruption and the public perception of this phenomenon should now be based on regular assessments of the situation in the regions. And national and local strategies to reduce the perception of corruption by the population of the country should be targeted for the long term. Such activities should be based today on the clear principles that define the limits of anti-corruption policy on the central level. Therefore, adherence to these principles can serve as a measure of the efficiency of the state’s anti-corruption policy. The prerequisites for the emergence and progression of this phenomenon on the territory of Ukraine have been determined in the article. The following principles include: political will; financial stability; public awareness raising; assessing the context and local conditions; engaging facilitators; problem identification, risk assessment and stakeholders identification; good governance; complex goal setting; a display of trust and stakeholder engagement; message creation and directing; motivating stakeholders and their expectations framing.

Lane Detection on Roads using Computer Vision

In recent times many technological advancements are coming in the domain of road safety as accidents has been increasing at an alarming rate and one of the crucial reason for such accidents is lack of driver’s attention. Technical advancements should be there to reduce the frequency of the accidents and stay safe. One of the way to achieve the same is through Lane Detection Systems which work with the intention to recognize the lane borders on road and further prompts the driver if he switches and moves to erroneous lane markings. Lane detecting system is an essential component of many technologically intelligent transport system. Although it’s a complex goal to achieve because of vacillating road conditions that a person encounters specially while driving at night or even in daylight. Lane boundaries is detected using a camera that captures the view of the road, mounted on the front of the vehicle. The approach used in this paper changes the image taken from the video into a set of sub-images and generates image-features for each of them which are further used to detect the lanes present on the roads. There are proposed numerous ways to detect the lane markings on the road. Feature-based or model-based are the two categories of the lane detection techniques. Down-level characteristics for example lane-mark edges are used by the feature-based functions.

Developing a monitoring system for Cloud-based distributed data-centers

Nowadays more and more datacenters cooperate each others to achieve a common and more complex goal. New advanced functionalities are required to support experts during recovery and managing activities, like anomaly detection and fault pattern recognition. The proposed solution provides an active support to problem solving for datacenter management teams by providing automatically the root-cause of detected anomalies. The project has been developed in Bari using the datacenter ReCaS as testbed. Big Data solutions have been selected to properly handle the complexity and size of the data. Features like open source, big community, horizontal scalability and high availability have been considered and tools belonging to the Hadoop ecosystem have been selected. The collected information is sent to a combination of Apache Flume and Apache Kafka, used as transport layer, in turn delivering data to databases and processing components. Apache Spark has been selected as analysis component. Different kind of databases have been considered in order to satisfy multiple requirements: Hadoop Distributed File System, Neo4j, InfluxDB and Elasticsearch. Grafana and Kibana are used to show data in a dedicated dashboards. The Root-cause analysis engine has been implemented using custom machine learning algorithms. Finally, results are forwarded to experts by email or Slack, using Riemann.