Small Obstacles Research Articles

FRAGMENTATION OF WATER DROPS IN COLLISION WITH A SMALL OBSTACLE

The study is dedicated to the general features of the processes of deformation and fragmentation of liquid drops have been studied when they collide with obstacles. Masks and filters, protecting against airborne infections, are among the possible obstacles. Coughing, sneezing, and talking cause the ejection of drops of saliva and bronchial mucus. A local drop-mask or drop-filter collision is modeled by the impact of a drop on a small obstacle as the simplest hydrodynamic case with a minimum number of influencing factors. For water-based oral and bronchial drops with a typical diameter <i>d<sub>i</sub></i> = 100 μm and impact velocity of the order of <i>v<sub>i</sub></i> = 10 m/s, the impact Weber number is about We<sub><i>i</i></sub> = ρ<i>v<sub>i</sub></i><sup>2</sup><i>d<sub>i</sub></i>/γ = 139. As a starting point in the problem of the drop breakup in a collision with a solid obstacle, we consider the coaxial impact of an inviscid liquid drop with a diameter of 2.8 mm on a disk with a diameter of 4.0 mm. In laboratory experiments, the similarity was provided by impact velocities of 1.88-3.57 m/s, which gives impact Weber numbers We<sub><i>i</i></sub> = 137-496. Such collisions are controlled only by inertia and capillarity, while the influence of all other factors is negligible. A round liquid lamella with a torus-shaped rim is formed upon the collision. The rim first expands and then retracts, forming radially directed liquid fingers in the rim. At low impact velocities, the fingers retained continuity, while at sufficiently high velocities, the fingers spattered into secondary droplets. Experiments have shown that the critical Weber number corresponding to the transition to spattering lies between 137 and 206. Approximately the same values of the Weber number occur when infected drops hit masks or filters.

Numerical analysis of the total scattering cross section on a set of sound-permeable spheres

One of the most important subtasks of the problem of acoustic wave scattering on a set of small spherical obstacles is to determine the main characteristic of the scattering phenomenon, namely, the total scattering cross section. Its solution will make it possible to establish at what system parameters the interaction between particles is insignificant and can be neglected (in this case, the problem can be simplified and reduced to the many single particles case), and at what parameters this interaction cannot be neglected. In present work a numerical parametric analysis of the total scattering cross section on a spheres system under the influence of a spherical wave from a monopole radiation source is carried out on the base on an explicit formula for the total scattering cross section on a set of interacting sound-permeable spheres. In order to determine the ratio of the physical parameters of the sphere and the environment, under which the effects of multiple scattering are significant for given types of system configuration, a series of computational experiments was carried out to calculate the main scattering characteristic taking into account multiple scattering, as well as the sums of characteristics for single sound-permeable spheres. It is shown that in all cases considered, the effects of multiple scattering cannot be neglected when determining the total scattering cross section. In the case of air bubbles in water, the type of configuration of the system is an essential factor; for water droplets in the air, both the type of configuration and the number of spheres in it are essential; and for dichloroethane droplets in water, the type of configuration and the number of spheres in it are insignificant factors.

Role of Small Business in Economic Development: A Quantitative Investigation

Small businesses have always been seen as essential to economic growth. Small enterprises have been crucial in recent years in promoting economic growth and opening up job opportunities. Despite the difficulties, small businesses have persisted in displaying resilience and adaptability, helping the local and global economies recover. As these account for a sizable portion of job creation, innovation, and entrepreneurial activity, these play a significant role in the growth of the economy. Many individuals can find work, especially in rural and low-income areas, and these frequently act as a driver of regional economic development. However, small businesses encounter many obstacles in the efforts to support economic growth, such as restricted access to capital, regulatory limitations, and competition from bigger businesses. Therefore, by fostering an environment that is enabling the growth and development, policymakers and stakeholders must assist small businesses. This can be accomplished through facilitating access to capital, streamlining regulatory procedures, and encouraging entrepreneurship-related education and training.

Influences of a small obstacle on the sidewall upon a detonation cellular structure

Influences of a small obstacle on the sidewall upon a detonation cellular structure

Imprinting Persistent Currents in Tunable Fermionic Rings

Persistent currents in annular geometries have played an important role in disclosing the quantum phase coherence of superconductors and mesoscopic electronic systems. Ultracold atomic gases in multiply connected traps also exhibit long-lived supercurrents, and have attracted much interest both for fundamental studies of superfluid dynamics and as prototypes for atomtronic circuits. Here, we report on the realization of supercurrents in homogeneous, tunable fermionic rings. We gain exquisite, rapid control over quantized persistent currents in all regimes of the BCS-BEC crossover through a universal phase-imprinting technique, attaining on-demand circulations $w$ as high as 9. High-fidelity read-out of the superfluid circulation state is achieved by exploiting an interferometric protocol, which also yields local information about the superfluid phase around the ring. In the absence of externally introduced perturbations, we find the induced metastable supercurrents to be as long-lived as the atomic sample. Conversely, we trigger and inspect the supercurrent decay by inserting a single small obstacle within the ring. For circulations higher than a critical value, the quantized current is observed to dissipate via the emission of vortices, i.e., quantized phase slips, which we directly image, in good agreement with numerical simulations. The critical circulation at which the superflow becomes unstable is found to depend starkly on the interaction strength, taking its maximum value for the unitary Fermi gas. Our results demonstrate fast and accurate control of quantized collective excitations in a macroscopic quantum system, and establish strongly interacting fermionic superfluids as excellent candidates for atomtronic applications.

Analyzing specklegrams of plastic optical fiber using convolutional neural network for weight recognition

A weight recognition scheme is proposed based on the analysis of plastic optical fiber (POF) specklegrams. A simple experiment is performed for data acquisition comprising specklegram images corresponding to different external applied weights ranging from 0 to 3 kg in steps of 0.5 kg on the POF. These specklegram images are further split into training, validation, and test datasets for employment in the convolutional neural network (CNN). The model is trained and validated with a sufficient number of epochs (iterations) to obtain optimal training and validation accuracies (>90 % ); it is then used for recognizing (classifying) the unseen test dataset images. A user-defined CNN model is optimized using four different optimizers: Adam, AdaMax, Nadam, and RMSProp. The recognition (or test) accuracy of these optimizers is compared. The Nadam optimizer has the highest recognition accuracy of 93.1% for increasing weights and 91.9% for decreasing weights. Furthermore, we investigate the impact of two parameters, namely temperature effect and information loss of specklegrams, on the model’s weight recognition accuracy. The temperature effect is studied for finite temperatures ranging from 29°C to 35°C with 3°C step fluctuations around the ambient temperature of 25°C. We find that the maximum deviation in recognition accuracy is about 1.2%. To quantify the information content (speckles) in each blocked specklegram, Shannon entropy (SE) is estimated. These images are then used in our existing CNN model with the Nadam optimizer to evaluate recognition performance with blocking. With increasing blocking, we observe a decrease in SE and recognition accuracy. This analysis suggests that, even with information loss in the specklegrams at ≤20 % blocking, a good representation of weights with high recognition accuracy (>80 % ) can be obtained. The presence of a small physical obstacle in front of the imaging system can cause information loss in specklegrams to manifest in practical scenarios.

Autonomous Underwater Vehicle Path Planning Method of Soft Actor–Critic Based on Game Training

This study aims to solve the issue of the safe navigation of autonomous underwater vehicles (AUVs) in an unknown underwater environment. AUV will encounter canyons, rocks, reefs, fish, and underwater vehicles that threaten its safety during underwater navigation. A game-based soft actor–critic (GSAC) path planning method is proposed in this study to improve the adaptive capability of autonomous planning and the reliability of obstacle avoidance in the unknown underwater environment. Considering the influence of the simulation environment, the obstacles in the simulation environment are regarded as agents and play a zero-sum game with the AUV. The zero-sum game problem is solved by improving the strategy of AUV and obstacles, so that the simulation environment evolves intelligently with the AUV path planning strategy. The proposed method increases the complexity and diversity of the simulation environment, enables AUV to train in a variable environment specific to its strategy, and improves the adaptability and convergence speed of AUV in unknown underwater environments. Finally, the Python language is applied to write an unknown underwater simulation environment for the AUV simulation testing. GSAC can guide the AUV to the target point in the unknown underwater environment while avoiding large and small static obstacles, canyons, and small dynamic obstacles. Compared with the soft actor–critic(SAC) and the deep Q-network (DQN) algorithm, GSAC has better adaptability and convergence speed in the unknown underwater environment. The experiments verifies that GSAC has faster convergence, better stability, and robustness in unknown underwater environments.

Çokuluslu Eğitim İşletmelerinde İnsan Kaynakları Yönetiminin İncelenmesi

It is hoped that this study, which aims to examine the management of human resources in multinational educational enterprises in general, will make an important contribution to the literature in its field. Multinational training businesses in the past, in the field of education, especially educational institutions, educational administration, served on the subject of technological innovations in the education sector for a long time played an important role in the development of global culture and civilization. The development process of multinational education enterprises' enterprises under formal structure control in the education sector has continued with all its speed and dynamism at every stage of the information age and has been groundbreaking in terms of many related sectors, especially education. Educational enterprises owned by multinational structures, huge enterprises in which ownership and management are significantly separated, continued to be effective and competent even when they came to management. Even today, multinational educational enterprises significantly control many huge progressive sectoral enterprises with a large number of shareholders. Although multinational educational enterprises have existed and operated for centuries, they were not considered a separate academic discipline field until the last quarter of the twentieth century. When entering the twenty-first century, multinational educational enterprises were considered an autonomous academic field of study, but the lack of a definition of how they have characteristics has become a small obstacle to the fact that this sectoral field is betting on research. Key Words: Multinational, Educational Enterprises, Human Resources

Computational homogenization of unsteady flows with obstacles

AbstractModeling flows in domains containing obstacles becomes challenging when the obstacles are very small compared to the domain. This problem is often known as modeling flow through permeable or porous media. Darcy's law is well known to provide a robust solution to this problem for viscous flows, given that the permeability of the medium can be characterized. Solutions for inertial flows have not been proposed yet. In this article, a principle multiscale virtual power is formulated for the computational homogenization of unsteady incompressible flows in domains containing small obstacles. In this theory, the coarse scale of the domain is separated from the fine scale of the obstacles. The finite element (FE) implementation of this theory is developed in the form of a parallel (FE) algorithm with two‐way coupling between the two scales. The incompressibility constraint is handled with special care by introducing an independent pressure variable at both scales and relying on the Taylor–Hood P2/P1 pair. Simulations are conducted to analyze the accuracy and efficiency of the proposed multiscale approach. The results show that the method is robust and interesting from both the points of view of computational cost and accuracy when the ratio between the domain size and the obstacle size is larger than 100.

Numerical and experimental investigation on the effect of heat release rate in the evolution of fire whirls

Buildings with large internal spaces, such as vertical shafts or atria, are widespread nowadays. In the case of fire, internal air currents may generate devastating fire whirls that can cause severe damage due to intensive heat release rate (HRR) and temperatures. This work presents the generation and evolution of fire whirls in a full-scale atrium experiment and their comparison with a numerical approach. A set of numerical models using FDS 6.7.5 are tested to assess the influence of the HRR curve and the impact of intrusive methods of temperature measurements on the prediction of whirls. The results show that the Burgers vortex model is well reproduced, although the continuous flame and plume regions can only be distinguished with fine grids. However, the periodic evolution of the whirls is better predicted with a time-averaged HRR curve, showing its influence on the flame height. The use of the experimental HRR curve presents more accurate results only in the temperatures far from the flame, with errors lower than 8.5% even for coarse grids. In addition, a small obstacle above the flame is observed to affect the formation of the whirls, which consequently impacts the grid sensitivity and computational cost.

Perception and Avoidance of Multiple Small Fast Moving Objects for Quadrotors With Only Low-Cost RGBD Camera

The autonomous navigation of unmanned aerial vehicles in a rapidly changing environment, such as avoiding small fast moving objects with onboard sensing, still remains a challenge. In this letter, we propose a complete system that only relies on a lightweight RGBD camera to achieve fast and accurate perception and avoidance of small dynamic obstacles, whereas navigating in a complex environment. Firstly, we detect the moving objects by Yolo-Fastest in RGB frame, obtain the 3D information with the depth image, and track the multiple detected objects with our proposed 3D-SORT (Simple Online and Real-time Tracking in Three-dimensional Space) algorithm. To achieve fast dynamic avoidance, we design an effective method to generate the optimized smooth trajectory to dodge all the static and dynamic obstacles with the predicted moving objects' trajectories. Finally, we integrate the above methods on our UAV platform, and demonstrate the performance of our system by testing thoroughly in simulation and real-world experiments.

Pemanfaatan Digital Content Tiktok dan Buku Kas Berbasis Android Bagi UMKM Anggota CU Hatirongga

Micro, Small and Medium Enterprises (MSMEs) face obstacles in financial reporting according to standards, do not know how much pure profit is obtained, lack of understanding of basic knowledge of financial records, lack of understanding of Android-based financial applications, and difficulty in obtaining financing from institutions. The purpose of this community service is to increase understanding of Tiktok Digital Content knowledge in business development and the ability to compile an Android - based cash book. Community service involves MSME actors who are members of the CU Hatirongga Pematangsiantar cooperative as objects of assistance and training. The method used in the training is an online method, indirect face – to - face and mentoring, namely by analyzing and problem solving. Materials for making tiktok accounts and android-based cash books are presented with lectures, training, questions and answers, demonstrations, and online case resolution. The material is made in a simple and attractive way so that the content of tiktok and android-based cashbooks can be understood by MSMEs, members of the CU Hatirongga Pematangsiantar cooperative. Furthermore, the recording process begins with examples of simple transactions that are usually carried out through the SI APIK application, an android application issued by Bank Indonesia. The results of the training and assistance in the creation of tiktok content and cashbooks through this android-based application are expected to run well

PEMANFAATAN DIGITAL CONTENT TIKTOK DAN BUKU KAS BERBASIS ANDROID BAGI UMKM ANGGOTA CU HATIRONGGA

Micro, Small and Medium Enterprises (MSMEs) face obstacles in financial reporting according to standards, do not know how much pure profit is obtained, lack of understanding of basic knowledge of financial records, lack of understanding of Android-based financial applications, and difficulty in obtaining financing from institutions. The purpose of this community service is to increase understanding of Tiktok Digital Content knowledge in business development and the ability to compile an Android - based cash book. Community service involves MSME actors who are members of the CU Hatirongga Pematangsiantar cooperative as objects of assistance and training. The method used in the training is an online method, indirect face – to - face and mentoring, namely by analyzing and problem solving. Materials for making tiktok accounts and android-based cash books are presented with lectures, training, questions and answers, demonstrations, and online case resolution. The material is made in a simple and attractive way so that the content of tiktok and android-based cashbooks can be understood by MSMEs, members of the CU Hatirongga Pematangsiantar cooperative. Furthermore, the recording process begins with examples of simple transactions that are usually carried out through the SI APIK application, an android application issued by Bank Indonesia. The results of the training and assistance in the creation of tiktok content and cashbooks through this android-based application are expected to run well

Enhancing Business Performance through Social Media Platforms Amid the COVID-19 Pandemic: A Study on Shopee in Malaysia

Since corona-virus disease (COVID-19) has caused a major economic shock, entrepreneurs such as small business owners, agents, and drop shippers face enormous obstacles to carry out their businesses. This study aims to investigate the extent of social media platforms such as Youtube, Facebook, and Instagram in attracting customers towards Shopee, leading its business performance. This brief discusses how the COVID-19 crisis is accelerating an expansion of e-commerce especially Shopee towards customers, likely involving a long-term shift of e-commerce transactions from luxury goods and services to everyday necessities in conjunction with driving users' satisfaction, leading to business performance improvements. An online survey questionnaire is used for data collection and the respondents consist of a total of 150 Shopee users (buyers) from Malaysia. The findings of this study serve a valuable insight and guidelines for businesses to integrate into social media platforms for effective marketing as well as potential future development. Keywords: Business performance, COVID-19, E-commerce, Entrepreneurs, Shopee, Social media.

Solution of World Robot Challenge 2020 Partner Robot Challenge (Real Space)

The World Robot Challenge is an international competition for the social implementation of robots. Among them, the Partner Robot Challenge (Real Space) is a category that focuses on domestic service robots, competing to achieve simple tasks such as tidying a room, avoiding small obstacles, grasping a specified object from the shelf, and delivering an object to a waving person. In this category, we focused on the theme of ‘Keep Moving’ and worked on researching and developing technologies for object recognition, grasping, and other tasks. For object recognition, we propose an automatic dataset generator using a physics simulator and generate about 490,000 images in two hours. We trained it with an instance segmentation model, achieving an accuracy of about 79.3% in all games. For object grasping, we installed a three-dimensional sensor on the robot hand, and achieved successful grasping with high accuracy of about 79.6% (88.9% excluding failures due to hardware problems) in all games. In addition, we propose a motion synthesis method that simultaneously performs movement and posture transition to achieve high-speed motion. When navigation is executed, the robot changes to the navigation posture while aiming for the goal. Before reaching the goal, it changes the posture for the following action. As a result, we realized a speedup of about 1.32 times in the pick-and-place task. In the tidy-up task, the robot could clear an average of 14 objects and a maximum of 16 objects in 15 minutes. In the obstacle avoidance task, the robot succeeded five times out of six games, and in the delivery task, it succeeded four times out of six games. Throughout all the tasks, we scored 800 points twice, the highest score in the world, and won the championship. This research is aimed at the practical application of domestic service robots. We believe that the results presented in this paper demonstrate the practicality of domestic service robots in a well-developed environment. The video of the finals is available at https://youtu.be/ElUb8bfSC34?t=5511 (right side). The our source code using the simulator is available at https://github.com/Hibikino-Musashi-Home/hma_wrs_sim_ws.

Factors of Proactive Disclosure of Information at the Local Level

In our paper, we concentrate on proactive transparency, provision of data without prior information requests. To do so, we collected data from all 2,926 municipalities in Slovakia and analyze political, economic, and social factors that affect the proactive transparency of these local bodies. This case selection provides two advantages. First, we study a relatively new democracy, where proactive transparency has not been analyzed so far. Second, our sample size is substantially larger than samples in most existing studies, and unlike in the case of the majority of previous research, we focus on a country with a highly fragmented municipal structure, where most municipalities have a small population. We find that a higher population, lower unemployment and female municipal leadership enhance the level of proactive transparency. The results also show a connection between reactive and proactive transparency at the local level. In general, our findings indicate that municipalities with a small population face substantial obstacles in disclosing information to the public.

Singular geometry perturbation based method for shape-topology optimization in unsteady Stokes flow

This paper concerns the topological derivatives and its applications for solving shape and topology optimization problems in fluid mechanics. The fluid flow is governed by the unsteady incompressible Stokes equations in the two dimensional case. We derive a topological sensitivity analysis for this parabolic-type operator. The proposed approach is based on a preliminary estimate describing the variation of the velocity field caused by the presence of a small obstacle inside the fluid flow. We obtain a topological asymptotic expansion for the unsteady Stokes operator valid for a large class of shape functions and an arbitrarily shaped geometric perturbation. Then, the topological gradient is exploited for building an efficient and accurate topology optimization algorithm. Finally, we present some numerical investigations showing the efficiency of the proposed approach.

A Detection and Tracking Method Based on Heterogeneous Multi-Sensor Fusion for Unmanned Mining Trucks.

There exist many difficulties in environmental perception in transportation at open-pit mines, such as unpaved roads, dusty environments, and high requirements for the detection and tracking stability of small irregular obstacles. In order to solve the above problems, a new multi-target detection and tracking method is proposed based on the fusion of Lidar and millimeter-wave radar. It advances a secondary segmentation algorithm suitable for open-pit mine production scenarios to improve the detection distance and accuracy of small irregular obstacles on unpaved roads. In addition, the paper also proposes an adaptive heterogeneous multi-source fusion strategy of filtering dust, which can significantly improve the detection and tracking ability of the perception system for various targets in the dust environment by adaptively adjusting the confidence of the output target. Finally, the test results in the open-pit mine show that the method can stably detect obstacles with a size of 30–40 cm at 60 m in front of the mining truck, and effectively filter out false alarms of concentration dust, which proves the reliability of the method.

Multi-obstacle aware smart navigation system for visually impaired people in fog connected IoT-cloud environment.

Design of smart navigation for visually impaired/blind people is a hindering task. Existing researchers analyzed it in either indoor or outdoor environment and also it's failed to focus on optimum route selection, latency minimization and multi-obstacle presence. In order to overcome these challenges and to provide precise assistance to visually impaired people, this paper proposes smart navigation system for visually impaired people based on both image and sensor outputs of the smart wearable. The proposed approach involves the upcoming processes: (i) the input query of the visually impaired people (users) is improved by the query processor in order to achieve accurate assistance. (ii) The safest route from source to destination is provided by implementing Environment aware Bald Eagle Search Optimization algorithm in which multiple routes are identified and classified into three different classes from which the safest route is suggested to the users. (iii) The concept of fog computing is leveraged and the optimal fog node is selected in order to minimize the latency. The fog node selection is executed by using Nearest Grey Absolute Decision Making Algorithm based on multiple parameters. (iv) The retrieval of relevant information is performed by means of computing Euclidean distance between the reference and database information. (v) The multi-obstacle detection is carried out by YOLOv3 Tiny in which both the static and dynamic obstacles are classified into small, medium and large obstacles. (vi) The decision upon navigation is provided by implementing Adaptive Asynchronous Advantage Actor-Critic (A3C) algorithm based on fusion of both image and sensor outputs. (vii) Management of heterogeneous is carried out by predicting and pruning the fault data in the sensor output by minimum distance based extended kalman filter for better accuracy and clustering the similar information by implementing Spatial-Temporal Optics Clustering Algorithm to reduce complexity. The proposed model is implemented in NS 3.26 and the results proved that it outperforms other existing works in terms of obstacle detection and task completion time.

BLOCKCHAIN TEKNOLOJİSİNDE YENİ DÖNEM VE DAHA İYİ MUHASEBE BİLGİSİ

The magnitude of the potential blockchain has been so powerful that the way of doing business in all sectors could change dramatically. The nature of blockchain seems well suited to meeting the needs of accounting as well. If the potentials offered by blockchain can be fully realized, today’s accounting practices are likely to change drastically in a way we have never seen before. In this study, it is tried to determine what kind of impact the blockchain holds for the future of accounting and auditing. “Decentralization” and “triple entry accounting” are revolutionary features blockchain could bring for accounting. In this study, it is understood that these changes seem theoretically possible, but not easy to use them effectively, because it turned out that there are many large and small obstacles ahead that had to be overcome before we could say full adoption of blockchain in accounting. It looks like there is a long way to go, at least for near future. However, considering the magnitude of innovative impact that blockchain will generate, it seems it is worth putting necessary effort in action to overcome these obstacles for high standards in accounting.