scholarly journals Refugees and Host State Security: An Empirical Investigation of Rohingya Refuge in Bangladesh

2021 ◽  
Author(s):  
Sarwar J. Minar
Keyword(s):  
Large Scale ◽  
Research Question ◽  
Economic Security ◽  
Host Community ◽  
Security Threats ◽  
Security Threat ◽  
Low Level ◽  
Medium Level ◽  
Level I ◽  
High Level

While it is conventionally believed that large scale refugees pose security threats to the host community or state. So, since the massive influx of Rohingyas in Bangladesh in 2017, which resulted a staggering total of 1.6 million Rohingyas refuge in Bangladesh, it was argued that Bangladesh will face severe security threats. This article investigates the security experience of Bangladesh in case of Rohingya influx in a span of three years, August 2017 to August 2020. The research question I intend to address is, has Bangladesh faced security threat due to massive Rohingya influx? If so in what ways? I test four security threat areas, which include, societal security, economic security, internal security, and public security. I have used newspaper reports or newspaper content analysis over past three years along with interview data collected from interviewing local people in cox’s bazar area in the first half of 2019 where the Rohingya camps are located. The identity of the interviewees is kept anonymous as per request. In order to assess if the threats are low level, medium level, or high level, I look into both the frequency of reports and the way they are interpreted. I find that Bangladesh has not experience any serious security threat in the last three years. There are some criminal activities and offenses, but these are only low-level security threat at best. My research presents empirical evidence that challenges conventional assertions that refugees are security threats or challenges in the host states.

scholarly journals EXPRESS: Marketers Project Their Personal Preferences onto Consumers: Overcoming the Threat of Egocentric Decision Making

2021 ◽  
pp. 002224372199837
Author(s):  
Walter Herzog ◽  
Johannes D. Hattula ◽  
Darren W. Dahl
Keyword(s):  
Decision Making ◽  
Consumer Preferences ◽  
Research Question ◽  
Pilot Studies ◽  
Low Level ◽  
Marketing Managers ◽  
False Consensus Effect ◽  
False Consensus ◽  
High Level

This research explores how marketing managers can avoid the so-called false consensus effect—the egocentric tendency to project personal preferences onto consumers. Two pilot studies were conducted to provide evidence for the managerial importance of this research question and to explore how marketing managers attempt to avoid false consensus effects in practice. The results suggest that the debiasing tactic most frequently used by marketers is to suppress their personal preferences when predicting consumer preferences. Four subsequent studies show that, ironically, this debiasing tactic can backfire and increase managers’ susceptibility to the false consensus effect. Specifically, the results suggest that these backfire effects are most likely to occur for managers with a low level of preference certainty. In contrast, the results imply that preference suppression does not backfire but instead decreases false consensus effects for managers with a high level of preference certainty. Finally, the studies explore the mechanism behind these results and show how managers can ultimately avoid false consensus effects—regardless of their level of preference certainty and without risking backfire effects.

Urban network of China from the perspective of population mobility: Three-dimensional co-occurrence of nodes and links

2021 ◽  
pp. 0308518X2199781
Author(s):  
Xinyue Luo ◽  
Mingxing Chen
Keyword(s):  
Three Dimensional ◽  
Geographical Distance ◽  
Two Dimensional ◽  
Population Mobility ◽  
Urban Network ◽  
Urban Networks ◽  
Low Level ◽  
Medium Level ◽  
High Level ◽  
External Connections

The nodes and links in urban networks are usually presented in a two-dimensional(2D) view. The co-occurrence of nodes and links can also be realized from a three-dimensional(3D) perspective to make the characteristics of urban network more intuitively revealed. Our result shows that the external connections of high-level cities are mainly affected by the level of cities(nodes) and less affected by geographical distance, while medium-level cities are affected by the interaction of the level of cities(nodes) and geographical distance. The external connections of low-level cities are greatly restricted by geographical distance.

scholarly journals A CloudSat–CALIPSO View of Cloud and Precipitation Properties across Cold Fronts over the Global Oceans

2015 ◽  
Vol 28 (17) ◽  
pp. 6743-6762 ◽  
Author(s):  
Catherine M. Naud ◽  
Derek J. Posselt ◽  
Susan C. van den Heever
Keyword(s):  
Large Scale ◽  
Cold Front ◽  
Conveyor Belt ◽  
Low Level ◽  
Scale Parameters ◽  
Convective Clouds ◽  
Cold Fronts ◽  
Surface Front ◽  
High Level ◽  
The Impact

Abstract The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the postfrontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low-level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime postfrontal precipitation.

scholarly journals Knowledge Integration Networks for Action Recognition

2020 ◽  
Vol 34 (07) ◽  
pp. 12862-12869
Author(s):  
Shiwen Zhang ◽  
Sheng Guo ◽  
Limin Wang ◽  
Weilin Huang ◽  
Matthew Scott
Keyword(s):  
Action Recognition ◽  
Large Scale ◽  
Knowledge Integration ◽  
Scene Recognition ◽  
Teacher Networks ◽  
Medium Level ◽  
Meaningful Context ◽  
Context Knowledge ◽  
High Level ◽  
Context Features

In this work, we propose Knowledge Integration Networks (referred as KINet) for video action recognition. KINet is capable of aggregating meaningful context features which are of great importance to identifying an action, such as human information and scene context. We design a three-branch architecture consisting of a main branch for action recognition, and two auxiliary branches for human parsing and scene recognition which allow the model to encode the knowledge of human and scene for action recognition. We explore two pre-trained models as teacher networks to distill the knowledge of human and scene for training the auxiliary tasks of KINet. Furthermore, we propose a two-level knowledge encoding mechanism which contains a Cross Branch Integration (CBI) module for encoding the auxiliary knowledge into medium-level convolutional features, and an Action Knowledge Graph (AKG) for effectively fusing high-level context information. This results in an end-to-end trainable framework where the three tasks can be trained collaboratively, allowing the model to compute strong context knowledge efficiently. The proposed KINet achieves the state-of-the-art performance on a large-scale action recognition benchmark Kinetics-400, with a top-1 accuracy of 77.8%. We further demonstrate that our KINet has strong capability by transferring the Kinetics-trained model to UCF-101, where it obtains 97.8% top-1 accuracy.

The Analysis of Students Mathematic Problem Solving Ability During Online Learning

2021 ◽  
Vol 6 (1) ◽  
pp. 62-68
Author(s):  
M. Arif Wahyu Daroini ◽  
Tri Novita Irawati ◽  
Sholahudin Al Ayubi
Keyword(s):  
Online Learning ◽  
Problem Solving ◽  
Mathematical Problem ◽  
Mathematical Problem Solving ◽  
Ability Level ◽  
Maximum Score ◽  
Low Level ◽  
Medium Level ◽  
Good For ◽  
High Level

This study aims to determine students' mathematical problem solving abilities based on their high, medium and low level of ability in solving the problem. This type of research is descriptive qualitative. The data collecting method that use are observation, test, and interview. The results showed that the problem-solving ability of high-level subjects reached an average of 75%, the problem-solving abilities of medium-level subjects reached an average of 67%, the problem-solving abilities of low-level subjects reached an average of 67%, out of a maximum score of 100. The result of interview, ability level high, medium, and low, students are capable and good even though it does not reach 100%. So, it can be concluded that high, medium, and low level abilities are good for going through the problem solving ability indicator.  Keywords: problem solving, online learning  

scholarly journals A High-Density Crowd Counting Method Based on Convolutional Feature Fusion

2018 ◽  
Vol 8 (12) ◽  
pp. 2367 ◽  
Author(s):  
Hongling Luo ◽  
Jun Sang ◽  
Weiqun Wu ◽  
Hong Xiang ◽  
Zhili Xiang ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Large Scale ◽  
Feature Fusion ◽  
High Density ◽  
Counting Problem ◽  
Crowd Counting ◽  
Low Level ◽  
Density Map ◽  
High Level

In recent years, the trampling events due to overcrowding have occurred frequently, which leads to the demand for crowd counting under a high-density environment. At present, there are few studies on monitoring crowds in a large-scale crowded environment, while there exists technology drawbacks and a lack of mature systems. Aiming to solve the crowd counting problem with high-density under complex environments, a feature fusion-based deep convolutional neural network method FF-CNN (Feature Fusion of Convolutional Neural Network) was proposed in this paper. The proposed FF-CNN mapped the crowd image to its crowd density map, and then obtained the head count by integration. The geometry adaptive kernels were adopted to generate high-quality density maps which were used as ground truths for network training. The deconvolution technique was used to achieve the fusion of high-level and low-level features to get richer features, and two loss functions, i.e., density map loss and absolute count loss, were used for joint optimization. In order to increase the sample diversity, the original images were cropped with a random cropping method for each iteration. The experimental results of FF-CNN on the ShanghaiTech public dataset showed that the fusion of low-level and high-level features can extract richer features to improve the precision of density map estimation, and further improve the accuracy of crowd counting.

Cloud Patterns as Seen from Altitudes of 250 to 850 Miles — Preliminary Results

1960 ◽  
Vol 41 (6) ◽  
pp. 291-297 ◽  
Author(s):  
John H. Conover ◽  
James C. Sadler
Keyword(s):  
Large Scale ◽  
Vertical Motion ◽  
Time Lapse ◽  
Squall Line ◽  
Low Level ◽  
The Earth ◽  
Stationary Front ◽  
Ballistic Missiles ◽  
High Level ◽  
Cloud Patterns

Time-lapse films of the earth from high-flying ballistic missiles have provided the meteorologist with the first synoptic detailed coverage of cloud patterns over large areas. Analysis of the film obtained on 24 August 1959 shows the cloud patterns over an area corresponding to one-twentieth of the earth's total surface. Comparison of the rectified cloud positions with, the high- and low-level synoptic charts shows large-scale cloud patterns directly associated with high-level vortices and troughs as well as patterns associated with a quasi-stationary front and the intertropical convergence zone. Details suggesting low-level vortices, frontal waves, and a squall line appear, but they cannot be verified due to sparse surface observations. Other details, such as the effects of large and small islands, coastlines and rivers upon the pattern of vertical motion are indicated by the clouds.

scholarly journals Tsunami risk levels mapping in Puger Sub-District, Jember Regency

2021 ◽  
Vol 930 (1) ◽  
pp. 012094
Author(s):  
E P Anindia ◽  
E Hidayah ◽  
R U A Wiyono
Keyword(s):  
Tsunami Hazard ◽  
Weighting Method ◽  
Risk Levels ◽  
Low Level ◽  
Prone Area ◽  
Medium Level ◽  
Run Up ◽  
Hazard Level ◽  
Tsunami Run Up ◽  
High Level

Abstract Puger sub-district is categorized as a tsunami-prone area because of its location in the South Coast, directly facing the Indian Ocean, which is the meeting point for two active tectonic plates. The active plate zone is prone to causing earthquakes that raise tsunamis. This article will describe the tsunami hazard and vulnerability level in Puger sub-district using the Geographic Information System (GIS) application. The method in this study uses a weighted overlay method. The weighting method is carried out to determine the level of tsunami hazard and vulnerability by following the weighting criteria in previous studies. Physical vulnerability criteria include land elevation, slope, beach type, land use, coastline distance, and rivers. The tsunami hazard level is determined based on the tsunami run-up map from previous studies. Based on the results of the risk mapping, it was found that there were five risk categories in Puger sub-district, namely the very low level (13.90 Ha), low level (271.99 Ha), medium level (7133.25 Ha), high level (644.22 Ha), and very high level (23.29 Ha).

scholarly journals Empowerment of Women in Fisheries: Evidence from Ganjam District of Odisha

2020 ◽  
pp. 61-68
Author(s):  
Priyanka Patra ◽  
S. S. Dana ◽  
S. B. Ramya Lakshmi
Keyword(s):  
The State ◽  
Composite Score ◽  
Women Empowerment ◽  
Low Level ◽  
Inland Fisheries ◽  
Medium Level ◽  
Good Concentration ◽  
Different Dimensions ◽  
High Level ◽  
Ganjam District

The present study was conducted to assess the empowerment level of women in the fisheries sector in the Ganjam district of Odisha. In the inland sector, the highest numbers of women are of the fishermen population in Ganjam district i.e. 29476 out of a total 263514 number of female fisheries population of the state (Directorate of Fisheries, Government of Odisha, 2015). A very good concentration of women is involving in fisheries activities in this district. But when sector-specific cases are concerned, there are very few studies found where different dimensions of women empowerment through fisheries are discussed. The results revealed that the majority of the respondents (66.60%) in the Inland sector are grouped under a medium level of empowerment followed by low and high-level empowerment (16.70%). These results indicated that there is a significant move towards the empowerment of women in the case of inland fisheries. However, in the Marine sector equal percentage of respondents belonged to both medium and high levels of women empowerment i.e. each 30 (50.00%) and low level of empowerment was nil which indicates the level of empowerment in the marine fisheries activities compared to inland fisheries. With this background, the overall empowerment score was categorized into the low, medium, and high level of empowerment where a majority of the respondents (71.6%) were under the medium level of empowerment followed by the equal percentage of the low and high level of empowerment (14.2%). The composite score of empowerment of women is also encouraging. However, efforts are needed to bring women empowerment from medium level to a higher level. There is also a need to uplift a section of women who are still in the lower category of empowerment.

scholarly journals The influence of the dimensions of perfectionism on the formation of emotional maladjustment

2021 ◽  
Keyword(s):  
Medical Students ◽  
Medical Profession ◽  
Compensatory Mechanisms ◽  
Daily Stress ◽  
Low Level ◽  
Medical Environment ◽  
Medium Level ◽  
Level Of Training ◽  
Main Components ◽  
High Level

The growing complexity of the medical profession places increased demands on the future physician’s adaptive capacity. The problem of the relationship of the aff ective spectrum disorders with such a dysfunctional personality trait as perfectionism is intensively discussed in clinical psychology. Medical students are in a more diffi cult position than others. It’s related to their future profession requires a high level of training and also associated with a high responsibility for the lives and patient’s health. High pace, intense workload, stress of life makes increased demands on the compensatory mechanisms of the medical student’s psyche, failure of which leads to psychological and social confl icts. The paper presents an empirical study of the severity of symptoms of depression, anxiety, and daily stress as the main components of emotional maladaptation, depending on the level of perfectionism in the medical student environment in conditions of increased psychological stress and pre-examination stress. Subjects with a low level of perfectionism are as emotionally prosperous as possible - they have no signs of depression in 89% of cases. In the group of subjects with a medium level of perfectionism, the number of respondents in whom there are no signs of depression decreases and the number with mild, moderate and high levels of depression increases. In the group with a high level of perfectionism, the number of people without signs of depression is half of the whole group, a sharp increase in the number of subjects with moderate and high levels of depression. The level of depression in all three groups is statistically signifi cantly diff erent from each other: the lowest in the group with a low level of perfectionism and the highest in the group with a high level of perfectionism (p <0.001). Positive correlations between the general indicator of perfectionism, its separate parameters and indicators of depression, anxiety and daily stress in the studied groups are revealed. The data obtained as a result of the study confi rm the high level of emotional maladaptation of medical students. In the academic student medical environment, respondents with a pronounced level of perfectionism experience more high-intensity, daily stress (both in the interpersonal and academic spheres of student life) compared to respondents with moderate and low levels of perfectionism.

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