Inhalation Dose and Source Term Studies in a Tribal Area of Wayanad, Kerala, India

Among radiation exposure pathways to human beings, inhalation dose is the most prominent one. Radon, thoron, and their progeny contribute more than 50 per cent to the annual effective dose due to natural radioactivity. South west coast of India is classified as a High Natural Background Radioactivity Area and large scale data on natural radioactivity and dosimetry are available from these coastal regions including the Neendakara-Chavara belt in the south of Kerala. However, similar studies and reports from the northern part of Kerala are scarce. The present study involves the data collection and analysis of radon, thoron, and progeny concentration in the Wayanad district of Kerala. The radon concentration was found to be within a range of 12–378 Bq/m3. The thoron concentration varied from 15 to 621 Bq/m3. Progeny concentration of radon and thoron and the diurnal variation of radon were also studied. In order to assess source term, wall and floor exhalation studies have been done for the houses showing elevated concentration of radon and thoron. The average values of radon, thoron, and their progeny are found to be above the Indian average as well as the average values reported from the High Natural Background Radioactivity Areas of Kerala. Exhalation studies of the soil samples collected from the vicinity of the houses show that radon mass exhalation rate varied from below detectable limit (BDL) to a maximum of 80 mBq/kg/h. The thoron surface exhalation rate ranged from BDL to 17470 Bq/m2/h.

Download Full-text

Stochastic Gradient Descent Based K-Means Algorithm on Large Scale Data Clustering

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.687-691.1342 ◽

2014 ◽

Vol 687-691 ◽

pp. 1342-1345 ◽

Cited By ~ 1

Author(s):

Jie Ding ◽

Li Peng Zhu ◽

Bin Hu ◽

Ren Long Hang ◽

Yu Bao Sun

Keyword(s):

Gradient Descent ◽

Large Scale ◽

Clustering Algorithm ◽

Distance Matrix ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

Data Sets ◽

Human Beings ◽

Large Scale Data ◽

Scale Data

With the rapid advance of data collection and storage technique, it is easy to acquire tens of millions or even billions of data sets. How to explore and exploit the useful or interesting information for human beings from these data sets has become an urgent issue. Traditional k-means clustering algorithm has been widely used in data mining community. First, randomly initialize k clustering centres. Then, all instances are classified into k different classes according to their distances to clustering centres. Lastly, update the clustering centres by the mean of its corresponding constituent instances. This whole process will be iterated until convergence. Obviously, at each iteration, distance matrix from all instances to k clustering centres must be calculated which will cost so much time when encounter large scale data sets. To address this issue, in this paper, we proposed a fast optimization algorithm based on stochastic gradient descent (SGD). At each iteration, randomly choose an instance, search its corresponding clustering centre and then update it immediately. Experimental results show that our proposed method achieves a competitive clustering results with less time cost.

Download Full-text

Tree-Based and Optimum Cut-Based Origin-Destination Flow Clustering

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8110477 ◽

2019 ◽

Vol 8 (11) ◽

pp. 477 ◽

Cited By ~ 1

Author(s):

Xiang ◽

Keyword(s):

Large Scale ◽

Spatial Scales ◽

Similarity Criterion ◽

Human Beings ◽

Travel Patterns ◽

Self Similarity ◽

Large Scale Data ◽

Spatiotemporal Clustering ◽

Maximum Spanning Tree ◽

Low Efficiency

Data about the movements of diverse objects, including human beings, animals, and commodities, are collected in growing amounts as location-aware technologies become pervasive. Clustering has become an increasingly important analytical tool for revealing travel patterns from large-scale movement datasets. Most existing methods for origin-destination (OD) flow clustering focus on the geographic properties of an OD flow but ignore the temporal information preserved in the OD flow, which reflects the dynamic changes in the travel patterns over time. In addition, most methods require some predetermined parameters as inputs and are difficult to adjust considering the changes in the users’ demands. To overcome such limitations, we present a novel OD flow clustering method, namely, TOCOFC (Tree-based and Optimum Cut-based Origin-Destination Flow Clustering). A similarity measurement method is proposed to quantify the spatial similarity relationship between OD flows, and it can be extended to measure the spatiotemporal similarity between OD flows. By constructing a maximum spanning tree and splitting it into several unrelated parts, we effectively remove the noise in the flow data. Furthermore, a recursive two-way optimum cut-based method is utilized to partition the graph composed of OD flows into OD flow clusters. Moreover, a criterion called CSSC (Child tree/Child graph Self-Similarity Criterion) is formulated to determine if the clusters meet the output requirements. By modifying the parameters, TOCOFC can obtain clustering results for different time scales and spatial scales, which makes it possible to study movement patterns from a multiscale perspective. However, TOCOFC has the disadvantages of low efficiency and large memory consumption, and it is not conducive to quickly handling large-scale data. Compared with previous works, TOCOFC has a better clustering performance, which is reflected in the fact that TOCOFC can guarantee a balance between clusters and help to fully understand the corresponding patterns. Being able to perform the spatiotemporal clustering of OD flows is also a highlight of TOCOFC, which will help to capture the differences in the patterns at different times for a deeper analysis. Extensive experiments on both artificial spatial datasets and real-world spatiotemporal datasets have demonstrated the effectiveness and flexibility of TOCOFC.

Download Full-text

Social inequality in the evolution of human societies

Sociology: Theory, Methods, Marketing ◽

10.15407/sociology2019.02.098 ◽

2019 ◽

pp. 98-120

Author(s):

Georgi Derluguian

Keyword(s):

Social Inequality ◽

Large Scale ◽

Human Beings ◽

Mass Violence ◽

Public And Private ◽

Tangible Assets ◽

Transition To Agriculture ◽

New Institutions ◽

High Level ◽

Political Economic

The author develops ideas about the origin of social inequality during the evolution of human societies and reflects on the possibilities of its overcoming. What makes human beings different from other primates is a high level of egalitarianism and altruism, which contributed to more successful adaptability of human collectives at early stages of the development of society. The transition to agriculture, coupled with substantially increasing population density, was marked by the emergence and institutionalisation of social inequality based on the inequality of tangible assets and symbolic wealth. Then, new institutions of warfare came into existence, and they were aimed at conquering and enslaving the neighbours engaged in productive labour. While exercising control over nature, people also established and strengthened their power over other people. Chiefdom as a new type of polity came into being. Elementary forms of power (political, economic and ideological) served as a basis for the formation of early states. The societies in those states were characterised by social inequality and cruelties, including slavery, mass violence and numerous victims. Nowadays, the old elementary forms of power that are inherent in personalistic chiefdom are still functioning along with modern institutions of public and private bureaucracy. This constitutes the key contradiction of our time, which is the juxtaposition of individual despotic power and public infrastructural one. However, society is evolving towards an ever more efficient combination of social initiatives with the sustainability and viability of large-scale organisations.

Download Full-text

Large-Scale Data Learning Method for Anomaly Detection using Machine Learning for Monitoring Vibration in Vehicle Equipment

IEEJ Transactions on Industry Applications ◽

10.1541/ieejias.140.480 ◽

2020 ◽

Vol 140 (6) ◽

pp. 480-487

Author(s):

Minoru Kondo

Keyword(s):

Machine Learning ◽

Anomaly Detection ◽

Large Scale ◽

Learning Method ◽

Large Scale Data ◽

Scale Data

Download Full-text

A Different Kind of Animal

10.23943/princeton/9780691195902.001.0001 ◽

2019 ◽

Author(s):

Robert Boyd

Keyword(s):

Cognitive Ability ◽

Cultural Adaptation ◽

Dominant Species ◽

Large Scale ◽

Human Beings ◽

Unique Combination ◽

Essential Ingredient ◽

Princeton University

Human beings have evolved to become the most dominant species on Earth. This astonishing transformation is usually explained in terms of cognitive ability—people are just smarter than all the rest. But this book argues that culture—our ability to learn from each other—has been the essential ingredient of our remarkable success. The book shows how a unique combination of cultural adaptation and large-scale cooperation has transformed our species and assured our survival—making us the different kind of animal we are today. The book is based on the Tanner Lectures delivered at Princeton University, featuring challenging responses across the chapters.

Download Full-text

STUDY OF ENVIRONMENTAL AWARENESS AMONG SENIOR SECONDARY SCHOOL STUDENTS IN RELATION TO THEIR GENDER AND ACADEMIC STREAM

JOURNAL OF ADVANCES IN HUMANITIES ◽

10.24297/jah.v3i2.5106 ◽

2015 ◽

Vol 3 (2) ◽

pp. 262-265

Author(s):

Dr.Navdeep Kaur

Keyword(s):

Environmental Education ◽

Natural Resources ◽

Large Scale ◽

Human Life ◽

Environmental Awareness ◽

Human Beings ◽

School Students ◽

The Earth ◽

Stages Of Learning ◽

The Masses

Since its evolution environment has remained both a matter of awe and concern to man. The frontier attitude of the industrialized society towards nature has not only endangered the survival of all other life forms but also threatened the very existence of human life. The realization of such potential danger has necessitated the dissemination of knowledge and skill vis-a-vis environment protection at all stages of learning. Therefore, learners of all stages of learning need to be sensitized with a missionary zeal. This may ensure transformation of students into committed citizens for averting global environment crisis. The advancement of science and technology made the life more and more relaxed and man also became more and more ambitious. With such development, human dependence on environment increased. He consumed more resources and the effect of his activities on the environment became more and more detectable. Environment covers all the things present around the living beings and above the land, on the surface of the earth and under the earth. Environment indicates, in total, all of peripheral forces, pressures and circumstances, which affect the life, nature, behaviour, growth, development and maturation of living beings. Irrational exploitation (not utilization) of natural resources for our greed (not need) has endangered our survival, and incurred incalculable harm. Environmental Education is a science, a well-thought, permanent, lasting and integrated process of equipping learning experiences for getting awareness, knowledge, understanding, skills, values, technical expertise and involvement of learners with desirable attitudinal changes about their relationship with their natural and biophysical environment. Environmental Education is an organized effort to educate the masses about environment, its functions, need, importance, and especially how human beings can manage their behaviour in order to live in a sustainable manner. The term 'environmental awareness' refers to creating general awareness of environmental issues, their causes by bringing about changes in perception, attitude, values and necessary skills to solve environment related problems. Moreover, it is the first step leading to the formation of responsible environmental behaviour (Stern, 2000). With the ever increasing development by modern man, large scale degradation of natural resources have been occurred, the public has to be educated about the fact that if we are degrading our environment we are actually harming ourselves. To encourage meaningful public participation and environment, it is necessary to create awareness about environment pollution and related adverse effects. This is the crucial time that environmental awareness and environmental sensitivity should be cultivated among the masses particularly among youths. For the awareness of society it is essential to work at a gross root level. So the whole society can work to save the environment.

Download Full-text