Gender data from Census of India 2011, highlighting the trends in Sex Ratio and Child Sex Ratio over geography and over time. This presentation was given in the XIV National Conference of the Indian Association for Women's Studies (IAWS) in Guwahati, held from 4-7 February 2014.
The Child Sex Ratio in India and states as per Census 2011, mainly through maps showing the dramatic and depressing continued fall in CSR and the spread of this fall into new areas of the country. This was presented at the CWDS media workshop on Sex Selection in Goa from 26th -28th September 2014. Most of these maps are part of the Census of India publication, The State of India's Children.
The Child Sex Ratio in India and states as per Census 2011, mainly through maps showing the dramatic and depressing continued fall in CSR and the spread of this fall into new areas of the country. This was presented at the CWDS media workshop on Sex Selection in Goa from 26th -28th September 2014. Most of these maps are part of the Census of India publication, The State of India's Children.
Slides for a talk I gave to Class XI and XII kids in my school, St Mary's Safdarjung Enclave!! Was so much fun and so inspiring to speak to a packed house with plenty of intelligent questions! The two best questions-
Q1- "How does it feel to report to an illiterate politician when you're so well qualified?"
A1- Despite being illiterate the politician had the grit to win an election! He/she is a leader and has done something you couldn't, with fewer resources than you! The people trusted him/her! Respect that, and he/she will respect your qualifications!
Q2- "How do you manage your time and look after family too?"
A- You have to conserve your time and energy, and do what matters most first, and family must come first! But its hard and you have to keep working at it.
Wind Power in India- An Ongoing Success StoryVarsha Joshi
Wind Power in India is now a mainstream source of energy production. This has come about through the combined efforts of the Central Government, State Governments, domestic manufacturers and power producers. There is a huge potential yet untapped, and a bright future ahead! These slides were presented at the Global Investor's Summit 2014 at Indore on 9th October 2014.
A demographic history of Delhi from ancient times, through Independence, and till the present day,using maps and Census data. Caveat- the administrative units described are as of 1st January 2010,on the basis of which Census 2011 was conducted. In 2012-2013, the number of Municipal Bodies increased to 5 because the MCD split into North, South and East MCD. The number of revenue districts increased to 11. Also- apologies for the distorted logo- in the original PPT, it's a rotating gif! Error pointed out by @rkarnad- Tughlaqabad was built by Ghiyasuddin Tughlaq, not Mohammad Bin Tughaq.
Our concern is with the sex ratio in infancy and childhood, and we use this in order to examine the magnitude and implications
of gender imbalance. More precisely, our focus in this paper is on the sex ratio (defined as the number of males per 100 females) from birth to 6 years of age—we shall refer to it simply as the child sex ratio (CSR). The narrowness of our focus has two advantages. First, whereas the overall population sex ratio is a complex aggregate that depends on many factors, the natural determinants of the child sex ratio are more limited, allowing us a cleaner analysis. Second, it is this ratio that is liable to be affected by selective abortions, whereas the population sex ratio moves only a little with these new developments.
Age and Sex Structure of Uttar Pradesh & Kerala: A comparative StudyNandlal Mishra
Age-Sex structure of Kerala highly resembles to that of the Developed nations. Age-Sex structure of Uttar Pradesh highly resembles to that of the Developing nations. Among all Indian states Uttar Pradesh and Kerala represents two opposite extremes for almost all age-sex measures.
Slides for a talk I gave to Class XI and XII kids in my school, St Mary's Safdarjung Enclave!! Was so much fun and so inspiring to speak to a packed house with plenty of intelligent questions! The two best questions-
Q1- "How does it feel to report to an illiterate politician when you're so well qualified?"
A1- Despite being illiterate the politician had the grit to win an election! He/she is a leader and has done something you couldn't, with fewer resources than you! The people trusted him/her! Respect that, and he/she will respect your qualifications!
Q2- "How do you manage your time and look after family too?"
A- You have to conserve your time and energy, and do what matters most first, and family must come first! But its hard and you have to keep working at it.
Wind Power in India- An Ongoing Success StoryVarsha Joshi
Wind Power in India is now a mainstream source of energy production. This has come about through the combined efforts of the Central Government, State Governments, domestic manufacturers and power producers. There is a huge potential yet untapped, and a bright future ahead! These slides were presented at the Global Investor's Summit 2014 at Indore on 9th October 2014.
A demographic history of Delhi from ancient times, through Independence, and till the present day,using maps and Census data. Caveat- the administrative units described are as of 1st January 2010,on the basis of which Census 2011 was conducted. In 2012-2013, the number of Municipal Bodies increased to 5 because the MCD split into North, South and East MCD. The number of revenue districts increased to 11. Also- apologies for the distorted logo- in the original PPT, it's a rotating gif! Error pointed out by @rkarnad- Tughlaqabad was built by Ghiyasuddin Tughlaq, not Mohammad Bin Tughaq.
Our concern is with the sex ratio in infancy and childhood, and we use this in order to examine the magnitude and implications
of gender imbalance. More precisely, our focus in this paper is on the sex ratio (defined as the number of males per 100 females) from birth to 6 years of age—we shall refer to it simply as the child sex ratio (CSR). The narrowness of our focus has two advantages. First, whereas the overall population sex ratio is a complex aggregate that depends on many factors, the natural determinants of the child sex ratio are more limited, allowing us a cleaner analysis. Second, it is this ratio that is liable to be affected by selective abortions, whereas the population sex ratio moves only a little with these new developments.
Age and Sex Structure of Uttar Pradesh & Kerala: A comparative StudyNandlal Mishra
Age-Sex structure of Kerala highly resembles to that of the Developed nations. Age-Sex structure of Uttar Pradesh highly resembles to that of the Developing nations. Among all Indian states Uttar Pradesh and Kerala represents two opposite extremes for almost all age-sex measures.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
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Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
4. SEX RATIO VS CHILD SEX RATIO
4
976
964
962
945
927
919
941
930
934
926
933
943
910
920
930
940
950
960
970
980
1961 1971 1981 1991 2001 2011
Sex Ratio and Child Sex Ratio
India: 1961-2011
Child Sex Ratio Sex Ratio
7. Sonitpur
Cachar
Karbi Anglong
Jorhat
Nagaon
Tinsukia
Dima Hasao
Baksa
Dhubri Kamrup
Dibrugarh
Kokrajhar
Dhemaji
Barpeta
Lakhimpur
Sivasagar
Udalguri
Chirang
Karbi Anglong
Goalpara
Golaghat
Darrang
Karimganj
Morigaon
Nalbari
Hailakandi
Bongaigaon
Kamrup
Metropolitan
959
966
967
954
964
960
962
963
954
964
959
959
967
950
960
968
966
961
969
963
973
968
969969
967 956
954
946
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949 (1)
950 and Above (26)
Kamrup
Metropolitan
Sonitpur
Cachar
Karbi Anglong
Jorhat
Nagaon
Tinsukia
Dima Hasao
Baksa
Dhubri Kamrup
Dibrugarh
Kokrajhar
Dhemaji
Barpeta
Lakhimpur
Sivasagar
Udalguri
Chirang
Karbi Anglong
Goalpara
Golaghat
Darrang
Karimganj
Morigaon
Nalbari
Hailakandi
Bongaigaon
974
974
955
961
975
958
962
963
955
967
974
967
963
970
968
964
961
961
965
974
975
958
977
966
927
943
972 961
ASSAM
CHILD SEX RATIO
2011
2001
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949 (2)
950 and Above (25)
State Average 962
State Average 965 7
8. Ribhoi
Jaintia Hills
West Khasi Hills
West Garo Hills
East Garo Hills
East Khasi Hills
South Garo Hills
967
976
976
980
964
953
974
MEGHALAYA
CHILD SEX RATIO
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949
950 and Above (7)
Ribhoi
Jaintia Hills
West Khasi Hills
West Garo Hills
East Garo Hills
East Khasi Hills
South Garo Hills
975
995
959
972
972
972
971
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949
950 and Above (7)
2011
2001
State Average 970
State Average 973 8
9. S
S - Senapati
Ukhrul
Chandel
Senapati
Tamenglong
Churachandpur
Thoubal
Bishnupur
Imphal West
Imphal East
Imphal East
948
923
917
918
921
935
949
933
943
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949 (9)
950 and Above
MANIPUR
CHILD SEX RATIO
S
S - Senapati
Ukhrul
Chandel
Senapati
Tamenglong
Churachandpur
Thoubal
Bishnupur
Imphal West
Imphal East
Imphal East
968
946
936
962
962
967
943
952
963
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949 (3)
950 and Above (6)
2011
2001
State Average 936
State Average 957 9
10. Lunglei
Aizawl
Mamit
Champhai
Lawngtlai
Saiha
Kolasib
Serchhip
963
971
979
979
967
980
932
949
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949 (2)
950 and Above (6)
MIZORAM
CHILD SEX RATIO
Lunglei
Aizawl
Mamit
Champhai
Lawngtlai
Saiha
Kolasib
Serchhip
962
974
973
937
947
973
950
974
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949 (2)
950 and Above (6)
2011
2001
State Average 970
State Average 964 10
12. North District
West District
East District
South District
929
964
960
953
SIKKIM
CHILD SEX RATIO
North District
West District
East District
South District
995
966
950
969
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949
950 and Above (4)
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949 (1)
950 and Above (3)
2011
2001
State Average 957
State Average 963 12
13. Dhalai
West Tripura
South Tripura
North Tripura
952
951
968
969
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949
950 and Above (4)
TRIPURA
CHILD SEX RATIO
Dhalai
West Tripura
South Tripura
North Tripura
967
961
965
970
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899
900 - 949
950 and Above (4)
2011
2001
State Average 957
State Average 966 13
14. Anjaw
Lohit
Dibang Valley
West Siang
Upper Siang
East Kameng
Changlang
Kurung Kumey
Tirap
Upper Subansiri
West Kameng
East Siang
Tawang
Lower
Subansiri
Papum Pare
Lower
Dibang Valley
889
941
946
983
970
991
979
973
1001
966
988
948
977
966
986
961
ARUNACHAL PRADESH
CHILD SEX RATIO
2011
2001
State Average 972
State Average 964
Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899 (1)
900 - 949 (3)
950 and Above (12)
Anjaw
Lohit
Dibang Valley
West Siang
Upper Siang
East Kameng
Changlang
Kurung Kumey
Tirap
Upper Subansiri
West Kameng
East Siang
Tawang
Lower
Subansiri
Papum Pare
Lower
Dibang Valley
874
950985
932
1010
954
955
1049
1035
933
958
955
978
972948
941 Number of Females per 1000 Males
(in age group 0-6)
Below 800
800 - 849
850 - 899 (1)
900 - 949 (4)
950 and Above (11)
14