Largest collection of Google Logos on the web Set 10

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In praise of noise cancelling headphones

Ive just come back from a trip to Europe involving two 24 hour plus air flights from and back to New Zealand. I recently treated myself to a pair of Bose QuietComfort 20i Acoustic Noise Cancelling Headphones. I dont usually promote products on this blog but I have to say I cant praise these headphones highly enough. Bose came up with the idea for noise cancelling headphones and they are issued to pilots and as standard in business class on many airlines. I would recommend that if you fly often you must invest in a pair. I finished each 24 hour flight (yes New Zealand is a long way from the rest of the world) feeling much more relaxed because I never heard that constant engine roar. I just heard the movies, my music or near silence. I really believe I left each flight much more rested than previously. Highly recommended.

from The Universal Machine http://universal-machine.blogspot.com/

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Four years of Schema org Recent Progress and Looking Forward

Posted by Ramanathan Guha, Google Fellow

In 2011, we announced schema.org, a new initiative from Google, Bing and Yahoo! to create and support a common vocabulary for structured data markup on web pages. Since that time, schema.org has been a resource for webmasters looking to add markup to their pages so that search engines can use that data to index content better and surface it in new experiences like rich snippets, GMail, and the Google App.

Schema.org, which provides a growing vocabulary for describing various kinds of entity in terms of properties and relationships, has become increasingly important as the Web transitions to a multi-device, mobile-oriented world. We are now seeing schema.org being used on many millions of Web sites, defining data types and properties common across applications, platforms and products, in order to enhance the user experience by delivering the most relevant information they need, when they need it.

Schema.org in Google Rich Snippets

Schema.org in Google Knowledge Graph panels

Schema.org in Recipe carousels

In Schema.org: Evolution of Structured Data on the Web, an overview article published this week on ACM, we report some key schema.org adoption metrics from a sample of 10 billion pages from a combination of the Google index and Web Data Commons. In this sample, 31.3% of pages have schema.org markup, up from 22% one year ago. Structured data markup is now a core part of the modern web.

The schema.org group at W3C is now amongst the largest active W3C communities, serving as a hub for diverse groups exploring schemas covering diverse topics such as sports, healthcare, e-commerce, food packaging, bibliography and digital archive management. Other companies, also make use of the same data to build different applications, and as new use cases arise further schemas are integrated via community discussion at W3C. Each of these topics in turn have subtle inter-relationships - for example schemas for food packaging, for flight reservations, for recipes and for restaurant menus, each have different approaches to describing food restrictions and allergies. Rather than try to force a common unified approach across these domains, schema.orgs evolution is pragmatic, driven by the combination of available Web data, and the likelihood of mainstream consuming applications.

Schema.org is also finding new kinds of uses. One exciting line of work is the use of schema.org marked up pages as training corpus for machine learning. John Foley, Michael Bendersky and Vanja Josifovski used schema.org data to build a system that can learn to recognize events that may be geographically local to a particular user. Other researchers are looking at using schema.org pages with similar markup, but in different languages, to automatically create parallel corpora for machine translation.

Four years after its launch, Schema.org is entering its next phase, with more of the vocabulary development taking place in a more distributed fashion, as extensions. As schema.org adoption has grown, a number groups with more specialized vocabularies have expressed interest in extending schema.org with their terms. Examples of this include real estate, product, finance, medical and bibliographic information. A number of extensions, for topics ranging from automobiles to product details, are already underway. In such a model, schema.org itself is just the core, providing a unifying vocabulary and congregation forum as necessary.

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Raspberry Pi Settlers of Catan Server

So a couple of days ago I decided I wanted my Pi to be a Settlers of Catan server.
I decided on using a custom compiled JSettlers version instead of the C++ pioneer version because of the extra perks it had.

It runs surprisingly well considering it is in java but it makes sense since it is making the clients computer do most of the work. I was also decently surprised with the bots. The server allows you to create practice games against bots or real games where other people can sign up to play with you.

It also has multiple scenarios and lots of documentation. Sometimes it is a little buggy but overall Im pretty happy with it as of right now.

Ive uploaded the version I have compiled and an install script. To run it, first you need to have java and apache (or some other web server) installed. If you dont, run:
sudo apt-get install apache2 openjdk-7-*

**Note, you dont need apache to run, you could use others such as NGinx or no web server at all and just play the game by yourself.

Then download the file, unzip it, and install:
wget "https://stevenhickson-code.googlecode.com/files/PiSettlers.tar.gz"
tar -xvf PiSettlers.tar.gz
cd JSettlers2
sudo ./install-web.sh

and now you should be done, you can go to your IP address in any computer on your network and play it.
Mine is at http://192.168.1.100/settlers/
**Note, if you want to play it outside of your network, i.e. you have a domain name, then you need to open port 8880 on your router to go to the pi.

Here is what it looks like playing a game hosted from the pi on my fedora laptop.

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A Comparison of Five Google Online Courses

Posted by Julia Wilkowski, Senior Instructional Designer

Google has taught five open online courses in the past year, reaching nearly 400,000 interested students. In this post I will share observations from experiments with a year’s worth of these courses. We were particularly surprised by how the size of our courses evolved during the year; how students responded to a non-linear, problem-based MOOC; and the value that many students got out of the courses, even after the courses ended.

Observation #1: Course size
We have seen varying numbers of registered students in the courses. Our first two courses (Power Searching versions one and two) garnered significant interest with over 100,000 students registering for each course. Our more recent courses have attracted closer to 40,000 students each. It’s likely that this is a result of initial interest in MOOCs starting to decline as well as students realizing that online courses require significant commitment of time and effort. We’d like other MOOC content aggregators to share their results so that we can identify overall MOOC patterns.

*based on surveys sent only to course completers. Other satisfaction scores represent aggregate survey results sent to all registrants.

Observation #2: Completion rates
Comparing these five two-week courses, we notice that most of them illustrate a completion rate (measured by the number of students who meet the course criteria for completion divided by the total number of registrants) of between 11-16%. Advanced Power Searching was an outlier at only 4%. Why? A possible answer can be found by comparing the culminating projects for each course: Power Searching consisted of students completing a multiple choice test; Advanced Power Searching students completed case studies of applying skills to research problems. After grading their work, students also had to solve a final search challenge.

Advanced Power Searching also differed from all of the other courses in the way it presented content and activities. Power Searching offered videos and activities in a highly structured, linear path; Advanced Power Searching presented students with a selection of challenges followed by supporting lessons. We observed a decreasing number of views on each challenge page similar to the pattern in the linear course (see figure 1).

Figure 1. Unique page views for Power Searching and Advanced Power Searching

Students who did complete Advanced Power Searching expressed satisfaction with the course (95% of course completing students would recommend the course to others, compared with 94% of survey respondents from Power Searching). We surmise that the lower completion rate for Advanced Power Searching compared to Power Searching could be a result of the relative difficulty of this course (it assumed significantly more foundational knowledge than Power Searching), the unstructured nature of the course, or a combination of these and other factors.

Even though completion rates seem low when compared with traditional courses, we are excited about the sheer number of students we’ve reached through our courses (over 51,000 earning certificates of completion). If we offered the same content to classrooms of 30 students, it would take over four and a half years of daily classes to teach the same information!

Observation #3: Students have varied goals
We would also like to move the discussion beyond completion rates. We’ve noticed that students register for online courses for many different reasons. In Mapping with Google, we asked students to select a goal during registration. We discovered that

• 52% of registrants intended to complete the course
• 48% merely wanted to learn a few new things about Google’s mapping tools

Post-course surveys revealed that

• 78% of students achieved the goal they defined at registration
• 89% of students learned new features of Google Maps
• 76% reported learning new features of Google Earth

Though a much smaller percentage of students completed course requirements, these statistics show that many of the students attained their learning goals.

Observation #4: Continued interest in post-course access
After each course ended, we kept many of the course materials (videos, activities) available. Though we removed access to the forums, final projects/assessments, and teaching assistants, we have seen significant interest in the content as measured by Google and YouTube Analytics. The Power Searching course pages have generated nearly three million page views after the courses finished; viewers have watched over 160,000 hours (18 years!) of course videos. In the two months since Mapping with Google finished, we have seen over 70,000 unique visitors to the course pages.

In all of our courses, we saw a high number of students interested in learning online: 96% of Power Searching participants agreed or strongly agreed that they would take a course in a similar format. We have succeeded in teaching tens of thousands of students to be more savvy users of Google tools. Future posts will take an in-depth look at our experiments with self-graded assessments, community elements that enhance learning, and design elements that influence student success.

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The Return of the ZX Spectrum

Esquire reports that the iconic ZX Spectrum may be about to have a comeback. For a brief moment in the 1980s, Britain was a technology superpower, with the iconic ZX Spectrum earning Sir Clive Sinclair his Sir and turning Britain into a fizzing hub of game-creation. OK I didnt actually own a ZX Spectrum back then, but two of my best friends did, and we spent many hours programming games into the ZX. The ZX wasnt just for gaming though; one of my friends wrote a program to check if the bank was charging the correct interest and fees on his fathers bank account - it wasnt. This retro ZX Spectrum is now on my "want-it" list.



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Do androids dream of electric sheep

"Do androids dream of electric sheep?" is the title of a Sci-Fi book by Philip K. Dick upon which the cult movie Blade Runner is based. Well, Google recently investigated this question by setting up feedback loop in its image recognition neural network - which looks for patterns in pictures - thereby creating hallucinatory images of animals, buildings and landscapes. Watch the video below to see what an AI dreams of.


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List of B Sc IT Colleges affiliated to Mumbai University

Search by Name of Colleges

Sr.No.	Name of Colleges (Click here to sort)	Contact No.
1	S.K. Somaiya College of Arts & Commerce, Vidyavihar ,Mumbai- 400 077
2	Lala Lajpatrai College of Commerce & Economics, Lala Lajpatrai Marg, Mahalaxmi, Mumbai- 400 034.
3	Valia Chhaganlal Laljibhai College of Commerce & Arts Andheri (West), Mumbai- 400 053.
4	Sathaye College, Dixit Road, Vile Parle, Mumbai- 400 057.
5	A.V. College of Arts, K.M. College of Commerce and ESA College of Science, Vasai Road, Dist-Thane-401 202.
6	Anjuman-I-Islams Akabar Peerbhoy College of Commerce & Economic, Moulana Shoukat Ali Road, Do Taki, Grant Road Station (East), Mumbai- 400 008.
7	Mulund College of Commerce, Sarojini Naidu Road, Mulund (W), Mumbai-400 080.
8	Guru Nanak Khalsa College of Arts, Science & Commerce, Kings Circle, Near Maheshwari Udyan, Matunga, Mumbai- 400 019.
9	K.M.E. Societys G.M. Momin Womens College, Bhiwandi, Thane Road, Dist-Thane.
10	Shankar Narayan College of Arts & Commerce Mahavidyalaya Marg, Navghar, Navghar Road, Bhayandar (E), Tal. Dist.Thane-401105.
11	St. Gonsalo Garcia College of Arts & Commerce, Behind Vasai Cricket ground, Vasai, Dist.Thane-401 201.
12	Biral College of Arts, Science & Commerce Birla College Road, Kalyan-421 304.
13	Vinayak Ganesh Vaze College of Arts, Science & Commerce, Mulund (East), Mumbai-400 081.
14	Kirti M. Doongursee College, Kashinath Dhuru Road. Off. Savarkar Road, Near Agar Bazar, Dadar (West), Mumbai- 400 028.
15	St. Andrews College of Arts , Science & Commerce St. Domnik Road, Bandra (West), Mumbai- 400 050.
16	Seth L.U. Jhaveri College of Arts, M.V. College of Science & Commerce, Dr.Radhakrishnan Road, Andheri(East) Mumbai- 400 069.
17	Gokhale Education Societys N.B. Mehta (Valwada) Science College, Acharya Bhise Vidyanagar, Bordi, Dist.Thane-401 701.
18	N.M. College of Arts, N.M. Institute of Science & HRJ College of Commerce, (Bhavans College ), Andheri (West), Mumbai- 400 058.
19	Abhinav College of Arts & Commerce Bhyandar (East), Dist.Thane-401 105.
20	B.N. Bandodkar College, Dnyandweep, Chendani Bunder Road, Thane-400 601.
21	Mahatma Education Societys Pillais College of Arts, New Panvel.
22	N.G. Acharya & D.K. Marathe of Arts, Science & Commerce N.G. Acharya Marg, Near Subhash Nagar, Chembur, Mumbai- 400 071.
23	Bhausaheb Vartak Arts, Commerce & Science College, Gorai Road, Borivli (West), Mumbai-400 062.
24	S.S. & L.S. Patkar College of Arts, Science & P.V.P. Varde College of Commerce, S.V. Road, Goregaon (West), Mumbai- 400 062.
25	Vivek College of Commerce, Siddharth Nagar, Goregaon (West), Mumbai- 400 062.
26	Nagindas Khandwala College, Bhardran Nagar Road No.1, Off. S.V.Road, Malad (West), Mumbai-400 064.
27	S.I.W.S. N.R. Swamy College of Commerce & Economics 337, Sewree Wadala Estate, Major R. Parmeshwaran Marg, Wadala, Mumbai- 400 031.
28	Thakur College of Science & Commerce Kandivli (East), Mumbai- 400 101.
29	Vivekanand Education Societys College of Commerce, N.G.Acharya Marg, Sindhi Society, Chembur, Mumbai- 400 071.
30	Vishnu Waman Thakur Charitable Trust Viva College of Arts & Commerce, Virar, Taluka-Vasai, Dist-Thane.
31	South Indian Education Societys College of Arts, Science & Commerce, Sri Chandrasekarendra Saraswathy Vidyapuram, Plot No.1-C, Sector, V, Nerul, Navi Mumbai - 400 706.
32	The South Indian Education Societys College of Commerce, and Economics, Plot No.71/72, Sion-Matunga Estate, Sion (East), Mumbai - 400 022
33	Peoples Education Societys Siddharth College of Commerce Anand bhavan, Dr. D.N. Marg, Fort, Mumbai-400 023.
34	I.C.L.s Motilal Jhunjhunwala Arts, Science and Commerce College, Plot No.53,Sector-9-A, Amlendu Roye Marg, Vashi,Navi Mumbai - 400 703.
35	Mahatma Gandhi Missions College of B.Sc.(Computer Science) Sector-18, Kamothe, Navi Mumbai-410 209.
36	D.G. Ruparel College of Arts, Science and Commerce, Opp. Matunga Road Rly. Stn (WR), Mahim, Mumbai- 400 016.
37	University Department of Information Technology, I.D.E. Building, Room No.207, Vidyanagari, Santacruz(E), Mumbai : 400 098.
38	Smt.Chandibai Himathmal Mansukhani College Post Box No.17,Opp.Ulhasnagar Railway Station, Ulhasnagar, Dist-Thane- 421 003.
39	Vidya Vikas Education Societys Vikas Night College of Arts, Science and Commerce,Kannamwar Nagar -2, Vikhroli (East), Mumbai -400 083
40	K.B. College of Arts and Commerce & S.C. College of Science, Mithbunder Road, Near Hume Pipe Factory, Kopri, Thane (West)-400 603.
41	Ramanand Arya D.A.V.College, Near Datar Colony, Station Road, Bhandup (East), Mumbai- 400 042.
42	K.J. Somaiya College of Science & Commerce, Vidyanagar, Vidyavihar,Mumbai - 400 077.
43	Elphinstone College, 156, M.G. Road, Fort, Mumbai -400 032
44	National Centre for Rural Development`s Sterling College of Arts, Science, & Commerce Plot No. 43, Section 19, Nerul, Navi Mumbai :400 706.
45	The Konkan Gynapeeths Arts, Commerce, and Science College, Karjat, Tal-Karjat, Dist, Raigad-402 107
46	Kishinchand Chellaram College, Dinshaw Wachha Road, Churchgate, Mumbai - 400 020
47	Rishi Dayaram National College of Artrs and Commerce and Wassiamul Assomul Science College, Linking Road, Bandra (West),Mumbai - 400 050.
48	Shahu Shikshan Sansthas College of Arts, Science & Commerce,Gorai, Plot No.2, RSc-34,Gorai-2,Mangal Murti Hospital Road, Near Shivnari Building, Borivli,Mumbai :400 091
49	Dr. Datar Science Dr.Behere Arts and Shri Pilukaka Joshi Commerce College, S.K. Patil Nagar,Chiplun, Tal.Chiplun, Dist-Ratnagiri - 415 605.
50	S.I.E.S. College of Arts, Science & Commerce, Sion (West), Mumbai- 400 022.
51	Dnyan Sadhana College of Arts, Science and Commerce Near Mental Hospital, Service Road, Thane:400 604.
52	Janata Shikshan Mandal, Smt.Indirabia G.Kulkarni Arts, J.B.Sawant Science and Sau.Jankibai Dhondo Kunte Commerce College, Alibag, Dist-Raigad - 402 201.
53	Khalapur Taluka Shikshan Prasarak Mandals Khopoli Municipal Council College, Khopoli, Dist-Raigad-410 203.
54	Nagarik Shikshan Santhas College of Commerce, C/o. Bhausaheb Hirey Vidhyalaya and Jr.College, 94, Tardeo Road, M.P.Mills Compound, Mumbai - 400 034. (not started)
55	Navnirman Shikshan Sansthas College of Arts, Commerce & Science , Mirjoli,Kuwarbav, Tal. Ratnagiri, Dist. Ratnagiri
56	Shikshan Vikas Mandals S. H. Kelkar College of Arts, Science and Commerce, Devgad, Dist-Sindhudurg- 416 613
57	Sundarrao More Arts and Commerce College At Poladpur,Dist-Raigad:402 303.
58	The Education Societys Arts and Commerce College, Kansai Section, Ambernath, Dist-Thane--421 501.
59	Royal Higher Education Society’s College of Arts, Science and Commerce, Ismail M. Kanga Educational Campus, Shrishti Housing Complex, Kashimira, Mira Road, Near Dahisar Checknaka, Dist- Thane.
60	Dhirajlal Talakchand Sankalchand Shah College of Commerce, Kurar Village, Malad (East), Mumbai-400 097.
61	Royal Education Society’s Dr. A.R. Undre Women’s Degree College, Bordi, Panchatan, Tal-Shrivardhan, Dist-Raigad.
62	S.P.K. Mahavidyala Pancham Khem Raj Sawantwadi, Dist- Sindhudurg.
63	Rayat Shikshan Sanstha’s Modern College, Vashi, Sector-15-A, Navi Mumbai-400 703.
64	Sadhubella Education Society’s J. Watumull Sadhubela Girls College, Ulhasnagar, Dist-Thane.
65	Vishweshwar Education Society’s Western College of Commerce & Business Management, Sector-1, Vashi, Navi Mumbai.
66	Anandibai Pradhan College, Nagothane, Dist-Raigad.
67	Shri. Sudhagad Education Society’s Seth Jamshedji Navarousji Paliwala Commerce, Arts and Science College, At Pali (Sudhagad) Dist-Raigad.
68	Janardan Bhagat Shikshan Prasarak Sanstha’s Changu Kana Thakur Arts, Commerce & Science College, Plot No.1, Sector-11, Khanda Colony, New Panvel (West), Dist-Raigad-410 206.
69	Vidyalankar Dnyanpeeth Trust College of B.Sc. (I.T.) Wadala, Mumbai-400 031.
70	Navyug Vidyapeeth Trust College of Science, B.Sc.(Computer Science) B.Sc. (I.T.), B.M.S., Ladvali, Tal.Mahad, Dist.Thane.
71	Oriental Education Society College of Arts ,Science and Commerce, B.M.S., B.Sc.(I.T.), Adarsh Nagar, Andheri (West), Mumbai-400 102.
72	Tilak Education Society`s College of Arts & Commerce, Plot No 131, Sector 28, Vashi, Navi Mumbai : 400 705.
73	Smt.Kamladevi Gauridatta Mittal College of Arts and Commerce, Marwari Vidyalaya, Bhandarwada, Gaothan Road, Rajanpada, Malad (West),Mumbai - 400 066.
74	Pragati Arts & Commerce College, Dombivli (East).
75	Uttar Bhartiya Sangh College of B.Sc. (I.T.),B.M.S. B.Sc., Bandra (East), Mumbai- 400 051.
76	N.S. Dixit Educational Foundation College of Science, B.Sc.(Compute Science), B.Sc. I.T., & B.M.S. Dadar (West), Mumbai- 400 028.
77	Shri Vile Parle Kelvani Mandals Usha Pravin Gandhi College of Management, Shri Bhaidas Maganlal Sabhagriha Building, North-South Road No.1, Juhu Scheme, Vile Parle (West), Mumbai- 400 0563.
78	Parle Tilak Vidyalaya Association`s Mulund College of Commerce , Sarojini Naidu Road, Mulund(West), Mumbai - 400 080.
79	Khar Education Society`s College of Commerce And Economics, Khar, Mumbai..
80	Keraleeya Samajam Dombivlis Model College,6 Near Police Colony, Plot No.32, Phase-II, MIDC, Residential Area, Dombivli(East), Dist-Thane: 421 203.
81	Chinchni Tarapur Education Societys Shri Purshottamdas Laldas Shroff College of Arts & Commerce Mhavidyalaya, Chinchani,Dist-Thane- 401 503.
82	Maharashtra College of Arts, Science and Commerce, 246-A, Bellasis Road, Byculla, Mumbai - 400 008.
83	Parle Tilak Vidyalaya Association`s M.L.Dahanukar 2005-2006 College of Commerce, Dixit Road, Vile Parle (East), Mumbai - 400 057.
84	Dnyan Prasarak Shikshan Sanstha`s Sandesh College of Commerc, Tagor Nagar,Vikroli (E), Mumbai : 400 083.
85	Seva Sadan`s R.K.TalrejaCollege of Arts, Science and Commerce, Ulhasnagar, Dist- Thane - 421 003.
86	Shree Sudhirji Madhavaji lal Welfare, & Education Trust’s,The Lords College of Commerce & Science & B.M.S, Daftarry Road, Opp. Railway Station, Malad (E),Mumbai – 400 097.
87	Jnan Vikas Mandals Mohanlal Raichand Mehta, College of Commmerces Diwali Maa College of Science,’Amritlal Raichand Mehta College of Arts, Dr. R.T.Joshi College of computer Science, Plot No. 9 Sector 19,Aroli, Navi Mumbai – 400 708.
88	Nirmala Memorial Foundation Degree College of Commerce Nr. Thakur Polytechnic, 90 Feet Road, Thakur Complex, Kandivli (East), Mumbai-400 101.
89	Sadhana Education Society’s L.S. Raheja College of Arts & Commerce , Juhu Road, Santacruz (West), Mumbai-400 054.
90	St. Xavier’s College, 5 Mahapalika Marg, Mumbai-400 001.
91	Bhavana Trust’s College of Commerce & B.Sc.(Computer Science) Chembur, Devnar, Mumbai-400 088.
92	Hindi Vidya Prachar Samiti’s Ramniranjan Jhunjhunwala College Opp. Railway Station, Ghatkopar (W), Mumbai-400 086.
93	The Gurunanak Vidyak Society’s College of Arts, Science & Commerce , Punjabi Colony, Guru Tegh Bahadur Nagar, Sion (East), Mumbai-400 037.
94	Wilson College Chowpatty, Mumbai-400 007.
95	Sanpada College of Commerce & Technology, Sector-2, Plot No. 3, 4 5, Behind Sanpada Stn., Sanpada (W), Navi Mumbai-400 705.
96	Abhinav Shetkari Shikshan Mandal’s Abhinav College of Arts, Science & Commerce , Plot No.43, Sector-19, Nerul, Navi Mumbai-400 705.
97	Sonubhau Baswant College of Arts & Commerce, Nr. Govt. Godown, Savroli Road, Shahapur, Dist : Thane-421 601.
98	The East Kalyan Welfare Society’s Model College of Science & Commerce, East Kalyan Welfare Society Building, Chinchpada Road, Rajbhar Nagar, Katemanivali Kalyan (East), Dist : Thane-421 306
99	Haji Jamaluddin Thim Trust College of BHTMS, M.B.M.S.& B.Sc (Computer Science),
100	K.M. Agarwal College of Arts, Commerce & Science M.K. High School Bldg., Agra Road, Kalyan Dist : Thane.
101	Seth Hirachand Mutha Shaikshanik Trust College of Arts, Commerce & Science, Koliwali, Kalyan (West), Dist : Thane
102	M.S.P.Mandal’s G.R. Patil College of Arts & Commerce Dombivli, Dist : Thane
103	Padmashri Annasaheb Jadhav Bharatiya Samaj Unnati Mandal’s Bhiwandi Nizampur Nagarpalika Arts, Science & Commerce College Bhiwandi, Dist : Thane – 421 305.
104	Konkane’s Kohinoor Technical Trust’s College of Hostel & Tourism Management Studies (B.H.T.M.S.), Bhatye, Ratnagiri-Pawas Coastal Highway, Tal & Dist : Ratnagiri
105	The Kandivli Education Societys Arts & Commerce College, Shantilal Modi Road, Kandivli (West), Mumbai- 400 067
106	Esplanade Education Society’s Niranjana Majithia College of Commerce, Bohra Colony, M.G. Road, Kandivli (W), Mumbai
107	Rajasthani Seva Sangha’s College of Arts and Commerce  Sriniwas Bagarkar Marg, J.B. Nagar, Andheri (East), Mumbai - 400 059.
108	Sanskardham Kelvani Mandals Jashbhai  Maganbhai Patel College of Commerce, Unnat Nagar, M.G.Road, Off.Ganapati Stores, Goregaon (West), Mumbai: 400 062.
109	Hind Seva Parishads Public Night Degree College of Arts and Commerce, Hind Nagar, Vakola Market, AARAM Society Road, Santacruz (East), Mumbai - 400 055.
110	Shri. Hari Educational Trust’s St. Rock’s College of Commerce, Talepakhdi, Eksar Village, Near Aquaria Club, Borivali (W), Mumbai.
111	Peoples Education Societys Dr.Ambedkar College of Commerce & Economics, Tilak Road, Wadala, Mumbai - 400 031.
112	Janardan Bhagat Shikshan Prasarak Sansthas Changu Kana Thakur Arts, Commerce and Science College, Plot No.01, Sector-11, Khanda Colony, New Panvel - 410 206.
113	Habib Educational & Welfare Society’s Arts,  Commerce, Science and B.M.S. Mumbra, Dist.Thane.
114	Thane Zilla Agri Shikshan Prasarak Mandal`s Pragati College of Arts and Commerce, D.N.K. Road, Dattata Nagar, Dombivli (East), Dist: Thane: 421 201.
115	Navnirman Shikshan Sansthas College of Arts, Commerce & Science, Mirjoli, Kuwarbav, Tal. Ratnagiri, Dist. Ratnagiri.
116	Shrimati Indira Mahadev Behere College of Arts Shriman Chandulal Sheth Commerce and Shrimati Shobhanatai Chandulal Sheth College of Science, Khed, Dist- Ratnagiri - 415 709
117	S.S.T. College of Arts and Commerce, Sahara Complex, First Floor, Fountain Section 25, Ulhasnagar- 421 004.
118	Pradnya Karuna Bahuodeshiya Shikshan Sanstha’s Arts, Commerce and Science, Kalyan (E), Dist. Thane.
119	Mangaon Shikshan Prasarak Mandals Senior College of Arts and Science, At -Post Mangaon, Dist-Raigad.
120	Tilak Education Society’s S.K. College of Science & Commerce at Nerul, New Mumbai.
121	Sarvadnya Education and Research Society’s College of Commerce & Science at Ghansoli, New Mumbai.
122	Jawaharlal Nehru Institute of Education Yashwantrao Chavan College of Arts, Commerce & Science at Sector- 15, Koper-khairane, New Mumbai.
123	Shri Dombivli Mitra Mandal’s College of Science & Commerce, at Diva-Vasai Rail Route(Kopargaon), Dombivli.
124	Smt. Durga Devi Sharma Charitable Trust’s Chandrabhan Sharma College of Arts, Commerce & Science at- Powai Vihar, Mumbai- 400 076.
125	Pune Vidyarthi Griha’s College of Science & Technology, CTS 128, Br. Nath Pai Nagar, Kurla-Powai Road, Ghatkopar(East), Mumbai-400 077.
126	Uran Education Society’s College of B.Sc.(I.T.) at Uran, Dist- Raigad.
127	Karnala Sports Academy’s KSA’s Barns College of Arts, Science & Commerce At Plot No.7, Sector-16, Behind HOC Colony, New Panvel(West).
128	Pragat Samajik Shikshan Society’s Dr. Babasaheb Ambedkar Science and Advocate Gurunath Kulkarni Commerce, Mahavidyalaya at Vasai(West).
129	Bunts Sangha’s S.M. Shetty College of Science Commerce and Management Studies at S.M. Shetty High School and Jr. College, Nr. Hiranandani Complex, Powai, Mumbai- 400 076.
130	Rahul Shikshan Prasarak Mandal’s Satyagraha Mahavidyalaya, at Supparak Bhavan, Plot No.52, Sector – 19, Kharghar, Navi Mumbai- 410 210.
131	Pillai’s HOC College of Science, At – Rasayani, Tal- Khalapur, Dist – Raigad.
132	Shubhankaroti Charitable & Education Trust’s Vasai College of Science & Technology, At – Manickput, Vasai Road(West ), Dist-Thane.
133	Bhavik Vidya Prasarak Mandal’s Jai Bhavani College, Near Vitava Octroi Naka, Vitava, Kalwa, Dist-Thane.
134	Ujwal Shikshan Sanstha’s College of Computer Science & Information Technology at Mhada Vasahat, Akurli Rd., Kandivali (East), Mumbai- 400 101.

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Microsoft announces release of universal translator

The Guardian reports that Microsoft is to release a near real time voice translator as Skype Translator by the end of this year. The service will first appear on Windows 8 but is expected to be rolled out to other platforms quickly. In a demo at the Code conference Skype Translator translated English to German and vice versa nearly perfectly. The video below explains how this works.


from The Universal Machine http://universal-machine.blogspot.com/

Put the internet to work for you.

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Automatically making sense of data

Posted by Kevin Murphy, Research Scientist and David Harper, Head of University Relations, EMEA

While the availability and size of data sets across a wide range of sources, from medical to scientific to commercial, continues to grow, there are relatively few people trained in the statistical and machine learning methods required to test hypotheses, make predictions, and otherwise create interpretable knowledge from this data. But what if one could automatically discover human-interpretable trends in data in an unsupervised way, and then summarize these trends in textual and/or visual form?

To help make progress in this area, Professor Zoubin Ghahramani and his group at the University of Cambridge received a Google Focused Research Award in support of The Automatic Statistician project, which aims to build an "artificial intelligence for data science".

So far, the project has mostly been focussing on finding trends in time series data. For example, suppose we measure the levels of solar irradiance over time, as shown in this plot:This time series clearly exhibits several sources of variation: it is approximately periodic (with a period of about 11 years, known as the Schwabe cycle), but with notably low levels of activity in the late 1600s. It would be useful to automatically discover these kinds of regularities (as well as irregularities), to help further basic scientific understanding, as well as to help make more accurate forecasts in the future.

We can model such data using non-parametric statistical models based on Gaussian processes. Such methods require the specification of a kernel function which characterizes the nature of the underlying function that can accurately model the data (e.g., is it periodic? is it smooth? is it monotonic?). While the parameters of this kernel function are estimated from data, the form of the kernel itself is typically specified by hand, and relies on the knowledge and experience of a trained data scientist.

Prof Ghahramanis group has developed an algorithm that can automatically discover a good kernel, by searching through an open-ended space of sums and products of kernels as well as other compositional operations. After model selection and fitting, the Automatic Statistician translates each kernel into a text description describing the main trends in the data in an easy-to-understand form.

The compositional structure of the space of statistical models neatly maps onto compositionally constructed sentences allowing for the automatic description of the statistical models produced by any kernel. For example, in a product of kernels, one kernel can be mapped to a standard noun phrase (e.g. ‘a periodic function’) and the other kernels to appropriate modifiers of this noun phrase (e.g. ‘whose shape changes smoothly’, ‘with growing amplitude’). The end result is an automatically generated 5-15 page report describing the patterns in the data with figures and tables supporting the main claims. Here is an extract of the report produced by their system for the solar irradiance data:

Extract of the report for the solar irradiance data, automatically generated by the automatic statistician.

The Automatic Statistician is currently being generalized to find patterns in other kinds of data, such as multidimensional regression problems, and relational databases. A web-based demo of a simplified version of the system was launched in August 2014. It allowed a user to upload a dataset, and to receive an automatically produced analysis after a few minutes. An expanded version of the service will be launched in early 2015 (we will post details when available). We believe this will have many applications for anyone interested in Data Science.

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Collection of SQL queries with Answer and Output Set 3

Here is a collection or a list of 38 SQL Queries with Answers as well as output. You can write your answer at the text box below each query any time you can see the table structure by clicking on Table Structure. And check your Answer by clicking on Answer. You can test your Skill in SQL. You can also go for an online Quiz in SQL in one of my previous posts: Click here for Quiz. More queries will be added to this post within few days, visit again!!!

Happy learning!!!
Carry on....
You can also share your queries in this site. Use this Link to share your part with the visitors like you.

SQL Query collection: Set1 Set2 Set3 Set 4

Below is the Table Structure using which you have to form the queries:


1) Who is the highest paid C programmer?

Table Structure

Write your answer hereAnswer

SELECT * FROM PROGRAMMER
WHERE SALARY=(SELECT MAX(SALARY)
FROM PROGRAMMER
WHERE PROF1 LIKE C OR PROF2 LIKE C)

2) Who is the highest paid female cobol programmer?

Table Structure

Write your answer hereAnswer

SELECT * FROM PROGRAMMER
WHERE SALARY=(SELECT MAX(SALARY)
FROM PROGRAMMER
WHERE (PROF1 LIKE COBOL OR PROF2 LIKE COBOL))
AND SEX LIKE F

3) Display the name of the HIGEST paid programmer for EACH language (prof1)

Table Structure

Write your answer hereAnswer

SELECT DISTINCT NAME, SALARY, PROF1
FROM PROGRAMMER
WHERE (SALARY,PROF1) IN (SELECT MAX(SALARY),PROF1
FROM PROGRAMMER
GROUP BY PROF1)

4) Who is the LEAST experienced programmer?

Table Structure

Write your answer hereAnswer

SELECT FLOOR((SYSDATE-DOJ)/365) EXP,NAME
FROM PROGRAMMER
WHERE FLOOR((SYSDATE-DOJ)/365) = (SELECT MIN(FLOOR((SYSDATE-DOJ)/365))
FROM PROGRAMMER)

5) Who is the MOST experienced programmer?

Table Structure

Write your answer hereAnswer

SELECT FLOOR((SYSDATE-DOJ)/365) EXP,NAME,PROF1,PROF2
FROM PROGRAMMER
WHERE FLOOR((SYSDATE-DOJ)/365) = (SELECT MAX(FLOOR((SYSDATE-DOJ)/365))
FROM PROGRAMMER)
AND (PROF1 LIKE COBOL OR PROF2 LIKE COBOL)

6) Which language is known by ONLY ONE programmer?

Table Structure

Write your answer hereAnswer

SELECT PROF1
FROM PROGRAMMER
GROUP BY PROF1
HAVING PROF1 NOT IN
(SELECT PROF2 FROM PROGRAMMER)
AND COUNT(PROF1)=1
UNION
SELECT PROF2
FROM PROGRAMMER
GROUP BY PROF2
HAVING PROF2 NOT IN
(SELECT PROF1 FROM PROGRAMMER)
AND COUNT(PROF2)=1;

7) Who is the YONGEST programmer knowing DBASE?

Table Structure

Write your answer hereAnswer

SELECT FLOOR((SYSDATE-DOB)/365) AGE, NAME, PROF1, PROF2
FROM PROGRAMMER
WHERE FLOOR((SYSDATE-DOB)/365) = (SELECT MIN(FLOOR((SYSDATE-DOB)/365))
FROM PROGRAMMER
WHERE PROF1 LIKE DBASE OR PROF2 LIKE DBASE)

8) Which institute has MOST NUMBER of students?

Table Structure

Write your answer hereAnswer

SELECT SPLACE
FROM STUDIES
GROUP BY SPLACE
HAVING COUNT(SPLACE)= (SELECT MAX(COUNT(SPLACE))
FROM STUDIES GROUP BY SPLACE)

9) Who is the above programmer?

Table Structure

Write your answer hereAnswer

SELECT NAME
FROM PROGRAMMER
WHERE PROF1 IN (SELECT PROF1
FROM PROGRAMMER
GROUP BY PROF1
HAVING PROF1 NOT IN (SELECT PROF2 FROM PROGRAMMER)
AND COUNT(PROF1)=1
UNION
SELECT PROF2
FROM PROGRAMMER
GROUP BY PROF2
HAVING PROF2 NOT IN (SELECT PROF1 FROM PROGRAMMER)
AND COUNT(PROF2)=1))
UNION
SELECT NAME
FROM PROGRAMMER
WHERE PROF2 IN (SELECT PROF1
FROM PROGRAMMER
GROUP BY PROF1
HAVING PROF1 NOT IN (SELECT PROF2 FROM PROGRAMMER)
AND COUNT(PROF1)=1
UNION
SELECT PROF2
FROM PROGRAMMER
GROUP BY PROF2
HAVING PROF2 NOT IN (SELECT PROF1 FROM PROGRAMMER)
AND COUNT(PROF2)=1))

10) Which female programmer earns MORE than 3000/- but DOES NOT know C, C++, Oracle or Dbase?

Table Structure

Write your answer hereAnswer

SELECT * FROM PROGRAMMER
WHERE SEX LIKE F
AND SALARY >3000
AND (PROF1 NOT IN(C,C++,ORACLE,DBASE)
OR PROF2 NOT IN(C,C++,ORACLE,DBASE))

11) Which is the COSTLIEST course?

Table Structure

Write your answer hereAnswer

SELECT COURSE
FROM STUDIES
WHERE CCOST = (SELECT MAX(CCOST) FROM STUDIES)

12) Which course has been done by MOST of the students?

Table Structure

Write your answer hereAnswer

SELECT COURSE
FROM STUDIES
GROUP BY COURSE
HAVING COUNT(COURSE)= (SELECT MAX(COUNT(COURSE))
FROM STUDIES
GROUP BY COURSE)

13) Display name of the institute and course Which has below AVERAGE course fee?

Table Structure

Write your answer hereAnswer

SELECT SPLACE,COURSE
FROM STUDIES
WHERE CCOST < (SELECT AVG(CCOST) FROM STUDIES)

14) Which institute conducts COSTLIEST course?

Table Structure

Write your answer hereAnswer

SELECT SPLACE
FROM STUDIES
WHERE CCOST = (SELECT MAX(CCOST) FROM STUDIES)

15) Which course has below AVERAGE number of students?

Table Structure

Write your answer hereAnswer

SELECT COURSE
FROM STUDIES
HAVING COUNT(NAME)<(SELECT AVG(COUNT(NAME))
FROM STUDIES
GROUP BY COURSE)
GROUP BY COURSE;

16) Which institute conducts the above course?

Table Structure

Write your answer hereAnswer

SELECT SPLACE
FROM STUDIES
WHERE COURSE IN (SELECT COURSE
FROM STUDIES
HAVING COUNT(NAME) < (SELECT AVG(COUNT(NAME))
FROM STUDIES
GROUP BY COURSE)
GROUP BY COURSE);

17) Display names of the course WHOSE fees are within 1000(+ or -) of the AVERAGE fee.

Table Structure

Write your answer hereAnswer

SELECT COURSE
FROM STUDIES
WHERE CCOST < (SELECT AVG(CCOST)+1000 FROM STUDIES)
AND CCOST > (SELECT AVG(CCOST)-1000 FROM STUDIES)

18) Which package has the HIGEST development cost?

Table Structure

Write your answer hereAnswer

SELECT TITLE,DCOST
FROM SOFTWARE
WHERE DCOST = (SELECT MAX(DCOST) FROM SOFTWARE)

19) Which package has the LOWEST selling cost?

Table Structure

Write your answer hereAnswer

SELECT TITLE,SCOST
FROM SOFTWARE
WHERE SCOST = (SELECT MIN(SCOST) FROM SOFTWARE)

20) Who developed the package, which has sold the LEAST number of copies?

Table Structure

Write your answer hereAnswer

SELECT NAME,SOLD
FROM SOFTWARE
WHERE SOLD = (SELECT MIN(SOLD) FROM SOFTWARE)

21) Which language was used to develop the package WHICH has the HIGEST sales amount?

Table Structure

Write your answer hereAnswer

SELECT DEV_IN,SCOST
FROM SOFTWARE
WHERE SCOST = (SELECT MAX(SCOST) FROM SOFTWARE)

22) How many copies of the package that has the LEAST DIFFRENCE between development and selling cost were sold?

Table Structure

Write your answer hereAnswer

SELECT SOLD,TITLE
FROM SOFTWARE
WHERE TITLE = (SELECT TITLE
FROM SOFTWARE
WHERE (DCOST-SCOST)=(SELECT MIN(DCOST-SCOST) FROM SOFTWARE))

23) Which is the COSTLIEAST package developed in PASCAL?

Table Structure

Write your answer hereAnswer

SELECT TITLE
FROM SOFTWARE
WHERE DCOST = (SELECT MAX(DCOST)
FROM SOFTWARE
WHERE DEV_IN LIKE PASCAL)

24) Which language was used to develop the MOST NUMBER of package?

Table Structure

Write your answer hereAnswer

SELECT DEV_IN FROM SOFTWARE
GROUP BY DEV_IN
HAVING MAX(DEV_IN) = (SELECT MAX(DEV_IN) FROM SOFTWARE)

25) Which programmer has developed the HIGEST NUMBER of package?

Table Structure

Write your answer hereAnswer

SELECT NAME FROM SOFTWARE
GROUP BY NAME
HAVING MAX(NAME) = (SELECT MAX(NAME) FROM SOFTWARE)

26) Who is the author of the COSTLIEST package?

Table Structure

Write your answer hereAnswer

SELECT NAME,DCOST
FROM SOFTWARE
WHERE DCOST = (SELECT MAX(DCOST) FROM SOFTWARE)

27) Display names of packages WHICH have been sold LESS THAN the AVERAGE number of copies?

Table Structure

Write your answer hereAnswer

SELECT TITLE
FROM SOFTWARE
WHERE SOLD < (SELECT AVG(SOLD) FROM SOFTWARE)

28) Who are the female programmers earning MORE than the HIGEST paid male programmers?

Table Structure

Write your answer hereAnswer

SELECT NAME
FROM PROGRAMMER
WHERE SEX LIKE F
AND SALARY > (SELECT(MAX(SALARY))
FROM PROGRAMMER
WHERE SEX LIKE M)

29) Which language has been stated as prof1 by MOST of the programmers?

Table Structure

Write your answer hereAnswer

SELECT PROF1
FROM PROGRAMMER
GROUP BY PROF1
HAVING PROF1 = (SELECT MAX(PROF1)
FROM PROGRAMMER)

30) Who are the authors of packages, WHICH have recovered MORE THAN double the development cost?

Table Structure

Write your answer hereAnswer

SELECT NAME distinct
FROM SOFTWARE
WHERE SOLD*SCOST > 2*DCOST

31) Display programmer names and CHEAPEST package developed by them in EACH language?

Table Structure

Write your answer hereAnswer

SELECT NAME,TITLE
FROM SOFTWARE
WHERE DCOST IN (SELECT MIN(DCOST)
FROM SOFTWARE
GROUP BY DEV_IN)

32) Who is the YOUNGEST male programmer born in 1965?

Table Structure

Write your answer hereAnswer

SELECT NAME
FROM PROGRAMMER
WHERE DOB=(SELECT (MAX(DOB))
FROM PROGRAMMER
WHERE TO_CHAR(DOB,YYYY) LIKE 1965)

33) Display language used by EACH programmer to develop the HIGEST selling and LOWEST selling package.

Table Structure

Write your answer hereAnswer

SELECT NAME, DEV_IN
FROM SOFTWARE
WHERE SOLD IN (SELECT MAX(SOLD)
FROM SOFTWARE
GROUP BY NAME)
UNION
SELECT NAME, DEV_IN
FROM SOFTWARE
WHERE SOLD IN (SELECT MIN(SOLD)
FROM SOFTWARE
GROUP BY NAME)

34) Who is the OLDEST female programmer WHO joined in 1992

Table Structure

Write your answer hereAnswer

SELECT NAME
FROM PROGRAMMER
WHERE DOJ=(SELECT (MIN(DOJ))
FROM PROGRAMMER
WHERE TO_CHAR(DOJ,YYYY) LIKE 1992)

35) In WHICH year where the MOST NUMBER of programmer born?

Table Structure

Write your answer hereAnswer

SELECT DISTINCT TO_CHAR(DOB,YYYY)
FROM PROGRAMMER
WHERE TO_CHAR(DOJ,YYYY) = (SELECT MIN(TO_CHAR(DOJ,YYYY))
FROM PROGRAMMER)

36) In WHICH month did MOST NUMBRER of programmer join?

Table Structure

Write your answer hereAnswer

SELECT DISTINCT TO_CHAR(DOJ,MONTH)
FROM PROGRAMMER
WHERE TO_CHAR(DOJ,MON) = (SELECT MIN(TO_CHAR(DOJ,MON))
FROM PROGRAMMER)

37) In WHICH language are MOST of the programmers proficient?

Table Structure

Write your answer hereAnswer

SELECT PROF1
FROM PROGRAMMER
GROUP BY PROF1
HAVING COUNT(PROF1)=(SELECT MAX(COUNT(PROF1))
FROM PROGRAMMER
GROUP BY PROF1)
OR COUNT(PROF2)=(SELECT MAX(COUNT(PROF2))
FROM PROGRAMMER
GROUP BY PROF2)
UNION
SELECT PROF2
FROM PROGRAMMER
GROUP BY PROF2
HAVING COUNT(PROF1)=(SELECT MAX(COUNT(PROF1))
FROM PROGRAMMER
GROUP BY PROF1)
OR COUNT(PROF2)=(SELECT MAX(COUNT(PROF2))
FROM PROGRAMMER
GROUP BY PROF2)

38) Who are the male programmers earning BELOW the AVERAGE salary of female programmers?

Table Structure

Write your answer hereAnswer

SELECT NAME
FROM PROGRAMMER
WHERE SEX LIKE M
AND SALARY < (SELECT(AVG(SALARY))
FROM PROGRAMMER
WHERE SEX LIKE F)

SQL Query collection: Set1 Set2 Set3 Set 4

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