Brother MFC-J450DW Inkjet Multifunction Printer

Brother MFC-J450DW Inkjet Multifunction Printer

When you’re selecting a color inkjet all-in-one for your home or home office, you want a machine that’s going to offer you easy, intuitive operation, plenty of connectivity options, and fast print speeds – all without breaking your budget. The Brother MFC-J450DW, part of the new Work Smart Series, may be exactly what you’re looking for! It helps improve your productivity with print speeds up to 33 ppm black/27 ppm color in fast mode and ISO print speeds up to 12 ppm black/10 ppm color. It’s compact, so it won’t waste your valuable work space, holds up to 100 sheets in the paper tray, and makes it easy to print, copy, scan and fax your important business documents.

Technical Information

Multifunction Devices:   Copier/Fax/Printer/Scanner
Recommended Use:   Plain Paper Print
Print Color:   Color
Maximum Mono Print Speed (ppm):   33
Maximum Color Print Speed (ppm):   27
ISO Mono Print Speed (ipm):   12
ISO Color Print Speed (ipm):   10
Maximum Print Resolution:   6000 x 1200 dpi
Wireless Print Technology:   Apple AirPrint
Wireless Print Technology:   Brother iPrint&Scan
Wireless Print Technology:   Google Cloud Print
Duplex Printing:   Automatic
Color Cartridge Type:   Individual Color Cartridge
Number of Colors:   4
Mobile Device Printing:   Yes


Standard Memory:   64 MB


USB:   Yes
USB Standard:   USB 2.0

Network & Communication

Wireless LAN:   Yes
Wireless LAN Standard:   IEEE 802.11b/g/n

Display & Graphics

Screen Size:   1.8″
Display Screen Type:   LCD


Scanner Type:   Flatbed
Maximum Scan Size:   8.4″ (213.9 mm) x 13.9″ (353.6 mm)
Scan Color:   Color
Optical Resolution:   1200 dpi
Hardware Resolution:   1200 x 2400 dpi
Interpolated Resolution:   19200 x 19200 dpi
Color Depth:   30-bit
Grayscale Depth:   10-bit


Copier Type:   Flatbed
Copy Color:   Color
ISO Mono Copy Speed (ipm):   5
ISO Color Copy Speed (ipm):   5
Maximum Copy Resolution:   1200 x 2400 dpi
Maximum Document Enlargement:   400%
Maximum Document Reduction:   25%
Number of Copies:   99


Fax Color:   Color
Maximum Fax Resolution:   203 x 392 dpi
Modem Speed:   14.40 Kbps
Fax Memory Capacity:   170 pages
Fax Compliant:   Group 3

Media Types & Handling

Borderless Printing:   Yes
Media Type:   Coated Paper
Media Type:   Envelope
Media Type:   Plain Paper
Media Type:   Transparency
Media Type:   Glossy Paper
Media Type:   Inkjet Paper
Media Size:   A4 – 8.3″ (210.8 mm) x 11.7″ (297.2 mm)
Media Size:   A5 – 5.8″ (147.3 mm) x 8.3″ (210.8 mm)
Media Size:   C5 Envelope – 9″ (228.6 mm) x 6.7″ (169.7 mm)
Media Size:   Com10 Envelope – 4.8″ (121.9 mm) x 9.5″ (241.3 mm)
Media Size:   Executive – 10.5″ (266.7 mm) x 7.3″ (184.2 mm)
Media Size:   Index Card – 5″ (127 mm) x 8″ (203.2 mm)
Media Size:   Legal – 8.5″ (215.9 mm) x 14″ (355.6 mm)
Media Size:   Photo – 4″ (101.6 mm) x 6″ (152.4 mm)
Media Size:   A6 – 4.1″ (104.1 mm) x 5.8″ (147.3 mm)
Media Size:   DL Envelope – 4.3″ (109.2 mm) x 8.6″ (218.4 mm)
Media Size:   Letter – 8.5″ (215.9 mm) x 11″ (279.4 mm)
Media Size:   Monarch Envelope
Media Size:   Photo-2L – 5″ (127 mm) x 7″ (177.8 mm)
Maximum Print Size:   Legal – 8.5″ (215.9 mm) x 14″ (355.6 mm)
Media Handling:   1 x Automatic Document Feeder 20 Sheet
Media Handling:   1 x Input Tray 100 Sheet
Media Handling:   1 x Output Tray 50 Sheet
Number of Input/Multipurpose Trays Installed:   1
Number of Input Trays Supported:   1
Standard Input Media Capacity:   100 sheets
Maximum Input Media Capacity:   100 sheets

Software Included

Scansoft PaperPort® v12 SE with OCR for Windows®
Presto!® PageManager® for Mac®


Duty Cycle:   2500 pages per month

Power Description

Power Source:   AC Supply
Input Voltage:   110 V AC
Operating Power Consumption:   19 W
Off-Mode Power Consumption:   200 mW
Sleep-Mode Power Consumption:   1.10 W

Physical Characteristics

Form Factor:   Desktop
Color:   Black
Height:   7.1″ (180.3 mm)
Width:   16.1″ (408.9 mm)
Depth:   14.7″ (373.4 mm)
Weight (Approximate):   8.90 kg

Package Contents

MFC-J450DW Inkjet Multifunction Printer
(4) Cartridges L101 Series
CD-ROM – Assembly for Windows and Mac
User’s Manual
Quick Setup Guide
Telephone Line Cord

Windows System Requirements

Windows 7, 8: 32 or 64-bit processor, 650 MB (drivers only) or 1.3 GB (drivers & applications
Vista: 32 or 64-bit processor, 500 MB (drivers only) or 1.3 GB (drivers & applications)
XP: 32 or 64-bit processor, 150 MB (drivers only) or 1.0 GB (drivers & applications)

Mac System Requirements

Intel processor, 80 MB (drivers only) or 550 MB (drivers & applications)

Certifications & Standards

Platform Supported:   Mac
Platform Supported:   PC
Recycled:   No
Recycled Content:   0%
Post-consumer-waste%:   0%
Assembly Required:   No

Brother MFC-J450DW Inkjet Multifunction Printer


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Getting to Know a Ph.D.

At Google, there are many opportunities for Ph.D. students to gain industry experience. Check out the story of Alessandro Epasto, a former Google European Doctoral Fellowship recipient, who interned on three different teams at Google, working on impactful projects across Google+, AdWords and different engineering and research teams.


Alessandro, tell us about yourself and your Ph.D. topic. 

I come from Italy where I completed my Ph.D. in Computer Science at the Ph.D. School of the Department of Computer Science at Sapienza University of Rome. The focus of my Ph.D. thesis and my main research interest is graph mining — in particular the study of algorithmic problems arising when analysing large-scale graphs. Graphs, or networks, are increasingly becoming the lingua franca of data mining (and Big Data), as they can be used to represent and analyse arbitrary relationships between arbitrary entities (including social networks, mobile networks and the Web, for instance).

The focus of my thesis was designing and evaluating efficient algorithms for extracting meaningful information from very large-scale graphs (with billions of nodes and edges), in which data might dynamically evolve at high speed. In particular, I have been interested in the problems of graph clustering, similarity rankings and in the study of information diffusion on social networks. All of these problems have important practical applications ranging from recommendation system design to social network security as well as a theoretical interest for the understanding of social behaviour. In this context, my aim was to design methods that are both practical and able to provide theoretical guarantees on their correctness.

Why did you apply for an internship at Google and how supportive was your Ph.D. advisor?
Before my internship at Google, my experience was mostly in academia. I was very curious about the challenges that a company with such amounts of data deals with every day. Moreover, I was extremely interested in experiencing the stimulating environment and culture at Google. I was advised by professor Alessandro Panconesi who was very supportive and encouraged me to apply for an internship at Google. 

You interned three times at Google. What projects were you focused on?
Each of the three times I interned, I had the opportunity to work on a distinct research problem with different research groups.

During my most recent internship I joined the Google+ group in the Mountain View, California headquarters working with Sunita Verma. We worked on the problem of friend suggestion, which deals with the challenging issue of suggesting to a given user the people he/she may be interested in adding as a friend. This is an important problem for online social networks, as receiving good friend suggestions significantly improves the user experience.

In one of my previous internships, I joined the AdWords team in New York City working with Jon Feldman where I worked on the problem of automatically identifying, for any given advertiser, who their main competitors in the AdWords system are. 

During my first internship in Mountain View working with Alon Altman I worked on defining algorithms for detecting potential attacks in the Google+ network. 

Could you share more details about the outcomes of your collaboration with teams at Google?
During all my internships I had the opportunity to closely collaborate with researchers in other teams at Google, in particular with the Graph Mining team in Google Research NY led by Vahab Mirrokni, who is also my Google Doctoral Fellowship mentor. A productive collaboration has continued even after the end of my internships. This joint collaboration with researchers at Google and at Sapienza University has also led to a publication awarded with the best paper award at the 2015 ACK SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).

While the three problems addressed in my internships have very different applications and independent interest, perhaps surprisingly, they can all be tackled by using related graph mining techniques. Both Google+ and AdWords datasets can, in fact, be modeled as a very large scale graph (or network).

In this context, one is interested in designing algorithms that can extract the information needed efficiently (the friends of a user, the competitors of a company, the potential spam users, etc.) while working at Google scale. In all of my internships I also had the opportunity to implement and test these algorithms in the powerful MapReduce infrastructure available at Google on extremely large datasets with billions of entities.

The approach at Google in evaluating the results of projects is very academic in the sense that rigorous empirical evaluations are conducted to show that the approach proposed actually improves over the state-of-the-art. I was also able to share some results of my work with the public through academic publications.

Did you publish at Google during your internship?
Yes, we successfully published a paper at the 2014 International World Wide Web Conference (WWW) as a result of my internship on the AdWords team in NYC. Moreover, we are currently working on a paper submission based on research done during my last summer internship. We also submitted two patents applications for the algorithms developed during my first two internships.

How closely connected was the work you did during your internships to your Ph.D. topic?
My Ph.D. topic, graph mining, is closely connected with all three of my internships at Google. During my Ph.D. studies, I improved my understanding of several topics in large-scale graph mining, which turned out to be very relevant for addressing important issues at Google, as evidenced by the internships projects I have completed. Among the various techniques that I learned during my Ph.D., graph clustering algorithms and random walks methods have been central to my internships, giving me the chance to use them in concrete scenarios at Google. Moreover, the fact that the paper published during my internship at Google is also part of my Ph.D. dissertation shows the relevance of such research projects to my Ph.D. studies.

What impact has this internship experience had on your Ph.D.?
Besides contributing to my Ph.D. thesis with a publication, the most important impact are the relationships I built with Google researchers. Even after the end of my Ph.D., I am still in close collaboration with various researchers at Google to complete publications stemming from my internships and other research projects. In addition, programming in a professional environment at Google has definitely improved my software engineering skills.

Has this internship experience impacted the way you think about your future career? 
Thanks to these internships, I have a clearer understanding of research outside of academia and of software engineering. Before joining Google, I had only experienced research at university and my career focus was limited to academic research. Now I know that conducting research at a company in the industry can be a very relevant career path to consider after obtaining a Ph.D.

Now that you just graduated, what’s next? 
I moved to the US to start a postdoc position at Brown University with supervisor Professor Eli Upfal. Our team is currently working in research areas closely related to my Ph.D. studies. I am focusing on algorithmic problems and machine learning methods in the analysis of large-scale datasets with potential applications ranging from social networks to computational biology.

Looking back on your experiences now, why should a Ph.D. student apply for an internship at Google? Do you have any advice to offer?
An internship at Google provides a great opportunity to apply your research skills to very challenging and concrete problems that can be tackled only with the scale of data and resources available at Google. Getting hands-on industry experience with a Google internship can be an inspiration for future academic research, as one gets a glimpse into which research problems are more likely to have a strong impact in practice. Furthermore, taking advantage of all the opportunities offered during a Google internship can boost your Ph.D. studies, by leading to new publications in top conferences. More importantly the internship provides valuable connections with high profile researchers and engineers working at Google, which can have a long-lasting positive impact on one’s career — regardless of whether you pursue a career in the industry or in academia. 

My suggestion is just to apply! Internships are a great way to experience research from a different and fascinating perspective. 

Posted by Ariana Palombo, Online Hiring & Insights Team

Supporting our young scientists through the Google Science Fair

Posted by Mariette DiChristina, Editor in Chief of Scientific American and Chief Judge of the Google Science Fair

(Cross-posted on the Official Google blog)

Editor’s note: Mariette DiChristina is the Editor in Chief and senior vice president of Scientific American—the first woman to hold the role in the magazine’s 170-year history. She has been a Fellow of the American Association for the Advancement of Science since 2011 and served as president of the National Association of Science Writers in 2009 and 2010. She joins us here today to share her perspective on the Google Science Fair, which is in its fifth edition this year.

This marks my fifth year with the Google Science Fair. In October 2010, when I had my first conversations with my friends at Google about their idea to create a global online science fair that any kid 13–18 could participate in, I thought it sounded pretty cool. But I couldn’t then imagine just how inspiring and powerful such a competition would turn out to be in reality.

At the time, I hadn’t even been editor in chief of Scientific American for a year, but I had real ambitions to try to do something to make a difference in educating our young people about science. You see, I believe that science is the engine of human prosperity—it’s the way we grapple with some of the world’s most challenging problems, from cures for diseases to living sustainably in a finite world. So I’ve always seen the idea of fostering evidence-based thinking in our next generation of global citizens as vital.

Now, five years later and working with partners LEGO Education, National Geographic and Virgin Galactic, the Google Science Fair has an impressive track record of enabling our world’s young scientists to shine. Over the years, they’ve tackled serious issues, like world hunger and the energy crisis. Their projects have worked on how to diagnose and treat diseases like cancer and Alzheimer’s. They’ve engineered flashlights powered by their hands and plastics made of banana peels. And to date, the fair has provided almost $1 million in scholarships, and sent four grand prize winners on trips around the world to further their scientific passions.

Tonight we added some new winners to that list as we recognized and celebrated the 2015 top 20 finalist projects and the bright young scientists behind them:

  • The Grand Prize went to Olivia Hallisey for creating a novel way to detect Ebola.
  • Girish Kumar won the Google Technologist Award for helping improve learning through auto-generated study questions.
  • The National Geographic Explorer Award went to Deepika Kurup for her idea to use solar-powered silver to create clean drinking water.
  • Krtin Nithiyanadam’s project focused on improved diagnosis and treatment of Alzheimer’s Disease and won him the Scientific American Innovator Award.
  • Pranav Sivakumar‘s automated search for gravitationally lensed quasars earned him the Virgin Galactic Pioneer Award.
  • And Anurudh Ganesan took home The LEGO Education Builder Award for his unique twist on effectively transporting vaccines.

If you didn’t get to tune in, you can still watch the Awards Show live stream and check out the complete list of impressive finalists and winners, including our first ever Inspiring Educator, Aydan Meydan from Bosnia and Herzegovina.

In all of these finalists and the thousands of submissions from students in 100+ countries, we see something common. These students are inventive, thoughtful, and determined to help make the world a better place. All they need is a chance and a platform to do so. And, unlike some of us adults, they are ready to try things that other people think are “impossible.” I find them inspiring.

It’s imperative for us to support and encourage our young people to explore and challenge the world around them through scientific discovery. So we’re especially glad that Ahmed Mohamed—the 14-year-old clock maker from Texas—took us up on our invite to attend this year’s event. Curious young scientists, inventors and builders like him should be encouraged and empowered.

The past decades have brought tremendous innovations and challenges, and none of us knows what the future of scientific discovery holds. But I can tell you one thing: it’s going to be better thanks to these kids. They will be part of building a brighter future for us all—and as they do, those of us at Scientific American, Google, LEGO Education, National Geographic and Virgin Galactic will be cheering them on.

So start thinking of your ideas for next year! We can’t wait to see what you’ll try next. 

2016 US and Canada scholarship opportunities for computer science students

We are excited to announce that applications are now open for 2016 Google scholarships. The application deadlines are in November and December, but don’t wait to get started on your application!

At Google, we believe information should be universally accessible. Our education and scholarship programs aim to inspire and help students become future leaders in computing and technology by breaking down the barriers that prevent them from entering these fields.  We are now accepting applications from current university students, undergraduate and graduate, for the following scholarship programs:

Scholarship recipients will receive $10,000 USD or $5,000 CAD for the 2016-17 academic year. Scholars will be invited to the annual Google Scholars’ Retreat in Mountain View, CA next summer. At the retreat, scholars will participate in networking and development sessions, including sessions on how to lead outreach in their communities.
2015 scholarship recipients participating in a code retreat at the annual Google Scholars’ Retreat.
For more information on all scholarship programs, please visit the Google Scholarships site.

Posted by Sarah Safir, Tech Student Development Programs