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One of the key market pillars for Google’s new Chrome OS is fact that it is targeting the netbook market. It’s a market that is growing rapidly with one forecast pegging 2009 growth of nearly 70 percent in 2009.

While Linux has been a player in the netbook market since the beginning, NPD Group recently reported that Microsoft Windows now represents 96 percent of the market. Amidst that backdrop, what will take for Chrome OS and other Linux vendors to capture share in the netbook market?

“Linux will naturally capture more share on netbooks as Microsoft economics prove unrealistic for this market,” Amanda McPherson, vice president of marketing and developer programs at the Linux Foundation told chúng tôi “Microsoft as it existed for the past 20 years does not fit into a world of free carrier-backed netbooks and an Internet OS.”

Microsoft (NASDAQ: MSFT) currently makes Window XP available to netbook vendors and is currently working on a version of Windows 7 for netbooks. Microsoft told chúng tôi earlier this year that Windows on Notebook PCs in the U.S have gone from under 10 percent in unit sales during the first half of 2008 to 96 percent as of February 2009.

The current market share for Windows on netbooks does not deter Linux backers. McPherson noted that the industry is moving into a services-based PC model and that will put margin pressure on the OS side of netbook vendors. It’s a margin pressure that in her view, does not favor Microsoft.

Novell and its SUSE Linux distribution are among the Linux vendors currently actively engaged in the netbook market. The key for Linux netbook growth, according to Novell’s openSUSE’s Community Manager Joe Brockmeier, is community and corporate cooperation.

“What we need in large part to capture more share is marketing and partnerships with the OEMs that sell netbooks,” Brockmeier told chúng tôi “This is something that vendors like Intel and Novell can help with, and something that the community at large isn’t well-suited to handle.”

Intel (NASDAQ: INTC) is one of the lead backers of the Moblin mobile Linux operating system. Novell has partnerships with Lenovo for netbooks, while Ubuntu has initiatives in place with Dell. Google has already announced that they are working with Hewlett-Packard (NYSE: HPQ), Acer and Lenovo for Chrome OS.

“On the community side, we need active development focused on netbooks and netbook-friendly applications,” Brockmeier said. “Work that reduces boot times, and work that helps tailor existing applications for netbooks and also creates new applications that people want on netbooks for Linux.”

Though Windows currently dominates the netbook space, Linux vendor Ubuntu is optimistic about their chances to gain significant share. Ubuntu founder Mark Shuttleworth told chúng tôi earlier this year that he sees Windows 7 as an opportunity for Linux growth.

It’s a sentiment that is now being echoed by others on Shuttleworth’s team. Gerry Carr, platform marketing manager at Canonical (Canonical is the lead commercial sponsor of Ubuntu) told chúng tôi that the fact that Ubuntu is shipping good numbers and working well with key partners gives them confidence.

Carr did not elaborate on the numbers that are being shipped. Ubuntu does have a netbook specific edition of its Linux distribution called the Ubuntu Netbook Remix, which is freely available.

“Android, Chrome, Moblin, Ubuntu Netbook Remix all see the value in a Linux strategy,” Carr said. “There is unprecedented excitement and investment in the market and netbook and notebook buyers are going to see choice and value on the software side they have not seen for some time. What do we need to do? Keep building better product, share learning and stay focused.”

Article courtesy of chúng tôi

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Netbook Shipments Jump In First Quarter

An Apple official may have trashed netbooks for cramped keyboards and “junky” hardware, but shipments for the inexpensive laptops are showing no signs of slowing down.

IDC last week said worldwide netbook shipments went up sevenfold to roughly 4.5 million during the first quarter of 2009 compared to the same quarter last year. Netbooks comprised approximately 8 percent of all PC shipments during the first quarter.

Despite an early backlash due to uncertainty surrounding the device, netbooks have been grabbing more attention since early 2008, said Jay Chou, research analyst at IDC. Netbooks are attractive as secondary devices because of their low prices and small sizes, he said. Low prices helped fuel netbook sales, although people in general have reduced spending during the recession.

“People in different areas have different expectations of what [netbooks] are supposed to do. Some of our surveys show students using it as a note-taking device. They don’t want to take a 6-pound [laptop] to campus,” Chou said.

Netbooks also meet the needs of many people for Web surfing and word processing.

“Vendors are waking up to the fact that people respond to so-called ‘good-enough’ computing. They don’t really need all the power of a Core 2 Duo CPU most of the time. Most of the time CPU usage is about 5 percent,” Chou said.

Netbook shipments for the year should double to 22 million in 2009 compared to last year, taking a larger share of PC shipments as the year goes on. Shipments should pick up during the back-to-school season in the third quarter, and possibly jump in the fourth-quarter holiday season.

However, shipments may record slower incremental growth starting in 2010 as netbooks become a mainstay of the PC market, Chou said.

Chou couldn’t provide exact market-share numbers for each vendor for the first quarter of 2009, but he didn’t expect a change in rankings from the fourth quarter. Acer was the top netbook vendor during the fourth quarter with a 32 percent market share, followed by Asustek, with a 26 percent market share. Following Asustek were Hewlett-Packard, Lenovo and Samsung.

Acer President and CEO Gianfranco Lanci recently said the company expects to ship between 10 million and 12 million netbooks during 2009. It shipped just over 5 million netbooks in 2008.

Due to seasonal reasons, shipments fell sequentially from the 6.2 million netbooks shipped in the fourth quarter of 2008. Buying activity is higher in the fourth quarter because of the holiday season. Purchases slowed down after the holiday season ended, affecting netbook shipments during the first quarter of 2009.

Netbook shipments saw sharp growth in Europe and Japan during the first quarter, Chou said. Japan is usually a market where people crave small things, and netbooks fit into that category, Chou said.

Samsung was a relative latecomer to the netbook space but saw plenty of buyers for its NC10 laptop in Western Europe, Chou said. Samsung offered users a better overall netbook experience with a larger screen and a decent-sized keyboard.

Telecommunication companies are playing a big part in Europe and Japan to drive the netbook phenomenon by bundling it with telecom services. The trend is also reaching the U.S., with AT&T offering a US$99 Acer netbook with a two-year mobile broadband contract.

Netbook adoption will also continue to grow as PC makers add more and more features like bigger screen sizes and better graphics, Chou said. Asus, for example, added a DVD drive to one of its models. Early netbooks have been panned for poor graphics capabilities, but Nvidia has come out with a chip platform that will make it possible to watch full high-definition video on netbooks.

There is also a growing interest in netbooks with screen sizes between 9 and 12 inches, Chou said. Early last year, laptops with a 7-inch screen size dominated shipments, but interest waned as laptops with larger screen sizes shipped, Chou said.

IDC defines netbooks — which it calls mini-notebooks — as laptops with screen sizes between 7 and 12 inches with low-power processors like Intel’s Atom processors.

Evoking The Imagination As A Strategy Of Influence

Evoking the Imagery as a Strategy of Influence

The available data indicates that imaging can significantly impact consumer behavior. It has been demonstrated to improve memory, even fabricate memories, and raise the perceived probability of an occurrence. For instance, visualizing a political candidate winning an election might enhance the perception of that candidate’s chances of winning, just as visualizing yourself picking up the jackpot can raise our perception of our chances of winning. It has also been shown that imagery increases the intentions to engage in a behavior. The desire to carry out specific actions increased when people imagined going on vacation, beginning a new career, or giving blood.

Nevertheless, the regular membership was 47.4% among those who envisaged getting cable TV service. Sales were increased by simply asking customers to picture themselves using the product. Given the research demonstrating how imagery affects customers’ perceptions and actions, it is crucial to comprehend the processes by which these effects take place. Although researchers have proposed numerous processes, it still needs to be determined how imagery affects consumer preferences and behavior.

Traditional Approaches to Processes Affecting the Effects of Imagery

Research on persuasion has traditionally focused on cognitive processes, including mood, argument consideration, and recollection. These methods have also been used to study the effects of imagery. For instance, research indicates that imagery can improve product evaluations due to the subjective responses it elicits. Additionally, research shows that information processed through imagery is retained in both a perceptual and conceptual code, making imagery easier to recall than information kept in a semantic code. It has also been proposed that vivid information or directions that visualize the goods probably affect brand preference by improving the accessibility of favorable product-related information, given the importance of information accessibility.

The availability-valence theory further contends that as imaging can enhance cognitive elaboration, it might increase or reduce product preferences depending on the value of the information about the product. In other words, images may make positive and negative product information more accessible. In these circumstances, urging customers to picture themselves using the goods can reduce their desire for them. Even though there is evidence to support these mechanisms, more recent research contends that other processes occur when customers envisage using the goods.

Similarly, imagery appeals may activate mechanisms distinct from those elicited by merely showing someone a picture of a product. According to a recent series of experiments, enhancing the luster of the product representation led to more product-relevant thoughts and better memory of the product’s details, supporting the availability-valence concept. Nevertheless, regarding imagery appeals, these impacts were not seen. Telling participants to use their imagination to absorb the information reduced the amount of product-related, product-specific, and attribute-specific thoughts and memory.

Modern Approaches to Processes Affecting the Effects of Imagery

Consumers’ subjective perceptions of fluency are the topic of another general research area that has sparked fresh inquiries into the mechanisms behind the benefits of imagery. Quite a bit of data has developed to show that when establishing attitudes, opinions, and judgements, people are likely to weigh both the content of the information they are given as well as how easily this information comes to mind. Consider the possibility that consumers may base their assessments of products not only on the information supplied on the products themselves but also on how quickly they can assimilate this information. Also, buyers frequently rely on their product choices on the subjective availability of these reasons rather than the number of justifications they may come up with for buying the goods.

Research on automated processes is a third source of fresh information about how imagination works. The ideomotor action principle states that simply thinking about behaviour may make one more likely to carry it out. It may be more likely for the behaviour to be activated when a representation of the behaviour is activated through imagination. Several studies have shown results that support this theory.

The engagement of a perceptual depiction may result in matching behaviour, according to research on the relationship between perception and conduct. We may anticipate that imagery may stimulate actual consumption by triggering a mental image of consuming the substance because perception and imagery involve similar mental processes.

Conclusion

Consumer researchers have just recently begun doing systematic research into the psychological mechanisms underpinning imagery’s impacts, even though imagery has long been understood and employed as a method of persuasion. The research under discussion offers significant new information about the potent influence that visualisation has on customer preferences and behaviour.

Additionally, it suggests procedures that are conceptually distinct from the psychological processes that influence and persuasion researchers have historically investigated. To further understand the mechanisms by which imagery affects consumer behaviour and the circumstances in which such impacts take place, more research is still required.

The Winning Approaches From Codefest 2023 – Nlp, Computer Vision And Machine Learning!

Introduction

Analytics Vidhya’s hackathons are one of the best ways to evaluate how far you’ve traveled in your data science journey. And what better way than to put your skills to the test against the top data scientists from around the globe?

Participating in these hackathons also helps you understand where you need to improve and what else you can learn to get a better score in the next competition. And a very popular demand after each hackathon is to see how the winning solution was designed and the thought process behind it. There’s a lot to learn from this, including how you can develop your own unique framework for future hackathons.

We are all about listening to our community, so we decided to curate the winning approaches from our recently concluded hackathon series, codeFest! This was a series of three hackathons in partnership with IIT-BHU, conducted between 31st August and 2nd September. The competition was intense, with more than 1,900 aspiring data scientists going head-to-head to grab the ultimate prize!

Each hackathon had a unique element to it. Interested in finding out more? You can view the details of each competition below:

Linguipedia – Natural Language Processing

Enigma – Machine Learning

Vista – Computer Vision

It’s time to check out the winners’ approaches!

Liguipedia – Natural Language Processing

Winners

Abhinav Gupta and Abhishek Sharma.

Problem Statement

The participants were given a list of tweets from customers about various tech firms who manufacture and sell mobiles, computers, laptops, etc. The challenge was to find the tweets which showed a negative sentiment towards such companies or products.

The metric used for evaluating the performance of the classification model was weighted F1-Score.

Winner’s Approach

Abhinav and Abhishek have summarized their approach in a very intuitive manner, explaining everything from preprocessing and feature engineering to model building.

Pre-processing:

Converted words to lower case

Replaced URLs with the word ‘URL‘ and @handle with the word ‘USER_MENTION‘

Removed RT (retweet), – , and ‘

Replaced #hashtag with hashtag

Replaced more than two dots with space, multiple spaces with a single space

Replaced emojis with either EMO_POS or EMO_NEG

Strip space, ” and ‘ from tweet

Removed punctuation

Used stemmer

Feature Extraction:

Top 15,000 unigrams in case of sparse vector representation (one-hot encoding), 90,000 in case of dense vector representation

They used tf-idf method in case of a sparse vector representation

For dense vectors, they used Glove embedding (trained on tweets)

Classifiers used:

Naive Bayes

Maximum entropy classifier

Decision Tree

Random Forest

XGBoost

Support Vector Machine

Multi-layer perceptron

Convolutional neural networks (We experimented with 1, 2, 3 and 4 layers)

LSTM (using the last layer obtained for classification)

LSTM (with attention mechanism)

They hypertuned each of the above classifiers and found that LSTM (with attention mechanism) produced the best result.

Ensemble

They gave one weight to each classifier – Naive Bayes, Maximum entropy classifier, Decision Tree, Random Forest, XGBoost, SVM, Multi-layer perceptron; two weights to CNN, three weights to LSTM (without attention), and five weights to LSTM (with attention)

These weights were obtained after hyperparameter tuning on a portion of data (they divided the train dataset into three parts)

Vista – Computer Vision

Winner

Deepak Rawat.

Problem Statement

The Vista hackathon had a pretty intriguing problem statement. The participants had to build a model that counted the number of people in a given group selfie/photo. The dataset provided had already been split, wherein the training set consisted of images with coordinates of the bounding boxes and headcount for each image.

The evaluation metric for this competition was RMSE (root mean squared error) over the headcounts predicted for test images.

Winner’s Solution

Check out Deepak’s approach in his own words below:

As this was an object detection problem, I implemented Mask R-CNN in Python 3, using Keras and TensorFlow. The model generated bounding boxes and segmentation masks for each instance of an object in the image. It’s based on Feature Pyramid Network (FPN) and a ResNet101 backbone

Mask R-CNN and ResNet101

Mask R-CNN is a two-stage framework:

The first stage scans the image and generates proposals (areas likely to contain an object)

The second stage classifies the proposals and generates bounding boxes and masks

Both stages are connected to the backbone structure.

I have used the ResNet101 backbone. Backbone is an FPN-style deep neural network. It consists of a bottom-up pathway, a top-bottom pathway, and lateral connections:

Bottom-up pathway extracts features from raw images

Top-bottom pathway generates feature pyramid map which is similar in size to the bottom-up pathway

Lateral connections are convolution and add operations between two corresponding levels of the two pathways

Pre-processing

I have used default 1024×1024 image size for better accuracy

Apart from this, I also applied some data augmentation techniques to avoid overfitting and for better generalization

Model Building

I also used pre-trained weights trained on the MS-COCO dataset. MS-COCO is a large-scale object detection, segmentation, and captioning dataset. I used transfer learning and fine-tuning of pre-trained weights to train own custom Mask R-CNN model on the given dataset

Finally, I used a weighted majority voting to ensemble the best models and predict the final values

Enigma – Machine Learning

Winner

Raj Shukla.

Problem Statement

As a part of enigma competition, the target was to predict the number of upvotes on a question based on other information provided. For every question – its tag, number of views received, number of answers, username and reputation of the question author, was provided. Using this information, the participant had to predict the upvote count that the question will receive.

The evaluation metric for this competition was RMSE (root mean squared error). Below is the data dictionary for your reference:

Variable Definition

ID Question ID

Tag Anonymised tags representing question category

Reputation Reputation score of question author

Answers Number of times question has been answered

Username Anonymised user id of question author

Views Number of times question has been viewed

Upvotes (Target) Number of upvotes for the question

Winner’s Solution

Here is Raj’s approach to cracking the Enigma hackathon:

Feature Engineering:

My focus was on feature engineering, i.e., using the existing features to create new features. Below are some key features I cooked up:

The first feature I create was taking the ratio of views and answers. I believe that the ratio is a better metric than the individual number of views or answers. Otherwise, a person with more answers and a high number of total views would get more credit than a person with few (but good) answers and overall fewer views

The second feature is the ratio of Reputation to five times the number of answers. I added the factor 5, because the reputation was roughly 5 times the answers. This ratio intuitively makes more sense

I created another feature using the views and reputation values. I took the absolute value of the difference between views and reputation

Model Building:

I used a linear regression model with polynomial features

I have restricted the degree of polynomial to 2, as increasing this will lead to a more flexible model and increase the chances of overfitting

End Notes

A big thank you to everyone for participating in codeFest 2023! This competition was all about quick and structured thinking, coding, experimentation, and finding the one approach that got you up the leaderboard. In short, what machine learning is all about!

Missed out this time? Don’t worry, you can check out all upcoming hackathons on our DataHack platform and register yourself today!

Related

The Linux Software Store Conundrum

For quite some time, I’ve pleaded with the Ubuntu team to consider updating the Ubuntu Software Center. It’s nearly unusable on older PCs, and even on modern hardware this method of software installation leaves a lot to be desired – especially with paid applications.

It’s my hope that this article will not only help each of us take a hard look at the existing methods of Linux software discovery and installation, but perhaps we’ll finally settle on a means of handling paid software titles as well.

Flash forward to now, we have Ubuntu’s Software Center, which is widely considered to be the closest thing to what Linspire once offered. The obvious difference here, however, is that the experience is downright painful when trying to download commercial applications. A sloppy checkout experience bundled with a “Buy” button for freeware applications has all but turned me off of trying to use anything other than Synaptic these days. If I do need a commercial application that badly, I find myself going out of my way to look for it elsewhere.

While there are a number of “other” software stores available for the Linux desktop, none of them actually support paid applications like the Ubuntu Software Center. The only viable alternative I’ve seen to the Ubuntu Software Center for distributing paid applications on the Linux desktop is Valve’s Steam digital software manager. Known as a top outlet for distributing paid Linux games, I’ve found that Steam is already being used to distribute software for other platforms. I think that it’s entirely possible Steam would be a good option for distributing paid software for Linux users as well.

Unlike other software distribution tools, Steam is designed specifically to handle payments in a much cleaner way than existing Linux alternatives. Also, Steam presents games and software titles in a fantastic light, so those browsing these titles can settle on the right application for their needs.

Now I’m not suggesting that Steam would be the best replacement for say, discovering open source software titles. I’m firmly against such an idea. I would suggest, however, that Steam provides a multiple distro option for handling all software/games of a proprietary nature.

By now, you may think that I’m firmly against software distribution tools like the Ubuntu Software Center. But the truth is, I’d love to see it improved and to succeed with as many open source titles as possible. Again, while I think it needs work, it still provides a fairly decent tool for software title discovery. But as I noted out above, the payment system provided in the Software Center is simply not providing a good user experience overall. It’s slow, and doesn’t really provide a solid tool for discovering the latest releases of paid software.

In this arena, I see Steam as the clear winner here. And if we can get Steam ramped up in distributing paid applications that people actually want to use – not just the limited paid title library for Linux we have now – the options could be limitless.

Imagine a new ecosystem where paid applications have their own distribution tool free from dependency on any one Linux distro. Ubuntu, Arch, OpenSUSE, whatever the distro might happen to be, I see Steam as the tool introducing yet-to-be-ported software over to the Linux space. And as new software titles are released and discovered, more will follow. Perhaps we’d even see mega-brands making an appearance? Adobe Photoshop and Microsoft Office – if the paying audience is there, I see no reason why these titles wouldn’t be made available.

There are some serious challenges to overcome before Steam for software could take a hold of the Linux space. The first challenge is the Linux user base itself: we can be cynical, reserved and always concerned about the next big “proprietary threat” coming down the road. Despite the warm reception Valve has seen with Steam delivering games onto the various Linux distributions, I think this “welcome” would cool a bit if software titles were also being actively promoted.

Google Chrome Os, A Google Netbook And The Web Store Landing December 7

Google has more or less confirmed the December 7 launch date for both the Chrome Web Store and, more exciting, Chrome OS. Google sent out invitations to an event for the date related to Chrome. The company isn’t saying much else, but, along with a couple of rumors that were flying around, it’s a safe bet that both of the highly expected products will be unveiled next week. “On December 7, you are invited to join us for an event in San Francisco, where we plan to share some exciting news about Chrome,” the invite sent out to various publications read. Earlier, separate rumors speculated about the launch of both the Web Store and Chrome OS. All Things D’s Media Memo, which has had some insider info about the Web Store before, reported that the Web Store was coming December 7. That would be in line with Google’s latest adjusted plans. The Web Store was originally slated for an October launch, but was delayed. The latest rumors and indications pointed at an early December launch date. Google Chrome 8, which comes with extensive support for Apps, landed yesterday. The Google Chrome 9 beta is now on its way. Apparently, the store will be launched for beta users first, so most people will only have access to it when Chrome 9 stable lands, mid-January next year. Even more exciting news comes from Engadget. The gadget blog reported that a Google-branded Chrome OS netbook will be launched on December 7. This was before Google announced the event. Some leaked photos of the device have already been made available online. The device won’t be made available for sale for the holiday season though. Apparently, the Chrome OS netbook will only be made available for Google employees and their families, 65,000 or so devices have been lined up for the launch, since Chrome OS is still in beta.

Google has more or less confirmed the December 7 launch date for both the Chrome Web Store and, more exciting, Chrome OS. Google sent out invitations to an event for the date related to Chrome. The company isn’t saying much else, but, along with a couple of rumors that were flying around, it’s a safe bet that both of the highly expected products will be unveiled next week. “On December 7, you are invited to join us for an event in San Francisco, where we plan to share some exciting news about Chrome,” the invite sent out to various publications read. Earlier, separate rumors speculated about the launch of both the Web Store and Chrome OS. All Things D’s Media Memo, which has had some insider info about the Web Store before, reported that the Web Store was coming December 7. That would be in line with Google’s latest adjusted plans. The Web Store was originally slated for an October launch, but was delayed. The latest rumors and indications pointed at an early December launch date. Google Chrome 8, which comes with extensive support for Apps, landed yesterday. The Google Chrome 9 beta is now on its way. Apparently, the store will be launched for beta users first, so most people will only have access to it when Chrome 9 stable lands, mid-January next year. Even more exciting news comes from Engadget. The gadget blog reported that a Google-branded Chrome OS netbook will be launched on December 7. This was before Google announced the event. Some leaked photos of the device have already been made available online. The device won’t be made available for sale for the holiday season though. Apparently, the Chrome OS netbook will only be made available for Google employees and their families, 65,000 or so devices have been lined up for the launch, since Chrome OS is still in beta.

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