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本日から4日間の日程でImagine Cup世界大会がシアトルのマイクロソフト本社にて行われます。初日の今日は、チームメンバー一人一人に対し、今回のデバイスを作ろうと思ったきっかけや、テクノロジーを好きになったきっかけについてなどインタビューが行われました。筑波大学の皆さんには今回のデバイスに対する強いパッションがあるだけでなく、この4人でなければ成し遂げられなかったというチームメンバー同士の強い結束感が感じられました。

マイクロソフト社員によるプレゼンテーションコーチングを終え、時差ボケにも負けず明日の発表に向けさらにプレゼンテーションに磨きをかけています。ソリューションには確固たる自信をもっている4人なのであとはこれまで練習してきた英語プレゼンを思う存分披露していただくだけです。シアトル時間で明日夕方に本番に挑みます。

Imagine Cupと並行で開催されるMSP (Microsoft Student Partners) Summitには日本のＭＳＰメンバーからも二人に参加いただいています。こちらも世界中のＭＳＰとのネットワーキングやハッカソンを通して是非日本のＭＳＰを代表した存在力を発揮してもらいたいですね！今夜は筑波大学Biomachine Industrial チームのプレゼンブラッシュアップにもオーディエンスとしてご協力いただいています！

Security is top of mind for everyone these days – securing your identity, securing your data. When you think about how you secure your data in the cloud you need to ensure that you understand how your data is stored and accessed. The Azure SQL Data Warehouse service utilizes Transparent Data Encryption (TDE) to encrypt your database, associated backups, and transaction log files at rest without requiring changes to your application.

SQL Data Warehouse’s TDE implementation is based on SQL Server’s TDE technology which encrypts the storage of an entire database by using industry standard AES-256 symmetric key called the database encryption key. SQL Data Warehouse protects this database encryption key with a service managed certificate.

Getting Started (the portal way)

The easiest way to turn on TDE for your database instance is via the Azure portal. Once in the portal, just navigate to your database, and expand the Transparent data encryption blade.

You simply click on the On button and then the Save button at the top.

In just a minute or so, your database will be secured.

Getting Started (the T-SQL way)

To enable TDE, via T-SQL you simple connect to the master database and execute the following command:

ALTER DATABASE [DemoDW] SET ENCRYPTION ON;

Verify Encrypted Status

You can verify the state of all of your databases by connecting to the master database and executing the following command:

SELECT name, is_encrypted FROMsys.databases;

The results list all of the databases by name and encrypted status (0 = not encrypted, 1 = encrypted).

Next Steps

Visit the SQL Data Warehouse Overview to learn more about Microsoft’s scale out relational data warehouse.

Jul.

27

Sample : https://code.msdn.microsoft.com/How-to-operate-Azure-69fd7487

This sample demonstrates how to operate Azure Virtual Network via REST API.

You can find more code samples that demonstrate the most typical programming scenarios by using Microsoft All-In-One Code Framework Sample Browser or Sample Browser Visual Studio extension. They give you the flexibility to search samples, download samples on demand, manage the downloaded samples in a centralized place, and automatically be notified about sample updates. If it is the first time that you hear about Microsoft All-In-One Code Framework, please watch the introduction video on Microsoft Showcase, or read the introduction on our homepage http://1code.codeplex.com/.

Microsoft nedávno uvolnil ostrou verzi nové generace vývojářské platformy .NET Core, a již za pár měsíců se chystá vydat další verzi svého klíčového produktu Windows Server 2016.

Konference CORESTART, to jsou tři dny plné novinek pro vývojáře a IT odborníky. Přijďte se podívat a dozvědět se něco nového o technologiích, které jsou aktuálně v kurzu.

Konference se koná 17. – 19. srpna 2016 v sídle společnosti Microsoft.

Program konference je opravdu bohatý, můžete se těšit na témata o virtualizaci, novém Nano serveru, čerstvě vydaném .NET Core nebo třeba DotVVM. Kompletní přehled přednášek najdete na webu konference – https://www.corestart.cz/. Na akci je nutné se zaregistrovat.

Para quem desenvolve para Android e sofre tem dificuldade com a velocidade dos emuladores do Android SDK, a Microsoft criou um emulador com muito mais performace do que os emuladores existentes. Outra grande vantagem desse emulador é que vem em uma instalação a parte que não depende de Visual Studio instalado.

O primeiro passo é garantir que o Android Studio e o Visual Studio Emulator for Android estão instalados e funcionando. Com o Emulador instalado, assim que você abrir o Android Studio para tentar executar a aplicação, se o Visual Studio Emulator estiver aberto, o Android Studio vai encontrar ele como um possível dispositivo conectado para execução da aplicação. Ou seja, não precisaríamos fazer os passos a seguir para que uma aplicação criada no Android Studio executasse no novo emulador Visual Studio Emulator for Android. Porém esses passos a seguir facilitam a utilização do emulador no dia a dia, pois adiciona atalhos no Android Studio, evitando ter que iniciar o emulador fora da IDE. Vamos para as configurações dos atalhos:

Abra o Android Studio –> Run –> Edit configurations…

Expandir o menu Defaults –> Clicar em Android Application. Em Deployment Target Options selecionar “Show Device Chooser Dialog” e clicar no checkbox “Use same device for future launches” e clique em OK. Com isso toda execução da aplicação irá abrir a janela perguntando qual o Device que deve ser utilizado e lembrará a opção definida.

Agora clique em File –> Settings –> Tools –> External Tools –> Add.

Aqui vamos adicionar o Emulator Manager ou os emuladores que serão utilizados.

Preencha o campo Name para identificar a ferramenta e uma descrição. Nos outros campos preencha:

Program: C:Program Files (x86)Microsoft Emulator Manager1.0emulatormgr.exe

Parameters: /sku:Android

Clique em OK.

Working directory: $ProjectFileDir$ (vou utilizar uma variavel que é substituída pela pasta do projeto)

Nesse caso cadastrei primeiro a ferramenta para abrir o gerenciador de emuladores, por isso selecionei o emulatormgr.exe que está na pasta de instalação do emulador.

Agora vamos cadastrar um atalho para abrir direto um dos emuladores instalados. Abra o prompt de comando na pasta em que o emulador foi instalado (nesse exemplo: C:Program Files (x86)Microsoft Emulator Manager1.0) e digite: “emulatorcmd.exe /sku:Android list /type:device”. Esse comando irá listar todos os emuladores instalados, suas versões e identificadores.

Com isso em mãos, adicione uma nova External tool clicando em Add. Novamente preencha os campos, mas agora com outras informações:

Name: 5.1″ Marshmallow (6.0.0) XXHDPI Phone (Escrevi o mesmo nome de um dos emuladores listados acima que estou adicionando)

Program: C:Program Files (x86)Microsoft Emulator Manager1.0emulatorcmd.exe (note que agora não estamos abrindo o gerenciador, e sim vamos selecionar um dos emuladores)

Parameters: /sku:Android launch /id:8AB3CF93-0E9D-4EF8-B132-66D6D7AB4820 (O mesmo ID referente ao emulador da lista)

Clique em OK e OK novamente para finalizar após adicionar os emuladores que pretende utilizar.

Clique com o botão direito na barra de ferramentas do Android Studio –> Customize Menos and Toolbars…

Vamos expandir a área Main Toolbar. Escolha o local onde vai adicionar os atalhos do Emulador criados anteriormente. Em meu caso criei após o último ícone, help. Se quiser fazer o mesmo, clique no link Help Topics –> clique no botão Add After…

Com isso irá abrir uma nova janela para escolher os atalhos. Clique em All Actions –> External Tools –> External Tools –> Selecione os emuladores cadastrados e clique em OK. Você pode selecionar um novo ícone para esses atalhos. Para finalizar clique em OK novamente.

Os ícones foram criados e estão na barra de ferramentas da IDE. Agora clique no ícone de algum dos emuladores criados para abrir o emulador.

Por fim com a aplicação aberta no Android Studio e com o emulador funcionando, clique em play para executar a aplicação e uma janela será aberta perguntando onde deve ser executada.

Clique no emulador do Visual Studio “VS Emulador” e clique em OK. Sua aplicação será executada no novo emulador.

That’s it.

Referência: https://blogs.msdn.microsoft.com/visualstudioalm/2015/07/20/using-the-visual-studio-emulator-for-android-from-android-studio-or-eclipse-with-adt

Приближаясь к годовщине запуска Windows 10, мы спешим поделиться с вами радостной новостью – Windows 10 уже установлена на 300 млн активных устройств по всему миру! Нам приятно осознавать, что Windows 10 стала одним из крупнейших онлайн-сервисов менее чем за год. Являясь центральным элементом концепции персонализированных компьютерных технологий, новая ОС предлагает пользователям знакомый, но более безопасный и защищенный, персонализированный и продуктивный сценарий взаимодействия, позволяя испытать новые ощущения и эмоции от работы.

Но период бесплатного обновления подходит к концу, успевайте обновить свою ОС до 29 июля.

Официальная страница Windows 10 по ссылке

Подробности читайте в официальном блоге Windows

Microsoft Cognitive Services (powered by Microsoft Research) make you free from the difficulties of intelligence algorithms, and everyone who is not the scientist can easily use this pre-built (ready-to-go) APIs for your application intelligence.

, but we focus on the language understanding (the linguistic computation including tagging, parsing, etc) in this post, and help you understand the clear point of each APIs.

The natural language processing itself covers speech recognition, translation, sentiment analysis, summarization (which is also possible in Microsoft Word), language generation, etc… Microsoft Cognitive Services is having a lot of APIs (over 20) and corresponding APIs.
But we focus on the language understanding (the linguistic computation including tagging, parsing, etc) in this post, and focus on the only 2 APIs, which are Linguistic Analysis API and Language Understanding Intelligent Service (LUIS).
I hope this helps you understand the clear point of language understanding in Microsoft Cognitive Services.

Notice : This post doesn’t explain about “how to use”, and please refer the official document (Linguistic Analysis API, LUIS) for the api usage.

Linguistic Analysis API

If you need the fundamental language parsing capabilities, you must use this API. The Linguistic Analysis API returns the parsing result as json from the original sentences.

Today you can use the following 3 types of linguistic analyzers.

Token Analyzer (PennTreebank3 – regexes)

This is the most simple analyzer which just separates the sentences and tokenizes.
The following is the tokenized result of the sample sentence “I want a sweet-smelling flower with a red flowerbot.”

This result is not including so much useful information, but you can use this analyzer with other analyzers (you can specify multiple analyzers in one API call), and you can get the additional tokenization information with other analyzer’s result.

{"analyzerId": "08ea174b-bfdb-4e64-987e-602f85da7f72","result": [
    {"Len": 52,"Offset": 0,"Tokens": [
        {"Len": 1,"NormalizedToken": "I","Offset": 0,"RawToken": "I"
        },
        {"Len": 4,"NormalizedToken": "want","Offset": 2,"RawToken": "want"
        },
        {"Len": 1,"NormalizedToken": "a","Offset": 7,"RawToken": "a"
        },
        {"Len": 14,"NormalizedToken": "sweet-smelling","Offset": 9,"RawToken": "sweet-smelling"
        },
        {"Len": 6,"NormalizedToken": "flower","Offset": 24,"RawToken": "flower"
        },
        {"Len": 4,"NormalizedToken": "with","Offset": 31,"RawToken": "with"
        },
        {"Len": 1,"NormalizedToken": "a","Offset": 36,"RawToken": "a"
        },
        {"Len": 3,"NormalizedToken": "red","Offset": 38,"RawToken": "red"
        },
        {"Len": 9,"NormalizedToken": "flowerbot","Offset": 42,"RawToken": "flowerbot"
        },
        {"Len": 1,"NormalizedToken": ".","Offset": 51,"RawToken": "."
        }
      ]
    }
  ]
}

The sentence is not only separated by white space or punctuation marks, but is tokenized by the context in the sentence. For example, it can correctly tokenize like “what’s your name ?” (which is equivalent to “what is your name ?”), “Mr. Williams” (which doesn’t mean the punctuation mark), and …

Part-of-speech (POS) Tagging Analyzer (PennTreebank3 – cmm)

If you want to retrieve some keywords and analyze the sentence, the identification (noun, verb, etc) is often needed. For example, if you want the emotional keywords and measure the emotion, the adjective should be the key word.
This POS tagging analyzer identifies these tags.

The following is the result of this analyzer, using the input sentence “I want a sweet-smelling flower with a red flowerbot.”

{"analyzerId": "4fa79af1-f22c-408d-98bb-b7d7aeef7f04","result": [
    ["PRP","VBP","DT","JJ","NN","IN","DT","JJ","NN","."
    ]
  ]
}

(See “Penn Treebank P.O.S. Tags – Penn (University of Pennsylvania)“)

The tag is not also distinguished only by words, but also the context is concerned.
For example, “dog” is usually the noun in the sentence, but it is used as “verb” in the following sentence. (I referred this example in “Wikipedia : Part-of-speech tagging“.)

“The sailor dogs the hatch.”

Constituency Forest Analyzer (PennTreebank3 – SplitMerge)

Assuming that you’re a shop owner of selling flowers in the internet and providing the intelligent search engine. Customers might input as follows.

“I want a red and sweet-smelling flower.”
“I want a sweet-smelling flower except for red flowers.”
“I want a sweet-smelling flower with a red flowerbot.”

You see that the each sentence is indicating the absolutely different items. But if you use POS tagging analyzer (previous one), the results doesn’t meet the needs.
In such a case, you must use the constituency forest analyzer.

The following is the result of this analyzer in the case of the sentence “I want a sweet-smelling flower with a red flowerbot.”

{"analyzerId": "22a6b758-420f-4745-8a3c-46835a67c0d2","result": ["(TOP (S (NP (PRP I)) (VP (VBP want) (NP (NP (DT a) (JJ sweet-smelling) (NN flower)) (PP (IN with) (NP (DT a) (JJ red) (NN flowerbot))))) (. .)))"
  ]
}

(See “Penn Treebank II Tags – MIT“)

As you see, the result expresses the tree of structure. For example, it means that “a red flowerbot” is subordinating noun of “a sweet-smelling flower”.

Language Understanding Intelligent Service (LUIS)

The constituency forest analyzer (previous one) returns so much useful information, but it’s still difficult to understand this tree structure in your program code.

Language Understanding Intelligent Service (called “LUIS”) is not for just the parsing and analyzing like Linguistic Analysis API, but it provides the direct answer to some application’s scenarios for language understanding tasks.
For example, assuming that there’s an application for booking airline ticket. You might imagine that an application is having the form and field area of “departure location”, “destination location”, and “date/time”.
Using LUIS, you can retrieve these input values from natural language sentences (like, “I want a flight from Orlando to Seattle on 23rd Jul”). LUIS is very straightforward for language understanding tasks.

For example, you can directly retrieve the following values (departure location, destination location, date/time) enclosed by the branckets.

Book a flight from {Orlando} to {Seattle} on {29/10/2016}.
Book me a flight to {Seattle} on {29th Oct}.
I want a flight from {Orlando} to {Seattle} {next Saturday}.
. . .

Notice : You see, the 2nd example lacks the input value “departure location”. But, in such a case, you can distinguish which parameters is needed (fullfilled) for action using LUIS,  and you can ask the user to fill the required parameter.

When you use LUIS, first you register the scenarios (called “intent”) like “Book Flight”, “Get Weather”, etc… For each intent, you register the sample sentences (called “utterances”) and teach the result. When you push “train” button, LUIS learns the pattern.
Now you can use LUIS calling rest endpoint. The rest endpoint returns the result as json, which matches the registered intent.

Notice : LUIS also provides the active learning which you can correct the sentences from existing unlabeled sentences.

LUIS is not only understanding words, but the context in sentence. For example, if you put “Book me a flight to etcetera etcetera on 29th Oct”, the word “etcetera etcetera” might be extracted as destination location.

Note that LUIS requires the previously registered intent, then it’s not used for the ad-hoc resolving, like natural language search, ad-hoc question answering. etc…
Moreover, LUIS only retrieves the target key phase, and doesn’t analyze the phase itself. Let’s consider the next example.

“I want a flowerbot which matches the red flowers for my mother.”

LUIS might retrieve the phase “a flowerbot which matches the red flowers” as target, but it doesn’t mean “a flowerbot and red flowers.” If you want to analyze this phase for acknowledging the exact customer needings, you must use the previous Linguistic Analysis API.

Notice : The name of Text Analytic API in Microsoft Cognitive Services reminds you the language parsing, but this API just analyzes the sentiment (human feeling of satisfied or not satisfied). Note that this doesn’t analyze the human emotion (glad, sad, angry, etc) like Emotion API (also, in Microsoft Cognitive Services), and the result is the scalar value (just the degree of sentiment). You can also retrieve the key phase which impacts to the sentiment. For example, if you collect the customer voice and you want to know what the customer is not satisfied with your services, you can also understand the possible reasons by retrieving this key phases (“facility”, “staff”, etc).

Hi all,

I am pleased to announce that the SSIS 2016 PDW connector for SQL Server 2016 with AU5 is now available for download!!

https://www.microsoft.com/en-us/download/details.aspx?id=51610&wa=wsignin1.0

This PDW SSIS destination connector is designed specifically for building and running Integration Services packages that load data into PDW.

Thanks

jimmy

Welcome to another Azure Content Spotlight! These articles are used to highlight items in Azure that could be more visible to the Azure community.

The Azure Security Center is now generally available as announced in Azure Security Center, now generally available, proven to improve security.  Cybersecurity, including threat detection and analysis, is challenging and requires specialized skills, training, and resources that might not exist in an organization or could be too costly to implement.  Though not a replacement for skilled analysts, Azure Security Center provides features to help address the challenges of detecting potential attacks and analyzing environments for potential vulnerabilities.

The Azure Security Center page is the best starting point with links to capabilities, documentation, and pricing.

In regards to pricing there are two offerings: free and standard.  In brief, both offer analysis and basic security alerting while standard offers more advanced threat detection including behavioral analysis and anomaly detection.

Cheers!

Jul.

28

Sample : https://code.msdn.microsoft.com/How-to-send-emails-using-40300e85

This sample demonstrates how to send email using Azure.

You can find more code samples that demonstrate the most typical programming scenarios by using Microsoft All-In-One Code Framework Sample Browser or Sample Browser Visual Studio extension. They give you the flexibility to search samples, download samples on demand, manage the downloaded samples in a centralized place, and automatically be notified about sample updates. If it is the first time that you hear about Microsoft All-In-One Code Framework, please watch the introduction video on Microsoft Showcase, or read the introduction on our homepage http://1code.codeplex.com/.

Imagine Cup 2016 世界大会2日目、いよいよ本番のプレゼンテーション（審査）に日本代表が挑みました。今回のImagine Cupは、この日に行われるプレゼンテーション10分間とその後の質疑応答20分間、合計30分間で、すべての評価が決定します。

この日のために、入念な準備を重ねてきた日本代表のBiomachine Industrial のメンバーは、Innovation部門全13チーム中、10番目の順番で本番に挑みました。

10分間のプレゼンテーションが終了すると、すぐに20分間の質疑応答に入ります。すべて英語での20分間の質疑応答は、相当にハードでした。海外の学生さん（Imagine Cupに出場してくる各国代表の学生さん）と比較した時、この英語でのコミュニケーション能力の向上は、ほとんどの日本の学生さんにとって、今後の大きな課題だと思います。

審査員の一人に、Bionic Scope を体感いただきました。手を全く使わず、ズームイン、ズームアウトして、Bionic Scope の操作を楽しむ審査員。「非常にクリアに見える」と語る審査員。彼らが作り上げたソリューションの完成度の高さを示した場面でした。

過去のImagine Cup日本代表の熱いメッセージが記された日本国旗を手に記念撮影。「自分達の力は全て出し切った」と語ってくれました。Imagine Cup 2016 日本代表 Biomachine Industrial のメンバーの皆さん、お疲れ様でした。

Речь пойдет о возможностях работы с платформой Microsoft Azure, как с технической стороны, так и для бизнеса. Также у вас будет возможность пообщаться с технологическим евангелистом Microsoft, задать ему вопросы и посоветоваться.

Ждем вас! Регистрация по ссылке

If you are upgrading to TFS 2015 there is a very tiny chance you might hit this error:

[19:40:39.780]   System.Data.SqlClient.SqlException (0x80131904): The CREATE UNIQUE INDEX statement terminated because a duplicate key was found for the object name ‘dbo.tbl_Workspace_Dataspace’ and the index name ‘IX_tbl_OwnerId_WorkspaceName_WorkspaceVersion_Type’. The duplicate key value is (1, <GUID>, <WorkspaceName>, 1, 0).

[19:40:39.780]   Rebuilding index: IX_tbl_OwnerId_WorkspaceName_WorkspaceVersion_Type

[19:40:39.780]   ALTER INDEX [IX_tbl_OwnerId_WorkspaceName_WorkspaceVersion_Type] ON [dbo].[tbl_Workspace_Dataspace] REBUILD WITH(ONLINE=OFF, MAXDOP=0)

The workaround is to run the follow SQL Script on the TFS Collection database that failed to upgrade and then restart the upgrade job.

A customer traced a bug in their program back to the fact
that somebody passed a stack buffer to a function that operates
asynchronously.
Something like this:

// This function sends the buffer to the destination

// asynchronously. When the send completes, the completion

// handler is invoked.

HRESULT SendDataAsync(void *buffer, size_t bufferSize,

                      ITransferCompletion* completion);
class ColorSender : public ITransferCompletion

{
…

};
// Code in italics is wrong

HRESULT ColorSender::SendColor()

{

  COLORREF color = GetColorToSend();

  return SendDataAsync(&color, sizeof(color), this);

}

This bug led to the destination sometimes receiving corrupted data
because it was a race between the stack variable being
reused for something else
and the data transport code copying the buffer into
the transport channel.
In this particular case, the customer fixed the problem
by making the color local variable
a member of the Color­Sender class,
because
the Color­Sender
object itself must remain valid for the lifetime of the
transfer seeing as it is the completion handler.
(We’re using the principle that

code is mostly correct.)

The customer wanted to add some debugging code
to the Send­Data­Async function
so that it can assert that the buffer is not on the stack.
The customer understands that this may be overly restrictive,
and would not be appropriate for a function with a broad audience,
but this function is used only within their application,
so being extra-restrictive is probably okay.¹

On Windows 8 and higher,
the customer can use the
Get­Current­Thread­Stack­Limits function
to get the bounds of the current thread’s stack and use that
to verify that the buffer pointer is not in that range.
(Since this is just for debugging purposes, they can skip
the test if running on older versions of Windows,
and hope that their testing on Windows 8 will catch the
problem.)

¹ If it turns out that the check is too restrictive,
they could create two functions.
The first is called
Send­Possibly­Stack­Data­Async that
does no validation,
and the second is
Send­Data­Async
which does the initial validation that the buffer is not on the
stack, and then calls
Send­Possibly­Stack­Data­Async.
Most callers use
Send­Data­Async,
but if you’re in a special case where you are sending stack
data and you know that you won’t return from the function
until the completion occurs,
then you can use
Send­Possibly­Stack­Data­Async.
The team could have a rule that equires all uses of
Send­Possibly­Stack­Data­Async
to undergo a special review.

皆様、アクティブメモリダンプはご存知でしょうか。Windows10 から追加された新しいダンプファイルの形式です。

いかがお過ごしでしょうか。WDK サポートチームの石沢です。

アクティブメモリダンプは、その特徴として、完全メモリダンプよりファイルサイズを抑えられることが挙げられます。

また、カーネルメモリダンプには存在しない、一部のユーザー空間のメモリ情報が付加されることも挙げられるでしょう。

上記のような特徴から、完全メモリダンプを出力するほどストレージの空き容量に余裕がない、出力に時間がかかってしまう、またカーネルメモリダンプでは情報が足りないという場合の選択肢として考えられます。

もちろんデバッグ時に、潤沢なリソースや環境がある場合は、完全メモリダンプを取得いただくことをお勧めいたします。

取得方法はいたって簡単！

先日の津田さんが執筆された記事「完全メモリダンプ採取の設定方法」の手順 (4) では [完全メモリダンプ] を選択しているのですが、こちらを [アクティブ　メモリ ダンプ]に変更するだけです。

あとはダンプファイルを生成して、コールスタックを確認すれば…ユーザー空間の情報が残っていることが確認できますね！

以下の例では、ntdll や USER32 などのユーザー空間上の処理がコールスタックから確認することができています。

プロセスによってはユーザー空間の情報が残っていないため、その点ご注意いただきながら、利用場面に応じてご活用ください。

ではまたお会いいたしましょう！

WDK サポートチーム 石沢 望夢

Kabar gembira kami sampaikan dari Seattle! Froggy and the Pesticides, game ciptaan tim None Developers dari Universitas Trunojoyo Madura, berhasil meraih Juara 2 Dunia di Imagine Cup 2016 World Finals untuk kompetisi Games.

Pengumuman sekaligus pemberian hadiah dilakukan oleh Steven Guggenheimer, Corporate Vice President of Developer Experience and Evangelism and Chief Evangelist, Microsoft Corp. Adalah hal yang sangat membanggakan kembali melilhat bendera Indonesia berkibar di panggung dunia!

Sebagai juara kedua kategori Games, None Developer berhak mendapatkan hadiah sebesar USD 10 ribu, atau kurang lebih 130 juta rupiah.

Dengan tercapainya juara kedua ini, maka Indonesia mengulang kesuksesan di Imagine Cup 2013 ketika menjadi Juara 2 Dunia juga untuk kategori Games. Yang menari, ketua tim saat itu, yaitu Asadullohil Ghalib Kubat dari Solite Studio, sekarang menjadi mentor bagi tim None Developers. Ini artinya, sudah dua kali tim dari Universitas Trunojoyo Madura menjadi juara di tingkat dunia! Luar biasa!

Setelah pengumuman pemenang, None Developers bersama finalis lainnya turut berpartisipasi dalam pameran inovasi bernama //oneweek di Microsoft Campus Field. Selain finalis Imagine Cup, pameran //oneweek ini juga diisi oleh ratusan pegawai Microsoft yang menampilkan inovasi dan karya mereka yang mereka kerjakan di luar waktu kerja. Berbagai teknologi canggih terkini dari Microsoft terlibat di sana, mulai dari IoT, HoloLens, robot, dan masih banyak lagi.

Untuk merayakan hasil yang dicapai, seluruh tim mengunjungi Space Needle, ikon utama kota Microsoft. Kesempatan yang langsung dimanfaatkan oleh seluruh anggota tim untuk mengambil banyak sekali foto

Terima kasih atas dukungan doa dan semangat yang mereka terima dari semua pembaca. Sungguh suatu hal yang sangat membanggakan, bisa mewakili Indonesia dan mengibarkan bendara Merah Putih di panggung dunia!

Recently one of the customer complained that the traffic overview page in WPF RM is very slow and the data on that page is not very useful for him. So he wanted to know whether there is any way by which he can disable that page. There is a dirty trick by which you can disable it and the trick is as follows: –

The traffic overview page makes few calls to the server to get the data and those calls ultimately execute these following 4 stored procedures which probably take time. So if you disable queries from those stored procedures, the page will not show any data and should not take any time to load. The stored procedures are prc_Notification_List, prc_NotificationV2_List, prc_ReleasePath_GetTrafficOverview, prc_ReleasePathV2_GetTrafficOverview. 

1. To disable query in prc_Notification_List, comment the complete section of  ‘Insert Into #TempNotification’ query.
2. To disable query in prc_NotificationV2_List, comment the complete section of  ‘Insert Into #TempNotificationV2’ query.
3. To disable query in prc_ReleasePath_GetTrafficOverview, comment the complete sections of ‘Insert into #ReleasePath’ and ‘Insert into #ReleaseStage’
4. To disable query in prc_ReleasePathV2_GetTrafficOverview, complete the complete sections of ‘Insert into #ReleasePath’ and ‘Insert into #ReleaseStage’

In majority of the cases, you would not be required to take this step, but if you really want there is a way.

Enjoy !!

Note: – This is not a supported trick by the team and you should do it on your own risk.