Легалізація громадських, благодійних організацій, ОСББ, ОСНLawngo
Новий практичний посібник «Легалізація та держреєстрація громадських, благодійних організацій, інших організацій у сфері місцевого розвитку» у частині процедур реєстрації благодійних та громадських організацій доповнений та змінений із врахуванням нових положень законодавства, а також підходів у практиці, враховуючи дворічну роботу програми правової підтримки неурядових організацій Центру громадської адвокатури, надання правових консультації, складання документів на реєстрацію організацій, іншого правового супроводу громадських ініціатив.
www.lawngo.net
Este documento compara fotografias de vários locais do centro de São Paulo em diferentes épocas, mostrando as transformações ocorridas ao longo do tempo, como a construção e demolição de prédios e a modernização da infraestrutura urbana.
Tutorial ini menjelaskan langkah-langkah dasar membuat model rumah sederhana di Blender, meliputi: (1) menambahkan gambar denah sebagai latar belakang, (2) mengubah ukuran objek plane sesuai denah, (3) mengekstrud dinding dan pondasi, (4) membuat atap dengan mengekstrud dan menambahkan permukaan.
1. The document discusses various statistics related to COVID-19 cases in the United States between January 22, 2020 and May 15, 2020.
2. It provides daily totals of confirmed COVID-19 cases and deaths for several states over this time period.
3. The data is organized into tables with columns for date, state, confirmed cases, and deaths.
São Paulo no início do século XX: bondes, teatros e hotéis icônicos da cidade. O documento descreve locais e transportes de São Paulo até 1940, incluindo fotos do bonde "camarão", do Observatório Astronômico, do Vale do Anhangabaú e da Represa de Santo Amaro.
Este documento descreve um projeto de aprendizagem sobre modelagem matemática e funções lineares. O projeto visa mostrar como a matemática está presente no nosso cotidiano através do uso de celulares. Os alunos irão pesquisar preços de ligações de duas operadoras e construir gráficos comparativos usando o software Winplot. Ao analisar os gráficos, os alunos poderão identificar qual operadora oferece o melhor custo-benefício com base no tempo de ligação.
Легалізація громадських, благодійних організацій, ОСББ, ОСНLawngo
Новий практичний посібник «Легалізація та держреєстрація громадських, благодійних організацій, інших організацій у сфері місцевого розвитку» у частині процедур реєстрації благодійних та громадських організацій доповнений та змінений із врахуванням нових положень законодавства, а також підходів у практиці, враховуючи дворічну роботу програми правової підтримки неурядових організацій Центру громадської адвокатури, надання правових консультації, складання документів на реєстрацію організацій, іншого правового супроводу громадських ініціатив.
www.lawngo.net
Este documento compara fotografias de vários locais do centro de São Paulo em diferentes épocas, mostrando as transformações ocorridas ao longo do tempo, como a construção e demolição de prédios e a modernização da infraestrutura urbana.
Tutorial ini menjelaskan langkah-langkah dasar membuat model rumah sederhana di Blender, meliputi: (1) menambahkan gambar denah sebagai latar belakang, (2) mengubah ukuran objek plane sesuai denah, (3) mengekstrud dinding dan pondasi, (4) membuat atap dengan mengekstrud dan menambahkan permukaan.
1. The document discusses various statistics related to COVID-19 cases in the United States between January 22, 2020 and May 15, 2020.
2. It provides daily totals of confirmed COVID-19 cases and deaths for several states over this time period.
3. The data is organized into tables with columns for date, state, confirmed cases, and deaths.
São Paulo no início do século XX: bondes, teatros e hotéis icônicos da cidade. O documento descreve locais e transportes de São Paulo até 1940, incluindo fotos do bonde "camarão", do Observatório Astronômico, do Vale do Anhangabaú e da Represa de Santo Amaro.
Este documento descreve um projeto de aprendizagem sobre modelagem matemática e funções lineares. O projeto visa mostrar como a matemática está presente no nosso cotidiano através do uso de celulares. Os alunos irão pesquisar preços de ligações de duas operadoras e construir gráficos comparativos usando o software Winplot. Ao analisar os gráficos, os alunos poderão identificar qual operadora oferece o melhor custo-benefício com base no tempo de ligação.
• Cembre foot operated double speed pump developing a pressure of 700 bar
• Cembre PO 7000 foot pump supplied complete with 3 metre long high pressure flexible hose complete with female self locking quick coupler
• Foot pump pressure can be released at any time by depressing the built in quick release lever
• Cembre PO 7000 foot pump features a solid shaped stand giving the pump stability during operation
• Supplied with a robust moulded case for storage of the Cembre toot pump
Dokumen tersebut membahas tentang contoh pengukur kekuatan password pada GMail dan beberapa faktor yang mempengaruhi kekuatan password seperti panjang, kompleksitas, dan tingkat keacakan password. Dokumen ini juga menyinggung tentang pentingnya mempertimbangkan informasi pribadi pengguna dalam memilih password untuk mencegah menebak password.
The document discusses concurrency and synchronization in distributed computing. It provides an overview of Petr Kuznetsov's research at Telecom ParisTech, which includes algorithms and models for distributed systems. Some key points discussed are:
- Concurrency is important due to multi-core processors and distributed systems being everywhere. However, synchronization between concurrent processes introduces challenges.
- Common synchronization problems include mutual exclusion, readers-writers problems, and producer-consumer problems. Tools for synchronization include semaphores, transactional memory, and non-blocking algorithms.
- Characterizing distributed computing models and determining what problems can be solved in a given model is an important area of research, with implications for distributed system design.
The document discusses weakly supervised learning from video and images using convolutional neural networks. It describes using scripts as weak supervision for learning actions from movies without explicit labeling. Methods are presented for jointly learning actors and actions from scripts, and for action learning with ordering constraints. The use of CNNs for object and action recognition in images is also summarized, including work on training CNNs using only image-level labels without bounding boxes.
This document discusses common C++ bugs and tools to find them. It describes various types of memory access bugs like buffer overflows on the stack, heap, and globals that can lead to crashes or security vulnerabilities. Threading bugs like data races, deadlocks, and race conditions on object destruction are also covered. Other undefined behaviors like initialization order issues, lack of sequence points, and integer overflows are explained. The document provides examples of each type of bug and emphasizes that undefined behavior does not guarantee a predictable result. It concludes with a quiz to find bugs in a code sample and links to additional reading materials.
AddressSanitizer, ThreadSanitizer, and MemorySanitizer are compiler-based tools that detect bugs like buffer overflows, data races, and uninitialized memory reads in C/C++ programs. AddressSanitizer instruments loads and stores to detect out-of-bounds memory accesses. ThreadSanitizer intercepts synchronization calls to detect data races between threads. MemorySanitizer tracks initialized and uninitialized memory using shadow memory to find uses of uninitialized values. The tools have found thousands of bugs with low overhead. Future work includes supporting more platforms and languages and detecting additional bug classes.
This document discusses common C++ bugs and tools to find them. It describes various types of memory access bugs like buffer overflows on the stack, heap, and globals that can lead to crashes or security vulnerabilities. Threading bugs like data races, deadlocks, and race conditions on object destruction are also covered. Other undefined behaviors like initialization order issues, lack of sequence points, and integer overflows are explained. The document provides examples of each type of bug and quizzes the reader to find bugs in a code sample. It recommends resources for further reading on debugging techniques and thread sanitizers that can detect races and data races.
This document provides examples and snippets of code for MapReduce, Pig, Hive, Spark, Shark, and Disco frameworks. It also includes two sections of references for related papers and Disco documentation. The examples demonstrate basic MapReduce jobs with drivers, mappers, and reducers in Java, Pig and Hive queries, Spark and Shark table operations, and a Disco MapReduce job.
30. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Îáùàÿ èäåÿ
Ñóòü àëãîðèòìà ïîõîæà íà âûáîðêó ñ îòêëîíåíèåì, íî åñòü
âàæíîå îòëè÷èå.
Ðàñïðåäåëåíèå q òåïåðü áóäåò ìåíÿòüñÿ ñî âðåìåíåì,
çàâèñåòü îò òåêóùåãî ñîñòîÿíèÿ àëãîðèòìà.
Êàê è ïðåæäå, íóæíî ðàñïðåäåëåíèå q , òî÷íåå, ñåìåéñòâî
q (x ; x (t ) ), ãäå x (t ) òåêóùåå ñîñòîÿíèå.
Íî òåïåðü q íå äîëæíî áûòü ïðèáëèæåíèåì p , à äîëæíî
ïðîñòî áûòü êàêèì-íèáóäü ñýìïëèðóåìûì ðàñïðåäåëåíèåì
(íàïðèìåð, ñôåðè÷åñêèé ãàóññèàí).
Êàíäèäàò â íîâîå ñîñòîÿíèå x ñýìïëèðóåòñÿ èç q (x ; x (t ) ).
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
31. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Àëãîðèòì
Î÷åðåäíàÿ èòåðàöèÿ íà÷èíàåòñÿ ñ ñîñòîÿíèÿ x (i ) .
Âûáðàòü x ïî ðàñïðåäåëåíèþ q (x ; x (i ) ).
Âû÷èñëèòü
(i ) x
a = p∗ (x(i )) q (x ; (i ) ) .
∗
p (x ) q (x ; x )
Ñ âåðîÿòíîñòüþ a (1, åñëè a ≥ 1) x (i +1) := x , èíà÷å
x (i +1) := x (i ) .
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
32. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Îáñóæäåíèå
Ñóòü â òîì, ÷òî ìû ïåðåõîäèì â íîâûé öåíòð
ðàñïðåäåëåíèÿ, åñëè ïðèìåì î÷åðåäíîé øàã.
Ïîëó÷àåòñÿ ýòàêèé random walk, çàâèñÿùèé îò
ðàñïðåäåëåíèÿ p ∗ .
q(x (i ) ;x ) äëÿ ñèììåòðè÷íûõ ðàñïðåäåëåíèé (ãàóññèàíà)
q ( x ; x (i ) )
ðàâíî 1, ýòî ïðîñòî ïîïðàâêà íà àñèììåòðèþ.
Îòëè÷èå îò rejection sampling: åñëè íå ïðèìåì, òî íå
ïðîñòî îòáðàñûâàåì øàã, à çàïèñûâàåì x (i ) åù¼ ðàç.
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
45. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Èç ÷åãî äåëàþò ìàðêîâñêèå öåïè: êîíêàòåíàöèÿ
Ìîæíî êîíêàòåíèðîâàòü ðàñïðåäåëåíèÿ, çàïóñêàÿ èõ äðóã
çà äðóãîì:
T (x , x ) = T2 (x , x )T1 (x , x )dx .
Ïðè ýòîì ñîõðàíÿåòñÿ èíâàðèàíòíîå ðàñïðåäåëåíèå
(äîêàæèòå).
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
46. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Èç ÷åãî äåëàþò ìàðêîâñêèå öåïè: ñìåñü
Ìîæíî ñìåøèâàòü ðàñïðåäåëåíèÿ. Åñëè áûëè ôóíêöèè
Ti (x , x ), òî ìîæíî ââåñòè íîâóþ
T (x , x ) = pi Ti (x , x ), ãäå pi = 1.
i i
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
47. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Óñëîâèå áàëàíñà
Åù¼ îäíî ïîëåçíîå ñâîéñòâî:
∀x , y T (x , y )p(y ) = T (y , x )p(x ).
Ò.å. âåðîÿòíîñòü òîãî, ÷òî ìû âûáåðåì x è äîéä¼ì äî y ,
ðàâíà âåðîÿòíîñòè âûáðàòü y è äîéòè äî x .
Òàêèå öåïè íàçûâàþòñÿ îáðàòèìûìè (reversible).
Åñëè âûïîëíÿåòñÿ óñëîâèå áàëàíñà, òî p (x )
èíâàðèàíòíîå ðàñïðåäåëåíèå. Ýòî ñâîéñòâî ìîæåò
ïðèãîäèòüñÿ.
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
48. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Ñóòü
Slice sampling åù¼ îäèí àëãîðèòì, ïîõîæèé íà àëãîðèòì
Ìåòðîïîëèñà.
Ïðèìåíÿåòñÿ â òåõ æå ñèòóàöèÿõ, íî â í¼ì áîëüøå
íàñòðàèâàåìûõ ïàðàìåòðîâ è âîîáùå ãèáêîñòè.
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
49. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Àëãîðèòì â îäíîìåðíîì ñëó÷àå
Ìû õîòèì ñäåëàòü random walk èç îäíîé òî÷êè ïîä
ãðàôèêîì p ∗ â äðóãóþ òî÷êó ïîä ãðàôèêîì p ∗ , äà òàê,
÷òîáû â ïðåäåëå ïîëó÷èëîñü ðàâíîìåðíîå ðàñïðåäåëåíèå.
Âîò êàê áóäåì äåëàòü ïåðåõîä (x , u ) → (x , u ):
Âû÷èñëèì p ∗ (x ) è âûáåðåì u [0, p ∗ (x )].
ðàâíîìåðíî èç
Ñäåëàåì ãîðèçîíòàëüíûé èíòåðâàë (x , x ) âîêðóã x .
l r
Çàòåì áóäåì âûáèðàòü x ðàâíîìåðíî èç (x , x ), ïîêà íå l r
ïîïàä¼ì ïîä ãðàôèê.
Åñëè íå ïîïàäàåì, ìîäèôèöèðóåì (x , x ).
l r
Îñòàëîñü ïîíÿòü, êàê ñäåëàòü (xl , xr ) è êàê åãî ïîòîì
ìîäèôèöèðîâàòü.
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
50. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Äîïîëíåíèÿ ê àëãîðèòìó
Èñõîäíûé âûáîð (xl , xr ):
Âûáðàòü r ðàâíîìåðíî èç [0, ].
x := x − r , x := x + ( − r ).
l r
Ðàçäâèãàòü ãðàíèöû íà , ïîêà p ∗ (x ) u
l è p ∗ (x ) u
r .
Ìîäèôèêàöèÿ (xl , xr ): Åñëè x ëåæèò âûøå p∗ , ñîêðàùàåì
èíòåðâàë äî x .
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
51. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Ñâîéñòâà
 àëãîðèòìå Ìåòðîïîëèñà íóæíî áûëî âûáèðàòü ðàçìåð
øàãà. È îò íåãî âñ¼ çàâèñåëî êâàäðàòè÷íî.
À òóò ðàçìåð øàãà ïîäïðàâëÿåòñÿ ñàì ñîáîé, è ýòà
ïîïðàâêà ïðîèñõîäèò çà ëèíåéíîå âðåìÿ (à òî è ëîãàðèôì).
 çàäà÷àõ ñ áîëüøîé ðàçìåðíîñòüþ íóæíî ñíà÷àëà
âûáðàòü (ñëó÷àéíî èëè ñîâïàäàþùèìè ñ îñÿìè)
íàïðàâëåíèå èçìåíåíèÿ y , à ïîòîì ïðîâîäèòü àëãîðèòì
îòíîñèòåëüíî ïàðàìåòðà α â ðàñïðåäåëåíèè p ∗ (x + αy ).
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
52. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Èäåÿ
Ðàññìîòðèì ñèòóàöèþ, êîãäà âåðîÿòíîñòü ìîæíî çàïèñàòü
êàê p (x ) = Z e −E (x ) .
1
Âî ìíîãèõ òàêèõ ñëó÷àÿõ ìîæíî âû÷èñëèòü íå òîëüêî
E (x ), íî è ãðàäèåíò E (x ).
Òàêóþ èíôîðìàöèþ õîòåëîñü áû èñïîëüçîâàòü.
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã
53. Ââåäåíèå è òðèâèàëüíûå ïîäõîäû Àëãîðèòì ÌåòðîïîëèñàÃàñòèíãñà è ñýìïëèðîâàíèå ïî Ãè
Âûáîðêà ïî çíà÷èìîñòè è âûáîðêà ñ îòêëîíåíèåì Ìàðêîâñêèå ìåòîäû è slice sampling
Ìàðêîâñêèå ìåòîäû ÌîíòåÊàðëî Êàê ñîêðàòèòü ñëó÷àéíîå áëóæäàíèå
Ãàìèëüòîíîâà ìåõàíèêà
Çàéì¼ìñÿ ìàòôèçèêîé: ðàññìîòðèì ìåõàíè÷åñêóþ ñèñòåìó.
Ñîñòîÿíèå ñèñòåìû îïèñûâàåòñÿ îáîáù¼ííûìè
êîîðäèíàòàìè q è îáîáù¼ííûìè ìîìåíòàìè p (âåêòîðíûå
ïåðåìåííûå).
ż îáùàÿ ýíåðãèÿ H (q , p , t ) = V (q , t ) + K (p , t ), ãäå V
ïîòåíöèàëüíàÿ, K êèíåòè÷åñêàÿ.
Ñåðãåé Íèêîëåíêî Ìåòîäû ÌîíòåÊàðëî: ñýìïëèíã