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Practicedisabling gock once you are done with your HTTP testing logic.A Go idiomatic approach for doing this can be using it in a defer statement, such as:func TestGock (t *testing.T) { defer gock.Off() // ... my test code goes here}Intercept an http.Client just onceYou don't need to intercept multiple times the same http.Client instance.Just call gock.InterceptClient(client) once, typically at the beginning of your test scenarios.Restore an http.Client after interceptionNOTE: this is not required is you are using http.DefaultClient or http.DefaultTransport.As a good testing pattern, you should call gock.RestoreClient(client) after running your test scenario, typically as after clean up hook.You can also use a defer statement for doing it, as you do with gock.Off(), such as:func TestGock (t *testing.T) { defer gock.Off() defer gock.RestoreClient(client) // ... my test code goes here}ExamplesSee examples directory for more featured use cases.Simple mocking via testspackage testimport ( "io/ioutil" "net/http" "testing" "github.com/nbio/st" "github.com/h2non/gock")func TestSimple(t *testing.T) { defer gock.Off() gock.New(" Get("/bar"). Reply(200). JSON(map[string]string{"foo": "bar"}) res, err := http.Get(" st.Expect(t, err, nil) st.Expect(t, res.StatusCode, 200) body, _ := ioutil.ReadAll(res.Body) st.Expect(t, string(body)[:13], `{"foo":"bar"}`) // Verify that we don't have pending mocks st.Expect(t, gock.IsDone(), true)}Request headers matchingpackage testimport ( "io/ioutil" "net/http" "testing" "github.com/nbio/st" "github.com/h2non/gock")func TestMatchHeaders(t *testing.T) { defer gock.Off() gock.New(" MatchHeader("Authorization", "^foo bar$"). MatchHeader("API", "1.[0-9]+"). HeaderPresent("Accept"). Reply(200). BodyString("foo foo") req, err := http.NewRequest("GET", " nil) req.Header.Set("Authorization", "foo bar") req.Header.Set("API", "1.0") req.Header.Set("Accept", "text/plain") res, err := (&http.Client{}).Do(req) st.Expect(t, err, nil) st.Expect(t, res.StatusCode, 200) body, _ := ioutil.ReadAll(res.Body) st.Expect(t, string(body), "foo foo") // Verify that we don't have pending mocks st.Expect(t, gock.IsDone(), true)}Request param matchingpackage testimport ( "io/ioutil" "net/http" "testing" "github.com/nbio/st" "github.com/h2non/gock")func TestMatchParams(t *testing.T) { defer gock.Off() gock.New(" MatchParam("page", "1"). MatchParam("per_page", "10"). Reply(200). BodyString("foo foo") req, err := http.NewRequest("GET", " nil) res, err := (&http.Client{}).Do(req) st.Expect(t, err, nil) st.Expect(t, res.StatusCode, 200) body, _ := ioutil.ReadAll(res.Body) st.Expect(t, string(body), "foo foo") // Verify that we don't have pending mocks st.Expect(t, gock.IsDone(), true)}JSON body matching and responsepackage testimport ( "bytes" "io/ioutil" "net/http" "testing" "github.com/nbio/st" "github.com/h2non/gock")func TestMockSimple(t *testing.T) { defer gock.Off() gock.New(" Post("/bar"). MatchType("json"). JSON(map[string]string{"foo": "bar"}). Reply(201). JSON(map[string]string{"bar": "foo"}) body := bytes.NewBuffer([]byte(`{"foo":"bar"}`)) res, err := http.Post(" "application/json", body) st.Expect(t, err, nil) st.Expect(t, res.StatusCode, 201) resBody, _

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:= ioutil.ReadAll(res.Body) st.Expect(t, string(resBody)[:13], `{"bar":"foo"}`) // Verify that we don't have pending mocks st.Expect(t, gock.IsDone(), true)}Mocking a custom http.Client and http.RoundTripperpackage testimport ( "io/ioutil" "net/http" "testing" "github.com/nbio/st" "github.com/h2non/gock")func TestClient(t *testing.T) { defer gock.Off() gock.New(" Reply(200). BodyString("foo foo") req, err := http.NewRequest("GET", " nil) client := &http.Client{Transport: &http.Transport{}} gock.InterceptClient(client) res, err := client.Do(req) st.Expect(t, err, nil) st.Expect(t, res.StatusCode, 200) body, _ := ioutil.ReadAll(res.Body) st.Expect(t, string(body), "foo foo") // Verify that we don't have pending mocks st.Expect(t, gock.IsDone(), true)}Enable real networkingpackage mainimport ( "fmt" "io/ioutil" "net/http" "github.com/h2non/gock")func main() { defer gock.Off() defer gock.DisableNetworking() gock.EnableNetworking() gock.New(" Get("/get"). Reply(201). SetHeader("Server", "gock") res, err := http.Get(" if err != nil { fmt.Errorf("Error: %s", err) } // The response status comes from the mock fmt.Printf("Status: %d\n", res.StatusCode) // The server header comes from mock as well fmt.Printf("Server header: %s\n", res.Header.Get("Server")) // Response body is the original body, _ := ioutil.ReadAll(res.Body) fmt.Printf("Body: %s", string(body))}Debug intercepted http requestspackage mainimport ( "bytes" "net/http" "github.com/h2non/gock")func main() { defer gock.Off() gock.Observe(gock.DumpRequest) gock.New(" Post("/bar"). MatchType("json"). JSON(map[string]string{"foo": "bar"}). Reply(200) body := bytes.NewBuffer([]byte(`{"foo":"bar"}`)) http.Post(" "application/json", body)}Hacking it!You can easily hack gock defining custom matcher functions with own matching rules.See add matcher functions and custom matching layer examples for further details.LicenseMIT - Tomas Aparicio

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Does not, you can skip this.)To check, run:ls /mnt/bootIf there is output (like grub memtest86+.bin memtest86+_multiboot.bin, but not necessarily exactly that), then the broken system's /boot is on the same partition as its / and you don't have to mount anything to access it.But if there is no output, then you will have to mount the /boot filesystem:sudo mount BOOT-PARTITION /mnt/bootReplace BOOT-PARTITION with the device name of the /boot partition (see step 6 above).chroot into the broken system, mount the remaining important virtual filesystems, and set some important environment variables:sudo chroot /mntmount -t proc none /procmount -t sysfs none /sysmount -t devpts none /dev/ptsexport HOME=/rootexport LC_ALL=CDetermine if Internet access works from within the chroot by pinging some reliable host that is known to respond normally to pings:ping -c 5 www.google.comYou should see something like this:PING www.l.google.com (74.125.131.147) 56(84) bytes of data.64 bytes from vc-in-f147.1e100.net (74.125.131.147): icmp_req=1 ttl=44 time=61.3 ms64 bytes from vc-in-f147.1e100.net (74.125.131.147): icmp_req=2 ttl=44 time=62.3 ms64 bytes from vc-in-f147.1e100.net (74.125.131.147): icmp_req=3 ttl=44 time=61.8 ms64 bytes from vc-in-f147.1e100.net (74.125.131.147): icmp_req=4 ttl=44 time=63.8 ms64 bytes from vc-in-f147.1e100.net (74.125.131.147): icmp_req=5 ttl=44 time=66.6 ms--- www.l.google.com ping statistics ---5 packets transmitted, 5 received, 0% packet loss, time 4006msrtt min/avg/max/mdev = 61.367/63.212/66.608/1.897 msIf it looks mostly like that, and the number before % packet loss is less than 100, then the Internet connection in the chroot is working:5 packets transmitted, 5 received, 0% packet loss, time 4006msIt's working, so you can skip step 11.If it looks mostly like that, and the number before % packet loss is 100, the connection needs troubleshooting. Make sure the connection on the live CD system (for example, through a web browser, or by running the same command in a separate, non-chrooted Terminal tab/window) works. Make sure you're typing the command correctly. Use www.google.com if you haven't been.If the output doesn't look like the above at all, but instead says ping: unknown host www.google.com, then networking isn't working yet in the chroot.Set up networking in the chroot. Skip this step unless you got an unknown host error in step 10 above.To set up networking, back up the broken system's hosts. Mr T Net Worth 2025 - Mr. T Net Worth 2025 Age, Height, Weight, Girlfriend, Dating, BioWiki, T’s estimated net worth is around $1.5 million. Mr T Net Worth 2025. Mr T Net Worth 2025. T net Mr T Net Worth 2025 - Mr. T Net Worth 2025 Age, Height, Weight, Girlfriend, Dating, BioWiki, T’s estimated net worth is around $1.5 million. Mr T Net Worth 2025. Mr T Net Worth 2025. T net worth leaves much to be desired.

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CiaB server and communication goes over TCP/IP with MOS protocol. if there is a failover on main CiaB server Client PC can run back up CiaB server exactly where it has stopped or + passing time for back up operation. Mirror Back Up Operation Easy Net Control can be used as exactly client server application. In order to build a MCR playout automation you need to mirror your playout server. Easy Net Control and Easy OnAir exactly works as MCR playout to build a mirrored playout server. Every action is mirrored when operator act on client reacts on playout servers. Beside client to server, Easy Net Control runs also server to client, it means, it works as bi-directional commands. Either you can control the playout server from server side, client side also will follow and react to slave server. Either operator can use from client application to control both master and slave playout servers. Client Application Easy Net Control is used as client application of Easy OnAir. For a music channel installation, Easy Net Control provides more properties than the server application, like category of list from file name, file management, MAM integration, CG Plus integration, Playlist Editor Integration, traffic systems integration and more facilities are come with Easy Net Control as Client Application. Operator can control playout server, beside playout server can control also live graphics, stream encoder, and ingest stations. Technical Requirements CPU Intel Processors • Intel i5 6600K 3.50GHz 6M 1151P CPU • Intel i7 6700K 4.00GHz 8M 1151P CPU MainBoard Asus Mainboard • Asus Z170-A LGA 1151 • Asus Z170 Pro Gaming LGA 1151 • Asus ROG Maximus VIII Ranger Gaming LGA 1151 • Asus Z170-Pro LGA 1151 • Asus Sabertooth Z170 S LGA 1151 Supermicro Mainboard • Supermicro X11SAT LGA 1151 • Supermicro X11SAT-F LGA 1151 • Supermicro X11SAE LGA 1151 • Supermicro X11SAE-F LGA 1151 Graphics Card Nvidia GeForce • NVIDIA GeForce 750TI 128B 2GB GDDR5 Memory Kingston • Kingston 16GB DDR4 2133MHZ • Kingston 16GB DDR4 2400MHZ • Kingston 16GB DDR4 2666MHZ Hard Drive OS HDD • 120GB Samsung 750 EVO • 120GB Kingston Hyperx Savage • 250GB Samsung 850 EVO • 240GB Kingston Hyperx Savage Operating System Microsoft Windows • Windows 7 Pro & Ultimate x86 or x64 • Windows 10 Pro x64 Turn-Key Systems Supermicro Turn-Key Systems • SuperWorkstation 5039A-iL• SuperWorkstation 7048A-T• SuperWorkstation 7038A-I• SuperWorkstation 5038A-I• SuperWorkstation 5038A-iL• SuperServer 5039AD-T• SuperServer 5038AD-I• SuperServer 5038AD-T• SuperWorkstation 7047A-T• SuperWorkstation 7047A-73• SuperWorkstation 7037A-i• SuperWorkstation 5037A-i HP Turn-Key Systems • HP Z240 Workstation• HP Z440 Workstation• HP Z640 Workstation• HP Z840 Workstation Program Requirements Microsoft Visual C++ Microsoft Visual C++ 2010 Redistributable Package (x86) or higher versions Microsoft .NET Framework 4.5 or higher versions Downloads SoftwareOpen or Close Please Contact Customer Service: info@easymediasuite.com User ManualOpen or Close Easy Net Control User Manual BrochureOpen or Close Easy Net Control Brochure Screenshots General Graphics User Interface General view of Easy Net Control Back Up Settings Master-Slave and M+N back up settings of Easy Net Control DVB Subtitle

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$75 million belongs to Lamar. He started his career in 2004 and he has been considered someone who has contributed to music a lot in this decade.27. Nas – Net Worth $70MhiphopdxOriginally known as Nasir Bin Olu, Nas has invested in many technology companies and these smart moves have made him that wealthy having an approximate net worth of $70 million. Nas has been in the industry since 1989 and is the co-founder of a record label called “Mass Appeal Records”.28. Will.i.am – Net Worth $70MrollingstoneWill.i.am is a member of the famous musical band “Black Eyed Peas” and has given sung some great songs like “Don’t stop the party”, “Where is the love” and “Pump It”, just to name a few. The guy’s net worth is almost $70 million as of now. He has produced the songs of many other musicians.29. Ice T – Net Worth $60MhollywoodreporterFamous for his raps on street crimes and public violence, Ice T, originally known as Tracy Marrow, is a 1958-born artist with many talents among which he has an art of making money, that has gradually resulted in his current net worth of around to be $60 million. His career began in 1982 and he has been entertaining us since then.30. Cole – Net Worth $60MrapupLast but not the least, J. Cole is here on the list with possessing net worth estimated to be $60 million as of now. His songs topped Billboard many times and he has certain awards and nominations throughout his

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And net exports, in a given country within a certain period.The Income method. The income method involves summing the total income, including salaries, business profits, and taxes, of citizens within a given country. Any subsidies, such as incentives to encourage economic activity, are not included in the calculation.Regardless of which approach is employed, the final figure should be roughly similar. However, there will be some differences to a certain extent as the GDP figure is based on different data sources.GDP FormulasThis GDP calculator employs the following formulas to determine the gross domestic product:GDP = C + I + G + NX (Expenditure Method)Where:GDP = gross domestic product, C = consumer spending, I = investment spending, G = government spending, and NX = net exports of goods and services (the value of a country's total imports extracted from its total exports).GDP = COE + I + R + P + C + T + D + N (Income Method)Where:GDP = gross domestic product, COE = compensation of employees, I = interest income, R = rents, P = proprietor's income, C = corporate profits, T = indirect business taxes, D = depreciation, and N = net factor income.You may also be interested in our Inflation Calculator or Gini Coefficient Calculator

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Data. For the image processing and fault diagnosis, the output layer is the data label. The structure of DNN is basically the same as the traditional ANN, but the training method is improved which make it have better performance. 4. Analysis of Prediction ResultsTo verify the validity of the model, the proposed model was validated in MATLAB R2018a. In this paper, the net load data of the upper bus of a city’s PV substation in the first 15 days of May 2017 were used. The sampling interval of the net load data is 5 min, and the installed capacity of the distributed PV power station is approximately 50 MW. The data from 1–11 May were selected as the training set to model the prediction model, and the parameters of the model were adjusted by cross-validation. The data from 12–15 May were selected as the samples of the prediction test, where 12 May was sunny, and 13–15 May were cloudy. 4.1. Result of the Phase Space Reconstruction by the C-C MethodThe net load data from 1–11 May were processed by the C-C method. The corresponding statistics of Δ S ¯ ( t ) and S c o r ( t ) are shown in Figure 4. The first extremum point of Δ S ¯ ( t ) was t = 7 . S c o r ( t ) had no obvious minimum point, and the optimal embedded window t ω was not obtained. According to the BDS statistics, when N > 3000 , m ∈ { 2 , 3 , 4 , 5 } , so the maximum value of m could only take 5. According to Formula (6), the final optimal embedding dimension mopt = 5 and optimal delay topt = 7 were obtained. 4.2. Prediction Results of the Deep Neural NetworkSince the embedding dimension is m = 5 as determined by the C-C method, there were five input neurons in the DNN. The cross-validation shows that when the number of layers in the hidden layer was 5, the predicted value showed a significant over-fitting. Therefore, the number of layers of the hidden layer was taken as 4, and the neurons of each hidden layer were taken as 5, 4, 3, and 2. The DNN used the single-step prediction and only predicted the next 5 min load value at a time. The predicted result is shown in Figure 5. The black solid line is the actual net load, the red solid line is the ultrashort-term prediction value based on the phase space reconstruction and DNN, and the blue dotted line is the ultrashort-term prediction value based on the traditional BP neural network.In Figure 5, at approximately 12:00 noon on a clear day (12th), a negative power was present in the payload due to an increase in the amount of PV power generation. The prediction results based on the phase space reconstruction and DNN were closer to the actual net load value, which was obviously better than the prediction results. Mr T Net Worth 2025 - Mr. T Net Worth 2025 Age, Height, Weight, Girlfriend, Dating, BioWiki, T’s estimated net worth is around $1.5 million. Mr T Net Worth 2025. Mr T Net Worth 2025. T net Mr T Net Worth 2025 - Mr. T Net Worth 2025 Age, Height, Weight, Girlfriend, Dating, BioWiki, T’s estimated net worth is around $1.5 million. Mr T Net Worth 2025. Mr T Net Worth 2025. T net worth leaves much to be desired.

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Must be completely re-entered. Details on using this program is covered in Section 7.6 of the RDU Mk2 Installation & Programming Manual LT0499. Extract the three files in the zip file and put into the directory where the existing RDU database file is for ease of use. Top of Page IO-NET SF0323 SmartConfig LITE is a Windows program for preparing an IO-NET (V2.xx) database file and downloading it to the controller. It can also read an existing database from earlier controller software versions. Top of Page QE90 EWIS LT0216 Zone naming label for QE90 fascia as Word File. LT0613 An Excel spreadsheet QE90 EWIS Configuration form that can be filled in electronically and emailed to us for manufacturing. Right click the link and Save As... to download the file. Issue 5. Top of Page T-Gen2 SF0323 This is an unlicenced version of SmartConfig that can be used to create custom configuration for T-Gen2 units. This version supports T-Gen2 Grade 2. Refer Product Bulletin PBG0209C and LT0345 for details. SF0534 V2.90 New firmware for T-Gen2. Supports Grade 3 and Grade 2 operation. Many new features and improvements have been included. Existing V1.xx T-Gen2 can be upgraded. Refer Product Bulletin PBG0216K for information. 4100ESi Security Services 2.04 Security Package required to allow the programming dongle or license to work. Top of Page

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Will occur when validating the project. The default report mode of this violation type is Warning. AutojunctionsA T-junction in a Bus is automatically connected by a junction object. If the Break Wires At Autojunctions option is enabled, on the Schematic - General page of the Preferences dialog, an existing Bus segment will be broken into two at the point where an autojunction is inserted. For example, when making a T-Junction, the perpendicular Bus segment will be broken into two segments, one on each side of the junction. With this option disabled, the Bus segment will remain unbroken at the junction.Bus EntriesA Bus Entry is a short, diagonal section of wire that allows an individual net to be 'ripped' out of a Bus (Place » Bus Entry).It also allows a net to be ripped out of a Bus in the same location as another individual net is ripped out of the Bus, as shown in the image below. If a Bus entry was not used in this situation, the two individual nets would connect together, creating a short-circuit. If it is not necessary to rip two individual nets from the same location on a Bus, a standard Wire connection can be used. Use Bus entries when the nets need to be ripped from both sides of the Bus.It is recommended that net labels in a Bus only contain alpha characters. For example, if you named the Bus D2[0..7], when the design is compiled, this would be expanded to D20, D21 .. D27, which can potentially cause net name conflicts. Printer-friendly version If you find an issue, select the text/image and pressCtrl + Enterto send us your feedback.. Mr T Net Worth 2025 - Mr. T Net Worth 2025 Age, Height, Weight, Girlfriend, Dating, BioWiki, T’s estimated net worth is around $1.5 million. Mr T Net Worth 2025. Mr T Net Worth 2025. T net

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Trans. Electr. Electron. Eng. 2019, 14, 376–382. [Google Scholar] [CrossRef]Liang, Y.; Niu, D.X.; Hong, W.C. Short term load forecasting based on feature extraction and improved general regression neural network model. Energy 2019, 166, 653–663. [Google Scholar] [CrossRef]Dai, S.Y.; Niu, D.X.; Li, Y. Daily Peak Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm. Energies 2018, 11, 163. [Google Scholar] [CrossRef]Heymann, F.; Silva, J.; Miranda, V.; Melo, J.; Soares, F.J.; Padilha-Feltrin, A. Distribution network planning considering technology diffusion dynamics and spatial net-load behavior. Int. J. Electr. Power Energy Syst. 2019, 106, 254–265. [Google Scholar] [CrossRef]Elghitani, F.; El-Saadany, E. Smoothing Net Load Demand Variations Using Residential Demand Management. IEEE Trans. Ind. Inform. 2019, 15, 390–398. [Google Scholar] [CrossRef]Kuppannagari, S.R.; Kannan, R.; Prasanna, V.K. Optimal Discrete Net-Load Balancing in Smart Grids with High PV Penetration. ACM Trans. Sens. Netw. 2018, 14, 24. [Google Scholar] [CrossRef]Zhou, X.; Zi, X.H.; Liang, L.Q.; Fan, Z.B.; Yan, J.W.; Pan, D.M. Forecasting performance comparison of two hybrid machine learning models for cooling load of a large-scale commercial building. J. Build. Eng. 2018, 21, 64–73. [Google Scholar] [CrossRef]Kong, W.C.; Dong, Z.Y.; Jia, Y.W.; Hill, D.J.; Xu, Y.; Zhang, Y. Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network. IEEE Trans. Smart Grid 2019, 10, 841–851. [Google Scholar] [CrossRef]Kim, H.S.; Eykholt, R.; Salas, J.D. Nonlinear dynamics, delay times, and embedding windows. Physica D 1999, 127, 48–60. [Google Scholar] [CrossRef] Figure 1. Single-hidden-layer neural network. Figure 1. Single-hidden-layer neural network. Figure 2. Forecasting model flow chart. Figure 2. Forecasting model flow chart. Figure 3. Deep neural network structure. Figure 3. Deep neural network structure. Figure 4. Curves of Δ S ¯ ( t ) and S c o r ( t ) . (a) Curve of statistic Δ S ¯ ( t ) ; (b) Curve of statistic S c o r ( t ) . Click here to enlarge figure --> Figure 4. Curves of Δ S ¯ ( t ) and S c o r ( t ) . (a) Curve of statistic Δ S ¯ ( t ) ; (b) Curve of statistic S c o r ( t ) . Figure 5. Load forecasting results based on different models: (a) 12 May; (b) 13 May; (c) 14 May; (d) 15 May. Figure 5. Load forecasting results based on different models: (a) 12 May; (b) 13 May; (c) 14 May; (d) 15 May. Table 1. Prediction accuracy of different models. Table 1. Prediction accuracy of different models. DateMAPE (%)RMSEC-C DNNBPNNC-C DNNBPNN12 May (Sunny)8.883818.37250.89731.332713 May (Cloudy)9.997817.68271.39701.824214 May (Cloudy)15.415617.64151.11931.364815 May (Sunny)4.06484.63881.09721.1916 © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (