TW202321907A - Virtualization environment creation method and electronic device - Google Patents
Virtualization environment creation method and electronic device Download PDFInfo
- Publication number
- TW202321907A TW202321907A TW110143653A TW110143653A TW202321907A TW 202321907 A TW202321907 A TW 202321907A TW 110143653 A TW110143653 A TW 110143653A TW 110143653 A TW110143653 A TW 110143653A TW 202321907 A TW202321907 A TW 202321907A
- Authority
- TW
- Taiwan
- Prior art keywords
- virtual environment
- hardware device
- target virtual
- target
- information
- Prior art date
Links
Images
Landscapes
- Debugging And Monitoring (AREA)
- Electrophonic Musical Instruments (AREA)
Abstract
Description
本發明是有關於一種電腦技術,且特別是有關於一種虛擬環境建立方法與電子裝置。The present invention relates to a computer technology, and in particular to a method for establishing a virtual environment and an electronic device.
隨著筆記型電腦等具運算功能的電子裝置的資料運算能力不斷提升,許多類型的電子裝置出廠時即附帶有虛擬環境(亦稱為虛擬機器(Virtualization machine, VM))的建立與執行功能。例如,微軟視窗化作業系統10(Windows 10)預設搭載用於Linux的視窗化子系統(Windows Subsystem for Linux, WSL)。WSL可運行於Windows 10的視窗化介面中,允許使用者在視窗化介面中操作Linux系統。但是,虛擬環境的建立需要設定許多資訊,例如使用者需要手動選擇要將主機裝置中哪些類型的硬體設備加入至虛擬環境中。此外,在虛擬環境建立後,也不允許使用者中途加入新的硬體設備至虛擬環境中。這些與硬體設備相關的操作限制往往在使用者操作虛擬環境時對使用者造成相當大的困擾。As the data computing capabilities of electronic devices with computing functions such as notebook computers continue to improve, many types of electronic devices are equipped with the establishment and execution functions of a virtual environment (also called a virtual machine (Virtualization machine, VM)) when they leave the factory. For example, Microsoft's Windows operating system 10 (Windows 10) is configured with a Windows Subsystem for Linux (WSL) for Linux by default. WSL can run in the windowed interface of Windows 10, allowing users to operate the Linux system in the windowed interface. However, the establishment of the virtual environment requires setting a lot of information, for example, the user needs to manually select which types of hardware devices in the host device are to be added into the virtual environment. In addition, after the virtual environment is established, the user is not allowed to add new hardware devices to the virtual environment midway. These operating limitations related to hardware devices often cause considerable trouble to users when they operate the virtual environment.
有鑑於此,本發明提供一種虛擬環境建立方法與電子裝置,可有效提高虛擬環境的建立效率。In view of this, the present invention provides a method and electronic device for establishing a virtual environment, which can effectively improve the efficiency of establishing a virtual environment.
本發明的實施例提供一種虛擬環境建立方法,其用於電子裝置。所述虛擬環境建立方法包括:根據訓練資料集訓練推理模型,其中所述訓練資料集包括至少一虛擬環境中的第一硬體設備之資訊;偵測虛擬環境建置指令;以及根據所述虛擬環境建置指令運行所述推理模型,以建立目標虛擬環境並將至少一第二硬體設備內建於所述目標虛擬環境中。An embodiment of the present invention provides a method for establishing a virtual environment, which is used in an electronic device. The method for establishing a virtual environment includes: training an inference model according to a training data set, wherein the training data set includes information of at least one first hardware device in a virtual environment; detecting a virtual environment construction instruction; and according to the virtual The environment building instruction executes the reasoning model to establish a target virtual environment and build at least one second hardware device into the target virtual environment.
本發明的實施例另提供一種電子裝置,其包括儲存電路與處理器。所述儲存電路用以儲存推理模型與訓練資料集,其中所述訓練資料集包括至少一虛擬環境中的第一硬體設備之資訊。所述處理器耦接至所述儲存電路。所述處理器用以:根據所述訓練資料集訓練所述推理模型;偵測虛擬環境建置指令;以及根據所述虛擬環境建置指令運行所述推理模型,以建立目標虛擬環境並將至少一第二硬體設備內建於所述目標虛擬環境中。An embodiment of the invention further provides an electronic device including a storage circuit and a processor. The storage circuit is used for storing the reasoning model and the training data set, wherein the training data set includes information of at least one first hardware device in the virtual environment. The processor is coupled to the storage circuit. The processor is used to: train the reasoning model according to the training data set; detect virtual environment building instructions; and run the reasoning model according to the virtual environment building instructions to create a target virtual environment and at least one The second hardware device is built in the target virtual environment.
基於上述,推理模型可根據訓練資料集進行訓練。特別是,訓練資料集可包括虛擬環境中的第一硬體設備之資訊。在偵測到虛擬環境建置指令後,所述推理模型可根據所述虛擬環境建置指令運行,以建立目標虛擬環境並將第二硬體設備內建於所述目標虛擬環境中。藉此,可有效提高虛擬環境的建立效率。Based on the above, the reasoning model can be trained according to the training data set. In particular, the training data set may include information of the first hardware device in the virtual environment. After the virtual environment building instruction is detected, the reasoning model can be run according to the virtual environment building instruction to create a target virtual environment and build a second hardware device into the target virtual environment. In this way, the efficiency of establishing the virtual environment can be effectively improved.
圖1是根據本發明的實施例所繪示的電子裝置的示意圖。請參照圖1,電子裝置10可包括智慧型手機、平板電腦、筆記型電腦、桌上型電腦、工業電腦或伺服器等各式具有資料處理功能的電子裝置。FIG. 1 is a schematic diagram of an electronic device according to an embodiment of the invention. Referring to FIG. 1 , the
電子裝置10包括處理器11、儲存電路12及輸入/輸出(I/O)介面13。處理器11用以負責電子裝置10的整體或部分運作。例如,處理器11可包括中央處理單元(Central Processing Unit, CPU)、圖形處理器(graphics processing unit, GPU)、或是其他可程式化之一般用途或特殊用途的微處理器、數位訊號處理器(Digital Signal Processor, DSP)、可程式化控制器、特殊應用積體電路(Application Specific Integrated Circuits, ASIC)、可程式化邏輯裝置(Programmable Logic Device, PLD)或其他類似裝置或這些裝置的組合。The
儲存電路12用以儲存資料。例如,儲存電路12可包括揮發性儲存電路與非揮發性儲存電路。揮發性儲存電路用以揮發性地儲存資料。例如,揮發性儲存電路可包括隨機存取記憶體(Random Access Memory, RAM)或類似的揮發性儲存媒體。非揮發性儲存電路用以非揮發性地儲存資料。例如,非揮發性儲存電路可包括唯讀記憶體(Read Only Memory, ROM)、固態硬碟(solid state disk, SSD)、傳統硬碟(Hard disk drive, HDD)或類似的非揮發性儲存媒體。The
輸入/輸出介面13可包括攝影鏡頭、通訊電路(例如網路介面卡)、滑鼠、鍵盤、觸控板、螢幕、揚聲器及/或麥克風等各式訊號的輸出/輸出裝置。本發明不限制輸入/輸出介面13的裝置類型。The input/
在一實施例中,儲存電路12可用以儲存訓練資料集101與推理模型102。訓練資料集101可用以訓練推理模型102。推理模型102可包括深度學習(deep learning)模型或神經網路(Neural Network)模型等各式可經由訓練來自主執行特定功能的人工智慧模型。In one embodiment, the
在一實施例中,訓練資料集101可包括至少一個虛擬環境中的硬體設備(亦稱為第一硬體設備)之資訊。例如,所述資訊可包括第一硬體設備的裝置類型等可用以描述第一硬體設備之資訊。此外,第一硬體設備是指應用於所述至少一虛擬環境中的硬體設備。例如,第一硬體設備可包括電子裝置10或其他電子裝置中的任意硬體設備。In an embodiment, the
在一實施例中,訓練資料集101還可包括裝置識別資訊及用以運行虛擬環境的程式之資訊的至少其中之一。例如,裝置識別資訊可包括特定電子裝置(例如電子裝置10或者其他電子裝置)的主機板序號或媒體存取控制位址(Media Access Control address, MAC address)等可用以識別特定電子裝置的資訊。此外,用以運行虛擬環境的程式之資訊則可包括用以運行虛擬環境的程式之程式名稱等可用以描述可用以運行虛擬環境的程式之資訊。In an embodiment, the
圖2是根據本發明的實施例所繪示的根據訓練資料集訓練推理模型的示意圖。請參照圖2,訓練資料集101可包括訓練資料21與22。訓練資料21包括與某一個虛擬環境(亦稱為第一虛擬環境)有關的硬體資訊211、識別資訊212及程式資訊213。硬體資訊211可包括應用於第一虛擬環境中的硬體裝置之描述資訊(例如裝置類型)。識別資訊212可包括運行第一虛擬環境的電子裝置的識別資訊(例如主機板序號)。程式資訊213可包括用以運行第一虛擬環境的程式之描述資訊(例如程式名稱)。FIG. 2 is a schematic diagram of training an inference model according to a training data set according to an embodiment of the present invention. Please refer to FIG. 2 , the
訓練資料22包括與另一個虛擬環境(亦稱為第二虛擬環境)有關的硬體資訊221、識別資訊222及程式資訊223。硬體資訊221可包括應用於第二虛擬環境中的硬體裝置之描述資訊(例如裝置類型)。識別資訊222可包括運行第二虛擬環境的電子裝置的識別資訊(例如主機板序號)。程式資訊223可包括用以運行第二虛擬環境的程式之描述資訊(例如程式名稱)。依此類推,與更多虛擬環境有關的訓練資料亦可包含於訓練資料集101中。The
在一實施例中,處理器11可根據訓練資料集101來訓練推理模型102。例如,在訓練推理模型102的過程中,訓練資料集101中的各項資訊可以被送至推理模型102中,以調整推理模型102的決策邏輯。In an embodiment, the
請回到圖1,在訓練推理模型102後,處理器11可偵測虛擬環境建置指令。例如,處理器11可經由輸入/輸出介面13偵測使用者操作並根據使用者操作獲得虛擬環境建置指令。此虛擬環境建置指令可指示建立一個虛擬環境(亦稱為目標虛擬環境)。以微軟視窗化作業系統10(Windows 10)為例,目標虛擬環境可基於WSL建立。或者,以Chrome作業系統為例,目標虛擬環境可基於Crostini建立。Please return to FIG. 1 , after training the
在一實施例中,處理器11可根據此虛擬環境建置指令運行推理模型102,以建立所述目標虛擬環境並將至少一硬體設備(亦稱為第二硬體設備)內建於目標虛擬環境中。或者,在一實施例中,處理器11可運行推理模型102,以篩選出適合內建於目標虛擬環境中的硬體設備(即第二硬體設備)。在將第二硬體設備內建於或加入至目標虛擬環境後,第二硬體設備即可於所建立的目標虛擬環境中使用。In one embodiment, the
在一實施例中,處理器11可根據虛擬環境建置指令,取得對應於目標電子裝置的裝置識別資訊。所述目標電子裝置是指用以運行目標虛擬環境的電子裝置。例如,目標電子裝置可以是電子裝置10或者其他的電子裝置。處理器11可將此裝置識別資訊輸入至推理模型102。然後,處理器11可根據推理模型102的輸出決定第二硬體設備。In one embodiment, the
圖3是根據本發明的實施例所繪示的決定第二硬體設備的示意圖。請參照圖3,處理器11可根據虛擬環境建置指令,取得識別資訊31。識別資訊31可包括目標電子裝置的裝置識別資訊(例如主機板序號)。處理器11可將識別資訊31輸入至推理模型102。推理模型102可根據識別資訊31輸出硬體資訊32。硬體資訊32可反映推理模型102預測適合內建於目標虛擬環境中的硬體設備(即第二硬體設備)。例如,硬體資訊32可包括第二硬體設備的描述資訊(例如裝置類型)。處理器11可根據硬體資訊32決定第二硬體設備。例如,第二硬體設備可包括目標電子裝置中的至少部分硬體設備。FIG. 3 is a schematic diagram of determining a second hardware device according to an embodiment of the present invention. Please refer to FIG. 3 , the
在一實施例中,處理器11可自動將第二硬體設備加入至所建立的建立目標虛擬環境中。藉此,在建立目標虛擬環境的過程中,使用者甚至可以完全不需要手動選擇欲加入至目標虛擬環境中的硬體設備。In one embodiment, the
在一實施例中,處理器11可根據第二硬體設備提供一個設備清單。此設備清單可記載第二硬體設備的描述資訊(例如裝置類型)。在建立目標虛擬環境的過程中,處理器11可根據使用者操作決定是否直接將第二硬體設備加入至所建立的目標虛擬環境中,或者需要對第二硬體設備進行刪減或補充。在一實施例中,處理器11可將使用者調整後的第二硬體設備加入至目標虛擬環境中。In one embodiment, the
在一實施例中,在建立目標虛擬環境後,在運行目標虛擬環境之期間,處理器11可偵測與至少一硬體設備(亦稱為第三硬體設備)有關的至少一中斷封包。例如,處理器11可經由目標電子裝置的作業系統偵測所述中斷封包。所述中斷封包可反映第三硬體設備在當前的操作行為中發生異常。響應於所述中斷封包,處理器11可判斷第三硬體設備是否正常運作於目標虛擬環境中。響應於第三硬體設備未正常運作於目標虛擬環境中,處理器11可根據第三硬體設備之資訊(例如裝置類型)重新訓練推理模型102,以對推理模型102進行優化。此外,若第三硬體設備正常運作於目標虛擬環境中,則處理器11可不更動推理模型102。In one embodiment, after the target virtual environment is established, the
在一實施例中,響應於所述中斷封包,處理器11可判斷第三硬體設備是否未配置於目標虛擬環境中、第三硬體設備是否在目標虛擬環境中出現異常及/或第三硬體設備的驅動程式是否在目標虛擬環境中出現異常。響應於第三硬體設備未配置於目標虛擬環境中、第三硬體設備在目標虛擬環境中出現異常及/或第三硬體設備的驅動程式在目標虛擬環境中出現異常,處理器11可判定第三硬體設備未正常運作於目標虛擬環境中。In one embodiment, in response to the interrupt packet, the
在一實施例中,一旦偵測到與第三硬體設備有關的中斷封包,處理器11可判斷第三硬體設備是否正常運作於目標虛擬環境中。若第三硬體設備未正常運作於目標虛擬環境中,處理器11可執行後續對推理模型102的優化。In one embodiment, once an interrupt packet related to the third hardware device is detected, the
在一實施例中,在偵測到與第三硬體設備有關的中斷封包後,處理器11可判斷與第三硬體設備有關的中斷封包的出現頻率是否高於預設值。響應於與第三硬體設備有關的中斷封包的出現頻率高於預設值(例如與第三硬體設備有關的中斷封包在一段時間內出現的次數高於預設數目),處理器11可執行上述判斷第三硬體設備是否正常運作於目標虛擬環境中之操作。然而,若與第三硬體設備有關的中斷封包的出現頻率未高於預設值(例如與第三硬體設備有關的中斷封包在一段時間內出現的次數不高於預設數目),則處理器11可暫不執行上述判斷第三硬體設備是否正常運作於目標虛擬環境中之操作。In one embodiment, after detecting the interrupt packet related to the third hardware device, the
在一實施例中,在根據第三硬體設備之資訊(例如裝置類型)重新訓練推理模型102的過程中,處理器11可將第三硬體設備之資訊加入至訓練資料集101的重新訓練清單中,並使用重新訓練清單中的資料來重新訓練推理模型102。In one embodiment, during the process of retraining the
以圖2為例,處理器11可將對應於目標虛擬環境的訓練資料21加入至重新訓練清單中。藉此,在重新訓練清單的訓練資料21中,硬體資訊211可包括第三硬體設備之描述資訊(例如裝置類型),識別資訊212可包括目標電子裝置的識別資訊(例如主機板序號),且程式資訊213可包括用以運行目標虛擬環境的程式之描述資訊(例如程式名稱)。處理器11可根據訓練資料21來重新訓練推理模型102,以對推理模型102進行優化。Taking FIG. 2 as an example, the
圖4是根據本發明的實施例所繪示的虛擬環境建立方法的流程圖。請參照圖4,在步驟S401中,根據訓練資料集訓練推理模型,其中訓練資料集包括至少一虛擬環境中的第一硬體設備之資訊。在步驟S402中,偵測虛擬環境建置指令。在步驟S403中,根據所述虛擬環境建置指令運行所述推理模型,以建立目標虛擬環境並將至少一第二硬體設備內建於所述目標虛擬環境中。FIG. 4 is a flowchart of a method for creating a virtual environment according to an embodiment of the present invention. Please refer to FIG. 4 , in step S401 , train an inference model according to a training data set, wherein the training data set includes information of at least a first hardware device in a virtual environment. In step S402, a virtual environment building command is detected. In step S403, the reasoning model is executed according to the virtual environment building instruction to build a target virtual environment and build at least one second hardware device into the target virtual environment.
圖5是根據本發明的實施例所繪示的虛擬環境建立方法的流程圖。請參照圖5,在步驟S501中,在運行目標虛擬環境之期間,經由電子裝置的作業系統偵測與至少一第三硬體設備有關的至少一中斷封包。在步驟S502中,判斷第三硬體設備是否正常運作於目標虛擬環境中。若第三硬體設備未正常運作於目標虛擬環境中,在步驟S503中,根據第三硬體設備之資訊重新訓練推理模型。此外,若第三硬體設備正常運作於目標虛擬環境中,則可回到步驟S501中且暫不更動推理模型。FIG. 5 is a flowchart of a method for creating a virtual environment according to an embodiment of the present invention. Please refer to FIG. 5 , in step S501 , during the running of the target virtual environment, the operating system of the electronic device detects at least one interrupt packet related to at least one third hardware device. In step S502, it is determined whether the third hardware device is normally operating in the target virtual environment. If the third hardware device does not operate normally in the target virtual environment, in step S503, retrain the reasoning model according to the information of the third hardware device. In addition, if the third hardware device is normally operating in the target virtual environment, return to step S501 and not change the reasoning model temporarily.
然而,圖4與圖5中各步驟已詳細說明如上,在此便不再贅述。值得注意的是,圖4與圖5中各步驟可以實作為多個程式碼或是電路,本發明不加以限制。此外,圖4與圖5的方法可以搭配以上範例實施例使用,也可以單獨使用,本發明不加以限制。However, each step in FIG. 4 and FIG. 5 has been described in detail above, and will not be repeated here. It should be noted that each step in FIG. 4 and FIG. 5 can be implemented as a plurality of program codes or circuits, which is not limited by the present invention. In addition, the methods shown in FIG. 4 and FIG. 5 can be used together with the above exemplary embodiments, or can be used alone, which is not limited by the present invention.
綜上所述,本發明所提出的實施例可根據訓練資料集中的與特定虛擬環境有關的資訊來訓練推理模型,以將一或多個使用者的操作習慣反映至推理模型中。經訓練的推理模型可用以預測適合內建於目標虛擬環境中的硬體設備並且在建立目標虛擬環境的同時將此些硬體設備預先加入至目標虛擬環境中。藉此,目標虛擬環境中內建的硬體設備可根據設定特定電子裝置的使用者的操作習慣而進行自動化設定,有效提高虛擬環境的建立效率。此外,在建立目標虛擬環境後,也可以根據目標虛擬環境運行過程中偵測到的中斷封包來動態對推理模型進行優化。To sum up, the embodiments of the present invention can train the reasoning model according to the information related to the specific virtual environment in the training data set, so as to reflect the operating habits of one or more users into the reasoning model. The trained reasoning model can be used to predict hardware devices suitable for being built into the target virtual environment and pre-add these hardware devices into the target virtual environment while establishing the target virtual environment. In this way, the built-in hardware equipment in the target virtual environment can be automatically set according to the operating habit of the user who sets the specific electronic device, effectively improving the efficiency of establishing the virtual environment. In addition, after the target virtual environment is established, the inference model can also be dynamically optimized according to the interrupt packets detected during the running of the target virtual environment.
雖然本發明已以實施例揭露如上,然其並非用以限定本發明,任何所屬技術領域中具有通常知識者,在不脫離本發明的精神和範圍內,當可作些許的更動與潤飾,故本發明的保護範圍當視後附的申請專利範圍所界定者為準。Although the present invention has been disclosed above with the embodiments, it is not intended to limit the present invention. Anyone with ordinary knowledge in the technical field may make some changes and modifications without departing from the spirit and scope of the present invention. The scope of protection of the present invention should be defined by the scope of the appended patent application.
10:電子裝置
11:處理器
12:儲存電路
13:輸入/輸出(I/O)介面
101:訓練資料集
102:推理模型
21, 22:訓練資料
211, 221, 32:硬體資訊
212, 222, 31:識別資訊
213, 223:程式資訊
S401~S403, S501~S503:步驟
10: Electronic device
11: Processor
12: storage circuit
13: Input/output (I/O) interface
101:Training dataset
102:
圖1是根據本發明的實施例所繪示的電子裝置的示意圖。 圖2是根據本發明的實施例所繪示的根據訓練資料集訓練推理模型的示意圖。 圖3是根據本發明的實施例所繪示的決定第二硬體設備的示意圖。 圖4是根據本發明的實施例所繪示的虛擬環境建立方法的流程圖。 圖5是根據本發明的實施例所繪示的虛擬環境建立方法的流程圖。 FIG. 1 is a schematic diagram of an electronic device according to an embodiment of the invention. FIG. 2 is a schematic diagram of training an inference model according to a training data set according to an embodiment of the present invention. FIG. 3 is a schematic diagram of determining a second hardware device according to an embodiment of the present invention. FIG. 4 is a flowchart of a method for creating a virtual environment according to an embodiment of the present invention. FIG. 5 is a flowchart of a method for creating a virtual environment according to an embodiment of the present invention.
S401~S403:步驟 S401~S403: steps
Claims (10)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
TW110143653A TWI811862B (en) | 2021-11-24 | 2021-11-24 | Virtualization environment creation method and electronic device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
TW110143653A TWI811862B (en) | 2021-11-24 | 2021-11-24 | Virtualization environment creation method and electronic device |
Publications (2)
Publication Number | Publication Date |
---|---|
TW202321907A true TW202321907A (en) | 2023-06-01 |
TWI811862B TWI811862B (en) | 2023-08-11 |
Family
ID=87803746
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
TW110143653A TWI811862B (en) | 2021-11-24 | 2021-11-24 | Virtualization environment creation method and electronic device |
Country Status (1)
Country | Link |
---|---|
TW (1) | TWI811862B (en) |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP3516516B1 (en) * | 2016-09-21 | 2022-05-11 | Accenture Global Solutions Limited | Dynamic resource allocation for application containers |
JP6988040B2 (en) * | 2016-12-31 | 2022-01-05 | インテル・コーポレーション | Systems, methods and equipment for heterogeneous computing |
KR20200106036A (en) * | 2017-12-08 | 2020-09-10 | 넷-썬더, 엘엘씨 | Automatically distributed information technology (IT) systems and methods |
US11055809B2 (en) * | 2019-06-28 | 2021-07-06 | Intel Corporation | Apparatus and method for provisioning virtualized multi-tile graphics processing hardware |
US20210165673A1 (en) * | 2019-12-02 | 2021-06-03 | Microsoft Technology Licensing, Llc | Enabling shared graphics and compute hardware acceleration in a virtual environment |
-
2021
- 2021-11-24 TW TW110143653A patent/TWI811862B/en active
Also Published As
Publication number | Publication date |
---|---|
TWI811862B (en) | 2023-08-11 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US8335935B2 (en) | Power management based on automatic workload detection | |
US9710137B2 (en) | Handedness detection | |
US20140152583A1 (en) | Optimistic placement of user interface elements on a touch screen | |
JP2016058027A (en) | Data processing device, data processing method, and program | |
US10705865B2 (en) | Disk resize of a virtual machine | |
US9645873B2 (en) | Integrated configuration management and monitoring for computer systems | |
TWI811862B (en) | Virtualization environment creation method and electronic device | |
JP6293910B2 (en) | Hardware acceleration for inline caching in dynamic languages | |
JP7173308B2 (en) | DETECTION DEVICE, DETECTION METHOD AND DETECTION PROGRAM | |
WO2023093260A1 (en) | Instruction processing apparatus and method, and computer device and storage medium | |
KR102091409B1 (en) | Electronic apparatus and control method thereof | |
EP3014426B1 (en) | Self-revealing symbolic gestures | |
TWI697776B (en) | Computer system, updating method thereof and computer program product | |
TWI652622B (en) | Electronic computing device, method for adjusting trigger mechanism of memory recovery function and computer program product thereof | |
US10162602B2 (en) | Method for handling user-level events for programming an application | |
TW202006519A (en) | Method of changing identified type of touch object | |
JP2018113031A (en) | Method and system for detecting automated input | |
CN106940657A (en) | A kind of method and terminal that task distribution is carried out to processor | |
US20170102987A1 (en) | Device expected state monitoring and remediation | |
US10678404B2 (en) | Operation of a data processing system during graphical user interface transitions | |
CN106775941A (en) | A kind of virtual machine kernel completeness protection method and device | |
EP3210101A1 (en) | Hit-test to determine enablement of direct manipulations in response to user actions | |
US11803459B2 (en) | Latency tolerance reporting value determinations | |
TWI701595B (en) | Memory performance optimization method and motherboard using the same | |
US11836314B1 (en) | Sensitivity adjustment for a touchpad of an information handling system |