搜索结果：Microsofts

The study analyzes the introduction of Microsoft 365 Copilot in a non-university research organization using a repeated cross-sectional employee survey. We assess usefulness, ease of use, output quality and reliability, and usefulness for typical knowledge-work activities. Administrative staff report higher usefulness and reliability, whereas scientific staff develop more positive assessments over time, especially regarding productivity and workload reduction. Copilot is widely viewed as user-friendly and technically reliable, with greatest added value for clearly structured, text-based tasks. The findings highlight learning and routinization effects when embedding generative AI into work processes and stress the need for context-sensitive implementation, role-specific training and governance to foster sustainable acceptance of generative AI in knowledge-intensive organizations.

Security operation centers contend with a constant stream of security incidents, ranging from straightforward to highly complex. To address this, we developed Microsoft Copilot for Security Guided Response (CGR), an industry-scale ML architecture that guides security analysts across three key tasks -- (1) investigation, providing essential historical context by identifying similar incidents; (2) triaging to ascertain the nature of the incident -- whether it is a true positive, false positive, or benign positive; and (3) remediation, recommending tailored containment actions. CGR is integrated into the Microsoft Defender XDR product and deployed worldwide, generating millions of recommendations across thousands of customers. Our extensive evaluation, incorporating internal evaluation, collaboration with security experts, and customer feedback, demonstrates that CGR delivers high-quality recommendations across all three tasks. We provide a comprehensive overview of the CGR architecture, setting a precedent as the first cybersecurity company to openly discuss these capabilities in such depth. Additionally, we release GUIDE, the largest public collection of real-world security incident

This study explores the integration of the ChatGPT API with GPT-4 model and Microsoft Copilot Studio on the Microsoft Teams platform to develop an intelligent tutoring system. Designed to provide instant support to students, the system dynamically adjusts educational content in response to the learners' progress and feedback. Utilizing advancements in natural language processing and machine learning, it interprets student inquiries, offers tailored feedback, and facilitates the educational journey. Initial implementation highlights the system's potential in boosting students' motivation and engagement, while equipping educators with critical insights into the learning process, thus promoting tailored educational experiences and enhancing instructional effectiveness.

Reliability is extremely important for large-scale cloud systems like Microsoft 365. Cloud failures such as disk failure, node failure, etc. threaten service reliability, resulting in online service interruptions and economic loss. Existing works focus on predicting cloud failures and proactively taking action before failures happen. However, they suffer from poor data quality like data missing in model training and prediction, which limits the performance. In this paper, we focus on enhancing data quality through data imputation by the proposed Diffusion+, a sample-efficient diffusion model, to impute the missing data efficiently based on the observed data. Our experiments and application practice show that our model contributes to improving the performance of the downstream failure prediction task.

In this Reply we respond to the comment by Antipov et al. from Microsoft Quantum on Hess et al., PRL 130, 207001 (2023). Antipov et al. reported only a single simulation and claimed it did not pass the Microsoft Quantum topological gap protocol (TGP). They have provided no parameters or data for this simulation (despite request). Regardless, in this reply we demonstrate that the trivial bulk gap reopening mechanism outlined in Hess et al., in combination with trivial ZBPs, passes the TGP and therefore can result in TGP false positives.

In the context of a collaboration with Berger-Levrault, an IT company producing information systems, we are working on migrating Microsoft Access monolithic applications to the web front-end and microservices back-end. Like in most software migrations, developers must learn the target technology, and they will be in charge of the evolution of the migrated system in the future. To respond to this problem, we propose the developers take over the migration project. To enable the developers to drive the migration to the target systems, we propose an Interactive, Iterative, Tooled, Rule-Based Migration approach. The contributions of this article are (i) an iterative, interactive process to language, library, GUI and architectural migration; (ii) proposal of a set of artefacts required to support such an approach; (iii) three different validations of the approach: (a) library and paradigm usage migration to Java and Pharo, (b) tables and queries migration to Java and Typescript, (c) form migration to Java Springboot and Typescript Angular.

Windows OS is facing a huge rise in kernel attacks. An overview of popular techniques that result in loading kernel drivers will be presented. One of the key targets of modern threats is disabling and blinding Microsoft Defender, a default Windows AV. The analysis of recent driver-based attacks will be given, the challenge is to block them. The survey of user- and kernel-level attacks on Microsoft Defender will be given. One of the recently published attackers techniques abuses Mandatory Integrity Control (MIC) and Security Reference Monitor (SRM) by modifying Integrity Level and Debug Privileges for the Microsoft Defender via syscalls. However, this user-mode attack can be blocked via the Windows 'trust labels' mechanism. The presented paper discovered the internals of MIC and SRM, including the analysis of Microsoft Defender during malware detection. We show how attackers can attack Microsoft Defender using a kernel-mode driver. This driver modifies the fields of the Token structure allocated for the Microsoft Defender application. The presented attack resulted in disabling Microsoft Defender, without terminating any of its processes and without triggering any Windows security fe

Modern analytical workloads are highly heterogeneous and massively complex, making generic query optimizers untenable for many customers and scenarios. As a result, it is important to specialize these optimizers to instances of the workloads. In this paper, we continue a recent line of work in steering a query optimizer towards better plans for a given workload, and make major strides in pushing previous research ideas to production deployment. Along the way we solve several operational challenges including, making steering actions more manageable, keeping the costs of steering within budget, and avoiding unexpected performance regressions in production. Our resulting system, QQ-advisor, essentially externalizes the query planner to a massive offline pipeline for better exploration and specialization. We discuss various aspects of our design and show detailed results over production SCOPE workloads at Microsoft, where the system is currently enabled by default.

There are Top three vendors in the ERP market: SAP, Oracle Net Suite and Microsoft dynamics 365 leading the Global ERP market.While analyzing the ERP selection and implementation trends, it is critical that any organization looking to implement an ERP system assesses the vendors through the lens of its own organization's specific requirements. When choosing the right ERP, a few things must be taken into consideration like the Time Budget and resources. The research paper analyses each phase and compares the methodologies of SAP, Oracle Net Suite and Microsoft Dynamics 365 and suggests the best methodologies to be practiced for any ERP projects. Like a poorly planned trip, if you don't have an effective methodology, you can expect a negative impact on your implementation, solution quality, and business satisfaction. Wrong choice of methodology may lead to poor decision-making, best practices may not be followed, and teams may be disjointed in the implementation, which can cause delays. Choosing the right ERP methodology is the key.Methodology is the lifeline for successful project implementation.

Scholarly knowledge graphs are valuable sources of information in several research fields. Despite the number of existing datasets related to publications and researchers, resource quality, coverage and accessibility are still limited. This article presents the Enhanced Microsoft Academic Knowledge Graph, a large dataset of information about scientific publications and involved entities, and the methods developed to build it. Data includes geographical information, researchers' collaborative networks and movements between institutions, academic-related metrics, and linguistic features. The dataset merges information from several data sources and has high temporal and spatial 7 coverage, allowing several use cases.

Augmented Reality is a promising technique for human-machine interaction. Especially in robotics, which always considers systems in their environment, it is highly beneficial to display visualizations and receive user input directly in exactly that environment. We explore this idea using the Microsoft HoloLens, with which we capture indoor environments and display interaction cues with known object classes. The 3D mesh recorded by the HoloLens is annotated on-line, as the user moves, with semantic classes using a projective approach, which allows us to use a state-of-the-art 2D semantic segmentation method. The results are fused onto the mesh; prominent object segments are identified and displayed in 3D to the user. Finally, the user can trigger actions by gesturing at the object. We both present qualitative results and analyze the accuracy and performance of our method in detail on an indoor dataset.

This paper analyzes the law and economics of United States v. Microsoft, a landmark case of antitrust intervention in network industries. [abridged]

Mathematical information retrieval is a relatively new area, so the first search tools capable of retrieving mathematical formulas began to appear only a few years ago. The proposals made public so far mostly implement searches on internal university databases, small sets of scientific papers, or Wikipedia in English. As such, only modest computing power is required. In this context, SearchOnMath has emerged as a pioneering tool in that it indexes several different databases and is compatible with several mathematical representation languages. Given the significantly greater number of formulas it handles, a distributed system becomes necessary to support it. The present study is based on the Microsoft BizSpark program and has aimed, for 38 different distributed-system scenarios, to pinpoint the one affording the best response times when searching the SearchOnMath databases for a collection of 120 formulas.

One often wishes to quickly add a few overlined characters such as anti-B0 or anti-neutrino to a Microsoft Word document. Underlined characters are straightforward but overlined characters require equation editor which makes small picture files. The font here allows one to directly add overlined English and the most used overlined Greek characters to Microsoft Word documents on Apple Macintosh computers.

This study describes a method to quantify potential gait changes in human subjects. Microsoft Kinect devices were used to provide and track coordinates of fifteen different joints of a subject over time. Three male subjects walk a 10-foot path multiple times with and without motion-restricting devices. Their walking patterns were recorded via two Kinect devices through frontal and sagittal planes. A modified sample entropy (SE) value was computed to quantify the variability of the time series for each joint. The SE values with and without motion-restricting devices were used to compare the changes in each joint. The preliminary results of the experiments show that the proposed quantification method can detect differences in walking patterns with and without motion-restricting devices. The proposed method has the potential to be applied to track personal progress in physical therapy sessions.

Routine ergonomic assessment of postures and gestures in the workplace are mostly conducted by visual observations, either direct or based on video recordings. Nowadays, low-cost three-dimensional cameras like Microsoft Kinect open the possibility of recording the full kinematics of workers in a non-intrusive way, providing a more precise, and reliable assessment of their motor strategies. As an illustration, we focus on a peculiar kind of workers: professional musicians (violinists), whose playing is representative of a work situation involving repeated gestures and postures that can be described as non-ergonomic. We show that the Microsoft Kinect can be efficiently used to quantify the motion performed by these musicians. Moreover, we argue that low-cost three-dimensional cameras can be a useful aid in ergonomic risk assessment of developing musculoskeletal disorders and give the example of the repetition of movements and postural items included in the OCRA checklist, whose scoring can be facilitated by such a device, as addressed in our TRACK TMS research project.

Privacy and Security are two universal rights and, to ensure that in our daily life we are secure, a lot of research is going on in the field of home security, and IoT is the turning point for the industry, where we connect everyday objects to share data for our betterment. Facial recognition is a well-established process in which the face is detected and identified out of the image. We aim to create a smart door, which secures the gateway on the basis of who we are. In our proof of concept of a smart door we have used a live HD camera on the front side of setup attached to a display monitor connected to the camera to show who is standing in front of the door, also the whole system will be able to give voice outputs by processing text them on the Raspberry Pi ARM processor used and show the answers as output on the screen. We are using a set of electromagnets controlled by the microcontroller, which will act as a lock. So a person can open the smart door with the help of facial recognition and at the same time also be able to interact with it. The facial recognition is done by Microsoft face API but our state of the art desktop application operating over Microsoft Visual Studio IDE

Large companies need to monitor various metrics (for example, Page Views and Revenue) of their applications and services in real time. At Microsoft, we develop a time-series anomaly detection service which helps customers to monitor the time-series continuously and alert for potential incidents on time. In this paper, we introduce the pipeline and algorithm of our anomaly detection service, which is designed to be accurate, efficient and general. The pipeline consists of three major modules, including data ingestion, experimentation platform and online compute. To tackle the problem of time-series anomaly detection, we propose a novel algorithm based on Spectral Residual (SR) and Convolutional Neural Network (CNN). Our work is the first attempt to borrow the SR model from visual saliency detection domain to time-series anomaly detection. Moreover, we innovatively combine SR and CNN together to improve the performance of SR model. Our approach achieves superior experimental results compared with state-of-the-art baselines on both public datasets and Microsoft production data.

Despite recent evidence that Microsoft Academic is an extensive source of citation counts for journal articles, it is not known if the same is true for academic books. This paper fills this gap by comparing citations to 16,463 books from 2013-2016 in the Book Citation Index (BKCI) against automatically extracted citations from Microsoft Academic and Google Books in 17 fields. About 60% of the BKCI books had records in Microsoft Academic, varying by year and field. Citation counts from Microsoft Academic were 1.5 to 3.6 times higher than from BKCI in nine subject areas across all years for books indexed by both. Microsoft Academic found more citations than BKCI because it indexes more scholarly publications and combines citations to different editions and chapters. In contrast, BKCI only found more citations than Microsoft Academic for books in three fields from 2013-2014. Microsoft Academic also found more citations than Google Books in six fields for all years. Thus, Microsoft Academic may be a useful source for the impact assessment of books when comprehensive coverage is not essential.