Relevant bibliographies by topics / Microsoft Visio;Evaluation

Academic literature on the topic 'Microsoft Visio;Evaluation'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Microsoft Visio;Evaluation"

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Pahlevanynejad, Shahrbanoo, Navid Danaei, and Reza Safdari. "Design, implementation, and evaluation of an innovative intelligence information management system for premature infants." DIGITAL HEALTH 8 (January 2022): 205520762211277. http://dx.doi.org/10.1177/20552076221127776.

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Introduction Low birth weight is the most important condition of neonatal community health and the main cause of neonates' mortality. Identifying the indexes associated with this condition, and factors to prevent, and managing related data can help reduce the birth of premature infants to reduce the mortality rate due to this condition. The goal of present study was to design, implement and evaluate an innovative intelligence information management system for premature infants. Material and method The present study was a multidisciplinary research that was done in 2019 to 2021 in four integrated phases in Iran. The first phase aimed to compare the current status of registration systems of premature infants through a systematic review and semi-structured interviews by using the Delphi model Then the minimum data set was determined and was designed a proposed model based on it. In the second phase, the structure and how the user interacts with the system were determined, and, using Microsoft Visio software, Unified Modeling Language diagrams were drawn to define the logical relationship of data. In the third phase, the system was developed, and finally in the last phase, in three methods, users' views on the usability of the system were evaluated. Results The findings of this study included 233 essential data elements that were placed in two main groups of essential data, and the system was approved by end users for 87.73% consent and 67.19% satisfaction for SUMI (Software Usability Measurement Inventory) and 7.97 of 9 in QUIS questionnaire. Conclusion This research's results can be beneficial and functional such as a complete sample for design and development of other systems concerned to health systems.
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Korsoveczki, Gyula, Balázs Bencsik, and Géza Husi. "Optical Inspection of CPVC Fitting Elbows and Fault Diagnosis of the Production Process." Műszaki Tudományos Közlemények 15, no. 1 (October 1, 2021): 56–60. http://dx.doi.org/10.33894/mtk-2021.15.11.

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Abstract The topic of this study is the optical inspection of CPVC fitting elbows concerning the geometric parameters that can be detected in 2 dimensions. Based on the evaluation of the results, fault diagnosis has been set up for the production line by statistical calculations. The optical inspection was carried out in the Vision Development Module software environment produced by National Instruments, and the data were evaluated using Microsoft Excel.
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Fiqri, Arijalul, Yuda Syahidin, and Meira Hidayati. "PERANCANGAN SISTEM INFORMASI KUNJUNGAN PASIEN RAWAT JALAN BERBASIS WEB." Jurnal SAINTEKOM 12, no. 1 (March 2, 2022): 81–91. http://dx.doi.org/10.33020/saintekom.v12i1.225.

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The design of an outpatient visit information system is a form of need for the hospital system which is believed to provide convenience for medical record officers in analyzing outpatient visit data. I hope that with the outpatient information system it can be easier to access data and store data. The outpatient visit system is not computerized and officers need to re-enter visit data to manage patient visit data and this is quite time-consuming which causes the information produced to be slow, less accurate and irrelevant. For this reason, researchers evaluate the existing work system at the hospital order to improve good system governance. Researchers use Microsoft Visual Studio 2010 determining the program. The results in this system are that initial introduction to prospective system users, a performance evaluation is carried out to anticipate changes information needs the future and is more thorough in lending and storing medical record files.
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Meli, Leonardo, Claudio Pacchierotti, Gionata Salvietti, Francesco Chinello, Maurizio Maisto, Alessandro De Luca, and Domenico Prattichizzo. "Combining Wearable Finger Haptics and Augmented Reality: User Evaluation Using an External Camera and the Microsoft HoloLens." IEEE Robotics and Automation Letters 3, no. 4 (October 2018): 4297–304. http://dx.doi.org/10.1109/lra.2018.2864354.

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Haenel, R., Q. Semler, E. Semin, P. Grussenmeyer, and S. Tabbone. "EVALUATION OF LOW-COST DEPTH SENSORS FOR OUTDOOR APPLICATIONS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W1-2022 (December 8, 2022): 101–8. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-w1-2022-101-2022.

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Abstract. Depth information is a key component that allows a computer to reproduce human vision in plenty of applications from manufacturing, to robotics and autonomous driving. The Microsoft Kinect has brought depth sensing to another level resulting in a large number of low cost, small form factor depth sensors. Although these sensors can efficiently produce data over a wide dynamic range of sensing applications and within different environments, most of them are rather suitable for indoor applications. Operating in outdoor areas is a challenge because of undesired illumination, usually strong sunlight or surface scattering, which degrades measurement accuracy. Therefore, after presenting the different working principle of existing depth cameras, our study aims to evaluate where two very recent sensors, the AD-FXTOF1-EBZ and the flexx2, stand towards the issue of outdoor environment. In particular, measurement tests will be performed on different types of materials subjected to various illumination in order to evaluate the potential accuracy of such sensors.
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Valdivia, Sergio, Robin Blanco, Alvaro Uribe-Quevedo, Lina Penuela, David Rojas, and Bill Kapralos. "Development and evaluation of two posture-tracking user interfaces for occupational health care." Advances in Mechanical Engineering 10, no. 6 (June 2018): 168781401876948. http://dx.doi.org/10.1177/1687814018769489.

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The spinal column requires special care through exercises focused on muscle strengthening, flexibility, and mobility to minimize the risk of developing musculoskeletal disorders that may affect the quality of life. Guidelines for spinal column exercises are commonly presented through printed and multimedia guides accompanied with demonstrations performed by a physiotherapist, occupational health expert, or physical fitness trainer. However, existing guides lack interaction and oral explanations may not always be clear to the user, leading to decreased engagement and motivation to start, continue, or complete an exercise program. In this article, we present two interactive and engaging posture-tracking user interfaces intended to promote proper spinal column exercise form. One user interface employs a wooden manikin with an integrated inertial measurement unit to provide a tangible user interaction. The other user interface presents a mobile application that provides instructions and explanations about the exercises. Both user interfaces allow recording key postures during the exercise for reference and feedback. We compared the usability of the interfaces through a series of flexion and extension exercises, monitored with an inertial measuring unit worn around the torso, and a Microsoft Kinect V2 vision-based sensor. Although no significant differences between the manikin user interface and the mobile application were found in terms of usability, the inertial measurement unit provided more accurate and reliable data in comparison to the Microsoft Kinect V2 as a result of body occlusions in front of the sensor caused during the torso flexion. Although both user interfaces provide different experiences and performed well, we believe that a combination of both will improve user engagement and motivation, while providing a more accurate motion profile.
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Jeon, Sanghun, and Mun Sang Kim. "End-to-End Lip-Reading Open Cloud-Based Speech Architecture." Sensors 22, no. 8 (April 12, 2022): 2938. http://dx.doi.org/10.3390/s22082938.

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Deep learning technology has encouraged research on noise-robust automatic speech recognition (ASR). The combination of cloud computing technologies and artificial intelligence has significantly improved the performance of open cloud-based speech recognition application programming interfaces (OCSR APIs). Noise-robust ASRs for application in different environments are being developed. This study proposes noise-robust OCSR APIs based on an end-to-end lip-reading architecture for practical applications in various environments. Several OCSR APIs, including Google, Microsoft, Amazon, and Naver, were evaluated using the Google Voice Command Dataset v2 to obtain the optimum performance. Based on performance, the Microsoft API was integrated with Google’s trained word2vec model to enhance the keywords with more complete semantic information. The extracted word vector was integrated with the proposed lip-reading architecture for audio-visual speech recognition. Three forms of convolutional neural networks (3D CNN, 3D dense connection CNN, and multilayer 3D CNN) were used in the proposed lip-reading architecture. Vectors extracted from API and vision were classified after concatenation. The proposed architecture enhanced the OCSR API average accuracy rate by 14.42% using standard ASR evaluation measures along with the signal-to-noise ratio. The proposed model exhibits improved performance in various noise settings, increasing the dependability of OCSR APIs for practical applications.
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Song, Zeliang, Xiaofei Zhou, Zhendong Mao, and Jianlong Tan. "Image Captioning with Context-Aware Auxiliary Guidance." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 3 (May 18, 2021): 2584–92. http://dx.doi.org/10.1609/aaai.v35i3.16361.

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Image captioning is a challenging computer vision task, which aims to generate a natural language description of an image. Most recent researches follow the encoder-decoder framework which depends heavily on the previous generated words for the current prediction. Such methods can not effectively take advantage of the future predicted information to learn complete semantics. In this paper, we propose Context-Aware Auxiliary Guidance (CAAG) mechanism that can guide the captioning model to perceive global contexts. Upon the captioning model, CAAG performs semantic attention that selectively concentrates on useful information of the global predictions to reproduce the current generation. To validate the adaptability of the method, we apply CAAG to three popular captioners and our proposal achieves competitive performance on the challenging Microsoft COCO image captioning benchmark, e.g. 132.2 CIDEr-D score on Karpathy split and 130.7 CIDEr-D (c40) score on official online evaluation server.
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Anthwal, Shivangi. "Modelling and Analysis of Facial Expressions Using Optical Flow Derived Divergence and Curl Templates." ELCVIA Electronic Letters on Computer Vision and Image Analysis 20, no. 2 (June 1, 2021): 1–21. http://dx.doi.org/10.5565/rev/elcvia.1275.

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Facial expressions are integral part of non-verbal paralinguistic communication as they provide cues significant in perceiving one’s emotional state. Assessment of emotions through expressions is an active research domain in computer vision due to its potential applications in multi-faceted domains. In this work, an approach is presented where facial expressions are modelled and analyzed with dense optical flow derived divergence and curl templates that embody the ideal motion pattern of facial features pertaining to unfolding of an expression on the face. Two types of classification schemes based on multi-class support vector machine and k-nearest neighbour are employed for evaluation. Promising results obtained from comparative analysis of the proposed approach with state-of-the-art techniques on the Extended Cohn Kanade database and with human cognition and pre-trained Microsoft face application programming interface on the Karolinska Directed Emotional Faces database validate the efficiency of the approach.
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Poleak, Chanrith, and Jangwoo Kwon. "Parallel Image Captioning Using 2D Masked Convolution." Applied Sciences 9, no. 9 (May 7, 2019): 1871. http://dx.doi.org/10.3390/app9091871.

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Automatically generating a novel description of an image is a challenging and important problem that brings together advanced research in both computer vision and natural language processing. In recent years, image captioning has significantly improved its performance by using long short-term memory (LSTM) as a decoder for the language model. However, despite this improvement, LSTM itself has its own shortcomings as a model because the structure is complicated and its nature is inherently sequential. This paper proposes a model using a simple convolutional network for both encoder and decoder functions of image captioning, instead of the current state-of-the-art approach. Our experiment with this model on a Microsoft Common Objects in Context (MSCOCO) captioning dataset yielded results that are competitive with the state-of-the-art image captioning model across different evaluation metrics, while having a much simpler model and enabling parallel graphics processing unit (GPU) computation during training, resulting in a faster training time.
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Conference papers on the topic "Microsoft Visio;Evaluation"

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Maria Coruzzolo, Antonio, Francesco Lolli, Nazareno Amicosante, Hrishikesh Kumar, Pramod Thupaki, and Saurav Agarwal. "Comparing semiautomatic Rapid Upper Limb Assessments (RULA): Azure Kinect versus RGB-based machine vision algorithm." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002596.

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Correctly using a rapid upper limb assessment for working postures is crucial to avoid musculoskeletal disorders. Although motion capture technologies and in particular depth cameras are widely used, they cannot be used in large-scale industrial environments due to their high cost and their performance greatly impacted by the surrounding environment. We thus compared the effectiveness of a commercial machine vision algorithm (named ErgoEdge) based on an RGB camera against an application here developed based on the depth camera Microsoft Azure Kinect for the RULA evaluation (AzKRULA). We conducted an experiment where fifteen static postures were evaluated with Microsoft Azure Kinect and ErgoEdge, and the results were also compared with those of an expert in ergonomics. This experiment showed a substantial agreement between the solutions provided by the semi-automatic RULA evaluation and the ergonomic expert and between AzKRULA and ErgoEdge. At the same time, it showed that the RGB camera must be placed on the side of the worker due to the difficulties of the machine vision algorithm in reconstructing from a frontal view, important joint angles in 2D space (e.g., to evaluate the neck and trunk), which can invalidate the RULA evaluation provided by ErgoEdge. Moreover, the RULA evaluation with AzKRULA and ErgoEdge highlighted the need for an in-depth study into the thresholds of the secondary factors (i.e., all the factors for the RULA evaluation that are not computed from the thresholds of joint angles) as the highest differences between the two evaluations and the ergonomist one arises on them.
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Thabit, Abdullah, Wiro J. Niessen, Eppo B. Wolvius, and Theo van Walsum. "Evaluation of marker tracking using mono and stereo vision in Microsoft HoloLens for surgical navigation." In Image-Guided Procedures, Robotic Interventions, and Modeling, edited by Cristian A. Linte and Jeffrey H. Siewerdsen. SPIE, 2022. http://dx.doi.org/10.1117/12.2607262.

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