The 360-degree feedback,also known as“multifaceted feedback”,is a management tool,according to which an employee receives feedback(comments)from peers,subordinates,supervisors and in some cases may include external ...The 360-degree feedback,also known as“multifaceted feedback”,is a management tool,according to which an employee receives feedback(comments)from peers,subordinates,supervisors and in some cases may include external feedback such as customers,suppliers or other interested parties.It is a process of systematic data collection from many sources regarding the skills,abilities and behavior of employees.In most cases the subject of the feedback is a senior executive.In contrast to the traditional approach,this method collects information from a set of individuals who form a“circle”around the feeder,hence the name of the tool.展开更多
The development of multimedia content has resulted in a massiveincrease in network traffic for video streaming. It demands such types ofsolutions that can be addressed to obtain the user’s Quality-of-Experience(QoE)....The development of multimedia content has resulted in a massiveincrease in network traffic for video streaming. It demands such types ofsolutions that can be addressed to obtain the user’s Quality-of-Experience(QoE). 360-degree videos have already taken up the user’s behavior by storm.However, the users only focus on the part of 360-degree videos, known as aviewport. Despite the immense hype, 360-degree videos convey a loathsomeside effect about viewport prediction, making viewers feel uncomfortablebecause user viewport needs to be pre-fetched in advance. Ideally, we canminimize the bandwidth consumption if we know what the user motionin advance. Looking into the problem definition, we propose an EncoderDecoder based Long-Short Term Memory (LSTM) model to more accuratelycapture the non-linear relationship between past and future viewport positions. This model takes the transforming data instead of taking the direct inputto predict the future user movement. Then, this prediction model is combinedwith a rate adaptation approach that assigns the bitrates to various tiles for360-degree video frames under a given network capacity. Hence, our proposedwork aims to facilitate improved system performance when QoE parametersare jointly optimized. Some experiments were carried out and compared withexisting work to prove the performance of the proposed model. Last but notleast, the experiments implementation of our proposed work provides highuser’s QoE than its competitors.展开更多
In this paper,a single-shot 360-degree cranial deformity detection system using digital image correlation(DIC)is presented to quickly obtain and detect accurate 3D data of infants’cra-nium.By introducing plane mirror...In this paper,a single-shot 360-degree cranial deformity detection system using digital image correlation(DIC)is presented to quickly obtain and detect accurate 3D data of infants’cra-nium.By introducing plane mirrors into a stereo 3D DIC measurement system,a multi-view 3D imaging model is established to convert 3D data from real and virtual perspectives into 360-degree 3D data of the tested infant cranium,achieving single-shot and panoramic 3D measurement.Exper-imental results showed that the performance and measurement accuracy of the proposed system can meet the requirements for cranial deformity detection,which provides a fast,accurate,and low-cost solution medically.展开更多
文摘The 360-degree feedback,also known as“multifaceted feedback”,is a management tool,according to which an employee receives feedback(comments)from peers,subordinates,supervisors and in some cases may include external feedback such as customers,suppliers or other interested parties.It is a process of systematic data collection from many sources regarding the skills,abilities and behavior of employees.In most cases the subject of the feedback is a senior executive.In contrast to the traditional approach,this method collects information from a set of individuals who form a“circle”around the feeder,hence the name of the tool.
文摘The development of multimedia content has resulted in a massiveincrease in network traffic for video streaming. It demands such types ofsolutions that can be addressed to obtain the user’s Quality-of-Experience(QoE). 360-degree videos have already taken up the user’s behavior by storm.However, the users only focus on the part of 360-degree videos, known as aviewport. Despite the immense hype, 360-degree videos convey a loathsomeside effect about viewport prediction, making viewers feel uncomfortablebecause user viewport needs to be pre-fetched in advance. Ideally, we canminimize the bandwidth consumption if we know what the user motionin advance. Looking into the problem definition, we propose an EncoderDecoder based Long-Short Term Memory (LSTM) model to more accuratelycapture the non-linear relationship between past and future viewport positions. This model takes the transforming data instead of taking the direct inputto predict the future user movement. Then, this prediction model is combinedwith a rate adaptation approach that assigns the bitrates to various tiles for360-degree video frames under a given network capacity. Hence, our proposedwork aims to facilitate improved system performance when QoE parametersare jointly optimized. Some experiments were carried out and compared withexisting work to prove the performance of the proposed model. Last but notleast, the experiments implementation of our proposed work provides highuser’s QoE than its competitors.
基金supported by the National Natural Science Found-ation of China(No.62075096)Leading Technology of Ji-angsu Basic Research Plan(No.BK20192003)+4 种基金National De-fense Science and Technology Foundation of China(No.2019-JCJQ-JJ-381)“333 Engineering”Research Project of Jiangsu Province(No.BRA2016407)Jiangsu Provincial“One Belt and One Road”Innovation Cooperation Project(No.BZ2020007)Fundamental Research Funds for the Central Universities(Nos.30921011208,30919011222 and 30920032101)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(No.JS-GP202105).
文摘In this paper,a single-shot 360-degree cranial deformity detection system using digital image correlation(DIC)is presented to quickly obtain and detect accurate 3D data of infants’cra-nium.By introducing plane mirrors into a stereo 3D DIC measurement system,a multi-view 3D imaging model is established to convert 3D data from real and virtual perspectives into 360-degree 3D data of the tested infant cranium,achieving single-shot and panoramic 3D measurement.Exper-imental results showed that the performance and measurement accuracy of the proposed system can meet the requirements for cranial deformity detection,which provides a fast,accurate,and low-cost solution medically.
