Reviewerly/exHarmony huggingface dataset:
Study on a New Type of Air-exchange Device for Refrigerated Container

Abstract In order to optimize the inconvenience of the switch operation of the existing air-exchange device and the loosening problem in the complex environment during transportation, a new type of air-exchange device for container is designed in this paper. The device adopts rotating opening, embedded sealing structure of sealing plug and combined with spring function, which effectively realizes the stability and reliability of the opening and closing of the air-exchange device. The structure is simple and the operation is also convenient. Therefore, the new air-exchange device has a wide application prospect in refrigerated containers.
Health Information Technologies for Cancer Care

The point-of-care processes of cancer diagnosis, treatment, and patient recovery require an integration of a variety of data and medical information to ensure optimal management. To better design and utilize these technologies, it is critical to understand the landscape of existing modalities and how they influence the care of cancer patients. Here, we review recent advances in the development and implementation of provider-oriented systems for oncologic care. We propose that these developments may be effectively characterized based on where they are situated in the timeline of cancer care; that is, technologies for cancer detection and diagnosis, intervention and surgery, and longitudinal patient therapy/management. The utility and impact of this class of informatics technologies is highlighted through a comprehensive case analysis of Figure1, a mobile application tailored to improve the continuing clinical education among providers. The advances and advantages showcased by Figure1 demonstrate the potential for provider-centered HIT to facilitate open clinical collaboration, collective growth of medical human capital, and ultimately more effective, personalized cancer care.
RETRACTED: Facial Recognition Using Aggregation and Random Forest Classification Method

Abstract Face detection and recognition performs an essential role in computer. There was tremendous increase in face recognition during the last years. There are numerous applications that require the face detection. As this face detection is the first step. There are many growing applications such as bank authentication, security access in system, enforcement of law, verification of credit cards, biometric authentication which works based on face detection. The goal of this paper is to presents a facial recognition system with deep learning methodologies. In this paper machine learning aggregation method is used to store the feature of detecting image and random forest algorithm also used to classify a detected image which is applied on face database and compared with previous algorithm which shows accurate ratio.
IEST: Interpolation-Enhanced Shearlet Transform for Light Field Reconstruction Using Adaptive Separable Convolution

The performance of a light field reconstruction algorithm is typically affected by the disparity range of the input Sparsely-Sampled Light Field (SSLF). This paper finds that (i) one of the state-of-the-art video frame interpolation methods, i.e. adaptive Separable Convolution (SepConv), is especially effective for the light field reconstruction on a SSLF with a small disparity range (<; 10 pixels); (ii) one of the state-of-the-art light field reconstruction methods, i.e. Shearlet Transformation (ST), is especially effective in reconstructing a light field from a SSLF with a moderate disparity range (10-20 pixels) or a large disparity range (> 20 pixels). Therefore, to make full use of both methods to solve the challenging light field reconstruction problem on SSLFs with moderate and large disparity ranges, a novel method, referred to as Interpolation-Enhanced Shearlet Transform (IEST), is proposed by incorporating these two approaches in a coarse-to-fine manner. Specifically, ST is employed to give a coarse estimation for the target light field, which is then refined by SepConv to improve the reconstruction quality of parallax views involving small disparity ranges. Experimental results show that IEST outperforms the other state-of-the-art light field reconstruction methods on nine challenging horizontalparallax evaluation SSLF datasets of different real-world scenes with moderate and large disparity ranges.
An improved baseline for person re-identification

Person re-identification(Re-ID) using deep learning has made great progress in the past few years, but there is one problem that many state-of-the-art Re-ID methods all use a complex network most of which use the structure of multi-branch and multi-loss function. At present, the database used for Person re-identification is relatively small. This complex network structure may bring a problem that although current methods may perform well in the small databases, but there may be some problems of overfitting problem, once applied in the bigger dataset or real scene these complex methods may perform not well. So this paper mainly proposes a new powerful baseline network. This end-to-end network only uses a global feature and does not use multi-branch structure, but achieves state-of-the-art level. The key point is that this network has good improvement potential to adapt to larger datasets and even practical application scenarios.
A Cloud-Based Dashboard for Time Series Analysis on Hot Topics from Social Media

Social Media has increasingly acquired enormous storehouses of shared interactive ideas among people in virtual communities over the past decade. While considering hot topics in social media as the culture of today’s world, related analysis derived from its trend allows researchers and society understand public point of view regarding emerging topics through online social interactions. The ease of categorizing the trends of topics makes it beneficial to find how people react to a certain topic. In our research, the distributions of keywords from hot topics are studied. First of all, a private cloud system is set up to collect and to filter raw data from social network (Twitter). Then, a web-based dashboard is developed to demonstrate static numbers and related charts. Some experiments are performed based on the newly-developed system deployed. Distribution functions of keywords are studied based on 2016 data, and further applications are applied based on 2017 spring data. Further cross comparisons are deployed based on daily, weekly, and monthly frequencies from different locations.
Understanding and Navigating the Scholarly Communication Landscape in the Twenty-First Century

SPECIALTY GRAND CHALLENGE article Front. Res. Metr. Anal., 13 November 2019Sec. Scholarly Communication Volume 4 - 2019 | https://doi.org/10.3389/frma.2019.00004
Sick and Tired: Narratives of Contested Illness in Chronic Fatigue Syndrome Blogs

Purpose While web logs often are taken to be “Internet diaries,” unlike diaries that are private and serve only the needs of their authors, public blogs serve as a technological tool, allowing for the formation of Internet communities and challenges to institutional and/or cultural narratives.
POL360: A Universal Mobile VR Motion Controller using Polarized Light

We introduce POL360: the first universal VR motion controller that leverages the principle of light polarization. POL360 enables a user who holds it and wears a VR headset to see their hand motion in a virtual world via its accurate 6-DOF position tracking. Compared to other techniques for VR positioning, POL360 has several advantages as follows. (1) Mobile compatibility: Neither additional computing resource like a PC/console nor any complicated pre-installation is required in the environment. Only necessary device is a VR headset with an IR LED module as a light source to which a thin-film linear polarizer is attached. (2) On-device computing: Our POL360’s computation for positioning is completed on the microprocessor in the device. Thus, it does not require additional computing resource of a VR headset. (3) Competitive accuracy and update rate: In spite of POL360’s superior mobile compatibility and affordability, POL360 attains competitive performance of accuracy and fast update rates. That is, it achieves the subcentimeter accuracy of positioning and the tracking rate higher than 60 Hz. In this paper, we derive the mathematical formulation of 6-DOF positioning using light polarization for the first time and implement a POL360 prototype that can directly operate with any commercial VR headset systems. In order to demonstrate POL360’s performance and usability, we carry out thorough quantitative evaluation and a user study and develop three game demos as use cases.
Forensic of an unrooted mobile device

With the people switching over to mobiles for all their computing needs, these ubiquitous devices have become huge data warehouses. In order to extract the required data, the inbuilt critical security mechanism of the device needs to be bypassed. With increased device security being implemented in latest android versions, gaining root access is a huge challenge. The research addresses the issue of getting data from smart phone without performing the rooting operation and without enabling USB debugging, which is one of the key challenges for mobile forensics. This paper proposes a mechanism to extract data by flashing team win recovery project (TWRP) on the device after unlocking the boot loader.
UAV-based Traffic Flow Estimation and Analysis

Due to the critical role of traffic flow information in urban activities, we propose a UAV-based system for traffic flow estimation and analysis. Deploying a quadrotor unmanned aerial vehicle (UAV) equipped with a downward-looking camera and range finder, we capture traffic videos for region of interest from a ’bird’s eye view’. To effectively process such videos where significant camera jitter may exist, we firstly design a low rank representation based method to simultaneously align the frames and detect the location of road. Then, we represent the well-aligned frames using spatiotemporal image, followed by a discriminative robust principal component analysis (RPCA) algorithm which fuses motion information with appearance for vehicle detection. Subsequently, leveraging on the camera height, the optical flow is exploited to classify vehicles into various size categories. Extensive experiments performed on the traffic data collected on university campus, achieving better performance than available methods.
Children’s Speaker Recognition Method Based on Multi-dimensional Features

In life, the voice signals collected by people are essentially mixed signals, which mainly include information related to speaker characteristics, such as gender, age and emotional state. The commonality and characteristics of traditional single-dimensional speaker information recognition are analyzed, and children’s individualized analysis is carried out for common acoustic feature parameters such as prosodic features, sound quality features and spectral-based features. Therefore, considering the temporal characteristics of voice, combined with the Time-Delay Neural Network (TDNN) model, Bidirectional Long Short-Term Memory model and the attention mechanism, the multi-channel model is trained to form a speaker recognition problem solution for children’s speaker recognition. A large number of experimental results show that on the basis of guaranteeing the accuracy of age and gender recognition, higher accuracy of children’s voiceprint recognition can be obtained.
Soft Video Uploading for Low-Power Crowdsourced Multi-view Video Streaming

The conventional digital video encoding and transmission are inefficient for crowdsourced multi-view video uploading due to its high power consumption, and undesirable quality degradation in unstable wireless channel. Soft video delivery scheme known as SoftCast skips digital video encoding and transmission to decrease power consumption in video encoding and transmission. In addition, it achieves graceful quality improvement with the improvement of wireless channel quality by directly sending linear-transformed video signals. However, there are two typical issues to apply conventional soft video delivery to crowdsourced multi-view video uploading. First, since soft video delivery has been designed for direct path between each contributor and the access point (AP), it may suffer low video quality when a contributor uploads its video to the AP over unstable direct wireless path. Second, conventional soft video delivery may suffer low video quality due to the redundant transmission of correlated videos because it does not exploit inter-camera correlations existed in multi-view videos. In this paper, we propose a cluster-based redirect video uploading scheme for high-quality and low-power crowdsourced multi-view video streaming. The proposed scheme integrates the four approaches of network clustering, delegate selection, soft video delivery, and four-dimensional discrete consine transform (4D-DCT) to redirectly upload the captured videos to the AP. Specifically, network clustering and delegate selection leverage the redirect path between the contributors and the AP. Soft video delivery removes power-hungry digital encoding and transmission by directly sending frequency-domain coefficients using multi-dimensional DCT and near-analog modulation. 4D-DCT exploits the content correlations between the contributors to reduce redundant transmissions. Evaluation results show that our proposed scheme outperforms the conventional soft video delivery scheme when the channel quality difference between the direct and redirect paths increases. In addition, our scheme outperforms the digital-based video uploading schemes in terms of both video quality and power consumption. For example, the proposed scheme yields graceful quality improvement with the improvement of wireless channel quality, however, the digital-based schemes suffer from sudden quality degradation due to synchronization errors in decoding.
Imagining the Cool-ag: Or, Freedom Considered Harmful

This short paper makes an argument about our lack of comfort, as researchers, in developing a science, and a technology, for enacting control over behavior. We present a design fiction about a smart prison, in which behavior change is facilitated via always-on IoT-facilitated monitoring. This fiction may be read simultaneously as a constructive application of behavioural science to an appropriate context, and as a dystopian attack on personal freedom. We argue that the implementation of ubicomp systems that are intended to facilitate behavior change (i.e., almost all ubicomp systems), will inevitably lead to questions over personal freedom. We draw parallels to the reaction of society to the field of behavioural psychology, which has an expressed goal of gaining prediction and control over behavior. Ultimately, if we are to realise the potential of ubicomp to change society positively, we need to become comfortable with enacting control, or in other words, taking responsibility.
Design and Implementation of SCC System based on Cloud Architecture

This paper addresses a service-oriented, customized on-demand, integrated cloud architecture for the satellite control center system. The cloud architecture is a three-layer hierarchy including service/business layer, platform layer and hardware layer. Based on the cloud architecture, the SCC system is designed to integrate computing, storage, and networking resources to form a powerful converged infrastructure platform. The SCC software are implemented as eleven functional services: data display software, data processing software, data storage and management software, database software, orbit calculation and analysis software, control calculation and analysis software, duplex management software, command operation software, monitor and control software, interface computer software and time service software. Details of the overall system architecture and the integration of the above software services are included in the paper. The paper concludes that design and implementation of efficient, reliable, scalable and flexible ground control system is an attractive but challenging area, and there is still work to be done.
Key Management for protection of health care Data of Multi-user using Access control in Cloud Environment

Storing an organization's database at an external service provider has become extremely common. This popular practice is called as Database Outsourcing, in which, data encryption, crypto key, and access control are very important security issues, especially if the data owner wishes to publish his data for external use. In this paper, implementation & present performance of statistical analysis of approaches for encrypting/decrypting data using FPE, FF1 with less computation and resource time, implementation of access control through selective encryption and providing secure access and sharing services for multi user's data using key distribution in the client side and access control lists is discussed. The primary goal of this paper is no requirement of re-distribution of keys or re-encryption of data for any administrative actions (updating access rights or adding/deleting users).
A Lightweight Selective Video Encryption Using Motion Vectors and IPMs for H.264 Codec

Selective video encryption is a technique of selectively choosing a part of the video bit stream for encryption. Such kind of encryption can impart good security and computational efficiency in the H.264 bit stream. In this paper, we propose a selective video encryption technique which uses the motion vectors and chrominance layer of each macro block in I frames for encryption. These two are important elements in the bit stream whose encryption shall reflect on the present GoP (Group of Pictures). The proposed technique is implemented in the JM 19.0 reference software under high profile condition. Different YUV sequences are used for the investigational evaluation of the proposed technique. Results are discussed according to the PSNR, bit rate, etc.
A Case Study of Captive-Portal Detection for Web Authentication on Wired LAN in a Campus Network

In order to quickly and properly handle a computer security incident or a network failure, it is necessary to identify a suspicious host and its user, and a network authentication is then necessary. Regarding wired LAN, web authentication can be feasible because a user does not need to configure his or her host in advance. There are, however, severe issues of web authentication that incurs very long delay. This paper reveals that the cause of this long delay is mainly by Windows update before an authentication. This paper then proposes the feasible web authentication using captive-portal detection that achieve simultaneous authentications of more than 40 clients.
Face Localization and Enhancement

Facial landmark localization plays a critical role in facial recognition and analysis. In this chapter, we first propose a novel cascaded backbone-branches fully convolutional neural network (BB-FCN) for rapidly and accurately localizing facial landmarks in unconstrained and cluttered settings. The proposed BB-FCN generates facial landmark response maps directly from raw images without any preprocessing. It follows a coarse-to-fine cascaded pipeline, which consists of a backbone network for roughly detecting the locations of all facial landmarks and one branch network for each type of detected landmark to further refine their locations (©[2019] IEEE. Reprinted, with permission, from [1].). At the end of this chapter, we also introduce the progress in face hallucination, a fundamental problem in the face analysis field that refers to generating a high-resolution facial image from a low-resolution input image (©[2019] IEEE. Reprinted, with permission, from [2].).
Introducing Word's Importance Level-Based Text Summarization Using Tree Structure

Text-summarization plays a significant role towards quick knowledge acquisition from any text-based knowledge resource. To enhance the text-summarization process, a new approach towards automatic text-summarization is presented in this article that facilitates level (word importance factor)-based automated text-summarization. An equivalent tree is produced from the directed-graph during the input text processing with WordNet. Detailed investigations further ensure that the execution time for proposed automatic text-summarization, is strictly following a linear relationship with reference to the varying volume of inputs. Further investigation towards the performance of proposed automatic text-summarization approach ensures its superiority over several other existing text-summarization approaches.
Toward Long Distance Tabletop Hand-Document Telepresence

In a telepresence scenario with remote users discussing a document, it can be difficult to follow which parts are being discussed. One way to address this is by showing the user's hand position on the document, which also enables expressive gestural communication. An important practical problem is how to capture and transmit the hand movements efficiently with high resolution document images. We propose a tabletop system with two channels that integrates document capture with a 4K video camera and hand tracking with a webcam, in which the document image and hand skeleton data are transmitted at different rates and handled by a lightweight Web browser client at remote sites. To enhance the rendering, we employ velocity based smoothing and ephemeral motion traces. We tested our prototype over long distances from USA to Japan and to Italy, and report on latency and jitter performance. Our system achieves relatively low latency over a long distance in comparison with a tele-immersive system that transmits mesh data over much shorter distances.
Implementation of PHPMailer with SMTP protocol in the development of web-based e-learning prototype

Abstract The usage of information technology has developed rapidly. At present, the information system has been widely used in various fields, including the education sector, through various web-based learning systems. Information system becomes an important factor in the process of decision making system, data management, document management, and performance efficiency. In the education sector, the development of information systems can be applied to the teaching and learning process. One of them is an e-learning as a new innovation in the learning process. The development of e-learning become a solution of learning to become more interactive and productive. This prototype use PHPMailer Library on the SMTP protocol which is an alternative tools in the e-learning development. The PHPMailer Library become an intermediary of e-learning in sending emails automatically. PHPMailer can provide information to users about the activities carried out. Teachers, students and parents can monitor the teaching and learning process and the learning outcomes through notifications that send from email. This study use a waterfall software research and development model, and Object Oriented Programming (OOP) programming concepts. The Tests show that this prototype is successfully with 100% accuracy with a good level of responsiveness. The system testing results indicate that e-learning can provide an email notification to teachers, students and parents during the learning process. The development of e-learning can also be accessed from various media or devices.