Reviewerly/exHarmony huggingface dataset:
Research on Target Tracking Algorithm Based on Kernel Correlation

With the development of sensor and image processing technology, computer vision plays an increasingly significant role in the chemical engineering because of its characteristics such as low cost, high resolution, and non-contact measurement. In this paper, the motion probability map can be obtained by sparse optical flow based on Harris corner point. Then the coarse contour of silicon dioxide particles which is the input of kernelized correlation filtering (KCF) algorithm can be generalized. KCF algorithm can easily complete tracking task under the influence of disturbance including light change, video shaking and so forth. A contour refining and tracking method are proposed. The geometric active contour (GAC) algorithm can use function as implicit expression of contour and can design the different energy functional to control contour evolution. By minimizing of energy functional, the refining contour is evolved. Then the target tracking is realized according to the refined contour.
Improving N-gram Language Models with Pre-trained Deep Transformer

Although n-gram language models (LMs) have been outperformed by the state-of-the-art neural LMs, they are still widely used in speech recognition due to its high efficiency in inference. In this paper, we demonstrate that n-gram LM can be improved by neural LMs through a text generation based data augmentation method. In contrast to previous approaches, we employ a large-scale general domain pre-training followed by in-domain fine-tuning strategy to construct deep Transformer based neural LMs. Large amount of in-domain text data is generated with the well trained deep Transformer to construct new n-gram LMs, which are then interpolated with baseline n-gram systems. Empirical studies on different speech recognition tasks show that the proposed approach can effectively improve recognition accuracy. In particular, our proposed approach brings significant relative word error rate reduction up to 6.0% for domains with limited in-domain data.
Differentiating Features for Scene Segmentation Based on Dedicated  Attention Mechanisms

Semantic segmentation is a challenge in scene parsing. It requires both context information and rich spatial information. In this paper, we differentiate features for scene segmentation based on dedicated attention mechanisms (DF-DAM), and two attention modules are proposed to optimize the high-level and low-level features in the encoder, respectively. Specifically, we use the high-level and low-level features of ResNet as the source of context information and spatial information, respectively, and optimize them with attention fusion module and 2D position attention module, respectively. For attention fusion module, we adopt dual channel weight to selectively adjust the channel map for the highest two stage features of ResNet, and fuse them to get context information. For 2D position attention module, we use the context information obtained by attention fusion module to assist the selection of the lowest-stage features of ResNet as supplementary spatial information. Finally, the two sets of information obtained by the two modules are simply fused to obtain the prediction. We evaluate our approach on Cityscapes and PASCAL VOC 2012 datasets. In particular, there aren't complicated and redundant processing modules in our architecture, which greatly reduces the complexity, and we achieving 82.3% Mean IoU on PASCAL VOC 2012 test dataset without pre-training on MS-COCO dataset.
Unsupervised Deep Metric Learning via Auxiliary Rotation Loss

Deep metric learning is an important area due to its applicability to many domains such as image retrieval and person re-identification. The main drawback of such models is the necessity for labeled data. In this work, we propose to generate pseudo-labels for deep metric learning directly from clustering assignment and we introduce unsupervised deep metric learning (UDML) regularized by a self-supervision (SS) task. In particular, we propose to regularize the training process by predicting image rotations. Our method (UDML-SS) jointly learns discriminative embeddings, unsupervised clustering assignments of the embeddings, as well as a self-supervised pretext task. UDML-SS iteratively cluster embeddings using traditional clustering algorithm (e.g., k-means), and sampling training pairs based on the cluster assignment for metric learning, while optimizing self-supervised pretext task in a multi-task fashion. The role of self-supervision is to stabilize the training process and encourages the model to learn meaningful feature representations that are not distorted due to unreliable clustering assignments. The proposed method performs well on standard benchmarks for metric learning, where it outperforms current state-of-the-art approaches by a large margin and it also shows competitive performance with various metric learning loss functions.
Holographic Sign Language Interpreters

We describe the implementation of a prototype system of 3D holographic sign language interpreters. The signing avatars, observed through wearable Mixed Reality (MR) smartglasses (e.g., Microsoft HoloLens), translate speech to Signed Exact English (SEE) in real-time. Such a system can be used by deaf and hard of hearing students in the classroom or other contexts to remove current accessibility barriers.
Best Shot Selection using Convolutional Neural Networks

Mobile phone cameras have small camera sensor size as compared to professional cameras, capture less light at a time and capture everything in focus. Also, it is very common for novice photographers to miss the best shot. These days’ companies use multiple camera systems to solve these problems, which in turn increase the complexity and the costs of deploying these systems. This paper presents an android based mobile phone camera application that takes help from the work done in segmentation networks to capture portrait images and it also tries to capture the best possible photograph using traditional image processing and convolutional neural networks. Our system is performing better in terms of Mean IOU than existing available systems. Results showed that our model is simple and cost effective. This model is easily embeddable in upcoming mobile phones as a best-shot selection feature.
Journal Management Services at Padjadjaran University Knowledge Management Center

The Open Journal System (OJS) in universities is used to increase university publications by providing open access to journals to keep knowledge alive. This study aims to determine the Open Journal System (OJS) service at the Knowledge Management Center of Padjadjaran University through collection analysis, retrieval system, and service model. This study uses descriptive qualitative research methods. The results showed that the Open Journal System collection of the Knowledge Management Center Universitas Padjadjaran amounted to 105 journals from 14 faculties. Each journal represents the scientific study program in each faculty. Users in the retrieval system can determine information from the articles they are looking for, use features, and determine the right query, information search results, and additional records of information search results. The Knowledge Management Center of Padjadjaran University provides information and consultation on journal indexation, and records journals, and provides guidance for journals that will apply for accreditation/reaccreditation. The OJS service model at the Unpad Knowledge Management Center has been carried out well using regular communication and sharing information with journal managers regarding journal management. The Unpad Knowledge Management Center has provided a good service model in the form of guidance, direction, or consultation regarding journal management to university journals.
THE DESCRIPTION OF ENGLISH TEACHING STRATEGY USED IN TEACHING READING IN ISLAMIC SENIOR HIGH SCCHOOL

This research is talked about descriptive qualitative, this research was done to know the teaching strategy in teaching English. This research was want to answer the question How is the teaching strategy in teaching reading in MA Maarif , and the objective was to describe the teaching strategy in teaching reading. To describe the answer the researcher used three instruments for taking the data, they are observation and questionnaire. Finding, the teacher applied those strategies. From the first to the third meeting, the teacher applied the different strategies. At the first and second, the teacher applied the discovery learning strategy where the learning materials were searched and found by the students themselves through various activities, and the third meeting the teacher used question answer strategy and discussion strategy.
IMPROVING THE STUDENTS’ READING COMPREHENSION THROUGH THE SSS (START WITH SIMPLE STORIES) METHOD IN EXTENSIVE READING ACTIVITTY

This paper presents the idea of applying the SSS Method extensive reading to enhance comprehension of the lower achieving students in the school. The subjects of the research were the first-year students of senior high school in Probolinggo. Two classes of them were assigned as the control and the experimental groups. The control group was taught reading comprehension using the conventional way, while the experimental group was taught reading utilizing the SSS Method extensive reading. After the treatment both groups were given post test. The result of the study showed that there was a1significant1difference1in1the students’ reading comprehension achievement. The students in the experimental group significantly obtained higher scores than the ones in the control group. the conclusion of the research findings is that the low achieving students of the first year at SMAI NURUS SALAFIYAH Probolinggo Senior High School taught using the SSS METHOD extensive reading perform better in reading comprehension than those taught reading using the conventional way. In general, exposing students to the SSS METHOD extensive reading activity could effectively raise their reading comprehension achievement.
A Study on the Development of the Chinese Industrial Robot Industry

Although the production and usage of robots in China reached the world’s highest level in 2016, China shows significant gaps from robot industrial powers not only in terms of performance such as accuracy and repeatability but also in terms of industrial robot density, which is a quantitative aspect, with 64 robots per 10,000 workers. In particular, joint ventures of foreign companies such as FANUC, Yaskawa, and ABB dominate the industrial robot market. Even in the situation as such, in terms of industrial policies, diverse efforts have been devoted mainly by the Chinese local governments such as providing subsidies to manufacturing companies in the field of core technologies including Nantong Zhenkang Welding Electromachinery (南通振康), Tsino-Dynatron (清能德创), and Inovance (深圳汇川技术), and constructing a comprehensive industrial value chain. In terms of market and demand, Nantong Zhenkang Welding Electromachinery participates in the establishment of national standards, Siasun is making cooperative robots with 7 degrees of freedom with competitiveness in welding robots and AGV robots, and Leaderdrive(绿的谐波) is showing competitiveness close to the parameters of Japanese companies in the field of harmonic drives, Tsino-Dynatron has targeted the niche markets of Japanese and American companies, and Inovance is increasing its market share through its management team’s technical capabilities and teamwork.
Design of English Teaching Interactive System Based on Artificial Intelligence

By exploring the characteristic of interaction of network teaching, we proposed to develop an English teaching interaction system based on artificial intelligence, which can solve the problems in current English teaching class. We analyzed the functional requirements of the system corresponding to different user. By buiding Ubuntu operating system as the computing platform and exploring the object-oriented dynamic teaching environment provided by artificial intelligence platform, we build the LAMP development environment with MySQL database and PHP script language. We constructed a three-tier separated architecture system by using B/S mode, and refined the design and implementation of each module function through the secondary development of platform module plug-ins. To exhibit the advantages of the artificial intelligence system, we take college English teaching as an example to illustrate its functions. The functions of curriculum creation, teaching resources and activity design can be realized in the system, which verifies the effectiveness of the artificial intelligence system in interactive teaching and learning.
YOLO-TN: ultrasound diagnosis of thyroid nodules based on transfer learning and convolutional neural networks

Thyroid nodules are a common clinical condition. Currently, radiologists commonly use ultrasound as a method of diagnosing them. However, the varying experience of radiologists leads them to describe the features of nodules in the same ultrasound image differently. Incorrect descriptions will lead to misdiagnosis for the patient. To address the problem of difficult diagnosis of benign and malignant thyroid nodules in ultrasound images, we proposed a model for the diagnosis of thyroid nodules, which is named YOLO-TN (thyroid nodules). In this work, we used transfer learning and data augmentation to alleviate the data dependency of the model and designed CSPSE-DarkNet to simulate clinical diagnosis. In addition, we enhanced the detection of small objects and proposed soft ROI selection to enrich the contextual information of thyroid nodules. The model achieved a mAP value of 91.3% on our dataset, providing better performance than some of the popular networks currently available.
Presentation on Evaluating the Effectiveness of Insider Threat Mitigation Systems.

Prompt investigation of anomalies that may indicate a loss of SNM; (3) Timely and localized detection of loss, diversion, or theft of a goal quantity; (4) Rapid assessment and response to detection alarms; and (5) Timely generation of information to aid in the recovery of SNM in the event of an actual loss, diversion, or theft from the purview of the MC&A system. Control and accountability of material, equipment, and data are essential to minimizing insider threats.
Identifying the factors explaining the quality of scientific functions in the university Based on Glassick six-component approach

Identification of the Determinants of the Academic Functions Quality Based on the Glassick's Six Criteria for Scholarship
Real Time Pedestrian Detection and Tracking for Driver Assistance Systems

In Autonomous driving technology detecting pedestrians and vehicles should be fast and efficient in order to avoid accidents. Pedestrian detection and tracking is challenging for complex real world scenes. In proposed system Kalman filter has been used to detect and track the pedestrians. From three frames initially eigen object is computed in video sequences for detection of moving objects, then shape information is used to classify humans and other objects. Moreover with the help of continues multiple frames occlusion between objects get calculated. In the proposed system an application is developed which gives automatic warning in case of doubtful activities performed by pedestrian of zone monitoring which can be used in various domains like defence and traffic monitoring. Proposed algorithm gives accurate moving object detection and advanced sensors are used to detect human movements ahead and alert the driver by using buzzer, result does not affect by body pose of individual.
Encapsulation of Actions and Plans in Conditional Planning Systems

We introduce a notion of macroaction for a given subplan. A macroaction is an action representing the given plan and it can be considered as an abstraction, neglecting the internal structure of the original plan. The description of the macroaction is sufficiently powerful to represent all the information needed for synchronization and clobbering detection of the given subplan. It is possible to prove that when substituting in a correct plan a macroaction with its real composition, the overall plan remains correct. It is pointed out that it is possible to build large libraries of plans by means of techniques of plan compilation and manage them with fast-selection and plan re-use methods. A comparison of different kind of macroactions is done in the frameworks of linear, non-linear and conditional planning. It is shown that a conditional macroaction is required even in the case of nonlinear unconditional plans. A conditional planning model based on conditional formula calculus is used. Conditional formulae represent uncertain situations and denote sets of mutually exclusive states. The method of compilation is defined through a weakest precondition semantics for conditional plans.
Addressing consumerization of IT risks with nudging

In this work we address the main issues of Information Technology (IT) consumerization that are related to security risks, and vulnerabilities of devices used within Bring Your Own Device (BYOD) strategy in particular. We propose a ‘soft’ mitigation strategy for user actions based on nudging, widely applied to health and social behavior influence. In particular, we propose a complementary, less strict, more flexible Information Security policies, based on risk assessment of device vulnerabilities and threats to corporate data and devices, combined with a strategy of influencing security behavior by nudging. We argue that nudging, by taking into account the context of the decision-making environment, and the fact that the employee may be in better position to make a more appropriate decision, may be more suitable than strict policies in situations of uncertainty of security-related decisions. Several examples of nudging are considered for different tested and potential scenarios in security context.
OBJECTIVE ASSESSMENT OF CONCERT HALL ACOUSTICS

With the introduction of objective measures relating to subjective characteristics for listening to classical music in ISO 3382, most new auditoria are now tested in some sort of model, either computer simulation model or scale model. An alternative is to test by auralisation, an approach more valued by some than others! For work using objective measures, criteria are needed to assess the numerical values, the most common of which is to compare measured or predicted values with an optimum range. If a value of an objective measure falls outside the optimum range it can often not be obvious why this has occurred, what aspect of the geometrical design is responsible?
A Nafp Project: Use Of Object Oriented Methodologies And Design Patterns To Refactor Software Design

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract An NAFP Project: Use of Object Oriented Methodologies and Design Patterns to Refactor Software Design Gholam Ali Shaykhian, NAFP Fellow Engineering Directorate National Aeronautics and Space Administration Kennedy Space Center Ali.Shaykhian@nasa.gov Rhoda Baggs, Ph.D. Assistant Professor of Computer Sciences University College Florida Institute of Technology rbaggs@fit.edu Introduction In the early problem-solution era of software programming, functional decompositions were mainly used to design and implement software solutions. In functional decompositions, functions and data are introduced as two separate entities during the design phase, and are followed as such in the implementation phase. Functional decompositions make use of refactoring through optimizing the algorithms, grouping similar functionalities into common reusable functions, and using abstract representations of data where possible; all these are done during the implementation phase. This paper advocates the usage of object-oriented methodologies and design patterns as the centerpieces of refactoring software solutions. Refactoring software is a method of changing software design while explicitly preserving its external functionalities. The combined usage of object-oriented methodologies and design patterns to refactor should also benefit the overall software life cycle cost with improved software.
Wheelchair mechanism for negotiating obstacles

Moving with the wheelchair can be a serious problem, especially when the obstacle occurs on its way. An alternative solution would be to equip the wheelchair with appropriate mechanical device, thanks to that it becomes possible to overcome barriers such as kerbs or doorsteps. In this paper, the authors present an idea of mechanism overcoming barriers by the wheelchair. Type and geometrical synthesis have been presented. The mechanism is modelled in a multibody computer analysis system and sample simulation research results are reported.
PENINGKATAN PRESTASI BELAJAR PRAKARYA MELALUI MODEL PEMBELAJARAN AKTIF COURSE REVIEW HORAY (CRH)

The purpose of this classroom action research is to improve students' learning achievement of Craft Subjects through active learning model of CRH in grade VIII C students of semester I of SMP Negeri 2 Sukoharjo in the 2018/ 2019 school year.This research was conducted from July to December 2018 in SMP Negeri 2 Sukoharjo.The subjects of this study were students of class VIII C as many as 32 students.This research is a Classroom Action Research conducted in two cycles.Data collection techniques used documentation, observation, and written tests.Data collection tools are observation sheets, test items, and value list documents.Data analysis using comparative descriptive analysis followed by reflection on each cycle consists of four steps, namely: (1) Planning, (2) Action Implementation, (3) observation, and (4) reflection.The results of this study
Theoretical Basis for the Formation of a Program of Additional Education for Doctors

The new concept of a systemically responsible increase in the level of an individual’s scientific and philosophical culture is based on the dynamic three-phase nature of the main elements of the triad of the scientific and cognitive component (popularization of science, conceptualization of science, philosophization of science), which ultimately determines the context of the scientific and philosophical culture, and which is a generalized theoretical principle explaining the essence of the regular reflexive-recursive processuality and dialogicity of formation and cyclic development scientific world outlook culture.
Design Crawler: A Web Application for Digital Design Metadata Analysis

SoC designs are becoming more complicated over the years. SoC design, verification, and code maintainability are challenging tasks for engineers as it directly affects the product life cycle. Metadata plays an important role for source code maintenance as it helps in evaluating and differentiating the used constructs in various SoC designs with respect to each other. Metadata is a point of interest for different stakeholders such as software developers and testers as they always crave SoC design profiling. The proposed approach represents a complete platform for design visualization to improve debugging process. The prototype enables different features: design query using language features, design hierarchy, and a dashboard profiling the extracted design metadata. The system is inter-operable with any simulator and is independent on simulation time.