Reviewerly/exHarmony huggingface dataset:
Statistical Approach for Sky Clouds Density Classification

In the renewal energy mined from solar panels is essential to know the future amount of produced energy. The sun is a relatively stable source of energy, and we can precisely estimate extra-terrestrial sun intensity based on the hour of the day, day of the year, and respectful distance from the sun. The incident solar radiation hitting the Earth is affected by the Earth's atmosphere, climate, and the density of clouds. We need to predict sky clearness, respectively the density of clouds in the sky. This paper deals with sky clouds density estimation using a statistical approach. The data are acquired by a terrestrial fisheye camera facing the sky. In the first step, the various sky types were manually annotated to segment sky into artifacts - sun, clear sky, partial clouds, clouds, and terrestrial background. We used the set of Gaussian Mixture Models for the classification of such artifacts. We optimized the number of components in mixtures appropriate to different class requirements. The result of modelling should be the prediction of clouds density depending on the image captured by the fish-eye camera.
Particle Filter Optimization for Adaptive Radar Data Processing

Adaptive data processing in modern radar systems is standard approach. The classic kalman filter, extended kalman filter and many other applications are usually used for state estimate and radar target tracking. Signal and data processing technology improvement allows the more effective target tracking in real time. In this paper, we approach the structure and key features of the optimal particle filtering (PF). The optimization criteria for PF are proposed and analyzed. The dependence of mean square error on the number of particles during track prediction by particle filter is discussed. Using this dependence, we were able to determine the minimum required number of particles to correctly predict the trajectory of the target depending on its dynamics (trajectory complexity). The results of off-line real radar data processing are analyzed.
Exploration on the Maintenance and Management of College English Autonomous Learning Center Based on Cloud Computing

In this paper, the author first analyzes the concept of college English autonomous learning center, then expounds the problems existing in the traditional computer room, and finally makes an in-depth analysis of the characteristics and advantages of applying cloud settlement in college English autonomous learning center, including a detailed discussion and planning on the simplified installation of software, the setting of network blacklist, multi-system management functions and the application of cloud terminals. Starting from the development status of college English autonomous learning centers and cloud computing in China, cloud computing is continuously upgraded and optimized to promote its application and development in the maintenance and management of college English autonomous learning centers.
Learning Maximum Absolute Meaning Through Reasoning About Speaker Intentions

Abstract Three experiments investigated adult learners’ acquisition of a novel adjective. In English and other languages, meanings of some gradable adjectives are said to include an absolute standard of comparison (e.g., full means completely filled with content). However, actual usage is often imprecise, where a maximum absolute standard of comparison, strictly speaking, does not apply (e.g., a 90% full cup can be full depending on how it will be used). This creates problems for learners who acquire the absolute meaning from variable mappings between word forms and observations. We demonstrated that adult learners infer a maximum standard of comparison when they receive information about agents’ intended goals that lie behind imprecise word usage. Results suggested these inferences are conditioned on the amount of visually ambiguous observations made during learning. We conclude that access to agents’ intended goals allows learners to explain contextual sources of imprecision and helps the learning of a maximum absolute meaning from primarily nonabsolute observations.
Research on the Communication Media of Chinese International Education Based on Internet Multimedia from the Perspective of Communication Studies

Abstract Chinese international education is not only a simple teaching behavior, but also an international communication behavior. With the continuous development of society, communication and Chinese international education are more and more closely linked. Modern society is the era of network new media. Various network new media means emerge endlessly and change endlessly. Only by fully understanding the operation principle and communication law of each medium, can we achieve the best results in the international Chinese language education through the media. From the perspective of communication, this paper summarizes the types of current media. Combining with the current situation of Confucius Institute and using computer-aided technology, this paper illustrates the vigorous development of international Chinese education. Finally, the paper puts forward some measures.
Speech Recognition Approach for Motion-Enhanced Display in ARM-COMS System

This research proposes an idea of motion-enhanced display that utilizes the display itself as the communication media which mimics the motion of human head to enhance presence in remote communication. The idea has been implemented as an augmented tele-presence system called ARM-COMS (ARm-supported eMbodied COm-munication Monitor System). Basically, ARM-COMS detects the orientation of a subject face by the face-detection tool based on an image processing technique, and mimics the head motion of a remote partner in an effective manner. In addition to that, ARM-COMS makes appropriate reactions when a communication partner speaks even without any significant motion in video communication by using audio signal during talk.This paper covers two topics. The first one is a new design of the ARM-COMS robotic arm, with the configuration of six-axis servo motors to enable further smooth motion. In addition to the hardware configuration, the software configuration is also presented based on the ROS framework.The second topic is a camera stabilizer-based experimental configuration. This study worked on a feasibility study of experimental configuration of ARM-COMS. If it works feasible, the approach could be applied to the redesigned ARM-COMS robotic arm system.
Design of Oral English Learning System Based on Cloud Computing

With the maturity and popularization of cloud computing and mobile network technology, mobile learning develops rapidly in many fields, and the demand for mobile learning system is expanding, especially in oral English learning. A cloud computing based oral English learning system is designed. Users can learn oral English knowledge through a mobile terminal, simulate oral English tests and establish a special dictionary. Managers can manage learning resources, user information, and word base through the cloud server. The system can realize mobile learning based on cloud computing, cloud sharing of learning resources and other functions, improve the user’s learning experience, and effectively promote the user’s aural learning.
Identifying Students’ Inner Structure of Poetry with Environment Themes

Abstract This research purpose to identify inner structure of poetry by PGSD students in terms of theme, tone, feeling and mandate. This type of research is qualitative research, the method used in this research is descriptive qualitative. The data used in this study was written data in the form of poems text document by 2019 PGSD students with environment themes. The results showed that in general these poems have the same theme that is telling the state of the environment. For the tone of the poem pinned in the poem indicates about the condition of the surrounding environment that is exposed to water, soil and air pollution which is a result of the results of fires, floods, landslides and others. This can also be observed from the poems that have been identified that generally have almost the same taste about disappointment and sadness. Other reviews made about the taste in the poem are gratitude, joy, disappointment, sadness, and anger. The last part of the analysis of the inner structure of poem is the mandate. The general mandate of the poem that has been analyzed is the mandate that human beings are obliged to maintain and preserve the surrounding environment for further survival.
A Novel Unsupervised Hashing Method for Image Retrieval Based on K-Reciprocal Nearest Neighbors

Hashing methods play an important role in large-scale image retrieval. Unsupervised hashing is popular in practical applications because it does not require labels for supervised training. However, as one of the important steps in unsupervised hashing, construction of semantic relationships between data by k-nearest neighbors has limitations due to the existence of false neighbors among the first k neighbors. In this paper, we propose a novel unsupervised deep hashing method for image retrieval. We firstly construct a semantic similarity matrix which utilizes deep features and the expanded k-reciprocal nearest neighbors to guide the learning of hash codes. After that, we design a deep neural network to preserve the structural information of original images. In addition, a weighted pairwise loss function generated by the positive pairs and negative pairs is employed to solve data imbalance problem. Extensive experiments on CIFAR-10, MIRFLICKR and NUS-WIDE datasets show that our method significantly outperforms the state-of-the-art unsupervised hashing methods.
Implementation Of Naive Bayes Algorithm With Particle Swarm Optimization In Classification Of Dress Recommendation

Fashion is considered as a cycle of reflection of unique social, cultural and environmental characteristics in time besides playing an important role in completing one's self-image. Current developments in technology and information are foremost for the growth in the amount of data held been recorded and stored in large databases (data mountains) to turn into a piece of knowledge by classifying using machine learning. One of the classification methods that can be used is Naïve Bayes. The purpose of this study is Dress Classification Recommendation using the Particle Swarm Optimization-based Naïve Bayes algorithm by increasing the existing accuracy value. This study uses a public Dresses Attribute Sales dataset downloaded at the UCI Machine Learning repository with 13 Attributes and has two labels, 1 for recommendation and 0 for no recommendation. The amount of data is 500 data. The evaluation used is to use the Confusion Matrix, to determine the value of accuracy, precision, and recall. The results of the experiments carried out by using the optimization feature particle swarm optimization with population size 20 parameters and maximum of number generation 35, then using Cross-Validation with Naïve Bayes algorithm. The value of Cross-Validation used is 3, 5, 7 and 10, that the highest value of accuracy is to use the value of Cross-Validation (K Fold) K 10, with an accuracy value of 65.40% with precision 67.28% and recall 80.34%.
Research on the Application of Computer Technology in College English Translation Teaching

Abstract English translation is an important means to help students improve their oral English ability, which is the basic method to cultivate students’ good English literacy. With the continuous popularization of network technology, English translation teaching has also ushered in another climax. In teaching practice, we should actively use translation as an English teaching strategy, which will give full play to the advantages of English translation. On the one hand, under the positive transfer of mother tongue, English translation can improve the comprehensive language ability. On the other hand, English translation can improve the efficiency of English teaching. This paper first analyses the importance of translation teaching in English teaching. Then, this paper puts forward some problems in English translation teaching. Finally, some suggestions are put forward.
Research on the Model of Coordinated Development of Computer Aided Technology in University Library and Local Cultural Construction

Abstract The construction and development of local culture marks the local economic construction. The role, advantages and important functions of local university libraries in the construction of local culture explain the importance of local cultural construction in local development, and the cultural construction of university libraries also proposes that local cultural construction needs to be strengthened. Construction of document reading room and special collection room. The computer aided technology enters the university library and the local culture construction cooperates the development. Large-scale development of cultural resources in the localities and provision of corresponding cultural services. We provide services to the people in need of the society, play a cultural display function, and carry out certain cultural exchange activities according to the society and people’s lifestyles, so as to better provide regional cultural construction services.
A Deep Learning Approach to Large-Scale Light Curve Prediction and Real-Time Anomaly Detection with Grubbs Criterion

In light curves (LCs), the brightness of stars is associated with time, and so is its image. The traditional data processing methods cannot effectively handle real-time and large-volume data of various LCs. To address this issue, this work develops a deep neural network named Dropout-based Recurrent Neural Networks (DRNN). It extracts complicated features of all images captured by Mini Ground-based Wide-Angle Camera array (Mini-GWAC) for point source extraction and cross-certification through Long Short-Term Memory units. DRNN can also produce warnings for abnormal values of light change curves. Furthermore, this work optimizes the training model by combining a dropout method with an adaptive moment estimation algorithm to iteratively update the network weight of the RNN based on the LCs data. Extensive experiments with a Mini-GWAC dataset demonstrate that DRNN outperforms several typical methods in terms of prediction performance of star brightness in large-scale astronomical LCs.
Robust spatial information based tumour detection for brain MR images

Multimodal brain MR image analysis is still a challenging research area due to its complex intensity distribution and sensitivity towards the noise. Tumourous cells have different characteristics than normal human cells, which makes them more salient. In this Letter, the authors propose a novel unsupervised spatial information based saliency boosting tumour detection method which will help to identify tumourous cells by making it more clearly visible. Initially, a pseudo-coloured MR image is formed using the CIELab colour space. Saliency map has been established by calculating distance among scales varying elliptical windows in both spatial and colour space. Elliptical windows endeavour to cover-up curved outliers of the brain images. The average intensity value is kept constant by fixing the axis ratio for each window. The proposed algorithm has been evaluated on both real and simulated brain images of different patients from MICCAI-BRATS database. The performance analysis of the new algorithm exhibits higher accuracy with a low computational complexity as compared to other state of the art. The efficacy is due to the immobility of the window across rows and columns to move over the image. The novelty of the proposed technique is that neither it downscales the input images nor require any training bases.
Weather Dataset Analysis Using Apache Pig

This paper presents a review on using Apache Pig as a tool to analyze weather dataset. To analyze and extract information from dataset, Pig Latin which is a scripting language has been used. Since data are being produced at an alarming rate, management of data is the need of the hour. The storage, processing, and retrieval of such a huge volume of data is an area of concern nowadays. Through this paper, an effort to analyze weather dataset has been made through various commands written in Pig Latin. The results drawn from an analysis shows the power of Apache Pig as a data analysis tool.
Talking in Italian About AI with a Chatbot: A Prototype of a Question-Answering Agent

Talking with chatbots and question answering interfaces is nowadays common to most people using some kind of digital device. Artificial intelligence-based solutions to create chatbots are available on the market and are provided by all the big players like IBM, Microsoft, Google, and Amazon. Chatbots can differ for the type of corpus they rely upon, the type of questions they are suited for, the algorithms, and the ability to learn and expand their knowledge base. Moreover they differ for the language, with English chatbots being on average those best performing. In this paper we present ConversIAmo, a chatbot prototype designed to answer questions in Italian about introductory concepts on Artificial Intelligence. The natural language processing pipeline is built upon the IBM Watson suite and implements further modules for improving the answer selection and ordering, and to expand the knowledge base. Results are encouraging, especially with regard to the ordering of the correct answers. The paper describes the question answering dataset, the first in this domain, and outlines the dialog flow and the answering process.
CES: Design and Implementation of College Exam System

The caliber of a student is reflected by the results he obtains in his institution’s examinations. Properly conducting exams as well as maintaining results via a system thus is mandatory. The performance of a result system is measured by the efficiency it works with. Owing to the large magnitude and complexities of the tasks involved, an automated and easy to use result system is required in every educational establishment. A manual method of handling all the associated tasks won’t suffice because of the high chances of errors, complexities and computations involved. The proposed solution is a web application developed via JSP Servlets and MySQL database that handles all the result related activities right from the enrollment of the student to his result generation. As per the need of the institution, the grades and the semester grade point averages (SGPA’s) are displayed in a class-wise manner. The application also provides interfaces to maintain and modify schema, allocate faculties and submitting marks to the respective users.
Multifunctional Trajectory Control System of Robot Based on PC

The PC-based robot multi-function trajectory control system is developed and designed for the cumbersome control of industrial robot hand-held manipulators, poor human-computer interaction, and difficulty in system integration. The system is based on C# programming design, which is convenient for system integration and expansion. It interacts with the robot through Socket network communication so that it's able to monitor and control the robot's movement process in real time. The system effectively combines online programming and offline programming functions, and designs the “draw” 2D and 3D trajectory drawing function, which can easily and quickly generate 2D or regular 3D trajectories. The experimental results of laser marking show that the system can realize the laser marking process of two-dimensional or regular three-dimensional graphics through a variety of trajectory generation methods.
Error splitting method for training a built-in neural network storage element with SR-latch functionality

A method for dividing the error when passing through a storage element with SR-latch functionality for embedding in neural networks with one output and two inputs is presented. In the backpropagation method, the error is divided from one output to the two inputs with opposite coefficients. In this way, the element trains the previous neural layers to detect input vectors, which indicate the beginning and the end of statuses to be remembered. The forward and reverse interfaces of the element are defined, respectively for calculating the information signal and the error.
X-YOLO

Observing X-ray images manually is a common method for detecting contraband in packages. Long-term continuous observation is prone to visual fatigue, leading to problems of missed detection and false detection. Motivated by aiding operators in contraband detection in packages, we propose X-YOLO which is a deep learning based toolset with multiple optimization strategies for contraband detection to increase the detection precision. The path enhancement is designed to shorten the information path between the lower layer and the uppermost layer. We replace Leaky ReLU with Swish and Steps with SGDR to make training stable. Mixup, a dataset-independent method for data augmentation, is designed to increase the amount of training data for improving the generalization of model without expert knowledge. In order to solve the issue that Intersection over Union (IoU) can not deal with two non-overlapping objects, we apply Generalized Intersection over Union (GIoU) as bounding box losses. The experimental results show that X-YOLO achieves mAP up to 96.02% and recall up to 98.55%, surpassing Faster R-CNN, SSD, YOLOv1, YOLOv2, Tiny-YOLO, YOLOv3, YOLOv3-tiny, YOLOv3-spp and YOLOv3 with some of optimization strategies.
Government internet financial reporting in the African Countries

The paper investigates the disclosure of financial information at the government level in Africacountries. The research focuses on the accessibility of financial information or financial report in Africa and uses website content analysis on data of internet financial reporting of African countries. The study adopts 10 African countries randomly selected, and 3 websites from each country that relates to primary financial information for stakeholders, namely: the official government website, ministry of finance website and government auditor office website. The research uses the index of internet financial reporting to measure the accessibility of the data. Swaziland records the highest value of accessibility and absolute value from the three assessed websites. In contrast, Angola and the Democratic Republic of Congo record the least average accessibility value of 2.0 from the evaluated websites. The results show the existence of unequal accessibility values amongst the websites of study. The study claims that several countries finance department and government auditors' websites cannot be accessed on the first page of Google Search Engine. Finally, internet financial reporting (IFR) in Africa is relatively low because many countries’ results of their financial reports and the audit reports are not finalised as and when due.The study stresses the importance of African countries to adopt International Public Sector Accounting Standards (IPSAS) and thus improving the availability, quality and comparability of financial information that enhances the visibility of public sector entities’ activities throughout the world. Similarly, the study argues that because financial information is difficult to find and whereit exists lack detailed information and thereby affecting investors’ decision making about Africacountries.