Reviewerly/exHarmony huggingface dataset:
Design of distance education system for digital media online course based on improved genetic algorithm and speech recognition technology

The distance teaching of digital media network course under the network environment can improve the pertinence of teaching and the sharing of teaching resources. On this basis, a distance teaching system of digital media online course based on improved genetic algorithm and speech recognition technology is designed. The online course teaching system consists of network communication module, data acquisition module, bus transmission module and application loading module. The module connection and function control of online course teaching system are realized under VME bus architecture. Based on improved genetic algorithm and speech recognition technology, using eclipse as the development environment, the data storage layer, user analysis layer and log mining layer of online course teaching are constructed. The control and structure layout of online course teaching terminal are realized on the user interface, and the system optimization design is completed. The system test results show that the bus data transmission performance of the system for online course teaching is good, and it can effectively meet the personalized needs.
Advanced measurement infrastructures for time-sensitive applications using ACP architecture

The growth of humanity and online sources of stored digital recordings increases day by day in the form of digital files available in cloud explorer formats. Most of the industry will be affected by Bigdata in the foreseeable future. By providing a comprehensive and trustworthy summary of available information, Big Data can assist in the transformation of key organizational processes. Big data has played an important part in identifying violent crime. The current architecture for developing Bigdata deployments is efficient, high-performance computing by analyzing Bigdata combining multiple computing units to perform sophisticated computing. This article presents the Additional Commodity Planner (ACP) lightweight structure examines the basic concepts of many typical big data deployments. It concentrates on the notion of time-critical big data systems from the standpoint of requirements. ACP is the standard computational architecture that helps MapReduce and other Hadoop applications. ACP requires the concurrent execution of multiple programs on a shared server and the use of consent programs to allocate services as required. This final assessment was followed by issues raised by systems and facilities that support applications, and provide frameworks for effective initial features that often contribute to operational reliability.
Umrah Registration System Using Extreme Programming Method Towards Worship Tourism

The Umrah registration process at PT Annisa Mulia Wisata still uses a manual system, so the admin at the branch office must contact the head office first to find out the quota availability for the Umrah package ordered. For this reason, a system is needed to assist the ongoing Umrah registration activities so that errors during the registration process can be reduced and the system can run effectively and efficiently. The development stage of this web-based Umrah package registration system was built using the Laravel framework and system development life cycle (SDLC) to support this research using Extreme Programming (XP). With this web-based Umrah registration system, it can help prospective pilgrims in the Umrah registration process by choosing each type of package along with the price and number of quotas and as a medium of information in the marketing process and transaction data processing for companies.
Anti-Jamming Wireless Communication Using Chaos-Based Code Selection Spread Spectrum Technique

Physical layer performance of wireless communication, which is subjected to reactive jamming attack, is analyzed in this paper. The main problem in conventional direct sequence spread spectrum (DSSS) is the requirement of pre-shared key between sender and receiver. Many researchers focused to remove pre-shared keys for anti-jamming communication, but in those techniques, it requires enough time to de-spread the data. So to overcome the problem of pre-shared key and to enhance the security of wireless communication with minimum de-spreading time, chaos-based code selection (CCS) DSSS has been proposed in this paper. Matlab simulation results show that our proposed technique CCS DSSS indicates much better performance when compared with other unshared secret spreading keys in terms of security and de-spreading time. The de-spreading time required to extract the original message of size 512 bits is almost 0.05888 ms, which is minimum compared with other unshared secret spreading key spread spectra.
Learning to Predict What Humans Look at: Computational Visual Attention Model for Specific Category

Humans can easily find a specific category of objects in a complex scene, simulating this mechanism has both scientific and economic impact. The existing research usually focuses on where humans will look, overlooking the effects of the category of objects on visual attention. In this paper, we proposed a computational visual model aimed at mimicking human visual attention while they were looking for a specific category of objects. First, we proposed a machine learning-based Probabilistic Latent Semantic Analysis (PLSA) model to recognize the generic category of objects and find their locations. The PLSA model parameters are learned in a supervised manner. Then, the category and location information of objects are used as high-level information, together with low-level features of the same objects, to train a Support Vector Regression (SVR) model. With this SVR model, we can predict the visual attention for a specific category. To demonstrate the effectiveness and applicability of the proposed method, we conducted comprehensive experiments. The results show that the model can provide a reasonable estimate for human visual attention under the visual search task for a specific category. Besides, we evaluated the proposed model&#x0027;s ability to discover a specific category of objects and their locations on the natural image dataset. The results show that besides facilitating the human visual attention mechanism research, the proposed model can also be applied to find a specific category of objects from a set of images.
Professional Titles Evaluation System Based on PHP and MySQL

In this paper., a mature three-tier architecture based on B/S mode is adopted., and the Web technologies of jqgrid., layui., jQuery., PHP and MySQL is used to design and realize the professional titles evaluation system., which realizes the function modules of scientific research achievements management., teaching achievements management., Professional titles evaluation management and peer review. Under the current background of &#x201C;breaking five principles&#x201D;., the peer review module designed by the system can help colleges and universities evaluate teachers&#x0027; scientific research and teaching achievements objectively and fairly., and colleges and universities can refer to the results of peer review in the promotion of teachers&#x0027; professional titles. This system has been put into use in some colleges and universities., and has certain application innovation and promotion value.
Design of Distributed Terminal Data Joint Learning Model Based on Blockchain

With the rapid development of new-generation information technologies people enjoy the convenience of technology and are also troubled by privacy data leakage. Especially in artificial intelligence technology, its development is inseparable from the support of data. The quality of data directly determines the effect of the model. However, in recent years, with the increasing awareness of privacy protection and the promulgation of relevant laws and regulations, the collection and use of data has become a major problem, which greatly limits the development of artificial intelligence technology. The emergence of federated learning needs to solve this problem. It ensures that the data can not be exported to the user&#x0027;s local area and can also achieve the purpose of data utilization. This paper proposes a federated learning model based on the blockchain decentralized architecture, which aims to solve the contradiction between data privacy protection and data utilization, and achieve the purpose of data &#x201C;available invisible&#x201D;; finally, three different experiments were tested. The training method is summarized.
Design of transformer load management system based on multi-resources data

Abstract Ensuring data quality, the main transformer load risk assessment model based on load rate characteristics is established. Further, using deep learning algorithm, the main transformer heavy and overload risk prediction model is constructed to realize the risk grade assessment and risk prediction on load feature defects. Finally, through the construction of the system platform, the basic functions such as multi-dimensional index calculation, statistics and visual display of real-time load characteristics of the main transformer are realized.
Intelligent Drug Delivery Car System Using STM32

This system consists of STM32F407 single chip microcomputer, STM32F103 single chip microcomputer, openmv vision module and k210 vision module are composed. Taking stm32f407 single chip microcomputer as the control core, combined with STM32F103 single chip microcomputer, openmv and k210, the device is designed to be used for drug transportation in wards and isolation wards with large workload in the hospital. The device uses openmv to identify the red solid line on the transportation ground of the hospital, Through the dynamic priority scheduling algorithm in PD algorithm, the priority of tasks is dynamically allocated according to the resource requirements of tasks, so as to have greater flexibility in resource allocation and scheduling, realize flexible tracking function and dynamic adjustment process, and make the car drive along the red. K210 visual module is used to reflect the appearance difference through the given training photos, which is as same as the identification number as possible, which is convenient to improve the identification rate. After more identification times, the identification number and its position information can be accurately identified, and the identified number and its position information can be transmitted to stm32f407 single chip microcomputer through serial port communication (considering the need to identify four numbers at the same time, two k210 are installed on the front of each vehicle), stm32f407 single chip microcomputer processes the identification information of k210 and tells STM32F103 single chip microcomputer the movement state of the car at this time through serial port communication. Finally, STM32F103 single chip microcomputer controls the car to move accordingly. The data interaction method of the two cars adopts wireless communication. The system has the advantages of short recognition time, digital recognition accuracy of up to 90&#x0025; and good stability. It can better complete the drug delivery work required by hospital medical staff, and the work efficiency is higher than manual work. At the same time, the machine itself can also cut off the direct contact between medical staff and patients, which can greatly reduce the number of contact between medical staff and patients, Reduce the prevalence of cross infection and medical staff. The device adopts a multi-level priority scheduling algorithm to assign a priority to each process. During each process scheduling, the scheduler always schedules the task with the highest priority to execute, so as to make the car movement more flexible and more active. It is convenient to deal with some emergencies by using interrupts, which is more reasonable and suitable for real hospital medical work.
Research on infrared target recognition algorithm based on SSD-MobileNetv1 network

Infrared target recognition is a hot direction in computer vision and digital image processing, which has high theoretical research value and market application prospects, and develops gradually with the development of deep learning, image processing, pattern recognition and other fields. In order to solve the problem of insufficient accuracy and recognition speed of infrared target recognition in practical application. An infrared target recognition method based on SSD-MobileNetv1 target detection model is constructed. In this paper, the self-made infrared data set is used, and the data set is enhanced and annotated, and the noise is suppressed. In the Windows system, the object detection API of TensorFlow is used to train the data set, and the trained SSD-MobileNetv1 model is used to classify the test images and obtain the recognition results. The experimental results show that: The SSD-MobileNetv1 model has good detection and recognition effects on infrared images; The model has the advantages of accurate target location, high recognition accuracy, and good stability for the recognition of images with background interference.
Design and modeling of automation, autonomy, and artificial intelligence mission system for multi-domain joint operation

To cope with the challenges brought by the rapid development of system intelligence, the variety of mission system pattern, the complexity of mission system environment, the constantly changing of the situation, an Automation, Autonomy and Artificial intelligence (3A) mission system for multi-domain joint operation is proposed, and it’s modeling and analysis are carried out. First, this paper introduced the development trend of mission system for multidomain operation. On this basis, the concept of 3A system and the levels about intelligence have been proposed. Finally, the effectiveness of 3A-based mission system organization is illustrated by modeling and analysis of a typical aerial combat assumption scenario.
Paraconsistent Orbits of Logics

Some strategies to turn any logic into a paraconsistent system are examined. In the environment of universal logic, we show how to paraconsistentize logics at the abstract level using a transformation in the class of all abstract logics called paraconsistentization by consistent sets . Moreover, by means of the notions of paradeduction and paraconsequence we go on applying the process of changing a logic converting it into a paraconsistent system. We also examine how this transformation can be performed using multideductive abstract logics. To conclude, the conceptual notion paraconsistent orbit of a logic is proposed.
Case study on aquaculture monitoring system using IOT-based

Recently, fishing production has been decreasing, and as a countermeasure, we intend to increase production through aquaculture. However, problems such as water pollution, climate change, increase in marine waste, slowdown in fish farm growth, and death of unknown fish groups are being derived from aquaculture. In addition, depending on the size of the fish farm, poor management, lack of manpower, and safety accidents in aquaculture are occurring. Therefore, this study aims to present directions for the fish farm monitoring system based on IOT in the ocean and help those who want to study the fish industry.
Research on Layered Settlement Monitoring System of Airport High Filling Slope Based on Fiber Grating Technology

High-filling airports have the characteristics of large terrain fluctuations, complex geological conditions, diverse materials and huge engineering volume, which tend to cause problems such as site instability, differential settlement, and instability of high slopes. It is very important to strengthen the monitoring of airport high filling engineering, and the internal settlement of the filling body is one of the main items of high filling monitoring. When the traditional layered settlement monitoring device is used to monitor the internal settlement of the high filling slope, it has disadvantages such as the difficulty of embedding measuring elements, observation during construction, and automatic monitoring. Aiming at the current problems in the monitoring of the layered settlement of the filling body, this paper developed a layered settlement monitoring system of the filling body based on the fiber grating technology, which could realize the automatic settlement monitoring of the multi-point displacement inside the filling body. The on-site application test results show that the monitoring system has reasonable structure design. The monitoring system also has the advantages of easy operation, high precision and environmental compatibility and it is suitable for layered settlement monitoring of airport high filling slope.
Mobile Application Development Using MIT App Inventor: An Experiment at Raman Research Institute Library

App Inventor for Android is a no-code open platform for mobile app development using the drag-and-drop approach. In this paper, the authors explore the MIT App Inventor, its salient features, and how library professionals can use the tool to develop apps for their library. The article also gives glimpses of the Mobile Application developed by the authors using the MIT App Inventor app developing platform.
We-Care-A Donation App

This application goes to assist poor people of India as through this application we are visiting distribute leftovers, clothes and books of the center class and rich people to the poor those that need this food to fill their empty stomach and garments to wear together with books to teach themselves. We have taken a path to implement our innovative ideas in the form of this project named as “We-Care A Donation App”. In highly populated countries like India, food wastage is a disturbing issue. Marriages, canteens, restaurants, social and family get-togethers, and functions drive out so much food. Food wastage is not only an indication of hunger or pollution but also of many economic problems.. because of quick changes in habits and lifestyle. Instead of wasting these things we can put them to use by donating them to needy ones. This project is an mobile based android application that aims at donation for needy. The main purpose of this project is to make contribution on reducing the economic and social problems. This will help to reduce food wastage and fulfill other requirements like clothes, books, blood etc, for needy people. This Benefits in both the restaurants (reducing the carbon footprint and wastage), and the needy ones.
An Analysis of Factors Affecting Government Tax Revenue in India

The purpose of this paper is to study the role of tax education and tax knowledge towards tax revenue in India and the factors that affects government tax revenues in India. For this purpose, structured questionnaire has been framed and send to all the respondents. These respondents include Government Officials, Academicians and Members of Ministry of Finance. The questionnaire contained of open-ended and close-ended questions. For online data collection, the researcher emailed online questionnaire by Google Docs and requested respondents to access link and response were collected online in a spreadsheet as well as the personal survey was done by the researcher as per the convenience. The well-structured questionnaire comprising of bi-polar, and Likert’s 5 point scale type questions. To test the hypotheses and check the reliability of questionnaire Cronbach’s Alpha, Kruskal-Wallis Test, Simple percentage Analysis, One-way Analysis of Variance (ANOVA) have been applied and found as an outcome of Anova test that, there is no significant differences in the perception of stakeholders towards factor affecting government tax revenues in India aspects.
Stibnite Mineralization in Hamedan, West Iran

Hamedan (Faghireh) antimony deposit is located in the west of Iran relating to Alvand Granitoids. The mineralization occurs as a series of veins. Thickness of the veins is variable and reaches up to 1 m. The veins are emplaced along high angle faults. These faults were ways for migration of ore forming fluids. Mineralization is constituted of stibnite, pyrite, realgar and orpiment with quartz as a gangue. The veins are of the open-space-filling type with zones of brecciation. Monzogranites which formed the most part of Alvand Pluton are the host of the veins. Monzogranites consist of quartz, oligoclase, orthoclase, biotite and subordinate muscovite. The veins have average contents of 30% antimony, 0.8 ppm gold and 500 ppm arsenic. According to geochemical studies there are anomalies of Sb, Au, As, Ag, Hg, Sn, Ni, Co and Cr in the host rocks. Spider diagrams show a gentle decrease from La to Lu for host rocks and veins, and have some similarities but any comparing between them needs more evidences.
Orthogonal Constrained Meta Heuristic Adaptive Multi-View Clustering over Multi Labeled Categorical Data Analysis

In data mining, clustering is the one of the efficient research concept in real time data analysis, evaluation of attribute representation in clustering is main issue in artificial intelligence related research areas. Multi labeled clustering gives high amount of valuable data, which describes the evaluation and representation of attribute be the trending concept in multi labeled categorical data analysis. Multi dimensional clustering is combined complementary data from different dimensions to provide efficient clustering results in various conditions. Different multi view clustering techniques are proposed traditionally but they can give output as single clustering with input data. Because of multiplicity, multi dimensional data can have different grouping data which are reasonable consist perspective attributes. So how to find measurable and reasonable cluster results which are represented in multi view labeled data is still challenging task, so that in this paper, we propose a novel approach i.e. Orthogonal Constrained Meta Heuristic Adaptive Multi-View Clustering (OCMHAMVC) to represent data as a cluster with different categories. Based on multi labeled data, first proposed approach evaluates low dimensional data using optimized matrix factorization (OMF) method and clusters the similar labeled sample data into prototype cluster of dimensional data. After that we represent data in desirable orthonormality constrained view of data using adaptive heuristic to combine complementary data from different dimensions, also provide complexity in computational analysis of data representation. Experimental results of proposed approach applied on high amount of multi view data gives scalable and efficient performance with comparison to traditional multi view related clustering approaches.
The vocabulary of agriculture semi-popularization articles in English: A corpus-based study

Based on the obtained research results, this paper makes an in-depth study of English vocabulary interpretation retrieval technology, and proposes a corpus based automatic retrieval technology of English vocabulary interpretation. This paper adopts the basic idea of text formalization in the field of natural language processing, uses part of speech, grammar and semantic markers to formalize the interpretation of English vocabulary, and mainly adopts the way of using vocabulary and various markers separately or mixed to serialize the interpretation of English vocabulary. In order to analyze the user input English vocabulary, the first step is to segment the user input natural language, and then extract the key words which can express the meaning of the sentence. The construction of English vocabulary interpretation domain ontology based on corpus needs a set of perfect engineering system method. The automatic retrieval model of English vocabulary interpretation is constructed to realize the automatic retrieval of English vocabulary interpretation. The constructed automatic retrieval model of English vocabulary interpretation includes grammar analysis subsystem and grammar analysis subsystem. Through comparative experiments, it is verified that the retrieval response time of this technology is shorter, and the retrieval performance is improved.&#x0D;