Reviewerly/exHarmony huggingface dataset:
Face Recognition System Based on Improved LVQ Neural Network Algorithm

With the development of computer technology, face recognition has become one of the hot research topics today. Aiming at the current problems of face orientation recognition such as low recognition accuracy and influence by lighting conditions, this paper starts from the principle of LVQ algorithm, by establishing the improved LVQ algorithm model and applying it to face feature matching, realizing the session to establish 400 face images as training set and 40 as test set, and deriving the recognition accuracy of the improved LVQ algorithm model as 93%. The experiments compare the BP algorithm and SVM algorithm in four aspects: training set accuracy, training set loss function, test set accuracy, and recognition effect on different data sets, and verify that the LVQ algorithm has a greater advantage in accuracy and stability.
A Study on Design and Creative for Interactive Media and Using M-learning to mix-media on Cloud Technology: "How to understand and use herbs properly"

The purposes of this research were 1( to help learners to learn and understand history of herbs, 2( to enable the learners to classify herbs according to the purpose of use, 3( to make the learners realize the danger of inappropriate use of herbs, 4( to educate the learners to use herbs appropriately. The research was advised, examined, and evaluated by target group. The sample group for the study was 27 undergraduate students of Medical and Science Programmed Media Arts Department. Motion graphics were used to create this digital media, encouraging lifelong learning. The designed media was tested with a target group of participants aged 18 to 22. On visuals, storytelling, audio, soundtrack and music of the media evaluation, the average scores given by the target group were equal at 4. 09 (S. D. 0. 66) ) satisfactory level( The average score on the content and understanding of content per media viewing aspect was the highest, 4. 09 (S. D. 0. 76) ) satisfactory level( as the target group thought the media made them understand more of the benefits In summary, the designed media received the average score of overall media design at 4.28 (S.D. 0.74). Therefore, the Creative Media Design Using M-learning the topic of Herbs learn and use. the lesson was appropriate in terms of vision and sound and it was also evaluated as good by the experts and the target group. Therefore, it could be used and developed further.
Intelligent Balance Vehicle for Medical Nucleic Acid Collection Based on Path Planning

Aiming at the problems of difficult detection, high workload and high exposure risk in the nucleic acid detection process in hospitals, this project proposes a smart medical balance car based on path planning. The control system of the device is mainly controlled by a single chip microcomputer, and the controller is used as the system regulation feedback part to realize the PID regulation of the balance system, ensure the stability of the system and complete the medical work at the same time; For the data detection part of the balance system, the device uses integrated attitude sensors to detect various parameters of the balance car, realizing high-frequency sampling and real-time monitoring. The path planning part of the device samples the A * algorithm, which forms a topology map by modeling the map, and obtains the shortest path of nucleic acid detection process in different wards by sorting according to the calculated weights of each node, so as to achieve efficient and low energy consumption nucleic acid detection. In the process of nucleic acid detection, OpenMV samples and identifies the facial information of patients in different wards, and determines the information of nucleic acid monitors, Assist to complete nucleic acid detection task in monolayer ward.
Self-Calibrating Microring Resonator by Monitoring Wavelengths

We experimentally demonstrate a self-calibrating microring resonator with 7-bit high-precision configuration and resistance to temperature fluctuations by monitoring wavelengths. This work provides stable and accurate control of microring resonators for applications such as optical computing and optical information processing.
Detecting Software Code Vulnerabilities Using 2D Convolutional Neural Networks with Program Slicing Feature Maps

Throughout the post-PC world, IoT devices and real-time embedded systems have integrated themselves into every aspect of our lives. However, as technology integrates itself, the risk of security vulnerabilities and their impact also grows. Different languages have different susceptibilities to cyberattacks. Programs based on C and C++ are particularly vulnerable to cyberattacks through buffer overflow errors due to their lack of memory management. While security vulnerabilities are well-studied areas, with the increasing popularity of deep learning applications, the attack scenarios have become more sophis-ticated, and traditional techniques may no longer be enough to detect attacks or potential vulnerabilities. Therefore, the application of using deep learning to detect such vulnerabilities has become a trend. The appeal of using deep learning in software security is usually based on graphical models and data, which encourages researchers to use graphical-based deep learning methods like Graph Neural Networks (GNN). In this study, we use a Convolutional Neural Network (CNN) to detect security vulnerabilities due to its scalability and lower computation need. This paper proposes scanning vulnerable C/C++ functions for vulnerabilities using deep learning-based image classification. Our experiments are performed on the NIST SARD dataset. Inspired by existing high-level language vulnerability detection, we propose converting the function into an image through three steps: sentence embedding, a statically created program dependency graph, and social network analysis.We employ sentence embedding to convert each line of code into an equally sized representative vector. Following this, we produce a program dependency graph (PDG) for each function. Each line of code is then analyzed using three metrics: Katz, closeness, and destructibility. We compute the destructibility metric by employing forward-slicing on the PDG to determine the reachability of each line. The combination of the equally sized vectors and the analysis metrics are used to create a representative image of the source code. Finally, the image is classified through a Convolutional Neural Network.
Analysis of a Multichannel Learning Mechanism for Speech Detection in Social Networks

A useful approach, TF -IDF (Term Frequency - Inverse Text Frequency) looks at the frequency of terms to figure out how important they are in a particular document. It's an excellent starting point for many different projects since it's a straightforward method for assigning weights to words. Constructing search engines, summarising documents, and other related information retrieval and machine learning activities fall under this category.
Multi-Target Tracking Based on Ferguson-Hough Algorithm Against Frequency Ambiguity Issue

The Short-time Fourier transform (STFT) is widely used in the analysis of non-stationary signals because of its mature principle and simple implementation, as well as in the multi-target tracking based on Doppler Through-Wall Radar (TWR). However, due to the limitation of the uncertainty principle, when the frequencies of several echo signals are close to each other, there will be aliasing in the spectrum obtained by STFT, which will seriously degrade the accuracy of multi-target tracking. To overcome this limitation, we proposed an improved Ferguson-Hough algorithm, which combines the asymmetric Ferguson parameter model with the Hough transform and can fit the instantaneous frequency curve of the echo signal in the frequency ambiguous area, thus compensating for the loss of tracking accuracy. Experiments show that the method can effectively fit the frequencies in the frequency-ambiguous region, thus making the localization results approximate to the real data, and achieving better localization accuracy than other similar algorithms.
The Angle between Hyperplanes: A New Metric for Concept Drift

To detect concept drift, choosing an appropriate metric is the critical step. Without prior knowledge, academics are accustomed to using general metrics such as error rate, density, or distance. However, these metrics are easily affected by virtual drift and noise, thereby degrading the model’s performance. Based on support vector machines (SVM) , this paper proposes a new concept drift metric, namely, ABH (the angle between hyperplanes). SVM maps samples to a high-latitude space through a kernel function to form a hyperplane. Changes in the data distribution cause the hyperplane to deflect. We calculate the ABH, which estimates how much the data distribution varies. According to the properties of SVM, we prove that ABH requires no prior knowledge and is immune to virtual drift and noise. In the decision function of the drift detection method (DDM), we use ABH instead of the error rate as a new metric to model ABHDDM. Numerous experiments of data divided into two categories mainly compare the classification accuracy of ABHDDM with the DDM and the Weighted Incremental–Decremental SVM (WIDSVM). In addition, ABHDDM is also compared with many existing models. These experiments prove that ABHDDM is a model with excellent performance, and ABH can reflect the data distribution. These results directly contribute to the study of metrics to address concept drift.
The Phenomena of Using Adjectives as Verbs and Using Nouns as Adjectives in Chinese

In Chinese, adjectives are sometimes used as verbs and nouns are sometimes used as adjectives, especially online. Usually, although the word occupies only one part of speech, it may be used as another part of speech, which may violate the syntactical rules but make sense to most people. In this paper, various examples of these two phenomena will be closely examined, tests are implemented to verify the original part of speech of the exact word that is used as a different part of speech, and many observations are made.
Large-Scale Matrix-Vector Multiplication Based on Simplified Circular Optical Computing via Matrix Factorization

We propose and experimentally demonstrate a circular optical computing model based on limited number of delay lines capable of efficient large-scale matrix-vector multiplication via band constrained nonnegative matrix factorization.
Establishment and Evaluation of Measurement and Control System Model Based on Data Analysis Optimization

As an essential asset of an enterprise, data plays a vital role in risk assessment. To realize the effective integration of data related to the main factors of enterprise operation, including management, personnel and other data. To deepen the construction of data and analysis system, through the maturity analysis of different evaluation indicators to get the comprehensive evaluation results of the current system. Based on the above situation, this paper uses the principal component analysis method to integrate data analysis from the three aspects of personnel, arrangement and technology, and builds an index relationship network to show the relationship between different evaluation indicators. The principal component analysis method is used to identify the significant indicators in the network as the key points to be improved, and then analyzes the existing system maturity from three aspects to obtain the evaluation results. At the same time, the grayscale prediction model is established, and the overall evaluation analysis and prediction evaluation of the three parts and other indicators are carried out, and the comprehensive evaluation of the enterprise data is further carried out.
Compact and Low-Power Programmable Multiport Interferometer on CMOS-compatible Deuterated Silicon Nitride

A 6-mode programmable interferometer at 1550-nm wavelength is fabricated on CMOS-compatible silicon nitride platform. Featuring suspended thermo-optic phase shifters, the device shows 2-fold improvement in compactness and 10-fold in power efficiency compared to conventional device.
Two Modes Unscrambling Using a Coherent Micro-ring Resonator Network

We propose and demonstrate the use of a micro-ring resonator (MRR) based coherent network for unitary matrix operations. We demonstrated the MRR-based coherent network for polarization mode switching and mode unscrambling. Specifically, we show that two arbitrarily mixed modes can be unscrambled to crosstalk levels below -21dB.
Design of Geospatial Big Data Cloud Platform for Land Resources

This platform aims to fully support the "cloud + end " land resources geospatial big data business, integrate land resources, connect provincial and municipal big data centers, and form a smart city refined governance database. To build a geospatial big data service engine for land resources that integrates data collection, product processing, mining analysis, and storage services to achieve a unified business layout of data integration, direct connectivity, and a backup function of core backup, remote dual-action. According to the business architecture of "cloud + end " and integration of data and algorithms of the big data cloud platform, we designed a geospatial big data cloud platform for land and resources which will support the cloud management of land resources geospatial big data storage resources, algorithm and application component management, the integration of data, algorithm and storage and the construction of land resources business system.
Partially Disaggregated Data Centers: Service Provisioning and Resource Allocation

We propose a scheme that partially disaggregates resources in data centers for more efficient operations. To handle service provisioning and resource allocation in this type of data center, we develop an integer linear programming (ILP) model and an efficient heuristic algorithm. Simulations show that data centers with increasing disaggregation levels do much better than traditional server-based data centers. In addition, the proposed heuristic algorithm is efficient and performs close to the ILP model and outperforms a benchmark scheme.
Research on University Teaching Quality Evaluation System Based on Big Data Technology

Teaching quality evaluation (hereinafter referred to as TQE) plays an important role in improving the teaching quality of universities.In order to improve the accuracy of college TQE, based on the familiarity with big data technology and university TQE technology, this paper expounds the development and application scope of college teaching based on big data, and constructs a university TQE system based on big data technology, mainly including big data information collection and analysis function module, curriculum resource management function module, TQE management and feedback tracking function module and user management function module. In order to further improve the accuracy of the overall quality evaluation of the system, the system uses the fuzzy evaluation method to normalize the evaluation data and realize the accurate evaluation of the teaching quality. The experimental results show that the designed TQE system can accurately complete the evaluation of teaching quality, and has practical application value.
Kinect-based Data Processing Noncontact Robotic Arm Control System

We propose a method to control the motion of a robotic arm in real-time by using Kinect sensors to identify, track and simulate the motion of a human arm. This method uses Kinect’s 3D skeleton tracking technology to obtain joint data and controls the motion of the robot arm after processing the data. The biggest attempt of this research is to apply the spatial 3D shear transformation to the actual manipulator control, hoping to correct the arm data of different heights, arm lengths, and arm swing amplitudes into a unified operation unit space, and to limit the position of robot arm through the joint angle. In addition, by adding two-hand gesture recognition conditions to assist control, increase control functions as much as possible, and improve the control system. In this way, the cost of relying on external equipment in the traditional manipulator control scheme is reduced, which also proves the feasibility of such a method.
The application of blockchain technology in E-government in India using additive ratio assessment system ARAS method

In order to compile all pertinent research on Blockchain technology, we carried out a methodical mapping investigation for this study.Our goal is to comprehend the present research areas, challenges, and future directions in relation to Blockchain technology from a technical standpoint.Even though many of the recommended remedies haven't had their effectiveness empirically demonstrated, the majority of the studies concentrate on uncovering and resolving Bitcoin protocol privacy and security vulnerabilities.Many further scaling-related issues, including as throughput and latency, remain unresearched.It's one of the first scientific, participant papers that offers a thorough analysis of blockchain programmed and initiatives in the energy sector, far as we are aware.To create a map of the promise and feasibility of blockchain systems in the energy industry, our study uses their data to analyse 140 bitcoin research studies and start-up firms.They typically use various measurement units and take a different approach to optimization.The normalization seeks to produce ranges of criteria values that are similar.In this study, a brandnew "Additive Ratio Assessment (ARAS)" technique is presented.An actual case study of the evaluation of the microenvironment in offices is offered to show the ARAS method as it is stated.The case study seeks to ascertain the internal environment of the workplace and to specify the actions that need be made to enhance it.The alternatives are Consensus determination, read permission, Immutability, Efficiency, Centralized and Consensus process.The evaluation parameters are Public blockchain, Consortium blockchain and Private blockchain.Block chain technology for Additive Ratio Assessment method.Immutability is got the first rank whereas Read permission is got lowest value of rank.
Hybrid approaches to Product Recommendation Using DEMATEL Method

product recommendation.This has expanded the interest for reference frameworks like never before.Recommender frameworks are data separating frameworks that arrangement with the issue of data over-burden by sifting key snippets of data from progressively created data in light of a client's inclinations, interest, or noticed conduct about a thing.A suggestion framework can foresee regardless of whether a specific client will like an item founded on the client's profile.We propose a bound together item implanted portrayal improved for the undertaking of recovery based item suggestion.To this end, we acquaint another way with consolidate methodology explicit item embedding into a composite item inserting to improve both literary portrayals and pictures and item satisfied data, for example, item composite sifting signal.By presenting a combination step toward the finish of our engineering, we can prepare every technique independently, permitting us to have a measured design that is positive in certifiable suggestion organizations.The DEMATEL method is for creating the model A configuration panel of knowledge and subsystems Causal relationship, thru the causal diagram Visualize This is a powerful technique.DEMATEL or our changed DEMATEL The default preliminary direct-touch matrix to be checked.Each column of the matrix If the amount is less than one, DEMATEL Apply.Products, Users, Blips, Distinct tags, Total tags.From the result it is seen that Products is got the first rank where as is the Distinct tags is having the lowest rank.As a result, Products ranked first, while Distinct tags ranked lowest.
Developing Special Product Development Models

This development research aims to develop a customized product development model with a content structure: Model Name, Framework, and Procedure (explanation of steps in the Framework). This Development Research uses a Design-Based Research Model with the steps: 1. Identification of Problems and Needs, 2. Identification of Goals, 3. Artifact Design and Development, 4. Artifact Test, 5. Artifact Test Evaluation, 6. Artifact Communication. Data were collected through interviews and questionnaires and were processed using descriptive statistics. Development Research succeeded in developing a custom product development model (Customized) which was later named the Collaborative Model, along with a Framework and Explanation of Research and Development Procedures to be carried out. Collaborative Model: Customized Product Development Model was developed only from the identification of problems and needs of a special product development model for the academic community of one university in Malang. It is suggested to the next researcher to develop a development model for specific products that begins with identifying the problems and needs of academics from many tertiary institutions. Collaborative Model: Customized Product Development Model is used by experimenters to conduct research and development. The pilots stated that the model was very effective. Collaborative Model: Customized Product Development Model will be very useful, considering that there is no similar model in Indonesia that is easy to understand and speaks Indonesian.
Design and Develop Forensic Application on Client Server Network

Client server networks allow for creating efficiency and effectiveness in doing activity with teamwork, such as sharing resources. Improving technological development goes hand in hand with increasing crime rates caused by technology. Crimes that use technology still leave a trace that can be traced so that it can be paralleled with digital forensics. Digital forensics are usually done one by one per computer and cause it to take longer time to get evidence in criminal act. Looking at the problem, this study discusses the design of forensic applications on client server networks with live forensic methods and socket programming to perform forensics at the same time. Applications use Java sockets to establish a connection between the server and the client and the elevator method. The result of this study is server can collect data, like data of RAM, captured image, and snapshot disk from clients
Problems of Writing Teaching in University

In the process of learning English as a foreign language in Indonesia, it is still a scourge for most students in Indonesia. This study aims to determine the difficulties of students in the process of learning English. It is hoped that the results of this study will be useful for English teachers to find solutions to deal with the difficulties experienced by English learners. The method used is a literature review of various valid references in the form of books and articles published in various national and international scientific journals. Based on the results of the review conducted there were many problems or obstacles faced by students in writing courses where these obstacles were caused by various existing factors.