Reviewerly/exHarmony huggingface dataset:
Image recognition based on improved LSTM deep neural network

As the application of electronic equipment in people&apos;s production and life is becoming more and more common, digital images have become an indispensable means of information, and massive amounts of image data are being generated every moment. Image recognition is a very important research field in the field of computer vision, and the accurate recognition of objects in images is becoming more and more valuable. The purpose of this paper is to study deep neural network image recognition based on an improved LSTM. The five methods and steps of image recognition, the classification of convolutional neural networks on event images, the method based on LSTM subdivision and the existing event image classification methods are introduced. The experimental part introduces the parameter settings, and gives each visual the experimental results and analysis under the characteristics. Through the comparison of classification accuracy, after LSTM network processing, the event with the highest accuracy rate is 98%, which proves the superiority of the network structure constructed in this paper in the problem of event image recognition, and the classification performance has been improved to a certain extent.
Boundary Value Analysis Techniques for Testing Geographic Information System Applications for Public Facilities

The Geographic Information System for Public Facilities is a system that makes it easier for the public to search and find locations. The more people use this system, the more problems will arise. Because people still use the manual method, namely by asking about the location of public facilities in the surrounding community. This is very ineffective and accurate. Therefore, a public facility information system was built using CI 3, Java, and PHP in the form of android. The method used in this development system is the waterfall method. With this GIS, the public can search for the location of public facilities, find public facilities, and provide a route to the location using the Tracking process to find out where the current position is.
Predicting the Employment Destinations of University Students Based on Machine Learning Algorithms

The research on the classification prediction of students' employment destinations in higher education not only opens up new application areas for classification algorithms, but also represents a new attempt to introduce machine learning algorithms into the analysis of employment guidance and the development of teaching systems.The purpose of this paper is to study the employment destination prediction of college students based on machine learning algorithms.The factors influencing the employability of university students are analysed and the XGBoost model in decision trees is explored.A graduate employment prediction algorithm based on HMIGW feature selection and XGBoost algorithm is proposed to predict the employment situation of the class of 2022 and the type of employment, and the experimental results show that the algorithm is able to obtain relatively accurate conclusions on graduate employment prediction.
Handwritten Character Recognition through Feature Extraction using Artificial Neural Networks

Today’s computer can be fast, accurate and knowledgeable. But they are far from being intelligent; computers are still unable to communicate with human beings in natural forms like written languages, speeches, pictures and images. With the rapid development in the computer facilities users have now turned their attention to interact with computers in their local languages, so it is more user friendly. In Karnataka, HINDI is the local and official language. it is very convenient and faster to enter a HINDI document into computer by handwriting rather than by typing using existing HINDI converted English keyboard, where key combinations have to be used. This necessitates the development of an efficient online system to recognize HINDI handwritten characters or words. The concept in the online character recognition system is to capture a character as a sequence of [x(t),y(t)] points while the character is being written on a computer screen. Trajectory curvature, shape, size etc., are extracted from the characters. Each point of the input sequence is coded as a set of these features for recognition.
Text to Speech Converter Using Python

In this paper, an innovative, efficient, and cost-effective technique was presented that allows users to hear the content of text images instead of reading them. This type of system helps visually impaired people to interact effectively with computers through a speech interface. Extracting text from color images is a challenging task in computer vision. Text-to-speech conversion is a method that scans and reads aloud English letters and numbers. Reading scientific literature is essential for researchers and clinicians. With the overabundance of medical and dental journals, it is important to develop a method to select and read the correct articles. This article describes the design, implementation, and experimental results of the device.
Keyword selection on Google Ads

Google Advertising is a publicity agency that provides marketers with advertisements. By choosing keywords relevant to their ad material, advertisers fit the user's search terms and push advertising. Keywords will decide the type of users being pushed by an advertiser, the efficacy of the ad promotion, and therefore the ad product's sales. The main objective is to automatically choosing keywords that are satisfactory to advertisers from an outsized number of keywords given by Google Advertising. But there’s not an excessive amount of time for the framework to make a decision whether keywords are chosen and to pick the proper keywords within the shortest time. Therefore, a model structure which can obtain some helpful keywords for advertisers is built also to accomplish this multipurpose task, an enhanced method of multi-objective particle swarm optimization is introduced. Many technical challenges need to be solved to accomplish this multi-objective mission, such as the issue of mixed language, the problem of data imbalance, the issue of obtaining features from the collection, and so on. The mixture of evolutionary computation, deep learning, machine learning and text processing approaches is used here to solve the issue of keyword selection.
Dialog modeling of domain specific cognitive assistants

Intelligent virtual assistants of software are becoming more common. Frequently, the communication interface is dialogue which is expressed in natural language. When an assistant consists of questions that are associated with a single answer, the abstraction of the dialogue is straightforward, however, when there are conversations with multiple bifurcations in the flow of communication, the representation and documentation is complex. In this sense, there is a lack of formalities that allow a dialogue to be accurately represented and based on them, to proceed with its programming in an industrial framework. In this work we propose the use of finite state machines to model complex dialogues. Thus, we introduce a formal model for the representation of dialogue and its mapping to a real assistant, using an industrial framework. We believe that our approach will make it easier to design and to program assistants with complex interaction, enabling better adoption of them.
Multi-camera Moving Object Detection Based on Improved ORB Feature Matching

Collaborative object detection by multiple cameras can make up for the limitation of insufficient field of view of a single camera, and through the rich information obtained from multiple perspectives, object detection and other tasks can be better completed. For the sake of detect moving object in multiple cameras in real time and accurately, a moving object detection algorithm based on improved ORB feature matching was proposed. In the first place, the ORB algorithm was used to extract and describe the feature points. Then, in order to improve the accuracy of feature matching, BF and grid-based motion statistics were combined to eliminate the wrong matching pairs. Finally, through time synchronization of multiple cameras, the matching results of each camera were selected to obtain the final detection results. Experimental results show that this algorithm apart from maintains the superiority of ORB itself, it also improves the detection accuracy of the improved feature matching algorithm, which can accurately detect the moving object between multiple cameras in real time.
DOMINO: Domain-aware loss for deep learning calibration

Deep learning has achieved the state-of-the-art performance across medical imaging tasks; however, model calibration is often not considered. Uncalibrated models are potentially dangerous in high-risk applications since the user does not know when they will fail. Therefore, this paper proposes a novel domain-aware loss function to calibrate deep learning models. The proposed loss function applies a class-wise penalty based on the similarity between classes within a given target domain. Thus, the approach improves the calibration while also ensuring that the model makes less risky errors even when incorrect. The code for this software is available at https://github.com/lab-smile/DOMINO.
Estimation of Blast-resistant Buildings Using Weight Product Method

This research is architectural space in blast-resistant buildings Aims to determine status and its effective indicators. Explosion-proof structures are necessary to protect personnel from construction hazards created when personnel work in potentially explosive areas. Blast-proof buildings usually precast cast-in-place concrete or Constructed of steel frosted steel frames are permanent structures. Suitable types of window glass and provides specific recommendations on contraindications. Incorporating blast-resistant glazing into its framing and It mentions the considerations involved in linking. Most notably, laminated glass and made of laminated glass Based on traditional window glass design methods for insulating glass Authors relatively to simplify the design of explosion-resistant glazing them offer a simple approach. Weighted Production Method (WPM) is less important than TOPSIS method and a more stringent method for penalizing computationally cheaper alternatives. It is dimensionless and the rank abnormality problem is not applicable to WPM. Option code of each alternative independent of other alternatives, More acceptable One can set the limit for the option code. Hence, for dynamic decision-making situations we recommend WPM as a better alternative than TOPSIS. Blast resistant building is alternatives are reconstruction capability (C1), implementation costs (C2), access to material supply (C3), maintenance costs (C4), environmental footprint (C5) and reduction of energy loss (C6). Evaluation Parameter is Brick Façade (A1), Stone Façade (A2), Coatings Cement Façade (A3) and Composite Façade (A4). In this type of analysis, WPM methods determine for the best solution to settlement, As a result, access to material supply (C3) is got the first rank whereas is reconstruction capability (C1) is having the lowest rank.
SPNet: Utilizing Subspace Projection to Achieve Feature Interaction for Click-Through Rate

Click-through rate prediction is critical to online advertising services, wherein feature interaction is fundamental. There exist a number of schemes studying feature interaction, including factorization machine, xDeepFM, and other deep learning based models. Nevertheless, multiple features in one layer are not able to interact with each other or can not interact effectively. To resolve this problem, we propose a novel Subspace Projection Network (SPNet) in this paper. SPNet leverages subspace projection to make all features interact with each other in one subspace. Different subspaces employ different approaches to interact features in one layer. By stacking multiple layers, complex feature interactions can be implemented. To verify effectiveness of SPNet, we conduct experiments on two large-scale datasets. Experimental results demonstrate that SPNet not only outperforms the state-of-the-art shallow models, but also surpasses most deep learning based schemes.
Moving Toward Self-Sovereign Identity

Self-sovereign identity (SSID) is a digital solution intended to ameliorate the drawbacks associated with existing digital identification management approaches. This chapter begins with an overview of identity management systems. It explores the essential elements of SSID, including verifiable credentials, distributed ledger technology (DLT), and privacy engineering protocols, and highlights research initiatives, governmental projects, and regulatory frameworks that leverage evolving technologies to improve data integrity, efficiency, and security. The authors survey key challenges and advantages associated with SSID, establishing a taxonomy of the SSID model and a summary of privacy engineering techniques that work in concert with SSID, including zero knowledge proofs (ZKPs) and bring your own identity (BYOI) systems. The authors highlight several innovators in the SSID ecosystem that are contributing to the growth and maturity of this model.
ANALISIS SISTEM INFORMASI KEBERHASILAN WEBSITE SIAP PPDB ONLINE DINAS PENDIDIKAN PROVINSI JAMBI DENGAN METODE DELONE AND MCLEAN

The PPDB ONLINE website is one of the applications of information technology that is used to make it easier for users to obtain information related to New Student Admission (PPDB), with services provided by the Jambi Provincial Education Office. The researcher analyzes the success rate of the PPDB ONLINE website in Jambi Provincial Education Office using the Delone and Mclean methods and finds out the effect of the independent variables (quality of the system, quality of information, quality of services provided) on the dependent variable (usage, user satisfaction, net benefits) using the SEM method. and SmartPLS software. This study resulted in 6 accepted hypotheses from 9 proposed.
Control Applications Using Reinforcement Learning: An Overview

This article presents the general formulation and terminology of reinforcement learning (RL) from the perspective of Bellman’s equations based on a reward function, its learning methods and algorithms. The important key in RL is the calculation of value-state and value state-action functions, useful to find, compare and improve policies for learning agent through different methods based on values and policies such as Q-learning. The deep deterministic policy gradient (DDPG) learning algorithm based on an actor-critic structure is also described as one of the ways of training the RL agent. RL algorithms can be used to design closed loop controllers. Through simulation, using the DDPG algorithm, an example of the application of the inverted pendulum is proposed in simulation, demonstrating that the training is carried out in a reasonable time, showing the role and importance of RL algorithms, like tools that combined with control can address this type of problems.
Handwritten Chinese Signature Detection on Scanned Technical Documents for Authenticity Verification

Signature detection is one of the crucial predecessor procedures to prove the authenticity of handwritten signatures. Despite the increasing demand for automatedly verifying the signatures on contracts, bills, reports, etc., the research based on signature detection is very limited. One of the impediments to signature detection is the lack of public annotated datasets due to the interests of privacy and confidentiality. In this paper, we explore a data augmentation method, the Copy-Paste augmentation, to alleviate the scarcity of signed documents. Modeling signature detection as an object detection task, we experiment on Chinese technical documents using different object detection models. The experiment shows that YOLOv5 with Copy-Paste augmentation performs best. Based on the experiment, we propose a prototype system for signature detection.
Ecological Element in Oral Literature Wayang Jek Dong Malang Style

Literature as part of the representation of human life is always tied to human culture nd environment. The problems raised by writers in literary works are part of the relity that occurs in the environment where they live. No exception with oral literature. As a traditional literary genre, oral literature has a depedence on ecological elements that exist in the universe. Plants an animals, for example, have a role in the literary context as part of the universe. Plants and animals, for example, have a role in the literary context as part of the puppetry element of the wayang Jek Dong Malang style. Oral literature contained in pupetry jek dong malangan style, for example, in practice by the puppeteer always involves ecological elements. Through the study of an ecocritical perspective, it can be seen that the presence of oral literture in Malangan style jek dong puppetry is always thick in the image of nature such as Pandawa Tani, Wader Bang Sisik Kencana, Wedus Putih Ngamen, and so on. The involvement of thes ecological elements shows a strong image of the nature, and culture of the Malang people.
Multilingual Signs: The Linguistic Landscape in Nusa Dua Tourist Area, Bali

This research aimed at finding out and describing the profile of linguistic lanscape, namely the languages used in the informational signs in Nusa Dua, Bali tourist destination. These signs can include information boards, warning boards, prohibition board, and boards for the name of hotels, buildings, restaurants, food courts, spa, shopping center and hospital. This research was a qualiatative in nature through describing the languages used in the tourist destination. The data was obtained by means of handphone camera, and about 116 visual pictures were collected. The results showed that there are 8 (eight) variations in the use of languages in the linguistic landscape in Nusa Dua, Bali tourist destination. The eight variations were: 1) Indonesian 2). English, 3). bilingual Indonesian and English, 4). bilingual English and Indonesian, 5). bilingual Balinese and English, 6). multilingual Balinese, Indonesian and English, 7). multilingual Japanese, English, Chinese and Korean, and 9) multilingual Balinese, English, Japanese, Chinese. Russian, Hindi, Jerman, Korean, Indonesia and French
Needle-size fibre endoscope with 3D printed DOEs for minimally invasive procedures in biomedicine

Endoscopes with 3D imaging have been known for some time. Additional information about the depth allows further statements during the examination and better visualisation. However, the measuring heads of such endoscopes are bulky, since they must accommodate optics that enable axial scanning. Hence, the field of application remains very limited. We present an endoscope without optics on the distal end and a significantly smaller measuring head in the sub-millimetre range. This enables endoscope technology to be used in new areas of surgery, such as in brain or cochlea. Conventional endoscopes are too large for these regions. A static phase correction has been demonstrated to be sufficient to maintain phase information. Hence, programmable optics like spatial light modulators are no longer needed. Therefore, we applied 3D printed phase masks using 2-photon polymerisation. This allows a robust and cost-efficient system to be realised. In addition to the process of printing phase correction DOEs, we also present a new setup which allows the sample in front of the endoscope head to be imaged through the fibre bundle directly to a camera sensor. No raster scan is required like in past approaches. Hence, an image can be generated in a single shot without further computational reconstruction.
Analisis Kepuasan Pengguna Aplikasi Lazada Masyarakat Penajam Menggunakan Metode Pieces Framework

Lazada is one of the most popular mobile-platform-based e-commerce in Indonesia today with more than 100 million downloads. During the current COVID-19 pandemic, the Lazada application can be a very helpful application to meet user needs without having to leave the house. In this study, evaluation activities were carried out on a Lazada information system to assess whether the Lazada application used was able to meet the needs of its users, namely Lazada application users. In conducting an analysis or evaluation of a system, it is carried out with an analytical model. Data collection uses the PIECES Framework method, data calculation uses a Likert scale, and determines the average satisfaction. Based on the calculation results, it is known that the PIECES method can be seen in almost every variable getting results (PUAS).
The Discourse Structure and Linguistic Features of Research Articles and Thesis Abstracts in English by Indonesian Academics

Scholars and practitioners should be aware that writing a good and eye-catching abstract is significant but tough work. Scholars and researchers are challenged to produce an informative and persuasive abstract to be accepted then published in either national or international publication and they should know the current characteristics of abstracts written by the students or apprentice writers. The study aims at examining the comparison of discourse structure and linguistic features between English abstracts of research articles by Indonesian researchers and English abstracts of the thesis by Indonesian scholars. The corpus data were taken from 10 research articles abstracts of Indonesian researchers concerning English education published in ERIC and 10 thesis abstracts of the graduate program of English Education in UIN Syarif Hidayatullah Jakarta. Thus, a genre-based analysis proposed by Bhatia’s move structure and Swales’ and Feak’s move structure will be used to investigate the discourse structure and Paltridge starfields will be used to investigate linguistic features. The results indicated that 60% of abstracts published in the international journal were organized well while 40% of thesis abstracts were not organized well. Furthermore, past tenses were frequently used in both article abstracts and thesis abstracts in terms of aim, method, and result move. While present tense was still used in aim and result move in article abstracts. In conclusion, most abstracts published in international publications used well organizational move. While most abstracts published in local ones are not used well organizational move.Keywords: Discourse structure; linguistic features; research article abstracts; rhetorical move; thesis abstracts.