Reviewerly/exHarmony huggingface dataset:
Simultaneous Mapping Localization and Path Planning for UAV Swarm

The ability to control a swarm of Unmanned Aerial Vehicle (UAV) with minimal human intervention open new areas for autonomous UAV and drone applications. These applications include collaborative crop monitoring, aerial transportation, offshore delivery, facility monitoring, disaster relieve as well as search and rescue. Current UAV operations are heavily dependent on human operators that require each UAV to be controlled by dedicated safety pilot as well as a separate payload operator which limits the efficient use of UAVs required in envisaged swarm applications. Thus, there is an imperative to mature high autonomy guidance and navigation technologies to allow UAV swarm operations. This paper explores UAV swarm navigation and control strategies that allow higher levels of autonomy for a reliable UAV swarm operation. This paper presented the novel strategies developed in performing simultaneous swarm mapping, swarm search, and swarm path planning. The methods developed can be easily scaled up or down to adapt to different number of UAVs in a swarm for any application. The developed strategies are implemented and tested with Monte-Carlo simulations for a search and rescue type mission. The results from these simulation experiments have shown comparable achievements on the performance and robustness when compared to optimal control strategy.
Extended Abstract of Graph4Web: A Relation-Aware Graph Attention Network for Web Service Classification

Software reuse, as a means to develop new software products with similar functions by virtue of existing software components, has become a popular way during the software development process. In particular, as the service-oriented architecture became popular, web services turned into an indispensable part in modem software development Web services provide a basic composition with high cohesion and loose coupling to support responses among heterogeneous software components, which is the valuable resources for software reuse. The popular web service repositories, such as Programmable Web, contain a mass of web services for beginners and developers to choose from. Nevertheless, the large number of web services also makes it difficult to select the suitable services. Thus, the key to reuse software components lies in how to find appropriate web services from repositories to meet developers requirements in specific application scenarios.
Face Invariant Classification and Detection of Mythology Characters Using Custom Dataset (ClaDeMuC-CD)

Innovation and learning are bound together. The digital space has evolved greatly with the innovations and new state-of-art-technologies where all domains adopt this dynamic change to explore and deliver to the people in many ways. A great interest thrived in us to explore the digital evolution in Indian mythologies. The basic notion is to connect the people with the mythological stories and to make it more innovative and creative to create a better and smarter world with manifold technologies available now. To give life to the stories, a few characters exist and people remember them forever a decade. Nowadays, it appears to be a challenging task for the youth to be aware of various mythological stories and the characters involved in those stories. The ignorance level of this kind of story seems to be more and it might not fascinate in the near future. Hence, to educate and create awareness about the mythological characters, the need for a learning model is required. The objective of this work is to deploy various models to do classification and detect Mahabharata characters like Arjun, Bheem, Karan, Krishna, etc. Moreover, experimental analysis has been done on state-of-the-art models like traditional Resnet50 and detection models like yolov5. Performance metrics such as training accuracies, validation accuracies, and then test accuracies are examined.
Machine Learning Algorithms for URLs Classification

Phishing is a technique used to collect sensitive data from a user (password or credit card information) for future misuse by posing as a trustworthy source. It often takes advantage of the user’s gullibility in ways that the user will not detect at first look, and in the worst-case scenario, the attacker maintains the user’s data without the user’s awareness. Typically, the URL is the first and simplest piece of information we know about a website. As a result, it is logical to design algorithms for distinguishing harmful from benign URLs. Additionally, accessing and downloading the website’s material may be time-consuming and involves the danger of downloading potentially hazardous information. Machine Learning techniques are used to train a model on a collection of URLs specified as a set of characteristics and then predict and categorize the URLs as benign or dangerous. This technology enables us to identify and avoid possibly dangerous URLs shortly.
Conclusions and Future Work

Abstract Hypergraph computation has attracted much attention and shown apparent advantages in many application fields, such as computer vision, social networks, and biomedicine. In this book, we systematically introduce the basic knowledge, algorithms, and applications of hypergraph computation in three parts and discuss some recent progress in this direction.
THE NIGHT PATROLLING ROBOT

The greatest issue today in many parts of the world is the safety of women.Both men and women continue to be afraid of isolated regions.In light of this, we now suggest a Raspberry PI-powered security patrolling robot.To protect any location, the system mounts cameras and microphones on a robotic vehicle.The robotic vehicle travels along a predetermined path and has sensors for sound and cameras.When patrolling, it employs a predetermined line to guide its path.If the sound is heard, it stops at specific locations and carries on to the following locations.To patrol designated areas, the system uses an IR-based path-following technology.Using a combination of two HD cameras, it watches each region to find any issues.On-site sound can be monitored by it.When the surroundings are calm and the robot detects any sound, it begins to follow a predetermined course in the direction of the sound.Then, it uses its camera to scan the environment for any signs of human faces The photographs of the scenario are quickly captured and sent to the IoT website.The IoT gecko is used in this case to receive transferred photos and display them to the user together with alert sounds.So, to secure the facility, we propose an autonomous security robot that works nonstop and covers enormous regions by itself.Robotic night patrols have the advantage of being able to operate continuously without stopping or becoming fatigued.They may also go across hazardous terrain and bad weather while being constantly watched.
48P An AI System for accurate Ki-67 IHC assessment in breast cancer following the IKWG whole section global scoring protocol

Assessment of immunohistochemical (IHC) Ki-67 expression plays a crucial role in breast cancer diagnostics for many therapy decisions. The International Ki-67 in Breast Cancer Working Group (IKWG) has recently proposed a new global scoring method on whole tissue sections to improve accuracy, involving assessment of up to four representative tumor areas with negligible, low, medium and strong proliferation levels. As precise manual assessment is time-consuming, artificial intelligence (AI) support is necessary to make this method practicable for clinical routine. We developed an AI software for automated Ki-67 scoring according to the IKWG protocol. Seven pathologists assessed Ki-67 IHC status in 2 x 214 readings of whole-slide images (WSI) derived from 72 breast cancer specimens, four scanning hardware types and two clones. Pathologists selected representative areas manually, scored them with assistance of a CE-cleared AI software for region-of-interest (ROI) analysis and concluded global scores (weighted/unweighted). After a 2-week washout period, the same pathologists were presented with the same slides together with results by a fully automatic AI (AI-only): 1) selection of regions, 2) score and weight per region, and 3) two global scores (weighted/unweighted). Being able to adjust the AI-suggested results, pathologists concluded the two global scores (AI+path). For weighted global scoring, interrater-agreements between a) pathologist and AI+path, b) pathologist and AI-only, and c) AI-only and AI+path were 93.9%, 92.5%, and 96.7%, respectively (for unweighted scores, 91.1%/92.1%/96.3%). With AI-assistance, pathologists scored significantly faster compared to manual scoring (median time per WSI: 229 vs. 306 sec). Used as a diagnostics assistance tool, the presented AI system showed high agreement with pathologist scores, while reducing assessment time. Likewise, also fully automatic AI use showed high agreement with human scoring. Overall, this demonstrates that the investigated AI system is suitable to enable safe implementation of the global scoring protocol in clinical routine, ultimately leading to higher accuracy and reproducibility in Ki-67 IHC scoring.
BUILDING A JOB PORTAL USING WEB SCRAPPING

Job portals are online platforms that facilitate the matching of job seekers with potential employers.Web scraping, which involves extracting data from websites, is commonly used to gather information from job portals to gain insights into the current job market.Through web scraping of job portals, software tools or bots can extract data such as job titles, industries, required skills, and locations of job vacancies.This information can be analyzed to provide valuable insights into the job market, including the most in-demand skills, industries that are hiring the most, and the regions with the most job opportunities.Web scraping of job portals can also provide job seekers with useful information about job titles and roles offered by recruiters, along with the skills required for a particular job.This information can help job seekers to better understand the job market and the skills they need to acquire to increase their employability.For instance, if web scraping reveals that programming skills are in high demand, a job seeker can take courses to improve their programming skills and increase their chances of getting a job in the IT industry.However, it is important to note that web scraping of job portals can be unethical and illegal if done without permission from the job portal or in violation of the portal's terms of service.Some job portals may prohibit data scraping, and any attempt to scrape data from these portals may lead to legal action.Therefore, it is crucial to conduct web scraping of job portals in a responsible and ethical manner, ensuring that any data extraction is done with appropriate permissions and within legal boundaries.
HAND GESTURE RECOGNITION FOR DEAF AND DUMP USING CNN TECHNIQUES

Sign language is a type of communication used by people with hearing and speech impairments.Disabled People utilise these sign language gestures as a form of non-verbal communication to convey their own feelings and ideas to other regular people.It can be quite difficult to communicate with persons who have hearing loss.Since Deaf and Mute persons communicate via hand gestures, normal people have difficulty understanding the signs they make.Systems that can identify various indications and provide information to common people are therefore necessary.However, these common people find it difficult to interpret their expression, thus qualified sign language experts are required during medical and legal appointments, as well as educational and training sessions.The demand for these services has grown during the previous few years.Other types of services have been established, such as video remote human interpretation using a high-speed Internet connection.These services offer a simple sign language interpretation service that can be used and is beneficial, but has significant drawbacks.We can employ artificial intelligence technology to examine the user's hand with finger detection in order to solve this issue.We may construct the vision-based system in real-time situations using the proposed technology.Convolutional neural network algorithm, a deep learning method, is then used to classify the sign and provide a label regarding recognised sign.
A fracturing practice

With a background in jewellery and the craft of stone cutting, I am interested in understanding how materials and landscapes are cut, fractured, and broken up and how the fragmentation and reconstruction of the landscape is intimately connected with human skills, techniques, craft, and technologies. Within my practice I explore the idea that matter, rather than being an inert object, is sensitive, embedded in aliveness.
YOLOv4 and branch attention: An improved approach to real-time object detection

We propose a new enhanced YOLOv4-based model that outperforms the accuracy of YOLOv4 without considerably compromising its speed. We study the implementation of Selective Kernel attention mechanism and make extensive experiments to reliably optimize it. We explore several optimization techniques, mainly grouped, depth-wise separable and dilated convolution. We introduce selective kernel convolution in CSPdarknet53 which is based on multiple branches with different kernel sizes. Our implementation allows the neurons to dynamically adjust their receptive fields. This version of YOLOv4 enables the network to adaptively choose the appropriate kernel size according to the input. Experiments show that our model improved YOLOv4 by 1.8% with a negligible increase in inference time. We were also able to decrease the GFLOPs and parameters of YOLOv4 making the training process more efficient. Our model achieves 80.2% accuracy on the dataset Pascal VOC at a real time speed of 64 FPS on a single Tesla P100 GPU.
Traffic sign recognition for controlling intelligent vehicle

Deep learning is a subfield of artificial intelligence that has emerged this recent years with several applications. We are particularly interested in using convolutional neural networks for traffic sign images classification. Our traning framework is based on the AlexNet pre-trained model. To improve its prediction accuracy we use fine tuning techniques. The generated prediction model is then interfaced with a mobile robot equipped with a Raspberry Pi hardware board and a camera. Test environment shows how well robot system takes naviguation decisions based on the classification pre-trained model.
3D Image Segmentation For Lung Cancer Using U-Net Architecture

Segmentation of pulmonary cancer is the big ambiguity of medical staff in their diagnostic, we will present our U-NET algorithm in this paper. The general idea is to create an optimal segmentation that allowed the medical staff to distinct the different parts of the tumor using the U-Net architecture which represent the more elegant architecture, called a fully convolution network. The main idea is to complete a contracting network by successive layers; pooling operations are replaced by over sampling operators. So, the resolution of the output is increased by these layers. To obtain the best result of the performance from the different data merged we choose the technique of 3D-UNET architecture. To elicit the optimal and best quality result of the segmented images, we choose this technique that allowed merging the different data source. The experimental results of the segmentation are approved by using U-NET for image segmentation.
Education Policy of the Second Republic and the Role of Auh Chun Suk

오천석(天園吳天錫, 1901-1987)은 제2공화국 시기 문교부 장관의 직위에 있으면서 다양한 교육정책을 검토하고 실천하였다. 교육의 민주화 정책과 교육의 질적 향상 정책으로 나누어 제2공화국 시기의 오천석의 역할을 정리하면 다음과 같다. 첫째, 교육의 민주화 정책에서의 오천석의 역할은 교육행정의 민주화와 지방분권, 교육 기회의 평등, 교원노조 등의 이슈 대응에서 찾을 수 있다. 중앙교육위원회를 통해서 다양한 법안의 제출동의를 받았으며, 교육의 행정권 일부를 지방으로 이양하였고, 교육자치제에 기초한 지방분권을 적극적으로 추진하였다. 교육의 기회 평등을 위해 국민학교 시설 등의 확대를 추진하였고, 부정입학 문제에 단호히 대응하였으며, 학제의 변경은 추진하지 않았다. 교원노동조합 운동에 대해서는 쟁의권을 부여하지 않는 범위에서 허용하는 것을 원칙으로 하였으며, 학생시위를 강경하게 다루지 않는 모습을 보이기도 했다. 둘째, 교육의 질적 향상 정책에서의 오천석의 역할은 교육의 기초를 강화하기 위해 다양한 법과 제도의 실천, 교육과정개편 노력, 교육 수준을 향상하기 위한 교육대학 설치, 향토학교 운동 등에서 찾을 수 있다. 「교육세법」은 일반국민의 세금 징수를 완화하는 방향으로 개정되었고, 「국립학교설치령」에서 초등교육의 전문성을 확보하려 하였으며, 「대여장학금」법에서는 통해 학생들의 경제적 사정을 고려했다. 교육과정 개편은 「교육과정심의회규정」을 제정․시행하는 것까지 진전시킨다. 교육 수준을 향상하기 위한 정책으로 교육대학 설치를 추진하고, 향토학교를 구상하였으며, 대학 교육의 발전을 위해 외국의 원조 확약을 받기도 하였다. 셋째, 제2공화국 시기 오천석이 추진하였던 교육정책의 일부는 과도정부 시기 이병도 장관의 정책을 계승한 것이 있었으며, 새롭게 추진했던 교육정책도 윤택중 장관 시기를 거쳐 5․16군사정변 이후에도 일부는 계승되었다고 볼 수 있다. 중앙교육위원회, 학교시설확충 등을 통한 의무교육완성 등은 이병도 장관 시기의 정책을 계승한 것이며, 의무교육완성 계획, 교육대학 설치, 향토학교 운동 등은 5․16군사정변 이후에도 계승되었다. 교육 민주화를 위한 교육행정권 지방이양, 교육자치제도는 5․16군사정변 이후에 폐지되었으며, 교원노조운동은 불인정되었다.The role of Auh Chun Suk in the education policy of the Second Republic is as follows. First, Auh Chun Suk received consent to submit various bills through the Central Board of Education. Part of the administrative power of education was transferred to the provinces. Decentralization based on the educational autonomy system was promoted. For equal opportunities for education, he promoted the expansion of facilities such as elementary schools and firmly responded to the problem of illegal admission. The teachers' union movement was allowed to the extent that it did not grant the right to dispute, and student demonstrations were not dealt with strongly. Second, the Education Tax Act was revised to ease tax collection for the general public. The National School Establishment Act tried to secure the expertise of elementary education. The reorganization of the curriculum has progressed to enact regulations of the Curriculum Council. The establishment of an educational university was promoted, and a community school was conceived. Third, the completion of compulsory education through the expansion of school facilities and the Central Board of Education inherited the policies of the previous period. The plan to complete compulsory education, the establishment of an educational university, and the community school movement were inherited even after the 5.16 military coup. The transfer of educational administrative power to local governments for educational democratization, the educational autonomy system was abolished after the 5.16 military coup, and the teachers' union movement was rejected.
Fitch-Style Modal Necessity as a Substructural Sequent-Style System

The question of defining a Jaskowski-Fitch natural deduction system for modal logic has been settled since the very introduction of such formalisms in the middle of the last century. In contrast, a sequent-style formulation of this approach has only been discussed since the turn of this century but exclusively from the point of view of type theories. In this paper we propose a substructural sequent-style deductive system, based on previous ideas by Borghuis and Clouston, which captures Fitch-style for modal logic in a faithful way, meaning that the features of the original diagrammatic proofs are enforced by the sequent rules. This answers the question of what is a sequent-style version of Fitch-style natural deduction in the case of the necessity fragment of minimal modal logic S4.
Specifying and Verifying a Transformation of Recursive Functions into Tail-Recursive Functions

It is well known that some recursive functions admit a tail recursive counterpart which have a more efficient time-complexity behavior. This paper presents a formal specification and verification of such process. A monoid is used to generate a recursive function and its tail-recursive counterpart. Also, the monoid properties are used to prove extensional equality of both functions. In order to achieve this goal, the Agda programming language and proof assistant is used to generate a parametrized module with a monoid, via dependent types. This technique is exemplified with the length, reverse, and indices functions over lists.
Development of Traveling Friends Search Service Through Mobile Application “Destinasi”

Traveling is a moving activity with the aim of recreation.The purposes of traveling are usually to relax, explore, discover or learn at someplace.A solo traveler is someone who enjoys traveling alone, while a group traveler is someone who travels together with other fellow travelers.When people want to travel together but do not have a partner to go to, a travel agency is often an option to get a traveling partner.For some people, a travel agency is inflexible, making the trip unenjoyable.Moreover, the fees charged to agents and tour guides are not ideal for backpackers with a low budget.This research aims to develop an application-based traveling companion search service called "Destinasi".The research method is carried out by distributing questionnaires to the traveler communities in Indonesia using Google Forms to find out how the traveler's interest is in developing application-based services.All the responses will be contributed as the input for the application features.The results show that some of the essential application features for Indonesian travelers are a tour guide, information on traveling places, sharing stories, ratings, selection of partners based on gender, chat, news, nature lovers, and mystical tours.
Application of Big Data for Students’ Behavior Prediction in Education Industry

Big data is a highly innovative technology that provides economic and social benefits for all segments of society.Big data analysis offers significant savings and new possibilities by moving the decision support of many critical areas of knowledge to an upper dimension in many different industries such as banks, energy companies, the pharmaceutical industry, health services, public services, etc.Even though there are few studies about big data applications in education, big data will revolutionize the learning industry in the coming years.Therefore, this study deals with big data applications in the education sector, especially in predicting student behavior.This paper investigated the existing literature for big data usage for predicting students' behavior in the education industry.Then it proposed a specific methodology for determining students who are likely to drop out early from the university.Because the increasing graduation rate is the strategic goal of any public or private educational institution, it is believed that with the proposed model, they can take the right action at the right time to reduce the drop-out rate and increase the graduation rate.