bluuebunny/crossref_metadata_2025 huggingface dataset:
Metafor yöntemiyle çalışılmış müzik makalelerindeki genel eğilim
Authors: ÜSTÜN Ayşenur , UMUZDAŞ Serpil
Published: June 2023

Güncel haliyle, metafor yöntemiyle çalışılmış 35 Türkçe müzik makalesi bulunmaktadır. Metaforla veri elde etme; başka disiplinlerde kullanılagelen bir yöntem olmasına karşın müzik alanındaki kullanımı oldukça geç olmuştur. Görüldüğü kadarıyla, Türkiye’de müzik alanında ilk çalışma 2013 yılında yapılmıştır. Yöntemin kullanımı zamanla yaygınlaşmıştır. Mevcut çalışma, müzik alanı için yeni sayılabilecek bu yöntemin kullanılış esaslarını tanıtmakta ve kullanımdaki genel eğilimi göstermektedir. Türk müzik araştırmacılarının metaforu kullanma davranışları ve durumlarının sentezini içeren bu çalışma; bu yöntemle veri toplamanın araştırması için uygun olabileceğini düşünen yeni araştırmacılara ekonomik bir yön gösterici olacaktır. İncelenen makalelerde bağlamın, fenomenolojik desen ile oluşturulduğu görülmektedir. Müzik araştırmacıları “ses, müzik, çalgı” gibi olguların hedef kitleleri tarafından nasıl algılandığını metaforlar aracılığıyla betimlemişlerdir. Çalışmalar; olgular, çalışma grupları, yıl, kapsam, işlem basamakları, yayınlandıkları dergilerin özellikleri, kullanılan kaynaklar bakımından incelenmiştir. Yapılan sentez, yıllar içinde konu ve yönteme olan eğilimin yönünü ve bu çalışmaların birbiriyle olan bağını göstermektedir.
The Utilization Of Golden Snail Shell For Domestic Liquid Waste In The Banksa Suci Cihuni
Authors: Ismi Nurlatifah  , Siti Maftukhah  , Dine Agustine
Published: June 2023

Community service in the form of domestic liquid waste treatment at Banksa Suci (Cisadane River Garbage Bank) Ciheuni is motivated by domestic wastewater flowing into the Cisadane river and passing through the Banksa Suci Ciheuni park which has been polluted with black waste water showing. The waste water comes from the area around the Banksa Suci Ciheuni park which consists of residential areas, offices and hospitals. Polluted wastewater that flows into the Cisadane river can contaminate the Cisadane river body and its ecosystem. This activity aims to purify the waste sample water so that it is in accordance with the quality standards. This community service is carried out by adding golden snail shell powder to wastewater, with a concentration of 0%, 10% and 20% then stirring and filtering, then analyzed in the laboratory. The results of the analysis show that the golden snail shell is able to reduce the turbidity of the holy banksa wastewater.
Pelatihan Pembuatan citrus Dishwash Sebagai Peluang Wirausaha Rumah Tangga di Desa Alai Selatan, Kecamatan Lembak
Authors: Lazuarni Shafiera , Putri Andini Utari , Asharie Asmawati
Published: June 2023

Pengembangan potensi desa melalui kewirausahaan merupakan salah satu bentuk upaya dalam meningkatkan kesejahteraan masyarakat desa. Kegiatan pelatihan melalui Pengabdian Kepada Masyarakat (PKM) ini bertujuan memberikan pemahaman dan meningkatkan kemampuan menciptakan wirausaha rumah tangga hingga wirausaha desa. Kegiatan ini dilaksanakan dengan mengintegrasikan kegiatan Kuliah Kerja Nyata (KKN) mahasiswa. Kegiatan ini memberikan keterampilan baru kepada peserta untuk membuat sabun cuci piring dengan menggunakan potensi alam yang banyak dijumpai di Desa Alai Selatan yaitu daun binahong, selain pembuatan sabun cuci piring peserta juga mendapatkan pemahaman mengenai pengemasan sabun cuci piring agar dapat meningkatkan nilai jual dari produk tersebut. Berdasarkan hasil evaluasi yang dilakukan peserta menganggap pelatihan ini sangat dibutuhkan oleh masyarakat desa mengingat akses dan pengetahuan untuk meningkatkan soft skill mereka selama ini sangat terbatas. Kedepannya diharapkan program pelatihan lainnya khususnya pelatihan desain grafis dapat dilaksanakan untuk menunjang keterampilan yang sudah dimiliki saat ini.
Training for English Teachers on Writing Scientific Articles and Using Mendeley as a Collaboration and Reference Tool
Authors: Fiftinova  , Erlina  , Ismail Petrus  , Muslih Hambali
Published: June 2023

Writing scientific articles is a skill that must be owned by a teacher and the usage of Mendeley technology in writing scientific articles is a supporting facility in obtaining qualified scientific papers. Therefore, the execution of training activities needs to be carried out with the purpose of enhancing the motivation, knowledge, and abilities of high school English instructors in the city of Palembang. The activity model carried out is mentoring with the lecture approach, discussion, peer and tutor feedback and assignments. Evaluation of activities is carried out by administering tests and questionnaires as well as monitoring and documenting articles produced by the teacher. The findings of the evaluation demonstrated that the enthusiasm, knowledge, and skills of teacher participants in writing scientific articles increased. However, teachers still have issues using Mendeley as a citation and collaborative tool.
Improving the Family Economy Through Education on Making Pekaor (Organic Glass Cleaner) From Waste Orange Peel, Lemongrass, Aloe Vera in Brayan Bengkel District
Authors: Fetra Venny Riza  , Sri Prafanti  , Widia Astuty  , Desi Sri Pasca Sari Sembiring
Published: June 2023

Garbage is leftover material that is no longer used, disliked, or something that must be disposed of, which generally comes from activities carried out by humans. Reducing pollutants and wastes from the environment is absolutely necessary for us to understand the relative importance of using different steps and setting up networks for continuous changes in carbon especially in the environment. Citrus fruit is one of the fruits that we often encounter in Indonesia. Approaching the orange season, we meet many vendors selling oranges on the side of the road or in other public places at affordable prices. And also not a few people are interested in buying it. But most people often throw the skin from the oranges they eat out of place. This often disturbs the beauty and cleanliness of our environment. Lemongrass is also a plant that is often used in household kitchens. Meanwhile citronella waste has good quality with a protein content of 7%, far above rice straw waste which is only 3.9%. Utilization of Citronella Waste (Cymbopogon nardus) Ammonia can also be used as another mixture. Likewise, with aloe vera skin waste, it is necessary to utilize the skin waste more optimally so that it can be utilized. Aloe vera peel waste can be utilized to become an extract that has the potential as a natural antimicrobial agent because it contains a number of secondary metabolite compounds. Today, home business is one of the most promising forms of business. Various kinds of creativity are carried out to be able to generate additional income by utilizing materials that are easy and easy to obtain by utilizing existing waste such as orange peels, lemongrass, and aloe vera. One with a lot of waste is in the Pulo Brayan Bengkel Village, located on Jl. Commission B No.10b, Pulo Brayan Bengkel Baru has a non-productive community that has a direct impact, so various programs are needed to increase productivity, including self- sufficiency in meeting the community’s economic needs and product marketing. There are problems that need to be assisted by Partners, namely a lack of knowledge and skills regarding the processing of orange peel, lemongrass, and aloe vera waste in the Brayan workshop village, the Brayan Bengkel community does not yet understand in depth about the knowledge and skills in terms of making packaging designs/brands for these products, not yet have good marketing and management techniques. To solve this problem the service team tries to help provide solutions in the form of training in processing orange peel, lemongrass, and aloe vera waste, training in making packaging designs/brands, and training in marketing techniques for the results of the Brayan Bengkel Village community.
Training on the Implementation of Storytelling Learning with the Animation Film Method for PAUD Teachers in Bontoa Maros District
Authors: Nurhayati  , Inriati Lewa  , Mulimat  , Muh. Akdan  , Indarwati
Published: June 2023

This Community Service is entitled Training on the Implementation of Storytelling Learning using the Animation Film Method for FAUD Teachers throughout the Bontoa Maros District. This topic was chosen based on the results of an interview with a teacher in Bonto Maros, South Sulawesi, that PAUD teachers in that area really need this material because they don't know what literature, children's literature, and the method of telling stories through animated films are. The importance of this material is given because so far PAUD teachers in the area still use conventional methods in teaching fairy tales. The method used in this service is training and practice. During the training, teachers were given learning materials for literature in general, children's literature, and learning methods using the animated film method. The results achieved were that PAUD teachers got the material and would apply it in class. The importance of this training for PAUD teachers throughout the Bontoa District considering that they are still using conventional methods. The teachers were satisfied and asked if it was possible to add more time to the material.
Prosecutor in the court debate of the parties in the criminal process of the Russian Empire
Authors: Gorbachev Vasily
Published: June 2023

The article analyzes the legal status and the actual role of the prosecutor in the judicial debate of the parties in the criminal process of the Russian Empire. The overall result of the consideration of the criminal case largely depends on this part of the trial. And the study of historical experience is necessary for a better understanding and solution of the problems of modern criminal procedure, which is based on many principles established by the judicial reform of 1864. The judicial debates were a manifestation of the new principle of adversarial in criminal process. In their accusatory speeches, the prosecutors often not only went beyond the established limits of the debate, but also did not comply with moral requirements in relation to defendants and defenders. In some cases, there were conflicts between prosecutors and defense lawyers in the trial, and the most gross violations of the rules of conduct by the parties of the debate led to the cancellation of the verdicts by the Governing Senate. At the initial stage after the judicial and military-judicial reforms, the prosecutors in court were correct and unbiased. However, in the 1880s, the tendency of their accusatory bias increased, mainly in political cases
The specifics of states and the harmonization of international human rights norms
Authors: Kartashkin Vladimir A.
Published: June 2023

This publication reveals the content and specifics of the complex process of interstate harmonization of human rights norms against the background of the formation and development of modern International Law as the main regulator of international relations. The author believes that an analysis of the experience and practice of this coordination will help to better understand not only the key cause of the current crisis in international relations, but also the possibilities of overcoming it. The article traces the different approaches of states to the formation and observance of the principles and norms in the field of human rights - from the Cold War to the warming of the international situation, and then in the conditions of modern interstate relations. The publication concludes with the conclusion that the geopolitical situation in the world has a serious impact on modern International Law. Today, International Law is at a turning point: in which direction the main vector of its movement will be directed will become clear in the near future.
About non-federal justice Part I. Should the constitutional (statutory) ones have been abolished courts of the subjects of the Russian Federation?
Authors: Kleandrov Mikhail I.
Published: June 2023

In this article, the first of a series of articles, devoted to the problems of domestic non-federal justice, examines a set of issues related to the constitutional (statutory) courts of the Russian Federation. The author, considering the role and importance of this institution of justice in Russia, the presence of a huge scientific and legal component of its foundation and other factors, as well as the insufficiency of the grounds for its abolition, came to the conclusion that it is necessary to restore it. Taking into account the main drawback of the named institution in the public consciousness – its “high cost” and low “productivity”, the author makes specific proposals to offset this shortcoming when recreating – on a new legislative basis – this institution of domestic justice.
ЧИННИКИ ВИНИКНЕННЯ ТРИВОЖНИХ СТАНІВ У ПРАЦІВНИКІВ IT-СФЕРИ
Authors: АНТОНОВА Зінаїда , БАХТІГОЗІНА Дінара
Published: June 2023

Стаття присвячена дослідженню чинників виникнення тривожних станів у працівників ІТ-сфери. Зазначено, що багаточисельні зміни в нашій країні призводять до виникнення різноманітних негативних почуттів, зокрема до виникнення тривожності, що особливо стосується діяльності ІТ-працівників, адже здебільшого їх діяльність здійснюється віддалено і залежність від електропостачання. У статті розглянуто сутність поняття «тривожність». Проаналізовано особливості професії типу людина-знакова система. Висвітлено основні чинники виникнення тривожних станів у працівників ІТ-сфери. Визначено вагомі причини та основні прояви тривожності у працівників ІТ- сфери. Розглянуто психологічні особливості тривожних станів у працівників ІТ-сфери.

Висвітлено результати емпіричного дослідження основних чинників виникнення тривожних станів у працівників ІТ-сфери. За результатами дослідження визначено, що основними чинниками виникнення тривожних станів у працівників ІТ-сфери є: нестабільна ситуація в країні, перенавантаження, нестача комунікації, високий  рівень відповідальності, низька самооцінка, дисбаланс між роботою та особистим життям, ригідність, інтелектуальна концентрація, страх перед змінами, труднощі в плануванні свого робочого часу.

Перспективою подальшого дослідження вбачаємо у розробці практичних рекомендацій працівникам ІТ-сфери задля зменшення рівня тривожності.
The history of targeted therapy
Authors: Gerk I.A.
Published: June 2023

targeted therapy
Story Design in Fine Dining Projection Mapping Project “ Si Dulang “
Authors: Widiastomo Yohanes Merci
Published: June 2023

Projection technology is a technology that is familiar to modern society. It has been seen a lot in everyday life, from attending class lectures and watching movies in the theater. Projection technology is also used in creating art, such as projection mapping in various objects. Projection-Mapping is one of the technological achievements that opens complete access for artists to create and tell stories uniquely. Storytelling is something that humans always do over generations. The usage of technology these days is not limited in terms of form. One of the innovative ways to use projection mapping is "le Petit Chef." The combination of fine dining restaurants and the immersive experience when watching animation on a consumer table has positive outcomes for the restaurant industry. Based on the case study of projection mapping named "le Petit Chef", this research will focus on creating a story for projection mapping titled "Si Dulang". This research will also identify the factors the storyteller needs to consider when adopting new technology. 

Keywords: storytelling; projection mapping; fine dining; animation
Representation of Superheroes in The Character of Alana in The Film Sri Asih
Authors: Arpan Dedy
Published: June 2023

Sri Asih, the first superhero character in Indonesia created in 1954 by R.A Kosasih in comic media, has undergone several adaptations in comics and films with different character variations and story backgrounds. In 2022, Jagat Sinema Bumilangit re-adapted the Sri Asih film using a different approach. The film introduces a new main character named Alana and presents a storyline adapted to the current context. This research purpose is to analyze the representation of superheroes manifested in Alana’s character in the Sri Asih film 2022. The study employs a descriptive qualitative approach and refers to Roland Barthes' theory to uncover the meanings of denotation, connotation, and myth within the Sri Asih film. The research findings reveal 10 scenes that represent superheroes through the character of Alana. The results provide insights into how superheroes are portrayed through the character of Alana in the Sri Asih film. Additionally, the study uncovers the presence of heroic myths in the visual narrative structures of the film. These findings contribute to understanding the adaptation of superhero characters and how they remain relevant to popular cultural trends, attracting fans from generation to generation.

Keywords: representation; superhero; sri asih;  film; barthes; myth
Literature Review: 21st Century Skills Learning Through Numeracy Literacy Integration In Promoting The National Literacy Movement
Authors: Azzajjad Muhammad Fath , Ahmar Dewi Satria , Mustapa Kasmudin , Ahmar Ansari Saleh
Published: June 2023

This study aims to review various articles that discuss numeracy literacy studies published in journals in the field of education in Indonesia. This research is categorized as a literature review. The information data used was obtained from scientific journals with Science and technology index (SINTA) accreditation. Information was collected by taking publishing data from 2019 to 2022. Researchers reviewed, analyzed, and collaborated to evaluate, compile and review the findings obtained. Selecting 10 published articles that examine numeracy literacy, consisting of 6 types of qualitative research approaches, 3 quantitative research approaches, and 1 classroom action research article. The results of the literature review found that there were still articles that were not representative in explaining the number of research subjects, not in-depth in explaining the number of meetings in each cycle, and discussions that were still not optimal in answering problems rationally. However, in general, the results of the article review have provided information systems and have excellent references in describing specific concepts. The recommendation of the collaboration results is that in addition to deepening the methodological study, namely the research subject and the number of meetings in one cycle, it also requires modeling in writing articles that are solutions to each problem in the study. Modeling can be in the form of motivation and reinforcement given to improve learners' numeracy literacy in accordance with the vision of the national literacy movement in Indonesia.
ANALISIS DAN PERBANDINGAN STEGANOGRAFI PADA MEDIA AUDIO DAN GAMBAR MENGGUNAKAN LSB DAN RC4
Authors: Ashari Ilham Firman , Siwi Lkhsanudin Raka , Londata Hafizh , Wicaksono Ihtiandiko
Published: June 2023

Pada zaman digital saat ini, memberikan keamanan dan kerahasiaan informasi sangat penting ketika melakukan pertukaran informasi melalui jaringan komunikasi. Hal ini bertujuan agar informasi yang dikirimkan oleh pengirim dapat diterima secara utuh oleh penerima tanpa adanya campur tangan pihak ketiga yang tidak berhak atas informasi tersebut. Kriptografi dan Steganografi merupakan teknik yang dapat digunakan untuk mengamankan sebuah pesan rahasia, salah satu jenis metode yang dapat digunakan adalah algoritma RC4 yang digunakan untuk mengamankan pesan asli menjadi pesan rahasia yang acak agar tidak diketahui orang lain. Pada steganografi yang digunakan sebagai media untuk mengamankan pesan antara lain gambar, audio, video, dan dokumen, dimana salah satu metode yang digunakan adalah algoritma least significant bit (LSB). Berdasarkan pengujian yang dilakukan terkait pada penyisipan pesan pada media gambar dan audio didapatkan analisis terkait enkripsi dan dekripsi algoritma rc4. Pengujian aspek imperceptibility, dari histogram gambar dan spektrum audio terlihat tidak ada perbedaaan antara gambar dan audio sebelum dan setelah penyisipan. Pengujian aspek fidelity, dari PSNR dihasilkan rata-rata nilai > 30 dB. Pengujain aspek recovery, menunjukan bahwasanya aspek recovery berhasil 100 % karena tidak ada perbedaan antara pesan asli dan setelah ekstraksi. Pengujian aspek capacity, menunjukkan bahwasanya semakin besar ukuran media penampung maka semakin besar pesan yang bisa disisipkan.
IoT Frequency Band Channelization in Indonesia as A Recommendation for Machine-To-Machine Communication Preparation in the 5G Era
Authors: Nurpulaela Lela , Hadikusumo Ridwan Satrio
Published: June 2023

This study aims to provide recommendations regarding frequency and channel settings for machine-to-machine (M2M) communication in preparation for the 5G era in Indonesia. In the rapid development of the Internet of Things (IoT), M2M communication is becoming increasingly important to support efficient and reliable connectivity between IoT devices. In this study, we conduct an in-depth analysis of the available frequency spectrum in Indonesia, considering existing regulatory constraints and technical requirements. The results of this study show that the frequency bands 920-925 MHz and 925-928 MHz suit M2M communication in Indonesia with the suggested channel settings. These recommendations are based on spectrum availability, M2M communication needs, and relevant technical requirements. Implementing these recommendations is expected to increase the efficiency and reliability of M2M communications in Indonesia, facilitate the further development of IoT technology, and prepare Indonesia well to face the 5G era. This study contributes to designing a regulatory framework and optimal spectrum use to support successful M2M communications in Indonesia.
Analytical Rational Solitons of the Modified Lakshmanan-Porsezian-Daniel Equation
Authors: GİRESUNLU İlker Burak , YILDIZ Bengi
Published: June 2023

In this paper, the Lakshmanan-Porsezian-Daniel (LPD) equation is studied. New analytical rational solitons to the LPD equation are presented by an ansatz method. Wave solutions of three types, such as parabolic, trigonometric and hyperbolic function solutions have been retrieved. All solutions are plotted in 3D to enhance the understanding of their physical characteristics. These simulations, which represent the behavior of the resulting hyperbolic, parabolic and trigonometric solitons, are provided by choosing different appropriate values of the parameters.
An empirical study on the match-lead-in training mode in the general football course of physical education institute
Authors: Chen Jixing , Liu Fuli , Pu Tingyan
Published: June 2023

Football has always been a traditional item in sports colleges and universities in China, and is loved by teachers and students, but the traditional teaching mode of football general course has failed to meet the requirements of contemporary high-quality teaching. The author introduces the “match lead-in training” mode into the general football course to carry out teaching experimental research. Through the comparative analysis of the statistics of technical data and the test of special skills in four-person and six-person matches, the author finds that this teaching mode is more conducive to the improvement of students’ football technology, skill level and competition ability than that of the traditional football general course.
A novel dimensionality reduction and optimal deep learning based intrusion detection system for internet of things
Authors: Ponniah Krishna Kumar , Retnaswamy Bharathi
Published: June 2023

The internet of things (IoT) has significantly influenced day-to-day life in large industrial systems. The Internet of Things (IoT) offers a platform for information systems to integrate effectively with network servers. In contrast, cyber threats are becoming critical, especially for IoT servers. A strong strategy must be in place to protect the network system from multiple attacks. In order to detect malicious behaviors that deteriorate network performance, an intrusion detection system (IDS) is crucial. An IDS use a detection method to monitor network activity to alert IoT users regularly. This paper proposes a novel IDS for IoT using log-sigmoid kernel principal component analysis (LSK-PCA) and activation updated deep feed-forward neural network (AU-DFFNN) based dimensionality reduction (DR) and classification technique. Initially, the input data is taken from the NSLKDD dataset and undergoes pre-processing. Afterwards, attribute extraction is carried out, followed by Fisher’s Yates Adapted Golden Eagle Optimizer (FY-GEO) based feature selection. Then, DR of the feature selected data is done using the LSK-PCA model. Finally, the reduced dataset is given as an input to the classifier for classifying the data as attacked and normal data. As a final point, experimental analysis is performed using performance metrics like precision (PR), recall (RC), f-score (FS), accuracy (AC), false alarm rate (FAR) and computational time (CT). The results proved that the proposed work detects intrusion effectively compared to state-of-art techniques.
Forecasting Covid-19 outbreak using CLR optimized stacked generalization computational models
Authors: Jeyabalan Saranya Devi , Yesudhas Nancy Jane , Sathyanarayanan Jayashree , Harichandran Khanna Nehemiah
Published: June 2023

Coronavirus disease 2019 (Covid-19) is a contagious pandemic illness characterized by severe acute respiratory syndrome. The daily rise of Covid-19 instances and fatalities has resulted in worldwide lockdowns, quarantines and social distancing. Researchers have been working incredibly to develop precisely focused strategies to warfare the Covid-19 pandemic. This study aims to develop a cyclical learning rate optimized stacked generalization computational models (CLR-SGCM) for predicting Covid-19 pandemic outbreaks. Stacked generalization framework performs hierarchical two-phase prediction. In the first phase, deep learning models namely Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) and statistical model Auto Regressive Integrated Moving Average (ARIMA) are used as sub models to create pooled datasets (PDS). Cyclical learning rate (CLR) optimizer is used to enhance learning rate of ensemble deep learning models namely LSTM and GRU. In the second phase, meta learner is trained on dataset PDS using four different regression algorithms such as linear regression, polynomial regression, lasso regression and ridge regression to perform the final predictions. Time series data from India, Brazil, and the United States were utilized to forecast the Covid-19 pandemic outbreak. According to experimental finding, the presented stacking ensemble model outpaces the individual learners in terms of accuracy and error rate.
Breast cancer detection using Histopathology Image with Mini-Batch Stochastic Gradient Descent and Convolutional Neural Network
Authors: Sasirekha N. , Karuppaiah Jayakumar , Shekhar Himanshu , Naga Saranya N.
Published: June 2023

Cancer is a devastating disease that has far-reaching effects on our culture and economy, in addition to the human lives it takes. Regarding budgetary responsibility, investing just in cancer treatment is not an option. Early diagnosis is a crucial part of the remedy that sometimes gets overlooked. Malignancy is often diagnosed and evaluated using Histopathology Images (HI), which are widely accepted as the gold standard in the field. Yet, even for experienced pathologists, analysing such images is challenging, which raises concerns of inter- and intra-observer variability. The analysis also requires a substantial investment of time and energy. One way that such an examination may be sped up is by making use of computer-assisted diagnostics devices. The purpose of this research is to create a comprehensive cancer detection system using images of breast and prostate histopathology stained with haematoxylin and eosin (H&E). Proposed here is work on improving colour normalisation methods, constructing an integrated model for nuclei segmentation and multiple objects overlap resolution, introducing and evaluating multi-level features for extracting relevant histopathological image and interpretable information, and developing classification algorithms for tasks such as cancer diagnosis, tumor identification, and tumor class labelling. Mini-Batch Stochastic Gradient Descent and Convolutional Neural Network which obtained statistical kappa value for breast cancer histopathology images shows a high degree of consistency in the classification task, with a range of 0.610.80 for benign and low grades and a range of 0.811.0 for medium and high rates. The Support Vector Machine (SVM), on the other hand, shows an almost perfect degree of consistency (0.811.0) across the several breast cancer picture classifications (benign, low, medium, and high).
Blocking intrusion logic using optimized multi-head convolution in wireless sensor network
Authors: Prabhu S. , Mary Anita E.A. , Mohanageetha D.
Published: June 2023

Wireless sensor nodes (WSN) combine sensing and communication capabilities in the smallest sensor network component. Sensor nodes have basic networking capabilities, such as wireless connection with other nodes, data storage, and a microcontroller to do basic processing. The intrusion detection problem is well analyzed and there exist numerous techniques to solve this issue but suffer will poor intrusion detection accuracy and a higher false alarm ratio. To overcome this challenge, a novel Intrusion Detection via Salp Swarm Optimization based Deep Learning Algorithm (ID-SODA) has been proposed which classifies intrusion node and non-intrusion node. The proposed ID-SODA technique uses the k-means clustering algorithm to perform clustering. The Salp Swarm Optimization (SSO) technique takes into residual energy, distance, and cost while choosing the cluster head selection (CHS). The CHS is given the input to a multi-head convolutional neural network (MHCNN), which will classify into intrusion node and non-intrusion node. The performance analysis of the suggested ID-SODA is evaluated based on the parameters like accuracy, precision, F1 score, detection rate, recall, false alarm rate, and false negative rate. The suggested ID-SODA achieves an accuracy range of 98.95%. The result shows that the suggested ID-SODA improves the overall accuracy better than 6.56%, 2.94%, and 2.95% in SMOTE, SLGBM, and GWOSVM-IDS respectively.
Spherical video synopsis generation and visualization framework
Authors: Priyadharshini S. , Mahapatra Ansuman
Published: June 2023

With the advances in video technology, the advent of spherical video (360° video) recorded using an omnidirectional camera offers a limitless field-of-view (FoV) to the viewers. However, they suffer from the fear of missing out (FOMO) because they can only see a particular FoV at a time. Reviewing a long recorded surveillance video i.e., 24 hours a day is a time-consuming process due to temporal and spatial redundancy. A solution to this problem is to compactly represent the video synopsis by shifting the objects along the time domain. Using a multi-camera setup for surveillance creates blind spots. This problem is solved by using a spherical camera. Therefore, in this paper, we focus on creating and visualizing the video synopsis recorded by the spherical camera. The optimization algorithm plays a key role in condensing the recorded video. Hence, a novel spherical video synopsis optimization framework has been introduced to generate compact videos that eliminate FOMO. The synopsis is generated by shifting objects on the temporal axis and displays them simultaneously by optimizing multiple constraints. It minimizes activity loss, virtual collisions, temporal inconsistencies, and synopsis video length by preserving interactions between objects. The proposed multiobjective optimization includes a new constraint to restrict the number of objects displayed per frame due to the limitation of the human visual system. Direction-based visualization methods have been proposed to improve the viewer’s experience without FOMO. Comparative performance of the proposed framework using the latest metaheuristic optimization algorithms with existing video synopsis optimization algorithms is performed. It is found that chronological disorder ratio and overall virtual collision are minimized effectively through the recent metaheuristics optimization algorithms compared to the related works on video synopsis.
Leveraging Multi-Word Concepts to Predict Acute Kidney Injury in Intensive Care
Authors: Brancato Lorenzo , Calixto Iacer , Abu-Hanna Ameen , Vagliano Iacopo
Published: June 2023

Acute kidney injury (AKI) is an abrupt decrease in kidney function widespread in intensive care. Many AKI prediction models have been proposed, but only few exploit clinical notes and medical terminologies. Previously, we developed and internally validated a model to predict AKI using clinical notes enriched with single-word concepts from medical knowledge graphs. However, an analysis of the impact of using multi-word concepts is lacking. In this study, we compare the use of only the clinical notes as input to prediction to the use of clinical notes retrofitted with both single-word and multi-word concepts. Our results show that 1) retrofitting single-word concepts improved word representations and improved the performance of the prediction model; 2) retrofitting multi-word concepts further improves both results, albeit slightly. Although the improvement with multi-word concepts was small, due to the small number of multi-word concepts that could be annotated, multi-word concepts have proven to be beneficial.
Using Digital Tools to Train Health Emergencies Personnel in Fragile Contexts
Authors: Attias Melissa , Utunen Heini , Crowder Ryan , Black Andrew , Arabi Elham , Litam Katrina , Tokar Anna
Published: June 2023

The Leadership in Emergencies learning programme, launched in 2019, was designed to strengthen the competencies of World Health Organization (WHO) and Member State staff in teamwork, decision-making and communication, key skills required to lead effectively in emergencies. While the programme was initially used to train 43 staff in a workshop setting, the COVID-19 pandemic required a new remote approach. An online learning environment was developed using a variety of digital tools including WHO’s open learning platform, OpenWHO.org. The strategic use of these technologies enabled WHO to dramatically expand access to the programme for personnel responding to health emergencies in fragile contexts and increase participation among key groups that were previously underserved.
A Study on the Reliability of Visual XAI Methods for X-Ray Images
Authors: Stodt Jan , Madan Manav , Reich Christoph , Filipovic Luka , Ilijas Tomi
Published: June 2023

The YOLO series of object detection algorithms, including YOLOv4 and YOLOv5, have shown superior performance in various medical diagnostic tasks, surpassing human ability in some cases. However, their black-box nature has limited their adoption in medical applications that require trust and explainability of model decisions. To address this issue, visual explanations for AI models, known as visual XAI, have been proposed in the form of heatmaps that highlight regions in the input that contributed most to a particular decision. Gradient-based approaches, such as Grad-CAM [1], and non-gradient-based approaches, such as Eigen-CAM [2], are applicable to YOLO models and do not require new layer implementation. This paper evaluates the performance of Grad-CAM and Eigen-CAM on the VinDrCXR Chest X-ray Abnormalities Detection dataset [3] and discusses the limitations of these methods for explaining model decisions to data scientists.
Diagnostic Classification of ASD Using Fractal Functional Connectivity of fMRI and Logistic Regression
Authors: Rakshe Chetan , Kunneth Suja , Sundaram Soumya , Agastinose Ronickom Jac Fredo
Published: June 2023

Our study used functional magnetic resonance imaging and fractal functional connectivity (FC) methods to analyze the brain networks of Autism Spectrum Disorder (ASD) and typically developing participants using data available on ABIDE databases. Blood-Oxygen-Level-Dependent time series were extracted from 236 regions of interest of cortical, subcortical, and cerebellar regions using Gordon’s, Harvard Oxford, and Diedrichsen atlases respectively. We computed the fractal FC matrices which resulted in 27,730 features, ranked using XGBoost feature ranking. Logistic regression classifiers were used to analyze the performance of the top 0.1%, 0.3%, 0.5%, 0.7%, 1%, 2%, and 3% of FC metrics. Results showed that 0.5% percentile features performed better, with average 5-fold accuracy of 94%. The study identified significant contributions from dorsal attention (14.75%), cingulo-opercular task control (14.39%), and visual networks (12.59%). This study could be used as an essential brain FC method to diagnose ASD.
Brain Tumor Classification and Segmentation Using Dual-Outputs for U-Net Architecture: O2U-Net
Authors: Zargari Seyed Aman , Kia Zahra Sadat , Nickfarjam Ali Mohammad , Hieber Daniel , Holl Felix
Published: June 2023

We propose a modified version of the U-Net architecture for segmenting and classifying brain tumors, introducing another output between down- and up-sampling. Our proposed architecture utilizes two outputs, adding a classification output beside the segmentation output. The central idea is to use fully connected layers to classify each image before applying U-Net’s up-sampling operations. This is achieved by utilizing the features extracted during the down-sampling procedure and combining them with fully connected layers for classification. Afterward, the segmented image is generated by U-Net’s up-sampling process. Initial tests show competitive results against comparable models with 80.83%, 99.34%, and 77.39% for the dice coefficient, accuracy, and sensitivity, respectively. The tests were conducted on the well-established dataset from Nanfang Hospital, Guangzhou, China, and General Hospital, Tianjin Medical University, China, from 2005 to 2010 containing MRI images of 3064 brain tumors.
Factors Influencing the Evolution of Topics in Biomedical Informatics
Authors: Mihalas George , Kulikowski Casimir
Published: June 2023

Our study contributes to the history of international medical informatics through investigating the thematic evolution of the MEDINFO conferences during a period of consolidation and expansion of the discipline. The themes are examined and potential factors influencing the evolutionary developments are discussed.
Patient-Centric Interoperability and Cybersecurity for Cross-Border Healthcare
Authors: Latorre Fernando , Hawks Claudia E. , Colmenares Bruno , Verma Deepika , Gil Marisa , Sala Nuria
Published: June 2023

In Web 3.0 the user owns the information. Decentralized Identity Documents (DID documents) allow users to create their own digital identity and decentralized cryptographic material resistant to quantum computing. A patient’s DID document also contains a unique identifier for cross-border healthcare, endpoints for receiving DIDComm messages and for SOS services, and additional identifiers (passport, etc.). We propose a blockchain for cross-border healthcare to store the evidence of different electronic, physical identities, and identifiers, but also the rules approved by the patient or legal guardians to access patient data. The International Patient Summary (IPS) is the de facto standard for cross-border healthcare and includes an index of information classified into sections (HL7 FHIR Composition) that healthcare professionals and services can update and read on the patient’s SOS service, then retrieving all the necessary patient information from the different FHIR API endpoints of different healthcare providers according to the approved rules.
Development of Tuberculosis Vulnerability Assessment Conceptual Framework Using Automatic Content Analysis
Authors: Handayani Sri , Hinchcliff Reece , Hasibuan Zainal A.
Published: June 2023

The tuberculosis prevention and control model needs to be explored. This study aimed to create a conceptual framework for measuring TB vulnerability to guide the prevention program’s effectiveness. SLR method was employed, resulting in 1.060 articles being analyzed with ACA Leximancer 5.0 and facet analysis. The built framework consists of five components: risk of TB transmission, damage caused by TB, health care facility, the burden of TB, and awareness of TB. Future research is required to explore variables in each component to formulate the degree of TB vulnerability.
Human Factors Influencing the Experience of Healthcare Professionals Using Digital Tools
Authors: Wosny Marie , Strasser Livia , Hastings Janna
Published: June 2023

Digitalization in healthcare has the potential to offer numerous advantages to various stakeholders, however, healthcare professionals often encounter difficulties while using digital tools. We conducted a qualitative analysis of published studies to examine the experience of clinicians using digital tools. Our findings revealed that human factors influence clinicians’ experiences and that integration of human factors into the design and development of healthcare technologies is of high importance to improve user experience and overall success.
Modeling Cholecystectomy Hospital Stay Through a Linear Approach
Authors: D’Amore Antonio , D’Onofrio Gaetano , Ascione Flora , Sarnelli Raffaele , Triassi Maria , Marino Marta Rosaria
Published: June 2023

Cholecystectomy is among the most frequent procedures in general surgery. In the healthcare facility organization, it is important to evaluate all interventions and procedures that have a great impact on health management and that have a clear effect on the Length of Stay (LOS). The LOS represents, in fact, an indicator of performance and measure the goodness of a health process. This study was conducted with the aim of providing LOS for all patients undergoing cholecystectomy at the “A.O.R.N. A. Cardarelli” of Naples. Data were collected in the two years 2019 and 2020 and included 650 patients. A MLR model is created in the work to predict the value of LOS as a function of the following variables: gender, age, pre-operative LOS, presence of comorbidities and complication during surgery. The results obtained are as follows: R=0.941 and R2=0.885.
From Assessment to Action: Exploring the Dynamics Between Maturity Assessments and Strategy Implementation in Digital Health
Authors: Zhao Yu , Schalet Denise , Alsalamah Shada , Pujari Sameer , Labrique Alain
Published: June 2023

A country’s digital health maturity is a key factor in the digital transformation of a national health system. Although many maturity assessment models exist in the literature, they perform as stand-alone tools without a clear indication to inform a country’s strategy implementation in digital health. This study explores the dynamics between maturity assessments and strategy implementation in digital health. First, it analyses the word token distribution of key concepts in indicators from five pre-existing digital health maturity assessment models and those originated from the WHO’s Global Strategy on Digital Health. Second, it compares type and token distributions in the selected topics mapped against the policy actions under the GSDH. The findings reveal existing maturity models with a significantly heavier focus on health information systems and highlight gaps in measuring and contextualising topics e.g., equity, inclusion, and digital frontiers.
The Slovenian Patient Summary: One Digital Record, Multitude of Applications
Authors: Stanimirovic Dalibor , Tepej Jocic Lucija
Published: June 2023

The Central Registry of Patient Data is the most complex public information system in the Slovenian healthcare, providing valuable information to patients, healthcare professionals and health authorities. Its most important element is a Patient Summary, which contains essential clinical data required to ensure safe treatment of patients at a point of care. This article focuses on the Patient Summary and the review of its application aspects, especially in relation to the Vaccination Registry. The research employs a case study framework, supported by focus group discussions being a primary data collection technique. Single-entry collection and reuse of data, as implemented in the case of Patient Summary, could significantly optimize current practices and necessary resources for processing health data. Moreover, the research reveals that structured and standardized data from the Patient Summary could provide an important input for primary use and other applications across the digital landscape in the Slovenian healthcare system.
The Efficacy of Long-Term Hydroxychloroquine Use in the Prevention of COVID-19: A Retrospective Cohort Study
Authors: Finkelstein Joseph , Huo Xingyue
Published: June 2023

The use of hydroxychloroquine (HCQ) in the prevention or treatment of COVID-19 remains controversial due to the insufficient supporting evidence and clinical studies indicating that it does not reduce COVID-19 mortality. Its potential protective effects against SARS-CoV-2 are still unclear. Big data resources, such as MarketScan database containing over 30 million insured participants annually, have not been used systematically to assess the association between long-term HCQ use and the risk of COVID-19. This retrospective study aimed to determine the protective effect of HCQ using the MarketScan database. We examined COVID-19 incidence from January to September 2020 among adult patients with systemic lupus erythematosus or rheumatoid arthritis who had received HCQ for at least 10 months in 2019 compared to those who did not. Propensity score matching was used to control for confounding variables and make the HCQ and non-HCQ groups comparable in this study. After matching at the ratio of 1:2, the analytical dataset comprised 13,932 patients who received HCQ for over 10 months and 27,754 HCQ-naïve patients. Multivariate logistic regression showed that long-term HCQ use was associated with a lower likelihood of COVID-19 in patients who had been receiving HCQ for over 10 months (OR=0.78, 95% CI: 0.69-0.88). These findings suggest that long-term HCQ use may provide protection against COVID-19.
Clinical Decision Support Systems Applied to the Management of Breast Cancer Patients: A Scoping Review
Authors: Novikava Natallia , Redjdal Akram , Bouaud Jacques , Seroussi Brigitte
Published: June 2023

Breast cancer is the most commonly diagnosed cancer worldwide, and its burden has been rising over the past decades. A significant advance in healthcare is the integration of Clinical Decision Support Systems (CDSSs) into medical practice, which support healthcare professionals improving clinical decisions, leading to recommended patient-specific treatments and enhanced patient care. Breast cancer CDSSs are thus currently expanding, whether applied to screening, diagnostic, therapeutic or follow-up tasks. We conducted a scoping review to study their availability and use in practice. Except risk calculators, very few CDSSs are currently routinely used.
Questionnaire to Capture the Over Time User Preference During the Comparison of Pharmacovigilance Software Systems
Authors: Bonotis Panos , Natsiavas Pantelis
Published: June 2023

The study aimed to assess the usability of the PVClinical platform, which is designed for detecting and managing Adverse Drug Reactions (ADRs). A “slider” type comparative questionnaire was designed to capture the preferences of six end-users over time between PVC clinical platform and the established clinical and pharmaceutical ADR detection software tools. The results of the questionnaire were cross-examined with the results of the usability study. The questionnaire was a quick preference-capturing tool over time and provided impactful insights. Coherence in participants’ preferences for PVClinical platform was observed, but further research is needed to establish the effectiveness of the questionnaire as a preference-capturing tool.