bluuebunny/crossref_metadata_2025 huggingface dataset:
Recognition of Object Presence and Material Type in a Water Container Using High Frequency Ultrasound
Authors: Sadh Mehul Vishal , Huber Manfred
Published: May 2023

Detection and characterization of soluble, diffuse, and solid objects and their characteristics in water has important implications in various applications, including water quality assessment and incontinence monitoring for health applications. In particular in the latter task, it is essential to be able to non-intrusively detect the appearance, presence, and consistency of materials in the water without the need for special purpose instruments or a special purpose setting. To achieve this, this work investigates the potential use of high frequency sonar sensors retrofitted to an existing, water-filled container to detect and characterize events where materials are added to the water, and to classify characteristics of the materials in terms of solubility, granularity, and density.
A Survey on Sentiment Classification Methods and Challenges
Authors: Keivandarian Neda , Carvalho Marco
Published: May 2023

Sentiment classification (SC) is an important natural language processing (NLP) task that aims to determine the sentiment or emotional tone in a given text. With the increasing pervasiveness of internet-based applications and social media, massive amounts of unstructured data are generated daily, elevating the opportunity and challenges associated with automated sentiment extraction for tasks such as customer feedback analysis, social media monitoring, and opinion mining. In this review paper, we provide an update on the state of the art in sentiment analysis, including an overview of and classification methods leveraging machine learning and deep learning methods.
Evaluation of Techniques for Sim2Real Reinforcement Learning
Authors: Ranaweera Mahesh , Mahmoud Qusay
Published: May 2023

Reinforcement learning (RL) has demonstrated promising results in transferring learned policies from simulation to real-world environments. However, inconsistencies and discrepancies between the two environments cause a negative transfer. The phenomenon is commonly known as the “reality gap.” The reality gap prevents learned policies from generalizing to the physical environment. This paper aims to evaluate techniques to improve sim2real learning and bridge the reality gap using RL. For this research, a 3-DOF Stewart Platform was built virtually and physically. The goal of the platform was to guide and balance the marble towards the center of the Stewart platform. Custom API was created to induce noise, manipulate in-game physics, dynamics, and lighting conditions, and perform domain randomization to improve generalization. Two RL algorithms; Q-Learning and Actor-Critic were implemented to train the agent and to evaluate the performance in bridging the reality gap. This paper outlines the techniques utilized to create noise, domain randomization, perform training, results, and observations. Overall, the obtained results show the effectiveness of domain randomization and inducing noise during the agents' learning process. Additionally, the findings provide valuable insights into implementing sim2real RL algorithms to bridge the reality gap.
Towards a Framework for Intelligent Urban Traffic Routing
Authors: Švadlenka Matyáš , Chrpa Lukáš
Published: May 2023

Intelligent traffic routing is one of the key techniques that can be used to optimise traffic, especially in urban areas. Deliberative reasoning techniques such as Automated Planning have shown their potential since they can take a global and longer-term perspective on the traffic situations. Such techniques have to be embedded in a urban traffic control framework such that they can generate and assign routes to the vehicles on the fly while considering the current traffic situation in the area.

This paper presents an ongoing work on a framework that, in a nutshell, integrates an automated planning component, responsible for intelligent traffic routing, in the well known SUMO simulator in order to evaluate and study its impact in realistic traffic settings. In particular, the framework has to simplify the representation of the road network provided by SUMO, translate it into PDDL, a language for describing planning problems, and then interpret plans and fed them in form of vehicle routes into SUMO.
Improving Word Embedding Using Variational Dropout
Authors: Albujasim Zainab , Inkpen Diana , Han Xuejun , Guo Yuhong
Published: May 2023

Pre-trained word embeddings are essential in natural language processing (NLP). In recent years, many post-processing algorithms have been proposed to improve the pre-trained word embeddings. We present a novel method - Orthogonal Auto Encoder with Variational Dropout (OAEVD) for improving word embeddings based on orthogonal autoencoders and variational dropout.  Specifically, the orthogonality constraint encourages more diversity in the latent space and increases semantic similarities between similar words, and variational dropout makes it more robust to overfitting.   Empirical evaluation on a range of downstream NLP tasks, including semantic similarity, text classification, and concept categorization shows that our proposed method effectively improves the quality of pre-trained word embeddings. Moreover, the proposed method successfully reduces the dimensionality of pre-trained word embeddings while maintaining high performance.
Using machine learning algorithms (supervised) to generate automatically labeled dataset for detecting digital dating abuse from text messages
Authors: Roy Tania , Maranzatto Thomas , Loomas Zachary
Published: May 2023

Digital dating abuse is a form of intimate partner violence that uses technology as a medium to propagate fear and cause harm for dating partners. Over several years digital dating abuse has been on the rise, and particularly during COVID-19, the issue has risen exponentially. This project aims to create a tool that raises awareness and detects digital dating from text messages. Previously, we generated a dataset with expert labelers to use supervised machine learning algorithms for abuse detection. However, the cost and time associated with generating human-annotated datasets limit the size of these verified datasets. This poster explores using machine learning algorithms trained on human-annotated datasets to label more extensive crowd-sourced datasets and generate a larger training dataset for abuse detection algorithms. We used Naive Bayes, Decision Tree, LSVM, and LSTM to test for accuracy and speed of labeling this more extensive dataset.
Considerations in the Design of Realistic Agents for Serious Games
Authors: Sottilare Robert , Ballinger Christopher , McGroarty Christopher
Published: May 2023

Artificially intelligent software agents are a staple of the video game and simulation industry, and are used for many purposes ranging from entertainment to training to analysis and decision support. Using data from live training exercises, this paper considers the process of constructing an effective data pipeline to determine the critical features that should be represented in intelligent agents for use in game-based training environments. Intelligent agents are often developed to represent the cognitive processes and behaviors of individuals or aggregate units or teams. The goal of the research described herein is to determine if the construction, training and validation of autonomous agents can be enhanced by modeling their perception, decision, and action processes after real entity behaviors captured during live training exercises.
On Bounding the Behavior of a Neuron
Authors: Borowski Richard , Arthur Choi
Published: May 2023

A neuron with binary inputs and a binary output represents a Boolean function. Our goal is to extract this Boolean function into a tractable representation that will facilitate the explanation and formal verification of a neuron's behavior. Unfortunately, extracting a neuron's Boolean function is in general an NP-hard problem. However, it was recently shown that prime implicants of this Boolean function can be enumerated efficiently, with only polynomial time delay. Building on this result, we propose a best-first search algorithm that is able to incrementally tighten inner and outer bounds of a neuron's Boolean function. These bounds correspond to truncated prime-implicant covers of the Boolean function. We provide two case studies that highlight our ability to bound the behavior of a neuron.
Topological Data Analysis in Natural Language Processing -- A Tutorial
Authors: Zadrozny Wlodek
Published: May 2023

Topological Data Analysis (TDA) introduces methods that capture the underlying structure of shapes in data.Within the last two decades, TDA has been mostly examined in unsupervised machine learning tasks. TDAhas been often considered an alternative to the conventional algorithms due to its capability to deal with highdimensionaldata. in different tasks including but not limited to clustering, This tutorial will focus on applications of topological data analysis to text data.
Machine Learning for Early Mental Health Support and Offenders Correction
Authors: Elsayed Nelly , ElSayed Zag , Ozer Murat
Published: May 2023

The effective rehabilitation and supervision of law offenders are vital to promoting community safety and enabling individuals to reintegrate into society. Community supervision presents several challenges for agencies like the Adult Parole Authority (APA), which must oversee individuals released from prisons under various forms of supervision, including courtesy supervision for different counties and interstate compact cases. With such a large number of individuals under supervision, the APA struggles to provide adequate oversight and support to guide individuals towards positive behavioral changes and reduce the risk of recidivism. To address these challenges, this paper proposes a machine learning-based system designed to monitor and support individuals under community supervision. The model would track various indicators to identify individuals at risk of self-harm or harming others and enable the APA to provide timely and appropriate support to these individuals. Improving the monitoring and support offered during the rehabilitation and supervision period would enhance the effectiveness of community supervision and contribute to safer and more stable communities.
Computing an Optimal Pitching Strategy in a Baseball At-Bat
Authors: Douglas Connor , Witt Everett , Bendy Mia , Vorobeychik Yevgeniy
Published: May 2023

The field of quantitative analytics has transformed the worldof sports over the last decade. To date, these analytic ap-proaches are statistical at their core, characterizing what isand what was, while using this information to drive decisionsabout what to do in the future. However, as we often viewteam sports, such as soccer, hockey, and baseball, as pairwisewin-lose encounters, it seems natural to model these as zero-sum games. We propose such a model for a baseball at-bat,which is a matchup between a pitcher and a batter. Specifi-cally, we propose a novel model of this encounter as a zero-sum stochastic game, in which the goal of the batter is to geton base, an outcome the pitcher aims to prevent. The valueof this game is the on-base percentage (i.e., the probabilitythat the batter gets on base). In principle, this stochastic gamecan be solved using classical approaches. The main techni-cal challenges lie in predicting the distribution of pitch loca-tions as a function of pitcher intention, predicting the distri-bution of outcomes if the batter decides to swing at a pitch,and characterizing the level of patience of a particular batter.We address these challenges by proposing novel pitcher andbatter representations as well as a novel deep neural networkarchitecture for outcome prediction. Our experiments usingKaggle data from the 2015 to 2018 Major League Baseballseasons demonstrate the efficacy of the proposed approach.
Learning to Take Cover with Navigation-Based Waypoints via Reinforcement Learning
Authors: Aris Timothy , Ustun Volkan , Kumar Rajay
Published: May 2023

This paper presents a reinforcement learning model designed to learn how to take cover on geo-specific terrains, an essential behavior component for military training simulations. Training of the models is performed on the Rapid Integration and Development Environment (RIDE) leveraging the Unity ML-Agents framework. This work expands on previous work on raycast-based agents by increasing the number of enemies from one to three. We demonstrate an automated way of generating training and testing data within geo-specific terrains. We show that replacing the action space with a more abstracted, navmesh-based waypoint movement system can increase the generality and success rate of the models while providing similar results to our previous paper's results regarding retraining across terrains. We also comprehensively evaluate the differences between these and the previous models. Finally, we show that incorporating pixels into the model's input can increase performance at the cost of longer training times.
Towards Species-Specific Coral Classification in Reef Monitoring Efforts
Authors: Jang Hyeong , Leidig Jonathan , Wolffe Greg
Published: May 2023

Monitoring the health of coral reefs has traditionally required human labor-intensive effort in the collection and analysis of captured survey data and underwater images. Typical Marine Ecology tasks involve the classification of features within benthic maps and the estimation of coral coverage of the seafloor. In an effort to determine the feasibility of automating part of this process, this work trained and evaluated machine learning models to classify eleven species of stony and fire corals. A binary classifier was developed for each separate species (attaining 95-99% accuracy per model), followed by a single multi-class model (attaining over 92% accuracy). This paper details the architecture, parameterization, and effectiveness of these models as trained on a curated set of images. The models were then evaluated using one square kilometer maps of the seafloor to assess their practicability for automating several image-based analysis tasks on a widespread scale. Developing future monitoring workflows that utilize these machine learning models will minimize the human labor-intensive component of benthic map analysis.
Parsing-Based Recognition of Hierarchical Plans Using the Grammar Constraint
Authors: Pantůčková Kristýna , Ondrčková Simona , Barták Roman
Published: May 2023

Plan recognition is the problem of recognizing a goal task and an agent’s plan based on the observed actions. Plan recognition techniques can be employed in multiagent systems, behaviour recognition, computer security, and other fields related to artificial intelligence. Hierarchical task networks (HTN) describe the decomposition hierarchy of tasks in planning problems. In HTN plan recognition, a prefix of the plan (actions observed so far) is given as an input, and the aim is to find a task that decomposes into a sequence of actions with the given prefix. In this paper, we show how the performance of parsing-based HTN plan recognition can be improved by restricting possible suffixes of the given prefix based on generalized arc consistency of a corresponding context-free grammar.
Learning Policies for Neural Network Architecture Optimization Using Reinforcement Learning
Authors: Vadhera Raghav , Huber Manfred
Published: May 2023

Deep learning systems tend to be very sensitive to the specific network architecture both in terms of learning ability and performance of the learned solution. This, together with the difficulty of tuning neural network architectures leads to a need for automatic network optimization. Previous work largely optimizes a network for one specific problem using architecture search, requiring significant amounts of time training different architectures during optimization. To address this and to open up the potential for transfer across tasks, this paper presents a novel approach that uses Reinforcement Learning to learn a policy for network optimization in a derived architecture embedding space that incrementally optimizes the network for the given problem. By utilizing policy learning and an abstract problem embedding, this approach brings the promise of transfer of the policy across problems and thus the potential optimization of networks for new problems without the need for excessive additional training. For an initial evaluation of the base capabilities, experiments for a standard classification problem are performed in this paper, showing the ability of the approach to optimize the architecture for a specific problem within a given rang of fully connected networks, and indicating its potential for learning effective policies to automatically improve network architectures.
Dynamic FastMap: An Efficient Algorithm for Spatiotemporal Embedding of Dynamic Graphs
Authors: Thakoor Omkar , Kumar T. K. Satish
Published: May 2023

Efficiently embedding graphs in a Euclidean space has many benefits: It allows us to interpret and solve graph-theoretic problems using geometric and analytical methods. It also allows us to visualize graphs and support human-in-the-loop decision-making systems. FastMap is a near-linear-time graph embedding algorithm that has already found many real-world applications. In this paper, we generalize FastMap to Dynamic FastMap, which efficiently embeds dynamic graphs, i.e., graphs with time-dependent edge-weights, in a spatiotemporal space with a user-specified number of dimensions, while reserving one dimension for representing time. Through a range of experiments, we also demonstrate the efficacy of Dynamic FastMap as an algorithm for spatiotemporal embedding of dynamic graphs.
FLAIRS-36 Invited Talk Abstracts
Authors: Chun Soon
Published: May 2023

Three invited speakers for the general conference include  Deborah L. McGuinness, Christoph Benzmüller and Bonnie J. Dorr.  The special track invite speaker is for Nobal Niraula for the Applied Natural Language Processing track.
An Introduction to Neural Networks
Authors: Bisant David
Published: May 2023

Neural networks ares an important type of machine learning that have generated significant interest due to their success on difficult problems.. This tutorial will provide an introduction and a high-level overview of artificial neural networks. It will include the biological basis and the inspiration for these methods, and their colorful history.  An explanation of deep learning and deep belief networks, hardware acceleration, and case studies will be used to illustrate how the technology works and the direction in which it is developing.
Qualitative Choice Logic For Modeling Experts Recommendations of Antibiotics
Authors: Sedki Karima , Lamy Jean-Baptiste , Rosy Tsopra
Published: May 2023

Qualitative Choice Logic (QCL) is a logic-based formalism for preference handling. The logic adds to classical propositional logic a new connective called ordered disjunction (~).x~y intuitively means: if possible x, but if x is not possible then at least y. The aim of this paper is to explore QCL in healthcare domain, particularly for modeling experts reasoning for providing recommendations of antibiotics. We show that QCL is fully adapted for modeling this problem.
Yoruba Culture in a Changing World
Authors: Adejumo Arinpe G.
Published: May 2023

Culture, a way of life, ideology, and philosophy of a people, has been a focal point of scholarly research in the fields of literature, language, history, and sociology, among others. The findings of existing research have established that culture is dynamic. The Yorùbá culture, like other cultures of the world is not static. Hence, in this discourse, we will examine the impact of the changes in the Yorùbá society on the culture of the people.

Data for the study drawn from Yorùbá cultural heritage, literary works, home video, films and oral genres. The data were subjected to content and interpretive analysis. Findings reveal that some indices of Yorùbá culture have experienced constant flux due to the mobile nature of the culture and its contact with other cultures. The research also affirm that the preservation of the culture prompted some stakeholders to change the existing norm in order to add value to the Yorùbá culture for the benefit of the upcoming generation. It further revealed that the changes that the culture witnesses could be seen as a two-edged sword, with both positive and negative impacts. Positive in the sense of elements that enhance sustainable development and negative from the purview of elements that degrade, diminish, and decimate human flourishing.

The research concludes that the response of the Yorùbá culture to changes could impact positively on growth. In other word, human activities in Yorùbá culture should be tailored in positive direction to enhance national and social-economic development. Hence, the revitalization, documentation and preservation of culture should be of interest to the government and policy makers.
Yoruba Language Use in Lagos State Legislative Assembly: Challenges and Prospects
Authors: Suleiman Hassan Biodun
Published: May 2023

Abstract

This study examined the challenges and prospects of the use of the Yoruba Language for legislative business in the Lagos State House of Assembly. The Assembly adopted the use of the Yoruba language for its deliberation every Thursday in 2007. This study made use of an in-depth interview guide to elicit responses from research subjects, who were drawn from among the Legislative officers, aides, and assistants, totaling ten. In addition, we consulted archival notes, Order Paper, Proceedings of the House, newspapers, and other recorded material. Our findings revealed that there is an insufficient number of Yoruba legislative reporters, while some legislators are still trying to grapple with the use of Yoruba. Similarly, most statutory committee members do not speak the Yoruba language during meetings or public hearings. The prospects of the initiative include, among others, bringing legislative practice to the doorstep of the common man. For instance, the House has now passed a bill into law making Yoruba language compulsory both as a subject and a language in Lagos State public schools toward the growth of the economy of Lagos State.
Gendered Species of Yoruba Plants: An Ecofeminist Perspective
Authors: Faleye Adeola Adijat
Published: May 2023

The phenomena of female and male collaboration or concurrence towards making a positive and progressive impact in most environmental situations in Yorùbá land cannot be over-emphasized. From published works of Yorùbá literature and other oral data, such as in poetry texts, findings show extant research on many herbs [plants]. Such findings show that there exists a dichotomy between the gendered species of plants. In addition, evidence reveals that within the Yorùbá belief system, some cultural practices are evident in support of the ecofeminist thought spanning various contexts in politics, warfare, or conflict resolutions, as well as Yorùbá Òrìṣà cults. Therefore, this essay seeks to explore the feminine relevance and significance in some contexts of herb or plant growth and their nature. The theory of ecofeminism and the sociology of literature are applied. The study shall make use of relevant orature to support the validity and essentialism of creation and the strengths deposited in the female gender regarding its purpose and values in contents and context, modern diversity, and contemporary views at large on nature. This is to emphasize the significance of the abo-female as supported by nature and other iconic materials within the sacred/metaphysical realm.
The Dominance of Homeopathic Medicine in Yoruba Healthcare Delivery
Authors: Oyelakin Richard Taye
Published: May 2023

This essay, in the main, argues that the strength and dominance of Yoruba Indigenous Medicine (here-in YIM) consists, not just in outlining the properties of the ingredients, structure, and process of production, as well as modes and mediums of administration, but also, and fundamentally, in the whole qualifying moral and spiritual status of the producers and administrators of the medicine. Further argued that this qualification is what enables YIM to be able to heal rather than cure, where healing is addressing the both physical and spiritual cause(s) and source(s) of the illness. A system of medicine, which prioritizes the sanctity of the dispensers in addition to the drug processes, is considered dominant. Consequently, by being dominant, YIM could help in combating any emerging pandemic, if accorded due recognition. The paper calls for this recognition and development of medicine to enable the world to benefit from it in case of a future and perhaps more deadly outbreak.
The Relevance of the Practice of Ifá Divination in Ola Rotimi’s The Gods are not to Blame
Authors: Olu-Osayomi Olusegun , Adebua Babatunde
Published: May 2023

The custom of Ifá divination is common among the Yorùbá of Western Nigeria, and among Africans generally. This paper attempts an evaluation of the relevance of the practice of Ifá divination in the selected play of Ola Rotimi to Yorùbá culture and metaphysics. This is purposely to attain a greater and more profound awareness of its role as a symbol of communal and cultural identicalness. Using The God Are Not to Blame (1975) as an illustration, the paper contends, in a poignant manner, that the elements of Yorùbá Ifá divination, through oracular devices, well manifested in the structuring principles of Rotimi’s work. This is analyzed from spiritual and mythological angles. With an overwhelming lucidity, the paper posits that actions in the play are influenced by an assumption that any collective catastrophe or adversities are the outcomes of disharmony between disparate cosmos. The aforementioned includes a detailed interrogation of the rationality and logic of these beliefs as Rotimi presents them. Through the ambiance of the various events in the play, the paper establishes that the practice of Ifá divination in Yorùbá land is not only a way of life but has also transcended traditional, Christian, and Muslim traditions and beliefs. Finally, while recognizing the enduring popularity and artistic forte of Rotimi’s magnum opus, the paper broadens spasmodically our perception of the pervasiveness and practical relevance of the practice of Ifá divination as means for rectifying evil destiny, regulating what the future holds and resolving problems of existence in Yorùbá culture and metaphysics.
Iwolefu Funeral Insurance and the Socioeconomics of Burial Ceremony in Ikorodu area of Lagos State
Authors: Boge Faruq Idowu
Published: May 2023

Death is an inevitable aspect of human existence. Human beings have evolved the custom of honouring the deceased with organized burial arrangements. Each society, therefore, has a different tradition for funeral arrangements and burial ceremonies. Among the Yoruba people, the deceased is honored with elaborate funeral arrangements incurring huge expenses. Traditionally, these expenses are borne by the deceased’s lineage. The Ikorodu (Remo) sub-ethnic Yoruba group has a traditional form of funeral insurance that makes funeral arrangements and expenses a communal responsibility. This study microscopically examines aspects of burial arrangements among the people. It specifically concentrates on the traditional funeral insurance practice, locally known as iwolefu, among the people. The study argues that the traditional funeral insurance practice is among the main instruments by which the institutions of ẹbí (family) and ìdílé (lineage) are preserved among the aborigines of the Ikorodu area. The study uses historical and ethnographical approaches to data collation and interpretation.
Of Evangelism or Merchandise? The Role of Selected Christian Faith-based Schools in Nigerian Education
Authors: Ajibade Mobolaji Oyebisi
Published: May 2023

There is no doubt that Christianity had contributed immensely to the religious, political, educational, and socio-economic development of Nigeria. However, the story is not holistic. Hence, this paper critically examines the role of both mainline and Pentecostal churches in education in relation to National development in Nigeria. It examines the contribution of faith-based schools in southwestern Nigeria to education. Data for this research was obtained through primary and secondary sources. The primary source includes in-depth interviews with the owners of the selected faith-based schools. The secondary source includes books, journal articles, the Internet, and structured questionnaires as tools for producing information. In addition, all relevant documents of the selected institutions were collected. Data collected were analyzed through the sociology of religion. The study concludes that the mission schools have seriously deviated from their primary aim of using religion as a channel to evangelize but have turned to real enterprises. In addition, it shows that the entrepreneurial sense of the Pentecostal churches is higher than that of the Orthodox missions, especially when we examine the school fees that they charge students in their schools.
Resolving Lexical Verb Ambiguity in Yoruba through Semantic Web Annotations
Authors: Akindele Aina A.
Published: May 2023

Lexical verb ambiguity refers to the potential for multiple interpretations of units of speech in languages that renders it difficult or impossible to understand a lexical item without additional information. The goal of semantic web research is to allow the vast range of web-accessible information and services to be more effectively exploited by both humans and automated tools. Technological advancement has given rise to scholars developing automated translation systems from English to the Yorùbá language. However, the problem arises that these tools are not coping easily with semantic nuances found especially in Yorùbá verbs. To explore this problem, a number of Yorùbá lexical ambiguous verbs which may pose serious challenges to the existing machine translation tools were generated and analyzed. To facilitate a solution to the problem, the identified verbs are annotated following the Qualia Structure (QS) of the Generative Lexicon. Protégé 4.5 is employed as the editing tool to map the semantic interpretations of the QS to the semantic web. With the aid of the unique formal specification implemented for each of the lexically ambiguous verbs, the existing automated translation system can now utilize the Internationalized Resource Identifier (IRI) of the Unified Resource Locator (URL) found in the model developed to link the loop and thereby alleviate the problem of ambiguity for the automated translation system. This paper, therefore recommends that more efforts be geared towards ontological annotation in order to foster more automated tools that will be built for the Yorùbá language.
Àgbéyẹ̀wò “Digital Nollywood” (Ọ̀ rọ̀ láti ẹnu àwọn àgbà òṣèré) àti “Ògbóǹtarìgì”
Authors: Adeoba ‘Gbenga
Published: May 2023

Digital Nollywood jẹ́ iṣé ìwádìí dígítà tí ó bẹ̀ rẹ̀ ní 2018 láti ṣe àgbékalè ìtàn fíìmù ní Nàìjíríà. Ìlànà ìwádìí yìí ń ṣe àmúlò àwọn ohun àfojúrí àti àwọn ìwé àlẹ̀ móde tí wọ́ n fi ṣe ìpolówó àwọn fíìmù, pàápàá jù lọ ní ikọ̀ fíìmù tí a mọ̀ sí Nollywood. Fún iṣẹ́ Digital Nollywood, a rí àwọn ohun èlò àfojúrí àti ìwé àlẹ̀ móde wọ̀ nyí gẹ́ gẹ́ bíi iṣẹ́ ọnà tí ó wúlò fún ìṣèwádìí iṣẹ́ ìtàn Nollywood ní ọ̀ nà tí ó yàtò. Ní oríṣiríṣi ọ̀ nà, iṣẹ́ yìí ń lo àwọn ìwé àlẹ̀ móde wọ̀ nyí láti ṣe àgbékalè ìtàn àwọn ohun ìkéde tí ó ṣe àmúlò àwọn nǹkan tí ó jé tiwantiwa. Ní ìtají sí bí àwọn ohun èlò àfojúrí àti ìwé àlẹ̀ móde wọ̀ nyí ti ṣe ń di àwátì, iṣẹ́ yìí ń ṣe àmúlò àwọn ìtẹ̀ síwájú tí ó pemọ́ ìmọ̀ ẹ̀ rọ láti wo àwọn ọ̀ nà míràn tí a lè gbà se iṣẹ́ ìwádìí ìtàn tàbí se àgbéyèwò àṣà àti ìṣe ní ilè Africa. Nípasẹ̀ àmúlò ohun àgbéjáde ayélujára, Digital Nollywood ní èrò láti di iṣẹ́ ìwádìí dígítà tí ó ń ṣe ìdásí àti ìtẹ́ pẹpẹ ìwé àlẹ̀ móde àwọn fíìmù Nollywood nípasẹ̀ àgbàjọ àwọn ìwé wọ̀ nyí ní orí pẹpẹ Omeka.
PENGUKUR KEJENUHAN OKSIGEN DALAM DARAH BERBASIS ANDROID
Authors: Rosiana Elfirza , Dinata Seflahir , Cahya saputra Rivaldy
Published: May 2023

Penyakit Coronavirus 2019 (COVID-19) adalah keadaan darurat kesehatan masyarakat. Beberapa pasien mungkin hadir dengan happy hipoksia, suatu kondisi dimana pasien memiliki saturasi oksigen rendah (SpO2 <90%), tetapi tidak mengalami gangguan pernapasan yang signifikan dan seringkali tampak baik secara klinis. Ketersediaan alat pengukur kejenuhan oksigen dalam darah menjadi hal penting yang harus dimiliki masyarakat dan pusat kesehatan masyarakat. Hasil pengukuran yang dapat dikirim ke petugas kesehatan atau dokter secara langsung menjadi keharusan sebagai tindakan preventif. Penelitian ini bertujuan mengembangkan sistem pengukuran kejenuhan oksigen dalam darah (oksimeter) non-invasive dengan metode fotopletismografi berbasis android. Metodologi penelitian ini memanfaatkan sensor oximetry, data tegangan dari sensor dikirimkan ke arduino dan raspberry untuk diproses sehingga menghasilkan nilai SpO2 dan detak jantung. Hasil analisa alat pulse oximetry yang telah dibuat menunjukan hasil yang baik dengan perolehan akurasi sebesar 98.62% dan error rata-rata sebesar 1.378% untuk pengukuran SpO2. Pengukuran detak jatung pada alat ini memiliki error rata-rata sebesar 2.34%. Hasil pengukuran dapat dikirimkan secara jarak jauh melalui android dengan memanfaatkan aplikasi Blynk.Kata kunci : oximeter; detak jantung; non-invasive; SpO2; Android
„Reziliens Ukrajna” és a háború narratívái Európában
Authors: Reid Julian
Published: May 2023

Az egyik fő narratíva, amelynek révén (legalábbis a nyugati világban) az ukrajnai háborút keretbe foglalták, Ukrajna rezilienciája volt. Például Antony Blinken, az Egyesült Államok külügyminisztere a BBC-nek adott, 2022. március 5-én megjelent interjújában az orosz katonai erők ellen harcoló hétköznapi ukránok „rendkívüli rezilienciáját” dicsérte (BBC 2022). A nyugati média tele volt az ukránokat az orosz invázióval járó rendkívüli viszontagságokkal szemben „reziliensnek” minősítő híradásokkal (Sauer 2022). Közben olyan képek keringtek, amelyeken a civil ukránok ellenállnak az orosz katonai erőknek, Molotov-koktélokat dobálnak az ellenséges tankokra és orosz katonai járművekre vizelnek (India Herald 2022). Ikonikus módon a Time magazin március 28-i számának borítóján, amelyen „A reziliens Ukrajna” főcím szerepelt, egy ukrán menekült gyermekről készült 45 méteres fotó képe látható, amelyet több mint száz ember tartott fel a lvovi operaház előtt (Time 2022). Mindezek hozzájárultak az Ukrajna kiemelkedő rezilienciájáról alkotott kép elterjedéséhez. Maguk az ukránok is továbbírták ezt a narratívát azzal, hogy hangsúlyozták saját rezilienciájukat. Ahogyan egy ukrán politikai elemző, Roman Rukomeda fogalmazott: „[Ez a] háború nagy megvilágosodás az ukránok számára önmagukról és rezilienciájukról. Következetesen alábecsültük a jellemünket, a kölcsönös támogatásra való készségünket, az egymás iránti empátiánkat és értékeinket” (Rukomeda 2022).
The anatomical position of the vermiform appendix and its morphometry in relation to the extension of the mesoappendix: a study on fresh cadavers
Authors: Aragão José Aderval , Aragão Iapunira Catarina Sant’Anna , Aragão Felipe Matheus Sant’Anna , Lourenço Bárbara Costa , Kuhn Caio Siqueira , Munaretto Giovanna Freitas , Guerra Danilo Ribeiro , Feitosa Vera Lúcia Correa , Reis Francisco Prado
Published: May 2023

Introduction: the Vermiform Appendix (VA) is a highly variable organ, being an enigma for the surgeon regarding its position, size and symptomatology. Rapid and accurate diagnosis for adequate treatment of acute appendicitis not only depends on the symptoms, but also on the knowledge of variations in its anatomical position. Objective: to determine the occurrence of the anatomical position of the VA in fresh cadavers, its relationship with the mesoappendix and morphometry. Material and method: the Vermiform Appendages (VAs) of 50 fresh cadavers were examined, the morphological aspects and morphometry of the VAs were studied, such as: position, length and diameter of the appendix, in addition to the length of the mesoappendix and whether it occupied the entire length of the appendix length. Morphometric data were performed with a digital caliper with a precision of 0.01 mm. Result: of the 50 cadavers autopsied during the study, 44 (88%) were male and six (12%) were female. Age ranged from 14 to 80 years, with an average of 36.8 years. Regarding the biotype, 44% (22) were athletic, 32% (16) leptosomic and 24% (12) pycnic. The VA was located in six different positions, with the pelvic and retrocecal positions being the most prevalent. The mesoappendix occupied, in 92% of the cases, the entire length of the VA. Conclusion: the most frequent position of the VA was the pelvic type. Knowledge about the anatomical position of the appendix and the complete mesoappendix in the population can contribute significantly to improving the early clinical diagnosis of appendicitis and, consequently, reducing morbidity.
ملامح التطور والتجديد في غزليات العصرين الإسلامي والاموي
Authors: عبد علي م.د عبد الحسين برغش
Published: May 2023

6
MÁQUINAS QUE CIRCULAM AFETOS E POSSÍVEIS CURTOS
Authors: Muniz Fernandes Arthur , Nobre Fábio Rodrigo Ferreira
Published: May 2023

Ensaio-teórico com o objetivo de compreender como os circuitos de afetos são postos em movimento por Máquinas Abstratas e Concretas, refletindo acerca do efeito deste processo mundial no campo do desejo, na formação dos corpos e na produção das identidades. E a partir de tal reflexão, tecer considerações sobre possíveis curtos-circuitos na maquinaria de captura dos desejos e controle dos corpos, abrindo os territórios para outras linhas afetivas que sejam balizadas não no poder, mas na potência, não em afetos passivos ou tristes, mas ativos e alegres, em especial, por sobre dois campos, na produção de Máquinas de Anti-Captura e conquista do devir na superfície de nossas peles enquanto produção de uma ética de si, com o objetivo de liberar as próprias máquinas desejantes que nos compõem, como também nas superfícies das estruturas burocráticas, imaginando como perverter os dispositivos concretos construídos para a captura, disciplina e controle, os utilizando para o seu inverso.

Palavras-chave: Circuito dos Afetos; Máquinas Abstratas; Máquinas Concretas; Devir; Micropolítica.
Stochastic simulations of the Schnakenberg model with spatial inhomogeneities using reactive multiparticle collision dynamics
Authors: Sayyidmousavi Alireza , Rohlf Katrin
Published: May 2023

A numerically efficient globally averaged number density approach is used to simulate a reaction-diffusion system using a particle-based stochastic simulation algorithm called reactive multiparticle collision (RMPC) dynamics. Constant diffusivity of the particles is achieved through a time-varying rotation angle (also called collision angle). Variation in the diffusion coefficient between two different chemical species is achieved in one of two ways: (ⅰ) using a different kBT/m value for one species compared to the other, or (ⅱ) using the same kBT/m value for both species, but using a different probability to free-stream for one species compared to another. For smaller diffusivities and larger spatial inhomogeneities, bath particles were necessary for the model to agree with the PDE solution. The latter approach was further used without a bath, and shown to be capable of producing Turing patterns after long simulation times. The significance of our work is that RMPC can serve as a feasible simulation tool for both short and long-term simulations, can handle spatial inhomogeneities, can model a fairly large range of diffusivities in a reaction-diffusion scenario, and is capable of producing Turing patterns. An advantage of this method includes more detailed system information in feasible simulation times.
Spiral Wave Dynamics in Excitable Media with Spherical Geometries
Authors: Rohlf Katrin , Glass Leon , Kapral Raymond
Published: May 2023

We describe the spatial and temporal organization of spiral and scroll waves in spherical shells of different sizes and solid spheres. We present simulation results for the evolution of the dynamics and clustering of spiral waves as a function of the excitability of the medium. The excitability, topology, and size of the domain places restrictions on how single and multiarmed spiral waves are organized in space. The results in spherical geometries are compared with those in planar twodimensional media. These studies are relevant to the dynamics of spiral waves in a variety of media including the heart, and chemical reactions on spherical surfaces. 
Paediatric pandemic planning: children’s perspectives and recommendations
Authors: Koller Donna
Published: May 2023

Children, as major stakeholders in paediatric hospitals, have remained absent from discussions on important healthcare issues. One critical area where children’s voices have been minimised is in the planning for future pandemics. This paper presents a subset of data from a programme of research which examined various stakeholder experiences of the severe acute respiratory syndrome (SARS) outbreaks of 2003. These data also generated recommendations for future pandemic planning. Speciﬁcally, this paper will examine the perspectives and recommendations of children hospitalised during SARS in a large paediatric hospital in Canada. Twenty-one (n = 21) child and adolescent participants were interviewed from a variety of medical areas including cardiac (n = 2), critical care (n = 2), organ transplant (n = 4), respiratory medicine (n = 8) and infectious diseases (patients diagnosed with suspected or probable SARS; n = 5). Data analyses exposed a range of children’s experiences associated with the outbreaks as well as recommendations for future pandemic planning. Key recommendations included speciﬁc policies and guidelines concerning psychosocial care, infection control, communication strategies and the management of various resources. This paper is guided by a conceptual framework comprised of theories from child development and literature on children’s rights. The authors call for greater youth participation in healthcare decision-making and pandemic planning.
School reintegration following hospitalisation for children with medical complexity and chronic disease diagnoses: a scoping review protocol
Authors: Burns Samantha , Doering Katie , Koller Donna , Stratton Catherine
Published: May 2023

Introduction 

Schools play a significant role in children’s social, emotional and intellectual well- being. For children with medical complexity (CMC) and chronic disease diagnoses (CDD), an absence from school due to prolonged hospitalisation places them at risk for greater social exclusion and poorer academic outcomes than their healthy counterparts. Processes that support the school reintegration of children with complex and chronic medical conditions currently lack consistency and identified evidence- based practices. This scoping review aims to integrate the relevant literature on current reintegration procedures as well as assess stakeholders’ perceived challenges related to children with CMC and CDD’s return to school following hospitalisation. Finally, information will be synthesised regarding parental and child involvement in reintegration strategies. 

Methods and analysis 

The current scoping review follows the five- stage framework proposed by Arksey and O’Malley (2005). The search syntax will be applied in Medline, Web of Science, PsycInfo, Education Resource, ERIC, CINAHL and SocIndex. Peer- reviewed journal articles will be included without the restriction of publication year or language. However, only children and adolescents aged 4–18 with CMC and CDD, who have been out of school for 2 weeks or more and reintegrated into a non- hospital school setting will be included. Articles will be screened by two authors based on the outlined eligibility criteria. Data will be summarised qualitatively and where applicable, visualisation techniques such as tables, graphs and figures will be implemented to address approaches, strategies and outcomes related to reintegration to school following hospitalisation. 

Ethics and dissemination 

The current study comprises available publications and does not collect primary data. For this reason, ethics approval is not necessary. The results of this scoping review will be prepared and submitted for publication in a peer- reviewed journal and presented at future conferences to key stakeholders focusing on educational accessibility and inclusion.
The voices of children and young people during COVID-19: A critical review of methods
Authors: Jorgensen Eva , Koller Donna , Raman Shanti , Olatunya Oladele , Asemota Osamagbe , Ekpenyong Bernadine N. , Gunnlaugsson Geir , Okolo Angela
Published: May 2023

Aim 

Critically review research methods used to elicit children and young people's views and experiences in the first year of COVID-19, using an ethical and child rights lens. 

Methods 

A systematic search of peer-reviewed literature on children and young people's perspectives and experiences of COVID-19. LEGEND (Let Evidence Guide Every New Decision) tools were applied to assess the quality of included studies. The critical review methodology addressed four ethical parameters: (1) Duty of care; (2) Children and young people's consent; (3) Communication of findings; and (4) Reflexivity. 

Results 

Two phases of searches identified 8131 studies; 27 studies were included for final analysis, representing 43,877 children and young people's views. Most studies were from high-income countries. Three major themes emerged: (a) Whose voices are heard; (b) How are children and young people heard; and (c) How do researchers engage in reflexivity and ethical practice? Online surveys of children and young people from middle-class backgrounds dominated the research during COVID-19. Three studies actively involved children and young people in the research process; two documented a rights-based framework. There was limited attention paid to some ethical issues, particularly the lack of inclusion of children and young people in research processes. 

Conclusion 

There are equity gaps in accessing the experiences of children and young people from disadvantaged settings. Most children and young people were not involved in shaping research methods by soliciting their voices.

 
Patient disclosure of medical errors in paediatrics: A systematic literature review
Authors: Koller Donna , Rummens J Anneke , Le Pouesard Morgane , Espin Sherry , Friedman Jeremy , Coffey Maitreya , Kenneally Noah
Published: May 2023

Medical errors are common within paediatrics; however, little research has examined the process of disclosing medical errors in paediatric settings. The present systematic review of current research and policy initiatives examined evidence regarding the disclosure of medical errors involving paediatric patients. Peer-reviewed research from a range of scientific journals from the past 10 years is presented, and an overview of Canadian and international policies regarding disclosure in paediatric settings are provided. The purpose of the present review was to scope the existing literature and policy, and to synthesize findings into an integrated and accessible report. Future research priorities and policy implications are then identified. 