bluuebunny/crossref_metadata_2025_split huggingface dataset:
Collective Cyberbullying Ditinjau dari Psikologi Sosial
Authors: Yasmin Sahnaz Almuntaha  , Ikhwanul Ihsan Armalid  
Published: July 2023

With the development of communication technology, the use of social media in Indonesia is also increasing. The high use of social media has led to an increase in various criminal behaviors, such as cyberbullying. Cyberbullying is the act of insulting or hurting others through social media. This widespread social media influence can turn the influence of behavioral transmission on other users into collective behavior (collective cyberbullying). This case has had a very negative impact on aspects of the victim’s life. Therefore, literature review research is carried out in order to know the specific factors and impact of collective cyberbullying from the perspective of social psychology. The results of this study show that there are several key factors, including technological development, individual psychology, community understanding, and social and environmental influences. This form of cyberbullying behavior can also be explained based on the transmission theory of Gustav Le Bon, where there are three mechanisms that influence the formation of collective behavior: anonymity, transmission, and ease of being influenced. The impact on victims was then categorized into four categories: psychological, psychosocial, academic, and physical.Abstrak
Seiring berkembangnya teknologi komunikasi semakin tingginya juga penggunaan media sosial di masyarakat Indonesia. Tingginya penggunaan media sosial mengakibatkan meningkatnya berbagai perilaku kejahatan seperti cyberbullying. Cyberbullying merupakan perilaku menghina atau menyakiti orang lain melalui media sosial. Pengaruh media sosial yang luas ini dapat menimbulkan pengaruh penularan perilaku pada pengguna lain menjadi sebuah perilaku kolektif (collective cyberbullying). Kasus ini membawa dampak buruk yang sangat berpengaruh pada aspek kehidupan korban. Oleh karena itu, penelitian literature review dilakukan agar dapat mengetahui faktor dan dampak spesifik pada collective cyberbullying yang ditinjau dari perspektif Psikologi Sosial. Hasil penelitian ini menunjukkan bahwa terdapat beberapa faktor utama antara lain perkembangan teknologi, psikologis individu, pemahaman masyarakat, dan pengaruh lingkungan sosial. Bentuk perilaku cyberbullying ini juga dapat dijelaskan berdasarkan Teori Penularan milik Gustav Le Bon, dimana terdapat tiga mekanisme yang mempengaruhi pembentukkan perilaku kolektif, yaitu anonimitas, penularan, dan kemudahan untuk dipengaruhi. Kemudian dampak pada korban dikategorikan menjadi empat kategori, yakni dampak psikologis, psikososial, akademik, dan fisik.
Ujaran Kebencian dalam Perspektif Teori Kepribadian dalam Psikologi
Authors: Amelia  , Nafidatul Mauliyah  , Raissa Dwifandra Putri  
Published: July 2023

The development of social media makes it easy to communicate remotely. Apart from making it easier, social media is often used by some individuals to express anger in the form of utterances of hate towards others. Hate speech is a derogatory speech about personal or group characteristics, such as race, religion, gender, or even sexual orientation. Various factors can underlie this behavior. Meanwhile, the purpose of this study is to examine hate speech from the perspective of personality theory in psychology. The method used for data collection is a literature study. The results of this study indicate that hate speech can occur as a form of expression of emotions and conflicts that are not resolved in a person's subconscious mind. These unresolved conflicts and emotions lead to anxiety and psychological distress. Hate speech can appear as a form of a defense mechanism known as displacement. In addition, hate speech can also be done only for personal pleasure (trolling). This is used by individuals because their basic needs to feel safe and valued in everyday life are not met so individuals will develop basic anxiety which eventually leads to compulsive, neurotic, or aggressive behavior patterns, like trolling.
Abstrak
Perkembangan media sosial memberikan kemudahan untuk berkomunikasi dengan jarak jauh. Selain memudahkan, media sosial sering kali digunakan oleh beberapa individu untuk meluapkan kemarahan dalam bentuk ujaran kebencian kepada orang lain. Ujaran kebencian atau hate speech adalah ucapan yang menghina tentang karakteristik pribadi atau kelompok, seperti ras, agama, jenis kelamin, atau bahkan orientasi seksual. Beragam faktor dapat mendasari perilaku ini. Adapun, tujuan penelitian ini adalah mengkaji ujaran kebencian dalam perspektif teori kepribadian dalam psikologi. Metode yang digunakan untuk pengumpulan data yaitu studi literatur. Hasil dari penelitian ini menunjukkan bahwa ujaran kebencian dapat terjadi sebagai bentuk ekspresi dari emosi dan konflik yang tidak selesai dalam pikiran bawah sadar seseorang. Konflik dan emosi yang tidak terselesaikan ini menyebabkan kecemasan dan tekanan psikologis. Ujaran kebencian dapat muncul sebagai bentuk mekanisme pertahanan yang disebut sebagai pelampiasan (displacement). Selain itu, ujaran kebencian dapat juga dilakukan hanya untuk kesenangan pribadi (trolling). Hal ini digunakan individu sebab kebutuhan dasar mereka akan rasa aman dan dihargai di kehidupan sehari-hari tidak terpenuhi sehingga individu akan mengembangkan kecemasan dasar yang akhirnya memunculkan pola perilaku kompulsif, neurotik, atau agresif salah satunya seperti trolling.
Keterkaitan Demensia dan Penyakit Parkinson pada Manusia
Authors: Fadli Kamuli  , Faiz Yunsar Hammam  , Haikal Al Hafidz  , Iqlima Pratiwi  
Published: July 2023

Dementia is a disease that can have lasting effects on sufferers. The vulnerable group for dementia is the elderly. Based on the scale, the elderly aged 70 years and over occupy the second highest position at 5.4%. Dementia has a progressive nature for the sufferer, where this can cause disturbances to the sufferer, such as cognitive decline to disturbances in the motor system so that in the end it will cause a disease called Parkinson's. The purpose of this study is to examine the relationship between dementia and Parkinson's in individuals. The method used is through a literature review. The results show that Parkinson's itself is a disease caused by a disturbance of the brain's nerves which triggers motor disturbances which are triggered by a dead or disrupted neuron system. Usualy Parkinson's disease is synonymous with symptoms of tremor when resting, rigidity, bradykinesia, and reduced or even loss of reflexes from body posture. The patient's risk of dementia and PD (Parkinson Disease) can be predicted by reviewing the visual size and retinal GCL (glion cell layer) and IPL (inner plexiform layer) volume. This examination includes an eye examination, retinal imaging with optical coherence tomography, visual assessments such as acuity and contrast sensitivity, visuoperception measures high levels of tilt tolerance and biologic movements.
AbstrakDemensia merupakan suatu penyakit yang dapat menyebabkan efek berkelanjutan pada penderitanya. Kelompok rentan terhadap penyakit demensia ialah lansia. Lansia berdasarkan skala di usia 70 tahun ke atas menduduki posisi kedua tertinggi senilai 5,4%. Demensia memiliki sifat progresif bagi para penderitanya yang di mana hal ini dapat memberikan gangguan pada penderitanya seperti adanya penurunan kognitif hingga gangguan terhadap sistem motorik sehingga pada akhirnya nanti akan menyebabkan salah satu penyakit bernama Parkinson. Adapun tujuan dari penelitian ini ialah untuk mengkaji keterkaitan antara demensia dan parkinson pada individu. Metode yang digunakan ialah melalui kajian literatur. Hasil menunjukkan bahwa Parkinson sendiri merupakan sebuah penyakit yang disebabkan adanya gangguan saraf otak yang memicu adanya gangguan motorik yang dipicu karena adanya sistem neuron yang mati atau terganggu. Biasanya penyakit Parkinson identik dengan gejala tremor ketika beristirahat, rigiditas, bradikinesia, dan berkurang atau bahkan hilangnya refleks dari postural tubuh. Risiko demensia dan PD (Parkinson Disease) pasien dapat diprediksi melalui peninjauan ukuran visual dan GCL (lapisan sel glion) retina dan volume IPL (lapisan pleksiform dalam). Pemeriksaan ini dilalui dengan diantaranya pemeriksaan mata, pencitraan retina dengan tomografi koherensi optik, penilaian visual seperti ketajaman dan sensitivitas kontras, ukuran visuoperception tingkat tinggi toleransi miring dan gerakan biologis.
AS ABORDAGENS DO CAMPO DE HISTÓRIA DA SAÚDE NO ENSINO BÁSICO DE HISTÓRIA
Authors: MARINHO JOSEANNE ZINGLEARA SOARES , NERY ANA KAROLINE DE FREITAS 
Published: July 2023

Na Educação Básica a disciplina História possui como uma prerrogativa relevante oportunizar que os discentes possam conhecer as condições do presente a partir das especificidades identificadas no processo histórico com a finalidade de estarem preparados para analisar, refletir e atuar no cenário social. É nesse contexto que o campo da história da saúde torna-se significativo como abordagem na disciplina História, já que a partir dos conteúdos expressos na iconografia e textualidade ocorre a vinculação com as intercorrências do tempo presente, particularmente a partir da pandemia de Covid-19. Considerando-se a análise dos quatro volumes que compõem a Coleção Projeto Mosaico-História de livros didáticos do 6º ao 9º ano do Ensino Fundamental, verificaram-se as possibilidades de abordagens das temáticas de história da saúde, considerando uma produção acadêmica que também pode estar presente nas aulas do Ensino Básico de História.
Résistance à la sécheresse de mollusques du genre <em> Bulinus </em> vecteurs de trématodoses humaines et animales au Sénégal. II. Etude dans les conditions naturelles en zone Nord-soudanienne. Ecologie et résistance à la sécheresse de <em> Bulinus umbilicatus </em> et <em> B. sene </em>
Authors: Diaw O.T. , Seye M. , Sarr Y. 
Published: July 2023

Les auteurs rapportent les résultats d'une étude de 2 ans sur l'écologie et la résistance à la sécheresse de B. umbilicatuset B. senegalensisdans 3 mares temporaires de la zone Nord-soudanienne (région de Tamba­ counda, Sénégal). Les variations de certains facteurs abiotiques comme la température et le pH de l'eau ne semblent pas avoir une grande influence sur l'écologie, alors que la pluviométrie a une grande importance sur la distribution et la densité des Mollusques. En effet, la quantité d'eau et la durée d'assèchement des mares dépendent des pluies et sont des éléments qui gouvernent l'existence et la survie de cette faune malacologique. C'est dans la 2ème partie de la saison des pluies, période de reproduction, que la population atteint son maximum. Les observations mensuelles montrent que l'abondance relative de B. umbilicatus est supérieure à celle de B. senegalensis. Ces mares sont à sec 6 à 8 mois dans l'année, et cependant, les populations de Mollusques se renouvellent régulièrement, ce qui laisse supposer une capacité de résistance à la sécheresse. Certains traversent avec succès cette période d'as.sèchement mais ce sont ceux de taille moyenne (7 à 9,9 mm) qui résistent le mieux (70 à 80 p. 100 de la population). Dès la remise en eau, ils reprennent leur activité et pondent intensément afin de reconstituer la population. B. umbilicatus et B. senegalensis sont des hôtes intermédiaires potentiels de trémato­ doses humaines, mais dans cette zone étudiée, seul B. umbilicatus intervient dans la transmission (S. haematobium, S. curassom) qui a lieu entre septembre et novembre. Dans les conditions naturelles du Sahel, le cycle épidémiologique est court, et tout se passe en 4 à 6 mois avec renouvellement et accroissement de la population de Mollusques, infestation de ces derniers et transmission des trématodoses. Le comportement écologique de ces Mollusques dans la zone Nord­ soudanienne a une importance primordiale dans l'épidémiologie des trématodoses humaines et animales et nécessite une nouvelle stratégie de lutte. La destruction des Mollusques est plus efficace et plus économique à la fin de la saison des pluies, début d'assèchement de la mare, période où ils se concentrent dans des flaques d'eau résiduelles.
Assessing the impact of pregnancy and birth factors on the maternal and infant microbiota
Authors: Al Kait F , Allen Laura , Bedell Samantha , Burton Jeremy P , de Vrijer Barbra 
Published: July 2023

Background: The microbiota acquired at birth is known to play an intimate role in later life health and disease and has been shown to be affected by the mode of birth. There has been recent interest in microbiota correction by maternal vaginal seeding in Cesarean section-born infants; however, the safety of this practice has been debated. The aim of this study was to assess how other factors, such as timing of sampling, maternal obesity, vaginal Group B Streptococcus colonization (GBS), and antibiotic exposure, affect the maternal and infant microbiota.
Methods: Maternal vaginal and saliva samples were collected at three time periods: 35-37 weeks gestation (prenatal), within 24-36 hours after birth (birth), and at ~6 weeks postpartum. Infant saliva and stool samples were collected at ~6 weeks postpartum. 16S rRNA amplicon sequencing was utilized to assess the taxonomic and inferred functional compositions of the bacterial communities from both mothers and infants.
Results: Samples from 36 mothers and 32 infants were obtained. Gestational age, breastfeeding, mode of birth, and gravidity were associated with taxonomic alterations in the infant samples, while obesity, antibiotic use, and GBS status were not. Maternal samples were predominantly affected by time, whereby significant alterations including increased microbial diversity were seen at birth and persisted to 6 weeks postpartum.
Conclusion: This study provides information on the relationship between health and delivery factors and changes in vaginal and infant microbiota. These results may better direct clinicians and mothers in optimizing the infant microbiota towards health during infancy and later life.
A Sustainability Model for a Municipal Entity
Authors: Brink Floyd Warren , Singh Shamila 
Published: July 2023

The main purpose is to create a model for managing sustainability in the metro and its entities in Gauteng. Within this context, the study will focus on the issue of measures, outcomes, and impacts in the City of Johannesburg (CoJ). The study will clarify a public sector application in municipal entities of the CoJ because sustainability is not well understood or used in the public sector. This article investigates the sustainability phenomena in a metropolitan setting, including the CoJ and its municipal entities. The purpose is rather two-fold. A focus group discussion was held with CoJ senior executive managers to provide feedback on the sustainability model. The information and insights were used to refine the sustainability model to manage sustainability in Coj and its enti-ties. The data was analysed using thematic analysis to refine the sustainability model. The re-sults indicated that sustainability is a function of having a shared understanding of sustainabil-ity, the ability to mainstream and integrate sustainability thinking into all programmes and ac-tivities, leadership commitment, requisite competencies, and monitoring and evaluation of sus-tainability.
The implication for leadership is to ensure the alignment of sustainability to the strategic objec-tives of CoJ and to foreground any planning in CoJ with a sustainability lens. Achieving this focus requires a shared understanding, development of competencies, committed leadership to imple-ment measurement and impact framework, and adjusting plans based on monitoring and evalua-tion outcomes.
Toward Effective Framework for Wireless Intrusion Detection System in Detecting Krack and kr00k attacks in IEEE 802.11
Authors: Salah Zaher , Abu Elsoud Esraa 
Published: July 2023

The rise in Internet users has brought with it the impending threat of cybercrime as the Internet of Things (IoT) increases and the introduction of 5G technologies continues to transform our digital world. It is now essential to protect communication networks from illegal intrusions in order to guarantee data integrity and user privacy. In this situation, machine learning techniques used in data mining have proven to be effective tools for constructing intrusion detection systems (IDS) and improving their precision. We use the well-known AWID3 dataset, a comprehensive collection of wireless network traffic, to investigate the effectiveness of machine learning in enhancing network security. Our work primarily concentrates on the Krack and Kr00k attacks, which target the most recent and dangerous flaws in IEEE 802.11 protocols.
Through diligent implementation, we were able to successfully identify these threats using an IDS model that is based on machine learning. Notably, the resilience of our method was demonstrated by our Ensemble classifier’s astounding 99% success rate in detecting the Krack attack. The effectiveness of our suggested remedy was further demonstrated by the high accuracy rate of 96.7% displayed by our Neural Network-based model in recognizing instances of the Kr00k attack. Our research shows the potential for considerably boosting network security in the face of new threats by leveraging the capabilities of machine learning and a diversified dataset. Our findings open the door for stronger, more proactive security measures to protect IEEE
802.11 networks’ integrity, resulting in a safer online environment for all users.
Orbital Learning: A Novel, Actively Orchestrated Decentralised Learning for Healthcare
Authors: Chakshu Neeraj Kavan , Nithiarasu Perumal 
Published: July 2023

Abstract

A novel collaborative and continual learning across a network of decentralised healthcare units, avoiding identifiable data-sharing capacity, is proposed. Currently available methodologies, such as federated learning and swarm learning, have demonstrated decentralised learning. However, the majority of them face shortcomings that affect their performance and accuracy. These shortcomings include a non-uniform rate of data accumulation, non-uniform patient demographics, biased human labelling, and erroneous or malicious training data. A novel method to reduce such shortcomings is proposed in the present work through selective grouping and displacing of actors in a network of many entities for intra-group sharing of learning with inter-group accessibility. The proposed system, known as Orbital Learning, incorporates various features from split learning and ensemble learning for a robust and secure performance of supervised models. An example of ECG classification for arrhythmia with 6 clients is used to analyse its performance and is compared against federated learning. In this example, four separate experiments are conducted with varied configurations, such as varied age demographics and clients with data tampering. The results obtained show an average area under receiver operating characteristic curve (AUROC) of 0.819(95% CI: 0.784 – 0.853) for orbital learning whereas 0.714(95% CI: 0.692 – 0.736) for federated learning. This result shows an increase in overall performance and establishes that the proposed system can address the majority of the issues faced by existing decentralised learning methodologies.
Analysis of Path finding techniques for flying robots through intelligent decision making algorithms in Quantum inspired computing environment
Authors: Maity Ritu , Mishra Ruby , Pattnaik Prasant Kumar 
Published: July 2023

Abstract

Path planning is one of the most significant and challenging parts in the development of unmanned aerial vehicles. Over years many path-planning techniques are proposed and are being successfully used in various fields. Intelligent algorithms can be used for building autonomous drones. Though a number of algorithms haven been proposed in past few years but there is lack of research papers which compares different path planning algorithm and to find the optimal one by considering important parameters required for path planning of flying robot. Here we have used five varieties of algorithms ie ABC, ACO, PSO Quantum PSO, and hybrid algorithm which is a combination of ABC and PSO for path planning of our developed fixed-wing type flying robot for operating inside a closed room environment. We have used the quantum-inspired computing method as its search performance is better as compared to classical techniques. Then we tried to compare and find the best algorithm for our flying robot out of the above five algorithms using multi-criteria decision making (MCDM) and TOPSIS where the following parameters like minimum cost, the shortest path traveled, and the least time taken were considered to find the most relevant results for autonomous flying robot path planning.
A grid and consensus based privacy preservation scheme for crowdsensing
Authors: Zheng Xiao dong , Cui Lianhe , Yuan Qi , Feng Guangsheng 
Published: July 2023

AbstractIn the process of task allocation in crowdsensing, the precise location of the sensing initiator or the location of the sensing user may be released to each other, which will violate the privacy of various users in crowdsensing. Thus, in order to cope with the problem of privacy leakage in crowdsensing, and further deal with the problem of inconformity in feeding back results, in this paper, a privacy preservation scheme for crowdsensing which is based on the conception of division grids and distributed consensus (short for GDDCC) has been proposed. In this scheme, the region used to publish sensing tasks is divided into smaller girds with enough sensing users, and a sub-area with sensing grids is sent to all users in this region. Then sensing users in each grid unify their sensing results and send the consensus result as the precise result to the sensing initiator. As a result, during the process of crowdsensing, the sensing initiator does not know the precise location of the sensing user and the sensing user does not know the precise location of the sensing initiator, so the privacy of each entity in the crowdsensing is preserved. In addition, the idea of prefix membership verification is used to preserve the privacy of sensing users in the same grid during the process of result consensus. Then in the section of security analysis, the privacy security of each entity is analysed, and in the section of performance analysis, experimental results with elaborate reasons are given to further demonstrate the superiority of the proposed GDDCC.
A Novel Algorithm for Pre-Processing of WT Blade Images by SS and Bilateral Filter with Machine Learning Frameworks
Authors: Chen Joy I. Z. , Lee Chien-Yeh 
Published: July 2023

Abstract
This article is based on the motivation of turbine migration, selects high-dimensional data from the data set of WT (wind turbine) blades, overfitting and strict feature selection are the three keys to solving the problem of NN (neural network) computing systems. For the above-mentioned conflicting problem, in this study, the characteristics of the WT including the similarity in the color of WT blades and the difference in shape are deployed to evaluate the performance of the machine learning system. Therefore, the pre-processing with Bilateral filter is applied to join with the SS (selective synthesizer) of blade fouling patterns are proposed where adopts the framework of ResNet50 to examine the computational efficiency in the study. The experimental results verify that according to the feature selection after the introduction of the SS method, the accuracy rate of the NN model can reach higher than 92%. Finally, it is found that when the proposed CC (correlation coefficient) and SS are combined, the image pre-processing of the machine learning image data model can show the most significant feature selection performance. For the purpose of data validation, the YOLO (Only Look Once) deep learning framework. The reason for using YOLOv4-Tiny is that the current YOLO framework can obtain a compromise balance and practical recognition in terms of affecting the recognition speed and accuracy rate. Moreover, it has been integrated with the edge computing hardware Nvidia Jetson Nano.