bluuebunny/crossref_metadata_2025 huggingface dataset:
Imbalanced image classification algorithm based on fine-grained analysis
Authors: Pingping Liu , Yuhan Chen , Xiaoyu Xie , Xiaokang Yang
Published: October 2024

Fine-grained attribute analysis and data imbalance have always been research hotspots in the field of computer vision. Due to the complexity and diversity of fine-grained attribute images, traditional image classification methods have shortcomings in paying attention to fine-grained attributes of images and perform poorly when dealing with imbalanced data sets. To overcome these problems, this study proposes a fine-grained image threshold classification algorithm based on deep metric learning. By introducing a metric learning method, the focus on fine-grained attributes of images is enhanced. At the same time, by applying pairwise loss and proxy loss, the classification accuracy of the model is improved and the model convergence speed is accelerated. In order to deal with the problem of data imbalance, a classifier based on threshold analysis is designed. The classifier uses threshold analysis technology to achieve multi-level classification of fine-grained images, thereby improving the problem of low classification accuracy of a few categories in imbalanced data sets. Experimental results show that the proposed fine-grained image threshold classification algorithm based on deep metric learning is significantly superior to other methods in terms of classification accuracy.
Graph node classification algorithm based on similarity random walk aggregation
Authors: Xiangjiu Che , Yupeng Sun
Published: October 2024

Aiming at the relatively low accuracy of methods such as MLP and GCN in heterogeneous graph node classification tasks, this paper proposes a graph neural network based on similarity random walk aggregation (SRW-GNN). Most existing node classification methods usually take neighbor nodes as neighborhoods, but the target node and its neighbors in heterogeneous graphs usually belong to different categories. To reduce the impact of heterogeneity on node embedding, SRW-GNN uses the similarity between nodes as probability to perform random walks and takes the sampled paths as neighborhoods to obtain more homogeneous information. The order in which nodes appear in the path is particularly critical for capturing neighborhood information. However, most existing GNN aggregators are insensitive to node order. This paper introduces a path aggregator based on recurrent neural network (RNN) to simultaneously extract the features and order information of nodes in the path. In addition, nodes have different preferences for different paths. In order to adaptively learn the importance of different paths in node encoding, an attention mechanism is used to dynamically adjust the contribution of each path to the final embedding. Experimental results on multiple commonly used heterogeneous graph datasets show that the accuracy of this method is significantly better than that of MLP, GCN, H2GCN, HOG-GCN and other methods, verifying its effectiveness in heterogeneous graph node classification tasks.
Medical image segmentation method based on confidence learning and collaborative training
Authors: Hongwei Zhao , Yuhan Chen , Pingping Liu , Qiuzhan Zhou
Published: October 2024

Confidence learning plays an important role in the training of low-quality annotated data of medical images. However, the current applications of confidence learning are based on the average teacher model, and the possibility of confidence learning on other networks has not been explored. To address this problem, a segmentation model based on confidence learning and co-training is proposed. The model uses two different networks to encourage the output results of the two networks to be consistent. Then, the output of one of the networks is compared with the original low-quality annotations using confidence learning, and the low-quality annotated data is corrected to provide an effective training reference. The proposed model is compared on three medical image datasets of different modalities. Experimental results show that the segmentation effect of the proposed model is better than that of the existing confidence learning model.
Vulnerability Detection Method Based on Word Vector Model
Authors: Wei Xiao , Jinghao Hu , Zhengzhang Hou , Tao Wang , Chao Pan
Published: October 2024

Aiming at the problems of non-uniform experimental platforms and heterogeneous datasets faced in the field of vulnerability detection, we studied the application of word vector models in C/C + +function vulnerability detection. Five word vector models were used for the knowledge representation of the abstract syntax tree structure generated by the source code, and six neural network models were used for vulnerability detection. The experimental results show that functionlevel code has shallow semantic relationships and tight connections within code blocks.
Text-aware small sample remote sensing image classification based on contrastive learning
Authors: Wenhui Li , Chen Yang
Published: October 2024

In view of the fact that existing methods mainly use a single modality of remote sensing images to solve the problem of low similarity of the same category, a remote sensing image classification method based on multimodal learning is proposed. Firstly, the spatial features of the image are corrected and the image encoder is pre-trained using contrastive learning to generate image features, and the text encoder is used to generate text features. Secondly, a feature decoder is introduced to obtain text-aware visual features, and a new attention mechanism method is proposed in the feature fusion stage. Then, a new image encoder is designed to improve the classification accuracy. Finally, the similarity between the support set and the query set is calculated to further predict the category. Experiments are conducted on the NWPU-RESISC45, AID, and UC Merced datasets. Its 5-way 5-shot accuracy reaches 86.46%、85.89%and 80.32%outperforms the existing small-sample remote sensing image classification methods, respectively.
Live feature transformation scale extraction of face images based on deep learning algorithm
Authors: Xiaoqi Lyu , Hao Li , Yu Gu
Published: October 2024

In view of the low extraction accuracy and efficiency of the current feature extraction methods of face images, a method for extracting the scale of live feature transformation of face images based on deep learning algorithm is proposed. First, the deep learning method is used to complete the denoising of face images; then the Gabor wave filter is used to decompose the face signal, and it is input into the deep subspace model to complete the extraction of feature transformation scale; finally, the live feature transformation scale extraction of face images is completed based on (particle PSO swarm optimization algorithm). Experimental results show that the proposed method for extracting face image features has higher accuracy, faster recognition speed and better overall application effect.
Redundancy Design of FADS System for Complex Leading- Edge Aircraft Based on Neural Network
Authors: Yinjia Zhou , Qian Wan , Yizhe Xu , Yin Qi , Yong Shi
Published: October 2024

The flush airdata sensing system (FADS) calculates flight parameters such as angle of attack, sideslip angle, Mach number, incoming flow pressure and static pressure based on the pressure measurement of the aircraft surface. It can effectively solve the problem that the leading edge of the pitot tube protruding from the fuselage cannot adapt to the severe aerodynamic heating faced by hypersonic aircraft during the cruise phase, and at the same time meet the aircraft's demand for stealth performance. At present, there is little analysis and research on the use of neural network methods and FADS systems for complex leading edge aircraft. In view of the subsonic/transonic conditions of hypersonic aircraft returning autonomously during the landing phase, the redundancy design and verification of the head FADS system of complex leading edge aircraft are carried out considering the influence of thin leading edge and inlet components. 15 pressure measuring holes are opened in the head of the complex leading edge aircraft. Through a large number of refined numerical simulations, the pressure database of the aircraft under different incoming flow conditions is established, and the typical working conditions are verified by wind tunnel tests. For the complex leading edge aircraft, 4 sets of neural network algorithms are established based on pressure data and redundant design research is carried out, including 1 set of 9-hole algorithm and 3 sets of redundant algorithms. Among them, the 9-hole algorithm has a higher accuracy, with the solution error of the angle of attack within 0.07∘, the solution error of the sideslip angle within 0.3∘, the solution error of the Mach number within 0.0012, and the relative error of the solution of the incoming flow pressure and static pressure within 1.5%. In addition, a system solution process with a certain fault tolerance was established, which can continue to maintain the effective output of the incoming flow parameters in the event of failure of any single pressure measuring hole.
Design of Neural Network-Based Multi-Fault Tolerant Control System for Unmanned Aerial Vehicles
Authors: Kun Yan , Jinze Zhao , Chaobo Chen , Songxiong Gao , Kai Cao
Published: October 2024

Actuator failure seriously threatens the flight safety of unmanned helicopters. Considering the problem of multiple faults such as actuator bias and failure in unmanned helicopters, a composite fault-tolerant flight control algorithm is proposed. For actuator bias fault, a nonlinear fault observer is designed to estimate it in real time; for actuator failure fault, a same-dimensional auxiliary system is constructed and processed by neural network technology. The composite fault-tolerant flight controller of the unmanned helicopter is designed by backstepping method, and the Lyapunov stability theory is used to prove that the error signals of the closed-loop system are bounded and convergent. Simulation results show that the proposed control algorithm can improve the fault tolerance of the unmanned helicopter when multiple actuator faults occur, ensuring its safe flight.
Design of Time Series Fuzzy Segmentation Algorithm for Communication Data Classification
Authors: Yongfei Zhang , Tao Chen
Published: October 2024

In order to solve the problem that the imbalance of communication data sets leads to a significant increase in classification difficulty, a classification algorithm for fuzzy segmentation of time series is proposed. The principal component analysis method is used to obtain the eigenvector with the largest eigenvalue. The time series of data is established according to the interval number theory. The segmentation target of the communication data time series is characterized by the Langmuir distance measurement function between data and categories. The classification result of fuzzy segmentation is obtained based on the judgment relationship between the difference of fuzzy classification matrix and the closing condition. The experimental results show that the number of data in the three classification situations of the algorithm in this paper is always at the corresponding ideal level, with high accuracy and low error and failure.
A COMPARATIVE ANALYSIS WITH THE BLACK BOX MODEL & DSS SYSTEM
Authors: Harutyunyan Eleonor
Published: October 2024

This article explores Decision Support Systems (DSS) in emergency management and scrutinizes the mathematical and technological perspectives of DSS. It focuses on how these DSS handle uncertainty, manage resources, and make choices during emergencies. Some features that distinguish them as strong are data analysis as well as coping with ambiguity, while other characteristics include things like real-time monitoring and visualization of data. At the same time, there are certain obstacles to their implementation, such as inadequate data generation or refusal by users. Therefore, instances from real life based on various kinds of disaster-stricken zones are illustrated in this research work. Also, we will find out the interconnection term in Emergency DSS in Uncertainty. It explores the Black Box model and designs the main processes in Emergency DSS in Uncertainty. This work analyzes quantitative adaptation, modeling and optimization, iterative improvement, mathematical formulation, system analysis utilities, and system modeling in dynamic cases.
The influence of IQ, emotional and spiritual perceptions on sports participation in an effort to improve physical health
Authors: Gemaini Andri , Kiram Yanuar , Komaini Anton , Eken Özgür , Jalius Hardzikrillah , Sepdanius Endang , Rifki Muhamad Sazeli , Ayubi Novadri
Published: October 2024

This study aimed to determine the influence of intellectual intelligence (IQ), emotional, and spiritual perceptions on sports participation to improve physical health. It employed a quantitative research design using a survey method, with questionnaires distributed to participants. A total of 100 respondents, comprising both men and women who were government employees, took part in the study. Data collection was carried out through questionnaires distributed via Google Forms and documentation. Data analysis was conducted using the Partial Least Squares (PLS) method with SmartPLS software version 3. The results of this study indicated that emotions had a positive and statistically significant effect on IQ (p < 0.05), a negative and statistically insignificant effect on perceptions of physical health (p > 0.05), and a positive and statistically significant effect on spirituality (p < 0.05). IQ had a negative and statistically insignificant effect on perceived physical health (p > 0.05). In contrast, spirituality had a positive and statistically significant effect on perceptions of physical health (p < 0.05). This study suggested that for sports participants aiming to enhance their health through physical activity, it was beneficial to incorporate emotional intelligence, IQ, and spirituality. Consequently, the selection of sports activities should consider these factors (emotions, IQ, and spirituality) to maximize their positive effects.
Impact of social media on violence reduction in sports stadiums
Authors: Al Hammouri Walid , Al Basheer Mahmoud
Published: October 2024

This study aimed to identify the role of sports media based on social media in reducing the phenomenon of violence in stadiums from the viewpoint of Sports Science Faculty students at the University of Jordan. A descriptive method was employed, and a sample of 190 students (120 males and 70 females) participated. A comprehensive review of relevant research and collection of pertinent information led to the development of a tailored questionnaire. The instrument consisted of four axes and 24 items, answered using a five-point Likert scale. Statistical data processing was conducted using the SPSS program. The results indicated that, from the students' perspective, the role of sports media based on social media in reducing violence was moderate. Additionally, statistically significant differences (p<0.05) were found according to gender across all study axes, where males achieved higher arithmetic averages. Significant differences (p<0.05) were also observed according to academic year in the axis of professional commitment to sports media, with second-year students showing higher arithmetic averages. The researchers recommend that sports media based on social media adopt a balanced language when describing matches.
A kinematic analysis of the two types of soccer throw-in techniques
Authors: Abd-Al-Karem Radwan Omar , A’mir Omar , Abdel Fattah Osama , Hashem Jaber Osama , Mohammad Ermely Ziyad , Asri Al-Saoud Hasan
Published: October 2024

This study aimed to identify kinematic variables in two soccer throw-in techniques, examine their relationship to throw distance, and explore differences based on technique. A descriptive approach was used, with a purposive sample of 15 first-grade players from the Hussein Youth Club. Each player performed both types of throw-in techniques, recorded at 60 f/s using a Nikon D3400 camera placed laterally. A total of 30 successful attempts were analyzed using Kinovea 0.8.27 x64. Variables studied included foot distance, skill duration, release velocity and angle, and ball release height. Data were analyzed with SPSS. The results revealed weaknesses in the side throw-in technique, such as a low release angle, though better distances were achieved with the second technique. Significant correlations were found between foot distance, release angle, release velocity, vertical velocity, and throw distance (p<0.05). There were also statistically significant differences in knee angle, moment of throw, and throw distance, favoring the second technique (p<0.05). The sample's technique shows several weaknesses impacting performance. Projectile variables strongly influence throw distance, closely linked to various kinematic factors. Moreover, the throw-in method is crucial in determining the overall distance.
Psychopedagogy applied to the teaching-learning process in football tactics training: A bibliographic review
Authors: Pérez Murga Cindy Polet , Laz Arechua Judith Mariela , Estacio Alvear Daniel Israel
Published: October 2024

Research in sports psychopedagogy and its applied recommendations are characterized by a contrast between different learning theories in football tactics training. Traditional theories and their corresponding approaches for the specific case of teaching and learning how to play football are subject to compatibilities and incompatibilities. It is analyzed how behaviorism as an approach to teaching the game shows more incompatibilities with the nature of tactical actions compared to constructivism. As coaches strive to teach the game and get their players and team to perform, it is argued that teaching the game requires teaching approaches that will help develop their playing without taking away their autonomy and adaptability. The teaching-learning process during training to play soccer must be carried out to harmonize the characteristics of the content, the context and the individual in question. Finally, it is argued that coherent game design provides minimum conditions for teaching approaches, and that such design should be a priority when developing learning activities throughout the player development process. In conclusion, interactionist theory is the one that best serves for teaching the game and developing tactical behavior. Therefore, it is argued that its principles can help coaches adapt their own strategy for teaching the game to students.

La investigación en psicopedagogía del deporte y sus recomendaciones aplicadas se caracterizan por un contraste entre las diferentes teorías de aprendizaje en el entrenamiento de tácticas en el fútbol. Las teorías tradicionales y sus correspondientes enfoques para el caso específico de enseñar y aprender cómo jugar al fútbol están sujetos a compatibilidades e incompatibilidades. Se analiza cómo el conductismo como un enfoque para enseñar el juego muestra más incompatibilidades con la naturaleza de las acciones tácticas en comparación con el constructivismo. A medida que los entrenadores se esfuerzan por enseñar el juego y hacer que sus jugadores y equipo rindan, se argumenta que enseñar el juego requiere enfoques de enseñanza que ayudarán a desarrollar su forma de jugar sin quitarles su autonomía y adaptabilidad. El proceso de enseñanza-aprendizaje durante el entrenamiento para jugar al futbol debe llevarse a cabo para armonizar las características de los contenidos, el contexto y el individuo en cuestión. Finalmente, se argumenta que el diseño coherente de los juegos proporciona condiciones mínimas para los enfoques de enseñanza, y que dicho diseño debe ser una prioridad al elaborar las actividades de aprendizaje a lo largo del proceso de desarrollo del jugador. Como conclusión, la teoría interaccionista es la que mejor sirve para la enseñanza del juego y el desarrollo del comportamiento táctico. Por lo tanto, se defiende que sus principios pueden ayudar a los entrenadores a adaptar su propia estrategia para enseñar el juego a los estudiantes.
Effectiveness of eye-cervical re-education versus motor imagery therapy on chronic neck pain: A randomized controlled trial
Authors: Abdel-Aal Nabil Mahmoud , ElKeblawy Maher Ahmed , Mohamed Amine Randa Ahmed
Published: October 2024

The aim of this study was to investigate the effect of adding eye cervical re-education exercises (ECRE) versus motor imagery therapy (MIT) to conventional physical therapy (CPT) on pain, functional disability, and cervical range of motion (ROM) in subjects with chronic neck pain (CNP). The study employed a randomized controlled trial design with 60 patients with CNP. Participants were selected from the outpatient clinics of the Faculty of Physical Therapy at Cairo University and were randomly assigned to three groups: conventional physical therapy only (CPT) (Group I, N = 20), eye-cervical re-education exercises plus CPT (Group II, N = 20), and motor imagery therapy plus CPT (Group III, N = 20). All participants received 3 sessions per week for 4 weeks. Visual Analogue Scale (VAS), Neck Range of Motion (ROM) and Neck Disability Index (NDI) were measured at baseline and after 4 weeks of intervention. In terms of pain intensity, neck disability index, neck flexion and extension, right and left lateral flexion, and right and left rotation ROM outcome measures, the results revealed statistically significant differences between groups (p < 0.05). Group II showed statistically significant improvement compared to both Group I and Group III in all measured outcomes (p < 0.05). Additionally, Group III showed statistically significant improvement compared to Group I in all measured outcomes (p < 0.05). Adding eye-cervical re-education exercises or motor imagery therapy to conventional physical therapy resulted in notable improvements. Eye-cervical re-education exercises, in particular, showed greater benefits in reducing pain, enhancing cervical ROM, and decreasing disability compared to conventional physical therapy alone in patients with chronic neck pain.
Understanding of Student Manners and Norms in Keboan Anom Gedangan Elementary School
Authors: Ita Alfia Masruroh  , Fanny Arif Mahya
Published: October 2024

This study is motivated by the phenomenon that the majority of students in class VI-D at SD Negeri Keboan Anom Gedangan do not reflect the etiquette and norms that have been established in the school environment. In this case the researcher aims to examine the extent of students understanding of etiquette and norms. The aim to be adchieved in this research is to describe students understanding of etiquette and norms at SD Negeri Keboan Anom Gedangan, the describer students habituation of etiquette and norms at SD Negeri Keboan Anom Gedangan. This study is research that uses a qualitative approach. The data collection method used was to provide a questionnaire containing 25 statements that had to be ticked by class VI-D students at SD Negeri Keboan Anom Gedangan and an interview containing 10 question conducted with the class VI-D teacher. Data analysis data, compiling data systematically, and drawing conclusions. Like the data that has been obtained through questionnareires and interviews conducted with the homeroom teacher and class VI-D students at SD Negeri Keboan Anom Gedangan, the results of the data are the analysed by researchers so that conclusions can be drawn. Based on the results of likert scale calculations, it shows that there are 13 children who really understand, 13 children understand, and 2 children does not understand etiquette and norms. From these results it can be concluded that the majority of class VI-D students understand the etiquette and norms that exist in the school environment, SD Negeri Keboan Anom Gedangan also made adjustments to instill etiquette and norms.
Autonomous Drone System for Emergency Charging of Electric Vehicles
Authors: Kim Tae-Yang
Published: October 2024

This study explores the development of an emergency charging system for electric vehicles (EVs) using drones. The system is designed to address the limitations of current EV charging infrastructure, particularly in remote or inaccessible areas. The proposed solution involves a drone equipped with a battery pack, which can be dispatched to a stranded EV to provide immediate power.
Influence of mesenchymal stromal cells of different origins on behavioural reactions of rats with cerebral ischemia-reperfusion
Authors: Konovalov Serhii , Moroz Vasyl , Yoltukhivskyy Mykhaylo , Gadzhula Nataliia
Published: October 2024

A new direction in cell therapy for ischemic stroke has been the use of mesenchymal stromal cells, which have shown a positive impact on functional changes in the central nervous system due to their neuroprotective effects, reduction of ischemia-reperfusion-induced injury, inhibition of ischemia-reperfusion-induced apoptosis, and restoration of motor function. This study aimed to investigate the effect of mesenchymal stromal cells of different origins, their lysate, and citicoline on the functional state of the central nervous system in rats with experimental brain ischemia-reperfusion. The study considered the effect of mesenchymal stromal cells derived from human umbilical cord Wharton’s jelly, human and rat adipose tissue, rat embryonic fibroblasts, as well as mesenchymal stromal cell lysate and citicoline on the emotional and behavioural responses of sexually mature Wistar rats (3-4 months) weighing 160-190 g. The behavioural responses of rats were studied using the open field test on the 7th and 14th days of the experiment; the following behavioural acts were recorded: ambulation (locomotion), climbing, rearing, and grooming. The significance of differences was determined using the non-parametric Mann-Whitney U test. It was established that after ischemia-reperfusion, animals with control pathology showed a significant decrease in the duration of episodes of ambulation in peripheral and central squares, vertical locomotor activity, and exploratory activity compared to the sham-operated group. In rats that received citicoline and transplanted human umbilical cord Wharton’s jelly mesenchymal stromal cells, a significant increase in the duration of episodes of horizontal locomotor activity was observed compared to other types of stem cells and the control. Intravenous administration of rat embryonic fibroblasts increased the emotional activity of the experimental animals. The least impact on locomotor and adaptive exploratory activity in rats with ischemia-reperfusion was registered in groups of animals that received mesenchymal stromal cells from human and rat adipose tissue, as well as mesenchymal stromal cell lysate. The practical significance of the study lies in the search for the most effective class of stem cells with neuroprotective properties for the creation of an injectable drug for intravenous transplantation in the treatment of patients with acute ischemic stroke
Disrupción en las ciencias sociales y sus oportunidades antela crisis sanitaria del Covid 19
Authors:   Universidad Autónoma de Guadalajara, Arroyo Martínez Simona , Corona Figueroa Beatriz Adriana , Parra López Lilian Patricia
Published: October 2024

Un libro producto de las ponencias presentadas en el 1er. Congreso Internacional de Investigación en Ciencias Sociales Económicas y Administrativas convocado por la Universidad Autónoma de Guadalajara. Cada artículo se distingue por analizar a profundidad y buscar soluciones frente a distintas problemáticas generadas por la contingencia del COVID-19. Los principales ejes de investigación abordan cuestiones económicas, de administración en el sector salud, los retos de la educación a distancia, los cambios en la dinámica social y el impacto en la salud mental.
CONCEPTUAL FRAMEWORK FORMATION OF AN EFFECTIVE SYSTEM OF PUBLIC ADMINISTRATION AND DEVELOPMENT OF LOCAL SELF-GOVERNMENT AS A NECESSARY CONDITION FOR BUILDING A FAIR INNOVATIVE KAZAKHSTAN
Authors: Muzapar D. J. , Rakimbaev E. N.
Published: October 2024

This article examines the challenges associated with forming an effective system of public administration and local self-government within the executive branch of government. It specifically focuses on the proposals made by the President of the Republic of Kazakhstan regarding the improvement of the country’s administrative and territorial structure, the decentralization of public administration, and the development of local self-government.

The planned structural economic reforms necessitate a comprehensive reboot of the public administration system. The authors identify fundamental issues and present the conceptual foundations for decentralizing the public administration system. This approach is grounded in functional analysis and emphasizes the importance of establishing an effective system of public administration and local self-government as a crucial condition for building a fair and innovative Kazakhstan.
TRABALHO, MIGRAÇÃO E REPRODUÇÃO SOCIAL NA COSTURA: Trabalhadoras bolivianas em São Paulo
Authors: Lemos Patrícia
Published: October 2024

O artigo discute como a dinâmica da produção para o capital e a realidade de produção e reprodução da força de trabalho migrante estruturam as condições de trabalho de extrema precariedade a que essa população está submetida e, ao mesmo tempo, constituem barreiras à sua superação. A análise se apoia nos resultados da pesquisa de pós-doutorado realizada entre 2021 e início de 2023. A partir, principalmente, da experiência de mulheres de origem boliviana, trabalhadoras da costura em São Paulo, o artigo evidencia as opressões de raça e gênero como constitutivas da dinâmica de organização desse setor baseada na redução sistemática e profunda dos custos de reprodução social da força de trabalho imigrante. Com isso corroboramos as teses de que o trabalho escravo contemporâneo, bem como o trabalho precário e informal localizam-se no cerne da acumulação de capital e em sintonia com as tendências globais de flexibilização e precarização do trabalho.
Assessment of Property Taxes and their Impact on Real Estate Investment in Plateau State, Nigeria
Authors: Datukun Hannatu Lucius , Mailumo Anthony Sambo , Kassam Istifanus George
Published: October 2024

Taxes imposed on property in the country are characterised by intricate and complex interactions of both traditional, colonial, and modern-day circumstances, and the revenue generated from these taxes is often an important source of finance for the government. In most developing countries, these taxes have led to multiple taxation due to complex, diverse, inadequate, and imperfect information. Thus, this study aims to assess the various property taxes in practice and their impact on real estate investment in Plateau State, Nigeria. The objectives pursued include identifying the various property taxes along with their administering agencies and assessing the impact of these taxes on property investment. The researchers targeted 90 respondents from an estimated population of one million five hundred in the Greater Jos area, and successfully recovered 68 responses through simple random sampling based on the survey conducted among residents.  A questionnaire was used to gather the views of taxpayers on multiple taxation and its effects on land and buildings, and the collected data was analysed descriptively. The results revealed that almost all taxpayers in Plateau State pay taxes to the government consistently and to more than two agencies. Furthermore, all tiers of government have their own forms of taxes collected, which have a direct effect on investment. It is therefore recommended, among other measures, that tax collection should be clearly defined and streamlined with respect to which tier of government is responsible for collecting specific taxes on property occupation. This could help reduce, if not eliminate, the issue of taxing the same property multiple times.
Comparison of Clinical Outcomes in Lung Cancer Patients Diagnosed through Screening Programs versus Symptomatic Presentation: A Retrospective Study
Authors: Derdiyok Onur
Published: October 2024

Objectives The objective of this study is to compare the clinical outcomes of lung cancer patients diagnosed through screening programs (workplace screening, premarital screening, and check-up programs) and those diagnosed based on symptomatic presentation, all of whom underwent video-assisted thoracoscopic surgery (VATS) lobectomy or segmentectomy between 2019 and 2021. Methods A retrospective study was conducted involving 45 patients diagnosed with stage I and II lung cancer. Patients with comorbid conditions, those with a history of major surgery, tuberculosis, or cancer, and those aged over 65 were excluded. All included patients received chemotherapy. Patients were divided into two groups: Those diagnosed through screening programs (16 patients) and those diagnosed based on symptoms (29 patients). All patients underwent VATS lobectomy or segmentectomy. Postoperative complications, 36-month survival rates, and causes of death were compared between the groups. Results The 36-month survival rate was higher in the screening group compared to the symptomatic group. Additionally, the recurrence rate was lower in the screening group. Among symptomatic patients, 3 presented with hemoptysis. Causes of death included respiratory failure, metastasis, and cardiovascular events. These findings suggest that early diagnosis through screening programs leads to better clinical outcomes. Conclusions Screening programs for lung cancer facilitate early diagnosis and treatment, resulting in improved survival rates and lower recurrence rates. The implementation and promotion of these programs could significantly enhance patient outcomes.
A INFLUÊNCIA DE ATIVIDADES VOLTADAS PARA O DESENVOLVIMENTO NEUROPSICOMOTOR EM CRIANÇAS COM TRANSTORNO DO ESPECTRO AUTISTA
Authors: Duarte Maria Clara Vieira , Morais Laine dos Santos , Sousa Bruna Benvinda da Silva , Machado Joicy Maria Chaves , Sousa Maria da Cruz Santos , Sousa Jiovanna Maria da Silva , Sousa Jhones Nascimento de , Sales Bruna Layane Gouveia de Lucena , Cavalcante Ana Claudia , Pereira Suellen Aparecida Patricio
Published: October 2024

Objetivo: Analisar na literatura a aplicação de intervenções voltadas para o desenvolvimento neuropsicomotor em crianças com TEA. Metodologia:Trata-se de uma revisão integrativa da literatura, referente à área de fisioterapia em neuropediatria, evidenciando conceitos relacionados com transtorno do espectro autista em crianças e a influência de atividades voltadas para o desenvolvimento neuropsicomotor. Neste estudos, foram incluídos artigos primários, referentes à relato de caso, estudos de casos e controles, detecção de casos (“screening”), estudos de coorte e ensaios clínicos controlados randomizados, publicados no período entre 2019-2023, de livre acesso por meio eletrônico, correspondente aos termos de busca escritos: transtorno do espectro autista, habilidade motora, desenvolvimento motor, em português e em inglês, e que contemplassem os aspectos relacionados às dificuldades motoras em crianças com TEA e seu desenvolvimento neuropsicomotor. Todos os artigos duplicados, textos de teses, dissertações e jornais foram excluídos. Em sua totalidade, foram encontrados 74 artigos e após leitura dos resumos e aplicação dos critérios de exclusão, 5 trabalhos foram selecionados. Resultados e Discussão: Ferramentas de avaliação como a Escala de Avaliação do Autismo na Infância (CARS) e a Escala de Inteligência Wechsler para Crianças (WISC- III) proporcionam uma compreensão precisa de seu perfil cognitivo e motor. Considerações Finais: As abordagens de intervenção e avaliação motoras discutidas foram eficazes no tratamento das dificuldades motoras encontradas em crianças com Transtorno do Espectro Autista (TEA). A implementação de programas de exercícios que se concentram em coordenação, equilíbrio, força e mobilidade pode facilitar significativamente os ganhos relacionados ao desenvolvimento neuropsicomotor. Utilizando tanto intervenções presenciais quanto telessaúde, esses programas permitem uma abordagem abrangente e flexível, garantindo que as necessidades individuais de cada paciente sejam atendidas de maneira eficaz e contínua.
THE EFFECT OF EMOTIONAL INTELLIGENCE ON EMPLOYEE GREEN BEHAVIOR: THE CASE OF THE REPUBLIC OF NORTH MACEDONIA
Authors:   Faculty of Business Administration and Economics, South-East European University,  North Macedonia, Berisha Besar
Published: October 2024

This study examines the relationship between emotional intelligence (EQ) and employee green behavior (EGB) in the workplace within the context of the Republic of North Macedonia. Given the increasing emphasis on sustainable business practices, understanding the factors influencing employees' environmentally friendly behaviors is essential. This research explores whether higher levels of emotional intelligence among employees contribute to more proactive engagement in green behaviors, such as energy conservation, waste management and recycling at work. The findings suggest that emotional intelligence significantly influences employee green behavior, with implications for organizational strategies aimed at fostering sustainability. Additionally, the study investigates gender differences in the relationship between EQ and EGB. Results indicate that female employees are more likely to engage in green behaviors compared to their male counterparts, although emotional intelligence remains the more substantial predictor of EGB regardless of gender. These insights highlight the importance of developing EQ across all employees while considering gender dynamics to enhance organizational sustainability efforts.
PERCEPTIONS OF TAX BURDEN AND ITS INFLUENCE ON TAX EVASION IN KOSOVO
Authors:   Faculty of Business and Economics, South East European University, Tetovo, North Macedonia, Bujupi Mjellma
Published: October 2024

The paper aims to analyze perceptions of tax burden and its influence on tax evasion in Kosovo. 320 respondents were taken in analysis and is used ordinal logistic regression. Based on the analysis of the scientific work it has emerged that, age, marital status, types of taxes paid, application of VAT, non-issuance of fiscal receipt and perceptions of the tax system significantly influence perceptions of tax burden and tax evasion in Kosovo. Other predictors included were not significant, indicating they may not have a strong influence on perceptions. The study has some limitations, this have to do with not including other countries in analyzing their perceptions of tax burden and its influence on tax evasion. However, the finding of the paper may be beneficial to other researchers and policymakers.
Investigation of Phosphate Removal from Aqueous Solutions Using Zinc Extraction Waste
Authors: Türk Feride Naime
Published: October 2024

It is important for waste management to economically evaluate the solid leach residues released in zinc production facilities and classified as hazardous waste due to the metals they contain, without harming the environment and human health. Although the disposal of these residues often requires special technologies, hazardous wastes are left to the environment or landfills due to the expense of these technologies and the inadequacy of legal sanctions in some cases. For this reason, it is important from an economic and environmental perspective to evaluate these residues and bring them into the industry. In this study, lead cake formed during zinc extraction production, brought from Kayseri Çinkur enterprises, was used. Since this waste contains high amounts of lead as well as zinc and iron, the conditions for removing phosphate from aqueous solutions were investigated. Phosphate removal adsorption isotherms were obtained using the obtained batch test results. Additionally, some thermodynamic quantities regarding phosphate removal were calculated. As a result of the experiment, it was determined that the P removal efficiency from aqueous solutions significantly depends on the solution pH and the dose of waste lead cake. It was also determined that phosphate removal from aqueous solutions obeyed the Langmuir and Freundlich isotherm. Additionally, it was observed that phosphate adsorption equilibrium was established after a period of 120 min. By mixing 100 mg/L phosphate solution with pH 7.69 with 20 g/L lead cake without any addition and contacting for 120 minutes, approximately 74% of the phosphate can be effectively removed by adsorption.
An Experimental Study on the Compressibility of Clays Reinforced with Basalt Fiber
Authors: Aslan Topçuoğlu Yasemin , Gürocak Zülfü
Published: October 2024

The use of basalt fiber has become quite common in soil reinforcement works, which emerged as an alternative to traditional soil improvement methods and are carried out using different types of fibers. Basalt fiber, whose raw material is basalt rock, is preferred in soil reinforcement works due to its features such as high strength, economical, environmentally friendly, natural and abundant. In this study, the effects of basalt fiber reinforcement on the compressibility of high plasticity bentonite clay were examined. Bentonite clay was reinforced with 24 mm long basalt fiber at different rates between 0.5% and 5.0%, and standard proctor tests were carried out on these mixtures. With experimental studies, maximum dry density (γdmax) and optimum water content (Ꞷopt) values were determined and the effects of basalt fiber reinforcement on these parameters were evaluated. According to the test results, while γdmax values increased up to 2.5% basalt fiber reinforcement ratio, Ꞷopt values decreased. In samples with basalt fiber ratio greater than 2.5%, γdmax values decreased and Ꞷopt values increased. The results obtained showed that the basalt fiber ratio at which bentonite can be compressed best is 2.5%, and basalt fiber reinforcement at rates greater than this ratio negatively affects the compressibility.
Mn and Ti Co-doping of LiNiO2 to Improve Performance
Authors: Öz Erdinç , Dahn Jeff
Published: October 2024

LiNiO2 (LNO) has high capacity but suffers from structural instability and capacity fade, which limits its practical use in lithium-ion batteries. This study proposes co-doping LNO with Mn and Ti (MnTi25) as a strategy to overcome these issues. MnTi25 was thoroughly characterized, revealing improved structural stability and significantly reduced cation mixing compared to pristine LNO. The half-cell performance of MnTi25 is noteworthy, exhibiting a capacity similar to the established 4% Mn-substituted ZoomWeMn4 standard, demonstrating efficient Li-ion extraction and insertion. Additionally, full-cell testing against a graphite anode shows that MnTi25 delivers a capacity almost identical to a commercial LNO-based material. This promising achievement highlights the effectiveness of co-doping in addressing LNO's limitations while preserving its high-capacity potential. This study demonstrates that MnTi25 can be a promising cathode material for high-performance lithium-ion batteries by tailoring the material's structure through co-doping.
Simulation of the Collapse Mechanism of a Minaret under the Effect of Strong Wind
Authors: Altıok Taha Yasin , Demir Ali
Published: October 2024

In this study, the collapse mechanism of a destroyed minaret under strong wind influence was simulated to understand such structural interactions and identify potential risky regions. Wind profiles were defined according to Eurocode and Turkish Standards and were used in Computational Fluid Dynamics analyses. The pressure and suction stresses obtained with these wind analyses were applied on the minaret’s surface with Abaqus and the nonlinear finite element analyses were performed. As a result of the numerical analyses, displacements, stresses, plastic strains, and damages were obtained and results were comparatively presented. The results obtained with both standards are quite close and top displacements exceed the limit value specified in the Italian Building Code and Eurocode 8. Besides, many mesh elements in the minaret’s transition segment were damaged with tension stresses in nonlinear finite element analyses. Finally, the minaret’s failure behaviour was successfully simulated with the used methods.
Determination of Training Participants in Community Work Training Centers Using the Naïve Bayes Classifier Algorithm
Authors: Hananto April Lia , Hananto Agustia , Huda Baenil , Rahman Aviv Yuniar , Novalia Elfina , Priyatna Bayu
Published: October 2024

Community work training centers are skills training institutions that aim to improve the skills of the surrounding community by providing training programs that align with industry needs. Registration of training participants at the Al-Ikhwan Islamic Boarding School community work training centers often faces obstacles, namely, the selection process is still manual, so it takes a long time, and there is a possibility of errors. This study aims to apply the Naive Bayes Classifier Algorithm to determine whether applicants pass training at the Al-Ikhwan Islamic Boarding School community work training centers. This classification method is used to help optimize the applicant selection process by considering administrative factors, income, and training quotas. RapidMiner software is used as a tool to implement the algorithm. This study found that the Naive Bayes Classifier Algorithm can provide good accuracy results in determining applicants who pass the training selection. The test results show that the resulting model has an accuracy of 90.00% in determining passing training participants with data that has the highest chance of passing, namely data that has the attributes of the female gender, age 20 years, last education Senior High School/Vocational High School, student work/student, income 364,912, father's work as laborer, father's income 3912,280, mother's work as an IRT, and mother's income 885,964. This research increases efficiency and accuracy in determining training applicants at the Al-Ikhwan Islamic Boarding School community work training centers.
Detecting Distributed Denial-of-Service (DDoS) Attacks Through the Log Consolidation Processing (LCP) Framework
Authors: Khairuddin Mohammad Adib , Mohd Isa Mohd Rizal , Mohd Shukran Mohd Afizi , Ismail Mohd Nazri , Maskat Kamaruzaman
Published: October 2024

One major problem commonly faced by organizations is a network attack especially if the network is vulnerable due to poor security policies. Network security is vital in protecting not only the infrastructure but most importantly, the data that moves around the network and is stored within the organization. Ensuring a secure network requires a complex combination of hardware including both network and security devices, specialized applications such as web filtering and log management, and a group of well-trained network administrators and highly skilled analysts.  This paper aims to present an alternative to the current log management solution. A hindrance to the current log management solution is the difficulty in amalgamating and correlating a vast number of logs with different formats and variables. This paper uses a novel framework called Log Consolidation Processing (LCP) based on the System Information Event Management (SIEM) technology, to monitor the behavior and the fitness of a network. LCP provides a flexible and complete solution to collect, correlate, and analyze logs from multiple devices as well as applications. An experiment testing the effectiveness of LCP in detecting DDoS attacks in a campus network environment was conducted, demonstrating a highly successful rate of detection. Besides threat detection and avoidance through log monitoring and analysis, other benefits of implementing the LCP framework are also included. This paper concludes by mentioning suggested enhancements for the LCP framework.