bluuebunny/crossref_metadata_2025 huggingface dataset:
Convolutional neural network combined with the attention mechanism for facial emotion recognition
Authors: Luo Xiguo
Published: October 2023

Facial Emotion Recognition (FER) holds great importance in the fields of computer vision and machine learning. In this study, the aim is to improve the accuracy of facial expression recognition by incorporating attention mechanisms into Convolutional Neural Networks (CNN) with FER2013 dataset, which consists of grayscale images categorized into seven expressions. The combination of proposed CNN architecture and attention mechanisms is thoroughly elucidated, emphasizing the operations and interactions of their components. Additionally, the effectiveness of the new model is evaluated through experiments, comparing its performance with existing approaches in terms of accuracy. Besides, the results demonstrate that the CNN architecture with attention mechanisms outperforms the original CNN by achieving an improved accuracy rate of 69.07%, which is higher than 68.04% accuracy rate of original CNN. Moreover, the study further discusses the confusion matrix analysis, revealing the challenges faced in recognizing specific emotions due to limited training data and vague facial features. In the future, this study suggests addressing these limitations through data augmentation and to reduce the gap between training and testing accuracy. Overall, this research highlights the potential of attention mechanisms in enhancing facial expression recognition systems, paving the way for advanced applications in various domains.
Hough transform and line rotation on analog gauge reading: A case study
Authors: Peng Ziqian
Published: October 2023

While digital meters can automatically communicate with a database to store reading values, many industries still utilize analog meters which are not economically or physically viable to replace. Instead, computer vision modules may be attached to cameras to automatically read values and record them. This paper tests three implementations of gauge reading, two simple Hough line and circle transform methods and one lightweight naive line rotation method. A dataset was created for testing purposes, consisting of 46 images from various sources and variations including pointer rotations, binarizations, and text or logo removal. Results showed the line rotation technique substantially more robust and accurate than both Hough line implementations. Two major obstructions were detected: pointer tails and dense text/logos, and their removal via photoshop tools improved the average accuracy to roughly 1 degree from ground truth. This is accurate enough to replace human readers in most imprecise situations and is lightweight enough to function under nearly all circumstances. Future research seeks to validate these findings further by testing line rotation on more varied gauges.
A critical examination of deficiencies in the convolutional neural network model for facial emotion recognition
Authors: Tao Yuhui
Published: October 2023

The challenge of addressing the issue of low accuracy in specific scenarios encountered during the implementation of facial emotion recognition systems arises due to the wide array of environments and varying conditions. In this study, the Facial Expression Recognition-2013 (FER-2013) dataset sourced from the Kaggle serves as the basis for training the models, with subsequent analysis conducted on the experimental outcomes. The dataset comprises a training set and a testing set, each annotated with labels representing seven distinct emotions, ranging from "angry" to "surprise". The models developed for facial emotion classification, tasked with automatically recognizing emotions based on provided images, consist of a MobileNet-based model and a self-built model employing convolutional neural networks. Both models exhibit an accuracy of approximately 60%, yet demonstrate deficiencies in predicting the "neutral" label. Additionally, the utilization of techniques such as confusion matrix and saliency map enable the comparative evaluation of model performance across different emotion labels and facilitates an analysis of their corresponding dominant facial regions. Based on a comparison of results obtained from representative cases, two potential factors contributing to these limitations are identified: a paucity of training data and the presence of ambiguous features. The findings of this study are expected to inform future directions for improvement and modification of facial emotion recognition models in order to enhance their applicability in diverse scenarios.
Brain tumor diagnoses based on VGG-16 and MobileNet
Authors: Liu Yuheng
Published: October 2023

Brain tumor, recognized as one of the most formidable and aggressive diseases globally, continues to pose significant challenges for medical practitioners in clinical diagnosis and treatment. Addressing the burden on doctors and addressing resource limitations in certain hospitals necessitates the development of efficient and dependable alternative approaches. Convolutional Neural Networks (CNNs), renowned for their prowess in image recognition, hold immense potential in addressing this pressing issue. Leveraging transfer learning, the capabilities of established models such as VGG-16 and MobileNet can be harnessed to construct superior models within a comparatively abbreviated timeframe. This research paper aims to construct and evaluate VGG-16 and MobileNet-based models, employing transfer learning, to explore the applicability of these two classical models in the context of brain tumor diagnosis. The ultimate goal is to assist doctors and hospitals in alleviating the challenges associated with brain tumor diagnoses. The results demonstrated the effectiveness of brain tumor recognition based on CNNs.
Galaxy classification based on convolutional neural networks with dropout technique
Authors: Hu Haoyu
Published: October 2023

Galaxy morphology classification is essential for studying the formation and evolution of galaxies. However, previous studies based on Convolutional Neural Network (CNN) mainly focused on the structure of convolutional layers without exploring the designs of fully connected layers. In this regard, this paper trains and compares the performance of CNNs with 4 types of fully connected layers on the Galaxy10 DECaLS dataset. Each type of the fully connected layers contains one dropout layer, and dropout rates including 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90% are tested in the experiment to investigate how dropout rates in fully connected layers can affect the overall performance of CNNs. Meanwhile, these models utilize the EfficientNetB0 and DensnNet121 as their feature extraction networks. During the training process, feature-wise standardization, morphological operations, and data argumentation are used for preprocessing. Technics including class weights, exponential learning rate decay, and early stopping are applied to improve model performance. Saliency maps and Grad-CAM are also used to interpret model behaviours. Results show that the architectures of fully connected layers have a significant effect on models overall performance. With the same dropout rate and convolutional layers, models using global average pooling and an additional dense layer outperform others in most cases. The best model obtained an accuracy of 85.23% on test set. Meanwhile, the experimental results on dropout indicate that dropout layer can reduce the effect of the architectures of fully connected layers on overall performance of some CNNs, leading to better performance with less parameters.
The investigation of transferability utilizing the ImageNet weight-based pretrained model for medical image classification: A case study on kidney CT images
Authors: Hsu An
Published: October 2023

Due to recent growth in technology, machine learning has emerged to be an effective auxiliary tool in medical field. However, the effectiveness of transfer learning architectures trained on non-medical image data remains unclear. In this paper, two VGG-16 models, a type of pre-trained Convolutional Neural Network architecture, were constructed to classify kidney CT images that belong to four categories: normal, stone, cyst, and tumor. Two VGG-16 models have identical parameters except for the pre-trained weights: one has pre-trained weights trained on ImageNet, and the other one trained on a random large-scale dataset. To gather a more detained insight into models performances, saliency maps and Grad-CAM are employed to assess the models' ability to extract relevant features from the CT images. The result demonstrated that VGG-16 model that is trained on ImageNet can achieve 98.96% accuracy, which is about 30% higher than the other VGG-16 model. The saliency maps and Grad-CAM also support the difference in test accuracy: the model with random pre-trained dataset has saliency map that highlights the whole picture and Grad-CAM image that does not highlight any part of the CT image data, showing that it cannot correctly locate the key features. Additionally, the model with ImageNet can correctly highlight the principal features in both maps. In this study, the utilization of ImageNet is proven to be effective in the usage of transfer learning in processing medical image. Future research and exploration should focus on further enhancing the application of transfer learning in the medical field.
Research on kitting evaluation method of complex electromechanical products
Authors: Zhao Pengfei
Published: October 2023

Precise and efficient product kitting evaluations are vital for boosting assembly performance and customer contentment for varied, small-batch, and intricate electromechanical products. However, current enterprise resource planning systems (ERP) provide inadequate support for analyzing the kitting of products. How to evaluate the degree to which customers' demands for a complete set of multiple products can be met when adjusting the importance level of customer demands without changing the customer demand date in the production system and affecting the scheduled customer orders has become one of the urgent problems that enterprises need to solve. In response to the above issues, this article presents a method for evaluating product kitting, which takes the maximum quantity of complete sets of products as the optimization objective, considers multiple constraints such as material inventory data and in process business data, and designs a multi-level BOM decomposition algorithm. Finally, a case study of a company producing core components for standard high-speed trains demonstrates the practicality and efficacy of the proposed method.
Parametric modeling logic analysis and precision control method application of nonlinear landscape structures based on Rhino+Grasshopper platform: A case study of the Flying Goose viewing platform in Beijing
Authors: Zheng Zi'ang
Published: October 2023

The development of digital technology has made non-linear landscape structures mainstream and has brought new challenges to design methods. The efficiency and accuracy of applying Rhino+Grasshopper parametric modelling to such structures has gained the attention of design practitioners and scholars. However, there are still research gaps in this approach in current research. Therefore, this study uses the Flying Goose viewing platform as a case study to supplement the lack of specific case studies on non-linear landscape structures; it analyses the modelling logic through three parts: morphological characteristics, structural system, appendages and decoration to supplement the lack of systematic knowledge on modelling logic; it analyses the four methods of unfolding control, isometric projection, function shaping and linear interference. The analysis and discussion of the four core precision control methods used in the Rhino+Grasshopper parametric modelling process complements the current lack of specific research on Rhino+Grasshopper parametric modelling morphological precision control methods. The aim is to provide a systematic analysis of the modelling logic of non-linear landscape structures and a detailed analysis of the precision control methods on top of the non-linear landscape structures morphological realisation, providing a theoretical basis and application examples for future research of the same type.
Intelligent logistics system based on visual detection of fruit freshness
Authors: Liu Hengyu
Published: October 2023

Because of its tremendous potential for financial advantage, the academic and business communities have begun to focus a significant amount of attention on the intelligent logistics system. For the purpose of addressing the issue of quality supervision of fruit while it is being transported logistically, this study presents a proposal for an intelligent logistics system that is based on the detection of fruit freshness. The physical, chemical, and image processing techniques that are utilized at various points during the logistics process make up the core detection methods utilized by this system. The ability of the system to perform monitoring of the freshness of the fruit in real time guarantees that the fruit will be transported in a manner that is both secure and effective. The results of the analysis show that this system plays an essential part in a number of steps, including fruit harvesting, fruit sorting, transportation planning, and fruit delivery right to consumers front doors.
Using transformer in stock trend prediction
Authors: Liu Zhichen
Published: October 2023

Large transformer model had achieved good results in many tasks, such as computer vision (CV) and natural language processing (NLP). However, in financial domains, the application of large deep learning models is rarely observed. Stock Trend Prediction (STP) is a task that using Limit Order Books (LOBs) to predict the future stock price trend by the sequence of historical limit order information, the trend can be Current works are mostly based on the structure of Convolutional Neural Network (CNN) + Recurrent Neural Networks (RNN). This structure is hard to parallel and cannot make full use of GPU resources. It is also difficult to increase the dimension to fit more complex data and performs poor when time sequence is long. Recently, some works proposed that CNN + Transformer model can also work is solving this task. This paper verifies that Transformer can be directly used into STP task and gain a good result, and proposes a novel Transformer-based model, Transformer-LOB, to enhance the basic transformer model performance. This model uses attention mechanisms to extract temporal information rather than using RNN, which utilizes the GPU effectively. Since all the feature extractions are based on transformer modules, the model is scalable and easy to parallel. Transformer-LOB is tested on FI-2010 LOB dataset and SZ-2015 LOB dataset, and outputs ideal results on both datasets.
Students' cognition of artificial intelligence in education
Authors: Xu Jingdong
Published: October 2023

As artificial intelligence (AI) becomes more widely used in classrooms, it is important to learn more about students' perspectives on its usefulness and the factors that affect their performance. In order to better understand how students think about AI in the classroom, this experiment builds a more precise random forest model to foretell how they will do on AI-related tasks. Kaggle's "Students' Perceptions of AI Survey Analysis" dataset was used in the study as it contained important information about students' AI-related attitudes, expertise, and learning objectives. Engineering techniques were incorporated into the methodology as part of the feature selection process once the data had been collected and preprocessed. In order to process, visualize, and model the data, we used data analytic tools including Pandas, Matplotlib, Seaborn, and Scikit-learn. Students' AI knowledge, information availability, attitudes, and recognition of AI's impact on many sectors were all exposed through exploratory data analysis. The results were interpreted and analyzed in the debate, which also highlighted the merits and shortcomings of the approach and its possible limitations. Notably, the random forest model outperformed other methods in forecasting students' performance on the AI exam task.
Challenges and strategies for sentiment analysis of irony and humor in social media based on machine learning
Authors: Li Zijun
Published: October 2023

Sentiment analysis of irony and humor in social media poses a formidable challenge owing to the complexity and context-dependency of such expressions. This report offers a comprehensive overview of diverse machine learning techniques utilized in the analysis of irony and humor, encompassing traditional machine learning algorithms and deep learning approaches. Moreover, this review scrutinizes the challenges and future prospects for the sentiment analysis of irony and humor in social media. Future research pathways involve cross-lingual and cross-cultural analysis, multimodal information integration, autonomous identification of novel patterns, adversarial training, and augmenting the explainability and interpretability of sentiment analysis models. The report highlights the importance of these challenges and potential directions, unveiling their impact on this advancing field of research.
Analysis of face recognition technology based on deep learning
Authors: Wang Xinya
Published: October 2023

The emergence of face recognition technology has brought great convenience to human society. After years of research and improvement, face recognition technology has matured. This paper mainly studies face recognition technology based on deep learning, and introduces five main applications, including occlusion face recognition, 3D face recognition, and expression recognition. The typical algorithms listed show that, compared with the traditional feature face algorithms and local binary patterns, algorithms such as DeepFace, FaceNet, ResNet, etc. have made significant progress in recognition efficiency and accuracy in recent years. After combining the development status of face recognition technology with the problems and security risks of the current technology, this paper proposes three solutions: increasing the amount of data, optimizing the model, and government control. In the future, legal data sharing and code open source will be major progress in this field, and dynamic face recognition technology will also be widely used.
Research on the application of Artificial Intelligence tools in higher vocational education
Authors: Xu Yong
Published: October 2023

With the rapid development of the artificial intelligence industry, its application in higher vocational education has gradually become a research hotspot. This study explores how AI tools can enhance the quality of teaching, assist teachers, and improve students' learning experiences. Through the research and analysis of various AI tools, it was found that AI tools can adapt to the learning needs of students in a personalized manner, provide effective teaching support, and thus improve teaching efficiency. AI tools can also help teachers handle heavy daily tasks, such as grading assignments and exams, allowing them to invest more energy in instructional design. These tools can also provide enlightening data feedback to help teachers and students better understand the progress and effectiveness of learning. The results of this study indicate that the application of AI tools in higher vocational education has enormous potential and may have a profound impact on teaching methods. This paper is dedicated to analyzing the research on the application of AI tools in the field of higher vocational education.
Seminal plasma protein profiles and testosterone levels as biomarker semen quality of candidate Madura bulls
Authors: Azizah Nurul , Susilowati Suherni , Utomo Budi , Kusumaningrum Diana , Kostaman Tatan , Muttaqin Zultinur , Arrazy Aqdi
Published: October 2023

Objective: This study aims to determine the protein profile based on molecular weight (MW) and testosterone levels in seminal plasma (SP) that correlates to the semen quality of candidate Madura bulls.
Material and Methods: A total of 10 male candidate madura bulls underwent semen evaluation (motility, viability, membrane plasma integrity (MPI), and sperm concentration). The centrifuge was run at 1,200 rpm (4°C) for 20 min to collect SP. SP testosterone levels were measured using an Enzyme-linked immunosorbent assay. The characterization of SP proteins in Madura bulls was done using 1D sodium dodecyl-sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis. All parameters were analyzed using Pearson correlation analysis.
Result: The results of the SDS-PAGE analysis found eight protein bands with the highest MW of 110 kDa and the lowest of 12 kDa. The mean and SD of SP testosterone levels were 20.58 ± 8.56 ng/ml, motility 59.32% ± 20.14%, viability 67.45% ± 20.22%, MPI 32.77% ± 16.52%, and sperm concentration 1,002.64 ± 429.33 106/mm3. Proteins with MWs of 110 and 91 kDa significantly correlated with MPI, and 110 kDa negatively correlated with sperm concentration (p < 0.05). Proteins with MWs of 73 and 36 kDa significantly correlated with SP testosterone levels, while proteins with MWs of 29 kDa significantly correlated with sperm viability (p < 0.05).
Conclusion: The expressed protein fraction based on MW is closely related to the quality of semen, so it has the potential to be a biomarker of semen quality. Further research is needed to determine the specific proteins in certain fractions.
Microfilariae infection by Acanthocheilonema reconditum and Dirofilaria immitis and their molecular detection in a dog with lymphoma: Case report
Authors: Vargas Rodrigo , Ramirez Ruben , Godoy Nicolas , n Iang
Published: October 2023

Objective: Microfilariae parasites are common in tropical regions, and some species are reported as potentially zoonotic. The diagnosis of filarial infection in dogs by cytology or hematologic tech¬niques showed lower sensibility and specificity, which may result in misdiagnosis. Thus, molecular techniques seem to be an alternative to identifying and detecting microfilariae infections. On the other hand, lymphoma is one of the main tumors in domestic animals, with a high prevalence in domestic canines. This study aims to report a mixed infection with microfilariae in a dog with lymphoma, emphasizing its diagnosis and the possible role of this infection in the development of the neoplasia.
Materials and Methods: An 8-year-old male mixed breed dog was referred to consultation due to the presence of lethargy, recumbency, skin ulceration lesions, nonspecific pain manifestations, emesis, myoclonus in the left temporalis muscle, and seizures. Routine blood and biochemistry tests were normal, and cytology of the skin evidenced a microfilariae infection. The dog died due to a cardiorespiratory arrest, and tissue sampling was done for histopathology and molecular analysis at the necropsy examination.
Results: Skin lesions were related to a microfilarial pyogranuloma related to Acanthocheilonema reconditum. Histopathology of the spleen and liver revealed a diffuse lymphoma composed of blast cells and large lymphocytes, distributed diffusely in the parenchyma and surrounding the vasculature. In the skin, microfilariae were seen in some superficial capillaries.
Conclusion: This study describes a microfilariae mixed infection with A. reconditum and Dirofilaria immitis in a dog with a lymphoma and its molecular detection. To the knowledge of the authors, this is the first report of a mixed microfilariae infection in a tumor of a dog and highlights the use of molecular techniques, i.e., polymerase chain reaction, for an accurate diagnosis.
Production performance of Charolais crossbred steers fed total mixed ration containing a high level of dried cassava top
Authors: Inngarm Ekkapan , Pilajun Ruangyote , Thummasaeng Kungwan , Lunpha Areerat , Morm Sophany
Published: October 2023

Objective: The objectives were to determine the appropriate level of dried cassava top (DCT) in total mixed ration (TMR) based on production performance and carcass characteristics of fattening Charolais crossbred steers.
Materials and Methods: Fifteen fattening Charolais crossbred steers were randomly assigned to a randomized complete block design with initial body weight to receive three treatments, including without DCT, 15% DCT, and 30% DCT in TMR, on a dry matter (DM) basis. The production trial lasted 120 days; then, the fattened steers were slaughtered to study the carcass characteristics.
Results: The in vitro gas production from the immediately soluble fraction of TMR containing 30% DCT was higher than the others (p < 0.05). However, in vitro DM and organic matter degradability were not significantly different among treatments. Feed intake, final weight, feed cost per gain, and carcass characteristics such as warm carcass percentage, marbling score, and loin eye area of feedlot steers were not affected by the inclusion of DCT in TMR. Although steers fed TMR containing 15% DCT had body weight gain, average daily gain, and feed conversion ratio lower than the control (p < 0.05); however, the use of DCT at 30% DM in TMR reduced the feed cost of feedlot beef production (p < 0.05).
Conclusion: Using local ingredients such as cassava tops can increase profit margins for farmers without sacrificing product quality, but they must closely look at growth performance.
Beğenilme Arzusunun Yordayıcıları: Lüks Tüketim Eğilimi ve Olumsuz Değerlendirilme Korkusu
Authors: BULUT Meryem Berrin , DUĞAN İlknur , KILIÇ Gül Nihal , DEMİR Merve
Published: October 2023

Modern dünyada tüketim şeklinin değişmesi ile birlikte lüks tüketim ortaya çıkmıştır. Sosyal medyanın özellikle pandemi süreciyle hayatımızdaki etkisinin artması bireylerin diğerleri tarafından beğenilmek ve onlar tarafından olumlu olarak değerlendirilmek istemelerine neden olmaktadır. Bu araştırmanın temel amacı, lüks tüketim eğilimi ve olumsuz değerlendirilme korkusunun beğenilme arzusu üzerindeki etkisini incelemektir. Ayrıca çalışmada lüks tüketim eğilimi, olumsuz değerlendirilme korkusu ve beğenilme arzusu değişkenlerinin katılımcıların cinsiyetlerine göre farklılaşıp farklılaşmadığı da araştırılmıştır. Bu kapsamda, araştırmaya Türkiye’nin çeşitli illerindeki üniversitelerde öğrenim gören 405 (Nkadın= 267 ve Nerkek= 137) üniversite öğrencisi gönüllü olarak katılmıştır. Katılımcıların yaş ortalaması 21,52 (yaşa bağlı standart sapma değeri 2,82 ve yaş aralığı 18-38)’dir. Çalışmada verileri toplamak amacıyla Lüks Tüketim Eğilimi Ölçeği, Olumsuz Değerlendirilme Korkusu Ölçeği, Beğenilme Arzusu Ölçeği ve kişisel bilgi formu kullanılmıştır. Veriler nicel analiz teknikleri (korelasyon, regresyon ve bağımsız gruplar t-testi) ile çözümlenmiştir. Bulgular, beğenilme arzusu ve lüks tüketim eğilimi; olumsuz değerlendirilme korkusu ve lüks tüketim eğilimi; beğenilme arzusu ve olumsuz değerlendirilme korkusu arasında istatistiksel açıdan anlamlı ve olumlu yönde ilişkiler olduğunu göstermektedir. Hem lüks tüketim eğilimi hem de olumsuz değerlendirilme korkusu beğenilme arzusunu istatistiksel açıdan anlamlı olarak yordamaktadır. Olumsuz değerlendirilme korkusu değişkeni için kadınların ortalama puanlarının erkeklerinkinden istatistiksel açıdan anlamlı olarak daha yüksek olduğu tespit edilmiştir. Bulgular ilgili literatür temelinde tartışılmış ve ileride yapılacak olan çalışmalar için önerilerde bulunulmuştur.
A QUESTÃO DAS MENINAS ADOLESCENTES VÍTIMAS DE EXPOSIÇÃO SEXUAL NAS MÍDIAS DIGITAIS
Authors: Melo Ana Paula Dias , Ferreira Silvio Almeida , Maçalai Gabriel , De Sousa Jamilly Ferreira , De Souza Elizabethe Duarte , Dos Santos Katia da Silva , Wagner Everson Rafael , Barbosa Ederjofre de Oliveira , De Oliveira Wyderlannya Aguilar Costa , Da Silva Allan Cruz , Nunes Jadyelly Hilery Santana
Published: October 2023

O presente artigo tem como objetivos analisar os impactos na saúde mental das adolescentes vítimas de exposição sexual nas mídias digitais; e investigar os fatores biológicos e psicológicos envolvidos nos comportamentos das adolescentes em consequência da exposição em meios virtuais. Em relação à metodologia, realizamos uma pesquisa exploratória a fim de entendermos a realidade estudada, assim como contribuir para o debate e resolução do problema. A violência contra adolescentes dependendo da fase de crescimento e desenvolvimento em que ocorre, desenvolve alterações cerebrais podendo evoluir para problemas mentais, físicos e comportamentais, tornando-se perceptíveis na fase adulta. Com base nas pesquisas realizadas, concluímos que os indivíduos adolescentes estão na fase de reproduzir comportamentos assistidos no seu convívio social, isso explica porque da influência do contexto social no comportamento e desenvolvimento do adolescente, ressaltando a importância da educação em todas as esferas, tanto em saúde, como no social, e espiritual, assim como a importância de políticas públicas voltadas a essa população, ressaltamos no decorrer da pesquisa o importante papel da escola em repassar a educação aos adolescentes visto que é um ambiente onde esses indivíduos passam a maior parte do tempo e desenvolvem a maioria das suas relações sociais.
Kurdish literature in foreign languages as an alternative to Kurdish Language
Authors: Ismail Saeed Zahir , Salih Mawlood Rezan
Published: October 2023

kurdish is one of those nations in thousand in its history doesnt have a unity language and independent part.that´s why kurdish literature and its language was under the effects of the colony countries.The Kurdish poets and and writes couldn´t write and describe their own feelings with thier own languages because of the colony countries.Dividing kurds into four geographical parts (lraq,lran, Turkey and Syria) had effects on the kurdish poets and writers of those parts couldnt use kurdish language in their writings because of the threats and sansors. Even in those three parts(lran ,Syria and Turkey) writing and studying in kurdish was frobidden. Sometimes, The kurdish poets and writers faced jail and difficulty to get out of their homeland. Though it was difficult at that time to print their writings in Kurdish and mostly they denied to print their poems, So The kurdish poets and writers obligely they had written poems with the language of the colony countries. As a result، there was doubt the nationality of these literatures.Sometimes world had effects on them.Without facing any troubles and difficulties the writers had written with foreign languages.They thought that if they only write with Kurdish,though only kurdish could know them in this limited area and it couldn´t reach foreign readers.therefore they wanted to write with foreign languages.
The opinions of Sheikh Abu Bakr Al-Musannaf in his book Al-Dahih fi Sharh Al-Muharrar
Authors: Ahmed Kaka Hama Diyari , Bayez Muhammad Amin Akram
Published: October 2023

This research aims to find out the most correct opinion on an important jurisprudential issue. In which the jurists differed, which is the reading of the follower of Surat Al-Fatihah in the aloud prayer, starting with the weighting of Sheikh Abi Bakr, the Kurdish workbook in it, and then bringing the doctrines of the jurists, and their evidence, and explaining the aspect of the evidence from it, by referring to the approved jurisprudential books that were contained in it, concluding with mentioning the opinion of the researcher towards this difference; based on the comparative method.The research reached several results; Most notably: the obligation of the follower to read Surat Al-Fatihah in the silent prayer, and not to read it in the prayer out loud; Since he is commanded to listen to the imam, and there are no strokes for the imam in which the reading of Al-Fatihah can accommodate.Keywords: Abu Ba
The quality of YouTube videos on radiotherapy and prostatectomy for prostate cancer
Authors: Wong Natalie , Ingledew Paris-Ann
Published: October 2023

Introduction: Prostate cancer ranks as the third leading cause of death among Canadian men, and is primarily treated with radiotherapy and prostatectomy. Given YouTube's significant global traffic, patients often turn to it for information on treatment and side effects. This study assessed YouTube videos for prostate cancer patients, focusing on radiotherapy, prostatectomy, and side effect management.
Methods: The study analyzed 50 YouTube videos, comparing their accuracy and coverage against the National Comprehensive Cancer Network (NCCN), UpToDate, and cancer.ca. Two raters were involved in the review of the videos to ensure inter-rater reliability.
Results: Video lengths ranged from 1–60 minutes (mean 11 minutes), and creation dates ranged from 2012–2021. Videos were presented by physicians, patients, or allied health professionals (75%, 16%, and 8%, respectively). Results showed physician presenters had a Video Power Index (video popularity) of 23.45, while patient presenters had an average of 61.36 (almost three times as popular as physician-led videos). The overall accuracy of videos showed that 82% demonstrated completely accurate and detailed information, 18% showed partially complete information, and 76% showed no biased information. No false information was found in any videos.
Conclusions: This study showed that while the YouTube informational videos included good coverage of treatment side effects, there were gaps in information regarding quality of life after treatment or management of side effects. Information from this study can benefit the provider-patient interaction, with the hope that healthcare providers create more videos on quality of life after treatment and management of side effects to satisfy patient needs.
Genç Erkek Basketbolcularda Sürat, Çeviklik, Sıçrama ve Tekrarlı Sprint Performansı İlişkisi
Authors: ÇAYIR Hüseyin , CANİKLİ Abdullah , SÜEL Emin
Published: October 2023

Amaç: Bu çalışmanın amacı genç erkek basketbolcularda sürat, çeviklik, sıçrama ve tekrarlı sprint performansı ilişkisini incelemektir. Yöntem: Araştırmanın örneklemini 20 genç erkek basketbol oyuncusu (yaş: 16.00 ± 0.56; boy: 173.35 ± 6.34; kilo: 65.49 ± 6.67) gönüllü olarak oluşturmaktadır. Çalışmada 5 metre ve 10 metre sürat, T Testi çeviklik, karşı hareket sıçraması, skuat karşı hareket sıçraması ve tekrarlı sprint yeteneği testleri ölçülmüştür. Verilerin analizinde SPSS 26 istatistik programı kullanılmıştır. Bulgular: Çalışmanın bulgularına göre T Testi ile 5m (p
Improved Muscle Mass and Function With Protein Supplementation in Older Adults With Sarcopenia: A Meta-Analysis
Authors: Kwon Hyo Eun , Ko Nayeon , Yuk Doyoung , Choi Seo Won , Koh Seong-Eun
Published: October 2023

Objective: To systematically review the effects of protein supplementation in older adults with sarcopenia.Methods: A systematic literature search was conducted in PubMed, Cochrane Library, and Embase databases until May 2023. The inclusion criteria were as follows: (1) randomized controlled trials with a quantitative study design; (2) studies with a study group of older adults with sarcopenia; (3) studies comparing muscle mass, muscle strength, and performance of older adults with sarcopenia after protein supplementation; and (4) studies published up to May 2023.Results: Six retrospective comparative studies, including 715 patients, met the inclusion criteria. The nutritional supplementation group exhibited significant improvement in appendicular skeletal muscle mass (standardized mean difference [SMD]=0.41; 95% confidence interval [CI], 0.24–0.58; p<0.001; I2=1%), while handgrip strength (SMD=0.37; 95% CI, -0.32–1.07; p=0.29; I2=94%) and Short Physical Performance Battery (SPPB) (SMD=0.35; 95% CI, -0.47–1.18; p=0.40; I2=94%) showed a tendency for improvement.Conclusion: Nutritional supplementation with protein increased appendicular muscle mass in older adults with sarcopenia and improved handgrip strength and SPPB scores.
Social Media and Women Mobilization for Community Development
Authors: Ahmad Sharu Aisha , Joseph Ayodele B.
Published: October 2023

The study explored the potential of social media for women mobilization to attain community development. Social media has become a very powerful platform that informs and educates its users. Community development is the advancement and progress of a particular community. Women play a vital role in community development. The study seeks to know the effects of social media in mobilizing women as well as examining how social media can help in women empowerment for community development. For the purpose of this study, the Diffusion of Innovation theory was employed to further expatiate the impact of social media for community development. Conclusively, it can be seen as though social media is very essential in mobilizing women for community development. Social media plays a vital role in enhancing community development. However, government should support programs that empower women. It is recommended that Development Agencies and State Ministry of Women Affairs should increase advocacy visits to women in the communities.
The Impact of Poverty and Capital Expenditure on The Human Development Index in North Sumatra
Authors: Murbanto Sinaga  , Rika Surianto Zalukhu
Published: October 2023

Human development in north Sumatra is showing progress. However, the human development disparity in the North Sumatra province is still showing. The problem must be overcome quickly to prevent further disparity from developing. The study was to analyze the impact of poverty and capital expenditure on Human Development Index (HDI) of regency/city in North Sumatra. This study uses quantitative descriptive methods which have been provided by previous study conducted on 33 regencies/cities in the North Sumatra. The data covers the poverty rate, capital expenditure and HDI of regency/city in North Sumatra in 2019. Data was accessed online on the Central Statistical Agency (BPS) for North Sumatra Province website. Data analysis method using multiple linear regression analysis method. Analysis shows that poverty has a negative and significant impact on HDI of regency/city in North Sumatra. Meanwhile, capital expenditure has a positive and insignificant effect on of regency/city in North Sumatra. Poverty and capital expenditure are simultaneously significant on HDI of regency/city in North Sumatra. The result of this study implicates allocation of capital expenditure and the creation of human development strategies for the district or city in the north Sumatra province.
ANALYSIS OF EFFECTIVENESS AND EFFICIENCY OF EXPENDITURE BUDGET ABSORPTION AT UNIVERSITAS NEGERI MALANG FOR THE 2019-2021 FISCAL YEAR
Authors: Puji Agus Kurniawan  , Djuni Farhan
Published: October 2023

Financial governance in the management of the expenditure budget is a planning tool to indicate targets to be achieved and a control tool to indicate the allocation of funds. The budget that has been set can be used as a standard for performance measurement activities, so every organization is expected in controlling or supervising to pay attention to and improve performance with value for money, namely effectively and efficiently. This study aims to analyze: (1) measure the effectiveness and efficiency of budget absorption at Universitas Negeri Malang for the 2019-2021 Fiscal Year, (2) analyze the level of effectiveness and efficiency of budget absorption at Malang State University for the 2019-2021 Fiscal Year The research method used is descriptive qualitative with a case study research method using non-statistical qualitative research techniques. The results showed that there were expenditure programs that were not realized and several other programs whose realization was not optimal so they did not reach the target.
Investigating the Factors Influencing Employee Performance
Authors: Deddy Novie Citra Arta  , Syamsu Rijal  , Harun Samsudin  , I Nyoman Tri Sutaguna
Published: October 2023

This study aims to analyze the influence of Leadership Style, Motivation and Work Discipline on the Performance of Government Apparatuses in Cicendo District, Bandung City. This study involved 63 Cicendo District government officials, Bandung City, and all of them became respondents using a multiple linear regression analysis model. The results of this study indicate that Leadership Style, Motivation and Work Discipline simultaneously have a positive and significant influence on the performance of Cicendo District Government Apparatuses, Bandung City. While partially it was found that the leadership style factor had the most dominant significant influence on the performance of the Cicendo District Government Apparatus, Bandung City.
MARKETING STRATEGY FOR INCREASING SALES OF COOKING OIL SHOES IN BAROKAH TRADING BUSINESS
Authors: I Nyoman Tri Sutaguna  , Gusti Noorlitaria Achmad  , Andriya Risdwiyanto  , Muhammad Yusuf
Published: October 2023

In every line of business, strategy is important because it is a series of decisions and actions directed at achieving company goals. More than that, entrepreneurs need a marketing strategy for their business. This is very important because it is a fundamental tool planned to achieve company goals by developing a sustainable competitive advantage through the markets entered and marketing programs used to serve target markets. This research conducted in UD. Barokah which is located in Jatinangor, Sumedang Regency. The phenomenon that occurs is that the monthly target set by the company is not achieved even though several strategies have been implemented. The purpose of this research is to find out the right marketing strategy in increasing the number of sales and being able to survive in the face of competition in basic cooking oil at UD. Barokah, Sumedang District. This research is a field research with a descriptive qualitative approach. Data is obtained from shop owners, employees, and regular customers. Methods of data collection by observation, interviews, and documentation. The approach used in this study is the SWOT analysis approach, which is the systematic identification of various factors to formulate corporate strategy. Based on the results of the analysis of the SWOT diagram and SWOT matrix, it can be seen that Barokah Trading Business is in quadrant I (Aggressive Strategy) and on the SO strategy, where the company's strengths and opportunities are greater than its weaknesses and threats. The SO strategy is the most appropriate strategy for UD. Barokah , while other strategies can be used as alternative strategies for reference and consideration that can develop and increase sales of Barokah Business Trade products . In addition, the Barokah Trading Business can also combine the ST strategy, WO strategy and WT strategy as needed to maximize the marketing strategy implemented. where the strengths and opportunities of the company are greater than the weaknesses and threats. The SO strategy is the most appropriate strategy for UD. Barokah , while other strategies can be used as alternative strategies for reference and consideration that can develop and increase sales of Barokah Business Trade products . In addition, the Barokah Trading Business can also combine the ST strategy, WO strategy and WT strategy as needed to maximize the marketing strategy implemented. where the strengths and opportunities of the company are greater than the weaknesses and threats. The SO strategy is the most appropriate strategy for UD. Barokah , while other strategies can be used as alternative strategies for reference and consideration that can develop and increase sales of Barokah Business Trade products . In addition, the Barokah Trading Business can also combine the ST strategy, WO strategy and WT strategy as needed to maximize the marketing strategy implemented.
THE EFFECT OF OPERATING CASH FLOW AND NET PROFIT ON SHARE RETURN, 2022-2022
Authors: Abdul Karim
Published: October 2023

This study aims to find out, analyze and describe the effect of operating cash flow and net income on stock returns in 2022-2022 in agricultural sector companies. This study uses secondary data contained in the Indonesian Stock Exchange. With the sample technique carried out by the author, the authors obtained a sample of this research as many as 7 companies from 21 companies in the agricultural sector, from 2022-2022 with annual data from operating cash flow and net income on stock returns resulting in 32 data in this study.
THE IMPACT OF PRIVACY, SECURITY, AND TRUST ON ONLINE TRANSACTION INTENTIONS AT BANK BCA BANDUNG
Authors: Eva Purnamasari  , Asri Ady Bakri  , Eko Cahyo Mayndarto
Published: October 2023

Bank BCA is one of the banks that strengthens its efforts in developing service products by utilizing the internet to make online transactions. So this study aims to determine the effect of privacy, security, and trust on the intention to transact online at Bank BCA Bandung. The method used in this research is a quantitative descriptive method. Research location at Bank BCA Bandung No. 18 in October 2022. The population is customers who visited in the October 2022 period. Sampling was carried out using an incidental sampling technique with a total of 97 customers. Data collection techniques using a questionnaire. Data analysis techniques were performed using the t-test and F-test. The results of the study found that privacy, security, trust has a simultaneous and partial effect on the intention to transact online at Bank BCA Bandung. The effect is 51.9%, while the remaining 48.1% is influenced by other variables not examined in this study
DEVELOPMENT OF MACRO-BASED STRATEGIC PLANNING APPLICATION EXCEL: AS A TOOL FOR FORMULATING HUMAN RESOURCE MANAGEMENT SRATEGIS
Authors: Elfia Nora  , Madziatul Churiyah
Published: October 2023

Abstract

So far, in formulating strategies in an organization, especially reviewing from the aspect of human resource management, analytical tools that are often used to process the data obtained are SWOT Analysts, Internal Factor Analysis and External factors and Competitive Profile Matrix how to analyze the strength of weaknesses in opportunities and threats of a company (SWOT)  and matrix Competitive profile analyzes the strategic position of the company compared to similar competitors, especially in terms of human resource management, namely employees, because employees are the spearhead of an organization.

The purpose of software development in the form of this application is so that it can be used to formulate strategies in the organization and  its specifics can be applied also to formulate strategies in the human resource management division Software   tools developed in  the form of analytical tools in the form of applications consisting of SWOT Analysis, Competitive Profile Matrix, External and Internal environment analysis per business  in the form of data analysis tables and diagrams that can illustrate weights, ratings and interpret the company's position and formulate strategies that are suitable for the company to apply.

The development method carried out is the development model of Borg & Gall (2001) using waterfall grooves at the development stage.

The results of this software development are called macro excel-based strategic planning applications) which are tested by including fictitious data on human resource management, IFA and EFA analysis, SWOT analysis, and Competitive Profile Matrix, and the  result is a quadrant of strategies that formulate what strategies can be applied to the organization's resource management division.
Social Media Marketing's Effect On Customer Satisfaction
Authors: Frans Sudirjo  , I Nyoman Tri Sutaguna  , Rina Sovianti  , Arief Yanto Rukmana  , PA. Andiena nindya putri
Published: October 2023

Human wants are limitless. Primary needs, secondary needs, and tertiary needs are the three sorts of needs that humans have. All of these requirements, especially basic requirements, are critical to human survival. The fundamental necessities themselves are food, clothing, and shelter, i.e. the need for important goods like clothing, food, and shelter. The most crucial element is the necessity for a place to live, a place to dwell or what we often refer to as home, as a place for us to take refuge and socialise with the environment. As a result, many people desire a suitable place to reside. This study took a quantitative approach, with 195 persons chosen utilising the Accidental Sampling technique. Multiple regression analysis reveals that all independent factors (product quality and price) have a positive effect on purchase intent.