bluuebunny/crossref_metadata_2025 huggingface dataset:
Operability of Smart Spaces in Urban Environments: A Systematic Review on Enhancing Functionality and User Experience
Authors: Ndaguba Emeka , Cilliers Jua , Ghosh Sumita , Herath Shanaka , Mussi Eveline Tancredo
Published: August 2023

This literature review highlights the emergence of the Internet of Things (IoT) and the proliferation of connected devices as the driving force behind the adoption of smart spaces. This review also discusses the various applications of smart spaces, including smart homes, smart cities, and smart healthcare: (1) Background: the aim of this research is to provide a comprehensive overview of the concept of smart spaces, including their key features, technologies, and applications in built environments and urban areas; (2) Methods: The study adopts a qualitative approach, drawing on secondary sources, such as academic journals, reports, and online sources; (3) Results: The findings suggest that smart spaces have the potential to transform the way people interact with their environment and each other. They could improve efficiency, safety, and quality of life. However, there are also concerns about privacy and security in relation to the collection and use of personal data; (4) Conclusions: The study concludes that smart spaces have significant theoretical and practical implications for various fields, including architecture, urban planning, and healthcare. The theoretical implications include the need for new models and frameworks to understand the complex relationships between technology, space, and society. The practical implications involve the development of new standards and regulations to ensure the responsible and ethical use of smart spaces.
The NWRD Dataset: An Open-Source Annotated Segmentation Dataset of Diseased Wheat Crop
Authors: Anwar Hirra , Khan Saad Ullah , Ghaffar Muhammad Mohsin , Fayyaz Muhammad , Khan Muhammad Jawad , Weis Christian , Wehn Norbert , Shafait Faisal
Published: August 2023

Wheat stripe rust disease (WRD) is extremely detrimental to wheat crop health, and it severely affects the crop yield, increasing the risk of food insecurity. Manual inspection by trained personnel is carried out to inspect the disease spread and extent of damage to wheat fields. However, this is quite inefficient, time-consuming, and laborious, owing to the large area of wheat plantations. Artificial intelligence (AI) and deep learning (DL) offer efficient and accurate solutions to such real-world problems. By analyzing large amounts of data, AI algorithms can identify patterns that are difficult for humans to detect, enabling early disease detection and prevention. However, deep learning models are data-driven, and scarcity of data related to specific crop diseases is one major hindrance in developing models. To overcome this limitation, in this work, we introduce an annotated real-world semantic segmentation dataset named the NUST Wheat Rust Disease (NWRD) dataset. Multileaf images from wheat fields under various illumination conditions with complex backgrounds were collected, preprocessed, and manually annotated to construct a segmentation dataset specific to wheat stripe rust disease. Classification of WRD into different types and categories is a task that has been solved in the literature; however, semantic segmentation of wheat crops to identify the specific areas of plants and leaves affected by the disease remains a challenge. For this reason, in this work, we target semantic segmentation of WRD to estimate the extent of disease spread in wheat fields. Sections of fields where the disease is prevalent need to be segmented to ensure that the sick plants are quarantined and remedial actions are taken. This will consequently limit the use of harmful fungicides only on the targeted disease area instead of the majority of wheat fields, promoting environmentally friendly and sustainable farming solutions. Owing to the complexity of the proposed NWRD segmentation dataset, in our experiments, promising results were obtained using the UNet semantic segmentation model and the proposed adaptive patching with feedback (APF) technique, which produced a precision of 0.506, recall of 0.624, and F1 score of 0.557 for the rust class.
Visual Intelligence in Precision Agriculture: Exploring Plant Disease Detection via Efficient Vision Transformers
Authors: Parez Sana , Dilshad Naqqash , Alghamdi Norah Saleh , Alanazi Turki M. , Lee Jong Weon
Published: August 2023

In order for a country’s economy to grow, agricultural development is essential. Plant diseases, however, severely hamper crop growth rate and quality. In the absence of domain experts and with low contrast information, accurate identification of these diseases is very challenging and time-consuming. This leads to an agricultural management system in need of a method for automatically detecting disease at an early stage. As a consequence of dimensionality reduction, CNN-based models use pooling layers, which results in the loss of vital information, including the precise location of the most prominent features. In response to these challenges, we propose a fine-tuned technique, GreenViT, for detecting plant infections and diseases based on Vision Transformers (ViTs). Similar to word embedding, we divide the input image into smaller blocks or patches and feed these to the ViT sequentially. Our approach leverages the strengths of ViTs in order to overcome the problems associated with CNN-based models. Experiments on widely used benchmark datasets were conducted to evaluate the proposed GreenViT performance. Based on the obtained experimental outcomes, the proposed technique outperforms state-of-the-art (SOTA) CNN models for detecting plant diseases.
Empirical Analysis of the Impact of Top Management Team Social Networks on the Homophily Effect of ESG Disclosure in Companies
Authors: Zhang Jing , Liu Ziyang
Published: August 2023

This study investigates the homophily effect in corporate information disclosure, specifically focusing on executive social networks. We analyze data from 385 privately listed companies in China’s Growth Enterprise Market between 2018 and 2021. An OLS regression model is employed to examine the presence of a homophily effect in ESG information disclosure by private enterprises, along with regional and industry variations. Additionally, we utilize a moderation effect model to assess the influence of executive social networks on the homophily effect of ESG information disclosure. We conduct robustness tests based on our findings. The results indicate a significant homophily effect in ESG information disclosure by private enterprises, with varying magnitudes across regions and industries. Furthermore, executive social networks positively moderate the homophily effect, suggesting that a more diverse social network among the executive team enhances the homophily effect of ESG information disclosure for private enterprises. These findings offer valuable insights for corporate low-carbon sustainable development.
Seasonal Influenza Vaccine Effectiveness in Persons Aged 15–64 Years: A Systematic Review and Meta-Analysis
Authors: Martins João Paulo , Santos Marlene , Martins André , Felgueiras Miguel , Santos Rui
Published: August 2023

Influenza is a respiratory disease caused by the influenza virus, which is highly transmissible in humans. This paper presents a systematic review and meta-analysis of randomized controlled trials (RCTs) and test-negative designs (TNDs) to assess the vaccine effectiveness (VE) of seasonal influenza vaccines (SIVs) in humans aged 15 to 64 years. An electronic search to identify all relevant studies was performed. The outcome measure of interest was VE on laboratory-confirmed influenza (any strain). Quality assessment was performed using the Cochrane risk-of-bias tool for RCTs and the ROBINS-I tool for TNDs. The search identified a total of 2993 records, but only 123 studies from 73 papers were included in the meta-analysis. Of these studies, 9 were RCTs and 116 were TNDs. The pooled VE was 48% (95% CI: 42–54) for RCTs, 55.4% (95% CI: 43.2–64.9) when there was a match between the vaccine and most prevalent circulating strains and 39.3% (95% CI: 23.5–51.9) otherwise. The TNDs’ adjusted VE was equal to 39.9% (95% CI: 31–48), 45.1 (95% CI: 38.7–50.8) when there was a match and 35.1 (95% CI: 29.0–40.7) otherwise. The match between strains included in the vaccine and strains in circulation is the most important factor in the VE. It increases by more than 25% when there is a match with the most prevalent circulating strains. The laboratorial method for confirmation of influenza is a possible source of bias when estimating VE.
Volatile Sulfur Compounds Produced by the Anaerobic Bacteria Porphyromonas spp. Isolated from the Oral Cavities of Dogs
Authors: Ito Noriyuki , Itoh Naoyuki , Kameshima Satoshi
Published: August 2023

Porphyromonas spp. are oral anaerobic Gram-negative bacteria that form black-pigmented colonies on blood agar and produce volatile sulfur compounds (VSCs), such as hydrogen sulfide (H2S), methyl mercaptan (CH3SH), and dimethyl sulfide ((CH3)2S), which cause halitosis and the destruction of periodontal tissues. P. gulae is considered the main pathogen involved in periodontal disease in dogs. However, the characteristics of the VSCs produced by P. gulae are unknown. In the present study, VSCs were measured in 26 isolates of P. gulae and some isolates of the other Porphyromonas spp. obtained from the oral cavities of dogs with periodontal disease using an in vitro assay with an Oral ChromaTM gas chromatograph. The results demonstrated that P. gulae was able to produce large amounts of H2S and CH3SH, and the dominant product was CH3SH (CH3SH/H2S was approximately 2.2). Other Porphyromonas spp. that were also obtained from the oral cavities of dogs with periodontal disease indicated similar levels of production of H2S and CH3SH to those of P. gulae. It is strongly suggested that the high levels of H2S and CH3SH produced by P. gulae and other Porphyromonas spp. contribute to halitosis and the destruction of periodontal tissues during the progression of periodontal disease in dogs.
The role of MR spectroscopy in the differential diagnosis of anaplastic glioma
Authors:   FSBEI HE Privolzhsky Research Medical University of the Ministry of Health of the Russian Federation, Nizhny Novgorod, Badu S.K.
Published: August 2023

The role of biomarkers for detecting tumors has aroused interest in their use for diagnostics as well. Biomarkers can be isolated from biological fluids, such as blood, cerebrospinal fluid, and urine. Apparently, the most promising is the study of blood plasma and serum, which are isolated from whole blood and are the most studied biological resources for the potential detection of molecular markers. This direction includes studies to identify immunological or biochemical biomarkers of the presence of tumors in the cerebrospinal fluid or in the blood of patients. Infrared spectroscopy of plasma and blood serum of patients with tumors is more promising in terms of identifying not only individual mRNAs as markers of gliomas, but also fats, proteins, and carbohydrates. The study of the profile of metabolites in blood plasma by methods of the recently emerged science of "metabolomics" has good prospects. This gives information about the biochemical processes occurring in tumors and provides knowledge for determining the treatment tactics for recurrent growth.
An up-to-date look at the options for transforming the plot of delusional ideas (literature review)
Authors:   Federal State Budgetary Educational Institution of Higher Education «Saratov State Medical University named after V. I. Razumovsky » of the Ministry of Health of the Russian Federation, Knyazeva A. O. , Samoilova D. D. ,   Federal State Budgetary Educational Institution of Higher Education «Saratov State Medical University named after V. I. Razumovsky » of the Ministry of Health of the Russian Federation
Published: August 2023

The article discusses the relevance of studying the variants of transformation of stories, plots, and themes of delusional ideas in the structure of mental disorders under the influence of sociocultural factors. Delusional ideas related to the KGB activities, the Internet use, a clinical case of «delusions of coronаvirus self-contempt», and delusional ideas that arose under the influence of religious motives are given as an example.
Degenerative disc disease: pathophysiology, diagnosis, and classification
Authors:   Department of Neurological Diseases and Neurosurgery, Peoples' Friendship University of Russia, Moscow, Russia, Musa G. , Makirov S. K. ,   Scientific Technical Center, Clinic «Semeynaya», Moscow, Russia, Chmutin G. E. ,   Department of Neurological Diseases and Neurosurgery, Peoples' Friendship University of Russia, Moscow, Russia, Chmutin E. G. ,   Department of Neurological Diseases and Neurosurgery, Peoples' Friendship University of Russia, Moscow, Russi, 3FSBI National Medical Research Center for High Medical Technologies named after A. A. Vishnevsky of the Ministry of Defense of the Russian Federation, Krasnogorska, Antonov G. I. ,   Department of Neurological Diseases and Neurosurgery, Peoples' Friendship University of Russia, Moscow, Russia, Kim A. V. ,   Demikhov City Clinical Hospital No. 68, Moscow, Russia, Shaafal H. M. Q. ,   Department of Neurological Diseases and Neurosurgery, Peoples' Friendship University of Russia, Moscow, Russia, Khovrin D. V. ,   S.S. Yudin City Clinical Hospital No. 7, Moscow, Russia, Otarov O. ,   Scientific Technical Center, Clinic «Semeynaya», Moscow, Russia
Published: August 2023

Degenerative-dystrophic disease (DDD) and its complications is the most common condition in spinal neurosurgery. It affects about 80 % of all people over 80 and is the most common cause of disability in the middle-aged population. The main symptoms include mechanical back pain, symptoms of radiculitis and limping, limited mobility, and poor quality of life. Determining the pathophysiology, causes of DDD pain, as well as diagnostic tools and expected changes is paramount to improve patient care and satisfaction. In this paper, we present an overview of DDD pathophysiology, classification, and diagnosis.
Hypothymia in alcohol dependence
Authors:   Department of Psychiatry and Narcology, I.M. Sechenov First Moscow State Medical University, Moscow, Darenskiy I.D.
Published: August 2023

The purpose of the work is to identify hypothymic disorders typical for patients with alcohol dependence. Material and methods. 100 male patients aged 38-53 years who were hospitalized for alcohol dependence with a typical course in the early post-withdrawal period were examined. The examination was carried out by the clinical method and using the HDRS scale. Results. Affective disorders in alcohol addicts manifested in the form of hypothymia within the asthenic (cerebro-asthenic) syndrome, which is fundamentally different from the depressive disorders that are typical for psychiatric diseases. Conclusions. The peculiarity of the hypothymic symptoms is sufficient to negate their similarity to depression in psychiatric illnesses. The use of the concept of depression in narcology is carried out with an assumption that often distorts the true state of affairs in the clinical picture.
Development and Evaluation of an On-Line Educational Module for Volunteer Leaders on Bio-Security in Washington State 4-H Livestock Projects
Authors: Stevenson Jill , Moore Dale , Newman Jerry , Schmidt Janet , Smith Sarah , Smith Jean , Kerr Susan , Wallace Michael , Boyes Pat
Published: August 2023

A module on disease prevention was created for 4-H volunteer leaders who work with livestock projects in Washington to better prepare them to teach youth about bio-security and its importance in 4-H livestock projects. Evaluation of the module and usage statistics since the module's debut were collected and evaluated. The module increases awareness of disease prevention and provides practical approaches to implementation of bio-security, but is underused by the target audience, possibly due to leaders' lack of computer access, time, or awareness of the module. Promotion of the module and incentives must be explored to increase module usage.
An Evaluation of Partners in Parenting: A Parent Education Curriculum Implemented by County Extension Agents in Colorado
Authors: Wilson Kristina , Hahn Laura , Gonzalez Patricia , Henry Kimberly , Cerbana Christine
Published: August 2023

The study reported here evaluated the efficacy of Partners in Parenting (PIP), which, in collaboration with Colorado State University Extension, was implemented in seven counties across Colorado. A total of 54 parents took part in the study. A pretest/posttest design was used to assess short-term changes in parenting practices, parental attitudes, and parental stress following intervention. After PIP, parents demonstrated improvement in basic elements of parent-child relationships and parenting attitudes and skills. These promising results warrant further investigation into the benefits of parent education programs implemented by Extension agencies in the communities they serve.
Information Needs of Agricultural Consultants in Ohio
Authors: Diekmann Florian , Battle Marvin
Published: August 2023

The research reported here aimed to better further a better understanding of Ohio agricultural consultants' information needs and use. Our sample represented private consultants from organizations of different sizes and types servicing various segments of the agricultural sector. Findings of an online survey show that a high demand exists for information related to crops and environment/conservation subject-matter areas. Agribusiness/economics information also ranked high in importance. Respondents were familiar with the services Ohio State University Extension provided and reported to frequently use Extension information. Most popular were print publications and electronic newsletters followed by visits to Extension websites.
Shared Beds: Ragdale Ring 2019
Authors:   Cornell University, Costanza David , Mazzocca Pierianna ,   University of Texas at Austin
Published: August 2023

Launched as an international competition in 2013 to reinterpret Howard Van Doren Shaw’s Ring as a temporary, experimental environment, the Ragdale Ring competition has provided young architects and designers the annual occasion to conceive and construct a temporary performance venue and public gathering space on the Ragdale campus in Lake Forest, Illinois. The premise of the competition responds and reinterprets Shaw’s original Ragdale Ring, which was conceived as an open-air theatre for his poet and playwright wife, Frances Wells Shaw.1 As the winning proposal of the competition and built on the grounds of the Ragdale Foundation in June 2019, Shared Beds sought to challenge the role of the individual vis-à-vis the collective by reconsidering the seemingly inanimate quality of everyday objects such as beds and their assumed immutable location inside private domains. Thus, beds are used in this project to invoke a shared public life through a nuanced, abstract language of simple geometrical forms.
Crisiscity: Cyborg Infrastructure in the Anthropocene
Authors:   Pratt Institute, Barker Alexandra
Published: August 2023

In the Anthropocene thesis, nature is partly a human creation. Human activity has affected all ecologic, geologic and biological systems, eroding the boundary between human and non-human life and between nature and culture, producing catastrophic impacts on the Earth that have brought us to a point of climate crisis. As recent texts have argued, the cur¬rent social and health crises are direct resultants of human actions dating back to the time of Western colonization. Human pollution of the global ecosystem has produced the climate crisis. As the pandemic of COVID-19 continues to show, the health of people, animals, ecosystems and the environment are intimately linked. The health crisis has also exposed weaknesses in our global supply chain network for consumer goods. Localizing food and fuel production and storage for easy distribution is a key approach to addressing issues of food and energy insecurity in this context. This graduate architecture studio project proposes additions to and reuse of existing urban infrastructure to locally situate small-scale food and energy production and storage facilities squarely within the dense urban fabric of major metropolitan areas as a retrofit embedded inside existing building fabric within the public realm. Seafood aquaculture, aquaponics, hydroponics, and algae farming processes produce high yields in relatively compact environments without the necessary access to light and space that typical crops require. Oyster aquaculture can produce food as well as seed for filtering oyster beds that are critical for the cleansing of polluted waterways. These programs also provide a source of jobs locally accessible to urban communities. Our test site for this project is a speculative mixed-use addition and alteration to abandoned industrial buildings in Brooklyn’s industrial waterfronts of Red Hook and Sunset Park proposing light manufacturing in combination with public programs. Anamorphic projection techniques in the design process produce specific orientations toward both human and non-human occupants.
Draped Stone: A Synclastic Tensile Canopy
Authors:   Cornell University, Costanza David
Published: August 2023

Draped Stone is a research project that uses stone in tension through fiber-reinforcement, producing a hanging marble canopy. The research is in collaboration with stone fabrica¬tor Quarra Stone in Madison Wisconsin as part of a Research Fellowship. The project is still in development and is currently the subject of multiple grants to complete the pavilion. The project submission represents the work in progress to date— with all the research and development—for a fiber-reinforced stone and an automated workflow for 5-Axis machining mar¬ble and laminating fiberglass to machined marble surfaces.
Efectos indirectos no deseados del sistema de crédito hipotecario UVA
Authors:   , Pratolongo Adrián Jesús Matías
Published: August 2023

En el presente trabajo de tesis, se buscará comprobar la existencia de efectos indirectos no deseados producto de la implementación del Sistema de Crédito Hipotecario UVA. Estos efectos no deseados, se centrarán sobre aspectos relacionados a indicadores laborales y/o de endeudamiento que afecten a la generalidad de los tomadores de crédito. La presunción intuitiva que guiara el análisis son los efectos adversos que produce el desacople de la relación cuota ingreso en los tomadores, buscando vislumbrar las diversas respuestas generadas en termino de ahorro o decisiones laborales que han debido tomar las familias tomadoras del crédito.
PENGARUH MODEL PROBLEM-BASED LEARNING TERHADAP KETERAMPILAN BERPIKIR KRITIS SISWA KELAS XI MIA SMA NEGERI 10 GOWA
Authors: Sinusi Nur Suhaiba
Published: August 2023

Abstrak : Penelitian ini bertujuan untuk mengetahui pengaruh model pembelajaran problem-based learningterhadap peningkatan keterampilan berpikir kritis siswa pada kelas XI MIA SMA Negeri 10 Gowa. Sampel dalam penelitian ini adalah siswa kelas XI MIA 2 sebagai kelas eksperimen dan kelas XI MIA 3 sebagai kelas kontrol yang diperoleh dengan menggunakan teknik simple random sampling. Penelitian ini menggunakan rancangan penelitian eksperimen semu pretest-posttest nonequivalent control group design. Keterampilan berpikir kritis diukur dengan menggunakan tes essay pada materi sistem sirkulasi. Data yang diperoleh dianalisis secara statistik deskriptif dan statistik inferensial dengan anakova. Hasil penelitian menunjukkan bahwa (1) rata-rata nilai keterampilan berpikir kritis siswa yang dibelajarkan dengan model problem-based learningadalah 73 yang masuk dalam kategori tinggi; (2) terdapat pengaruh pengaruh model pembelajaran Problem-based learning terhadap keterampilan berpikir kritis siswa dengan nilai signifikansi 0.00.
Pengaruh Model Pembelajaran Berbasis Masalah Terhadap Hasil Belajar Biologi dan Keterampilan Berpikir Kritis Peserta Didik
Authors: Patmawati Patmawati , Hala Yusminah , Arsyad Muhammad
Published: August 2023

Influence Of Problem Based Learning Model To Biology Learning Outcomes And Critical Thinking Skill Of Students. This research is a quasi experimental with pretest posttest control group design which aims to determine critical thinking skills and learning outcomes. The research sample was randomly selected and the XII IPA 1 was selected as the control and the XII IPA 3 as experimental class. The technique of collecting data was through giving test description to measure critical thinking skills and multiple choice test to measure biology learning outcomes. The data analysis technique used are descriptive and inferential statistics analysis with the independent sample t-test. The result of descriptive analysis show that students who are taught with the model problem based learning have critical thinking skills and learning outcomes in the middle category. While the results of inferential analysis show that there are differences in critical thinking skills and learning outcomes of students who are using the problem based learning model and conventional learning, that show average value of problem-based learning model are higher. The results show the problem based learning model has a positive effect on critical thinking skills and biology learning outcomes in mutation topic at SMAN 10 Luwu Utara.
Pengaruh Penerapan Model Problem Based Learning Terhadap Hasil Belajar dan Motivasi Belajar Peserta Didik MTsS Nurul Yaqin Benteng Kabupaten Kepulauan Selayar
Authors: Nurmiati Nurmiati , Daud Firdaus , Danial Muhammad
Published: August 2023

The study is a quasi-experimental research (quasi-experimental design) which aims to examine the influence of Problem Based Learning model on learning outcomes and students’ learning motivation at MTsS Nurul Yaqin Benteng in Selayar Islands district. The population in this study were all students of MTsS Nurul Yaqin Benteng of grade VIII for academic year of 2021/2022. Samples were taken by using Random Sample technique. The learning motivation data were collected by using learning motivation questionnaire; whereas, the learning outcomes data were collected by using multiple choice test. Data were analyzed by employing descriptive analysis and t-test on SPSS version 23.0. The results of the study reveal that the students who were taught by using the Problem Based Learning model experienced an increase in learning outcomes which is in high category. Meanwhile, the students who were taught by using direct learning also experienced an increase in learning outcomes and learning motivation which is in high category. The results of hypothesis testing using the t-test show the learning outcomes sig (2-tailed) > α 0.05 or 0.000 > α 0.05. H0 is rejected and H1 is accepted. Based on the test criteria, it can be concluded that there is an influence of implementing the Problem Based Learning model on learning outcomes and students’ learning motivation on Human Digestive System material in grade VIII at MTsS Nurul Yaqin Benteng in Selayar Islands district.
Pengaruh Model Pembelajaran Guided Discovery terhadap Peningkatan Hasil Belajar dan Efikasi Diri Peserta Didik
Authors: Wahidah Nur , Hala Yusminah , Arsyad Muhammad
Published: August 2023

This study is a quasi-experimental research that aims to examine whether there is an influence of Guided Discovery learning model on learning outcomes and students’ self-efficacy with  pretest-posttest control group design. Data on learning outcomes were obtained through pre-test and post-test by giving a written test in the form of multiple choice questions with 30 questions, while self-efficacy data was also obtained through pre-test and post-test from filling out a self-efficacy questionnaire with 30 statements. The data analysis technique employed descriptive statistical analysis, N-Gain, and inferential with t test (independent sample test). The results of descriptive analysis show that (1) the learning outcomes of experimental class students are in moderate category. (2) for self-efficacy of experimental class students in moderate category. (3) the learning outcomes in the control class is in low category. (4) the students’ self-efficacy in the control class is in low category (5) the results of inferential statistical analysis show that there is a significant influence of implementing Guided Discovery learning model on the improvement of learning outcomes and self-efficacy of grade VIII students at SMPN Gollek No. 34 Selayar Islands.
Pengembangan Media Pembelajaran E-Book Biologi pada Materi Sistem Reproduksi Manusia di Kelas XI
Authors: Hadir Husnul Khatimah
Published: August 2023

This study is a development research that aims to produce a product in the form of a Biology e-book learning media on human reproductive system material. This development research refers to the development model of Alessi & Trollip’s model which consists of three stages, namely planning, design, and development. The research instruments used were instrument validation sheets, teacher’s response questionnaire, students’ questionnaires, and learning outcomes test. The samples in this study were students of grade XI at SMK Kesehatan Yapika Makassar (Vocational High School of Health at Yapika Makassar). Based on the results of data analysis, it shows that: 1) the Biological e-book learning media on human reproductive system material meets the valid criteria with a mean score of 4.8 (valid), 2) the Biology e-book learning media on human reproductive system material meets the practical criteria based on the results of the teacher's response by 80.71% (very positive) and the result of the students’ responsesby 78.70% (positive), and 3) the Biology e-book learning media on human reproductive system material meets the effective criteria with the percentage of completeness of learning outcomes by 75% (good). Based on the results of the study, it can be concluded that the Biological e-book learning media on human reproductive system material has met valid, practical, and effective criteria.
ANALISIS MEDIA SIBER PADA AKUN INSTAGRAM @POTONGANFILM SEBAGAI RUANG KOMUNITAS VIRTUAL
Authors: Anandayan Valen , Adiprabowo Vani Dias
Published: August 2023

Penelitian ini dilakukan bertujuan untuk memahami aktivitas interaksi pada komunitas virtual serta unsur komunikasi visual yang terjadi di dalam akun instagram @potonganfilm. Akun instagram @potonganfilm merupakan satu dari sekian banyaknya media online yang menciptakan komunitas virtual dengan penyajian konten yang menarik mengenai film sebagai lingkup informasinya. Akun instagram @potonganfilm mampu membentuk komunitas virtual dengan terciptanya interaksi, diskusi, serta bertukar pikiran antar pengguna. Penelitian ini menggunakan metode kualitatif dengan etnografi virtual melalui pendekatan analisis media siber yang mencakup 4 level, yaitu level ruang media, level dokumen media, level objek media, dan level pengalaman. Hasil penelitian ini menunjukan bahwa level ruang media pada akun tersebut berisikan informasi dan review film opini pemilik akun tersebut dengan menampilkan grafis informasi beberapa film. Pada level dokumen, unggahan yang disajikan akun instagram @potonganfilm meliputi; judul film, tahun film, tahun film, poster film, dan screenshot potongan film (legal). Serta akun ini telah memenuhi unsur komunikasi visual yaitu: garis, bentuk, tekstur, gelap terang, ukuran, warna, dan tipografi. Pada objek media, interaksi dan aktivitas para pengikut ialah memberikan komentar pada postingan. Level pengalaman media, sebagian besar pengikut mengikuti akun tersebut karena mendapatkan informasi tentang film dengan penyajian yang menarik.
PERAN JEJARING SOSIAL KOMUNIKASI DALAM ANALISIS SENTIMEN DI TWITTER PADA TAGAR #KOMNASHAM (STUDI KASUS: KKB PAPUA)
Authors: Fikriyah Saniyah Nabila , Weninggalih Prawiro
Published: August 2023

Penelitian ini mengkaji jaringan komunikasi di media sosial Twitter yang cepat menyebar dari sebuah tagar #KomnasHAM dan KKB Papua yang menjadi buah bibir seluruh masyarakat Indonesia untuk memberikan opini publik atau kritik kepada pejabat tinggi yang ada di Komnas HAM.Penelitian ini bertujuan untuk menganalisis opini atau perilaku pengguna media sosial tersebut, apakah menjadi sebuah kritikan yang membangun pada permasalahan ini atau tidak, menganalisis perannya jaringan sosial, dan mengidentifikasi pengguna media sosial Twitter yang berpengaruh pada tagar #KomnasHAM dan KKB Papua. Metode penelitian yang dilakukan pada penelitian ini adalah Social Network Analysis (SNA). Hasilnya memperlihatkan bahwa entitas user yang memiliki sentimen netral menjadi entitas dengan jumlah terbanyak dibandingkan entitas dengan sentimen positif maupun negatif.
Inception-V3 Versus VGG-16: in Rice Classification Using Multilayer Perceptron
Authors: Firmansyah Ichsan , Rosnelly Rika , Wanayumini Wanayumini
Published: August 2023

Rice is an intriguing research topic, particularly in computer vision fields, because it is a staple food consumed in many parts of the world. Different rice varieties can be classified using the rice grain image based on their textures, sizes, and colors. To extract features from rice images, we used two popular pre trained convolutional neural network models, Inception V3 and VGG 16. The extracted features are then used as transfer learning in six variations of multilayer perceptron models, using rectified linear units as the activation function and adaptive moments as the loss function. The results show that the VGG 16 network performs better than the Inception V3, with 0.5% higher accuracy, precision, and recall value. Also, using the VGG 16 network produces a lower misclassification percentage, compared to the Inception V3 network, with a difference of 2.6%.
Transfer Learning for Feral Cat Classification Using Logistic Regression
Authors: Tambunan Fazli Nugraha , Rosnelly Rika , Situmorang Zakarias
Published: August 2023

Machine learning is an alternative tool for classifying animal species, especially feral cats. In this research, we use a machine learning algorithm to classify three species of feral cats: American Wildcat, Black-footed Cat, and European Wildcat. We also use a transfer learning model using the VGG-19 network for extracting the features in the feral cat images. By combining the VGG-19 and logistic regression algorithm, we build six models and compare which one is the best to solve the problem. We evaluate and analyze all models using a 5-fold, 10-fold, and 20- fold cross-validation, with accuracy, precision, and recall as the base performance value. The best result obtained is a model with a lasso regularization and cost parameter value of 1, with an accuracy value of 0.846667, a precision value of 0.845389, and a recall value of 0.846667. We also tune the C parameter in each LR model with values such as 0.1, 0.5, and 1. The most optimum C value for the lasso and ridge regularization is one, resulting in an average value of accuracy = 0.813, precision = 0.812, and recall = 0.813.
Combination of Pre-Trained CNN Model and Machine Learning Algorithm on Pekalongan Batik Motif Classification
Authors: Wahyuni Masri , Rosnelly Rika , Wanayumini Wanayumini
Published: August 2023

Pekalongan is a region in Indonesia well-known for its batik production. The Pekalongan batik is rich in varieties of motifs, such as the Jlamprang, Liong, Terang Bulan, and Tujuh Rupa. The difficulty of distinguishing Pekalongan batik motifs for ordinary people causes the need for a model that can help recognize these motifs automatically based on input from digital images. This research aims to classify the Pekalongan batik motifs using a pre-trained Convolutional Neural Network (CNN), the Inception V3, and machine learning, the K-Nearest Neighbors (K-NN) algorithm. First, we extract the features from the digital image using the Inception V3 model, resulting in m x 2048 features, where m is the number of images. The extracted features generated from the Inception V3 model will be used as the dataset for the motif classification. We build models to classify the features using the K-Nearest Neighbors (KNN) with a K value of 5. In the classification process, we employ two distance metrics, the Euclidean and Manhattan distance, and analyze their performance using the 10-fold and 20-fold cross validation. The results of this study are the highest overall performace of accuracy (0.987), precision (0.987), and recall (0.987) produced by the Euclidean model.
Classification of Basurek Batik Using Pre-Trained VGG-16 and Support Vector Machine
Authors: Handayani Meli , Rosnelly Rika , Hartono Hartono
Published: August 2023

By introducing Indonesian batik motifs, we know that the island of Sumatra, especially Bengkulu and Jambi provinces, has a distinctive batik called Basurek batik. This research aims to classify the two batik motifs using the Support Vector Machine (SVM) algorithm. First, we extract the image of the batik motif with a pre trained VGG-16 model and then use them as a dataset for the SVM classification process. The classification process itself uses linear, polynomial, and sigmoid kernels. We divided the data 90:10 and used 10-fold cross-validation to analyze each training and testing data classification result. The results of this study are the highest values of accuracy, precision, and recall of 76.4%, 76.5%, and 76.4% produced by the linear kernel for the training data classification. For the testing data classification, both the linear and polynomial kernels generate the best accuracy, precision, and recall values of 87.5%, 90%, and 85.5%. On average, incorporating the training and testing classification results, we found that the linear kernel is the best function for classifying the Basurek batik motif using the collected images from the internet.
Analysis of Machine Learning Algorithms in Predicting the Flood Status of Jakarta City
Authors: Daniel Irwan , Hartono Hartono , Situmorang Zakarias
Published: August 2023

By mining the information in the dataset, we can solve a prediction problem, especially flood status prediction based on floodgate levels, using machine learning algorithms. This research employs three machine learning algorithms (K-Nearest Neighbor, Naive Bayes, and Support Vector Machine) for predicting the flood status using a dataset containing the data of DKI Jakarta's floodgate levels. Using a 5-fold, 10-fold, and 20-fold cross-validation evaluation, we get the highest accuracy (85.096%), f-score (85.1%), precision (85.641%), and recall (85.096%) from the model using the SVM algorithm with a polynomial kernel. Average performance-wise, the K-NN algorithm performs better than the other algorithm with an average accuracy of 83.147%, an average f-score of 83.156%, an average precision of 83.566%, and an average recall of 83.147%.
Detection of Book and Borrower Communities Based on Book Borrowing Records in the Library Using Complex Network Analysis
Authors: Setiadi Tedy , Ratih Rina , Arkiyah Nanik , Prestisia Gretha
Published: August 2023

To improve user services, libraries need to have deep insight into users and the books they manage. This study aims toidentify the community of users and  borrowed books based on book borrowing records using complex network analysis. It starts with collecting book-borrowing data, then converting it into a bipartite book-borrowing network using python programming and visualizing it with Gephi. Network analysis is performed to investigate network properties, and to use the BIMLPA method to find communities. The results of the investigation show that the structure of the book borrowing network is divided into two separate components. One main component of the network represents the optimal process of borrowing books, and the rest consists of many small components representing suboptimal borrowing. Community detection on the main component found 217 borrowing communities and 141 book communities. Most of the communities are small, where the book community is 2-4 members, while the borrowing community is in the form of individual borrowers. This research also produces the top 5 book communities, and borrower communities, the most popular books, and the most active borrowers. The characteristics of the users and the books found can be used as a library reference for a more effective and efficient book development policy strategy, as well as book recommendations for more targeted users.
Predicting Non-Performing Loan's Risk Level Using K-Means Clustering and K-Nearest Neighbors
Authors: Siregar Muhammad Mizan , Roslina Roslina , Hayadi B Herawan
Published: August 2023

In data mining, clustering is an unsupervised learning technique often used to group data by similarity. Clustering, especially the K-means clustering algorithm, is a feasible tool for expanding a dataset label by increasing the cluster's number according to the label's categories. This research extends the credit loan label data set from two categories (non-performing and performing loans) to four risk levels (high risk, medium risk, low risk, and no risk). The combination of three K-nearest neighbor’s distance metrics, Euclidean, Manhattan, and Chebyshev distance, with four different K values (K = 3, K = 5, K = 7, and K = 9) produced the best model with accuracy, precision, and recall values of 90%, 90.53571%, and 90%, from the model using the Euclidean distance with K = 9.
Study of the level of adhesive activity of probiotic cultures at different storage periods
Authors: Guzhvynska S. О. , Paliy А. P. , Pavlichenko O. V.
Published: August 2023

The paper presents the results of studying the level of adhesive activity of probiotic cultures. It has been found that the studied cultures showed different ability to adhesion. The highest adhesion coefficient was found in the strains B. adolescentis 17 (64.2 ± 7.30%), B. adolescentis 23 (61.5 ± 3.27%), B. adolescentis 17-316 (60.1 ± 5,97%), and L. plantarum 7 (59.8 ± 5.01%). Studies have shown that after 3 years of storage, 4 strains (26.7%) turned out to be highly adhesive, and 2 strains (13.3%) — medium adhesive. When determining the adhesive properties of the studied microorganisms after 4 years of storage, it was found that 4 microorganisms (26.7%) were highly adhesive and 1 (6.7%) — medium adhesive
Feasibility and efficiency of probiotics, antibiotics and vaccines in associated bacterial infectious diseases in cattle
Authors: Hadzevych O. V. , Hadzevych D. V. , Stegniy B. T.
Published: August 2023

The article presents the results of determining the feasibility and efficiency of the vaccine for the prevention of associated diseases in a farm with a high level of animal morbidity and the circulation of multidrug-resistant pathogens. The incidence of pneumoenteritis in calves was 38.0%, the incidence of various forms of mastitis and endometritis in cows was 48.2% and 76.2%, respectively. The causative agents of escherichiosis (Escherichia coli), staphylococcosis (Staphylococcus aureus), anaerobic enterotoxemia (Clostridium perfringens), and a number of opportunistic pathogens that were involved in complicating the associated course of the disease, were isolated from sick animals. The isolated microflora was resistant to penicillin drugs, aminoglycosides, macrolides, amphenicols, lincosamides, cephalosporins and even to some fluoroquinolones. In addition, it was found that probiotic cultures of the genus Bacillus had more pronounced antagonistic activity against isolated pathogens, so it is advisable to use them in disease outbreaks to displace pathogenic microflora from the source of infection. In the prevention of the disease and for normalization of the microflora after the use of antibacterial drugs, it is advisable to use probiotics based on lactobacilli, as they have the highest adhesion (from 6.4 ± 0.6 to 8.9 ± 0.4). Vaccination has contributed to a decrease in animal morbidity. The incidence in vaccinated cows was lower than in the control group, in particular the incidence of mastitis was lower by 15–25%; manure retention — by 15–32.7%, endometritis — by 17–30%. Double vaccination of dry cows provides the formation of colostral immunity in calves and 20% decrease in the incidence of respiratory and gastrointestinal diseases in calves. In addition, vaccination of cows helped to improve the quality of milk by the degree of its contamination with bacterial microflora
Perception of Students and Faculty about Mounted Display of Dry Human Bones as Visual Educational Tool
Authors: Charania Jayaben , Lone Mangesh , Randhir Nisha , Shete Rohini , Khushale Kishor
Published: August 2023

This study aimed to assess the usefulness of mounted display boards of dry human bones as a self-directed learning tool for 1st year Bachelor of Medicine, Bachelor of Surgery (MBBS) students studying osteology. A prospective observational questionnaire-based study was conducted in a medical college attached to a tertiary care hospital in western Maharashtra. Feedback was obtained from 159 out of 200 participating students and was subjected for analysis. The results showed that the majority of students found the mounted display boards to be interesting (89%), beneficial for presentation skills (83%), improving thinking ability (82%), easing drawing tasks (62%), facilitating self-directed learning (79%), reducing mistakes during assessments (84%), enhancing subject understanding (91%), and promoting departmental involvement. The findings suggest that the development of department-specific display boards can enhance students' drawing skills, improve subject comprehension, thinking ability, and reduce errors made by students (75% students). Furthermore, the inclusion of charts with muscle attachments on the display boards was recommended by 94\% students for additional utility. Overall, these findings highlight the significance of incorporating mounted display boards into anatomy departments as a valuable educational resource.
Evaluating most relaxing Audio Accompaniment for Post-Workout Relaxation
Authors: Frolova Jekaterina , Pandya Chinmay
Published: August 2023

This research article aimed to evaluate the most relaxing audio accompaniment for post-workout relaxation. The study involved ten relaxation sessions with different musical accompaniments, and five participants rated their experiences on a relaxation scale, ranging from 1 (not at all relaxing) to 5 (completely relaxed and blissful). The sessions included nature sounds, musical instruments, vocalizations, and silence. The results showed varying responses among the participants (1.8 to 4.6 out of 5), indicating the influence of audio accompaniment on relaxation. The sounds of waterfall (3/5), beach campfire (2.8/5), the piano (3/5), vocalise (3.2/5) and the forest (3.2/5) were average and not fully relaxing, while singing bowls (4.2/5) and Koshi chimes (4.4/5) received highly positive responses. The harp received above average ratings (3.6/5), while silence presented challenges (2.8/5) for some participants; interestingly, session of silence had positive rating post 2 hours of the session. The wind session was the least relaxing (1.8/5), causing anxiety and discomfort. These ratings, collected immediately after the session, were similar to ratings collected after two hours of session confirming consistency of result and post impact. The study had recognized its limitation of the subjectivity of individual experiences and the impact of participants' initial states. Though other sounds suggested during the sessions also had a beneficial effect, the marked effects of wind chimes and singing bowls were highlighted in the study indicating its potential in relaxation. The research suggests incorporating these instruments into regular relaxation routines for enhanced well-being.