bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrating IoT and Machine Learning for Advanced Breast Cancer Detection: A Secure Framework for Enhanced Diagnostic Accuracy
Authors: Warish Patel
Published: November 2024

Background: Breast cancer continues to be a major global health issue, with outmoded analytic methods often limited in their capacity for early detection. The emergence of telehealth care emphasizes the need for advanced, advanced diagnostic explanations.
Objective: This study explores the possibility of integrating advanced technologies, such as thermal imaging cameras, with sophisticated ML algorithms, particularly CNNs, to enhance breast cancer discovery beyond the capabilities of conventional risk models.
Method: We propose a pioneering predictive healthcare system that harnesses the IoT and EHRs for real-time, automated breast cancer detection. This system is designed to operate in various healthcare environments, including hospitals, nursing homes, and schools. Beyond early breast cancer detection, it seeks to identify other health issues using the shared rule of DL and IoT techniques. To maintain data integrity and protect patient confidentiality, the system implements strong security protocols, including encrypted data transmission, secure access controls, and adherence to healthcare data protection regulations.
Results: The study explores the methodologies and technological frameworks necessary for developing this comprehensive cancer detection system. Emphasis is placed on secure data management practices and the implementation of security protocols to safeguard sensitive health information.
Main Findings: This research assesses whether the proposed system can effectively address global challenges related to breast cancer detection and contribute to enhanced patient outcomes. The integration of advanced security features aims to defend patient data and certify the system's reliability and trustworthiness in diverse healthcare settings.
Conclusion: This investigate evaluates capabilities of new health care system that combines smart technologies with ML methods to identify breast cancer and possibly other health problems at an early stage. Future investigate should focus on assessing the system’s practical feasibility and effectiveness in real-world scenarios, as well as its ability to uphold stringent security standards. This emphasizes its efficiency when operating on a lightweight and portable processor. Our experimental results indicate that our system achieves a 96.32% accuracy on the BreakHis database and can operate on a Raspberry Pi device with minimal resources.
Analysis of Physiological Signals to Detect the Symptoms of Paralysis Disorder using Neural Network Approach: a Cohort Study
Authors: Vijay Kumar
Published: November 2024

As per World Medical Associations, Paralysis attack is one of the leading causes of disorder in the human subjects after other chronic disorders such as Cancer and Heart Attack. Due to the attack of Paralysis, the body parts of human body become un responsive due to which the person may be physically disabled from hands or legs-based locomotion. There is scarcity in the methodologies who can early indicate the symptoms and alert the medical practitioners or human subject under surveillance. In this study, the health-related signals were studied and as per consultation of medical experts, total eight key parameters were identified and then based on that the output decision that weather person has symptoms of paralysis or not. The observatory data base has been prepared from more than 40,000 human subjects for the duration January 2018 to December 2023. As per categorical analysis based on training, validation and testing of three-layer Recurrent Neural Network, it has been observed that the ECG, Blood pressure, Heart Rate and PPG signals are key indicators to judge the susceptance of Paralysis disorder in the human subjects. Based on the evaluation parameters of machine learning models, the conjunction of response in association with selected input parameters gives 94% accuracy than other models. Our study helps research community to develop such methodologies by which the early indication of such disorders can be helpful to human health.
AI-Enhanced Predictive Analytics for Proactive Healthcare Management: Leveraging Machine Learning to Improve Patient Care and Operational Efficiency
Authors: Ratnaprabha Ravindra Borhade
Published: November 2024

As healthcare changes quickly, combining artificial intelligence (AI) and machine learning (ML) technologies has become a major force that can change things. This is because it improves predictive analytics for proactive healthcare management. This essay looks at how AI-powered predictive analytics might be able to help healthcare systems provide better care to patients and run more smoothly. Machine learning algorithms can find patterns and trends in huge amounts of patient data that traditional analysis methods might miss. This lets healthcare workers make smart decisions before big problems happen. The study looks into many uses of AI-enhanced prediction analytics, such as figuring out which patients are at the highest risk, finding diseases early, and making treatment plans work better. Using past patient data and real-time tracking, predictive models can figure out how likely it is that a person will develop a chronic condition. This lets doctors act quickly and make personalized care plans for each person. This cautious method not only improves the health of patients, but it also makes healthcare systems less busy by cutting down on hospital readmissions and trips to the emergency room. The paper also looks at how predictive analytics can help healthcare groups streamline their working processes. Healthcare facilities can better arrange staff and tools, making sure that resources are available where and when they are needed, by predicting how many patients will be admitted and how resources will be used. This speed makes patients happier, cuts down on wait times, and raises the standard of care generally. The study also looks at the problems that come with using AI and predictive analytics in healthcare, such as worries about data privacy, integrating new systems with old ones, and the need for strong algorithms that can handle a wide range of patients. It stresses how important it is for lawmakers, healthcare workers, and data scientists to work together to make ethical rules for the use of AI in healthcare situations.
Incentivized BiLSTM with Triplet Attention for Predecting Congestion in Network Traffic
Authors: Tejas Prashantrao Adhau
Published: November 2024

In the world of online live video streaming, network traffic congestion poses a serious risk to user experience and service quality. Several factors contributing to the congestion include insufficient bandwidth, an increase in user demand, as well as ineffective data routing. The incapacity of the prediction algorithms to Adjust to modifications in network circumstances and challenges in detecting long-range relationships may restrict their ability to effectively estimate congestion in dynamic contexts when it comes to online streaming video. In order to overcome these constraints, this study created an Incentivized-RF-Triplet ASTM (“Incentivized learning-based triplet attention enabled rat fierce hunting optimized Bidirectional Long Short-Term Memory) for network traffic congestion prediction in online streaming video. A reward” scheme built into the Incentivized learning mechanism pushes the algorithm to prioritize online live video streaming congestion prediction. The sequential structure of network traffic data is handled by the BiLSTM architecture, that is well-known for capturing temporal dependencies. By utilizing the triplet Attention method, the model is better able to identify relevant regions within the input data as well as identify congestion patterns more successfully. The RFSO method incorporates social behavior with selection and searching qualities to further improve the classifier's parameters. Therefore, the characteristics of the model can be tuned more effectively and robustly, improving its effectiveness in congestion detection. The outcomes of the experiment show how well the Incentivized-RF-Triplet ASTM technique works to precisely estimate traffic congestion for the Darpa99week1 dataset. 95.97% accuracy, 96.08% specificity, and 0.22 mean square error are reported.
Design and Implementation of Innovative Statistically Secured Hash Algorithm using Decentralized Hash Function
Authors: Bhagvant Ram Ambedkar
Published: November 2024

Information technology is in high demand today due to the expanding global use of the internet for information sharing. Every user wants to secure communication over a public network and to confirm the accuracy of their data. Hash algorithms are used to translate the fixed-length hash code from the input message, which is used to verify the integrity of the input message or any information exchanged through the web. Numerous hash algorithms are proposed by researchers but many algorithms use high consumption time during hash function processing time and they are using centralized hash function processing. Therefore we are designing an Innovative hash algorithm to generate a 96-bit hash code using a decentralized hash function.
Part-of-Speech (POS) Tagging of Low-Resource Language (Limbu) with Deep learning
Authors: Abigail Rai
Published: November 2024

POS tagging is a basic Natural Language Processing (NLP) task that tags the words in an input text according to its grammatical values. Although POS Tagging is a fundamental application for very resourced languages, such as Limbu, is still unknown due to only few tagged datasets and linguistic resources. This research project uses deep learning techniques, transfer learning, and the BiLSTM-CRF model to develop an accurate POS-tagging system for the Limbu language. Using annotated and unannotated language data, we progress in achieving a small yet informative dataset of Limbu text. Skilled multilingual tutoring was modified to enhance success on low-resource language tests.
The model as propose attains 90% accuracy, which is very much better than traditional rule-based and machine learning methods for Limbu POS tagging. The results indicate that deep learning methods can address linguistic issues facing low-resource languages even with limited data. In turn, this study provides a cornerstone for follow up NLP-based applications of Limbu and similar low-resource languages, demonstrating how deep learning can fill the gap where data is scarce.
Customer Churn Prediction Model Based on Adaptive Clustering Mixed-Sampling
Authors: MA Wen-bin
Published: November 2024

Predicting the probability of customer churn is an important reference for formulating and implementing customer retention strategies. Compared with single classification method, ensemble learning method can obtain better generalization ability and ensemble learning-based customer churn prediction method has gradually become a research focus. However, the prediction data of customer churn is usually imbalanced in class, and there are problems of overlapping and class-imbalance, so the prediction effect of ensemble learning model is ineffective. Therefore, an ensemble learning method based on adaptive clustering mixed-sampling (CUS-Ensemble) is proposed. This method is based on Bagging and regarded the gradient boosting decision tree as classifier, Firstly, cleanse the date of the whole training set, Secondly, the clustering under-sampling method is used to sample majority class instances, so that the sampled majority class instances are slightly more than the minority class instances, then, the sampled majority class instances and all minority class instances form a new training subset and provide a data cleansing again, next, using Borderline-SMOTE to balance the cleaned subset, and input it into the decision tree. Finally, the output of several gradient boosting decision trees is integrated as the final prediction result. Experimental results on six imbalanced customer datasets show that, compared with EasyEnsemble and other comparison methods, the AUC and Recall value of this method are increased by 4% and 13.6% on average, which is helpful to reduce the losses caused by customer churn.
Mathematical Techniques in the Design of Robust Control Systems
Authors: Jubber Salim Nadaf
Published: November 2024

Solid control frameworks are exceptionally imperative for making beyond any doubt that energetic frameworks remain steady and work well in a parcel of diverse circumstances and with a parcel of questions. This diagram tells you everything you wish to know about the numerical strategies utilized to form steady control systems. Strong control tries to bargain with issues like unknowns within the system model, stuns from the exterior, and changes within the system's parameters. It does this to form beyond any doubt that the framework keeps working well and remaining steady in spite of these issues. Lyapunov soundness hypothesis and the H-infinity (H∞) optimization strategy are two of the foremost critical arithmetic apparatuses. Lyapunov steadiness hypothesis gives us a way to see at how steady a framework is, and H∞ minimizes the worst-case pick up from unsettling influence to yield. State-space representations are moreover utilized to show and ponder multi-input multi-output (MIMO) frameworks, which makes control plan more organized. When making controls that guarantee steady execution, strategies like Direct Framework Disparities (LMIs) and Riccati conditions are utilized. The thought of unwavering quality limits is additionally displayed to degree how well the framework can handle factors. The solid control plan incorporates frequency-domain apparatuses, such as the Nyquist and Bode plots, to see at how the framework acts at distinctive frequencies. This makes it simpler to form controllers that can bargain with high-frequency occasions. We conversation around progressed strategies like α-synthesis and strong shaft situation that can offer assistance with certain control problems in dubious settings. Down to earth illustrations appear how these scientific strategies can be used, showing how vital they are in numerous building areas, such as the airplane, vehicle, and prepare control industries. The unique emphasizes how imperative these numerical strategies are for making beyond any doubt that solid control frameworks can handle the challenges of the genuine world, which improves system security, execution, and steadfastness in a wide run of circumstances. The abstract's objective with this outline is to provide you a basic idea of the math that's critical to the field of solid control framework plan.
Statistical Signal Processing for Radar Systems
Authors: Rajesh Kedarnath Navandar
Published: November 2024

Through measurable models, "Factual Flag Handling for Radar Frameworks" goes into detail around the progressed procedures and strategies utilized to see at and progress radar information. This field employments thoughts from both measurable hypothesis and flag preparing to unravel difficult issues in radar framework execution, like finding targets, taking after them, and speculating what they are. This article talks approximately distinctive factual models and strategies that can be utilized with radar. These incorporate Bayesian gauges, versatile sifting, and theory testing. This paper talks around how factual apparatuses can be utilized to create radar frameworks more precise, dependable, and clear by mimicking and decreasing the impacts of commotion, impedances, and outside components. Creating factual flag preparing methods for lessening disarray, distinguishing targets, and estimating parameters are a few of the foremost critical subjects. Other imperative points incorporate ways to analyze and get it radar information in genuine time. It gives a careful see at both the hypothetical bases and real-world applications, appearing how measurable strategies can be utilized to make strides radar framework capabilities. There are case thinks about and real-life examples that appear how these strategies can be utilized totally different radar circumstances, such as military, flying machine, car, and climate radars. This book gives engineers and understudies the instruments they got to move forward radar framework plan and execution in settings that are getting more complicated and changing rapidly by combining factual flag preparing with radar innovation.
AI-Based Phishing Detection and Automated Response: A Multi-Channel Security Framework for Modern Communication Platforms
Authors: Sarika Nitin Zaware
Published: November 2024

Phishing attacks have evolved in sophistication over the changing digital communication landscape, taking advantage of several channels like social media, SMS, and email to trick people and businesses. This research offers a multi-channel security architecture for automated phishing response and detection that uses cutting-edge artificial intelligence (AI) technology to counteract this ubiquitous threat. The system utilizes automatic reaction mechanisms to mitigate threats in real time and incorporates state-of-the-art AI algorithms to improve the detection of phishing attempts across various communication channels. This study examines recent developments in artificial intelligence (AI) for cybersecurity, emphasizing the use of deep learning, machine learning, and natural language processing in phishing detection and response. It also looks at how phishing techniques have changed over time, how difficult it is to integrate AI across different platforms, and how dangerous it could be for AI systems to come under hostile attack. The report shows the usefulness and practical use of AI-driven solutions with case studies from social media, financial services, and enterprise communication platforms. It also discusses ethical and regulatory issues, highlighting the necessity of adhering to data protection regulations and using AI responsibly. The technological difficulties, potential avenues for future investigation, and prospects for innovation in AI-based phishing detection are covered in the paper's conclusion. With this methodology, cybersecurity researchers and practitioners can benefit from a thorough approach to improving cybersecurity with artificial intelligence.
Circular Shaped Ultrawide-Band Antenna for Wireless Communication
Authors: Abhishek Tiwari
Published: November 2024

This paper presents the design of (UWB) antenna with asymmetrical U-Slot, operating in the microwave band of (3.5-15) GHz. This design permits its applications in various sectors, such as wireless communications, radar systems, and remote sensing. The antenna is covering bandwidth of (11.5) GHz with gain of (6.298) dB at (14.25) GHz. The substrate used is (FR4 Epoxy) of (????????=4.4), loss tangent of (0.02), and thickness of (1.575) mm. The extensive bandwidth of the antenna makes it operate in both the C-Band and X-Band. Overall, the design of this (UWB) antenna aims to provide a high-performance antenna that can operate over a wide frequency range, making it suitable for various applications.
Đặc điểm lâm sàng, cận lâm sàng và mối liên quan với nồng độ EBV-DNA huyết thanh ở bệnh nhân ung thư vòm mũi họng giai đoạn III - IVA tại Bệnh viện K
Authors: Đăng Nguyễn Văn , Thắng Phạm Văn
Published: November 2024

Ung thư vòm mũi họng là bệnh ung thư thường gặp vùng đầu cổ. Bệnh có yếu tố địa lý rất rõ rệt và liên quan chặt chẽ với virus Epstein Barr. Nghiên cứu cắt ngang trên 118 người bệnh ung thư vòm mũi họng giai đoạn III - IVA từ tháng 06/2023 đến tháng 06/2024 tại Bệnh viện K nhằm mô tả một số đặc điểm lâm sàng, cận lâm sàng và mối liên quan nồng độ EBV-DNA huyết thanh. Xuất hiện hạch cổ là triệu chứng hay gặp nhất, chiếm 61,8%. Trên cộng hưởng từ, xâm lấn nền sọ, cột sống cổ, khoang cạnh mũi chiếm tỉ lệ cao nhất với 59,3%. Khối u T3 hay gặp nhất với 34,7%; di căn hạch N2 hay gặp nhất với 56,8%. Tỉ lệ giai đoạn III, IVA lần lượt là 57,6% và 42,4%. Có 91% bệnh nhân định lượng EBV-DNA huyết thanh dương tính. Nồng độ EBV-DNA ở nhóm bệnh nhân giai đoạn IVA cao hơn giai đoạn III, trong đó liên quan có ý nghĩa với mức độ di căn hạch N (p < 0,05).
Khảo sát tỉ lệ và đặc điểm lâm sàng rối loạn giấc ngủ ở bệnh nhân bệnh thận mạn lọc máu chu kỳ
Authors: Ninh Đinh Vũ Ngọc , Trung Nguyễn Xuân , Bảo Hoàng Bùi , Hằng Trần Như Minh , Khang Đặng Trần , Đại Ngọ Đình , Nga Dương Thanh , Hằng Nguyễn Thị Thu
Published: November 2024

Nghiên cứu mô tả cắt ngang trên 216 bệnh nhân bệnh thận mạn lọc máu chu kỳ điều trị tại Bệnh viện Quân Y 175 – Thành phố Hồ Chí Minh, từ tháng 09/2023 đến tháng 06/2024. Chúng tôi tiến hành nghiên cứu với mục tiêu: “Khảo sát tỉ lệ và đặc điểm lâm sàng rối loạn giấc ngủ ở bệnh nhân bệnh thận mạn lọc máu chu kỳ.” Kết quả cho thấy tỷ lệ nam giới là 54,6%. Độ tuổi trung bình của nhóm đối tượng là 56,7 ± 14,5. Tỷ lệ mất ngủ là 48,1%; ngủ nhiều gặp 5,1%; chân cử động không yên có 4,6%; ác mộng có 3,2%; ngưng thở khi ngủ, nói trong khi ngủ, nghiến răng chiếm 2,3% và các rối loạn khác chiếm dưới 2%. Thời gian ngủ trung bình hàng ngày là 6,07 ± 2,00 giờ; số ngày trong tuần bị rối loạn giấc ngủ có trung vị là 2,8 ngày; thời gian bị rối loạn giấc ngủ có trung vị là 23,7 tuần. Kết luận cho thấy rối loạn giấc ngủ là rối loạn tâm thần phổ biến của bệnh thận mạn lọc máu chu kỳ với rối loạn mất ngủ chiếm tỷ lệ cao nhất. Rối loạn giấc ngủ nhóm bệnh nhân này có đặc điểm chất lượng giấc ngủ kém, mức độ mất ngủ vừa đến nặng, thời gian ngủ ngắn, số lần thức giấc trong đêm nhiều, thức giấc buổi sáng sớm hơn, vào giấc ngủ lâu hơn.
Nghiên cứu tác dụng giảm ho và long đờm của cao lỏng thuốc ho bổ phổi Abipha trên thực nghiệm
Authors: Anh Phạm Thị Vân , Huệ Lê Kim , Thảo Bùi Thị Hương , Hằng Đinh Thị Thu
Published: November 2024

Nghiên cứu được tiến hành nhằm đánh giá tác dụng giảm ho, long đờm của Thuốc ho bổ phổi Abipha trên thực nghiệm. Tác dụng giảm ho của Thuốc ho bổ phổi Abipha được đánh giá trên mô hình gây ho bằng amoniac trên chuột nhắt trắng chủng Swiss. Tác dụng long đờm của Thuốc ho bổ phổi Abipha được đánh giá dựa trên nồng độ phenol đỏ của dịch rửa khí quản chuột nhắt trắng chủng Swiss. Kết quả nghiên cứu cho thấy Thuốc ho bổ phổi Abipha cả 2 liều 9 mL/kg và 18 mL/kg có tác dụng làm giảm số cơn ho, khả năng ức chế cơn ho rõ rệt và kéo dài thời gian tiềm tàng xuất hiện cơn ho. Về tác dụng long đờm, Thuốc ho bổ phổi Abipha cả 2 mức liều 9 mL/kg/ngày và 18 mL/kg/ngày làm tăng nồng độ phenol đỏ tiết ra ở khí quản có ý nghĩa thống kê so với lô đối chứng. Như vậy, Thuốc ho bổ phổi Abipha là thuốc thử nguồn gốc từ dược liệu thể hiện tác dụng giảm ho, long đờm rõ rệt trên thực nghiệm.
Tác dụng điều trị của điện phúc châm kết hợp siêu âm trị liệu trên bệnh nhân đau thần kinh hông to
Authors: Trang Trần Thị Thu , Hà Nguyễn Thị Thu , Hùng Trần Quốc
Published: November 2024

Nghiên cứu nhằm đánh giá tác dụng giảm đau, mức độ cải thiện tầm vận động cột sống thắt lưng và chức năng sinh hoạt hàng ngày của phương pháp điện phúc châm kết hợp siêu âm trị liệu trên bệnh nhân đau thần kinh hông to. Nghiên cứu can thiệp lâm sàng, so sánh trước sau và có đối chứng. 80 bệnh nhân đau thần kinh hông to có điểm VAS từ 3 đến 6 điểm được chia thành hai nhóm. Nhóm nghiên cứu được điều trị bằng điện phúc châm kết hợp siêu âm trị liệu. Nhóm đối chứng được điều trị bằng thể châm kết hợp siêu âm trị liệu. Kết quả cho thấy sau 20 ngày điều trị, nhóm được điều trị bằng điện phúc châm kết hợp siêu âm trị liệu cải thiện mức độ đau qua thang điểm VAS (p < 0,01), tầm vận động cột sống thắt lưng (p < 0,05) và chức năng sinh hoạt hàng ngày qua bộ câu hỏi ODI (p < 0,01). Sự khác biệt không có ý nghĩa thống kê so với nhóm được điều trị bằng thể châm kết hợp siêu âm trị liệu (p > 0,05).
Union Responses to Workplace COVID-19 Vaccine Mandates in Canada
Authors: Braley-Rattai Alison , Savage Larry
Published: November 2024

This article explores union responses to workplace-based covid-19 vaccine mandates in Canada. Specifically, the authors examine the complex interplay of factors that drove unions to adopt their respective positions on vaccine mandates and to frame those positions in particular ways for the benefit of their members and the wider public. Interviews with key informants, along with analysis of documents and arbitration decisions, reveal a disjuncture between the discursive quality of certain unions’ positions and their actual positions. In particular, media framing of unions as either “for” or “against” vaccine mandates oversimplified or misrepresented the actual positions adopted. In response, the article introduces a typology of union positions that distinguishes between support for mandatory-vaccination policies and support for voluntary-vaccination policies and reveals that the vast majority of unions favoured the latter. The authors further reveal that workplace vaccine mandates were both internally divisive and disorienting for unions, given the central role labour organizations play in managing workplace disputes and representing the interests of workers, both individually and collectively.
Program P5 Kurikulum Merdeka: Mengasah Kreativitas dan Keterampilan Siswa melalui Kegiatan Memasak dan Menyulam
Authors: Zebua Martina , Gulo Margareta , Lubis Giovani Br , Tarigan Noveria Br , Simanungkalit Tuti Vina Winata Br , Situngkir Friska Ledina
Published: November 2024

Program P5 (Proyek Penguatan Profil Pelajar Pancasila) Kurikulum Merdeka bertujuan untuk mengembangkan kreativitas dan keterampilan siswa melalui pendekatan pembelajaran berbasis proyek. Salah satu kegiatan yang dilaksanakan di SMP Budi Murni 2 Medan adalah projek memasak dan menyulam. Kegiatan ini tidak hanya berfokus pada keterampilan teknis, tetapi juga mengajarkan nilai-nilai kewirausahaan sosial kepada seluruh  siswa kelas IX  yang berjumlah  sekitar 210 siswa. Dalam proses ini, siswa diajarkan cara mengolah bahan makanan menjadi produk siap jual serta menciptakan produk kerajinan tangan melalui menyulam yang bernilai ekonomi. Melalui kolaborasi tim, siswa belajar bekerja sama, berpikir kreatif, dan mengembangkan kemampuan manajerial sederhana. Projek ini bertujuan untuk mempersiapkan siswa agar lebih mandiri, inovatif, dan siap menghadapi tantangan dunia kerja di masa depan. Hasil dari kegiatan ini menunjukkan peningkatan signifikan pada kemampuan kreativitas dan keterampilan siswa, serta munculnya minat mereka dalam bidang kewirausahaan. Dengan adanya program ini, diharapkan siswa dapat mengaplikasikan keterampilan yang diperoleh tidak hanya dalam lingkungan sekolah, tetapi juga di masyarakat. Program ini menjadi contoh sukses dalam penerapan Kurikulum Merdeka yang mendukung pengembangan potensi siswa secara menyeluruh.
Volunteer Accuracy in a Benthic Macroinvertebrate Participatory Science Project
Authors: Hamilton Virginia , Stepenuck Kristine F. , Zinna II Robert A. , Traylor Ann Marie , Penrose David , Sigler W. Adam
Published: November 2024

Concerns about the accuracy of volunteer-derived aquatic macroinvertebrate identifications and the resulting influence on calculated water quality metrics can limit use of volunteer-generated data in freshwater-focused participatory science programs. To address these concerns, we assessed 357 benthic macroinvertebrate quality control (QC) samples collected by volunteers using leaf packs, kick nets, and visual assessments between 2011 and 2016 for the Environmental Quality Institute (EQI) in North Carolina, USA. We reviewed each sample for quality, and compared macroinvertebrate identifications and water quality metric scores determined by volunteers to identification and metrics determined by an entomologist. About 80% of the QC samples were identified to be of high quality, indicating proper preparation, preservation, and labeling of samples. The majority of samples that received low quality ratings were improperly or poorly preserved. We recommend use of 95% (rather than 70%) ethanol for macroinvertebrate preservation, and increased communication to volunteers during QC sampling periods to enhance their success in properly preserving samples. We observed significant (p < 0.005) linear relationships between volunteer and entomologist-derived water quality metrics including a biotic index, Taxa Richness, and percent intolerant Ephemeroptera, Plecoptera and Trichoptera (EPT) taxa. However, visual assessments – those in which no sampling equipment was used to collect aquatic macroinvertebrates – reduced the goodness of fit between volunteer and entomologist-derived biotic index scores and artificially increased the goodness of fit between volunteer and entomologist derived Taxa Richness and percent EPT scores. We recommend calculating water quality metrics based only on leaf pack and kick net samples collected by volunteers.
IMPORTANCE OF EXCITOTOXICITY IN STRESS: A MINI REVIEW
Authors: Majumder Dr. Titlee , Alam Lasker Khurshid , Ghosh Dr. Subrata
Published: November 2024

Excitotoxicity refers to the process where nerve cells are damaged or killed due to excessive stimulation by neurotransmitters, primarily glutamate. This overactivation of receptors, such as NMDA (N-methyl-D-aspartate) receptors, causes an influx of calcium ions into the neurons, leading to cell damage or death. It is a key factor in various neurodegenerative diseases and acute neurological conditions like stroke and traumatic brain injury. Many researchers suggested that chronic stress can exacerbate excitotoxicity by increasing the release of glutamate in the brain. There are numerous factors play extremely important roles in many endorsing the excitotoxicity are increased glutamate levels, vulnerability of the neurones and neuro-degeneration in the diseases like Parkinsons. Several protective measures are obtained by the review of many researches. Effective stress management, including mindfulness, exercise, and therapy, can help regulate glutamate levels and reduce the risk of excitotoxicity.Enhancing antioxidant defences through diet or supplementation may protect neurons from the oxidative stress induced by excitotoxicity.Drugs that block NMDA receptors or regulate glutamate activity are being explored as treatments for conditions associated with excitotoxicity.
Big Data Analytics in Telecom Operations: Exploring the application of big data analytics to optimize network management and operational efficiency in telecom, reflecting your experience with analytics-driven decision-making in telecom environments.
Authors: KUMAR MANDA JEEVAN
Published: November 2024

In today's rapidly evolving telecommunications industry, the vast amounts of data generated every second hold immense potential to transform network management and operational efficiency. This abstract delves into the application of big data analytics in telecom operations, highlighting how advanced data techniques can optimize network performance and streamline operations. Imagine a bustling telecom network, where data from millions of calls, messages, and internet sessions flow continuously. Analyzing this data can reveal patterns and insights that were previously hidden. By leveraging big data analytics, telecom operators can predict network congestions before they happen, enhance service quality, and reduce downtime. This not only improves customer satisfaction but also drives cost efficiency. From my experience in analytics-driven decision-making within telecom environments, the benefits are tangible. For instance, real-time data analysis can help in quickly identifying and rectifying network issues, ensuring minimal disruption. Predictive analytics can forecast demand spikes, allowing for proactive adjustments in network capacity. Additionally, big data helps in personalizing customer experiences by understanding user behavior and preferences, leading to targeted marketing strategies and improved customer retention. Moreover, the integration of big data analytics in telecom operations facilitates better resource allocation. By understanding usage patterns and trends, telecom companies can optimize their infrastructure investments, ensuring that resources are deployed where they are needed most. This not only enhances operational efficiency but also supports sustainable growth.
РОЛЬ ИПОТЕЧНОГО КРЕДИТОВАНИЯ В ФОРМИРОВАНИИ СОЦИАЛЬНО-ЭКОНОМИЧЕСКОГО БЛАГОПОЛУЧИЯ НАСЕЛЕНИЯ РЕСПУБЛИКИ АДЫГЕЯ
Authors: И.Г. ТХАРКАХОВА , Р.А. ТХАГАПСО
Published: November 2024

Экономика народного хозяйства направлена на развитие не только промышленности, сельского хозяйства и прочего, но и на повышение уровня благосостояния населения страны. С позиции экономики управление данным процессом довольно сложно и трудоемко. Это связано прежде сего с тем, что уровень жизни населения — многогранный показатель, который формируется под влиянием разнообразных факторов. Основными из них являются экономические, социальные, политические и прочие. В данной работе рассмотрено ипотечное кредитование в Республике Адыгея и то, каким образом оно оказывает влияние на уровень жизни. Этот вид финансирования обеспечивает гражданам возможность покупки жилья путём поэтапной оплаты его стоимости в течение фиксированного периода времени. В рамках данного исследования были раскрыты сущность, виды и принципы ипотечного кредитования, а также проанализированы объёмы выданных ипотечных кредитов с 2016 г. по 2023 г., что позволяет сделать вывод о динамике изменения спроса на жилищные кредиты в данном регионе. Изучение экономических взаимосвязей и тенденций в данной области поможет более точно дать ответ о взаимосвязи ипотечного кредитования и уровня жизни населения региона, а также позволит выработать более результативные механизмы управления данным финансовым инструментом.

The national economy is aimed at developing not only industry, agriculture, etc., but also at raising the level of well-being of the country's population. From an economic point of view, managing this process is quite complex and labor-intensive. This is primarily due to the fact that the standard of living of the population is a multifaceted indicator that is formed under the influence of various factors. The main ones are economic, social, political and others. This paper examines mortgage lending in the Republic of Adygea and its impact on the standard of living. This type of financing provides citizens with the opportunity to purchase housing, paying its cost in stages over a fixed period of time. This study reveals the essence, types and principles of mortgage lending, analyzes the volumes of issued mortgage loans from 2016 to 2023, which allows us to draw a conclusion about the dynamics of changes in demand for housing loans in this region. The study of economic relationships and trends in this area will help to more accurately answer the question of the relationship between mortgage lending and the standard of living of the region's population, and will also allow us to develop more effective mechanisms for managing this financial instrument.
BONUS DEMOGRAFI: PERAN LINGKUNGAN KELUARGA UNTUK PENGOPTIMALAN JUMLAH WIRAUSAHAWAN DI MASA DEPAN
Authors: Muhammad Tafdhil Amanda  , Myrtana Pusparisti  , Yohanes Wien Tineka  , Deswita Auraliyani Fatolah Putri
Published: November 2024

This study is motivated by the demographic bonus phenomenon both in terms of benefits and threats in the future. Increasing the number of entrepreneurs in the future is one way to take advantage of the demographic bonus because at least it will open up many opportunities to become a producing country and reduce unemployment. Focusing on entrepreneurial intentions, this research examines one of the factors that can influence it from an early age, namely the family environment. Quantitative sampling methods were used with students majoring in business, and provided assumptions of validity and reliability. The research results show that there is a significant positive impact between the family environment and entrepreneurial intentions, which also implies that to take advantage of the demographic boom phenomenon by creating many entrepreneurs in the future, encouragement and education can be targeted at the family environment from an early age
Sosialisasi PPh 21 Menggunakan TER pada Guru Produktif SMK di Denpasar, Gianyar, Badung, dan Tabanan
Authors: Mariani Wayan Eny , Pramitari I Gusti Ayu Astri , Lasmini Ni Nengah , Sumiari Kadek Nita , Utami Ni Made Mega Abdi
Published: November 2024

Pajak merupakan salah satu sumber pendapatan bagi suatu negara, termasuk Indonesia. Pada praktiknya perpajakan di Indonesia telah mengalami perkembangan secara terus-menerus. Salah satu perkembangan yang terbaru dari peraturan perpajakan adalah Peraturan Pemerintah Nomor 58 Tahun 2023 tentang Tarif Pemotongan PPh 21 Menggunakan Tarif Efektif (TER). Pengetahuan pajak adalah faktor yang melatarbelakangi tingkat kepatuhan wajib pajak dalam memenuhi kewajiban perpajakan. Guru merupakan bagian dari wajib pajak di Indonesia. Profesi sebagai guru khususnya di bidang akuntansi sangat erat kaitannya dengan adanya perubahan peraturan di bidang perpajakan. Kegiatan pengabdian ini bertujuan untuk memberikan kesempatan bagi para guru akuntansi SMK di Denpasar, Gianyar, Badung, dan Tabanan untuk memperluas pemahaman mengenai peraturan terbaru terkait PPh Pasal 21 yang telah berlaku. Kegiatan pengabdian ini dilakukan dengan berkolaborasi dengan Majelis Guru Mata Pelajaran (MGMP) Akuntansi Provinsi Bali serta melibatkan Dunia Usaha dan Dunia Industri (DUDI) dalam hal ini adalah kantor konsultan pajak. Para peserta yang merupakan guru produktif SMK sangat puas dan merasakan manfaat atas pemaparan materi mengenai PPh Pasal 21 menggunakan TER yang masih kategori regulasi baru. Wawasan ini dapat mereka gunakan sebagai tambahan pengetahuan untuk diajarkan kepada siswa di sekolahnya masing-masing.
Memperkuat Literasi Teknologi melalui Pembelajaran Interaktif dengan Menggunakan Media Kahoot di Kelas V Sekolah Dasar
Authors: Rukmana Rukmana , Wakhyudin Husni , Nuruliarsih Nuruliarsih , Azizah Mira
Published: November 2024

Dalam dunia pendidikan, teknologi dapat digunakan untuk meningkatkan pengetahuan teknologi siswa. Media pembelajaran interaktif seperti Kahoot telah terbukti efektif dalam meningkatkan keterlibatan siswa dan membuat proses belajar lebih menyenangkan dan bermakna. Penelitian ini dilaksanakan di SD N Sambirejo 02 pada kelas V, pada saat mata pelajaran IPAS. Penelitian ini menggunakan metode kualitatif yang menggunakan data deskriptif, yang berarti informasi dikumpulkan melalui kata-kata. Hasil tes evaluasi ini mendukung hipotesis bahwa siswa sekolah dasar dapat secara signifikan lebih memahami teknologi melalui pembelajaran interaktif dengan media Kahoot. Penggunaan teknologi dalam pembelajaran tidak hanya meningkatkan motivasi dan keterlibatan siswa, tetapi juga secara signifikan meningkatkan hasil akademik mereka.
Pelatihan Peningkatan Kemampuan Evaluasi Pembelajaran Melalui Pendekatan Tehnology Enhanced Language Learning (TELL) Bagi Guru-Guru Madrasah Aliyah Muhammadiyah Balassuka
Authors: Rahman Abd. , Fatmawati Fatmawati , Hasmin Hasmin
Published: November 2024

Pelatihan peningkatan kemampuan evaluasi pembelajaran melalui pendekatan Technology Enhanced Language Learning (TELL) dilaksanakan di Madrasah Aliyah Muhammadiyah Balassuka. Pelatihan ini bertujuan untuk meningkatkan kemampuan guru dalam melakukan evaluasi menggunakan berbagai aplikasi sehingga proses evaluasi pembelajaran yang dilakukan oleh guru semakin objektif dan menyenangkan. Pengabdian dilakukan melalui metode pelatihan, peserta menerima pemahaman terkait pendekatan TELL kemudian melakukan praktik pengelolaan materi evaluasi sesuai mata pelajaran masing-masing. Hasil dari pengabdian ini menunjukkan bahwa penggunaan pendekatan Technology Enhanced Language Learning (TELL) dalam evaluasi pembelajaran merupakan hal yang baru didapatkan oleh guru-guru sehingga memberikan motivasi dalam melakukan pengelolaan pembelajaran khususnya evaluasi pembelajaran.
Optimalisasi Pemanfaatan Lahan Pekarangan Melalui Pelatihan Teknologi Akuaponik Pada Kelompok Ibu Rumah Tangga di Kampung Nelayan Untia Makassar
Authors: Mandra Mohammad Ahsan S. , Ali A. M. Taufik , Yusuf A. Zulfikar , Mario M.
Published: November 2024

Pekarangan merupakan area di sekitar rumah yang kadangkala kurang termanfaatkan untuk menunjang  perekonomian keluarga. Salah satu pemberdayaan masyarakat untuk optimalisasi lahan pekarangan dengan menciptakan usaha budidaya skala rumah tangga melalui teknologi akuaponik. Akuaponik adalah teknologi gabungan sistem akuakultur dan hidroponik melalui kombinasi tanaman dan budidaya ikan yang saling menguntungkan. Program pengabdian kepada masyarakat ini terdiri dari 4 (empat) tahapan utama yaitu: (1) sosialisasi dan pelatihan pembuatan sistem akuaponik; (2) pelatihan penyemaian bibit tanaman; (3)  pelatihan pemanfaatan dan perawatan instalasi akuaponik, dan (4) evaluasi pelaksanaan kegiatan. Hasil pelatihan menunjukkan aspek penguasaan pengetahuan sebesar 82% dan keterampilan sebesar 70% pada peserta. Hal ini menunjukkan adanya potensi minat dari masyarakat untuk mengelola teknologi akuaponik pada lahan pekarangan mereka. Adapun kendala yang dihadapi masyarakat yaitu modal yang butuhkan untuk membuat instalasi akuaponik, dan pendampingan masyarakat terkait penerapan teknologi akuaponik secara berkelanjutan.
Pelatihan Membuat Poster dengan Menggunakan Aplikasi Canva pada Santri MA Pondok Pesantren Al-Miftah Mlangi
Authors: Khusna Ala Asmaul , Astuti Annida Rizki Luthfi , Rifai Aulia Faqih , Wonoseto Muhammad Galih
Published: November 2024

Pondok pesantren adalah lembaga pendidikan non formal Islam yang memberikan pendidikan, pengajaran, dan mengembangkan serta menyebarkan agama Islam. Kemajuan teknologi yang sangat pesat menjadikan  pesantren untuk mengikuti perkembangannya. Salah satunya dengan adanya kegiatan pelatihan membuat poster dengan menggunakan aplikasi canva. Pelatihan ini bertujuan membantu meningkatkan keterampilan literasi digital kepada santri. Metode pelaksanaan dilakukan dengan tahapan alur, yaitu pra kegiatan, sosialisasi, pelatihan, pendampingan, dan evaluasi. Pelatihan desain grafis dengan menggunakan Canva ini dapat menambah wawasan kepada para santri di PP Al-Miftah Mlangi. Literasi digital dalam penggunaan teknologi khususnya terkait pada desain grafis dapat membuka insight para santri bahwa penggunaan teknologi itu sangat penting, terutama untuk kemajuan pondok pesantren.
Peningkatan Efektivitas Project-Based Learning Melalui Integrasi Kecerdasan Buatan
Authors: Baskara FX. Risang , Winarti Eny , Prasetya Andreas Erwin
Published: November 2024

Perkembangan pesat teknologi kecerdasan buatan (AI) membuka peluang sekaligus tantangan baru dalam implementasi Project-Based Learning (PjBL). Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan efektivitas PjBL melalui integrasi AI, fokus pada pengembangan kompetensi guru. Menggunakan pendekatan mixed-method, studi ini melibatkan survei pra-pelatihan dan program pelatihan intensif tiga hari untuk 95 guru dari SMP/SMA Regina Pacis Surakarta dan SMP Maria Assumpta Klaten. Materi mencakup eksplorasi Generative AI Tools, aplikasi interaktif, dan integrasi AI dalam PjBL. Hasil survei pra-pelatihan menunjukkan penggunaan teknologi dasar tinggi (rata-rata 4.59/5 untuk komputer/laptop) namun minat moderat terhadap AI (rata-rata 46/100). Analisis ANOVA mengungkap perbedaan signifikan penggunaan teknologi berdasarkan usia, guru muda menunjukkan adopsi lebih tinggi. Selama pelatihan, peserta mendemonstrasikan peningkatan pemahaman dan keterampilan mengintegrasikan AI dan teknologi interaktif ke PjBL, meski tantangan seperti kesenjangan literasi digital dan kekhawatiran etis tetap ada. Peserta berhasil mengembangkan proyek pembelajaran terintegrasi AI inovatif, namun pemahaman mendalam prinsip-prinsip PjBL masih perlu ditingkatkan. Temuan menegaskan efektivitas program dalam menjembatani kesenjangan antara potensi AI dan implementasinya dalam PjBL, sekaligus mengidentifikasi kebutuhan pengembangan profesional berkelanjutan. Implikasi mencakup perlunya dukungan berkelanjutan bagi guru, pengembangan kerangka kerja etis penggunaan AI dalam pendidikan, dan kolaborasi multi-stakeholder untuk implementasi AI dalam PjBL yang efektif dan bertanggung jawab.
Pelatihan E-Filing, Digital Marketing, dan Content Planner pada Desa Mengwitani, Kab. Badung
Authors: Yasa Gede Sedana Wibawa , Widiantara I Made , Sintadevi Ni Putu Rita , Astariani Putu Sandra Putri
Published: November 2024

Desa Mengwitani merupakan salah satu desa di Kabupaten Badung yang memiliki luas wilayah sebesar 4.39 km2. Secara administratif Desa Mengwitani terdiri dari 2 Desa Adat, 19 Banjar Adat dan 13 Banjar Dinas Struktur Perekonomian Desa Mengwitani bertumpu pada sektor pertanian, yang mana sebagian besar penduduk Desa Mengwitani menggantungkan hidupnya dari pertanian, Desa Mengwitani mempunyai kendala dalam pengarsipan terhadap arsip masyarakat, selain itu UMKM sekitar desa juga belum memaksimalkan pemasaran produk yang menyebabkan kurangnya serapan dari produk yang dihasilkan, dilain pihak anak muda di desa ingin menjadi content creator namun tidak memiliki informasi dari mana untuk memulainya. Kegiatan pengabdan ini dilakukan dalam bentuk pelatihan E-Filling, Digital Marketing serta Content Planner yang diharapkan dapat memberi solusi atas masalah yang terjadi di Desa Mengwitani. Kegiatan pelatihan ini diikuti oleh 45 orang peserta yang terdiri dari UMKM dan Perangkat Desa, hasil dari kegiatan pelatihan ini berupa struktur pengarsipan berbasis cloud, konten digital untuk sosmed yang sudah di praktikkan oleh UMKM desa. Keterlibatan masyarakat setempat di kegitatan ini sangat baik, hal ini terbukti dari antusiasme peserta yang mengikuti pelatihan, ke depannya diharapkan kegiatan ini akan memberi dampak untuk mendorong perkembangan ekonomi desa melalui adopsi teknologi dan strategi pemasaran modern selain itu besar harapan kami kegiatan ini juga akan meberi dampak terhadap pembangunan desa dalam mempersiapkan masyarakat untuk menghadapi era digital dan daya saing usahal lokal.
Menggali Potensi Kreatif Mahasiswa Melalui Kompetisi Esai dan Poster Nasional
Authors: Yusuf Arya , Wulida Siti Nursipa
Published: November 2024

Pemuda sebagai garda terdepan bagi kemajuan bangsa berperan strategis dalam pengembangan ilmu pengetahuan dan teknologi (IPTEK) dalam mewujudkan fungsi agent of change salah satunya melalui kegiatan kompetisi bidang menulis esai dan poster. Tujuan utama pengabdian kepada masyarakat ini untuk membentuk semangat pemuda sebagai agent of change dalam kemajuan bangsa untuk keberlanjutan. Kegiatan pengabdian ini bertempat di Gedung Aula E Fakultas Kesehatan, Universitas Dhyana Putra, Bali. Kegiatan ini dilaksanakan pada 18-19 Mei 2024 dengan jumlah peserta sebanyak 200 tim dari 28 beberapa perguruan tinggi di Indonesia. Adapun kegiatan kompetisi yang dilaksanakan merupakan presentasi gagasan dan ide esai maupun poster yang telah dibuat. Metode pendekatan yang digunakan untuk pengabdian ini terdiri dari tiga tahap yakni persiapan, pelaksanaan dan evaluasi. Kategori penghargaan yang diberikan berupa juara 1 sampai dengan juara harapan 3 pada esai dan poster. Selain itu para peserta melakukan fieldtrip untuk menunjang wawasan dan pengetahuan baru dari tempat yang dikunjungi. Pengabdian ini sukses dilaksanakan karena telah menjadi wadah untuk mendorong keterampilan dalam menulis dan berpikir kritis mahasiswa, membantu dalam memperluas pengetahuan mahasiswa, dan memberi kesempatan mahasiswa untuk berinteraksi dan memperluas jaringan sosial dalam menciptakan semangat persatuan dan kesatuan.