bluuebunny/crossref_metadata_2025 huggingface dataset:
Klasik Şiirin Taşradaki Aktüel İzleri: Hasan Şahmaranoğlu'nun Almıla'daki Klasik Türk Şiiri Nazım Şekilleriyle Yazılmış Şiirleri
Authors: Kaya Bülent
Published: October 2024

Klasik Türk şiiri geleneği yaygın anlamda yaklaşık altı asır sürmüş, önemli temsilciler yetiştirmiştir. 19. yüzyılda da devam eden şiir geleneğinde şekil, muhteva, vezin vb. noktalarda önceki yüzyıllara nazaran bazı değişiklikler ve yenilikler olmuştur. Bu yüzyıldan sonra klasik şiir geleneği devam etmekle beraber eski yaygınlığını yitirmiş, modern Türk şiirinde, halk şiirinde ve halk belleğinde bünyesindeki kaynaklar, motifler, benzetmeler ve diğer unsurlarla yaşamaya devam etmiştir. Günümüzde kısmi de olsa geleneği devam ettiren, klasik Türk şiiri geleneğinin şekil ve muhteva noktasındaki kalıplarına yer veren şair ve şiirler vardır. Bu bağlamda Kilis gibi tarihî ve kültürel zenginliğe sahip, bağrından birçok sanatkâr ve edip yetiştirmiş olan bu şehrin öne çıkan kişiliklerinden Hasan Şahmaranoğlu’nun Almıla adlı eserindeki klasik Türk şiiri nazım şekilleriyle yazılmış şiirler incelenecektir. Bahsi geçen eserdeki yedi gazel, bir tazmin ve yedi tahmis, Şahmaranoğlu’nun klasik şiir geleneğine olan temaslarıyla, kendi şiir sanatı ve üslubu dikkate alınarak şiirlerinden örneklerle değerlendirilecektir. Kilis’in yetiştirdiği önemli simalar arasında yaptığı çalışmalar ve ortaya koyduğu eserlerle unutulmaz bir yer edinen Şahmaranoğlu’nun, klasik edebiyat geleneği hususunda birçok şairin çıktığı Kilis’in aktüel bir temsilcisi olarak gelenek doğrultusunda ortaya koyduğu şiirler ölçü, muhteva, edebî sanatlar gibi farklı açılardan ele alınacaktır. Böylelikle Kilis özelinde klasik şiir geleneğinin yaşayan formları şekil ve muhteva açısından ortaya konularak alana küçük de olsa katkı sağlanacaktır.
Bir Interpretatio Christiana Örneği Olarak Hıristiyan Sembolizminin Mitolojik Varlıkları: Basilisk, Kentaur ve Grifon
Authors: Öner Yasin
Published: October 2024

Bu çalışma, Hristiyan sembolizminin alt dallarından biri olan hayvan sembolizminde yer alıp mitolojik unsurlar barındıran bazı varlıkları konu edinmektedir. Roma İmparatorluğu’nun Milan Fermanı’nı (313) yayımlayarak Hristiyanlığı resmî olarak kabul etmesiyle birlikte diğer dinî inançlara ait sembol ve imgeler tümüyle ortadan kaldırılmamış ve bunlardan bazıları Interpretatio Christiana’ya tabi tutularak olumlu ve olumsuz olmak üzere ayrıştırılıp Hristiyan anlamı taşıyan sembollere dönüştürülmüştür. Bu noktada pek çok kültürün hafızasında yeri bulunan basilisk, kentaur (centaur) ve grifon (griffin) gibi grotesk varlıklar da sahip oldukları arkaik hikayeleri ve fiziksel özellikleri nedeniyle kendilerine yüklenen sembolik anlamlarla Hristiyan inanç ve düşüncesi çerçevesinde yeni anlamlar kazanmıştır. Çalışmanın omurgasını oluşturan bu hayvanların ortak özellikleri, vücutlarının farklı bileşenlerden meydana gelecek şekilde tasarlanmış olmasıdır. Bu anlamda basiliskin vücudunun üst kısmı horoz, geri kalanı yılandan oluşmaktadır. Kentaurun baş ve göğüs kısmı insanken bedeni attır. Grifon ise başı ve kanatları kartaldan, vücudu da aslandan oluşan bir varlıktır. Bu doğrultuda çalışmanın amacı, bahsi geçen varlıkların çeşitli kültürlerdeki anlatılarını ortaya koymak ve Hristiyanlığa geçişle birlikte edindikleri anlamlarla neyi sembolize ettiklerine odaklanmaktır. Amaca hizmet edecek şekilde çalışmada diğer kültürlerle benzerlik ve farklılıkların ortaya konulması açısından karşılaştırma yöntemine sıkça başvurulmuştur. Bununla birlikte ilgili varlıkların mevzu bahis edildiği metinler deskriptif metotla incelenmiştir. Böylece bakışlarıyla düşmanlarını öldürebilme yeteneğine sahip olan basilisk, şeytanla; otoriteye başkaldıran ve saldırgan bir yapıya sahip olan kentaur, Kilise’ye karşı çıkan muhaliflerle; iki üstün varlığın birleşimi olan ve koruyucu kimliği ön plana çıkan grifon ise, genellikle İsa Mesih’in kurtarıcılık yönüyle özdeşleştirilerek Hristiyan hikâyesinin parçası haline gelmiştir.
Temiz Enerjiye Sahip Ülkelerde Kamu Enerji Harcamalarının ve Enerji Vergilerinin Düşük Karbonlu Enerji Tüketimine Etkisi
Authors: Değirmenci Tunahan
Published: October 2024

Küresel çevre sorunları son yıllarda artmış ve acil eylem gerektiren bir sorun hâline gelmiştir. Enerji sektörü, üretilen kirliliğin büyük kısmında sorumludur. Buna karşın düşük karbonlu enerji çözümleri yoluyla bu zorlukları hafifletmenin anahtarını elinde tutmaktadır. Yenilenebilir ve nükleer enerji gibi düşük karbon salınımına sahip enerji kaynaklarına geçişin önemi son yıllarda ivme kazandı. Enerji vergileri ve enerjiye ilişkin araştırma ve geliştirme harcamaları, düşük karbonlu enerji tüketiminin şekillendirilmesinde önemli bir rol oynayabilir. Hükümetler, karbon yoğun yakıtlara vergi uygulayarak ve temiz enerji teknolojilerine yatırımları teşvik ederek düşük karbonlu enerjinin benimsenmesini etkileyebilir. Ayrıca, araştırma ve geliştirmeye yönelik kamu harcamaları, enerji sektöründe yenilikçiliği ve teknolojik ilerlemeleri kolaylaştırmakta, böylece düşük karbonlu enerji çözümlerinin uygulanabilirliğini ve rekabet gücünü artırmaktadır. Bu noktadan hareketle bu çalışma, 1994'ten 2021'e kadar en yüksek temiz enerji kullanımına sahip 10 ülkede kamu enerji harcamalarının ve enerji vergilerinin düşük karbonlu enerjiye etkisini DCCE ve CCE uzun vadeli tahmincileriyle araştırmaktadır. Sonuçlara göre Finlandiya'da enerji vergileri ve enerji harcamaları düşük karbonlu enerji tüketimini teşvik etmektedir. Norveç ve İsviçre'de devlet enerji harcamaları ve Avusturya'da enerji vergileri düşük karbonlu enerji tüketimini olumsuz etkilemektedir. Bu bulgular, hükümetlerin düşük karbonlu enerji teknolojilerine yatırımı etkili bir şekilde teşvik eden, küresel ölçekte sürdürülebilir ve çevre dostu enerji geçişlerini sağlayan kapsamlı politikalar uygulama ihtiyacının altını çiziyor. Gelecek nesillere daha yeşil bir gelecek sağlamak için hükümetlerin ve özel sektörlerin ortak çabaları çok önemlidir.
Stitches Across Time: Tracing the Chamba Rumal’s Journey to Scotland
Authors:   Assistant Professor, Fine Arts, Saroop Rani Government College for Women, Amritsar, Jyoti Jyoti
Published: October 2024

The paper aims to document the century-long journey of a Chamba Rumal, an exquisite example of Indian embroidery, from the princely hill state of Chamba in Himachal Pradesh to Scotland. The Chamba Rumal was created by the Rani of Chamba in July 1898 for Jessie Ann Tuly, the governess of children. This embroidered artefact portrays Lord Krishna’s Ras Leela with Radha and Gopis and is emblematic of Chamba’s fabric artistry, which was inspired by miniature painting during the 17th and 18th centuries. The paper also investigates the history of the craft and its evolution with the patronage of local rulers such as Raja Umed Singh and King Sham Singh, who contributed to the development of Chamba’s murals. Furthermore, the paper analyzes the transfer history of this specific Rumal, currently preserved at the Glasgow Museums Resource Centre, and examines how this textile art contributed to nurturing relations. The paper emphasizes the significance of such artefacts in defining cultural memory and heritage. It shows how these objects chronicle the integrated histories of societies, their art, and the dynamics of reciprocal interactions across continents and centuries.
Construction Risk Assessment of Super-Large-Diameter Shield Tunnel in Karst Area Based on FAHP-TOPSIS Method
Authors: Liu Jiguo , Song Ming , Zhou Yongtao
Published: October 2024

Background:

In recent years, construction accidents happen frequently in shield tunnel crossing
karst caves due to the complex karst geological structure. These are more obvious in super-large-diameter
shield tunnel during construction. In the past, the studies and patents of risk assessment tended
to be subjective since these reviews were mainly based on experience.

Methods:

A super-largediameter tunnel model is constructed by using calculation principle of FAHP--
TOPSIS method based on quantitative analysis and objective weighting method to conduct risk assessment
in karst area based on risks evaluated in a shield tunnel project under construction in a city. The
risk classification is formulated, and the risk assessment system for a super-large-diameter shield tunnel
under construction in karst area is developed to perform computation for assessment.

Results:

The results show that the closeness of the construction risk for a shield tunnel with super-
large-diameter crossing the karst area is 0.034, and the risk level is V, that is, high risk, which
brings great potential safety hazard to tunnel construction. The computation results are consistent with
those of site conditions to verify the feasibility and effectiveness of the method.

Conclusion:

The results have provided a reference for the risk assessment of similar engineering practice
under construction.
Article Highlights:
● At present, many researchers focus on risk assessment management of shield method, but there is a
lack of research on risk assessment of shield construction in the context of cavern development, in contrast,
this study carries out risk assessment of karst super-large-diameter shield construction, which is a
high research innovation.
● With the help of reliable and novel research tools, this study constructs a risk assessment model
based on the calculation principle of FAHP-TOPSIS method with quantitative and objective empowerment
for the construction of oversized diameter shield tunnels in karst areas, which is able to calculate
the risk level more accurately.
● The system constructed in this study can be applied to the field construction. The calculation results
of the construction risk assessment system of super-large-diameter shield tunnel in karst area constructed
in this paper were compared with the field situation, and the match was good, which can provide a
reference for other similar projects and guarantee the safety of field construction, so it has a good promotion.
Malignancy Detection in Lung and Colon Histopathology Images by Transfer Learning with Class Selective Image Processing
Authors: Sukhavasi Vidyullatha , Kulkarni Shridhar , V Raghavendran , C Dastagiraiah , Apat Shraban Kumar , Reddy Pundru Chandra Shaker
Published: October 2024

Aims & Background:

Due to its ferocity, enormous metastatic potential, and variability,
cancer is responsible for a disproportionately high number of deaths. Cancers of the lung
and colon are two of the most common forms of the disease in both sexes worldwide. The excellence
of treatment and the endurance rate for cancer patients can be greatly improved with
early and precise diagnosis.

Objectives & Methodology:

We suggest a computationally efficient and highly accurate strategy
for the rapid and precise diagnosis of lung and colon cancers as a substitute for the standard
approaches now in use. The training and validation procedures in this work made use of an
enormous dataset consisting of lung and colon histopathology pictures. There are 25,000 Histopathological
Images (HIs) in the dataset, split evenly among 5 categories (mostly lung and
colon tissues). Before training it on the dataset, a pretrained neural network (AlexNet) had its
four layers fine-tuned.

Results:

The study enhances malignancy detection in lung and colon histopathology images by
applying transfer learning with class-selective image processing. Instead of enhancing the entire
dataset, a targeted contrast enrichment was applied to images from the underperforming
class, improving the model's accuracy from 92.3% to 99.2% while reducing computational
overhead. CONCLUSION: This approach stands out by emphasizing class-specific enhancements,
leading to significant performance gains. The results meet or exceed established CAD
metrics for breast cancer histological images, demonstrating the method's efficiency and effectiveness.
Boon Plant Calendula Officinalis Linn. (CO): An Investigation, Ethnopharmacological, Phytoconstituent Review’
Authors: Gupta Naincy , Choubey Ankur , Gupta Naveen , Rajput Dharmendra , Shukla Mukesh Kumar
Published: October 2024

Introduction:

Calendula (English Marigold), or "Pot Marigold," is a well-known herbal plant from the family of Asteraceae, which has been used for thousands of years as a me-dicinal herb. It is one of the most widely used aromatic herbs in the Ayurvedic system of medi-cine, which is based on the ethnological significance of the plant. Extracts of this plant have been found to possess a range of therapeutic benefits, including anti-hyperlipidaemia, cardiovascular and antidiabetic properties, as well as antioxidant and anti-inflammatory properties. Additionally, it has been found to be effective in wound healing and has anti-cancer, anti-hepatitis, antibacteri-al, and antiretroviral properties. Traditionally, it has been used as a herbal remedy to treat skin tumours and dermatological lesions as well as ulcers and swellings, as well as nervous disorders.

Aims:

In addition to ethnopharmacology, pharmacology, and toxicology, this abstract also covers the morphology, microscopy, phytoconstituents, pharmacological reports, phytochemistry, and toxicity of the well-known Calendula species. Cosmetic ingredients derived from the C offici-nalis plant include extracts, flower oil, seed oil, and other components of the plant. These com-ponents include minerals, carbohydrates, and lipids; phenolic acids; flavonoids; tannins; couma-rins; sterols; steroids; monoterpenes; sesquiterpene; triterpenes; tocopherol; quinones; amino ac-ids; and resins. A chemical analysis of these ingredients reveals a wide variety of chemical com-pounds, including amino acid, triterpenoid, quinone, flavonoid, volatile oil, carotenoid, and other chemicals. Some Calendula officinalis species have medicinal value, and a literature review high-lights their utilization.

Results:

Calendula officinalis has a wide range of medicinal properties, ranging from antibacte-rial and antifungal properties to anthelmintic and antiviral properties. Additionally, it has antioxi-dant and hepatoprotective properties, as well as cardioprotective and wound-healing properties. Furthermore, it has been used to treat gastrointestinal, eye, and skin diseases. The plant has the potential to be a significant medicinal resource for mankind. It exhibits anti-HIV, cytotoxic, anti-inflammatory, hepatoprotective, and spasmolytic properties. The plant is used in almost 200 cosmetic formulations and has the potential for further research.

Conclusion:

This review emphasizes the future scope of Calendula species, focusing on their multifarious biological activities and potential applications as medicinal agents. This research fills gaps in existing studies, allowing researchers to validate traditional claims and advance the safe and effective use of CO in treating various ailments.
Editorial: Diversidad biológica, multiculturalismo y gestión del conocimiento
Authors: El Director
Published: October 2024

En el Perú, durante el año 2022, el total de exportaciones alcanzó los USD 63,193 millones. De esta suma, solo aproximadamente el 3% (USD 1,200 millones) correspondió a exportaciones de servicios y productos tecnológicos, una cifra insignificante en comparación con los productos tradicionales como minerales y productos agrícolas. Estos datos, ofrecidos por entidades como PROMPERÚ y el Banco Central de Reserva del Perú (BCRP), destacan el predominio del modelo primario exportador y explican en gran medida las disparidades en nuestro desarrollo sostenible. Esto impacta negativamente en la diversificación económica, la competitividad del tejido productivo y el medio ambiente.
The effect of English learning media in improving student's writing skills through the mastery of different discourse markers
Authors:   Doctoral Program, Sultan Ageng Tirtayasa University, Banten, Indonesia, Suryadi Suryadi , Muhyidin Asep ,   Doctoral Program, Sultan Ageng Tirtayasa University, Banten, Indonesia, Syafrizal Syafrizal ,   Doctoral Program, Sultan Ageng Tirtayasa University, Banten, Indonesia, Wu Chi Cheng ,   Education Department, Kun Shan University, Tainan, Taiwan, Erlangga Fajar ,   Informatics Department, Indraprastha University, Jakarta, Indonesia
Published: October 2024

This research aims to determine the effect of learning media and mastery of discourse markers (DMs) on students' writing skills. Students in Indonesia experience many obstacles in their ability to write English. However, along with changes in students' needs in learning to write, digital-based learning media using Google Word Coach Game and Scrabble Word offers new ways to improve students' writing skills through teaching media Google Word Coach Game and Scrabble Word, learning media integrated with Mastering DMs can help improve students' writing skills. However, previous research still needs to incorporate mastery of DMs with the Google Word Coach Game and Scrabble Word learning media. Therefore, this research looks at how the Google Word Coach Game and Scrabble word learning media integrated with mastery of DMs can improve students' English writing skills. This research also examines how the interaction between the Google Word Coach Game and Scrabble word learning media is integrated with mastery of DMs. This research suggests a Google Word Coach Game and Scrabble Word learning media and provides suggestions about the importance of mastering DMs for students in high schools in Indonesia. It also outlines how to test these suggestions and suggests directions for future research.
SEMI-FRAGILE BLIND WATERMARKING MECHANISM FOR COLOR IMAGE AUTHEN
AGE INVARIANT FACE RECOGNITION USING QUADRATIC SUPPORT VECTOR MACHINE – PRINCIPAL COMPONENT ANALYSIS
Authors:   Deenbandhu Chhotu Ram University of Science and Technology, India, M Deepika , J Priyanka ,   Deenbandhu Chhotu Ram University of Science and Technology, India
Published: October 2024

Age Invariant Face Recognition (AIFR) is a new research area in the domain of face recognition that lately received a lot of interest due to its tremendous potential with relevant applications in real-world. It is very challenging research problem to extract robust features describing aging facial information, usually when broad age difference between face images are perceived. In this paper, by using the quadratic support vector machine and principal component analysis technique of feature selection that is robust to aging we address this challenge and achieved the highest accuracy as compared to other methods such as K-Neighbor Neural Network (KNN), Probabilistic Neural Network (PNN), Backpropagation Neural Network (BPNN). FGNET aging dataset is used for the implementation of proposed method which includes a total of 82 separate subjects comprising 1002 images and each subject includes 6-18 images per subject obtained primarily from scanning photographs of subjects between the age ranging from newborn to 69-year-old subjects. From the images, LBP, Gabor and shape features have been extracted and PCA is used as a method of feature reduction. Four stages have been explored in this work: (a) Face recognition (b) Identify the gender of the object (c) Identify the age of the subject using the backpropagation neural network (BPNN) (d) Age invariant face recognition using KNN, PNN, NN and QSVM-PCA. The highest accuracy is achieved using the Quadratic Support Vector Machine – Principal Component Analysis (QSVM-PCA) classifier.
EXTENDING BENEFIT BASED SEGMENTATION TECHNIQUES PERFORMANCE ANALYSIS OVER INTENSITY NON UNIFORMED BRAIN MR IMAGES
Authors:   Sadakathullah Appa College, India, A Farzana , Sathik M Mohamed ,   Sadakathullah Appa College, India, Nisha S Shajun ,   Sadakathullah Appa College, India
Published: October 2024

We find the usefulness of computers in every field including medical field. Scanning the affected part has become a standard study. Diagnosing a disease at the right time, i.e. early detection, from the study of images enables the physician to take right decision and provide proper treatment to the patient. With the alarming growth of population, it is difficult for every individual patient to get a second opinion from medical expert. In these situations, computer-aided automatic diagnosis system will be much helpful. Diabetic retinopathy is a disorder that arises from increase in blood glucose level. Based on the severity, it has been distinguished into four stages. Diagnosing diabetic retinopathy at an early stage from retinal images and providing proper treatment will save the patient from severe vision loss. The proposed method adopts hybridized GLCM features and wavelet features to classify the fundus images according to the severity of the disease. The method is tested with fundus images collected from Indian Diabetic Retinopathy Dataset. The bias field is an undesirable image foible that formulate during the process of image procurement. Segmentation is the procedure of segregating a digital image into constituent component or substantial segments which help in extracting quality amount of information from the region of interest. There is several bias correction strategies have been recommended till date, all these algorithms helps in reducing bias but none of them perfectly removes bias. When incorporating computer aided diagnosing in treatment planning, the leftover bias cause to inaccurate segmentation which leads to faulty diagnosis of the diseases. This paper scrutinizes the segmentation algorithms over bias corrupted brain MR Images and analyzes which segmentation algorithm efficiently segments the image components even though it is corrupted by bias field. The bench mark brain MR Images with different bias spectrum is employed for the research. Quantitative metrics are adopted to conclude the result. The outcome of this paper tends to provide accuracy in computer aided diagnosing and to elect appropriate segmentation technique while developing bias correction based segmentation algorithm.
TRANSFER LEARNING APPROACH FOR SPLICING AND COPY-MOVE IMAGE TAMPERING DETECTION
Authors:   Thadomal Shahani Engineering College, India, K Hebbar Nagaveni , S Kunte Ashwini ,   Thadomal Shahani Engineering College, India
Published: October 2024

Image authentication before using in any security critical applications has become necessary as the image editing tools are increasing and are handy to use in today''s world. Images could be tampered in different ways, but a universal method is required to detect it. Deep learning has gained its importance because of its promising performance in many applications. In this paper a new framework for image tampering detection using Error Level Analysis (ELA) and Convolutional Neural Network (CNN) with transfer learning approach is proposed. In this method, the images are pre-processed using ELA to highlight the tampered region and are used to fine tune the entire model. Six different pre-trained models are used in the proposed framework to compare the performance in classifying the tampered and authentic images. The complexity and processing time of the proposed method is low with respect to most of the existing methods as the images are not divided into patches. The performance of the model obtained is also considerably good with an accuracy of 97.58% with Residual Network 50(ResNet50).
CLASSIFICATION OF COLOR SATELLITE IMAGES USING COMPUTATIONAL INTELLIGENCE
Authors:   National Institute of Electronics and Information Technology, India, Chib Sunita , Devi M Syamala ,   Panjab University, India
Published: October 2024

The classification of color satellite images is presented using Multilayer Perceptron Neural Network and Support Vector Machine. Multilayer Perceptron is used for non-linear classification with 10 hidden layers using different number of epochs. A multiclass SVM is chosen for classification using radial basis function (RBF) kernel. Before performing classification, the image enhancement and feature extraction steps are carried out. The image enhancement is done using contrast stretching. The color features are extracted by using Principal Components Analysis (PCA). Classification results are obtained and testing is done by varying the number of images in the training and test datasets, the number of features and different classifiers. 100 images each obtained from Landsat satellite of NASA, US and Bhuvan geoportal of NRSC, Hyderabad are used in classification. Seven class categories, residential land, commercial land, grasslands, evergreen forest, mixed forest, sediments and clear water are identified. The results are analyzed and it is observed that SVM provides better results as compared to Multilayer Perceptron (MLP). Performance analysis is carried out with respect to classification accuracy and time.
AN EFFICIENT MULTI-DIRECTIONAL INTERPOLATION ALGORITHM FOR SPATIAL ERROR CONCEALMENT
Authors:   Kim Il Sung University, Pyongyang, D.P.R. Korea, Hyon Jo Jong , Su Hwang Pyong ,   Kim Il Sung University, Pyongyang, D.P.R. Korea, Hyon Ri Je ,   Kim Il Sung University, Pyongyang, D.P.R. Korea
Published: October 2024

In real-time video applications, error concealment is used to conceal the corrupted parts of the video sequence without retransmission. In this paper, an efficient multi-directional interpolation algorithm is presented for spatial error concealment. First, the significant edges of missing macroblock are only estimated using a directional edge analysis on the correctly received neighboring blocks. Second, an approximation for each missing pixel is computed along each significant edge. For two boundary pixels along each significant edge direction, the sum of magnitudes of gradients, which has the same quantized direction level as the edge direction, are computed on seven neighboring pixels. Finally, a weighted average of multiple approximations is computed using the sum of gradient magnitudes as weighting factors. Compared with the previous methods using multidirectional interpolation, experimental results show that the proposed method gives better reconstruction quality in terms of objective and subjective evaluations.
LAND USE LAND COVER STUDY OF SENTINEL-2A AND LANDSAT-5 IMAGES USING NDVI AND SUPERVISED CLASSIFICATION TECHNIQUES
Authors:   Karnataka State Akkamahadevi Women’s University, India, Makandar Aziz , Kaman Shilpa ,   Karnataka State Akkamahadevi Women’s University, India
Published: October 2024

Land Use Land Cover (LULC) change monitoring plays very significant role in planning, policy making, management programs required for development activities at regional levels of any country. This study is an attempt to monitor LULC change of Vijayapura taluk, Karnataka, India for the period of 25 years from 1995 to 2021 using Remote Sensing (RS) and Geographic Information System (GIS). Satellite Images from Sentinel-2A MSI (Multispectral Imager), Landsat-5TM (Thematic Mapper) are used to generate LULC maps. Vegetation Change in the study area is computed using Normalized Difference Vegetation Index (NDVI) and results show that vegetation rate is increased from 0.6% in 1995 to 27.5% in 2021. Supervised Classification is carried out by using Maximum Likelihood Classification (MLC). 5 major classes considered for classification are namely: Waterbodies, Cropland/Vegetation, Fallow Land, Built-up Area and Barren Land. ArcGIS software tool is used for implementing the proposed study. Google Earth Pro used for accuracy assessment which is done by taking ground truth values for corresponding Classifications. Results show that the proposed system is able to achieve 88.16% of overall accuracy.
IMPROVING MEDICAL IMAGE PREPROCESSING USING DENOISING TECHNIQUE
Authors:   Bishop Heber College, India, P Thamilselvan
Published: October 2024

Image denoising is a main issue found in medical images and computer vision issues. There are different existing techniques in denoising image but the significant property of a decent image denoising model is that eliminate noise beyond what many would consider possible just as protect edges. Digital images accept a fundamental part both in step-by-step medical image applications, for instance, satellite TV, figured tomography. This method implemented for removing the noise from the lung cancer medical images with securing, transmission and gathering and capacity and recovery measures. This paper presents a pre-processing calculation which is named as Preprocessing Profuse Clustering Technique (PPCT) in light of the super pixel clustering. K-Means clustering, Simple Linear Iterative Clustering, Fusing Optimization algorithms are engaged with this proposed Preprocessing Profuse Clustering Technique and is additionally utilized for denoising the Lung Cancer images to get the more exact outcome in the dynamic interaction.
GENETIC ALGORITHM OPTIMIZATION OF FEATURE SELECTION FOR MEDICAL IMAGE CLASSIFICATION
Authors:   Soban Singh Jeena University, India, Saxena Parul , Huque M.D. Sirajul ,   Guru Nanak Institutions Technical Campus, India, Vhatkar Sangeeta ,   Thakur College of Engineering and Technology, India, Ramana K. Venkata ,   Dr. J.J. Magdum College of Engineering, India, Durai C. Anand Deva ,   King Khalid University, Saudi Arabia
Published: October 2024

Medical image classification plays a pivotal role in diagnosing various diseases. However, selecting informative features from these images remains a challenging task due to the high dimensionality and complexity of the data. Genetic algorithms (GAs) offer a promising approach for feature selection in medical image classification tasks by mimicking the process of natural selection to evolve optimal solutions. This study proposes a genetic algorithm optimization framework for feature selection in medical image classification. The GA iteratively searches the feature space to find the subset of features that maximizes the classification performance. Fitness evaluation is based on a classifier’s performance using selected features, and genetic operators such as crossover and mutation are applied to produce new generations of feature subsets. The proposed framework contributes to enhancing the efficiency and effectiveness of medical image classification by identifying relevant features. By employing GAs, it overcomes the limitations of traditional feature selection methods and adapts to the complexity of medical image data. Experimental results on benchmark medical image datasets demonstrate the effectiveness of the proposed approach. Significant improvements in classification accuracy and computational efficiency are observed compared to baseline methods. Moreover, the selected features exhibit robustness across different classifiers, highlighting the generalizability of the proposed framework.
PREDICTIVE MAINTENANCE IN INDUSTRIAL SYSTEMS USING DATA MINING WITH FUZZY LOGIC SYSTEMS
Authors:   Tagore Engineering College, India, B Selvalakshmi , P Vijayalakshmi ,   Knowledge Institute of Technology, India, N Subha ,   Knowledge Institute of Technology, India, T Balamani ,   M. Kumarasamy college of Engineering, India
Published: October 2024

In industrial systems, predictive maintenance has emerged as a crucial strategy to minimize downtime and optimize operational efficiency. This study explores the utilization of data mining techniques, specifically fuzzy logic systems, for predictive maintenance. The background section examines the importance of predictive maintenance in industrial contexts and highlights the limitations of traditional approaches. The methodology section outlines the process of employing fuzzy logic systems for predictive maintenance, including data preprocessing, feature selection, fuzzy rule generation, and model evaluation. The contribution of this research lies in providing a comprehensive framework for implementing predictive maintenance using fuzzy logic systems, offering insights into the integration of data mining techniques with industrial systems. Results demonstrate the effectiveness of the proposed methodology in accurately predicting maintenance needs and minimizing unplanned downtime. Findings suggest that fuzzy logic systems can enhance predictive maintenance capabilities by handling uncertainties and vagueness inherent in industrial data.
Sustratos para la propagación de plantas de mango en vivero
Authors: León Pacheco Rommel Igor , Parra Fuentes Madeleyne , Gómez Correa Juan Camilo
Published: October 2024

Los sustratos son materiales sólidos simples o mezclados, que se usan para sustituir el suelo y facilitar el anclaje, el aporte de agua y los nutrientes, y de esta manera garantizar un crecimiento adecuado del sistema radicular de las plantas. Los sustratos se clasifican en orgánicos (figura 1) e inorgánicos (figura 2). En el primer grupo, se encuentran los materiales orgánicos naturales, como la turba; los originados por subproductos agroindustriales, como la fibra de coco, la cascarilla de arroz, las pajas, las virutas, los bagazos, entre otros, y los generados de síntesis, como el poliuretano y el estireno.
Occurrence of Stigmatizing Documentation Among Hospital Medicine Encounters With Opioid-Related Diagnosis Codes: Cohort Study
Authors: Bradford William S , Bratches Reed W R , Porras Hollie , Chen David R , Gagnon Kelly W , Ascher Simon B
Published: October 2024

Background

Physician use of stigmatizing language in the clinical documentation of hospitalized adults with opioid use is common. However, patient factors associated with stigmatizing language in this setting remain poorly characterized.

Objective

This study aimed to determine whether specific demographic factors and clinical outcomes are associated with the presence of stigmatizing language by physicians in the clinical documentation of encounters with opioid-related ICD-10 (International Statistical Classification of Diseases, Tenth Revision) codes.

Methods

Hospital encounters with one or more associated opioid-related ICD-10 admission diagnoses on the hospital medicine service during the 2020 calendar year were analyzed for the presence of stigmatizing language in history and physical and discharge summaries. Multivariable adjusted logistic regression models were used to determine associations of age, race, gender, medication for addiction treatment use, against medical advice discharge, homelessness, comorbid polysubstance use, comorbid psychiatric disorder, comorbid chronic pain, cost, and 30-day readmission with the presence of stigmatizing language.

Results

A total of 221 encounters were identified, of which 64 (29%) encounters had stigmatizing language present in physician documentation. Most stigmatizing language was due to use of “substance abuse” rather than the preferred term “substance use” (63/66 instances). Polysubstance use and homelessness were independently associated with the presence of stigmatizing language (adjusted odds ratio [aOR] 7.83; 95% CI 3.42-19.24 and aOR 2.44; 95% CI 1.03-5.90) when controlling for chronic pain and other covariates.

Conclusions

Among hospital medicine encounters with an opioid-related diagnosis, stigmatizing language by physicians in clinical documentation was common and independently associated with comorbid polysubstance use and homelessness.
Memetakan Garis Pertahanan Melawan Leptospirosis: Pendekatan Spasial untuk Meningkatkan Respons dan Pencegahan
Authors: Giyantolin Giyantolin , Subiakto Yuli
Published: October 2024

Latar Belakang: Leptospirosis adalah penyakit zoonosis yang disebabkan oleh bakteri Leptospira. Penyakit ini menjadi perhatian serius di banyak negara, termasuk Indonesia, khususnya di Kabupaten Demak, Provinsi Jawa Tengah. Kabupaten Demak memiliki topografi dan iklim yang mendukung pertumbuhan bakteri Leptospira, ditambah dengan pola perilaku yang dapat meningkatkan risiko paparan terhadap penyakit ini.Tujuan: Penelitian ini bertujuan untuk memetakan garis pertahanan dalam mencegah dan mengendalikan penyakit leptospirosis melalui pendekatan spasial.Metode: Penelitian ini menggunakan cross-sectional yang melibatkan analisis spasial terhadap data kasus leptospirosis yang dilaporkan di Kabupaten Demak dari tahun 2014-2023. Data yang dianalisis mencakup daerah spasial kasus dan informasi demografis terkait. Analisis dilakukan menggunakan metode analisis geospasial seperti peta choropleth, analisis hotspot, dan analisis klaster.Hasil: Hasil penelitian menunjukkan bahwa pada tahun 2014, hanya sebagian kecamatan (57%) yang mengalami kejadian leptospirosis (35 kasus), namun pada 2018 semua kecamatan (100%) terdampak (112 kasus). Analisis spasial menunjukkan bahwa penyakit ini lebih sering terjadi di daerah utara dibandingkan daerah selatan Kabupaten Demak, terutama di daerah rendah atau dekat perairan.Kesimpulan: Penyebaran penyakit ini dalam satu dekade terakhir menunjukkan bahwa wilayah utara lebih rentan. Melalui pendekatan spasial, intervensi kesehatan masyarakat yang tepat sasaran dapat diimplementasikan untuk mengurangi insiden leptospirosis dan melindungi masyarakat dari ancaman penyakit leptospirosis.
Bebas dan Terawasi: Dinamika Flexing pada Gen Z di Instagram
Authors: Hartono Langit Gemintang Muhammad
Published: October 2024

Flexing merupakan salah satu cara individu mengekspresikan dirinya di media sosial. Dengan flexing, seseorang mampu mendapatkan emosi positif yang berdampak baik bagi well-being-nya, seperti tervalidasi sampai merasakan kebanggaan. Flexing bukan merupakan fenomena individual, melainkan juga fenomena yang memiliki akar struktural. Dalam penelitian ini, flexing dilihat sebagai fenomena individualisasi, yaitu masyarakat dengan relasi sosial yang renggan dan tidak terikat dengan institusi-institusi tradisional. Oleh karena itu, flexing merupakan bentuk ekspresi individualitas pada subjek yang merupakan manifestasi struktural dari fenomena tersebut. Walaupun begitu, individu tidak sepenuhnya terbebas dari bentuk kontrol baru yang memaksa individu melakukan perilaku-perilaku adaptif. Dalam konteks media sosial, kontrol itu dimediasi oleh intrumentarianisme survelliance capitalism. Melalui instrumentarianisme, kontrol digenerasi oleh otoritas yang tidak terlihat yang tercipta melalui jejaring interaksi yang dikondisikan oleh suatu arena sosial yang spesifik, yaitu media sosial. Akibatnya, individu mengalami suatu dilema: di satu sisi ia dapat dengan bebas mengekspresikan individualitasnya di media sosial; tetapi, di sisi lain ia harus berhadap-hadapan dengan kontrol yang memaksa dirinya untuk berperilaku adaptif. Melalui fenomenologi, penelitian ini berusaha memahami konstruksi makna tentang flexing dan bagaimana struktur membatasi ekspresi individualitas yang dilakukan di Instagram.
Effect of Cooking Treatments on Drying Kinetics, Polyphenols Content and Antioxidant Activity of Orange-Fleshed Sweet Potato
Authors: Kamal Aya , Golshany Hazem
Published: October 2024

This study examines the effects of boiling, steaming, and microwaving on the drying kinetics, total polyphenol content (TPC), antioxidant activity, and total carotenoid content (TCC) of orange-fleshed sweet potatoes (OFSP), a vital source of beta-carotene for combating vitamin A deficiency. Results indicate that steaming preserved the highest TPC at 4.28 mg GAE/g DW, while microwaving yielded the highest TCC at 527.35 µg BCE/g DW. Antioxidant activity, measured via DPPH radical scavenging, was significantly enhanced by steaming (3.48 μmol TE/g DW) and microwaving (3.29 μmol TE/g DW) compared to boiling (1.40 μmol TE/g DW). The drying kinetics followed the Page model, demonstrating a strong fit (R² > 0.9988) across treatments, highlighting the complex moisture loss behaviors influenced by cooking methods. Boiling resulted in a 51% reduction in TPC due to leaching, while both steaming and microwaving significantly increased antioxidant activity despite some degradation of phenolic compounds during microwaving. These findings underscore the importance of cooking methods in optimizing the nutritional value of OFSP, providing practical recommendations for food preparation to enhance health benefits and address vitamin A deficiency in vulnerable populations.
Recent Advances in the development of User-friendly Software Tools for Computational Protein Design, Modeling, and Molecular Docking
Authors: Joshua Magezi , Syrus Semawule , Magdalene Namuswe , Nwankwo Janice Adaeze
Published: October 2024

Computational protein design, modeling, and Molecular Docking represent a group of vital in-silico methods employed in predicting protein sequences with desired functions, predicting protein structures, and several molecular interactions with proteins. The application of such in silico methods is seen in the screening of potential targets during new drug designs, the discovery of novel protein sequences that could play new and vital functions such as industrial processes, understanding of protein function by studying its residues, and understanding of the effects of position mutations to the structure and function of the protein. This means these tools find a lot more use in protein-related research. However, many scientists are basic computer users and not experts in utilizing sophisticated software involved in in-silico Protein methods. This limits the progress of mainly young researchers towards protein-related research ideas. This review therefore discusses the progress in the development of user-friendly tools for assisted Insilco protein design, modeling, and docking.
Study of Disability Literature Analysis System
Authors: Some Anjan
Published: October 2024

This article is perhaps the most extensive review of the Disability Literature Analysis System (DLAS), a novel framework developed specifically to study and analyze the literary works that concern disability in a focused and organized manner. Therefore, the focus can be said to be on resolving the problem of incorporating literary studies into disability studies. The thesis offers an organised and comprehensive approach to addressing the issues related to representation of disability or ‘disability narratives’ in works of literature. The current research studies a wide range of contemporary works of disability literature through the lens of qualitative content analysis and semi-structured interviews with relevant authors, as well as quantitative text mining techniques in order to search for specific themes, language, and visual representation. In literature, there are important and illustrative developments in understanding how impairment and sickness are represented including the changes in presentation of character types, development of issues over a period of time and the distortion which author’s attitudes cause on images of disability. This research offers an analytic perspective salient to the specific disability studies in the literature because it provides an alternative scheme that is interesting, practical and illustrative on the benefits of interaction between ‘writing’ and ‘disability’. The study also provides them with the means to undertake in-depth reading of disability related literary texts and criticism and flush out the images of disability crafted by the authors. Lastly, it also creates avenues for future exploration of issues that relate disability studies to literary theory and practices as well as the digital humanities.
The importance of teaching paradigmatic lexical relations to EFL students: How to teach homonymy
Authors: Jashari Dr. Alda
Published: October 2024

Developing vocabulary knowledge is crucially important for second language learners because vocabulary is the key determinant of all skills, and these are, in turn, of vital importance for academic success, both in children and adults. Vocabulary is essential for expressing thoughts, ideas, and emotions clearly and accurately. A strong vocabulary enables students to articulate their viewpoints more effectively in both written and spoken forms, facilitating better interactions in academic and social contexts. English vocabulary is rich in pairs of words, identical in sound and spelling but different on meaning. One of the problems teachers are usually concerned is how to explain to the students the difference between two words of identical form but completely separated meanings and two words of the same form whose meanings are different but still related. The problem of teaching the sameness of name combined with the difference of meaning might seem to present teachers with an extremely daunting task. Understanding homonyms is crucial for students because it enhances their linguistic skills and improves reading comprehension. It also aids in developing critical thinking when faced with language ambiguities. This paper aims at providing a carefully and necessary analysis on the methods, activities and tools teachers should use as to encourage ELF students to explore the meanings of new homonymous words they encounter, to empower their linguistic and communicative skills and create an effective and inspiring learning environment.
Role of Psychologists and Psychological theories in Mental wellness of pupils in the context of National Education Policy-2020
Authors: Rose Dr. Vanita , Kadian Romi
Published: October 2024

In view of increasing cases of mental health disorders among students especially the young ones, there is a need to incorporate psychological support into the education systems. This need is recognized by the National Education Policy 2020 through adoption of student centered education that includes the social, emotional, and psychological aspects of the student. This paper seeks to understand psychologists or theories of psychology that would support the enhancement of students’ mental wellness under NEP 2020. Further, we explore the different theories of psychology including cognitive behaviorism, humanism, and social-cultural that help in identifying the students’ psychological needs. Understanding of these theories assists educators to design a positive emotionally supportive climate conductive to the growth of emotional security, social skills, and intellectual abilities. Drawing from the literature in psychology, we present a discussion into integration of psychological principles in curriculum development, instruction and students’ evaluation. It also looks at some of the threats that may inhibit organizational setups within the education sector from implementing mental health service delivery and ways of increasing successful implementation. The study implies that, for the realization of the NEP 2020 goals of a balanced education system with regards to mental wellness of the learners, collective efforts of educators, psychologists, parents and policy makers should be encouraged.