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Organic Amendments: A Natural Way To Suppress Phytopathogens: A Sustainable Approach To Go Green, Rameesha Naghman, Mahnoor Tanveer Bhatti, Zarqa Najabat, Sajjad Hyder, Zarrin Fatima Rizvi, Amjad Shahzad Gondal, Zikria Zafar, Sadia Malik, Rashid Iqbal, Aqsa Hafeez, Baber Ali, Romi̇na Alina Marc
Organic Amendments: A Natural Way To Suppress Phytopathogens: A Sustainable Approach To Go Green, Rameesha Naghman, Mahnoor Tanveer Bhatti, Zarqa Najabat, Sajjad Hyder, Zarrin Fatima Rizvi, Amjad Shahzad Gondal, Zikria Zafar, Sadia Malik, Rashid Iqbal, Aqsa Hafeez, Baber Ali, Romi̇na Alina Marc
Turkish Journal of Agriculture and Forestry
No abstract provided.
Plant Growth Regulators Ameliorate Biochemical And Molecular Parameters In Plantago Ovata Forssk. Under Salt Stress, Abdul Samad, Kanval Shaukat, Mahmood Ur Rahman Ansari, Hafiz Muhammad Ahmad, Mereen Nizar, Abdul Hakeem, Sajid Fiaz, Hayat Ali Alafari, Areej S. Jalal, Kotb A. Attia, Neva Karataş
Plant Growth Regulators Ameliorate Biochemical And Molecular Parameters In Plantago Ovata Forssk. Under Salt Stress, Abdul Samad, Kanval Shaukat, Mahmood Ur Rahman Ansari, Hafiz Muhammad Ahmad, Mereen Nizar, Abdul Hakeem, Sajid Fiaz, Hayat Ali Alafari, Areej S. Jalal, Kotb A. Attia, Neva Karataş
Turkish Journal of Agriculture and Forestry
No abstract provided.
Impact Of Dust Load And Lead (Pb) Stress On Leaf Functioning Of Urban Vegetation, Muhammad Azeem Sabir, Muhammad Farrakh Nawaz, Tanveer Hussain Khan, Usman Zulfiqar, Junaid Naseer, Sadam Hussain, Sadaf Gul, Muhammad Faisal Maqsood, Rashid Iqbal, Baber Ali, Rana Roy
Impact Of Dust Load And Lead (Pb) Stress On Leaf Functioning Of Urban Vegetation, Muhammad Azeem Sabir, Muhammad Farrakh Nawaz, Tanveer Hussain Khan, Usman Zulfiqar, Junaid Naseer, Sadam Hussain, Sadaf Gul, Muhammad Faisal Maqsood, Rashid Iqbal, Baber Ali, Rana Roy
Turkish Journal of Agriculture and Forestry
No abstract provided.
Delm: Deep Ensemble Learning Model For Multiclass Classification Of Super-Resolution Leaf Disease Images, Prabhjot Kaur, Mukund Pratap Singh, Anand Muni Mishra, Achyut Shankar, Prabhishek Singh, Manoj Diwakar, Soumya Ranjan Nayak
Delm: Deep Ensemble Learning Model For Multiclass Classification Of Super-Resolution Leaf Disease Images, Prabhjot Kaur, Mukund Pratap Singh, Anand Muni Mishra, Achyut Shankar, Prabhishek Singh, Manoj Diwakar, Soumya Ranjan Nayak
Turkish Journal of Agriculture and Forestry
No abstract provided.
The Study Of The Quality Parameters Of The Tortilla Chips Products Formulated From Mixtures Of Corn Flour And Legumes, Giorgiana Buzgau, Romi̇na Alina Marc, Crina Carmen Muresan, Anca Farcas, Sonia Ancuta Socaci, Andruta Muresan, Sevastita Muste
The Study Of The Quality Parameters Of The Tortilla Chips Products Formulated From Mixtures Of Corn Flour And Legumes, Giorgiana Buzgau, Romi̇na Alina Marc, Crina Carmen Muresan, Anca Farcas, Sonia Ancuta Socaci, Andruta Muresan, Sevastita Muste
Turkish Journal of Agriculture and Forestry
No abstract provided.
Optimization Of Vae-Cgan Structure For Missing Time-Series Data Complementation Of Uav Jujube Garden Aerial Surveys, Shunkang Ling, Nianyi Wang, Jingbin Li, Longpeng Ding
Optimization Of Vae-Cgan Structure For Missing Time-Series Data Complementation Of Uav Jujube Garden Aerial Surveys, Shunkang Ling, Nianyi Wang, Jingbin Li, Longpeng Ding
Turkish Journal of Agriculture and Forestry
No abstract provided.
Conventional And Organic Fertilization Improve The Growth Responses And Essential Oil Content Of Salvia Fruticosa Mill., Fi̇li̇z Öktüren Asri̇, Memi̇ş Ensar Ertürk, Murat Şi̇mşek, Fati̇h Alpay Vuran, Fatma Uysal Bayar
Conventional And Organic Fertilization Improve The Growth Responses And Essential Oil Content Of Salvia Fruticosa Mill., Fi̇li̇z Öktüren Asri̇, Memi̇ş Ensar Ertürk, Murat Şi̇mşek, Fati̇h Alpay Vuran, Fatma Uysal Bayar
Turkish Journal of Agriculture and Forestry
No abstract provided.
Crossing Success Of 'Pot Miniature Rose X Cut Rose', Merve Uran Şener, Soner Kazaz, Tuğba Kiliç, Ezgi̇ Doğan Meral
Crossing Success Of 'Pot Miniature Rose X Cut Rose', Merve Uran Şener, Soner Kazaz, Tuğba Kiliç, Ezgi̇ Doğan Meral
Turkish Journal of Agriculture and Forestry
No abstract provided.
Enhancing Exploration-Exploitation In Harmony Search For Airborne Hyperspectral Imaging Band Selection (E3hs), Mohammed Abdulmajeed Moharram, Divya Meena Sundaram
Enhancing Exploration-Exploitation In Harmony Search For Airborne Hyperspectral Imaging Band Selection (E3hs), Mohammed Abdulmajeed Moharram, Divya Meena Sundaram
Turkish Journal of Electrical Engineering and Computer Sciences
Hyperspectral imaging has emerged as a prominent area of research in the field of remote sensing science. However, hyperspectral images (HSIs) pose a notable challenge due to the presence of numerous irrelevant and redundant spectral bands exhibiting high correlation. Therefore, it is necessary to enhance the classification performance for HSI processing by selecting the most relevant discriminative spectral bands. To this end, this paper introduces a metaheuristic search method called enhancing exploration-exploitation in harmony search (E3HS). The standard harmony search suffers from many weaknesses, such as premature convergence and falling easily into the local optimum. Consequently, E3HS was proposed to …
Multi-View Brain Tumor Segmentation (Mvbts): An Ensemble Of Planar And Triplanar Attention Unets, Snehal Rajput, Rupal Kapdi, Mehul Raval, Mohendra Roy
Multi-View Brain Tumor Segmentation (Mvbts): An Ensemble Of Planar And Triplanar Attention Unets, Snehal Rajput, Rupal Kapdi, Mehul Raval, Mohendra Roy
Turkish Journal of Electrical Engineering and Computer Sciences
3D UNet has achieved high brain tumor segmentation performance but requires high computation, large memory, abundant training data, and has limited interpretability. As an alternative, the paper explores using 2D triplanar (2.5D) processing, which allows images to be examined individually along axial, sagittal, and coronal planes or together. The individual plane captures spatial relationships, and combined planes capture contextual (depth) information. The paper proposes and analyzes an ensemble of uniplanar and triplanar UNets combined with channel and spatial attention for brain tumor segmentation. It investigates the significance of each plane and analyzes the impact of uniplanar and triplanar ensembles with …
A Unique Hybrid Domain Hand-Crafted Feature To Classify Colorectal Tissue Histopathological Images Using Multiheaded Cnn, Anurodh Kumar, Amit Vishwakarma, Varun Bajaj
A Unique Hybrid Domain Hand-Crafted Feature To Classify Colorectal Tissue Histopathological Images Using Multiheaded Cnn, Anurodh Kumar, Amit Vishwakarma, Varun Bajaj
Turkish Journal of Electrical Engineering and Computer Sciences
Early diagnosis of colorectal cancer lengthens human life and is helpful in efforts to cure the illness. Histopathological inspection is a routinely utilized technique to diagnose it. Visual assessment of histopathological images takes more investigation time, and the decision is based on the individual perceptions of clinicians. The existing methods for colorectal cancer classification use only spatial information. However, studies on the spectral domains of information are lacking in the literature. Therefore, the performance of the existing techniques is moderate. To improve the performance of colorectal cancer classification, this work proposes a unique hybrid domain hand-crafted feature formulated using scale-invariant …
Hybrid Machine Learning Model To Predict Chronic Kidney Diseases Using Handcrafted Features For Early Health Rehabilitation, Amjad Rehman, Tanzila Saba, Haider Ali, Narmine Elhakim, Noor Ayesha
Hybrid Machine Learning Model To Predict Chronic Kidney Diseases Using Handcrafted Features For Early Health Rehabilitation, Amjad Rehman, Tanzila Saba, Haider Ali, Narmine Elhakim, Noor Ayesha
Turkish Journal of Electrical Engineering and Computer Sciences
Chronic kidney diseases proliferate due to hypertension, diabetes, anemia, obesity, smoking etc. Patients with such conditions are sometimes unaware of first symptoms, complicating disease diagnosis. This paper presents chronic kidney disease (CKD) prediction model to classify CKD patients from NCKD (Non-CKD). The proposed study has two main stages. First, we found the odds ratio through logistic regression and comparison test to identify early risk factors from kidneys? MRI and differentiate CKD from NCKD subjects. In stage 2, LR, LDA, MLP classifiers were applied to predict CKD and NCKD by extracting features from MRI. The odds ratio of blood glucose random …
Cognitive Digital Modelling For Hyperspectral Image Classification Using Transfer Learning Model, Mohammad Shabaz, Mukesh Soni
Cognitive Digital Modelling For Hyperspectral Image Classification Using Transfer Learning Model, Mohammad Shabaz, Mukesh Soni
Turkish Journal of Electrical Engineering and Computer Sciences
Deep convolutional neural networks can fully use the intrinsic relationship between features and improve the separability of hyperspectral images, which has received extensive in recent years. However, the need for a large number of labelled samples to train deep network models limits the application of such methods. The idea of transfer learning is introduced into remote sensing image classification to reduce the need for the number of labelled samples. In particular, the situation in which each class in the target picture only has one labelled sample is investigated. In the target domain, the number of training samples is enlarged by …
Classification Of Chronic Pain Using Fmri Data: Unveiling Brain Activity Patterns For Diagnosis, Rejula V, Anitha J, Belfin Robinson
Classification Of Chronic Pain Using Fmri Data: Unveiling Brain Activity Patterns For Diagnosis, Rejula V, Anitha J, Belfin Robinson
Turkish Journal of Electrical Engineering and Computer Sciences
Millions of people throughout the world suffer from the complicated and crippling condition of chronic pain. It can be brought on by several underlying disorders or injuries and is defined by chronic pain that lasts for a period exceeding three months. To better understand the brain processes behind pain and create prediction models for pain-related outcomes, machine learning is a potent technology that may be applied in Functional magnetic resonance imaging (fMRI) chronic pain research. Data (fMRI and T1-weighted images) from 76 participants has been included (30 chronic pain and 46 healthy controls). The raw data were preprocessed using fMRIprep …
Trcaptionnet: A Novel And Accurate Deep Turkish Image Captioning Model With Vision Transformer Based Image Encoders And Deep Linguistic Text Decoders, Serdar Yildiz, Abbas Memi̇ş, Songül Varli
Trcaptionnet: A Novel And Accurate Deep Turkish Image Captioning Model With Vision Transformer Based Image Encoders And Deep Linguistic Text Decoders, Serdar Yildiz, Abbas Memi̇ş, Songül Varli
Turkish Journal of Electrical Engineering and Computer Sciences
Image captioning is known as a fundamental computer vision task aiming to figure out and describe what is happening in an image or image region. Through an image captioning process, it is ensured to describe and define the actions and the relations of the objects within the images. In this manner, the contents of the images can be understood and interpreted automatically by visual computing systems. In this paper, we proposed the TRCaptionNet a novel deep learning-based Turkish image captioning (TIC) model for the automatic generation of Turkish captions. The model we propose essentially consists of a basic image encoder, …
Yolo And Lsh-Based Video Stream Analytics Landscape For Short-Term Traffic Density Surveillance At Road Networks, Lavanya K, Stuti Tiwari, Rahul Anand, Jude Hemanth
Yolo And Lsh-Based Video Stream Analytics Landscape For Short-Term Traffic Density Surveillance At Road Networks, Lavanya K, Stuti Tiwari, Rahul Anand, Jude Hemanth
Turkish Journal of Electrical Engineering and Computer Sciences
The duty of monitoring traffic during rush hour is difficult due to the fact that modern roadways are getting more crowded every day. The automated solutions that have already been created in this area are ineffective at processing enormous amounts of data in a short amount of time, leading to ineffectiveness and inconsistent results. The YOLO (you only look once) and LSH (locality sensitive hashing) algorithms are combined with the Kafka architecture in this study to create a method for assessing traffic density in real-time scenarios. Our concept, which is specifically designed for vehicular networks, predicts the traffic density in …
Deep Feature Extraction, Dimensionality Reduction, And Classification Of Medical Images Using Combined Deep Learning Architectures, Autoencoder, And Multiple Machine Learning Models, Ahmet Hi̇dayet Ki̇raz, Fatime Oumar Djibrillah, Mehmet Emi̇n Yüksel
Deep Feature Extraction, Dimensionality Reduction, And Classification Of Medical Images Using Combined Deep Learning Architectures, Autoencoder, And Multiple Machine Learning Models, Ahmet Hi̇dayet Ki̇raz, Fatime Oumar Djibrillah, Mehmet Emi̇n Yüksel
Turkish Journal of Electrical Engineering and Computer Sciences
Accurate analysis and classification of medical images are essential factors in clinical decision-making and patient care. A novel comparative approach for medical image classification is proposed in this study. This new approach involves several steps: deep feature extraction, which extracts the informative features from medical images; concatenation, which concatenates the extracted deep features to form a robust feature vector; dimensionality reduction with autoencoder, which reduces the dimensionality of the feature vector by transforming it into a different feature space with a lower dimension; and finally, these features obtained from all these steps were fed into multiple machine learning classifiers (SVM, …
Feature Distillation From Vision-Language Model For Semisupervised Action Classification, Asli Çeli̇k, Ayhan Küçükmani̇sa, Oğuzhan Urhan
Feature Distillation From Vision-Language Model For Semisupervised Action Classification, Asli Çeli̇k, Ayhan Küçükmani̇sa, Oğuzhan Urhan
Turkish Journal of Electrical Engineering and Computer Sciences
The training of supervised machine learning approaches is critically dependent on annotating large-scale datasets. Semisupervised learning approaches aim to achieve compatible performance with supervised methods using relatively less annotation without sacrificing good generalization capacity. In line with this objective, ways of leveraging unlabeled data have been the subject of intense research. However, semisupervised video action recognition has received relatively less attention compared to image domain implementations. Existing semisupervised video action recognition methods trained from scratch rely heavily on augmentation techniques, complex architectures, and/or the use of other modalities while distillation-based methods use models that have only been trained for 2D …
Cccd: Corner Detection And Curve Reconstruction For Improved 3d Surface Reconstruction From 2d Medical Images, Mriganka Sarmah, Arambam Neelima
Cccd: Corner Detection And Curve Reconstruction For Improved 3d Surface Reconstruction From 2d Medical Images, Mriganka Sarmah, Arambam Neelima
Turkish Journal of Electrical Engineering and Computer Sciences
The conventional approach to creating 3D surfaces from 2D medical images is the marching cube algorithm, but it often results in rough surfaces. On the other hand, B-spline curves and nonuniform rational B-splines (NURBSs) offer a smoother alternative for 3D surface reconstruction. However, NURBSs use control points (CTPs) to define the object shape and corners play an important role in defining the boundary shape as well. Thus, in order to fill the research gap in applying corner detection (CD) methods to generate the most favorable CTPs, in this paper corner points are identified to predict organ shape. However, CTPs must …
Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur
Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur
Turkish Journal of Electrical Engineering and Computer Sciences
Segmentation of lung regions is of key importance for the automatic analysis of Chest X-Ray (CXR) images, which have a vital role in the detection of various pulmonary diseases. Precise identification of lung regions is the basic prerequisite for disease diagnosis and treatment planning. However, achieving precise lung segmentation poses significant challenges due to factors such as variations in anatomical shape and size, the presence of strong edges at the rib cage and clavicle, and overlapping anatomical structures resulting from diverse diseases. Although commonly considered as the de-facto standard in medical image segmentation, the convolutional UNet architecture and its variants …
Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi
Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi
Turkish Journal of Electrical Engineering and Computer Sciences
Explainable AI (XAI) improved by a deep neural network (DNN) of a residual neural network (ResNet) and long short-term memory networks (LSTMs), termed XAIRL, is proposed for segmenting foot infrared imaging datasets. First, an infrared sensor imaging dataset is acquired by a foot infrared sensor imaging device and preprocessed. The infrared sensor image features are then defined and extracted with XAIRL being applied to segment the dataset. This paper compares and discusses our results with XAIRL. Evaluation indices are applied to perform various measurements for foot infrared image segmentation including accuracy, precision, recall, F1 score, intersection over union (IoU), Dice …
Cover And Contents
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
A Comprehensive Review Of Geometrical Thermodynamics: From Fluctuations To Black Holes, S. Mahmoudi, Kh. Jafarzade, Seyed Hossein Hendi
A Comprehensive Review Of Geometrical Thermodynamics: From Fluctuations To Black Holes, S. Mahmoudi, Kh. Jafarzade, Seyed Hossein Hendi
Turkish Journal of Physics
This paper presents a comprehensive review of geometrical thermodynamics, which employs geometric concepts to study the thermodynamic properties of physical systems. The review covers key topics such as thermodynamic fluctuation theory, proposed thermodynamic metrics in various coordinate systems, and thermodynamic curvature.Additionally, the paper discusses the geometrical approach to black hole thermodynamics and provides an overview of recent research in this field.
A Portable And Low-Cost Incubator System Enabling Real-Time Cell Imaging Based On A Smartphone, Ari̇f Engi̇n Çeti̇n
A Portable And Low-Cost Incubator System Enabling Real-Time Cell Imaging Based On A Smartphone, Ari̇f Engi̇n Çeti̇n
Turkish Journal of Physics
Incubators serve as essential tools for maintaining optimal temperature, humidity, and atmospheric gas composition for cell cultures. Their applications span across various fields like cell biology, microbiology, and molecular biology. However, in many cell-based studies, observing cellular changes often necessitates moving cells out of the incubator for microscope examination. Unfortunately, exposing cells to an environment that does not support healthy growth can undermine the reliability of test outcomes. In this article, we present a groundbreaking solution: a cost-effective, portable incubator system seamlessly integrated with a smartphone for real-time characterization tests. This innovation offers comparable imaging capabilities and maintains an environment …
Isotope And Hydrochemical Characteristics Of Thermal Waters Along The Active Fault Zone (Erzin-Hatay/Turkey) And Their Geothermal Potential, Di̇dem Yasi̇n, Gali̇p Yüce
Isotope And Hydrochemical Characteristics Of Thermal Waters Along The Active Fault Zone (Erzin-Hatay/Turkey) And Their Geothermal Potential, Di̇dem Yasi̇n, Gali̇p Yüce
Turkish Journal of Earth Sciences
Geochemical investigations carried out on thermal waters over the Erzin-Hatay area allowed the collection of a suite of 9 samples from natural springs and one well characterized by outlet temperatures in the range from 19.6 to 31.5 °C. All of the springs have slightly acidic pH (in the range of 6) but one sample was marked by a pH value >11 as a consequence of serpentinization processes. The water chemistry denotes water/rock interactions with either magmatic or carbonatic rocks in a water reservoir equilibrated at temperatures estimated to be in the range of 58-162 °C. The stable isotope composition of …
Density Functional Theory Calculations Of Equilibrium Oxygen Isotope Fractionation Between Borate Minerals And Aqueous Fluids, Hai-Zhen Wei, Martin Palmer, Jun-Lin Wang, Shao-Yong Jiang, Simon V. Hohl, Yuan-Feng Zhu, Chun Huan, Miao-Miao Zhang, Yeşi̇m Yücel Öztürk
Density Functional Theory Calculations Of Equilibrium Oxygen Isotope Fractionation Between Borate Minerals And Aqueous Fluids, Hai-Zhen Wei, Martin Palmer, Jun-Lin Wang, Shao-Yong Jiang, Simon V. Hohl, Yuan-Feng Zhu, Chun Huan, Miao-Miao Zhang, Yeşi̇m Yücel Öztürk
Turkish Journal of Earth Sciences
Borax, ulexite, and colemanite minerals are by far the most important economic source of boron and occur almost exclusively in nonmarine evaporite deposits. While much is known about the geological setting in which they are found, surprisingly little is known about the chemical and physical properties of the brines from which they are formed. Oxygen isotope studies have the potential to reveal important new information regarding borate formation, but unlike most other common oxygen-bearing salts precipitated from brines, there are no experimental data regarding the oxygen isotope fractionation factors between borates and brines. As a first attempt to address this …
A Review Of The Geothermal System Evolution And Distribution In The Central Anatolian Crystalline Complex (Türkiye), Mehmet Furkan Şener, Muhammed Zeynel Öztürk, Alper Baba
A Review Of The Geothermal System Evolution And Distribution In The Central Anatolian Crystalline Complex (Türkiye), Mehmet Furkan Şener, Muhammed Zeynel Öztürk, Alper Baba
Turkish Journal of Earth Sciences
Türkiye is located in the Mediterranean sector of the Alpine-Himalayan tectonic belt and is among the foremost seven countries in the world having an abundance of geothermal resources. The Central Anatolian Crystalline Complex (CACC) is one of the most important geothermal regions in Türkiye. This study aims to evaluate the geothermal system of CACC using the geological, structural, and hydrogeochemical properties that were obtained from previous studies. The present study investigated and evaluated the hydrogeochemical and isotopic properties of 762 water samples belonging to 45 different localities from 41 scientific studies. The result shows that CACC has different heat sources …
Dynamics Of A Giant Slow Landslide Complex Along The Coast Of The Aral Sea, Central Asia, Gökhan Aslan, Marcello De Michele, Daniel Raucoules, François Renard, John Dehls, Ivanna Penna, Reginald Hermanns, Zi̇yadi̇n Çakir
Dynamics Of A Giant Slow Landslide Complex Along The Coast Of The Aral Sea, Central Asia, Gökhan Aslan, Marcello De Michele, Daniel Raucoules, François Renard, John Dehls, Ivanna Penna, Reginald Hermanns, Zi̇yadi̇n Çakir
Turkish Journal of Earth Sciences
We report here a slow-moving landslide complex of the lateral spreading type revealed by Sentinel-1 interferometric timeseries analysis. Located along the western coast of the Aral Sea, with a >150-km length and 3-km width, a giant active landslide complex, slides with a constant velocity of up to 60 mm/year. Systematic subsidence up to 5 mm/year is also observed along narrow strips of terraces that appear to result from rotations of fault-bounded blocks. The landslide deformation velocity does not correlate with the annual variations of the water level in the southwestern lake of the Aral Sea during the observation period of …
Mineralogical-Petrographical Features, Geochemical Characteristics, And S Isotope Variability Of Pb-Zn Deposits In The Sakarya Fragment Of The Biga Peninsula (Nw Türkiye), Gökhan Demi̇rela, Si̇nan Akiska, Eli̇f Akiska
Mineralogical-Petrographical Features, Geochemical Characteristics, And S Isotope Variability Of Pb-Zn Deposits In The Sakarya Fragment Of The Biga Peninsula (Nw Türkiye), Gökhan Demi̇rela, Si̇nan Akiska, Eli̇f Akiska
Turkish Journal of Earth Sciences
The Biga Peninsula in northwestern Anatolia, a part of the Alpine-Himalayan orogenic belt, has a complex geology that was formed following the closure of the northern branch of the Neotethys. Intense volcanism and plutonism in the area from the Eocene to the Middle Miocene period caused several Pb-Zn-Cu±Ag±Au deposits to form. The geometry of the mineralizations is largely made up of polymetallic veins, manto-chimneys, and irregular replacement bodies. Ore-bearing and host rocks in the mineralization zones and the wall rocks outside the mineralization zones were compiled in this study. The most common minerals in the skarn zones are garnet, pyroxene, …