Block Mapping Research Articles

Interpretability of operative and pathological reports for radiotherapy planning of sinonasal carcinomas: An ancillary study of the GORTEC 2016-02 SANTAL trial.

Interpretation of surgical mapping is essential for postoperative radiotherapy planning. Operative and pathological reports lack comprehensive information on margins quality and tissue block mapping. Standardizing reports is essential to reduce uncertainties, aiming for less morbid poRT.

TCBR and TCBD: Evaluation metrics for tamper coincidence problem in fragile image watermarking

This paper proposed two evaluation metrics of the tamper coincidence in a block map design for image watermarking. These evaluation metrics are called Tamper Coincidence Block Ratio (TCBR) and Tamper Coincidence Block Density (TCBD). A tamper coincidence occurred in image authentication and self-recovery when the recovery data and the original block location were tampered with simultaneously. A high tamper coincidence limits image inpainting’s capability to recover the region, leading to an imprecise recovered image. The ratio and density of the tamper coincidence may significantly affect the final recovered image quality. Previously, researchers mentioned the tamper coincidence in their experiment but did not evaluate it with any metrics. They evaluated the robustness of their technique based on the final recovered image quality using the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM). Tamper coincidences are primarily affected by the block map design implemented by the researcher. Thus, TCBR and TCBD provide valuable insight into the block map design’s effectiveness in preventing tamper coincidence. The experimental result shows that the TCBR and TCBD values are inversely proportional to the recovered image quality. A high TCBR and TCBD value leads to low recovered image quality. Therefore, this paper will help the researchers design an effective block map by minimizing the TCBR and TCBD values to obtain the highest recovered image quality.

Simulation and experimental study on contact pressure distribution of contact interface in single and double bolted connection structures

Bolted joints play an important role in aerospace, machinery manufacturing, weapons and other fields, and the contact pressure distribution at the connection interface seriously affects the service performance of the bolts. Contact pressure analysis is an essential basis and reference for structural design, calibration, inspection, and safety monitoring of bolted connection structures. Considering the preload force and frictional contact between the joint components, a block mapping hexahedron mesh generation and finite element modeling method for bolted connections is presented, and the finite element models of single and double bolted structures are constructed. Then, an experimental test platform for measuring contact pressure distribution is constructed. Comparison of finite element analysis results with experimental results for the contact pressure distribution in the single and double-bolted joints; the root mean squared error of contact pressure distribution is less than 5%, which verifies the effectiveness of the finite element models. After that, the models are used to study the contact pressure distribution in single-bolted joints and contact pressure coupling effect of double-bolted joints, and the normal stress distribution features within members and contact pressure distribution contour are revealed for single and double-bolted joint. Finally, the finite element models are adopted to investigate the effects of the clamping length, preload, material properties, hole clearance, and bolt size on contact pressure distribution in single-bolted joints. The coupling effect of contact pressure distribution in double-bolted joints under different preloads and geometric parameters are also examined.

Block mapping and dual-matrix-based watermarking for image authentication with self-recovery capability.

Numerous image authentication techniques have been devised to address the potential security issue of malicious tampering with image content since digital images can be easily duplicated, modified, transformed and diffused via the Internet transmission. However, the existing works still remain many shortcomings in terms of the recovery incapability and detection accuracy with extensive tampering. To improve the performance of tamper detection and image recovery, we present a block mapping and dual-matrix-based watermarking scheme for image authentication with self-recovery capability in this paper. The to-be-embedded watermark information is composed of the authentication data and recovery data. The Authentication Feature Composition Calculation algorithm is proposed to generate the authentication data for image tamper detection and localization. Furthermore, the recovery data for tampered region recovery is comprised of self-recovery bits and mapped-recovery bits. The Set Partition in Hierarchical Trees encoding algorithm is applied to obtain the self-recovery bits, whereas the Rehashing Model-based Block Mapping algorithm is proposed to obtain the mapped-recovery bits for retrieving the damaged codes caused by tampering. Subsequently, the watermark information is embedded into the original image as digital watermarking with the guidance of a dual-matrix. The experimental results demonstrate that comparing with other state-of-the-art works, our proposed scheme not only improves the performance in recovery, but also extends the limitation of tampering rate up to 90%. Furthermore, it obtains a desirable image quality above 40 dB, large watermark payload up to 3.169 bpp, and the effective resistance to malicious attack, such as copy-move and collage attacks.

Optimalisasi Penomoran Rumah Dan Kaveling Serta Pemetaan Blok Di RW 7 Wonorejo Rungkut Kota Surabaya

This community service activity discusses the problem of irregular house and plot numbering in RW 7 Wonorejo, Rungkut, Surabaya, which complicates the process of address finding by couriers and guests. The purpose of this service activity is to optimize the numbering and block mapping system to facilitate navigation and location identification. The methods used include aerial photography with drones, data processing with mapping and GIS software, discussions with the head of RW, as well as grouping and numbering of buildings. The result is the creation of a more accurate and detailed map, with systematic street naming and more orderly building numbering. The success of this activity is measured by the increase in efficiency in address finding and the satisfaction of residents with the new numbering system. However, there are weaknesses in the integration of the map with Google Maps and accessibility for all layers of society. The conclusion of this activity is the importance of integrating mapping technology in urban management, with recommendations for further integration with Google Maps and improving map accessibility for all layers of society. This activity demonstrates the great potential of mapping technology in improving navigation efficiency and urban community management.

COVID-19 infection analysis framework using novel boosted CNNs and radiological images

COVID-19, a novel pathogen that emerged in late 2019, has the potential to cause pneumonia with unique variants upon infection. Hence, the development of efficient diagnostic systems is crucial in accurately identifying infected patients and effectively mitigating the spread of the disease. However, the system poses several challenges because of the limited availability of labeled data, distortion, and complexity in image representation, as well as variations in contrast and texture. Therefore, a novel two-phase analysis framework has been developed to scrutinize the subtle irregularities associated with COVID-19 contamination. A new Convolutional Neural Network-based STM-BRNet is developed, which integrates the Split-Transform-Merge (STM) block and Feature map enrichment (FME) techniques in the first phase. The STM block captures boundary and regional-specific features essential for detecting COVID-19 infectious CT slices. Additionally, by incorporating the FME and Transfer Learning (TL) concept into the STM blocks, multiple enhanced channels are generated to effectively capture minute variations in illumination and texture specific to COVID-19-infected images. Additionally, residual multipath learning is used to improve the learning capacity of STM-BRNet and progressively increase the feature representation by boosting at a high level through TL. In the second phase of the analysis, the COVID-19 CT scans are processed using the newly developed SA-CB-BRSeg segmentation CNN to accurately delineate infection in the images. The SA-CB-BRSeg method utilizes a unique approach that combines smooth and heterogeneous processes in both the encoder and decoder. These operations are structured to effectively capture COVID-19 patterns, including region-homogenous, texture variation, and border. By incorporating these techniques, the SA-CB-BRSeg method demonstrates its ability to accurately analyze and segment COVID-19 related data. Furthermore, the SA-CB-BRSeg model incorporates the novel concept of CB in the decoder, where additional channels are combined using TL to enhance the learning of low contrast regions. The developed STM-BRNet and SA-CB-BRSeg models achieve impressive results, with an accuracy of 98.01%, recall of 98.12%, F-score of 98.11%, Dice Similarity of 96.396%, and IOU of 98.85%. The proposed framework will alleviate the workload and enhance the radiologist's decision-making capacity in identifying the infected region of COVID-19 and evaluating the severity stages of the disease.

A blind recovery technique with integer wavelet transforms in image watermarking

The development of internet technology has simplified the sharing and modification of digital image information. The aim of this study is to propose a new blind recovery technique based on integer wavelets transform (BRIWT) by utilizing their image content. The LSB adjustment technique on the integer wavelet transform is used to embed recovery data into the two least significant bits (LSB) of the image content. Authentication bits are embedded into the current locations of the LSB of the image content, while the recovery information is embedded into different block locations based on the proposed block mapping. The embedded recovery data is securely placed at random locations within the two LSBs using a secret key. A three-layer embedding of authentication bits is used to validate the integrity of the image contents, achieving high precision and accuracy. Tamper localization accuracy is employed to identify recovery bits from the image content. This research also investigates the image inpainting method to enhance recovery from tampered images. The proposed image inpainting is performed by identifying non-tampered pixels in the surrounding tamper localization. The results demonstrate that the proposed scheme can produce highly watermarked images with imperceptibility, with an average SSIM value of 0.9978 and a PSNR value of 46.20 dB. The proposed scheme significantly improves the accuracy of tamper localization, with a precision of 0.9943 and an accuracy of 0.9971. The proposed recovery technique using integer wavelet transforms achieves high-quality blind recovery with an SSIM value of 0.9934 under a tampering rate of 10%. The findings of this study reveal that the proposed scheme improves the quality of blind recovery by 14.2 % under a tampering rate of 80 %.

Diagnostic criteria for proximal left bundle branch block and their significance in predicting the success of cardiac resynchronization therapy

Aim. To develop diagnostic criteria for proximal left bundle branch block (LBBB) based on non-invasive methods and to determine the significance of these criteria in predicting the effect of cardiac resynchronization therapy (CRT).Material and methods. To develop criteria, 58 patients (21 men, mean age, 76,1±7,1 years) with LBBB occurred immediately after transcatheter aortic valve implantation (TAVI) were included. To assess the significance of the developed criteria, the second group included 22 patients (11 men, mean age, 57,9±9,3 years) with dilated cardiomyopathy (DCM), who had indications for CRT. The effectiveness of CRT was assessed by echocardiography 6 months after implantation. All patients in the DCM group and 15 patients in the TAVI group underwent superficial epiand endocardial non-invasive mapping using Amycard 01C EP Lab (EP Solutions SA, Switzerland). Patients in the DCM group underwent contrast-enhanced cardiac magnetic resonance imaging (MRI) before device implantation.Results. The criteria for proximal LBBB included 3 electrocardiographic features: QRS complex >130 ms in women and 140 ms in men, QSor rS-configuration in V1 lead, notch in two or more lateral leads (I, avL, V5, V6), and 2 mapping criteria: characteristic location of block line and delayed activation point. In the DCM group, the criteria were positive in 13 of 22 patients (59%). The developed criteria for proximal LBBB showed a relatively strong, significant relationship with the positive effect of CRT (сhi-square test =5,46, p=0,02, Cramer test =0,5, odds ratio (OR)=15,0, 95% confidence interval (CI), 1,32-169,9, p=0,002). An additional analysis showed that both the criteria for proximal block and CRT effect are associated with myocardial fibrosis according to MRI. In particular, intramural stria-shaped contrast accumulation in the interventricular septum leads to a change in characteristic of proximal block mapping phenomena — displacement of delayed activation point (chi-square test =13,9, p<0,001, Cramer test =0,79) and displacement or absence of conduction block lines (chi-square test =6,92, p=0,009, Cramer test =0,56) and prevents the CRT effect (OR =8,67, 95% CI, 1,05-71,57 p=0,03).Conclusion. Proximal LBBB is only one of the factors determining the effectiveness of CRT. Proximal LBBB may mask significant myocardial structural changes that prevent the CRT success.

AuSR3: A new block mapping technique for image authentication and self-recovery to avoid the tamper coincidence problem

This paper proposes a new block mapping technique for image authentication and self-recovery designed to avoid the tamper coincidence problem called the AuSR3. The tamper coincidence problem can arise when modifications to an image affect the original block and its recovery data, resulting in the inability to recover the tampered region of the image. The new block mapping technique ensures that the recovery data of a block is embedded into the most distant location possible, minimizing the tamper coincidence problem. In addition, the improved LSB shifting algorithm is employed to embed the watermark data consisting of authentication and recovery data. The experimental result shows that the AuSR3 can produce high-quality watermarked images across various datasets with average PSNR values of 46.2 dB, which improved by 2.1 dB compared to the LSB replacement technique. The new block mapping technique avoids the tamper coincidence problem by up to 25% tampering rates. It contributes to the high-quality recovered image with a PSNR and SSIM value of 39.10 dB and 0.9944, respectively, on a 10% tampering rate on the USC-SIPI dataset.

Petrov–Galerkin zonal free element method for 2D and 3D mechanical problems

AbstractIn this article, a novel weak‐form zonal Petrov–Galerkin free element method is proposed for two‐ and three‐dimensional linear mechanical problems. By absorbing the advantages of finite block method and strong‐form finite element method, the block mapping technique is used in the free element method. Combining the characteristics of the meshless local Petrov–Galerkin method, the local Petrov–Galerkin formulation based on the zonal free element method is formed at last. Besides, the local integral domain selected in the local collocation element is circular or spherical to simplify programming. The transformation of the local integral domain between the physical and normalized spaces is given for two‐ and three‐dimensional problems. The comparison of accuracy and convergence between the new proposed Petrov–Galerkin method and the conventional methods is carried out. Some challenging examples including fracture mechanics problems and a complex 3D problem are given to validate the convergence and accuracy of the proposed method.

GRONDKAART LEGALITY AS EVIDENCE OF LAND TENURE RIGHTS BY PT. KAI ACCORDING TO AGRARIAN LAW

Grondkaart or block maps are documents that prove the ownership of assets which are wealth for an institution or company that must be maintained. There are several things that are still being debated regarding the position or legality of Grondkaart itself. One state company that still uses Grondkaart as proof of ownership of its land assets is PT. Kereta Api Indonesia (Persero) or PT. KAI. Land assets PT. KAI is a legacy of the Dutch railroad company which was subject to nationalization, the land often causes disputes due to evidence of land tenure in the form of Grondkaart which is not regulated in Law Number 5 of 1960 and Government Regulation Number 24 of 1997. The formulation of the problem in this article is (1) What is the position of Grondkaart as a basis for rights or evidence of land tenure according to Indonesian Agrarian Law? (2) How is the legal protection and legal certainty of Grondkaart as proof of land ownership by PT KAI so that it can provide a solution to land problems for the residents of Miji Mojokerto? The research method used in this article is the normative legal research method with statutory, conceptual and case approaches. The technique used in the analysis of legal material is to use grammatical interpretation and systematic interpretation. The results showed that Grondkaart's position was not regulated in Law No. 5 of 1960 concerning Basic Agrarian Regulations and Government Regulation No. 10 of 1960 Jo. Government Regulation Number 24 of 1997 concerning Land Registration, this has resulted in that Grondkaart is not a strong proof of ownership of railway land, but can be used as a basis for ownership or as the basis for PT. Kereta Api Indonesia (Persero) to register their land in order to obtain a strong Certificate of Land Rights. Grondkaart is proof of PT KAI's land ownership which if in the process of securing assets a dispute occurs it can be used as proof of ownership where rights have never been renewed.

Fast characterization of nonlinear feasible region based on deep neural network association mining

Dispatches of tie-line power between regional grids promote the use of natural resources. Therefore, the exact characterization of nonlinear tie-line feasible region becomes an important guarantee to ensure the power interaction. However, solving nonlinear problems using traditional methods usually requires a solver with powerful computational capabilities. We herein propose a feature association mining for nonlinear constraints and feasible region boundary to directly identify the boundary points with deep neural network (DNN) assisted prediction, which divides the identification of feasible region into two stages. Firstly, the cardinal decision variables are identified using the DNN to alleviate the numerical annihilation problem. Secondly, under the guidance of the characteristics of the description results, the association between the input constraints and the output feasible region is obtained and the block feature library of the sample data is constructed to reduce the learning difficulty. Finally, the block mapping of some key decision variables is completed. In the second stage, some cardinal decision variables are used as indicators to straightly locate the points. Moreover, a round of accuracy rectification is carried out using segment translation method and the results are corrected for ensuring the accuracy. Case studies demonstrate the effectiveness of the proposed methods.

Efficient Spectral Graph Convolutional Network Deployment on Memristive Crossbars

Graph Neural Networks (GNNs) have attracted increasing research interest for their remarkable capability to model graph-structured knowledge. However, GNNs suffer from intensive data exchange and poor data locality, which will cause critical performance and energy bottlenecks under conventional complementary metal oxide semiconductor (CMOS)-based von-Neumann computing architectures (graphics processing unit (GPU), central processing unit (CPU)) for the “Memory Wall” issue. Fortunately, memristive crossbar-based computation has emerged as one of the most promising neuromorphic computing architectures, which has been widely studied as the computing platform for convolutional neural network (CNNs), recurrent neural network (RNNs), spiking neural network (SNNs), etc. This paper proposes the deployment of spectral graph convolutional networks (GCNs) on memristive crossbars. Further, based on the structure of GCNs (extremely high sparsity and unbalanced non-zero data distribution) and the neuromorphic characteristics of memristive crossbar circuit, we propose the acceleration method that consists of Sparse Laplace Matrix Reordering and Diagonal Block Matrix Multiplication. The simulated experiment on memristor crossbars achieves 90.3% overall accuracy on the supervised learning graph dataset (QM7), and compared with the original computation, the proposed acceleration computing framework (with half-size diagonal blocks) achieves a 27.3% reduction of memristor number. Additionally, on the unsupervised learning dataset (Karate club), our method shows no loss of accuracy with half-size diagonal block mapping and reaches a 32.2% reduction of memristor number.

On von Neumann regularity of cellular automata

We show that a cellular automaton on a one-dimensional two-sided mixing subshift of finite type is a von Neumann regular element in the semigroup of cellular automata if and only if it is split epic onto its image in the category of sofic shifts and block maps. It follows from previous joint work of the author and Törmä that von Neumann regularity is a decidable condition, and we decide it for all elementary CA, obtaining the optimal radii for weak generalized inverses. Two sufficient conditions for non-regularity are having a proper sofic image or having a point in the image with no preimage of the same period. We show that the non-regular ECA 9 and 28 cannot be proven non-regular using these methods. We also show that a random cellular automaton is non-regular with high probability.

Прямой метод вычисления циклов ячеек карты блока простого планарного графа

The proposed algorithm for calculating the cycles of the cells the simple planar graph block map is an extension of the classical depth-first search algorithm for cycles of the DFS-basis. The key idea of the modification of this algorithm is the strategy of right-hand traversal when passing the graph in depth. The vertex with the minimum coordinate on the OY axis is assigned as the starting vertex in the right-hand traversal. The exit from the initial vertex is performed along the edge with the minimum polar angle. The continuation of the traversal from each next vertex is carried out along an edge with a minimum polar angle relative to the edge along which arrived at the current vertex. A two-level structure of nested cycles is introduced. This is the main level and the zero level of nesting. All cycles of the basis belong to the main level. Each of the cycles can additionally have a zero level of nesting in another main cycle for it, if it is nested in the main cycle and not nested in any other cycle from the main cycle. With the right-hand traversal, zero nesting cycles are adjacent to the main cycle and do not have common vertices outside the main cycle. These two properties allowed in each basis cycle sequentially select and exclude from it all its zero nesting cycles, using the symmetric difference operation. It is shown that the rest of the basic cycle is the cycle of the block map cell. The complexity of each step of the proposed algorithm does not exceed the quadratic complexity with respect to the number of vertices of the simple planar graph.

Utilization of drone for reclamation at the Batu Ampar block PT Timah Tbk

The Batu Ampar block is one of the ex-mining blocks in Bangka Regency where land revegetation has been carried out in 2019 and 2020. Observation of land realization is carried out by testing the accuracy of mapping using a base map from drone data and the success of the canopy cover level in accordance with the accuracy of the classification of the base map based on Regulations Head of the Geospatial Information Agency Number 15/2014. The results of processing and analysis show that the CE90 and LE90 accuracy test values for drone data geometry are 0.44 m and 0.86 m for the GCP georeference is said to be in class 3 on a scale of 1:2500 and class 1 on a scale of 1:5000. In the process without GCP georeference, the CE90 and LE90 values of 8.5 m and 6.8 m do not correspond to any class on the ideal scale for the layout of the Batu Ampar reclamation block mapping.

De novo genome assembly of rice bean (Vigna umbellata) - A nominated nutritionally rich future crop reveals novel insights into flowering potential, habit, and palatability centric - traits for efficient domestication.

Rice bean is a less-known underutilized legume crop with a high nutritional value among members of the Vigna family. As an initiative to compose rice bean (Vigna umbellata) genomic resource, the size of 414 mega-base pairs with an estimated identification of 31,276 high confidence index genes via 15,521 scaffolds generated from Illumina and PacBio platform 30X coverage data has achieved 96.08% functional coverage data from Illumina and PacBio platform. Rice bean genome assembly was found to be exquisitely close to Vigna angularis (experimental control/outgroup), Vigna radiata, and Vigna unguiculata, however, Vigna angularis being the closest. The assembled genome was further aligned with 31 leguminous plants (13 complete genomes and 18 partial genomes), by collinearity block mapping. Further, we predicted similar discriminant results by complete coding sequence (CDS) alignment. In contrast, 17 medically influential genomes from the National Institute of General Medical Sciences-National Institutes of Health NIGMS-NIH, when compared to rice bean assembly for LCB clusters, led to the identification of more than 18,000 genes from the entire selected medicinal genomes. Empirical construction of all genome comparisons revealed symplesiomorphic character in turn uncovering the lineage of genetic and functional features of rice beans. Significantly, we found deserving late-flowering genes, palatably indexed uncommon genes that regulate various metabolite pathways, related to abiotic and biotic stress pathways and those that are specific to photoperiod and disease resistance and so on. Therefore, the findings from this report address the genomic value of rice bean to be escalated via breeding by allied and applied approaches.

Analgesic efficacy of superficial versus deep serratus plane block for modified radical mastectomy under general anaesthesia: A randomised comparative study.

Serratus anterior plane (SAP) blocks can be given either superficial or deep to the serratus anterior muscle to block the branches of intercostal nerves providing analgesia to the anterolateral chest wall. This prospective randomised comparative study aimed to compare the analgesic efficacy of superficial and deep SAP block in breast surgeries. Forty female patients scheduled to undergo elective modified radical mastectomy under general anaesthesia (GA) were randomly assigned to receive ultrasound guided SAP block with 30 ml 0.375% ropivacaine either superficial (group S, n = 20) or deep (group D, n = 20) to the serratus anterior muscle, before the induction of GA. The primary outcome was post operative fentanyl requirement over 24 hours and secondary outcomes were comparison of numerical rating scale (NRS) scores for pain, sensory block mapping, time to perform the block, number of needle attempts, etc. The post operative 24-hour fentanyl requirement was comparable between group S and D (318.75 ± 80.65 versus 272.5 ± 80.25 μg, P = 0.07). NRS pain scores were comparable between the groups. Sensory block mapping done at various levels showed T3-T7 block in most of the patients with no difference between the groups. Block performance time (6.05 ± 3.27 versus 8.35 ± 3.26 minutes, P = 0.034) and number of needle attempts was significantly lesser in group D. There was no difference in analgesic efficacy when SAP block was given superficial or deep to serratus anterior muscle for modified radical mastectomies. However, deep SAP block required less time and number of attempts to perform than superficial technique.

Utilization of unmanned aerial vehicles for zonal winemaking in cool-climate Riesling vineyards

Individual vineyards can vary spatially for several viticultural attributes, including water stress, nutrient status, growth/vigour and disease—which can, in turn, impact berry composition and resulting wine products. The goal of this study was to determine if vineyard variability detected by remote sensing using an unmanned aerial vehicle (UAV) could be used to zonally harvest vineyard blocks and produce wines that are sensorially differentiable. The specific hypothesis was that remote sensing would detect vineyard variation in viticultural variables and associate this variation with differences in wine sensory attributes based upon zonal harvesting. In six commercial Riesling vineyards across the Niagara Peninsula in Ontario, Canada, a UAV collected multispectral data, which were used to calculate the normalized difference vegetation index (NDVI). Grapevines (≈ 80) in a grid pattern were geo-located within each block and vineyard UAV NDVI maps were used for zonal harvesting of geo-located vines in areas corresponding to high vs. low NDVI. Wines made from these zones were then compared chemically and sensorially. Overall, wines created from high vs. low NDVI zones differed inconsistently in their basic wine composition. Sensorially, for certain sites and vintages, panellists distinguished between wines made from high vs. low NDVI zones using a sorting task. UAV NDVI demonstrated the ability to determine areas within a vineyard block that could produce wines that were sensorially distinguishable from one another.

Enhanced lithological mapping of Durba-Araba basement blocks, along the eastern margin of the Central Gulf of Suez Rift, Egypt, using Landsat-8 Data

The eastern margin of the central Gulf of Suez rift exposes unique rotated basement blocks of Gabal Durba-Araba. According to geological maps, these blocks are composed of Dokhan volcanic, older, and younger granites cut by basaltic dikes and overlayed by a tilted sedimentary succession of Paleozoic to quaternary. Herein, we propose a workflow of stepwise preprocessing and classification procedures for Landsat-8 (OLI) data verified by control points from previous maps to update and improve lithological discrimination in converging areas that require further field mapping. The workflow applies digital image-processing techniques, including spectral signature analysis, band-ratio transformation, maximum likelihood, and Mahalanobis supervised classifications. The accuracy assessment of the lithological mapping reaches 86.6% and 75.7% for maximum likelihood and Mahalanobis classifications, respectively. By running the Tactical Hyperspectral Operations Resource (THOR) algorithm on the classified images, we could accurately map and modify the lithological boundaries for the following rock units: (1) gneiss-amphibolite-schist, tonalite, and granodiorite at Gabal Araba; (2) granitic gneiss, granodiorite, biotite-muscovite-leucogranite, and riebeckite-syenite-albitite at Gabal Abu Haswa; (3) Dokhan volcanic, granite biotite-muscovite-leucogranite, granites riebeckite-syenite-albitite, Pyroclastic breccia and lava flow, and NW tertiary dike at Gabal Abu Durba.