Log Volume Research Articles

Characterization and Yield of Eucalyptus regnans F. Muell Logs for Lumber Production

The yield of Eucalyptus regnans logs for lumber production was evaluated. Crack width and length at each log end were measured. Two log-cutting plans were used to obtain sawn lumber. The first plan (PA) considered logs with diameters varying from 28 to 40 cm, and in the second plan (PB), the log diameters ranged from 42 to 56 cm (PB). Lumber yield was determined using two log volume methods: the Japanese Agricultural Standards (JAS) and Smalian’s equation. The deformations of E. regnans lumber were measured. The Australian and Chilean standards were used to classify sawn lumber. The results showed that logs had radial cracks at both log ends. Cracks were classified into two groups, considering the crack length. Regarding the lumber deformations, most boards exhibited level B bows and crooks in both cutting plans. Levels A and B twists were prevalent in PA, whereas in PB, level A significantly outnumbered level B. The lumber yield of E. regnans in PB was higher than in PA. The lumber yield determined by Smalian’s equation was higher than that determined by the JAS method. This research provides insight into the characterization of E. regnans for lumber production, highlighting its relevance in the forestry industry.

Timber Production Opportunities from Private Native Forests in Southern Queensland

Historically, Queensland’s private native forests have supplied between 40 and 70% of the hardwood resource to the state’s primary processors. Hardwood timber production from state-owned native forests and plantations in Queensland has decreased substantially in recent decades, increasing the hardwood timber industry’s reliance on private native forests. However, timber production opportunities from these forests are poorly understood. This study assessed the future wood supply capacity from private native forests in southern Queensland assuming alternative levels of landowner interest in management for timber production and willingness to invest in silvicultural treatment. Commercial and harvestable private native forests in southern Queensland were classified into six forest types and their spatial distributions were assessed. Potential growth rates for each forest type were estimated based on available literature and expert opinion, and their ability to supply logs to industry with and without silvicultural treatments was projected. Commercial and harvestable private native forests were found to cover an area of approximately 1.9 M ha in southern Queensland, of which spotted gum (693,000 ha) and ironbark (641,500 ha) forest types are most common. The private native forest estate is distributed over 17,665 landholdings (LotPlans), with 17% of these accounting for 66% of the commercial and harvestable resource. Most private native forests have not been actively managed for timber production and are in poor condition. Nevertheless, they presently have the potential to supply between about 150,000 and 250,000 m3 of logs to industry per annum. Silvicultural treatments were found to have the potential to increase the mean annual increment of these forests by a factor of between two and four, indicating substantial opportunities to increase harvestable log volumes in the medium and long-term. Private native forests in southern Queensland could potentially more than compensate for the supply gap left by the declining area of state-owned native forests that are available for timber harvesting. Actual forest management performed and log volumes supplied to market will depend on the forest management decisions of thousands of individual landholders, which are influenced by their heterogeneous management objectives, the policy environment, perceptions of sovereign risk, timber markets and the long payback periods in forestry. An accommodating forest policy environment and landholder willingness to invest in forest management could maintain and potentially increase private hardwood log supply to industry, which would support farm income diversification and regional employment opportunities.

NIMG-38. TUMOR VOLUME GROWTH RATES AND DOUBLING TIMES DURING ACTIVE SURVEILLANCE OF IDH-MUTANT LOW-GRADE GLIOMA

Abstract PURPOSE Isocitrate-dehydrogenase-mutant (IDH-mt) gliomas are incurable primary brain tumors characterized by a slow-growing phase over several years followed by a rapid-growing malignant phase. We hypothesized that tumor volume growth rate (TVGR) on magnetic resonance imaging may act as an earlier measure of clinical benefit during the active surveillance period. METHODS We integrated 3-dimensional volumetric measurements with clinical, radiological, and molecular data in a retrospective cohort of IDH-mt gliomas that were observed after surgical resection in order to understand tumor growth kinetics and the impact of molecular genetics. RESULTS Using log-linear mixed modeling, the entire cohort (n=128) had a continuous %TVGR per 6 months of 10.46% (95% CI: [9.11%, 11.83%]) and a doubling time of 3.5 years (95% CI: [3.10-3.98]). High molecular grade IDH-mt gliomas, defined by the presence of homozygous deletion of CDKN2A/B, had %TVGR per 6 months of 19.17% (95% CI: [15.57%, 22.89%]) which was significantly different from low molecular grade IDH-mt gliomas with a growth rate per 6 months of 9.54% (95% CI: [7.32%, 11.80%]) (P < 0.0001). Using joint modeling to co-model the longitudinal course of TVGR and overall survival, we found each unit increase in log volume resulted in more than a 3-fold increase in risk of death (HR=3.83, 95% CI: [2.32-6.30], P < 0.0001). CONCLUSIONS TVGR may be used as an earlier measure of clinical benefit and correlates well with the WHO 2021 molecular classification of gliomas and survival. Incorporation of TVGR as a surrogate endpoint into future prospective studies of IDH-mt gliomas may accelerate drug development.

Terrestrial vs. UAV-Based Remote Measurements in Log Volume Estimation

This study compared oak butt-log volume estimations gained through terrestrial measurements in the forest stand with a remote approach using an unmanned aerial system (UAS) and photogrammetric post-processing. Terrestrial measurements were conducted in the lowland part of Croatia after a completed motor–manual final felling of a 140-year-old even-aged oak stand. Butt-logs’ volumes were estimated with four methods: the sectioning method and Huber’s, Smailan’s and Riecke–Newton’s methods. Measuring diameters and lengths and estimating volumes remotely were based on orthophotos using four different software: ArcGIS, QGIS, AutoCAD and Pix4D. Riecke–Newton’s method for volume estimation had the smallest relative bias of +1.74%, while for Huber’s method it was −8.07% and with Smailan’s method it was +21.23%. Log volume estimations gained remotely via ArcGIS and QGIS were, in the case of Huber’s method, at +3.63% relative bias, and in the case of Riecke–Newton’s method at +1.39% relative bias. Volume estimation using the sectioning method resulted in a total of 51.334 m3 for the whole sample, while the sectioning method performed with the help of AutoCAD resulted in 55.151 m3, i.e., +7.43% relative bias. Volume estimation of thirty oak butt-logs given by Pix4D software (version 4.8.4) resulted in +9.34% relative bias (56.134 m3). Comparing terrestrial measurements and the volume estimations based on them to those gained remotely showed a very high correlation in all cases. This study showed that using a UAS for log volume estimation surveys has the potential for broader use, especially after final felling in even-aged forests where the remaining trees in the stand would not block photogrammetric analysis.

Economic losses caused by butt rot in Norway spruce trees in Norway

ABSTRACT Butt rot is a main defect in Norway spruce (Picea abies (L.) Karst.) trees and causes large economic losses for forest owners. However, little empirical research has been done on the effects of butt rot on harvested roundwood and the magnitude of the resulting economic losses. The main objective of this study was to characterize the direct economic losses caused by butt rot in Norway spruce trees for Norwegian forest owners. We used data obtained from seven cut-to-length harvesters, comprising ∼400,000 trees (∼140,000 m3) with corresponding stem profiles and wood grade information. We quantified the economic losses due to butt rot using bucking simulations, for which in a first case, defects caused by butt rot were included, and in a second case, all trees were assumed to be free of butt rot. 16% of trees were affected by butt rot, whereby butt rot tended to occur in larger trees. When butt rot was present in a tree, the saw log volume was reduced by 48%. Proportions of roundwood volume affected by butt rot varied considerably across harvested stands. Our results suggest that butt rot causes economic losses upwards of 7% of wood revenues, corresponding to € 18.5 million annually in Norway.

Flexible barrier and flow-driven woody debris: an experimental investigation of their interaction

Flexible barriers have been recently proposed as a promising alternative for trapping woody debris driven by the flow in torrents and rivers before they reach elements at risks. Small-scale experiments in similitude with the real-scale have been conducted in view of addressing the interaction between the flow and the barrier. A particular attention was paid to the identification of the parameters with influence on the loading experienced by the barrier, varying the woody debris mixtures characteristics, water discharge, flume inclination and woody debris supply mode. This investigation emphasised the intricacy of the relation between the barrier loading and the characteristics of the trapped logs and of the logs accumulation. The barrier loading revealed inversely proportional to the woody debris accumulation permittivity, which quantifies its capacity to let the water seep through. Permittivity depended on the way the accumulation built up and on the evolution of its characteristics with increasing discharge and trapped logs volume. Finally, the loading exerted by the flow on the barrier was derived from the barrier elongation, revealing that it could be modelled as a hydrostatic load with a reduction factor of 0.5.

LPV: A Log Parsing Framework Based on Vectorization

Logs are pervasive in modern computing systems, and are valuable to service and system management. Nevertheless, with the rapidly growing size and complexity of computing systems, the log volume is exploding, which makes automatic log analysis imperative. Generally, in automatic log analysis, the first and fundamental step is log parsing, to which a lot of effort has been devoted. However, in most existing log parsing methods, log messages are merely treated as plain text. In natural language processing (NLP) area, it is a common practice to represent words and sentences with vectors, then the similarity between two words or sentences can be measured by the distance between their vectors. Inspired by these, we put forward a novel log parsing framework, named LPV (Log Parser based on Vectorization), which performs log parsing by converting log messages and log templates into vectors, with the help of a vectorization method in NLP. LPV incorporates offline and online log parsing. In the offline log parsing, the central idea is to first represent log messages with vectors, so that the similarity between two log messages can be measured by the distance between their vectors, then we cluster log messages via clustering the vectors, and finally we extract log templates from the resultant clusters. By the end of the offline log parsing, each log template is assigned with an average vector, so that in the online log parsing, the similarity between an incoming log message and each log template can also be measured by the distance between their vectors. Extensive experiments have been conducted based on several public log datasets to evaluate LPV with three different vectorization methods. The results demonstrate that, with a proper vectorization method, LPV performs competitive with state-of-the-art log parsing methods, in both effectiveness and efficiency.

Brain: Log Parsing With Bidirectional Parallel Tree

Automated log analysis can facilitate failure diagnosis for developers and operators using a large volume of logs. Log parsing is a prerequisite step for automated log analysis, which parses semi-structured logs into structured logs. However, existing parsers are difficult to apply to software-intensive systems, due to their unstable parsing accuracy on various software. Although neural network-based approaches are stable, their inefficiency makes it challenging to keep up with the speed of log production.We found that a logging statement always generate the same template words, thus, the word with the most frequency in each log is more likely to be constant. However, the identical constant and variable generated from different logging statements may break this rule Inspired by this key insight, we propose a new stable log parsing approach, called Brain, which creates initial groups according to the longest common pattern. Then a bidirectional tree is used to hierarchically complement the constant words to the longest common pattern to form the complete log template efficiently. Experimental results on 16 benchmark datasets show that our approach outperforms the state-of-the-art parsers on two widely-used parsing accuracy metrics, and it only takes around 46 seconds to process one million lines of logs.

Trends in Changes in Forests and the Reforestation Fund of the Irkutsk Region

In Russia and the Irkutsk region, there are a number of problems associated with reforestation. The significance of the issue is increasing due to the increase in felling volumes, the deterioration of natural and anthropogenic factors, and the lack of funding. The purpose of this study is to identify the main trends in changes in forests and the reforestation fund of the Irkutsk region. The article contains data on changes in the area of forests and species composition in Russia and Irkutsk region for the period 2010–2021. The problem of reforestation in Russia, especially in Irkutsk region, is considered and compared with world trends. We analyzed the dynamics of areas of coniferous, soft-leaved and hard-leaved vegetation in the Russian Federation and Irkutsk region. The study showed that in the Irkutsk region there is a higher rate of deforestation than in Russia as a whole. The study showed that in the Irkutsk region there is a higher rate of deforestation than in Russia as a whole. An analysis of the state of forest lands on the territory of the Russian Federation and the Irkutsk region showed that there is a stable change in the species composition in the forests of our country, not for the better, and a decrease in the area covered with forest vegetation. An assessment of the change in the area of forest lands in the Irkutsk region revealed an imbalance between retired and incoming forest plantations, and this imbalance is increasing every year. To solve the problem of deforestation and the decline in the quality of the country's forests, it is necessary to carry out reforestation measures on the lost forest areas of previous years. A new formula for calculating the reforestation fund has been proposed and, based on it, the volumes of reforestation work have been calculated. The authors draw attention to the need to preserve forest resources and propose measures to increase the proportion of artificial reforestation to prevent further loss of forests and preserve their ecological function. Keywords. Dynamics of the reforestation fund, the forest fund of the Irkutsk region, the forest cover of the Irkutsk region, the area of forests, the volume of harvested timber, the volume of illegal logging, reforestation fund calculation.

The Effects of Forest Accessibility on the Quantitative and Qualitative Characteristics of Deadwood: A Comparison between Recreational and Natural Forests

Deadwood is one of the main structural features of forest ecosystems and plays an important role in the nutrient cycle, in maintaining production and environmental heterogeneity, and acts as an indicator for assessing the biodiversity of forest ecosystems. This research was conducted with the aim of evaluating the quantitative and qualitative characteristics of deadwood according to the influence of forest accessibility indicators in a comparison between natural and recreational forests. The studied area was divided into three accessibility classes based on the slope gradient range, the slope direction towards the nearest road, the road type, and distance from the road. These classes were: Easy-recreational forest (RE-F), Medium-natural forest 1 (NA-F1), and Difficult-natural forest 2 (NA-F2). In each accessibility class, three transects (750 × 50 m) were established, and three deadwood groups (snag, log, and stump) were recorded along the transects and their volume was calculated. The results of the analysis of variance show that accessibility has a significant effect on the presence of deadwood. The number and volume of snags, logs and dead stumps per hectare was higher in NA-F2 than in NA-F1 and RE-F. In each of the investigated classes, logs and stumps had the highest and the lowest number and volume of deadwood per hectare, respectively. The snag longevity index (= log volume/snag volume) decreased with accessibility. NA F2 showed the greatest value, while REF and NA F1 were not significantly different from each other. The results show that decay classes DC2 in NA-F2 and DC3 in NA-F1 and RE-F had the highest percentage of decay frequency. Finally, the forest accessibility indicators have a significant effect on the quantity, quality and distribution of different groups of deadwood in the forest. This is related to the collection of deadwood by local people who remove deadwood with different levels of intensity.

Evaluating Productivity of Small-Scale Cable Yarding System Integrated with a Portable Winch

Small-scale forestry operations, which are used in non-industrial and site specific forestry, provide alternative logging methods suitable for precision forestry approach. In this study, a small-scale cable yarding system integrated with a portable winch was considered as alternative timber extraction method compared to a standard tower yarder. It was aimed to evaluate productivity of this yarding method, which was implemented during commercial harvesting activities performed in a 10.74 ha black pine stand located in Bursa province of Turkey. The main factors (i.e. slope, yarding distance, lateral pulling distance, log volume, log length), significantly affecting the productivity, were evaluated based on two slope classes (34–50% and 50–70%) and two yarding distances (100 m and 200 m). The results indicated that the average productivity was 0.95 m3/PMH and 0.90 m3/SMH. It was revealed that the productivity of the small-scale cable yarding decreased as the ground slope and the yarding distance increased. Statistical analysis indicated that there was a significant (p<0.001) relationship between productivity and log volume and length in four applications. On the other hand, it was found that there was a significant (p<0.05) relationship between productivity and lateral pulling distance in only the first application (34–50% slope; 100 m yarding distance). Considering the volume classes of the logs, it was determined that the productivity increased from the low volume class to the high volume class.

Suitability of Various Volume Equations for Logs Volume Calculation

Suitability of Various Volume Equations for Logs Volume Calculation

LCHAIN: A Secure Log Storage Mechanism using IPFS and Blockchain Technology

Data security is a very important and crucial part of Cloud storage. Day by day, thousands of operations function over the Cloud, verify logs generated from all transactions is very difficult. The attacker may temper or remove targeted logs or attack traces on the system with stealthy techniques. It is required to maintain the security of the log to trace back all the transactions to identify such tempering and loss of logs. Temper-proof log storage is a challenging issue on the Cloud. To overcome the issue, we propose strong and secure log storage using Blockchain technology and IPFS. Detecting log tempering and tracing is challenging due to large log volumes. We recommend the usage of Blockchain technology due to its inherent feature of immutability to address the issue of log tempering. We present LChain which provides immutable storage of logs with tracing. Blockchain technology helps yp create immutable logs but also offers non-repudiation and scalability. Smart contracts are used for efficient searching and enhancing computational power.

The positive effect of the propaganda of family ethics and family education based on big data technology on the ideological work of youth

Abstract Big data technology is gaining a lot of attention and research in the present day. In this article, based on big data technology, we use Spark’s big data hybrid computing model to promote family style and family education under the premise of large-scale information processing. The minimum average distance of all clusters is calculated by computing the mean and eigenvectors of the Hopkins statistic. The cohesiveness and separation of the contour coefficients on the clusters were evaluated based on the mean values. We also examine the error-squared and criterion functions and use this method to verify the positive effect of promoting family traditions and education on the minds of young people. In this paper, we get from the comparison experiment of mining algorithms: Spark algorithm mining efficiency is 200-300 higher than MR algorithm mining efficiency, and the mining efficiency is superior. Especially when the log volume is large, the efficiency enhancement effect is as high as 96.88%, which is conducive to creating a good ideological and political education environment for young people by further improving the positive role of propagating family style and family education in the ideological and political education of young people.

Ultrasound Imaging Markers of Carotid Atherosclerosis are Associated with Cognition Through Cerebral Small Vessel Disease on MRI (S15.001)

Ultrasound Imaging Markers of Carotid Atherosclerosis are Associated with Cognition Through Cerebral Small Vessel Disease on MRI (S15.001)

Keloids, hypertrophic scars, and uterine fibroid development: a prospective ultrasound study of Black and African American women

To examine the association between keloids, hypertrophic scars, and uterine fibroid incidence as well as growth. Both keloids and fibroids are fibroproliferative conditions that have been reported to be more prevalent among Blacks than Whites, and they share similar fibrotic tissue structures, including extracellular matrix composition, gene expression, and protein profiles. We hypothesized that women with a history of keloids would have greater uterine fibroid development. A prospective community cohort study (enrollment 2010-2012) with 4 study visits over 5 years to conduct standardized ultrasounds to detect and measure fibroids ≥0.5 cm in diameter, assess the history of keloid and hypertrophic scars, and update covariates. Detroit, Michigan area. A total of 1,610 self-identified Black and/or African American women aged 23-35 years at enrollment without a previous clinical diagnosis of fibroids. Keloids (raised scars that grow beyond the margins of the original injury) and hypertrophic scars (raised scars that stay within the bounds of the original injury). Because of the difficulties in distinguishing keloids and hypertrophic scars, we separately examined the history of keloids and the history of either keloids or hypertrophic scars (any abnormal scarring) and their associations with fibroid incidence and growth. Fibroid incidence (new fibroid after a fibroid-free ultrasound at enrollment) was assessed using Cox proportional-hazards regression. Fibroid growth was assessed using linear mixed models. The estimates for the change in log volume per 18 months were converted to the estimated percentage difference in volume for scarring vs. no-scarring. Both incidence and growth models were adjusted for time-varying demographic, reproductive, and anthropometric factors. Of the 1,230 fibroid-free participants, 199 (16%) reported ever having keloids, 578 (47%) reported keloids or hypertrophic scars, and 293 (24%) developed incident fibroids. Neither keloids (adjusted hazard ratio = 1.04; 95% confidence interval: 0.77, 1.40) nor any abnormal scarring (adjusted hazard ratio = 1.10; 95% confidence interval: 0.88, 1.38) were associated with fibroid incidence. Fibroid growth differed little by scarring status. Despite molecular similarities, self-reported keloid and hypertrophic scars did not show an association with fibroid development. Future research may benefit from the examination of dermatologist-confirmed keloids or hypertrophic scars; however, our data suggest little shared susceptibility for these 2 types of fibrotic conditions.

Exploring Species Extraction Volume and Residues of Illegal and Conventional Logging Operations

Governments, policymakers, at most public fora, condemn activities of chainsaw operations as illegal and in fact, it has been criminalized with an explanation that it is wasteful and destructive to the environment. The study compared species, diameter distribution, extracted, volume, and residues generated during conventional and illegal logging operations in the forest communities. Using quantitative design approach, the researchers estimated the volume of waste generated by illegal logging and that of conventional loggers and also identified the species targeted. In order to determine the diameter distribution of exploited species, and the recovery rate of logs in both reserves, the researchers measured both ends, diameter, and length of stump wood and merchantable branch wood left as waste using the smallian's formula. The total volume of logs utilized per tree (logvol) was then calculated as the sum of the volume of each log. Twenty-five commercial timber species were identified to have been felled on farmlands compared to 34 commercial species which were felled in the TBFR. On both the farmlands and in the TBFR, the number of species felled by chainsaw operators far exceeded those felled by the conventional loggers. On farmlands, only four (17%) out of the 25 timber species were felled by conventional loggers. The most dominant timber species felled by the conventional loggers on farmlands was ceiba which comprised more than half (53%) of the total trees felled, followed by yaya (32%), watapuo (Cola gigantea), and akasaa (Chrysophyllum albidum). The study concluded that not only do chainsaw operators target a variety of lumber species but they also exploit timber species that are near extinction, therefore, making their activities pose danger to species diversity and conservation. The study proposed that strengthening the policy regime on compensation payment could help reduce the Incidence of illegal logging.

Excess Anisotropy: A Method to Predict Frequency of Resistive Fractures in the Wolfcamp Shale

A horizontal well in the Wolfcamp Formation within the Delaware Basin exhibits cross-dipole sonic log anisotropy varying from 0.0% to 29.7% over the reservoir interval. Massive limestones exhibit little anisotropy while shales and intervals with high fracture counts have high anisotropy. Integrated analysis of acoustic, image and triple combo open-hole log data indicates that the computed volume of shale log is a strong predictor of anisotropy with a simple linear relationship. However, there is much anisotropy that is not accounted for by this lithologically related linear relationship. We refer to the residual obtained by subtracting the predicted anisotropy using this relationship from the measured anisotropy from a cross-dipole sonic tool as the excess anisotropy. The excess anisotropy is the remaining anisotropy that is not accounted for by linear regression between the volume of shale log and the measured anisotropy. We find that the excess anisotropy is linearly correlated to the resistive fracture density. Linear regression between the two variables yields a statistically significant relationship that enables a rough estimation of the resistive fracture frequency from the excess anisotropy. Validation in a second well produces a similar correlation to fracture frequency.

Forest Resources Projection Tools: Comparison of Available Tools and Their Adaptation to Polish Conditions

Over the years, various methods for estimating and projecting forest resources have been developed and are used by countries where the forest sector is important. Therefore, the obligation to report and account for forest resources, including changes in carbon stocks in a forest area, has gained attention. The latest regulations (Land Use, Land Use Change and Forestry—LULUCF) requires European Union (EU) members to annually report and publish national accounting plans estimating emissions and removals from managed forest areas (Regulation EU 2018/841). The major challenge is to choose and adapt a unique tool for this accounting. At the same time, they need to provide reliable estimates that are recognized by regulators and control authorities. This study focuses on comparing the adaptation of two accounting frameworks: the Operational-Scale Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) and the European Forest Dynamics Model (EFDM). Both tools are based on National Forest Inventory (NFI) data. It is assumed that the EFDM can provide similar results to the CBM-CFS3, which is already used in Poland. Implementing the EFDM and adapting it to Polish conditions could facilitate forest management decision-making and the preparation of forest policies. The main objective of this study was to compare and validate the accuracy of the results obtained with the EFDM framework. Metrics compared using both tools included growing stock volume, biomass of growing stock expressed in carbon units and age–class distribution over area. The comparison was based on the agreement of EFDM with CBM-CFS3 results. The volume of logging was taken from the EFDM and compared with the values obtained by Statistics Poland. This study also provides a guide for framework parameterization directly from the Polish National Forest Inventory data from the 2010–2015 cycle. Our main findings are that the results of the two models are reasonably comparable (the extent of deviation is acceptable). Moreover, the first implementation of the EFDM showed that it is an easy-to-use open-source program that allows forest managers to implement their own settings according to their needs. This document elucidates the concept of using both frameworks under Polish conditions and provides an impression of their performance for future modelers, students and researchers.

Hybrid ML-Based Technique to Classify Malicious Activity Using Log Data of Systems

A computer system generates logs to record all relevant operational data about the system and all operations performed in such systems. System log examination is crucial in the identification of network- and system-level assaults. In comparison to established hazards, new technological advancements and better connections pose a greater degree of risk. Several machine learning algorithms that continually monitor logs of data have been created in the past to defend the system against many threats. The majority of earlier anomaly detection methods need a priori knowledge and are not intended for spotting recent or impending threats. Additionally, the growing volume of logs creates fresh difficulties for anomaly identification. In this study, we developed a machine learning technique that identifies abnormalities in the system log with higher accuracy and efficiency. In our suggested strategy, we started with three log features, preprocessed them, and then got more than 10 features for the model. We performed studies to test the effectiveness of our suggested approach, and the criteria for that included F1 scores, ROCs, accuracy, sensitivity, and specificity. We also evaluated how well our suggested technique performs in comparison to other methods. Our suggested solution has a greater rate of anomaly identification than any previously published algorithms as per the experimental findings based on the dataset obtained from the Blue Green/l supercomputer system.