FR Method Research Articles

Flood vulnerability map of the Bagmati River basin, Nepal: a comparative approach of the analytical hierarchy process and frequency ratio model

AbstractThe analytical hierarchy process (AHP) and frequency ratio model (FR), along with the integration of GIS, have proven to be successful approaches for assessing flood-prone areas. However, in Nepal flood vulnerability mapping based on GIS decision analysis is limited. Thus, this study focused on comparing the data-driven FR method and expert knowledge-based AHP technique in a GIS environment to prepare a flood vulnerability map for the Bagmati River basin, helping to explore the gap in flood vulnerability mapping methodologies and approaches. By combining all class-weighted contributing factors, like elevation, precipitation, flow accumulation, drainage density, soil, distance from the river, land use land cover, normalized difference vegetative index, slope and topographic wetness index, the study evaluated the efficiency of FR and AHP in assessing flood vulnerability maps. An inventory map of floods containing 107 flood points was created. Subsequently, the flood vulnerability maps generated using FR and AHP models revealed that 9.30% and 11.36% of regions were in highly vulnerable areas, respectively. Receiver operating characteristics validated the model outcomes, indicating that the FR model’s accuracy of 91% outperformed the AHP model’s 84% accuracy. The study findings will assist decision-makers in enacting sustainable management techniques to reduce future damage in the Bagmati basin.

Landslide Susceptibility Mapping with GIS in Nagi Dada Area of Panauti Municipality, Kavrepalanchwok District: A Comparison Between AHP and FR Method

Landslide Susceptibility Mapping with GIS in Nagi Dada Area of Panauti Municipality, Kavrepalanchwok District: A Comparison Between AHP and FR Method

Hybrid Fuzzy AHP and Frequency Ratio Methods for Assessing Flood Susceptibility in Bayech Basin, Southwestern Tunisia

Flash floods are a significant threat to arid and semi-arid regions, causing considerable loss of life and damage, including roads, bridges, check dams and dikes, reservoir filling, and mudslides in populated areas as well as agricultural fields. Flood risk is a complex process linked to numerous morphological, pedological, geological, anthropic, and climatic factors. In arid environments such as where Bayech basin is located in southwestern Tunisia, the hydrometric data are insufficient due to the absence of measuring points. Using the hybrid fuzzy Analytical Hierarchy Process (F-AHP) and the frequency ratio statistical methods, this study aims to map flooding risks in an ungauged basin that is extremely prone to flooding. Data related to soil texture, slope, land use, altitude, rainfall, drainage density, and distance from the river were used in the risk analysis. The obtained flood risk maps from both F-AHP and FR models were validated on the basis of the Receiver Operating Characteristic (ROC), the Area Under the Curve (AUC), and the inventory map. Results revealed that areas of high and very high susceptibility to flooding are mainly located in the downstream part of the basin, where the town of Gafsa is located. Other upstream sites are also at risk. In this basin, slope is predominantly behind runoff accumulation, whereas soil type plays a major role in amplifying waterproofing and therefore overflow. The results derived from both methods clearly demonstrate a viable and efficient assessment in flood-prone areas. The F-AHP and FR methods have ROC values of 95% and 97%, respectively. Considering these results in the decision-making process, these outputs would enable the implementation of the necessary measures to mitigate flood risk impacts ensure sustainable development along with an effective management in Tunisian arid environments, for the well-being of local communities at risk.

Insights into co-pyrolytic behavior, emission, kinetics, synergy of bio-oil distillation residue and waxy product via TG-FTIR-MS

The technology pathways are maturing in the treatment of carbonaceous solid waste, however, there will inevitably be low value by-products downstream, which requires fine management. Herein, bio-oil distillation residue (DR) and waxy product (WP) as by-products contained considerable energy and chemical composition, and their similar thermogravimetric properties enable efficient synergy during co-pyrolysis. The emission decomposition kinetics, thermodynamics and synergy of DR co-pyrolysis with WP were investigated by TG-FTIR-MS. Thermal process of DR and WP occurred at 175.7–539.1 ℃ and 108.9–427.3 ℃. As the DR content increased, the absorption peak intensity of hydrocarbons was decreasing, but oxygenates changed little when the pyrolysis temperature exceeds 242 °C, the blend containing 50% DR presented the strongest synergy at the absorption peaks assigned to hydrocarbons at each blend. Evolved gas-phase species include mainly hydrocarbons, aromatics and small amount of oxygenated fractions, and higher DR share could obtain greater synergistic gain to CH4, benzene, phenol and naphthalene. Eα and ΔH decreased and then increased with increasing DR content. Average activation energy and enthalpy change of blends containing 25%, 50% and 75% DR were 88.9, 64.4 and 99.6 kJ/mol and 84.1, 59.6, 94.7 kJ/mol calculated through FR method, respectively. Order of reaction mechanism, diffusion mechanism nucleation mechanism affected the pyrolysis process of mixtures together, and the order of reaction model that better described the thermal decomposition of each pseudo-component.

Image Impulse Noise Reduction Using a Conjugate Gradient of Alternative Parameter

Conjugate gradient approaches emphasise the conjugate formula. This study creates a new conjugate coefficient for the conjugate gradient approach to restore pictures using Perry’s conjugacy condition and a quadratic model. Algorithms have global convergence and descent. The new technique performed better in numerical testing. The new conjugate gradient technique outperforms the FR method. The new technique performed better in numerical testing. The new conjugate gradient technique outperforms the FR method.

ANKLE ARTHRODESIS USING TTC (TIBIOTALOCALCANEAL) NAIL IN THE TREATMENT OF NEGLECTED TRIMALLEOLAR FRACTURES OF ANKLE WITH EARLY ARTHRITIS; CASE REPORT

Introduction: Patients rst consult traditional healers and it is when the signs persist that they consult the surgeon for a swollen and painful ankle. Initially we always performed anatomical repairs with osteosynthesis, but the majority of patients still complained of pain and disability. We therefore performed an arthrodesis on neglected post-traumatic ankles. The objective of our study was to describe the result of arthrodesis ankle using TTC (tibiotalocalcaneal) nail on a neglected post-traumatic ankle and to propose a therapeutic indication in the face of any neglected ankle fracture. This was a case of 38/m with 3 months old neglected trimalleolar ankle fr Material and Method: acture with early arthritis treated with ankle arthrodesis using ttc nail. Follow up taken over 3 months by serial x-rays and clinical evaluation. The average follow-up was 3 months and our results were satisfactory radiologically and Results: clinically. Discussion: Arthrodesis with ttc nail appears here as an important alternative in the treatment of neglected ankle fractures with early changes of arthritis

Thermal degradation study of natural fibre through thermogravimetric analysis

Thermogravimetric analysis was performed to understand the thermal degradation characteristics of natural fibre (bhimal). The objective of the study was to evaluate the suitability of fibre as an alternative to synthetic fibre for reinforcement in polymer composite synthesis. The thermal degradation study was conducted at three heating rates, 10, 15 and 20 °C/min from room temperature to 800 °C. The highest weight loss (65–71 wt%) was observed in the temperature range of 200–435 °C. Three model-free isoconversional methods, FWO, KAS, and Friedman, were applied to estimate the kinetic parameters (activation energy and pre-exponential factor). Average activation energies of 115.96 ± 30.89, 111.08 ± 33.01, and 112.67 ± 41.87 kJ/mol were calculated by FWO, KAS, and FR methods, respectively. The respective estimated pre-exponential factors were 1.41E + 11, 6.62E + 10, and 4.49E + 13 min−1. The kinetic parameters varied substantially with the conversion level, which shows the multi-step reaction mechanism of bhimal fibre thermal degradation. The present study suggests the apparent activation energy of bhimal fibre in the range of 108–120 kJ/mol for polymer composite synthesis.

DisP+V: A Unified Framework for Disentangling Prototype and Variation From Single Sample per Person.

Single sample per person face recognition (SSPP FR) is one of the most challenging problems in FR due to the extreme lack of enrolment data. To date, the most popular SSPP FR methods are the generic learning methods, which recognize query face images based on the so-called prototype plus variation (i.e., P+V) model. However, the classic P+V model suffers from two major limitations: 1) it linearly combines the prototype and variation images in the observational pixel-spatial space and cannot generalize to multiple nonlinear variations, e.g., poses, which are common in face images and 2) it would be severely impaired once the enrolment face images are contaminated by nuisance variations. To address the two limitations, it is desirable to disentangle the prototype and variation in a latent feature space and to manipulate the images in a semantic manner. To this end, we propose a novel disentangled prototype plus variation model, dubbed DisP+V, which consists of an encoder-decoder generator and two discriminators. The generator and discriminators play two adversarial games such that the generator nonlinearly encodes the images into a latent semantic space, where the more discriminative prototype feature and the less discriminative variation feature are disentangled. Meanwhile, the prototype and variation features can guide the generator to generate an identity-preserved prototype and the corresponding variation, respectively. Experiments on various real-world face datasets demonstrate the superiority of our DisP+V model over the classic P+V model for SSPP FR. Furthermore, DisP+V demonstrates its unique characteristics in both prototype recovery and face editing/interpolation.

Declaration of nullity for the divorced and remarried couples: A Study Case in Manado Diocese

This research seeks a permanent juridical solution for the pastoral problem of catholic split marriages. Many such couples need the Catholic Church's intervention to give way out of their family problem. And there is indeed a solution provided by Pope Francis with the reform of Canon Law regarding the issue of divorce and remarried couples of Catholic families. The research method is identifying and documenting what has been done in the diocese of Manado by Fr. Jan van Paassen and studying his approach to dealing with families needing help. Bibliographical research indicates the method of Fr. Jan van Paassen in dealing with the problem. It has a solid foundation and a reasonable argumentation which may be accepted by the authority of the Church based on the Calon Law itself. May this research help solve the pastoral problem of the catholic split marriage on the one hand. On the other side, the indissolubility of marriage remains the permanent teaching of the Catholic Church.

Geological Exploration, Landslide Characterization and Susceptibility Mapping at the Boundary between Two Crystalline Bodies in Jajarkot, Nepal

The geology of the Himalayas is intricated and intriguing. It features numerous tectonic bodies and structures too complex to interpret. Along with such mysteries it has too many common geohazards, such as landslides. In this study, a detailed geological investigation is carried out to overcome the discrepancies in structural interpretation, the nature of two crystalline bodies, and non-uniformity in geological mapping in the central Himalayan arc, in the Jajarkot district of Nepal. Along with the geological exploration and landslide characterization of the area, consequent landslide susceptibility mapping is performed considering 13 causative factors related to geology, topography, land use, hydrology, and the anthropogenic factor, using two bivariate statistical models. This study concludes that the two metamorphic crystalline bodies in the study area are most probably the klippen, due to the absence or erosion of the root zone. The field study revealed that haphazard road excavation without the consideration of geological and geotechnical features has caused shallow landslides. The results obtained from the susceptibility maps, with a varying range of susceptibility zones, are in good agreement with the spatial distribution of pre-historic landslides. The results of the susceptibility modeling are validated by calculating landslide density and plotting area under curves (AUC). The AUC value for the WOE, and the FR method, revealed an overall success rate of 79.42% and 77.62%, respectively.

Global convergence of Hager–Zhang type Riemannian conjugate gradient method

This paper presents the Hager–Zhang (HZ)-type Riemannian conjugate gradient method that uses the exponential retraction. We also present global convergence analyses of our proposed method under two kinds of assumptions. Moreover, we numerically compare our proposed methods with the existing methods by solving two kinds of Riemannian optimization problems on the unit sphere. The numerical results show that our proposed method has much better performance than the existing methods, i.e., the FR, DY, PRP, and HS methods. In particular, they show that it has much higher performance than existing methods including the hybrid ones in computing the stability number of graphs problem.

Using a new coefficient conjugate gradient method for solving unconstrained optimization problems

The conjugate gradient technique is a numerical solution strategy for finding minimization in mathematics. We present a simple, straightforward, efficient, and resilient conjugate gradient technique in this study. To address the convergence difficulty and descent property, the new technique is built on the quadratic model. Under some assumptions, the new improved approach meets the convergence characteristics and the adequate descent criterion. The suggested unique strategy is substantially more efficient than the classic FR method, according to our numerical analysis. The number of function evaluations, iterations and restarts are all included in the numerical results. The computational efficiency of the proposed approach is proved by comparative results.

A framework employing the AHP and FR methods to assess the landslide susceptibility of the Western Ghats region in Kollam district

A framework employing the AHP and FR methods to assess the landslide susceptibility of the Western Ghats region in Kollam district

GIS-Based AHP and FR Methods for Landslide Susceptibility Mapping in the Abay Gorge, Dejen–Renaissance Bridge, Central, Ethiopia

GIS-Based AHP and FR Methods for Landslide Susceptibility Mapping in the Abay Gorge, Dejen–Renaissance Bridge, Central, Ethiopia

Orthogonal Modality Disentanglement and Representation Alignment Network for NIR-VIS Face Recognition

Near-infrared and visual (NIR-VIS) face matching, as the most typical task in Heterogeneous Face Recognition (HFR), has attracted increasing attention in recent years. However, due to the large within-class discrepancies, including domain differences and residual discrepancies (i.e., lighting, expressions, occlusion, blurry, pose, etc), this is still a difficult task. Conventional NIR-VIS FR methods only focus on reducing the modality gap between cross-domain images, while neglecting to eliminate the residual variations. To better solve the above problems, this paper proposes a novel Orthogonal Modality Disentanglement and Representation Alignment (OMDRA) approach, which consists of three key components, including Modality-Invariant (MI) loss, Orthogonal Modality Disentanglement (OMD) and Deep Representation Alignment (DRA). Firstly, the MI loss is designed to learn modality-invariant and identity-discriminative representation, by increasing between-class separability and within-class compactness between NIR and VIS heterogeneous data. Secondly, the high-level Hybrid Facial Feature (HFF) layer of the backbone network is projected into two subspaces: the modality-related and identity-related subspaces. The OMD is designed to decouple modal information via an adversarial process, and we further impose Orthogonal Representation Decorrelation (ORD) to the OMD to decrease the correlation between identity representations and domain representations, as well as enhancing their representation capabilities. Finally, the DRA aims to eliminate the residual variations by performing a high-level representation alignment between non-neutral face and neutral face, which can effectively guides the network to learn discriminative and residual-invariant face representation. The joint scheme enables the disentanglement of modality variations, elimination of residual discrepancies, and the purification of identity information. Extensive experiments on challenging cross-domain databases indicate that our OMDRA method is superior to the state-of-the-art methods.

Genetic Diversity Assessment of Iranian Kentucky Bluegrass Accessions: I. ISSR Markers and Their Association with Habitat Suitability Within and Between Different Ecoregions.

Poa pratensis L. is a commonly used cool-season turfgrass and endemic to Iran. This research was carried out to examine the genetic diversity of this plant within and between ecoregions of Iran and the impact of climatic variables and elevation on the distribution of its genotypes, as well as habitat suitability modeling. We used fifty accessions collected from six ecoregions (West, South, North, North-West and North-East) for genetic diversity assessment using 20 ISSR marker primers. The prospective ecoregions for Kentucky bluegrass production were projected using habitat suitability modeling, which took into account important environmental parameters, such as annual mean temperature, annual mean rainfall, and elevation. According to the UPMGA dendrogram, the accessions were divided into two major types and four subclasses. The genetic distance between the North and North-east accessions, as well as the Center accessions, was greater than that of the other genotypes. Center accessions had the greatest levels of polymorphism, effective number of alleles, Shannon index, and Nei's genetic diversity. The FR method was used to create the habitat suitability map based on environmental factors. Rainfall had the largest influence on the genotype distribution of P. pratensis L. The findings of this study can be used asraw materials in future breeding programs to improve and generate new cultivars with superior characteristics. It can also assist programs in identifying rare cultivars as well as preserving and developing native P. pratensis L. genotypes.

New Spectral Idea for Conjugate Gradient Methods and its Global Convergence Theorems

Recently, the unconstrained optimization conjugate gradient methods have been widely utilized, especially for problems that are known as large-scale problems. This work proposes a new spectral gradient coefficient obtained from a convex linear combination of two different gradient coefficients to solve unconstrained optimization problems. One of the most essential features ofour suggested strategy is to guarantee the suitable subsidence direction of the line search precision. Furthermore, the proposed strategy is more effective than previous conjugate gradient approaches and stationery, which have been observed in the test problem. However, when it is compared to other conjugate gradient methods, such as FR methods, the proposed method confirmed the globally convergent, indicating that it can be used in scientific data computation.

Detecting Measurement Noninvariance with Continuous Indicators Using Three Different Statistical Methods under the Framework of Latent Variable Modeling

Under the framework of Latent Variable Modelling, three statistical methods, namely, the free baseline method (FR), the Benjamini-Hochberg method (B–H), and the alignment method (AM), were applied to identify the noninvariant measurement parameters at the indicator level through a simulation study. Model noninvariance was manipulated through varying the locations, degrees and magnitudes of noninvariant parameters with different sample sizes. As a result, the B-H method was discovered to possess a higher power rate in detecting noninvariant parameters than the other two methods, and the AM method performed the best in controlling the type I error rates in the process of parameter estimation. Comparatively speaking, the FR method performed the worst in almost all situations due to the choice of a fixed noninvariant reference indicator. The suggestions on which method is better used for model noninvariance detection was discussed and elaborated.

Study of thermal stability and determination of effective activation energy values during degradation of unsaturated polyester copolymers in the air atmosphere

The study of the kinetic parameters of copolymers based on polyethylene glycol fumarates, as well as the external and internal effects on them, is essential for production processes at various levels. This will solve a whole range of issues in the field of the shelf life of materials and storage conditions. All these point to the relevance of this research. The authors of the research attempt to test the most common thermogravimetric data processing methods and to improve them in terms of the quality of the predictive capabilities of the resulting regression equation. Both of them are important for the production of initial components and the manufacture of the final product from the studied materials. Therefore, the study and further use of the numerical data of the TG/DTA curves applies to both theoretical and practical branches of science. Thus, summarizing the experimental data on the thermal stability studies, we assume that p-EGF: AA copolymers with compositions of 21.03:78.97 and 68.96:31.04 wt.% have a relatively high degree of resistance to heating. It was found that the calculation by the FR method agreed well with the results of the KAS method. It should be noted that for the p-EGF: AA copolymer (21.03:78.97 wt.%) at heating rates of 5.0, 10.0, 20.0 °С∙min–1, the average activation energy data obtained for two methods increase in the following series:KAS E = 187.34 kJ /mol <FR E = 200.17 kJ/mol.

Изучение токсических свойств нефтезагрязнённой почвы с использованием методов биотестирования

The article presents the results of a study of the toxicity using the method of FR.1.39.2016.24117 for gray forest soil contaminated with oil. Seeds of watercress plants of the Zabava variety are used as a test object. Toxicity is assessed by five parameters: seed germination, average length of underground and aboveground parts and total length of seedlings, their average dry weight. The studies show that the most sensitive parameters are seed germination, as well as the average length of the underground, above-ground parts and the total length of seedlings. The tendency of the negative effect of the oil content on plants in the analyzed soil is established. The obtained results show the possibility of using phytotesting methods for analyzing the degree of soil purification.