Search Results (16)

The development of most modern software systems is accompanied by a significant level of uncertainty, which can be attributed to the unanticipated activities that may occur throughout the software development process. As these modern software systems become more complex and drawn out, escalating software project failure rates have become a critical concern. These unforeseeable uncertainties are known as software risks, and they emerge from many risk factors inherent to the numerous activities comprising the software development lifecycle (SDLC). Consequently, these software risks have resulted in massive revenue losses for software organizations. Hence, it is imperative to address these software risks, to curb future software system failures. The subjective risk assessment (SRM) method is regarded as a viable solution to software risk problems. However, it is inherently reliant on humans and, therefore, in certain situations, imprecise, due to its dependence on an expert’s knowledge and experience. In addition, the SRM does not allow repeatability, as expertise is not easily exchanged across the different units working on a software project. Developing intelligent modelling methods that may offer more unbiased, reproducible, and explainable decision-making assistance in risk management is crucial. Hence, this research proposes enhanced fuzzy induction models for software requirement risk prediction. Specifically, the fuzzy unordered rule induction algorithm (FURIA), and its enhanced variants based on nested subset selection dichotomies, are developed for software requirement risk prediction. The suggested fuzzy induction models are based on the use of effective rule-stretching methods for the prediction process. Additionally, the proposed FURIA method is enhanced through the introduction of nested subset selection dichotomy concepts into its prediction process. The prediction performances of the proposed models are evaluated using a benchmark dataset, and are then compared with existing machine learning (ML)-based and rule-based software risk prediction models. From the experimental results, it was observed that the FURIA performed comparably, in most cases, to the rule-based and ML-based models. However, the FURIA nested dichotomy variants were superior in performance to the conventional FURIA method, and rule-based and ML-based methods, with the least accuracy, area under the curve (AUC), and Mathew’s correlation coefficient (MCC), with values of approximately 98%. Full article

Clamping force control is one of the key technologies in the algorithm design and implementation of electro-mechanical braking system, whose control effects directly affect the vehicle braking performance and safety performance. In order to improve the clamping force control performance of electro-mechanical braking (EMB) system, an EMB clamping force control method based on Variable universe adaptive fuzzy PID (VUF-PID) controller is proposed, and stretching factors are added to the fuzzy PID control. According to the operation of the controlled object, the fuzzy theory domain can be adjusted in real time to keep the system in the proper parameter value and improve the adaptive ability of the system. The response characteristics and effectiveness of clamping force under step braking condition, gear switching braking condition and sine braking condition are verified by simulation experiments using MATLAB/Simulink. The results show that the proposed VUF-PID control method has strong tracking characteristics and stability characteristics, and meet the braking requirements under different braking conditions. Full article

Solid-state welding is a derivative of the friction stir spot welding (FSSW) technique, which has been developed as a new method for joining aluminum alloys. FSSW is a variant of linear friction stir welding intended to deal with lightweight alloy resistance spot welding (RSW) and riveting. Tensile strength refers to a material’s ability to withstand excessive stress when being stretched or pulled before necking; it is expressed in terms of force per unit area. The tensile strength in stir spot welding is affected by dynamic and static parameters. The control of dynamic parameters and static parameters is studied in this paper to optimize the friction stir spot welding strength. A fuzzy logic control system is used to optimize the process as a new approach that can be used in this field. The obtained results prove that the fuzzy logic control system is an easy and inexpensive technology that can be used in prediction and optimization for the strength of FSSW. Furthermore, the results show the efficacy and adequacy of the proposed fuzzy logic control system. Full article

Landslides are critical natural disasters characterized by a downward movement of land masses. As one of the deadliest types of disasters worldwide, they have a high death toll every year and cause a large amount of economic damage. The transition between urban and rural areas is characterized by highways, which, in rugged Himalayan terrain, have to be constructed by cutting into the mountains, thereby destabilizing them and making them prone to landslides. This study was conducted landslide-prone regions of the entire Himalayan belt, i.e., National Highway NH-44 (the Jammu–Srinagar stretch). The main objectives of this study are to understand the causes behind the regular recurrence of the landslides in this region and propose a landslide early warning system (LEWS) based on the most suitable machine learning algorithms among the four selected, i.e., multiple linear regression, adaptive neuro-fuzzy inference system (ANFIS), random forest, and decision tree. It was found that ANFIS and random forest outperformed the other proposed methods with a substantial increase in overall accuracy. The LEWS model was developed using the land system parameters that govern landslide occurrence, such as rainfall, soil moisture, distance to the road and river, slope, land surface temperature (LST), and the built-up area (BUA) near the landslide site. The developed LEWS was validated using various statistical error assessment tools such as the root mean square error (RMSE), mean square error (MSE), confusion matrix, out-of-bag (OOB) error estimation, and area under the receiver operating characteristic (ROC) curve (AUC). The outcomes of this study can help to manage landslide hazards in the Himalayan urban–rural transition zones and serve as a sample study for similar mountainous regions of the world. Full article

Agritourism is an increasing new trend in the global tourism industry. Vietnam has a long tradition of agricultural production combined with diverse natural resources stretching from the north to the south, bringing advantages in the development of agritourism. The study aims to choose the most appropriate agritourism location in Vietnam for long-term investment. A hybrid fuzzy multi-criteria decision model (FMCDM) is proposed to find the optimal location based on eco-nomic, social, and environmental factors. In the first stage, the fuzzy analytic hierarchy process (FAHP) is used to estimate the relative criteria rating through the evaluation process. In the second stage, the fuzzy technique for order preference using similarities to ideal solution (FTOPSIS) is applied to rank the potential alternative locations. Finally, the best alternative to tourist site investment is Can Tho (A8), which maximizes resources and enhances the local benefits. Future research can also be used to support similar site-selection processes in other regions or could be applied to other types of tourism. Full article

Ganglion cysts are commonly observed in association with the joints and tendons of the appendicular skeleton. Ultrasonography is the favored modality used to manage such benign tumors, but it may suffer from operator subjectivity. In the treatment phase, ultrasonography also provides guidance for aspiration and injection, and the information regarding the accurate location of the pedicle of the ganglion. Thus, in this paper, we propose an automatic ganglion cyst extracting method based on fuzzy stretching and fuzzy C-means quantization. The proposed method, with its carefully designed image-enhancement policy, successfully detects ganglion cysts in 86 out of 90 cases (95.6%) without requiring human intervention. Full article

Maintenance experts involved in managing major maintenance activities such as; Major overhauls, outages, shutdowns and turnarounds (MoOSTs) are constantly faced with uncertainties during the planning and/or execution phases, which often stretches beyond the organisation’s standard operating procedures and require the intervention of staff expertise. This underpins a need to complement and sustain existing efforts in managing uncertainties in MoOSTs through the transformation of knowledgeable actions generated from experts’ tacit-based knowledge. However, a vital approach to achieve such transformation is by prioritising maintenance activities during MoOSTs. Two methods for prioritising maintenance activities were adopted in this study; one involved a traditional qualitative method for task criticality assessment. The other, a quantitative method, utilised a Fuzzy inference system, mapping membership functions of two crisp inputs and output accompanied by If-Then rules specifically developed for this study. Prior information from a 5-year quantitative dataset was obtained from a case study with appreciable frequency for performing MoOSTs; in this case, a Rotary Kiln system (RKS) was utilised in demonstrating practical applicability. The selection of the two methods was informed by their perceived suitability to adequately analyse the available dataset. Results and analysis of the two methods indicated that the obtained Fuzzy criticality numbers were more sensitive and capable of examining the degree of changes to membership functions. However, the usefulness of the traditional qualitative method as a complementary approach lies in its ability to provide a baseline for informing expert opinions, which are critical in developing specific If-Then rules for the Fuzzy inference system. Full article

The two forms of transthyretin differing slightly in the tertiary structure, despite the presence of five mutations, show radically different properties in terms of susceptibility to the amyloid transformation process. These two forms of transthyretin are the object of analysis. The search for the sources of these differences was carried out by means of a comparative analysis of the structure of these molecules in their native and early intermediate stage forms in the folding process. The criterion for assessing the degree of similarity and differences is the status of the hydrophobic core. The comparison of the level of arrangement of the hydrophobic core and its initial stages is possible thanks to the application of divergence entropy for the early intermediate stage and for the final forms. It was shown that the minimal differences observed in the structure of the hydrophobic core of the forms available in PDB, turned out to be significantly different in the early stage (ES) structure in folding process. The determined values of divergence entropy for both ES forms indicate the presence of the seed of hydrophobic core only in the form resistant to amyloid transformation. In the form of aggressively undergoing amyloid transformation, the structure lacking such a seed is revealed, being a stretched one with a high content of β-type structure. In the discussed case, the active presence of water in the structural transformation of proteins expressed in the fuzzy oil drop model (FOD) is of decisive importance for the generation of the final protein structure. It has been shown that the resistant form tends to generate a centric hydrophobic core with the possibility of creating a globular structure, i.e., a spherical micelle-like form. The aggressively transforming form reveals in the structure of its early intermediate, a tendency to form the ribbon-like micelle as observed in amyloid. Full article

In this paper, complex q-rung orthopair uncertain linguistic sets (CQROULSs) for handling multi-attribute decision making (MADM) issues are proposed so that the assessed estimation of each trait can be presented by CQROULS. Another aggregation operator, called the partitioned Bonferroni mean (PBM) operator, is then considered to manage the circumstances under fuzziness. At that point, the PBM operator is stretched out to CQROULSs in which a complex q-rung orthopair uncertain linguistic partitioned Bonferroni mean (CQROULPBM) operator is then proposed. To wipe out the negative impact of preposterous assessment estimations of characteristics on total outcomes, complex q-rung orthopair uncertain linguistic weighted partitioned Bonferroni mean (CQROULWPBM) operator is further considered. These properties, idempotency, boundedness, and commutativity of the CQROULWPBM operator are obtained. The proposed CQROULSs with the CQROULWPBM operator is novel and important for MADM issues. Finally, an MADM based on CQROULSs is constructed with a numerical case given to delineate the proposed approach and then applied for selecting an antivirus mask for the COVID-19 pandemic. The advantages and comparative analysis with graphical interpretation of the explored operators are also presented to demonstrate the effectiveness and usefulness of the proposed method. Full article

Visual-motor tracking movement is a common and essential behavior in daily life. However, the contribution of future information to visual-motor tracking performance is not well understood in current research. In this study, the visual-motor tracking performance with and without future-trajectories was compared. Meanwhile, three task demands were designed to investigate their impact. Eighteen healthy young participants were recruited and instructed to track a target on a screen by stretching/flexing their elbow joint. The kinematic signals (elbow joint angle) and surface electromyographic (EMG) signals of biceps and triceps were recorded. The normalized integrated jerk (NIJ) and fuzzy approximate entropy (fApEn) of the joint trajectories, as well as the multiscale fuzzy approximate entropy (MSfApEn) values of the EMG signals, were calculated. Accordingly, the NIJ values with the future-trajectory were significantly lower than those without future-trajectory (p-value < 0.01). The smoother movement with future-trajectories might be related to the increasing reliance of feedforward control. When the task demands increased, the fApEn values of joint trajectories increased significantly, as well as the MSfApEn of EMG signals (p-value < 0.05). These findings enrich our understanding about visual-motor control with future information. Full article

The margins of Brazilian rivers are considered Permanent Preservation Areas—APPs, due to the riparian forest’s water resource preservation capacity. However, a significant portion of the Brazilian Atlantic Forest biome, in which the Jacaré River basin is located, has suffered increasing deforestation over the past decades. This research aimed to use a methodology integrating Geographic Information System (GIS), fuzzy logic, Analytic Hierarchy Process (AHP), and sensitivity analysis to model the selection of riparian protected area stretches that presents the best successful riparian forest reforestation using a real case, the Jacaré river basin, whose characteristics are often in Brazilian watersheds. To identify the main drivers that influence reforestation success, we carried out a broad and detailed bibliographic research. To establish the relative importance among the drivers, we conducted a survey with experts. The results showed that areas with moderate chances of reforestation prevail in the studied region. Due to the areas’ distribution pattern, a significant portion of the best sites were grouped, forming regions that create environments that favor aquatic and riverside life development and ecological balance maintenance, thus bringing together fundamental characteristics to improve water resources sustainability. The best sites have dystrophic or eutrophic soil, with a slope of up to 15%. Besides, they are mainly covered by grass and are close to forest fragments with low vulnerability. Full article

The importance of three-dimensional (3D) point cloud technologies in the field of agriculture environmental research has increased in recent years. Obtaining dense and accurate 3D reconstructions of plants and urban areas provide useful information for remote sensing. In this paper, we propose a novel strategy for the enhancement of 3D point clouds from a single 4D light field (LF) image. Using a light field camera in this way creates an easy way for obtaining 3D point clouds from one snapshot and enabling diversity in monitoring and modelling applications for remote sensing. Considering an LF image and associated depth map as an input, we first apply histogram equalization and histogram stretching to enhance the separation between depth planes. We then apply multi-modal edge detection by using feature matching and fuzzy logic from the central sub-aperture LF image and the depth map. These two steps of depth map enhancement are significant parts of our novelty for this work. After combing the two previous steps and transforming the point–plane correspondence, we can obtain the 3D point cloud. We tested our method with synthetic and real world image databases. To verify the accuracy of our method, we compared our results with two different state-of-the-art algorithms. The results showed that our method can reliably mitigate noise and had the highest level of detail compared to other existing methods. Full article

This study determines the practicality and feasibility of the application of pneumatic artificial muscles (PAMs) in a pneumatic therapy robotic system. The novel mechanism consists of a single actuated pneumatic artificial muscle (single-PAM) robotic lower limb that is driven by only one PAM combined with a torsion spring. Unlike most of previous studies, which used dual-actuated pneumatic artificial muscles (dual-PAMs) to drive joints, this design aims to develop a novel single-PAM for a one degree-of-freedom (1-DOF) robotic lower-limb system with the advantage of a mechanism for developing a multi-axial therapy robotic system. The lower limb robotic assisting system uses the stretching/contraction characteristics of a single-PAM and the torsion spring designed by the mechanism to realize joint position control. The joint is driven by a single-PAM controlled by a proportional pressure valve, a designed 1-DOF lower-limb robotic system, and an experimental prototype system similar to human lower limbs are established. However, the non-linear behavior, high hysteresis, low damping and time-variant characteristics for a PAM with a torsion spring still limits its controllability. In order to control the system, a fuzzy sliding mode controller (FSMC) is used to control the path tracking for the PAM for the first time. This control method prevents approximation errors, disturbances, un-modeled dynamics and ensures positioning performance for the whole system. Consequently, from the various experimental results, the control response designed by the joint torsion spring mechanism can also obtain the control response like the design of the double-PAMs mechanism, which proves that the innovative single-PAM with torsion spring mechanism design in this study can reduce the size of the overall aid mechanism and reduce the manufacturing cost, can also improve the portability and convenience required for the wearable accessory, and is more suitable for the portable rehabilitation aid system architecture. Full article

Selected amyloid structures available in the Protein Data Bank have been subjected to a comparative analysis. Classification is based on the distribution of hydrophobicity in amyloids that differ with respect to sequence, chain length, the distribution of beta folds, protofibril structure, and the arrangement of protofibrils in each superfibril. The study set includes the following amyloids: Aβ (1–42), which is listed as Aβ (15–40) and carries the D23N mutation, and Aβ (11–42) and Aβ (1–40), both of which carry the E22Δ mutation, tau amyloid, and α-synuclein. Based on the fuzzy oil drop model (FOD), we determined that, despite their conformational diversity, all presented amyloids adopt a similar structural pattern that can be described as a ribbon-like micelle. The same model, when applied to globular proteins, results in structures referred to as “globular micelles,” emerging as a result of interactions between the proteins’ constituent residues and the aqueous solvent. Due to their composition, amyloids are unable to attain entropically favorable globular forms and instead attempt to limit contact between hydrophobic residues and water by producing elongated structures. Such structures typically contain quasi hydrophobic cores that stretch along the fibril’s long axis. Similar properties are commonly found in ribbon-like micelles, with alternating bands of high and low hydrophobicity emerging as the fibrils increase in length. Thus, while globular proteins are generally consistent with a 3D Gaussian distribution of hydrophobicity, the distribution instead conforms to a 2D Gaussian distribution in amyloid fibrils. Full article

Lower-limb function in elderly people gradually degenerates with age, and poor rehabilitation conditions preventing the elderly from receiving scientific rehabilitation training result in the decline of social labor force and the increased economic burden of the elderly. Aiming at the characteristics of the single function and the complex structure of an existing telescopic leg trainer combined with the needs of the application group, a new type of leg-stretching training device with multiple training modes for lower extremity extension and flexion of the elderly is proposed. A new mechanical structure and electrical system is designed. At the same time, the anti-resistance training man–machine model is analyzed, aiming at the isokinetic resistance training mode, and a training controller strategy based on a fuzzy synovial algorithm is proposed. Finally, the feasibility of the designed controller strategy and the proposed leg training device are verified by prototype experiments, which will guide further research. Full article