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The study introduces a new method for predicting software defects based on Residual/Shuffle (RS) Networks and an enhanced version of Fish Migration Optimization (UFMO). The overall contribution is to improve the accuracy, and reduce the manual effort needed. The originality of this work rests in the synergic use of deep learning and metaheuristics to train the software code for extraction of semantic and structural properties. The model is tested on a variety of open-source projects, yielding an average accuracy of 93% and surpassing the performance of the state-of-the-art models. The results indicate an overall increase in the precision (78–98%), recall (71–98%), F-measure (72–96%), and Area Under the Curve (AUC) (78–99%). The proposed model is simple and efficient and proves to be effective in identifying potential defects, consequently decreasing the chance of missing these defects and improving the overall quality of the software as opposed to existing approaches. However, the analysis is limited to open-source projects and warrants further evaluation on proprietary software. The study enables a robust and efficient tool for developers. This approach can revolutionize software development practices in order to use artificial intelligence to solve difficult issues presented in software. The model offers high accuracy to reduce the software development cost, which can improve user satisfaction, and enhance the overall quality of software being developed.

A revelatory look at the secrets of marine fish migration. Not since F. R. Harden Jones published his masterwork on fish migration in 1968 has a book so thoroughly demystified the subject. With stunning clarity, David Hallock Secor's Migration Ecology of Fishes finally penetrates the clandestine nature of marine fish migration. Secor explains how the four decades of research since Jones's classic have employed digital-age technologies—including electronic miniaturization, computing, microchemistry, ocean observing systems, and telecommunications—that render overt the previously hidden migration behaviors of fish. Emerging from the millions of observed, telemetered, simulated, and chemically traced movement paths is an appreciation of the individual fish. Members of the same populations may stay put, explore, delay, accelerate, evacuate, and change course as they conditionally respond to their marine existence. But rather than a morass of individual behaviors, Secor shows us that populations are collectively organized through partial migration, which causes groups of individuals to embark on very different migration pathways despite being members of the same population. Case studies throughout the book emphasize how migration ecology confounds current fisheries management. Yet, as Secor explains, conservation frameworks that explicitly consider the influence of migration on yield, stability, and resilience outcomes have the potential to transform fisheries management. A synthetic treatment of all marine fish taxa (teleosts and elasmobranchs), this book employs explanatory frameworks from avian and systems ecology while arguing that migrations are emergent phenomena, structured through schooling, phenotypic plasticity, and other collective agencies. The book provides overviews of the following concepts: • The comparative movement ecology of fishes and birds • The alignment of mating systems with larval dispersal • Schooling and migration as adaptations to marine food webs • Natal homing • Connectivity in populations and metapopulations • The contribution of migration ecology to population resilience

In the wireless sensor networks (WSN), the cluster head node receives and aggregates the information collected by the sensors and forwards it to the base station (BS). Appropriate cluster head nodes help reduce the energy consumed for information transmission and prolong the network’s lifetime. The fish migration optimization (FMO) algorithm is an emerging meta-heuristic algorithm, that imitates the grayling foraging and breeding in nature. This paper proposes a modified FMO (modFMO) algorithm, which uses an opposition learning based on the elimination principle and Cauchy-based mutation to enhance the FMO algorithm. The improved modFMO is compared with some excellent algorithms on CEC 2014 function sets, and the Friedman ranks test demonstrates the effectiveness of the improvement. In this paper, the FMO algorithm and the modFMO algorithms with the centralized control algorithm are applied to select the optimal cluster head respectively. This paper takes the average energy consumption of the cluster head nodes as the objective function. Compared with other classic algorithms, the simulation results demonstrate that the modFMO algorithm can extend the lifetime of wireless networks, reduce energy consumption, improve information transmission efficiency and improved the ability of FMO algorithm.

Given the intricate nature of contemporary energy systems, addressing the control and stability analysis of these systems necessitates the consideration of highly large-scale models. Transient stability analysis stands as a crucial challenge in enhancing energy system efficiency. Power System Stabilizers (PSSs), integrated within excitation control for synchronous generators, offer a cost-effective means to bolster power systems’ stability and reliability. In this study, we propose an enhanced nonlinear control strategy based on synergetic control theory for PSSs. This strategy aims to mitigate electromechanical oscillations and rectify the limitations associated with linear approximations within large-scale energy systems that incorporate thyristor-controlled series capacitors (TCSCs). To dynamically adjust the coefficients of the nonlinear controller, we employ the Fractional Order Fish Migration Optimization (FOFMO) algorithm, rooted in fractional calculus (FC) theory. The FOFMO algorithm adapts by updating position and velocity within fractional-order structures. To assess the effectiveness of the improved controller, comprehensive numerical simulations are conducted. Initially, we examine its performance in a single machine connected to the infinite bus (SMIB) power system under various fault conditions. Subsequently, we extend the application of the proposed nonlinear stabilizer to a two-area, four-machine power system. Our numerical results reveal highly promising advancements in both control accuracy and the dynamic characteristics of controlled power systems.

In developing countries where data and resources are lacking, the practical relevance of Local Ecological Knowledge (LEK) to expand our understanding of the environment has been highlighted. The potential roles of the LEK varies from direct applications such as gathering environmental information to a more participative involvement of the community in the management of resources they depend on. Fishers’ LEK could therefore be useful in order to obtain information to advance management of coastal fisheries. Many targeted fish species migrate between habitats to feed, spawn or recruit, connecting important habitats within the seascape. LEK could help provide answers to questions related to this connectivity and the identification of fish habitat use and migrations for species and areas where such knowledge is scarce. Here we assess fishers’ LEK on connectivity between multiple habitats within a tropical seascape, investigate the differences in LEK among fisher groups and the coherence between LEK and conventional scientific knowledge (CSK). The study was conducted in Zanzibar, Tanzania, a tropical developing country, in 2017. One hundred and thirty-five semi-structured interviews were conducted in six different locations focusing on fish migrations, and matching photos of fish and habitats. Differences between fisher groups were found, where fishers travelling further, exposed to multiple habitats, and fish with multiple gears had a greater knowledge on connectivity patterns within the seascape than those that fish locally, in single habitats and with just one type of gear. A high degree of overlap in LEK and CSK was found, highlighting the potential benefits of collaboration between scientists and fishers and the use of LEK as complementary information in the management of small-scale fisheries.

Anthropogenic structures often block or delay the downstream migration of fish in rivers, thereby affecting their populations. A potential solution at run-of-river hydropower plants (HPPs) is the construction of a fish guidance structure in combination with a bypass system located at its downstream end. Crucial to fish guidance efficiency and thus to fish behavior are the hydraulic flow conditions in front of the fish guidance structure and upstream of the bypass entrance, which have not thus far been investigated in depth. The present study aims to extend the knowledge about the flow conditions at these structures. Based on the results of 3D numerical simulations of two idealized block-type HPPs with horizontal bar rack bypass systems, the flow conditions were examined, and the fish guidance efficiency was predicted. Herein, a new method was used to represent the fish guidance structure in the numerical model. The results show that the approach flow to fish guidance structures at block-type HPPs varies significantly along their length, and areas with unfavorable flow conditions for downstream fish migration frequently occur according to common guidelines. Subsequently, eight variations were performed to investigate the effect of key components on the flow field, e.g., the bypass discharge. Finally, the results were compared with literature data and discussed.

Horizontal bar racks used as fish protection measures at hydropower plants have rapidly gained importance in recent years. Despite the large number of installed racks in Europe, systematic investigations of the hydraulic losses and velocity fields were missing. To fill these research gaps, the hydraulic performance of horizontal bar racks was systematically investigated in a laboratory flume for a large number of rack parameters and different hydropower plant layouts. The results of the head loss assessment are published in a paper entitled Head Losses of Horizontal Bar Racks as Fish Guidance Structures, whereas the present paper focuses on the velocity fields. The measurements show that the bar shape, the horizontal approach flow angle, and the clear bar spacing have only a minor effect on the velocity fields. In contrast, bottom and top overlays might enhance the fish guidance efficiency for bottom and surface oriented fish, while the asymmetric downstream velocity field can reduce turbine efficiencies. The hydropower plant layout strongly affects the approach flow field to horizontal bar racks. For block-type hydropower plants, the installation of a dividing pier or partial opening of the spillways improves the flow field for better fish guidance.

This paper investigates the hydraulics and fish guidance efficiency of a Horizontal Bar Rack-Bypass System (HBR-BS) installed at a hydropower plant with a design discharge of 33 m3/s. The HBR is placed at a horizontal rack angle of 38° to the flow direction with clear bar spacing of 20 mm. The BS has a vertical-axis flap gate with two openings. The HBR-BS complies with most literature design criteria. Velocity measurements were conducted using a moving-vessel Acoustic Doppler Current Profiler (ADCP). The fish monitoring study was conducted using a stow net, video, and ARIS sonar recordings. The fish monitoring calculations imply guidance efficiency of 84%, even for fish with total body lengths below 10 cm. Furthermore, the hydraulic results show that the flow field is favorable in terms of fish guidance due to a good alignment of the rack and the BS, corroborating the fish monitoring results. The results indicate that the HBR-BS functions not only as a physical barrier but also as a mechanical behavioral barrier for some small fish that are capable of physically passing the HBR. The present results are compared and discussed with the laboratory and field results from different studies in the literature.

Location information is the primary feature of wireless sensor networks, and it is more critical for Mobile Wireless Sensor Networks (MWSN) to monitor specific targets. How to improve the localization accuracy is a challenging problem for researchers. In this paper, the Gaussian probability distribution model is applied to randomize the individual during the migration of the Adaptive Fish Migration Optimization (AFMO) algorithm. The performance of the novel algorithm is verified by the CEC 2013 test suit, and the result is compared with other famous heuristic algorithms. Compared to other well-known heuristics, the new algorithm achieves the best results in almost 21 of all 28 test functions. In addition, the novel algorithm significantly reduces the localization error of MWSN, the simulation results show that the accuracy of the new algorithm is more than 5% higher than that of other heuristic algorithms in terms of mobile sensor node positioning, and more than 100% higher than that without the heuristic algorithm.

This study investigated the response of sweetfish (Plecoglossus altivelis), a species that migrates dynamically throughout a river basin, to two flood events during the summer of 2020 in the Nagara River, located in the central region of Japan. By combining multiple environmental DNA (eDNA) surveys and hydrological modeling, the spatiotemporal distribution of P. altivelis throughout a mountainous river basin was captured and analyzed. The eDNA concentrations at 42 sites in the Nagara River Basin were analyzed five times from August to early October 2020. In addition, Rainfall–Runoff–Inundation model calculations were performed using 1-km resolution precipitation data as input values to analyze the magnitude of the flood disturbance at the eDNA sites. The daily specific discharge Qs (m3/s/km2) was employed as an index of the flood magnitude. The calculation period included Flood Events 1 and 2 with 52 and 38 days of precipitation reaching 1923 and 528 mm, respectively. The results of the eDNA analysis showed that, immediately after Flood Event 1, the spatial distribution of P. altivelis was unevenly distributed in the upper reaches of the Nagara River and some of its tributaries. Subsequently, the distribution expanded to the entire mainstem. The distribution of the maximum daily specific discharge suggested that the river segments with high eDNA concentrations of P. altivelis immediately after the high-magnitude flood event were those with a relatively low intensity of flood disturbance compared with those in the other connected river segments and tributaries. The results of this study indicate that the resilience of riverine communities to extreme floods is supported by the continuity and connectivity between the mainstem and its tributaries in mountainous river basins.