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Background: Software Product Line is the group of multiple software systems which share the similar set of features with multiple variants. Feature model is used to capture and organize features used in different multiple organization. Objective: The objective of this research article is to obtain an optimized subset of features which are capable of providing high performance. Methods: In order to achieve the desired objective, two methods have been proposed. a) An improved objective function which is used to compute the contribution of each feature with weight based methodology. b) A hybrid model is employed to optimize the Software Product Line problem. Results: Feature sets varying in size from 100 to 1000 have been used to compute the performance of the Software Product Line. Conclusion: The results shows that proposed hybrid model outperforms the state of art metaheuristic algorithms.

Introducction: Mobile Robot is a kind of robot system consisting of sensors, remote control operators and automatic control mobile carriers. It is a product of integrated application of integrated disciplines developed in recent years. In the research of mobile robot related technology, navigation technology is its core, and path planning is an important link and subject of navigation research. Objective: An improved firefly algorithm is proposed for path planning of Mobile Robots in this paper. Methods: In this paper, an improved firefly algorithm is proposed. Compared with traditional firefly algorithm, this algorithm has three main improvements: (1) using Sobol sequence to initialize population; (2) adding dynamic disturbance coefficient to enhance the global search ability of the algorithm; (3) considering the uncertainty of search, the attraction between individuals is strong. Fuzzy control is carried out by setting membership function. Results: The new algorithm takes advantage of the uniformity of Sobol sequence sampling and starts to optimize in a wider range, which makes the initial path of the algorithm longer, but because the new algorithm introduces the dynamic disturbance coefficient and the fuzzy control strategy, the average running time is shorter. Conclusion: In the simulation experiment of mobile robot path planning problem, the improved firefly algorithm proposed in this paper is easier to jump out of local optimum than the traditional firefly algorithm, and has more robust search ability. Discussion: It is obvious from the graph that in 100 iterations, the FaFA algorithm takes advantage of the uniformity of Sobol sequence sampling and starts to optimize in a wider range, which makes the initial path of the algorithm longer, but because the FaFA algorithm introduces the dynamic disturbance coefficient and the fuzzy control strategy, it makes the algorithm able.

Software testing is a valuable and time-consuming activity that aims to improve the software quality. Due to its significance, combinatorial testing focuses on fault identification by the interaction of small amount of input factors. But, deep testing is not sufficient due to time or resources availability. To select the optimal test cases with least computation time, Hybrid Multi Criteria Particle Swarm and Ranked Firefly Metaheuristic Optimization(HMCPW-RFMO) technique are introduced. Initially, the population of the test cases is randomly initialized. Then the fitness is calculated by the pairwise coverage, execution cost, fault detection capability and average execution frequency. RFM approach starts with ‘n’ fireflies. The light intensity of each firefly gets initialized.If the light intensity of one firefly is minor than the other one, it moves near the brighter one. Next, the rank is given to the firefly based on their light intensity. Lastly, the high ranked firefly is chosen as a global best solution.The result reveals that HMCPW-RFMO technique improves the software quality.

In the contemporary world, many dangerous disease which are affecting human beings and new pandemic disease is also raising alarm to have an effective health care system. In this aspect the technology plays a major role in improving and optimizing the health care system. The diagnostic is done by taking blood test, urine test, and medical imaging like X-ray, CT scan, Ultrasound scan and MRI scan system. Among these, the paper focus will be emphasized on MRI imaging in identifying the brain tumor using image processing. In the proposed work the fuzzy C means(FCM) algorithm along with firefly algorithm optimized support vector machine (SVM) are used to classify the MRI brain tumor images. The results of these works are compared using the performance metrics such as accuracy, sensitivity, specificity and precision. The proposed method gives best results for the classification of MRI brain tumor images.

PurposeCloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and compliance. This paper aims to maximize the covered human resource (HR) vulnerabilities and minimize the security costs in the enterprise cloud using a fuzzy-based method and firefly optimization algorithm.Design/methodology/approachCloud computing provides a platform to improve the quality and availability of IT resources. It changes the way people communicate and conduct their businesses. However, some security concerns continue to derail the expansion of cloud-based systems into all parts of human life. Enterprise cloud security is a vital component in ensuring the long-term stability of cloud technology by instilling trust. In this paper, a fuzzy-based method and firefly optimization algorithm are suggested for optimizing HR vulnerabilities while mitigating security expenses in organizational cloud environments. MATLAB is employed as a simulation tool to assess the efficiency of the suggested recommendation algorithm. The suggested approach is based on the firefly algorithm (FA) since it is swift and reduces randomization throughout the lookup for an optimal solution, resulting in improved performance.FindingsThe fuzzy-based method and FA unveil better performance than existing met heuristic algorithms. Using a simulation, all the results are verified. The study findings showed that this method could simulate complex and dynamic security problems in cloud services.Practical implicationsThe findings may be utilized to assist the cloud provider or tenant of the cloud infrastructure system in taking appropriate risk mitigation steps.Originality/valueUsing a fuzzy-based method and FA to maximize the covered HR vulnerabilities and minimize the security costs in the enterprise cloud is the main novelty of this paper.

Among numerous bioluminescent organisms, firefly is the most studied one. Recent experiment proposed that sulfoluciferin (SLH2 ) may serve as a storage form of luciferin (LH2 ). In the present article, we employed density functional theory calculation to uncover the mechanism and detailed process of the storage and release reactions. Due to lack of available crystallographic structure of the related enzyme, the calculation was performed on a model system. For the storage reaction, possible amino acid residues were used for imitating the protein environment. For the release reaction, the dielectric constant of 3.0 was employed to simulate the polarity of the protein cavity. The computational results indicated that the reactions from LH2 to SLH2 and from SLH2 to LH2 are both exergonic, which favor the storage and release processes and coincide with the experimental observation. Basing on experimental and current theoretical study, we supplemented the stages of LH2 storage and release in the entire bioluminescent cycle of firefly. The current theoretical calculation could inspire the study on LH2 storage and release of other bioluminescent organisms.

Dilip Kumar has been praised for his sublime dialog delivery, for his restrained gestures, and for his measured and controlled underplay of emotions in tragic stories as well as in light-hearted comedies. His debut in 1944 with Jwar Bhata (Ebb and Tide) met with less-than-flattering reviews. So did the next three films until his 1948 film, Jugnu (Firefly), which brought him recognition and success. Unlike his contemporaries such as Raj Kapoor and Dev Anand, who propelled their careers by launching their own production companies, Dilip Kumar relied on his talent, his unique approach to characterization, and his immersion in the projects he undertook. In the course of his career that spanned six decades, Kumar made only 62 films. However, his work is a textbook for other actors that followed. Not only did he bring respectability to a profession that had been shunned by the upper classes in India as a profession for “pimps and prostitutes,” but he also elevated film-acting and filmmaking to an academic discipline, making him worthy of the title ‘Professor Emeritus of Acting’. Rooted in the theoretical framework of Howard S. Becker’s work on the “production of culture” and “doing things together,” this paper discusses Kumar’s approach to acting, character development, and the level of his involvement and commitment to each of his projects. The author of this article argues that more than the creative control as a producer or a director, it is the artistic involvement and commitment of the main actors that shape great works of art in cinema. Dilip Kumar demonstrated it repeatedly. Dilip Kumar był chwalony za wysublimowane prowadzenie dialogów, opanowaną gestykulację oraz za wyważone i kontrolowane wyrażanie emocji zarówno w opowieściach tragicznych, jak też w beztroskich komediach. Jego debiut w 1944 w Jwar Bhata (Odpływy i przypływy) spotkał się z niezbyt pochlebnymi recenzjami. Podobnie było z kolejnymi trzema filmami, aż do filmu Jugnu (Świetlik) z 1948 roku, który przyniósł mu uznanie i sukces. W przeciwieństwie do swoich rówieśników, jak Raj Kapoor iDev Anand, którzy napędzali kariery, uruchamiając własne firmy produkcyjne, Dilip Kumar polegał na swoim talencie, unikalnym podejściu do charakteryzacji i zaangażowaniu w projekty, których się podjął. W ciągu swojej sześćdziesięcioletniej kariery Kumar nakręcił tylko 62 filmy. Jednak jego praca jest podręcznikowa dla młodszych aktorów. Nie tylko przyniósł szacunek zawodowi aktora, traktowanemu przez indyjskie klasy wyższe jako zawód „alfonsów i prostytutek”, ale także podniósł aktorstwo filmowe i filmowanie do dyscypliny akademickiej, co uczyniło Kumara godnym tytułu emerytowanego profesora aktorstwa. Artykuł ten, zakorzeniony w ramach teoretycznych pracy Howarda S. Beckera nad „produkcją kultury” i „robieniem rzeczy razem”, omawia podejście Kumara do aktorstwa i rozwoju postaci oraz poziom jego zaangażowania w każdy ze swoich projektów. Autor tego artykułu przekonuje, że to artystyczne zaangażowanie i poświęcenie głównych aktorów kształtują wielkie dzieła sztuki w kinie bardziej niż kontrola twórcza producenta czy reżysera. Dilip Kumar wielokrotnie to zademonstrował.

With the exponential increase of social media users, cyberbullying has been emerged as a form of bullying through electronic messages. Cyberbullying detection is generally in social networks like Twitter is one of the focussed research area. Cyberbullying is serious and widespread issues affecting increasingly more Internet users. Text mining tools are detecting cyber bullying and deal with several issues. However the existing system has issue with time consumption and inaccurate Cyberbullying detection results for the given Twitter dataset. To avoid the above mentioned issues, in this work, Enhanced Cuckoo Search optimization (ECSO) and Hybrid Firefly Artificial Neural Network (HFANN) algorithm is proposed. The proposed system contains three main phases are such as preprocessing, feature subset selection and classification. The preprocessing is done by using k-means algorithm for reducing the noise data from the given Twitter dataset. It handles the missing features and redundancy features through k-means centroid values and min max normalization respectively. It is used to increase the classification accuracy more effectively. The pre-processed features are taken into feature selection process for obtaining more informative features from the Twitter dataset. It is performed by using ECSO algorithm and the objective function is used to compute the relevant and important feature based on the best fitness values. Then the HFANN algorithm is applied for classification through training and testing model. It classifies the features more accurately using best fireflies rather than the previous algorithms. The experimental result proves that the proposed ECSO+HFANN algorithm provides better classification performance in terms of lower time complexity, higher precision, recall, f-measure and accuracy than the existing algorithms.

This essay starts with the assumption that philosophical practice is defined as an exercise of linguistic clarification. Whether in oral or written form, philosophy stems from the need to explicate and objectify the logós, formulating concepts. In the particular case of artistic practice, on the other hand, the signifier is more visible than the signified and the impermanence of objectivity is more clearly shown. In art, language is thus open to multiplicity and inexpressibility and the word is no longer logically or syntactically objectified. The truth which develops within art is not universal but the embodiment of an engaging and embryonic form. Art is the place where truth is in motion, a form of resistance, an all-embracing, unifying experience intimately close to world- changing practices.

Blasting has been widely recognized as an economical and viable method in geo-engineering projects. However, the induced ground vibration in terms of peak particle velocity (PPV) potentially can damage the nearby environment and inhabitants. Therefore, more accurate prediction of the PPV can lead to reduce undesirable and hazardous effects of blasting. With the increase in the computational power, wide variety of predictive PPV models using numerical tools and data mining approaches have been presented. In this paper, the optimum predictive PPV model was specified using generalized feedforward neural network (GFFN) structure integrated with a novel automated intelligent setting parameter approach. Subsequently, two new optimized hybrid models using GFFN incorporated with firefly and imperialist competitive metaheuristic algorithms (FMA and ICA) were developed and applied on 78 monitored events in Alvand–Qoly mine, Iran. According to analyzed metrics, the predictability level of hybrid GFFN-FMA dedicated 6.67% and 20% progress than GFFN-ICA and optimum GFFN. The pursued performance using precision–recall curves and ranked accuracy criteria also exhibited superior improvement in GFFN-FMA. Sensitivity analyses implied on the importance of the distance and burden as the most and least effective factors on predicted induced PPV in the study area.

Rapid growth in the transfer of multimedia information over the Internet requires algorithms to retrieve a queried image from large image database repositories. The proposed content‐based image retrieval (CBIR) uses Gaussian–Hermite moments as the low‐level features. Later these features are compressed with principal component analysis. The compressed feature set is multiplied with the weight matrix array, which has the same size as the feature vector. Hybrid firefly and grey wolf optimization (FAGWO) is used to prevent the premature convergence of optimization in the firefly algorithm. The retrieval of images in CBIR is carried out in an OpenCV python environment with K‐nearest neighbours and random forest algorithm classifiers. The fitness function for FAGWO is the accuracy of the classifier. The FAGWO algorithm derives the optimum weights from a randomly generated initial population. When these optimized weights are applied, the proposed algorithm shows better precision/recall and efficiency than other techniques such as exact legendre moments, Region‐based image retrieval, K‐means clustering ​and Color descriptor wavelet‐based texture descriptor retrieval technique. In terms of optimization, hybrid FAGWO outperformed various optimization techniques (when used alone) like Particle Swarm Optmization, Genetic Algorithm, Grey‐Wolf Optimization and FireFly algorithm.

Conventional DC motors often experience problems that require regular maintenance. The use of conventional DC motors can be replaced with Brushless DC (BLDC) motors. This BLDC motor has good efficiency and durability. Increasing the ability of BLDC motors can be done by speed regulation using the Proportional-Integral-Derivative (PID) method combined with Firefly Algorithm. Testing this method uses matlab 2014a. The firefly algorithm can obtain parameter values of Kp, Ki, and Kd which are then used as PID input. Because of inaccuracies in determining the value of a constant in PID and can cause the length of time to reach the desired speed. BLDC motor speed regulation with the PID method combined with firefly algorithm can make the BLDC motor reach synchronous faster

Purpose Accurate foreign tourist arrivals forecasting can help public and private sectors to formulate scientific tourism planning and improve the allocation efficiency of tourism resources. This paper aims to address the problem of low prediction accuracy of Chinese inbound tourism demand caused by the lack of valid historical data. Design/methodology/approach A novel hybrid Chinese inbound tourism demand forecasting model combining fractional non-homogenous discrete grey model and firefly algorithm is constructed. In the proposed model, all adjustable parameters of the fractional non-homogenous discrete grey model are optimized simultaneously by the firefly algorithm. Findings The data sets of annual foreign tourist arrivals to China are used to verify the validity of the proposed model. Experimental results show that the proposed method is effective and can be used as a useful predictor for the prediction of Chinese inbound tourism demand. Originality/value The method proposed in this paper is effective and can be used as a feasible approach for forecasting the development trend of Chinese inbound tourism.

Here, based on phylogenetic analyses of 18 taxa and 57 morphological characters, we propose a new firefly genus,Costalampysgen. nov., to accommodate eleven species. Five new species are herein described:C. bellasp. nov.,C. capixabasp. nov.,C delicatasp. nov.(designated as type species),C. joanaesp. nov.andC. minimasp. nov.In addition, six species are redescribed and transferred from other genera:C. bisbinotata(Pic)comb. nov., transferred fromPlatylampisMotschulsky;C. decorata(Olivier)comb. nov., transferred fromEthraLaporte;C. pauper(Olivier)comb. nov., transferred fromCladodesSolier; as well asC. klugii(Motschulsky)comb. nov.,C. quadriguttata(Gorham)comb. nov., andC. tricolor(Gorham)comb. nov., transferred fromLucidotaLaporte.Costalampysgen. nov.is tentatively placed in Lampyrinae, and is diagnosed by: antennae with 11 articles, III–X basally flabellate, lacking dense and upright bristles; clypeus connected to frons by membrane, pygidium rounded; sternum VIII mucronate; phallus with dorsal plate enlarged apically, projecting ventrally and partially embracing the internal sac. Our phylogenetic analyses supported both the monophyly ofCostalampysgen. nov.and the new combinations proposed. However, the relationship among congeneric species was poorly resolved. Finally, we provide illustrations of diagnostic features, distribution maps, as well as a key toCostalampysgen. nov.species, based on males.

Light plays paramount functions for living beings in nature. In addition to color, the polarization of light is used by many animals for navigation and communication. In this study, we describe the light polarizing role of special nanostructures coating cuticular surfaces of diverse arthropods. These structures are built as parallel nanoscale ridges covering the eyes of the sunlight-navigating spider Drassodes lapidosus and of the water pond-swarming black fly Simulium vittatum, as well as the light-emitting abdominal lantern of the firefly Aquatica lateralis. Exact topography and dimensions of the parallel nanoridges provide different light polarizing efficiencies and wavelength sensitivity. Optical modeling confirms that the nanoscale ridges are responsible for the spectral polarization dependency. Co-opting from our recent work on the self-assembly of Drosophila corneal nanostructures, we engineer arthropod-like parallel nanoridges on artificial surfaces, which recapitulate the light polarization effects. Our work highlights the fundamental importance of nanocoatings in arthropods for the light polarization management and provides a new biomimetic approach to produce ordered nanostructures under mild conditions.

The rapid spread of artificial light at night (ALAN) poses myriad problems for nocturnal biodiversity. Bioluminescent taxa that communicate via glowing lures, warning signals, or courtship advertisements may have their signals obscured by artificial illumination, unless the added light is spectrally tuned to reduce its impact. Previous research has demonstrated that broad‐spectrum white light inhibits the production of courtship advertisements by male firefly beetles, yet the impact of varying wavelengths of artificial light on both members of the courtship dialogue is largely unknown. We exposed courting pairs of Photinus obscurellus fireflies to five colours of downwelling illumination, at two intensities, and recorded changes in male flash rate and flash intensity, female responsiveness, and the flash pattern composition of both sexes. All artificial light treatments significantly suppressed courtship activity. Bright amber light had the greatest impact, suggesting that ALAN which most overlaps the spectrum of firefly bioluminescence will most disrupt firefly courtship. Our findings contradict similar investigations of non‐bioluminescent taxa and raise concerns about the possibility of a universal standard for ecologically sustainable ALAN.

OBJECTIVE MicroPure is an ultrasound imaging technology used for detecting microcalcifications. This study aimed to evaluate the usefulness of the Firefly sign in ultrasonic MicroPure imaging for detecting the vulnerability of carotid plaques. METHODS Ultrasonic grey-scale imaging was used to detect carotid plaques. Ultrasonic MicroPure imaging was used to detect the Firefly sign and to determine the location and number of Firefly signs. RESULTS A total of 142 plaques were detected in 72 patients, and 62.0% were Firefly-positive plaques. The length or thickness, the risk of rupture and the percentage of vulnerable plaques were greater in the Firefly-positive plaques than in Firefly-negative plaques. The assessment of plaque vulnerability built on the 4-point Firefly scoring system showed that the area under the ROC curve was 0.750 (P

Firefly algorithm has shown good performance for solving various optimization problems. Most of the nature-inspired algorithms have the same problem which can easily trap in local optimal. To overcome this defect, a novel personalized step strategy for firefly algorithm (PSSFA) is presented. It uses large step for the optimal firefly and linearly decreasing step for the other fireflies to improve the ability of exploration. Experiments on 20 test functions show that the proposed algorithm can promote accuracy of the original method. Finally, we integrate PSSFA with k-means clustering for five datasets. The results show that PSSFA is an effective optimization algorithm.

Let G be a connected graph of order n. Some new topological indices called domination topological indices are interduced recently [10]. In this research work we calculate some domination topologica...

This paper proposes the design of an approximated fractional-order low-pass Bessel filter using various optimisation techniques. Simulated annealing (SA), nonlinear least square (NLS), and firefly ...

Sonneratia caseolaris or known as Firefly Mangrove, or Mangrove Apple is an evergreen, tropical, commonly in Tanjung Jabung Barat, Jambi Province. The nutritional content in 100 g of pedada consists of 9.21% protein, 4.81% fat, 77.57% carbohydrates and 56.74 mg of vitamin C. The nutritional potential can be exploited through efforts to diversify food into fruit juice drinks. Knowing the characteristics of physical and sensory from pedada juice was the aim of this study. The effect of adding the proportion of pedada and sugar was P1 (pedada 150 g: 0% sugar), P2 (pedada 150 g: sugar 60%), P3 (pedada 150 g: 70% sugar), P4 (200 g of pedada: 0% sugar), P5 (200 g of pedada: 60% sugar) and P6 (200 g of pedada: 70% sugar). Data were statistically tested using two way ANOVA analysis. The results of the study of pedada juice with the composition of 200 g of pedada and the addition of 70% sugar had the best characteristics. The best physical characteristics of pedada fruit juice have a pH value of 3.20 (acid), viscosity 2.88 cp, and an L * 47.19 value (close to bright). The best sensory characteristics of pedada juice are the preferred color and odor, sweet and sour taste, liquid texture, overall acceptance is preferred. The use of 200 g of Pedada with 70% sugar can be applied in making the next pedada juice, but modification is needed to improve the color and odor.

This paper presents a literature review about Particle Swarm Optimization (PSO), Firework, Firefly, Clonal Selection, and Cuckoo Search algorithms, which are among the most common natural-inspired optimization algorithms. These algorithms were tried on different benchmark functions. The obtained results were analyzed, and the performance was compared. The results showed that PSO and Firefly Search algorithms provided the best performance in the studied cases.

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

Firefly luciferases usually emit green-yellow bioluminescence at physiological pH values. However, under acidic conditions, in the presence of heavy metals and, at high temperatures they emit red bioluminescence. To understand the structural origin of bioluminescence colors and pH-sensitivity, about 20 firefly luciferases have been cloned, sequenced and investigated. The proton and metal-binding site responsible for pH- and metal sensitivity in firefly luciferases was shown to involve the residues H310, E311 and E354 in firefly luciferases. However, it is still unclear how and why pH-sensitivity arose and evolved in firefly luciferases. Here, we cloned and characterized two novel luciferase cDNAs from the fat body and lanterns of the Brazilian firefly Aspisoma lineatum. The larval fat body isozyme (AL2) has 545 residues, and displays very slow luminescence kinetics and a pH-insensitive spectrum. The adult lantern isozyme (AL1) has 548 residues, displays flash-like kinetics and pH and metal sensitive bioluminescence spectra, and is at least 10 times catalytically more efficient than AL2. Thermostability and CD studies showed that AL2 is much more stable and rigid than the AL1 isozyme. Multialignment and modelling studies show that the E310Q substitution (E310 in AL2 and Q310 in AL1) may have been critical for the origin of pH-sensitivity in firefly luciferases. The results indicate that the lantern efficient flash-emitting pH-sensitive luciferases arose from less efficient glow-type pH-insensitive luciferases found in the fat body of ancestral larval fireflies by enzyme structure flexibilization and substitution at position 310.

During the past decade, assigning objects to one of several predefined classes with higher accuracy has received considerable focus among researchers. Hence, many algorithms such as statistical algorithms have been developed to solve classification problem. Recently, considerable literature has grown up around swarm intelligence algorithms. Firefly algorithm is a swarm intelligence algorithm that imitates the behavior of the firefly in nature. In this research, a novel classifier approach based on firefly algorithm is introduced as a supervised learning algorithm. Classification based on firefly algorithm is processed by simulating the behavior of firefly in attracting other mates based on intensity and distances. The full process of the proposed algorithm comprises three phases. Feature selection phase, which is responsible for reducing features and picking the most informative features, model construction phase responsible for picking firefly class presenters, and model usage/prediction phase responsible for allocating testing or unseen samples in their relative classes using class presenters. Seven different datasets have been used to test classifier performance. Some of the datasets results were compared with ant-miner algorithm. Results proved that firefly classifier algorithm is a promising and competitive classifier.

The principle purpose of the current study is to hybridize firefly algorithm (FA) as a nature-inspired meta-heuristic developed based on the flashing patterns and biogeography-based optimization (BBO) to present a qualified algorithm in the case of optimization of steel frame (SF) structures. In the proposed meta-heuristic algorithm, FA works as a global search engine while BBO achieves the local search task. The proposed algorithm is termed as a firefly algorithm–biogeography-based optimization (FA–BBO). FA–BBO algorithm was employed for the optimization of benchmark SF problems for the validity in the case of a new algorithm. The numerical outputs demonstrate that the new FA–BBO algorithm presents a better computational performance in the comparison of the current algorithms. No sponsor

Traffic congestion problems generally caused by the increasing use of private vehicles and public transportations. In order to overcome the situation, the optimization of public transportation’s route is required particularly the urban transportation. In this research, the performance analysis of Firefly and Tabu Search algorithm is conducted to optimize eleven public transportation’s routes in Bandung. This optimization aims to increase the dispersion of public transportation’s route by expanding the scope of route that are crossed by public transportation so that it can reach the entire Bandung city and increase the driver’s income by providing the passengers easier access to public transportations in order to get to their destinations. The optimal route is represented by the route with most roads and highest number of incomes. In this research, the comparison results between the reference route and the public transportation’s optimized route increasing the dispersion of public transportation’s route to 60,58% and increasing the driver’s income to 20,03%.

TV white spaces (TVWS) can be used by Secondary Users (SUs) through Dynamic Spectrum Access (DSA) as long as they do not cause harmful interference to Primary Users (PUs). Due to spectrum scarcity, there is increasing demand for DSA. When there is a high density of SUs in a TVWS network such as cellular access to TVWS, problem of interference among SUs will arise. Possibility of harmful interference to PUs may also arise. Power and spectrum allocation optimization is therefore necessary to reduce the level of interference among SUs and to protect PUs against harmful interference. In this paper different hybrid firefly algorithms with particle swarm optimization and genetic algorithm for optimization of spectrum allocation in a TVWS network as a discrete optimization problem and that of power allocation as a continuous optimization problem are compared. Simulation was done using Matlab. Simulation results show that hybrid firefly algorithm with genetic algorithm outperforms other hybrid firefly algorithms for spectrum allocation. On the other hand, hybrid firefly algorithm with genetic algorithm and particle swarm optimization outperforms all other algorithms for power allocation as continuous optimization problem

The ecological study of synchronous firefly from the genus Pteroptyx was conducted at Sungai Rembau, Negeri Sembilan. It involved year–long sampling efforts during night time from November 2017 until October 2018. A total of 20 sampling stations were selected along 5.59 km stretch of the river with an interval ranging between 100 to 500 m. Sampling was carried out using sweeping net, randomly for one minute at each sampling station. The collected specimens were brought to the Centre of Insect Systematics UKM (CIS) for identification and reposition. A total of 1161 individuals represented by three species of firefly namely Pteroptyx tener Olivier (1148 individuals), Pteroptyx malaccae Gorham (11 individuals) and Pteroptyx asymmetria Ballantyne (2 individuals). Mostly these species were recorded on Sonneratia caseolaris. The highest percentage of firefly abundance were recorded in December 2017 (38%) while the lowest was in April 2018 (2%). Wind speed had affected significantly the firefly variation temporally while air temperature and humidity spatially affected the population of insects (p 0.05). This study helps in the monitoring of firefly population in Sungai Rembau to ensure the survival of these species.

Fireflies use bioluminescent flashes to establish a dialogue between conspecific males and females. Through this dialogue, receptive females attract conspecific males for mating. In most firefly sp...

Excursions to the estimated 55 firefly sanctuaries of Mexico have seen phenomenal growth in the past decade. Visits to three firefly entomotourism destinations in the state of Tlaxcala (Canto del B...

Pteroptyx fireflies represent an important economic insect for ecotourism. Two methods, visual counting and sweep net collection, were used to survey Pteroptyx species at 23 study sites along the coast of Thailand. P. malaccae and P. valida were the most common species across all sites with significant differences in abundance among study sites. In contrast, P. asymmetria was found only in the southern region, and P. tener was found only at one site in Surat Thani province. Pteroptyx fireflies displayed in trees whose canopies were opened to view as opposed to those blocked by other vegetation. Fireflies most often perched in the top section. Pteroptyx horizontal distribution was affected by ambient wind direction and speed. In addition, most display trees were located at prominent spots on either the inside bends or the outside bends of mangrove rivers. The principal component regression analysis was performed to determine which environmental factors might influence Pteroptyx species abundances and revealed that three Pteroptyx species appear to be influenced by different combinations of environmental variables.

With increasing pressure from many threats including firefly tourism and urbanization, rearing of Pteroptyx fireflies and reintroducing the species to habitats with low populations is a conservation challenge. Here we report a novel rearing technique for P. valida Olivier, 1909 to develop on an artificial substrate, sodium polyacrylate, together with biological observations on the egg and pupa, stages which are typically difficult to observe. The life span of P. valida under the technique was 152.7 ± 5.2 days and did not differ between sexes. Mated females laid 202.9 ± 17.0 eggs per female with 84% hatching rate. The highest larval mortality rate occurred in the first and second instars with 32% and 25%, respectively. The larvae needed four to six instars to develop to adults. The developmental time of the first to sixth larval instars ranged from 22−32 days, with the pupal stage lasting 9 days. Larvae with additional instars were observed in lab culture, and these most often became female adults, resulting in female-biased sexual size dimorphism as discussed in this study.

Continuous Stirred Tank Reactor (CSTR) is the core of numerous procedures due to its simple structure, low cost, stable and productive activity. This paper presents PID controller tuning by using f...

Life time of sensor network is very crucial and hot topic of research in wireless sensor network (WSN) from past to future. It is crucial due to system recharging and replacing the sensors are difficult and costly affair. Clustering provides some solution to extend the network lifetime. Existing clustering algorithms, such as LEACH and other heterogeneous routing protocol, can significantly minimize the power consumption on each sensor and prolong the network lifetime but not consideration of coverage network area. Balanced Energy Efficient Multi-hop (BEEM) algorithm has implemented to simulated WSN network and the selection of the cluster head on the basis of firefly (FF) optimization algorithm. Performance of the proposed hybrid Algorithm is well suited in terms of energy consumptions, stability period, network lifetime, throughput, Alive & Dead Nodes & other parameters. Proposed algorithm has showed improved result in energy consumption with firefly-BEEM over the existing BEEM.

Dilychnia (Lampyridae: Lampyrinae) is a poorly known Neotropical genus of lampyrid firefly. Descriptions of Dilychnia species were traditionally based on differences in colour pattern, which are usually not reliable for species discrimination. Here, we review and redescribe the genus Dilychnia and its species, after examining the type material of all species, and we present the first phylogenetic analysis for the group, including 70 morphological characters and 15 species. After the proposal of new taxonomic combinations, Dilychnia was recovered as monophyletic with high support. We provide a key to species identification, updated geographical ranges and illustrations of diagnostic features for all species. We transfer Lucidota propinqua and Photinus succensus to Dilychnia and describe the new species Dilychnia dumasi sp. nov. We report, for the first time, that these three taxa are nocturnal and flash with an orange-yellow light. Phenotypic diversity within the genus is most pronounced in characters involved in mate tracking (i.e. antennae, eyes and light organs).

This paper studied the complete mitochondrial genomes of three fireflies, Pygoluciola qingyu, Emeia pseudosauteri and Abscondita terminalis. We discussed the variations in the mitochondrial genomes of samples of each firefly from different populations. The mitochondrial genomes of Abs. terminalis and P. qingyu are very stable among their different populations. The mitochondrial genome of E. pseudosauteri shows some variations among the different populations, especially in the COI sequence.

This article examines the concept of the post‐Western and its presence in contemporary American television. The displacement of the Western myth in these series allows their creators to take the au...

Background: Zone Routing Protocol is evolving as an efficient hybrid routing protocol with an extremely high potentiality owing to the integration of two radically different schemes, proactive and reactive in such a way that a balance between control overhead and latency is achieved. Its performance is impacted by various network conditions such as zone radius, network size, mobility, etc. Objective: The research work described in this paper focuses on improving the performance of zone routing protocol by reducing the amount of reactive traffic which is primarily responsible for degraded network performance in case of large networks. The usage of route aggregation approach helps in reducing the routing overhead and also help achieve performance optimization. Methods: The performance of proposed protocol is assessed under varying node size and mobility. Further applied is the firefly algorithm which aims to achieve global optimization that is quite difficult to achieve due to non-linearity of functions and multimodality of algorithms. For performance evaluation a set of benchmark functions are being adopted like, packet delivery ratio and end-to-end delay to validate the proposed approach. Results: Simulation results depict better performance of leading edge firefly algorithm when compared to zone routing protocol and route aggregation based zone routing protocol. The proposed leading edge FRA-ZRP approach shows major improvement between ZRP and FRA-ZRP in Packet Delivery Ratio. FRA-ZRP outperforms traditional ZRP and RA-ZRP even in terms of End to End Delay by reducing the delay and gaining a substantial QOS improvement. Conclusion: The achievement of proposed approach can be credited to the formation on zone head and attainment of route from the head hence reduced queuing of data packets due to control packets, by adopting FRA-ZRP approach. The routing optimized zone routing protocol using Route aggregation approach and FRA augments the QoS, which is the most crucial parameter for routing performance enhancement of MANET.

Objective: The aim of this study was to explore the effects and applications of a robotic minimally invasive bowel-segmental resection, following intracorporeal anastomosis for treatment of deep in...