Local adaptation is an important process that drives the evolution of populations within species, and it can be generally expressed by the higher fitness of individuals raised in their native habitats versus in a fore...Local adaptation is an important process that drives the evolution of populations within species, and it can be generally expressed by the higher fitness of individuals raised in their native habitats versus in a foreign location. The influence of local adaptation is especially prominent in species that subsist in small and/or highly isolated populations. This study evaluated whether the federally endangered Karner blue butterfly, Lycaeides melissa samuelis (Lepidoptera: Lycaenidae) is locally adapted to its exclusive larval host plant, the wild lupine (Lupinus perennis). To test for local adaptation, individuals from a laboratory-raised colony were reared on wild lupine plants from populations belonging to either their native (Indiana) or a foreign (Michigan and Wisconsin) region. For this purpose, lupine plants from the different populations were grown in a common garden in growth chambers, and one Karner blue larva was placed on each plant. Fitness traits related to growth and development were recorded for each butterfly across populations. Days from hatching to pupation and eclosion showed gender-specific significant differences across wild lupine populations and plant genotypes (within populations). The percent survival of butterflies (from hatching to eclosion) also differed among plants from different populations. These results indicate that wild lupine sources can affect some developmental traits of Karner blue butterflies. However, growth-related traits, such as pupal and adult weight of individuals reared in plants from native populations did not differ from those of foreign regions. The apparent absence of local adaptation to wild lupine suggests that, at least, some individuals of this species could be translocated from native populations to foreign reintroduction sites without experiencing decreased fitness levels. However, future studies including more populations across the geographical range of this butterfly are recommended to evaluate other environmental factors that could influence adaptation on a wider spatial scale.展开更多
Autism spectrum disorder(ASD)can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics,like changes in behavior,social disabilities,and difficulty communi...Autism spectrum disorder(ASD)can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics,like changes in behavior,social disabilities,and difficulty communicating with others.Eye tracking(ET)has become a useful method to detect ASD.One vital aspect of moral erudition is the aptitude to have common visual attention.The eye-tracking approach offers valuable data regarding the visual behavior of children for accurate and early detection.Eye-tracking data can offer insightful information about the behavior and thought processes of people with ASD,but it is important to be aware of its limitations and to combine it with other types of data and assessment techniques to increase the precision of ASD detection.It operates by scanning the paths of eyes for extracting a series of eye projection points on images for examining the behavior of children with autism.The purpose of this research is to use deep learning to identify autistic disorders based on eye tracking.The Chaotic Butterfly Optimization technique is used to identify this specific disturbance.Therefore,this study develops an ET-based Autism Spectrum Disorder Diagnosis using Chaotic Butterfly Optimization with Deep Learning(ETASD-CBODL)technique.The presented ETASDCBODL technique mainly focuses on the recognition of ASD via the ET and DL models.To accomplish this,the ETASD-CBODL technique exploits the U-Net segmentation technique to recognize interested AREASS.In addition,the ETASD-CBODL technique employs Inception v3 feature extraction with CBO algorithm-based hyperparameter optimization.Finally,the long-shorttermmemory(LSTM)model is exploited for the recognition and classification of ASD.To assess the performance of the ETASD-CBODL technique,a series of simulations were performed on datasets from the figure-shared data repository.The experimental values of accuracy(99.29%),precision(98.78%),sensitivity(99.29%)and specificity(99.29%)showed a better performance in the ETASD-CBODL technique over recent approaches.展开更多
The main task of thyroid hormones is controlling the metabolism rate of humans,the development of neurons,and the significant growth of reproductive activities.In medical science,thyroid disorder will lead to creating ...The main task of thyroid hormones is controlling the metabolism rate of humans,the development of neurons,and the significant growth of reproductive activities.In medical science,thyroid disorder will lead to creating thyroiditis and thyroid cancer.The two main thyroid disorders are hyperthyroidism and hypothyroidism.Many research works focus on the prediction of thyroid disorder.To improve the accuracy in the classification of thyroid disorder this paper pro-poses optimization-based feature selection by using differential evolution with the Butterfly optimization algorithm(DE-BOA).For the classifier fuzzy C-means algorithm(FCM)is used.The proposed DEBOA-FCM is evaluated with para-metric metric measures of sensitivity,specificity,and accuracy.In this work,the thyroid disease dataset collected from the machine learning University of Cali-fornia Irvine(UCI)database was used.The accuracy rate for the Differential Evo-lutionary algorithm got 0.884,the Butterfly optimization algorithm got 0.906,Fuzzy C-Means algorithm got 0.899 and DEBOA+Focused Concept Miner(FCM)proposed work 0.943.展开更多
Cloud computing technology provides flexible,on-demand,and completely controlled computing resources and services are highly desirable.Despite this,with its distributed and dynamic nature and shortcomings in virtualiz...Cloud computing technology provides flexible,on-demand,and completely controlled computing resources and services are highly desirable.Despite this,with its distributed and dynamic nature and shortcomings in virtualization deployment,the cloud environment is exposed to a wide variety of cyber-attacks and security difficulties.The Intrusion Detection System(IDS)is a specialized security tool that network professionals use for the safety and security of the networks against attacks launched from various sources.DDoS attacks are becoming more frequent and powerful,and their attack pathways are continually changing,which requiring the development of new detection methods.Here the purpose of the study is to improve detection accuracy.Feature Selection(FS)is critical.At the same time,the IDS’s computational problem is limited by focusing on the most relevant elements,and its performance and accuracy increase.In this research work,the suggested Adaptive butterfly optimization algorithm(ABOA)framework is used to assess the effectiveness of a reduced feature subset during the feature selection phase,that was motivated by this motive Candidates.Accurate classification is not compromised by using an ABOA technique.The design of Deep Neural Networks(DNN)has simplified the categorization of network traffic into normal and DDoS threat traffic.DNN’s parameters can be finetuned to detect DDoS attacks better using specially built algorithms.Reduced reconstruction error,no exploding or vanishing gradients,and reduced network are all benefits of the changes outlined in this paper.When it comes to performance criteria like accuracy,precision,recall,and F1-Score are the performance measures that show the suggested architecture outperforms the other existing approaches.Hence the proposed ABOA+DNN is an excellent method for obtaining accurate predictions,with an improved accuracy rate of 99.05%compared to other existing approaches.展开更多
M.Butterfly,written by David Henry Hwang,is one of the most influential plays in contemporary American dramatic his-tory.Hwang incorporates a stereotypical fantasy into his play,involving conflicts and misunderstandin...M.Butterfly,written by David Henry Hwang,is one of the most influential plays in contemporary American dramatic his-tory.Hwang incorporates a stereotypical fantasy into his play,involving conflicts and misunderstandings between the East and theWest,between men and women.Through the analysis of the construction of the Orientalist"Madame Butterfly Fantasy"in M.Butterfly,this paper analyzes sexual prejudice and racial bias embedded in the"Fantasy".展开更多
"Days of the Butterfly"was one of Alice Munro's short stories written in 1950 s, when she was still a new hand. This paper will mainly focus on the development of the main characters in the story, includ..."Days of the Butterfly"was one of Alice Munro's short stories written in 1950 s, when she was still a new hand. This paper will mainly focus on the development of the main characters in the story, including Myra, the black girl who was the heroine, the teacher Miss Darling, and the Narrator"I". In portraying these characters, Munro adopted several writing techniques including conversation, detailed description, psychological description and so on. She vividly transferred those characters into paper.展开更多
Many biological surface are hydrophobic because of their complicated composition and surface microstructure. Eleven species (four families) of butterflies were selected to study their micro-, nano-structure and super...Many biological surface are hydrophobic because of their complicated composition and surface microstructure. Eleven species (four families) of butterflies were selected to study their micro-, nano-structure and super-hydrophobic characteristic by means of Confocal Light Microscopy, Scanning Electron Microscopy and Contact Angle Measurement. The contact an- gles of water droplets on the butterfly wing surface were consistently measured to be about 150 ? and 100 ? with and without the squamas, respectively. The dust on the surface can be easily cleaned by moving spherical droplets when the inclining angle is larger than 3 ?. It can be concluded that the butterfly wing surface possess a super-hydrophobic, water-repellent, self-cleaning, or “Lotus-effect”characteristic. The contact angle measurement of water droplets on the wing surface with and without the squamas showed that the water-repellent characteristic is a consequence of the microstructure of the squamas. Each water droplet (diameter 2 mm) can cover about 700 squamas with a size of 40 m×80 m of each squama. The regular riblets with a width of 1000 nm to 1500 nm are clearly observed on each single squama. Such nanostructure should play a very important role in their super-hydrophobic and self-cleaning characteristic.展开更多
The contact angles of distilled water and methanol solution on the wings of butterflies were determined by a visual contact angle measuring system. The scale structures of the wings were observed using scanning electr...The contact angles of distilled water and methanol solution on the wings of butterflies were determined by a visual contact angle measuring system. The scale structures of the wings were observed using scanning electron microscopy, The influence of the scale micro- and ultra-structure on the wettability was investigated. Results show that the contact angle of distilled water on the wing surfaces varies from 134.0° to 159.2°. High hydrophobicity is found in six species with contact angles greater than 150°. The wing surfaces of some species are not only hydrophobic but also resist the wetting by methanol solution with 55% concentration. Only two species in Parnassius can not resist the wetting because the micro-structure (spindle-like shape) and ultra-structure (pinnule-like shape) of the wing scales are remarkably different from that of other species. The concentration of methanol solution for the occurrence of spreading/wetting on the wing surfaces of different species varies from 70% to 95%. After wetting by methanol solution for 10 min, the distilled water contact angle on the wing surface increases by 0.8°-2.1°, showing the promotion of capacity against wetting by distilled water.展开更多
There are billions of tiny scales on the butterfly wings, which array regularly as the tiles on the roof. Such tilts can form various colors of the wing and afford the species many abilities to survive and propagate. ...There are billions of tiny scales on the butterfly wings, which array regularly as the tiles on the roof. Such tilts can form various colors of the wing and afford the species many abilities to survive and propagate. Morphological experiments on the wing scales of six butterfly species living in northeast of China were conducted. By the optics microscope; the form, geometry dimension and array of the scales were observed generally. By using scanning electron microscope (SEM), the 2D scanning and measurement were carried out and the surface micro configurations of scales were observed. The dimension and microstructure characteristics of the cross section of single scale were achieved through transmission electron microscope (TEM). Finally, by using 3D software, three 3D models were described and the 3D visual effect was achieved. This work can put forward a basic method for the future study on the morphology of biological microstructure.展开更多
The forward flight of a model butterfly was stud- ied by simulation using the equations of motion coupled with the Navier-Stokes equations. The model butterfly moved under the action of aerodynamic and gravitational f...The forward flight of a model butterfly was stud- ied by simulation using the equations of motion coupled with the Navier-Stokes equations. The model butterfly moved under the action of aerodynamic and gravitational forces, where the aerodynamic forces were generated by flapping wings which moved with the body, allowing the body os- cillations of the model butterfly to be simulated. The main results are as follows: (1) The aerodynamic force produced by the wings is approximately perpendicular to the long-axis of body and is much larger in the downstroke than in the up- stroke. In the downstroke the body pitch angle is small and the large aerodynamic force points up and slightly backward, giving the weight-supporting vertical force and a small neg- ative horizontal force, whilst in the upstroke, the body an- gle is large and the relatively small aerodynamic force points forward and slightly downward, giving a positive horizon- tal force which overcomes the body drag and the negative horizontal force generated in the downstroke. (2) Pitching oscillation of the butterfly body plays an equivalent role of the wing-rotation of many other insects. (3) The body-mass- specific power of the model butterfly is 33.3 W/kg, not very different from that of many other insects, e.g., fruitflies and dragonflies.展开更多
Since the introduction of the Internet of Things(IoT),several researchers have been exploring its productivity to utilize and organize the spectrum assets.Cognitive radio(CR)technology is characterized as the best asp...Since the introduction of the Internet of Things(IoT),several researchers have been exploring its productivity to utilize and organize the spectrum assets.Cognitive radio(CR)technology is characterized as the best aspirant for wireless communications to augment IoT competencies.In the CR networks,secondary users(SUs)opportunistically get access to the primary users(PUs)spectrum through spectrum sensing.The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs.Therefore,several cooperative SUs are engaged in cooperative spectrum sensing(CSS)to ensure reliable sensing results.In CSS,security is still a major concern for the researchers to safeguard the fusion center(FC)against abnormal sensing reports initiated by the malicious users(MUs).In this paper,butterfly optimization algorithm(BOA)-based soft decision method is proposed to find an optimized weighting coefficient vector correlated to the SUs sensing notifications.The coefficient vector is utilized in the soft decision rule at the FC before making any global decision.The effectiveness of the proposed scheme is compared for a variety of parameters with existing schemes through simulation results.The results confirmed the supremacy of the proposed BOA scheme in both the normal SUs’environment and when lower and higher SNRs information is carried by the different categories of MUs.展开更多
文摘Local adaptation is an important process that drives the evolution of populations within species, and it can be generally expressed by the higher fitness of individuals raised in their native habitats versus in a foreign location. The influence of local adaptation is especially prominent in species that subsist in small and/or highly isolated populations. This study evaluated whether the federally endangered Karner blue butterfly, Lycaeides melissa samuelis (Lepidoptera: Lycaenidae) is locally adapted to its exclusive larval host plant, the wild lupine (Lupinus perennis). To test for local adaptation, individuals from a laboratory-raised colony were reared on wild lupine plants from populations belonging to either their native (Indiana) or a foreign (Michigan and Wisconsin) region. For this purpose, lupine plants from the different populations were grown in a common garden in growth chambers, and one Karner blue larva was placed on each plant. Fitness traits related to growth and development were recorded for each butterfly across populations. Days from hatching to pupation and eclosion showed gender-specific significant differences across wild lupine populations and plant genotypes (within populations). The percent survival of butterflies (from hatching to eclosion) also differed among plants from different populations. These results indicate that wild lupine sources can affect some developmental traits of Karner blue butterflies. However, growth-related traits, such as pupal and adult weight of individuals reared in plants from native populations did not differ from those of foreign regions. The apparent absence of local adaptation to wild lupine suggests that, at least, some individuals of this species could be translocated from native populations to foreign reintroduction sites without experiencing decreased fitness levels. However, future studies including more populations across the geographical range of this butterfly are recommended to evaluate other environmental factors that could influence adaptation on a wider spatial scale.
基金funded by the Deanship for Research&Innovation,Ministry of Education in Saudi Arabia,for funding this research work through Project Number:IFP22UQU4281768DSR145.
文摘Autism spectrum disorder(ASD)can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics,like changes in behavior,social disabilities,and difficulty communicating with others.Eye tracking(ET)has become a useful method to detect ASD.One vital aspect of moral erudition is the aptitude to have common visual attention.The eye-tracking approach offers valuable data regarding the visual behavior of children for accurate and early detection.Eye-tracking data can offer insightful information about the behavior and thought processes of people with ASD,but it is important to be aware of its limitations and to combine it with other types of data and assessment techniques to increase the precision of ASD detection.It operates by scanning the paths of eyes for extracting a series of eye projection points on images for examining the behavior of children with autism.The purpose of this research is to use deep learning to identify autistic disorders based on eye tracking.The Chaotic Butterfly Optimization technique is used to identify this specific disturbance.Therefore,this study develops an ET-based Autism Spectrum Disorder Diagnosis using Chaotic Butterfly Optimization with Deep Learning(ETASD-CBODL)technique.The presented ETASDCBODL technique mainly focuses on the recognition of ASD via the ET and DL models.To accomplish this,the ETASD-CBODL technique exploits the U-Net segmentation technique to recognize interested AREASS.In addition,the ETASD-CBODL technique employs Inception v3 feature extraction with CBO algorithm-based hyperparameter optimization.Finally,the long-shorttermmemory(LSTM)model is exploited for the recognition and classification of ASD.To assess the performance of the ETASD-CBODL technique,a series of simulations were performed on datasets from the figure-shared data repository.The experimental values of accuracy(99.29%),precision(98.78%),sensitivity(99.29%)and specificity(99.29%)showed a better performance in the ETASD-CBODL technique over recent approaches.
基金Taif University Researchers are supporting project number(TURSP-2020/211),Taif University,Taif,Saudi Arabia.
文摘The main task of thyroid hormones is controlling the metabolism rate of humans,the development of neurons,and the significant growth of reproductive activities.In medical science,thyroid disorder will lead to creating thyroiditis and thyroid cancer.The two main thyroid disorders are hyperthyroidism and hypothyroidism.Many research works focus on the prediction of thyroid disorder.To improve the accuracy in the classification of thyroid disorder this paper pro-poses optimization-based feature selection by using differential evolution with the Butterfly optimization algorithm(DE-BOA).For the classifier fuzzy C-means algorithm(FCM)is used.The proposed DEBOA-FCM is evaluated with para-metric metric measures of sensitivity,specificity,and accuracy.In this work,the thyroid disease dataset collected from the machine learning University of Cali-fornia Irvine(UCI)database was used.The accuracy rate for the Differential Evo-lutionary algorithm got 0.884,the Butterfly optimization algorithm got 0.906,Fuzzy C-Means algorithm got 0.899 and DEBOA+Focused Concept Miner(FCM)proposed work 0.943.
文摘Cloud computing technology provides flexible,on-demand,and completely controlled computing resources and services are highly desirable.Despite this,with its distributed and dynamic nature and shortcomings in virtualization deployment,the cloud environment is exposed to a wide variety of cyber-attacks and security difficulties.The Intrusion Detection System(IDS)is a specialized security tool that network professionals use for the safety and security of the networks against attacks launched from various sources.DDoS attacks are becoming more frequent and powerful,and their attack pathways are continually changing,which requiring the development of new detection methods.Here the purpose of the study is to improve detection accuracy.Feature Selection(FS)is critical.At the same time,the IDS’s computational problem is limited by focusing on the most relevant elements,and its performance and accuracy increase.In this research work,the suggested Adaptive butterfly optimization algorithm(ABOA)framework is used to assess the effectiveness of a reduced feature subset during the feature selection phase,that was motivated by this motive Candidates.Accurate classification is not compromised by using an ABOA technique.The design of Deep Neural Networks(DNN)has simplified the categorization of network traffic into normal and DDoS threat traffic.DNN’s parameters can be finetuned to detect DDoS attacks better using specially built algorithms.Reduced reconstruction error,no exploding or vanishing gradients,and reduced network are all benefits of the changes outlined in this paper.When it comes to performance criteria like accuracy,precision,recall,and F1-Score are the performance measures that show the suggested architecture outperforms the other existing approaches.Hence the proposed ABOA+DNN is an excellent method for obtaining accurate predictions,with an improved accuracy rate of 99.05%compared to other existing approaches.
文摘M.Butterfly,written by David Henry Hwang,is one of the most influential plays in contemporary American dramatic his-tory.Hwang incorporates a stereotypical fantasy into his play,involving conflicts and misunderstandings between the East and theWest,between men and women.Through the analysis of the construction of the Orientalist"Madame Butterfly Fantasy"in M.Butterfly,this paper analyzes sexual prejudice and racial bias embedded in the"Fantasy".
文摘"Days of the Butterfly"was one of Alice Munro's short stories written in 1950 s, when she was still a new hand. This paper will mainly focus on the development of the main characters in the story, including Myra, the black girl who was the heroine, the teacher Miss Darling, and the Narrator"I". In portraying these characters, Munro adopted several writing techniques including conversation, detailed description, psychological description and so on. She vividly transferred those characters into paper.
文摘Many biological surface are hydrophobic because of their complicated composition and surface microstructure. Eleven species (four families) of butterflies were selected to study their micro-, nano-structure and super-hydrophobic characteristic by means of Confocal Light Microscopy, Scanning Electron Microscopy and Contact Angle Measurement. The contact an- gles of water droplets on the butterfly wing surface were consistently measured to be about 150 ? and 100 ? with and without the squamas, respectively. The dust on the surface can be easily cleaned by moving spherical droplets when the inclining angle is larger than 3 ?. It can be concluded that the butterfly wing surface possess a super-hydrophobic, water-repellent, self-cleaning, or “Lotus-effect”characteristic. The contact angle measurement of water droplets on the wing surface with and without the squamas showed that the water-repellent characteristic is a consequence of the microstructure of the squamas. Each water droplet (diameter 2 mm) can cover about 700 squamas with a size of 40 m×80 m of each squama. The regular riblets with a width of 1000 nm to 1500 nm are clearly observed on each single squama. Such nanostructure should play a very important role in their super-hydrophobic and self-cleaning characteristic.
文摘The contact angles of distilled water and methanol solution on the wings of butterflies were determined by a visual contact angle measuring system. The scale structures of the wings were observed using scanning electron microscopy, The influence of the scale micro- and ultra-structure on the wettability was investigated. Results show that the contact angle of distilled water on the wing surfaces varies from 134.0° to 159.2°. High hydrophobicity is found in six species with contact angles greater than 150°. The wing surfaces of some species are not only hydrophobic but also resist the wetting by methanol solution with 55% concentration. Only two species in Parnassius can not resist the wetting because the micro-structure (spindle-like shape) and ultra-structure (pinnule-like shape) of the wing scales are remarkably different from that of other species. The concentration of methanol solution for the occurrence of spreading/wetting on the wing surfaces of different species varies from 70% to 95%. After wetting by methanol solution for 10 min, the distilled water contact angle on the wing surface increases by 0.8°-2.1°, showing the promotion of capacity against wetting by distilled water.
基金The authors are grateful to the financial support provided by the Key Project of Chinese Ministry of Education (No. 105059);Fok Ying Tong Education Foundation (No.101020);the Natural Science Foundation of China (No. 30570235,50635030 ).
文摘There are billions of tiny scales on the butterfly wings, which array regularly as the tiles on the roof. Such tilts can form various colors of the wing and afford the species many abilities to survive and propagate. Morphological experiments on the wing scales of six butterfly species living in northeast of China were conducted. By the optics microscope; the form, geometry dimension and array of the scales were observed generally. By using scanning electron microscope (SEM), the 2D scanning and measurement were carried out and the surface micro configurations of scales were observed. The dimension and microstructure characteristics of the cross section of single scale were achieved through transmission electron microscope (TEM). Finally, by using 3D software, three 3D models were described and the 3D visual effect was achieved. This work can put forward a basic method for the future study on the morphology of biological microstructure.
基金supported by the National Natural Science Foundation of China(11232002)the Ph.D.Student Foundation of Chinese Ministry of Education(30400002011105001)
文摘The forward flight of a model butterfly was stud- ied by simulation using the equations of motion coupled with the Navier-Stokes equations. The model butterfly moved under the action of aerodynamic and gravitational forces, where the aerodynamic forces were generated by flapping wings which moved with the body, allowing the body os- cillations of the model butterfly to be simulated. The main results are as follows: (1) The aerodynamic force produced by the wings is approximately perpendicular to the long-axis of body and is much larger in the downstroke than in the up- stroke. In the downstroke the body pitch angle is small and the large aerodynamic force points up and slightly backward, giving the weight-supporting vertical force and a small neg- ative horizontal force, whilst in the upstroke, the body an- gle is large and the relatively small aerodynamic force points forward and slightly downward, giving a positive horizon- tal force which overcomes the body drag and the negative horizontal force generated in the downstroke. (2) Pitching oscillation of the butterfly body plays an equivalent role of the wing-rotation of many other insects. (3) The body-mass- specific power of the model butterfly is 33.3 W/kg, not very different from that of many other insects, e.g., fruitflies and dragonflies.
基金This work was supported in part by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2016R1C1B1014069)in part by the National Research Foundation of Korea(NRF)funded by the Korea government(MIST)(No.2021R1A2C1013150).
文摘Since the introduction of the Internet of Things(IoT),several researchers have been exploring its productivity to utilize and organize the spectrum assets.Cognitive radio(CR)technology is characterized as the best aspirant for wireless communications to augment IoT competencies.In the CR networks,secondary users(SUs)opportunistically get access to the primary users(PUs)spectrum through spectrum sensing.The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs.Therefore,several cooperative SUs are engaged in cooperative spectrum sensing(CSS)to ensure reliable sensing results.In CSS,security is still a major concern for the researchers to safeguard the fusion center(FC)against abnormal sensing reports initiated by the malicious users(MUs).In this paper,butterfly optimization algorithm(BOA)-based soft decision method is proposed to find an optimized weighting coefficient vector correlated to the SUs sensing notifications.The coefficient vector is utilized in the soft decision rule at the FC before making any global decision.The effectiveness of the proposed scheme is compared for a variety of parameters with existing schemes through simulation results.The results confirmed the supremacy of the proposed BOA scheme in both the normal SUs’environment and when lower and higher SNRs information is carried by the different categories of MUs.