• Structural Engineering and Mechanics
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• v.62 no.3
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• pp.259-272
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• 2017

In this study, recently developed swarm intelligence algorithm called Social Spider Optimization (SSO) approach and its enhanced version of SSO algorithm with spider jump techniques is used to develop a structural optimization technique for steel space structures. The improved version of SSO uses adaptive randomness probability in generating new solutions. The objective function of the design optimization problem is taken as the weight of a steel space structure. Constraints' functions are implemented from American Institute of Steel Construction-Load Resistance factor design (AISC-LRFD) and Ad Hoc Committee report and practice which cover strength, serviceability and geometric requirements. Three steel space structures are optimized using both standard SSO and SSO with spider jump (SSO_SJ) algorithms and the results are compared with those available in the literature in order to investigate the performance of the proposed algorithms.

• Animal cells and systems
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• v.3 no.2
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• pp.167-172
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• 1999

We report for the first time the life history of a 'social' spider, Philoponella prominens, living in a temperate region. Philoponella prominens hibernated as immatures or subadults for 7-8 months in 1995 and 1996 from September-October to April-May in central Korea. When they emerged from their winter hibernation, a majority began their lives as commensals in the webs of other species. As the mating season approached, however, commensal spiders switched to become colonial or solitary. The mating season began in early June and lasted until early August. Newly-hatched spiderlings began to appear in the field in late June. They formed a colony by building their webs connected to the mother's by using pan of the mother's web as supporting substrates. As the season progressed, however, some of the colonial spiderlings became commensal or solitary individuals. Our field observations suggest that Philoponella prominens form colonies or commensal associations to reduce the web-building cost.

• Journal of Ecology and Environment
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• v.30 no.4
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• pp.315-318
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• 2007

Cooperative or non-territorial permanently social spiders are believed to have evolved from species showing subsocial maternal care. The transition from subsocial to cooperative social groups probably involved a transition from an outbreeding breeding system to one with inbreeding. Nepotistic recognition among siblings should facilitate the evolution of social cooperation through avoidance of inbreeding and maintenance of mutual tolerance between siblings. We conducted experiments to determine whether a mechanism for sibling recognition is present in the subsocial spider, Coelotes terrestris which displays extended maternal care in the form of food provisioning. The numbers of surviving individuals within unfed groups were observed and compared between non-sibling groups of ten spiderlings and groups of ten siblings. The number of survivors differed significantly between groups, with consistently fewer spiderlings surviving in the non-sibling groups than the sibling groups over the study period. This result suggests that sibling recognition and nepotism do occur in this subsocial species. The nepotism involved in the maternal social organization of the Coelotes might be an example of a preadaptation facilitating the evolution of permanent social life.

• Journal of Ecology and Environment
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• v.30 no.3
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• pp.277-280
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• 2007

Social spiders consistently show highly female-biased sex ratios. However, the sex ratio of subsocial spiders, which have been suggested as an intermediate stage of the evolutionary pathway towards permanent sociality, is generally unknown. We investigated the sex ratio and approximate date of fertilization of the subsocial spider, Amaurobius ferox Walckenaer (Araneae: Amaurobiidae). Investigation over 2 years revealed that sex ratio of A. ferox was consistent across years and averaged 0.49. By early May $(1^{st}{\sim}10^{th})$, 66.6% of female A. ferox observed in the field had already been inseminated, and by late May $(21^{st}{\sim}31^{th})$, 95.4% of females had been inseminated. This result suggests that A. ferox need a long time or cold temperatures to prepare them for reproduction after the developmental attainment of the adult stage.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.259-276
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• 2024

The undrained shear strength is widely acknowledged as a fundamental mechanical property of soil and is considered a critical engineering parameter. In recent years, researchers have employed various methodologies to evaluate the shear strength of soil under undrained conditions. These methods encompass both numerical analyses and empirical techniques, such as the cone penetration test (CPT), to gain insights into the properties and behavior of soil. However, several of these methods rely on correlation assumptions, which can lead to inconsistent accuracy and precision. The study involved the development of innovative methods using extreme gradient boosting (XGB) to predict the pile set-up component "A" based on two distinct data sets. The first data set includes average modified cone point bearing capacity (q_t), average wall friction (f_s), and effective vertical stress (σ_vo), while the second data set comprises plasticity index (PI), soil undrained shear cohesion (S_u), and the over consolidation ratio (OCR). These data sets were utilized to develop XGBoost-based methods for predicting the pile set-up component "A". To optimize the internal hyperparameters of the XGBoost model, four optimization algorithms were employed: Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), Arithmetic Optimization Algorithm (AOA), and Sine Cosine Optimization Algorithm (SCOA). The results from the first data set indicate that the XGBoost model optimized using the Arithmetic Optimization Algorithm (XGB - AOA) achieved the highest accuracy, with R2 values of 0.9962 for the training part and 0.9807 for the testing part. The performance of the developed models was further evaluated using the RMSE, MAE, and VAF indices. The results revealed that the XGBoost model optimized using XGBoost - AOA outperformed other models in terms of accuracy, with RMSE, MAE, and VAF values of 0.0078, 0.0015, and 99.6189 for the training part and 0.0141, 0.0112, and 98.0394 for the testing part, respectively. These findings suggest that XGBoost - AOA is the most accurate model for predicting the pile set-up component.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.13-16
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• 2011

최근 들어 네트워크1로 연결된 체계들을 효율적으로 운영하여 최대의 효과를 달성하기 많은 연구들이 수행되고 있다. 하지만 지휘통제체계 네트워크 구조 분석에 관한 연구는 상대적으로 미흡한 실정이다. 따라서 본 연구에서는 지휘통제체계 중 육군의 SPIDER체계를 대상으로 소설 네트워크 분석 (Social Network analysis)기법을 이용하여 중앙성분석과 시각화(Visualization)를 통해 핵심노드를 식별하는 arms value 알고리즘을 제안하고 분석 결과를 기반으로 TICN체계 전력화시 기초 연구자료로 활용하고자 한다.