Similar Behavior Research Articles

Can you be unique by wearing fast fashion? Exploring South African contemporary female consumers’ creative behaviour towards fast fashion uniqueness

Contemporary female consumers manage their appearance through current fashion trends and styles. The desire to be unique drives consumers to develop appearances that are perceived to differentiate them from others. In a world where fast fashion delivers multiple copies of one fashion item, it is difficult to imagine if fast fashion could deliver a unique appearance. Little research has considered the possibility of achieving fast fashion uniqueness. The behaviour of South African female consumers and their desire for fast fashion uniqueness as proposed in the theory of the need for uniqueness has also not been researched. The purpose of this study was to determine the meaning of fast fashion uniqueness and the behaviour related to the dimensions of uniqueness. An exploratory descriptive qualitative study was used to determine the fast fashion unique experiences of female fashion shoppers in South Africa. Thematic analysis of electronic individual interviews revealed the meaning of uniqueness manifested through mechanisms of self-expression and design creativity. Contribution to uniqueness theory is expressed through a socially acceptable appearance typified by creative choice counter-conformity behaviour. Unpopular choice counter-conformity behaviour was expressed through precautionary and guarding behaviour. Avoidance of similarity behaviour resulted in similarity acceptance behaviour characterized by helplessness and acceptance of fast fashion duplication, due to the inability to avoid similarity experienced during fast-fashion retail purchases. Coping strategies and avoidance behaviour tactics were applied to avoid fashion similarities. Fashion creativity serves as the mechanism through which contemporary fast fashion consumers achieve fast fashion appearance uniqueness. Fast fashion retailers in South Africa may need to improvise fashion offerings and give consumers alternative appearances to accommodate the creative uniqueness that female consumers are compelled to apply to achieve fast fashion uniqueness.

Discovery of Cloud Applications from Logs

Continuous discovery and update of applications or their boundaries running in cloud environments in an automatic way is a highly required function of modern data center operation solutions. Prior attempts to address this problem within various products or projects were/are applying rule-driven approaches or machine learning techniques on specific types of data–network traffic as well as property/configuration data of infrastructure objects, which all have their drawbacks in effectively identifying roles of those resources. The current proposal (ADLog) leverages log data of sources, which contain incomparably richer contextual information, and demonstrates a reliable way of discriminating application objects. Specifically, using native constructs of VMware Aria Operations for Logs in terms of event types and their distributions, we group those entities, which then can be potentially enriched with indicative tags automatically and recommended for further management tasks and policies. Our methods differentiate not only diverse kinds of applications, but also their specific deployments, thus providing hierarchical representation of the applications in time and topology. For several applications under Aria Ops management in our experimental test bed, we discover those in terms of similarity behavior of their components with a high accuracy. The validation of the proposal paves the path for an AI-driven solution in cloud management scenarios.

Contribution of very massive stars to the sulfur abundance in star-forming galaxies: Role of pair-instability supernovae

Context. Recent work presented increasing evidence of high non-constant S/O abundance ratios observed in star-forming metal-poor galaxies that deviated from the constant canonical S/O across a wide range of O/H abundances. Similar peculiarly high Fe/O ratios have also recently been detected. Aims. We investigate whether these high S/O ratios at low metallicities could be explained when the process of pair-instability supernovae (PISN) in chemical modelling is included, through which a similar behaviour of the Fe/O ratios was reproduced successfully. Methods. We used chemical evolution models that considered the stages of PISN in the previously published yields and adopted a suitable initial mass function (IMF) to characterize this evolutionary stage appropriately. Results. The peculiarly high values and the behaviour of the observed S/O versus O/H relation can be reproduced when the ejecta of very massive stars that go through the process of PISN are taken into account. Additionally, a bimodal top-heavy IMF and an initial strong burst of star formation are required to reach the reported high S/O values. Conclusions. We show that the role of very massive stars going through the process of PISN should be taken into account to explain the chemical enrichment of sulphur and oxygen in metal-poor star-forming regions.

Tit-For-Tat and Win Stay-Lose Shift strategies via memory-two

Decisions in many dilemmas are based on a combination of factors, including as incentive, punishment, reputation, and memory. The impact of memory information on cooperative evolution in multi-round games is a decision-making process in group evolution. The iterated prisoner’s dilemma is an excellent model for the development of cooperation amongst the payoff-maximizing individuals. Since tit-for-tat proved successful in Axelrod’s repeated prisoner’s dilemma tournaments, there has been a great deal of interest in creating new strategies. Every iterative prisoner’s dilemma method bases its decision-making on a specific duration of past contacts with the opponent, which is referred to as the memory’s size. This study examines the impact of strategy memory size on the evolutionary stability of n-person iterated prisoner’s dilemma strategies. In this paper, we address the role that memory plays in decision-making. We interested in the model of the Iterated Prisoner’s Dilemma game for three players with memory two, and we will look at strategies with similar behavior, such as Tit-For-Tat (TFT) strategies as well as Win Stay-Lose Shift (WSLS) strategies. As a result of this paper, we have shown that the effect of memory length is almost non-existent in the competitions of strategies that we studied.

A maximum satisfaction consensus-based large-scale group decision-making in social network considering limited compromise behavior

With the enrichment of social platforms, large-scale group decision-making (LSGDM) in social networks has gradually taken shape. In practice, experts may show limited compromise behavior during consensus reaching process (CRP), which may lead to bias or even failure in decision-making results. To tackle this issue, considering limited compromise behavior, this paper proposes a maximum satisfaction consensus (MSC) model, and focusing on LSGDM with fuzzy preference relation in social networks. Firstly, an expert weight determination algorithm integrating the interactive weights and individual weights is constructed. The interactive weights are determined by social influence strength, while the individual weights are measured by the compromise degree of limited compromise behavior and the consistency level of preferences. Subsequently, a grey clustering method is developed to classify experts into subgroups, considering both opinions similarity and limited compromise behavior similarity. In CRP, considering the limited compromise behavior, an MSC model under the limited budget determined by the minimum cost consensus (MCC) model is proposed. Based on MSC and MCC models, satisfaction-cost ratio is defined to measure the efficiency of CRP. Finally, a case study of selecting of shared bicycle operators and further discussion are conducted to verify the feasibility and superiority of the study.

A Data-driven Approach for Planning Stock Keeping Unit (SKU) in a Steel Supply Chain

In response to the growing complexities in supply chain management, there is an imperative need for a data-driven methodology aimed at optimizing inventory allocation strategies. The purpose of this research is to enhance the efficiency of allocation and operational scheduling, particularly concerning the stock keeping units (SKUs). To achieve this, one year's operational data from a specific organization's SKUs is taken and machine learning tools are employed on the data collected. These tools are instrumental in identifying clusters of SKUs that exhibit similar behaviour. Consequently, this research offers recommendations for rational inventory allocation strategies that are finely attuned to the unique characteristics of each SKU cluster. Results obtained reveals substantial disparities between the recommended strategies for the organization's SKUs and those typically found in the literature such as same strategy cannot be used for all different types for products. This underscores the critical importance of adopting a tailored approach to supply chain management. Furthermore, the research demonstrates the remarkable efficiency of unsupervised machine learning algorithms in determining the optimal number of segments within the SKUs. The current research differentiates from others in a way that in most of the research, the holistic data-driven approach is underutilized, right from the selection of the clustering algorithm to the validation of segments.

A Novel Hypothesis for Migraine Disease Mechanism: The Creation of a New Attractor Responsible for Migraine Disease Symptoms

Migraine Disease (MD) is one of the common primary headaches that can prevent patients from their everyday life. Despite the high prevalence, the pathophysiology of the disease has not been clearly understood yet. Here, the brain is considered as a dynamical system. The Chua’s circuit with a chaotic attractor is the proposed model. This attractor has a one-scroll mode representing a healthy brain and a double-scroll mode representing a migraine sufferer brain. We believe that MD and Chua’s systems have certain behavioral similarities. The boundaries of the attractor are the sensitive brain areas in which any small trigger can start the ictal phase of the migraine. The transition from the inter-ictal phase to the ictal phase in migraine patients occurs due to a decrease in serotonin levels when the brain is within the boundaries of the first attractor. Here, this is the results of the increase of system parameters. In addition, the transition from the ictal phase to the inter-ictal phase in a migraine sufferer brain is caused by a disruption of coordination in the brain’s structures and this lasts for a certain period for every migraine patient. The structures which are the result of the Migraine Generator Network (MGN) and Cortical Spreading Depression (CSD). This explanation may propose newer methods for preventing or curing MD. To better understand MD to control it and shrink the areas involved in this disease, it is better to know the dynamic systems better. It may help prevent the formation of migraine ictal attractor or even make the migraine ictal phase attractor smaller even after it has been formed.

Cyclic liquefaction in transitional and non-transitional tailings

Tailings have previously been identified as having the types of mixed mineralogies and gradings that can make them susceptible to having non-unique critical states and normally compressed states in laboratory element tests. This paper addresses how this mode of behaviour would affect their resistance to undrained cyclic loading, contrasting two triaxial studies, one on a tailings that has a conventional behaviour and one transitional. To demonstrate the influence of transitional behaviour it was necessary to create samples with as wide a range of initial specific volumes as possible, while trying keep the sample preparation methods the same for loose and dense samples. It was also necessary to examine the cyclic data in non-conventional ways, notably in the volumetric plane to highlight better the effects of initial sample specific volume. It is shown that, as previously determined for monotonic loading, the initial density has much less influence on the cyclic behaviour of a soil with transitional behaviour than it would for a conventional soil, and it is instead the stress history that is very much more important. Samples following their respective normal compression lines exhibit similar behaviour, but overconsolidation significantly enhances resistance and a sample that arrives at a given state by the undrained reduction of p′ due to cycling also has a much higher resistance.

An experimental and numerical study on the shear performance of friction-type high-strength bolted connections used for CLT-steel hybrid shear walls

One type of friction-type high-strength bolted connections (FHBCs) was developed to connect steel frames to the infilled cross-laminated timber (CLT) shear walls. In the FHBC, an opening was cut in the CLT near the wall-to-beam interface. Two predrilled holes existed within the CLT panel, running vertically from the bottom surface of the opening to the wall-to-beam interface. Two slotted holes were also predrilled on the top flange of the steel beam. Two high-strength bolts were attached to the upper anchor plate installed in the opening and the bottom anchor plate placed below the top flange of the steel beam. By applying the pretension force on the bolts, the CLT panel was pressed against the steel beam, forming the static friction force to resist the shear force along the wall-to-beam interface. In the study, cyclic tests were conducted to evaluate the friction properties of the interface between the infilled CLT wall and the steel beam. The CLT-steel friction coefficient was carefully investigated, which was a critical parameter for determining the maximum static friction force of the FHBCs. Three-dimensional solid finite element models were developed to predict the load-slip behaviors of the FHBCs, and their multi-stage load-slip behaviors were analyzed using the step-by-step method. It is found that the CLT-to-steel interface can perform with considerable shear-resisting capacity and shear stiffness in the pre-sliding friction as well as stable energy-dissipating capacity in its post-sliding behavior. The maximum static friction coefficient and the dynamic friction coefficient of the interface are recommended as 0.55 and 0.50, respectively. When the pretension force is enhanced from 40 kN to 80 kN, for the FHBCs with the three-layer CLT and those with the five-layer CLT, their ultimate shear-resisting capacity increases by 75.85% and 35.67%, respectively. The load-slip curves from the FHBC models exhibit a similar pre-sliding behavior with considerable shear stiffness and shear-resisting capacity. Whereas, the numerical load-slip curves of the post-sliding stage are distinctive between the FHBCs with the three-layer CLT and those with the five-layer CLT.

Avalanche scaling law for heterogeneous interfacial fracture

A new approach is proposed to study the statistical law of avalanches due to the fracture of a heterogeneous interface. Firstly, a discrete interface is considered as a bundle of fibers clamped with two elastic circular plates, fiber strength being either a random variable or a stochastic field. Based on the theory of solid mechanics, equations governing the dynamic fracture process of fibers under tension are exactly derived and solved. The statistical law of fracture avalanches is accurately obtained. By tuning parameters, the model covers the whole scheme of stress-transfer mechanism due to fiber breaking from local load sharing to equal load sharing. Results show that the distribution of avalanche size of interfacial fracture follows a power-law relation, with the power exponent in the range [1.5,2.5], depending on both disorders of interface and stiffness of plates. Particularly, the exponent monotonically increases with plate stiffness to the value 2.5, a universal constant obtained by Hemmer and Hansen (1992). Then, the fracture of a laminated interface is analyzed. By discretizing the interface to a set of prismatic elements, the problem reduces to that of a discrete interface. Similar statistical behaviors are also observed. Furthermore, the temporal variation of avalanche scaling law is investigated. It is shown that in the vicinity of collapse point, the exponent of each time window is smaller than the exponent evaluated with the whole time series of event, probably a precursor for imminent catastrophic failure of interface.

Sociability: Comparing the Effect of Chlorpyrifos with Valproic Acid.

In recent years, exposures to organophosphate pesticide have been highlighted as a possible cause or aggravating factor of autism spectrum disorder (ASD). The present study examined if Wistar rats prenatally exposed to chlorpyrifos (CPF) at a dose of 1mg/kg in GD 12.5-15.5 could express similar behaviors to those exposed to valproic acid (VPA, 400mg/kg) during the same administration window, which is an accepted animal model of autism. The 3-chambered test was employed to evaluate sociability and reaction to social novelty in two experiments, the first in adolescence and the second in adulthood. The results obtained in this study show that animals prenatally treated with CPF or VPA show a similar behavioral phenotype compared to the control group (CNT). In adolescence, the CPF animals showed a negative index in the reaction to social novelty, followed closely by the VPA, while both experimental groups showed a recovery in this aspect during adulthood. This study therefore provides evidence to suggest that prenatal exposure to CPF in rats could have similar effects on certain components of sociability to those seen in autistic models.

Epidemiological behavior of childhood obesity: A continental point of view

Weight excess during the childhood has been one of the most critical public health problems worldwide in the past few decades. It is considered a significant predictor of adulthood obesity, increased cardiometabolic diseases, and premature mortality. Since the Industrial Revolution, childhood obesity has risen due to sedentary lifestyles and poor eating habits, contributing to the development of obesogenic environments around children in different parts of the world. In this regard, Oceania is positioned as the continent with the highest prevalence globally; however, these results did not consider Australia and New Zealand’s data, probably due to the significant differences in population sizes. America has the second highest percentage of children under five who are overweight. Curiously, Asia’s obesity rates are more significant in higher socioeconomic statuses and urban areas than in children aged 2-4 years. Likewise, Africa displays similar epidemiologic behaviour. Qatar and Kuwait are the countries with the highest obesity prevalence on the continent. Moreover, Europe exhibits a notable South-North gradient, which establishes a higher prevalence of obesity in Mediterranean countries than the Nordic ones. In this regard, various prevention and interventional programs have been developed to combat this silent epidemic, focusing their efforts on nutritional education, improving children’s and parents’ lifestyles, and fighting the influence of the media on their behaviour, and decisions. Therefore, the objective of this review was to describe the epidemiological behaviour of childhood obesity from a continental perspective.

Mechanical Properties Characterization of Glass/Carbon Fiber Hybrid Multilayer Composite under Environmental Aging Condition

Metallic components in boating industry are being replaced with carbon fiber composites due to their light weight, excellent mechanical properties, and corrosion resistance. However, the carbon fiber cost has obstructed the substitution. Hybridization is suggested to merge carbon and glass fibers in cost-effective composites while maintaining the desired engineering properties. This study experimentally examines the impact of hybridization and seawater aging on the mechanical properties of glass and carbon fibers hybrid composites. A range of composites ([C]6, [CGC]s, [C]3[G]3, [GCG]s, and [G]6) are fabricated and aged in simulated seawater solution before their tensile, flexural, impact, and hardness properties are examined. The results revealed degradation in properties due to the ageing, the degree of degradation is influenced by the s hybridization configuration. The [G]6 sample shows the highest tensile strength reduction of 30% compared to 20% for the [C]6. The remaining samples exhibit reduction percentages falling between these two extremes. A similar behavior is observed in the flexural test, though the extremes values are smaller, 10.2%, and 12.5%. The impact and hardness tests showed an inverse relationship between the glass fiber content and impact strength degradation due to aging, while they exhibited a linear correlation for hardness degradation due to ageing.

Leveraging Machine Learning for Customer Segmentation in Retail

In the dynamic landscape of retail, understanding customer behavior is paramount for effective marketing strategies and business growth. Customer segmentation, the process of dividing customers into groups based on similar characteristics or behaviors, serves as a fundamental tool in this endeavor. Traditional methods of segmentation often fall short in capturing the complexity and nuances of customer preferences. This article explores the application of machine learning techniques in customer segmentation within the retail sector. Leveraging advanced algorithms, such as clustering and classification, machine learning enables retailers to uncover hidden patterns in vast datasets, leading to more accurate and actionable segmentation strategies. Through real-world examples and case studies, this article highlights the benefits, challenges, and best practices of employing machine learning for customer segmentation in retail. Keywords Machine Learning, Customer Segmentation, Retail, Clustering, Classification, Marketing Strategy

Voltametric Determination of Dopamine in Urine Samples Using Biochar-Modified Carbon Paste yielded from Spent Coffee Grounds

Dopamine (DA), a crucial neurotransmitter in human systems, coexists with uric acid (UA) and ascorbic acid (AA) in biological fluids, challenging its selective detection due to similar redox behavior. This study introduces a method for selectively preconcentrating dopamine before voltammetric determination. For that, eco-friendly biochar was prepared from spent coffee grounds (400 °C, 60 min), chemically activated with HNO3 (60 °C, 3 h), characterized using FTIR, XDR, and Boehm titration, and then used for assembling carbon paste modified electrodes (CPME). In the electrochemical process, the CPME was immersed in a solution containing the analyte and interferents (0.1 mol l−1 BR buffer, pH = 7.0), and then transferred to the electrochemical cell for detecting preconcentrated DA via differential pulse voltammetry (DPV). The method demonstrated selectivity and sensitivity with a linear dynamic range (LDR) of 10 to 200 μmol l−1, limits of detection (LOD) and quantification (LOQ) of 1.47 and 10.0 μmol l−1. Additionally, synthetic urine samples containing the analyte were analyzed in presence of equimolar concentrations of AA and UA, and the method successfully and selectively determinated DA even in a more complex matrix.

A study on the stratification of long-tail customers in civil aviation based on a cluster ensemble

Stratifying long-tail customers and identifying high-quality customers with high growth potential are crucial for civil aviation companies to explore new profit growth points. This paper proposes a long-tail customer stratification model based on clustering ensemble to address the problems of insufficient attention to long-tail customers in previous studies and the low accuracy and lack of accuracy testing of single clustering algorithms. First, the Bayesian information criterion is used to determine the optimal number of clusters. Then, an ensemble framework integrating the Gaussian mixture model, spectral clustering, Two step clustering and K-means algorithm is constructed, and the stacking and bagging ensemble methods are used for the cluster ensemble. Finally, three different indicators are used to evaluate the algorithm performance. Experimental results indicate that compared with single clustering algorithms, the Stacking algorithm increases the silhouette coefficient by 14.77% to 27.11%, the Calinski-Harabasz index by 38.83% to 122.18%, and the Davies-Bouldin Index by 19.38% to 98.04%. This indicates that each clustering has high cohesion and separation, with samples within a category being more closely related and those between categories having clear boundaries. It shows that the Stacking algorithm more accurately stratifies long-tail customers with similar consumption behaviors into different categories, achieving customer stratification.

Fetal Left Ventricle Function Evaluated by Two-Dimensional Speckle-Tracking Echocardiography across Clinical Stages of Severity in Growth-Restricted Fetuses.

Fetal growth restriction (FGR) can result in adverse perinatal outcomes due to cardiac dysfunction. This study used 2D speckle-tracking echocardiography to assess left ventricle (LV) longitudinal strain across FGR severity stages. A prospective longitudinal cohort study measured global (GLS) and segmental LV longitudinal strain in FGR fetuses, with evaluations conducted at various time points. FGR was classified into subtypes based on published criteria using fetal weight centile and Doppler parameters. A linear mixed model was employed to analyze repeated measures and compare Z-score measurements between groups throughout gestational age. The study included 40 FGR fetuses and a total of 107 evaluations were performed: 21 from small for gestational age (SGA), 74 from the FGR stage I, and 12 from the FGR stage ≥ II. The results indicate that SGA and stage I FGR fetuses exhibit higher LV GLS than stages ≥ II. Throughout gestation, SGA and FGR stage I fetuses showed similar behavior with consistently better LV GLS values when compared to FGR stages ≥ II. No significant differences were observed in LV GLS strain behavior between SGA and FGR stage I. In conclusion, all FGRs show signs of early cardiac dysfunction, with severe cases demonstrating significantly a lower LV GLS when compared to mild cases, suggesting deterioration of cardiac dysfunction with progression of fetal compromise.

Problematic Behaviour Among Students in Secondary Schools and the Role of Educational Counsellors

Nowadays it is very important to focus on selecting a topic. Students begin to adopt various types of problematic behaviours in the education system. They engage in problematic behaviour in interactions not only with their peers, but also their teachers. Compared to the situation in other countries, the prevalence of such behaviour is still low in our country. Nevertheless, the present study is aimed at addressing those issues. Humiliation, bullying, truancy and similar behaviour constitute a problem that occurs at an increasing frequency and might transform into major pathological phenomena.

Inefficacious drugs against covid-19: analysis of sales, tweets, and search engines.

Assess the correlation between the sales of two drugs with no proven efficacy against covid-19, ivermectin and chloroquine, and other relevant variables, such as Google® searches, number of tweets related to these drugs, number of cases and deaths resulting from covid-19. The methodology adopted in this study has four stages: data collection, data processing, exploratory data analysis, and correlation analysis. Spearman's method was used to obtain cross-correlations between each pair of variables. The results show similar behaviors between variables. Peaks occurred in the same or near periods. The exploratory data analysis showed shortage of chloroquine in the period corresponding to the beginning of advertising for the application of these drugs against covid-19. Both drugs showed a high and statistically significant correlation with the other variables. Also, some of them showed a higher correlation with drug sales when we employed a one-month lag. In the case of chloroquine, this was observed for the number of deaths. In the case of ivermectin, this was observed for the number of tweets, cases, and deaths. The results contribute to decision making in crisis management by governments, industries, and stores. In times of crisis, as observed during the covid-19 pandemic, some variables can help sales forecasting, especially Google® and tweets, which provide a real-time analysis of the situation. Monitoring social media platforms and search engines would allow the determination of drug use by the population and better prediction of potential peaks in the demand for these drugs.

Farklı Zemin Sınıfına Göre Elde Edilmiş Düşey Elastik Tasarım Spektrumlarının Yapı Davranışına Etkisi ve K.Maraş Deprem Verileri ile Karşılaştırılması

In practice and theory, many types of reinforced concrete slabs are used, such as beamed, beamless, and ribbed slabs. Beamed floors are connected to the columns by means of beams, and their vertical and horizontal loads are transferred to the columns through these beams. Therefore, beams are accepted as an important structural element by earthquake experts and many formulas and approaches have been developed in terms of horizontal and vertical load effects that occur in order to transfer the load transfer to the elements as desired. In this study, beam shear forces that occur under the influence of vertical earthquakes at the i and j ends of the beams of a fictional building whose floors are modeled according to the rigid diaphragm assumption in the ETABS were investigated. In this study, the shear forces that occur in the beams of a fictionally designed building under the effect of vertical earthquakes, and the floors carried by the beams are examined by designing with the assumption of a rigid diaphragm. The structure is designed with 3 openings in the X and Y directions and each opening is equal and 5 m. The 5-storey building has been designed to have equal floor heights of 3 m. The structure was obtained by using parameters belonging to 5 different soil classes as ZA, ZB, ZC, ZD, ZE, and 5 different vertical elastic design spectrums represented by the abbreviations EZ_ZA, EZ_ZB, EZ_ZC, EZ_ZD were activated in the ETABS. Seismic station coordinates numbered 4631 in K.Maras/Elbistan were used to obtain the parameters to be used in obtaining the vertical elastic design spectral of the structure. These coordinates were selected in order to compare the i and j end shear forces of the beam with the previously obtained beam i and j ends shear forces by influencing the Mw:7.6 Elbistan earthquake recorded by the seismic station to the building. Since the structure is symmetrical in both X and Y directions, the results obtained from beams B2, B3, B5, B19 represent the beam shear forces occurring at the i and j ends of all beams of the structure. As a result, it has been seen that the highest values of beam i and j end shear forces, obtained by affecting both the vertical elastic design spectral and the data of the vertical component of the Elbistan Mw:7.6 earthquake, were obtained on the 5th floor, which is the top floor of the building. The structure showed similar behavior among the different vertical elastic design spectral, and the highest value was obtained for each vertical elastic design spectrum at the 5th floor. Among these vertical elastic design spectral, the EZ_ZC spectrum gave the highest value at the 5th floor of the building. When the EZ_ZC vertical elastic design spectrum beam i and j end shear forces are compared with the beam i and j end shear forces of the vertical component data of the Elbistan Mw:7.6 earthquake, it is seen that the difference is not significant. It has been seen that the beam i and j end shear force value of the spectrum is higher than the shear force value.