Browsing by Publication Category "Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı"

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1441. Quantification of the Flow Noise in Household Refrigerators
(JVE INTERNATIONAL LTD., 2014) Körük, Hasan; Arısoy, Ahmet; Bilgin, Necati
The flow noise in household refrigerators is quantified in this study. First, the sound pressure measurements in a quiet room using typical household refrigerators are conducted and the noise characteristics of the refrigerators are presented. Then, the flow noise in household refrigerators is quantified using the results of the overall analysis and Fourier transform of the measured sound pressure data. After that, the flow noise in household refrigerators is quantified using the sound pressure measurements conducted using a specially designed test rig. The frequency characteristics of the flow noise in household refrigerators are also explored and the contribution of the flow noise is identified.
17th International Conference on Mechatronics Technology, October 15-18, 2013, Jeju Island, Korea
(Elsevier, 2015) Hwang, Sung Ho; Kim, Joon-wan; Dorantes-Gonzalez, Dante Jorge
In recent years, Mechatronics has gained a lot of interest as more applications have been introduced to industry and society. The need for new mechatronic technologies in the form of advanced production systems, mechatronic devices, control systems, robotics, biomedical applications, MEMS, and measurement systems, among others, is very much required in improving productivity and competitiveness in many industries. Thus, this conference was organized to address the state-of-the-art technology for the benefit of researchers and users, and this time the conference made a special focus on the topic: Sustainable Mechatronics Technology.
6331 Sayılı İş Sağlığı ve Güvenliği Kanununun Kişi Bakımından Kapsamı ve Karşılaştırmalı Hukukta İş Sağlığı ve Güvenliğinin Genişlemesine İlişkin Eğilimler
(2026) Günler, Salih Haydar
İş sağlığı ve güvenliği hukuku, çalışma hayatında insan sağlığını korumayı ve mesleki riskleri önlemeyi amaçlayan, temelinde kamu yararı olması sebebiyle de hem kamu hukuku hem özel hukuk unsurlarını taşıyan bir alandır. Çalışma ilişkilerinin dönüşüp çeşitlenmesi, bağımsız çalışmaların yaygınlaşması ve kamu ile özel sektör arasındaki sınırların esnekleşmesiyle birlikte iş sağlığı ve güvenliği önlemlerinin kişi bakımından kapsamı da daha önemli hale gelmiştir. Ülkemizde 6331 sayılı İş Sağlığı ve Güvenliği Kanunu, klasik anlamda işçi kavramının yerine daha geniş kapsamlı olan çalışan kavramı temelinde düzenlenmiştir. Bu çalışmada, 6331 sayılı Kanunun kişi bakımından kapsamı ele alınmakta; kanun kapsamında yer alan ve kapsam dışında bırakılan kişiler incelenmektedir. Ayrıca iş sağlığı ve güvenliği hukukunda kapsamın genişletilmesine yönelik yaklaşımlar, Avrupa Birliği düzenlemeleri ve karşılaştırmalı hukuk örnekleri çerçevesinde değerlendirilmektedir.
A Bayesian Allocation Model Based Approach To Mixed Membership Stochastic Blockmodels
(Taylor and Francis Ltd., 2022) Kırbız, Serap; Hızlı, Çağlar
Although detecting communities in networks has attracted considerable recent attention, estimating the number of communities is still an open problem. In this paper, we propose a model, which replicates the generative process of the mixed-membership stochastic block model (MMSB) within the generic allocation framework of Bayesian allocation model (BAM) and BAM-MMSB. In contrast to traditional blockmodels, BAM-MMSB considers the observations as Poisson counts generated by a base Poisson process and marks according to the generative process of MMSB. Moreover, the optimal number of communities for BAM-MMSB is estimated by computing the variational approximations of the marginal likelihood for each model order. Experiments on synthetic and real data sets show that the proposed approach promises a generalized model selection solution that can choose not only the model size but also the most appropriate decomposition.
A Benchmark Dataset for Turkish Data-To Generation
(Elsevier, 2023) Demir, Şeniz; Öktem, Seza
In the last decades, data-to-text (D2T) systems that directly learn from data have gained a lot of attention in natural language generation. These systems need data with high quality and large volume, but unfortunately some natural languages suffer from the lack of readily available generation datasets. This article describes our efforts to create a new Turkish dataset (Tr-D2T) that consists of meaning representation and reference sentence pairs without fine-grained word alignments. We utilize Turkish web resources and existing datasets in other languages for producing meaning representations and collect reference sentences by crowdsourcing native speakers. We particularly focus on the generation of single-sentence biographies and dining venue descriptions. In order to motivate future Turkish D2T studies, we present detailed benchmarking results of different sequence-to-sequence neural models trained on this dataset. To the best of our knowledge, this work is the first of its kind that provides preliminary findings and lessons learned from the creation of a new Turkish D2T dataset. Moreover, our work is the first extensive study that presents generation performances of transformer and recurrent neural network models from meaning representations in this morphologically-rich language.
A Capacitated Lot Sizing Problem With Stochastic Setup Times and Overtime
(Elsevier Science bv, 2019) Jabali, Ola; Gendreau, Michel; Jans, Raf; Taş, Duygu
In this paper, we study a Capacitated Lot Sizing Problem with Stochastic Setup Times and Overtime (CLSPSSTO). We describe a mathematical model that considers both regular costs (including production, setup and inventory holding costs) and expected overtime costs (related to the excess usage of capacity). The CLSP-SSTO is formulated as a two-stage stochastic programming problem. A procedure is proposed to exactly compute the expected overtime for a given setup and production plan when the setup times follow a Gamma distribution. A sample average approximation procedure is applied to obtain upper bounds and a statistical lower bound. This is then used to benchmark the performance of two additional heuristics. A first heuristic is based on changing the capacity in the deterministic counterpart, while the second heuristic artificially modifies the setup time. We conduct our computational experiments on well-known problem instances and provide comprehensive analyses to evaluate the performance of each heuristic. (C) 2018 Elsevier B.V. All rights reserved.
A Case Study of the Relationship Between Meaning and Formalism
(Unspecified, 2017) Aydın, Utkun
The purpose of this study was to explore the sources of mathematical ideas in terms of the relationships between meaning and formalism and their role in the transition between elementary mathematics and advanced mathematics. The two participants were high school mathematics teachers, who vary in their levels of experience. Two forms of data were collected to obtain more in-depth data about the transformations within among mathematical ideas: a questionnaire including 14 open-ended mathematical tasks and semi-structured interviews. Results indicated that individuals had different ways in constructing mathematical ideas and that their mathematical ideas were derived from the transition between meaning and formalism.
A Comparative Analysis on the Relationship Between Institutional Environment and Entrepreneurship in Emerging Economies
(2018) Karadağ, Hande
Institutional environment plays an important role in the quality and nature of entrepreneurial activities and the development of entrepreneurship ecosystem. The aim of this research is to evaluate institutional factors of selected emerging markets with Global Entrepreneurship and Development Index data. Findings of the study indicate that Turkey has one of the lowest scores among other emerging markets for the institutional variable of staff training and also has comparably low scores in venture capital, business strategy, and technology transfer. Results of the study show that except South Korea, all the selected economies have scored low on the institutional variable of gross domestic expenditure on research and development as a percentage of the gross domestic product. The study is expected to make valuable contributions to the literature with its novel approach of using comparative Global Entrepreneurship and Development Index scores for analyzing the institutional environment and entrepreneurship relationship in emerging economies.
A Comparative Study of Branch-And Algorithms for Vehicle Routing With Time Windows and Waiting Time Costs
(Wiley, 2026) Michelini, Stefano; Kucukaydin, Hande; Arda, Yasemin
Branch-and-price is one of the most commonly used methodologies for solving routing problems. In recent years, several studies have investigated advanced labeling algorithms to solve the related pricing problem, which is usually a variant of the elementary shortest path problem with resource constraints. Such algorithms include efficient techniques such as decremental state space relaxation, ng-route relaxation, and several hybridizations of these two relaxation methods. In this study, we compare the performance of these labeling algorithms in a branch-and-price framework when applied to the vehicle routing problem with time windows and a variant of this problem in which waiting times have a linear cost. For the latter problem, we also propose an appropriate label structure with associated resource extension functions and dominance rules. We perform these comparisons by using a rigorous methodology, which consists of parameterizing several features of these algorithms, obtaining a good parameter configuration for each algorithm, and analyzing the performance of these configurations on benchmark instances. In order to obtain good configurations, we make use of irace, which is a tool for automated parameter tuning, while statistical tests are used for performance comparisons. Our results show that a class of hybrid algorithms with certain features based on ng-route relaxation outperforms all the others.
A Configurational Analysis of the Impact of Entrepreneurial Orientation and Global Mindset on Export Performance of Smes
(SAGE Publications Inc., 2025) Matemane, R.; Mintah, R.; Şahin, F.; Karadağ, H.
Although contemporary literature provides several important insights into the role of attributes of SMEs, there is much less evidence on what configuration of entrepreneurial orientation and global mindset makes this process successful, that is, contributing to the export performance of SMEs. This study uses a fuzzy set qualitative comparative analysis on a sample of 97 SMEs in Ghana to explore the potential complementary role between the entrepreneurial orientation dimensions and global mindset for superior export performance. The results indicate two different yet equifinal configurations of these factors that lead to a high level of export performance of SMEs. One of the configurations shows that proactive and innovative SMEs with managers high on global mindset achieve superior export performance regardless of their willingness to take risks. Another configuration indicates that regardless of the global mindset of managers, SMEs can achieve higher export performance by being proactive, innovative, and willing to take high risks. Several implications for theory and practice are discussed based on the findings. © The Author(s) 2024.
A Data-Assisted Reliability Model for Carrier-Assisted Cold Data Storage Systems
(Elsevier, 2020) Arslan, Şuayb Şefik; Göker, Turguy; Peng, James
Cold data storage systems are used to allow long term digital preservation for institutions’ archive. The common functionality among cold and warm/hot data storage is that the data is stored on some physical medium for read-back at a later time. However in cold storage, write and read operations are not necessarily done in the same exact geographical location. Hence, a third party assistance is typically utilized to bring together the medium and the drive. On the other hand, the reliability modeling of such a decomposed system poses few challenges that do not necessarily exist in other warm/hot storage alternatives such as fault detection and absence of the carrier, all totaling up to the data unavailability issues. In this paper, we propose a generalized non-homogenous Markov model that encompasses the aging of the carriers in order to address the requirements of today's cold data storage systems in which the data is encoded and spread across multiple nodes for the long-term data retention. We have derived useful lower/upper bounds on the overall system availability. Furthermore, the collected field data is used to estimate parameters of a Weibull distribution to accurately predict the lifetime of the carriers in an example scale-out setting.
A Decomposition Algorithm for Single and Multiobjective Integrated Market Selection and Production Planning
(Informs, 2023) van den Heuvel, Wilco; Ağralı, Semra; Taşkın, Z. Caner
We study an integrated market selection and production planning problem. There is a set of markets with deterministic demand, and each market has a certain revenue that is obtained if the market's demand is satisfied throughout a planning horizon. The demand is satisfied with a production scheme that has a lot-sizing structure. The problem is to decide on which markets' demand to satisfy and plan the production simultaneously. We consider both single and multiobjective settings. The single objective problem maximizes the profit, whereas the multiobjective problem includes the maximization of the revenue and the minimization of the production cost objectives. We develop a decomposition-based exact solution algorithm for the single objective setting and show how it can be used in a proposed three-phase algorithm for the multiobjective setting. The master problem chooses a subset of markets, and the subproblem calculates an optimal production plan to satisfy the selected markets' demand. We investigate the subproblem from a cooperative game theory perspective to devise cuts and strengthen them based on lifting. We also propose a set of valid inequalities and preprocessing rules to improve the proposed algorithm. We test the efficacy of our solution method over a suite of problem instances and show that our algorithm substantially decreases solution times for all problem instances.
A Discourse Analysis of Bilateral Water Agreements Between Türkiye and Iraq: Legal Instruments of Water Diplomacy in the Euphrates-Tigris River Basin
(International Environmental Agreements: Politics, Law and Economics, 2026) Güleç, Cansu; Kibaroglu, Aysegul
This study examines the discursive dynamics of bilateral water diplomacy between T & uuml;rkiye and Iraq through a detailed analysis of the legal agreements governing the Euphrates-Tigris (ET) River system. Rather than focusing on the implementation or efficacy of these agreements, the paper investigates how discourse shapes the roles, identities, and power hierarchies of the involved actors over time. Employing a discourse-analytical framework, the research explores how water agreements position actors, embed values, and narrate cooperation in evolving geopolitical contexts. The paper begins with a historical overview of transboundary water relations in the ET basin, emphasizing the prevalence of bilateralism. It then lays out the conceptual and methodological foundations of discourse analysis, drawing on key literature and analytical categories such as presupposition, predication, and subject positioning. The core section applies this framework to four key water agreements between T & uuml;rkiye and Iraq, highlighting thematic shifts and evolving actor roles. A discussion section synthesizes findings through Doty's (1993) discourse model, emphasizing how identities and relations are constructed over time. Finally, the conclusion reflects on the implications of these discursive trends for the future of water diplomacy in the region. The T & uuml;rkiye-Iraq case reveals how bilateral agreements can evolve into discursive tools that align with evolving global water management paradigms, offering politically sensitive basins a transferable approach to linking contested transboundary water issues with more comprehensive and partnership-based water diplomacy.
A Distance-Dependent Random Graph Model and Its Analysis
(Taylor & Francis Inc, 2026) Arslan, İlker; Işlak, Ümit
Let W-1,..., Wn be non-negative random variables. We consider an undirected random graph model on the node set {1,. ..,n}, where two nodes i < j are adjacent if W-i < W-j. In our setting, the Wi's are independent but not necessarily identically distributed, resulting in a model that generalizes the classical random permutation graphs. The model exhibits a certain dependence among the edges. Moreover, when nodes have physical interpretations- such as points on the real line R with node i located at position x = i-the model gains spatial structure and becomes, in particular, distance-dependent. We derive theoretical results on degree distributions, the number of isolated vertices, and the number of close neighbors. Simulation-based observations are also provided for the average clustering and the global efficiency.
A Few Layers Graphene Encapsulated Fe-Based Nanoparticles Synthesized from Ferrocene Containing Precursors: CVD Optimization and Evaluation for Possible Nanocatalyst Performance towards H2 Production
(Pergamon-Elsevier Science Ltd, 2026) Demirbas, Derya; Kutluay, Sinan; Agaogullari, Duygu; Suzer-Cicek, Layda; Mertdinc-Ulkuseven, Siddika; Padberg, Gero; Felderhoff, Michael; Süzer-Çiçek, İlayda; Lütfi Öveçoğlu M.
This study focuses on optimizing the synthesis of a few-layer graphene-encapsulated iron-based nanoparticles (Fe/Fe3C@C), prepared through spray drying, chemical vapor deposition (CVD), and leaching processes using ferrocene-based precursors, and their application as nanocatalysts for hydrogen (H2) production via sodium borohydride (NaBH4) methanolysis. Ferrocene-impregnated silica powders were prepared by spray drying them from a solution containing ferrocene, fumed silica, and ethanol. Then, these prepared powders, known as precursor powders, were subsequently introduced into the CVD system. Both the reduction of ferrocene and the encapsulation of Fe-based nanoparticles by graphene layers occurred in-situ during the CVD process. CVD temperature and the flow rates of CH4 and H2 gases are critical parameters that effects of the microstructural, thermal, and magnetic properties of synthesized nanoparticles. The CVD system was performed at temperatures ranging from 850 to 1000 degrees C, with variable gas flow rates of 50 or 100 mL/min. Additionally, acid leaching with hydrofluoric (HF) and hydrochloric (HCl) acids ensured the synthesis of pure powders free from silica and uncoated Fe, confirming the chemical stability of the nanoparticles. The presence of graphene in all synthesized samples within these parameter ranges were confirmed by Raman spectroscopy. Phase identifications were carried out using X-ray diffraction (XRD) and Mo & uml;ssbauer spectroscopy, revealing the Fe and trace amount Fe3C as core phases. Transmission electron microscopy (TEM) revealed the core-shell structure of the nanoparticles with a few layers of graphene coatings. Based on the coercivity and magnetic saturation values obtained from vibrating sample magnetometry (VSM), synthesized core-shell nanoparticles exhibited soft magnetic properties (Ms = 22.4-33.5 emu/g, Hc = 82.3-278.3 Oe). Fe/Fe3C@C nanoparticles obtained under optimum conditions achieved very high H2 production rate (HPR = 54200 mLH2 gcat h- 1) values, with low activation energy (Ea = 20.08 kJ mol- 1) value, highlighting their potential as an efficient and promising candidate catalyst for industrial-scale H2 production via the NaBH4 methanolysis reaction. In addition, it was found that the Fe/Fe3C@C nanoparticles retained 48% and 71% of their initial activity after 5 consecutive cycles, as measured by the HPR and TOF values, respectively.
A Longitudinal Assessment of Variability in Covid-19 Vaccine Hesitancy and Psychosocial Correlates in a National United States Sample
(Elsevier Sci Ltd, 2023) Shook, Natalie J.; Oosterhoff, Benjamin; Sevi, Barış
Recent evidence suggests that COVID-19 vaccine hesitancy is not static. In order to develop effective vaccine uptake interventions, we need to understand the extent to which vaccine hesitancy fluctuates and identify factors associated with both between- and within-person differences in vaccine hesitancy. The goals of the current study were to assess the extent to which COVID-19 vaccine hesitancy varied at an individual level across time and to determine whether disgust sensitivity and germ aversion were associated with between- and within-person differences in COVID-19 vaccine hesitancy. A national sample of U.S. adults (N = 1025; 516 woman; M-age = 46.34 years, SDage = 16.56, range: 18 to 85 years; 72.6 % White) completed six weekly online surveys (March 20 - May 3, 2020). Between-person mean COVID-19 vaccine hesitancy rates were relatively stable across the six-week period (range: 38-42 %). However, there was considerable within-person variability in COVID-19 vaccine hesitancy. Approximately, 40 % of the sample changed their vaccine hesitancy at least once during the six weeks. There was a significant between-person effect for disgust sensitivity, such that greater disgust sensitivity was associated with a lower likelihood of COVID-19 vaccine hesitance. There was also a significant within-person effect for germ aversion. Participants who experienced greater germ aversion for a given week relative to their own six week average were less likely to be COVID-19 vaccine hesitant that week relative to their own six-week average. This study provides important information on rapidly changing individual variability in COVID-19 vaccine hesitancy on a weekly basis, which should be taken into consideration with any efforts to decrease vaccine hesitancy and increase vaccine uptake. Further, these findings identify-two psychological factors (disgust sensitivity and germ aversion) with malleable components that could be leveraged in developing vaccine uptake interventions.
A Lot-Sizing Problem in Deliberated and Controlled Co-Production Systems
(Taylor and Francis, 2022) Kabakulak, Banu; Ağralı, Semra; Taşkın, Z. Caner; Pamuk, Bahadır
We consider an uncapacitated lot sizing problem in co-production systems, in which it is possible to produce multiple items simultaneously in a single production run. Each product has a deterministic demand to be satisfied on time. The decision is to choose which items to co-produce and the amount of production throughout a predetermined planning horizon. We show that the lot sizing problem with co-production is strongly NP-Hard. Then, we develop various mixed-integer linear programming (MILP) formulation of the problem and show that LP relaxations of all MILPs are equal. We develop a separation algorithm based on a set of valid inequalities, lower bounds based on a dynamic lot-sizing relaxation of our problem and a constructive heuristic that is used to obtain an initial solution for the solver, which form the basis of our proposed Branch & Cut algorithm for the problem. We test our models and algorithms on different data sets and provide the results.
A Machine Learning Approach To Resolving Conflicts in Physical Human-Robot Interaction
(Association for Computing Machinery, 2025) Ulas Dincer, Enes; Al-Saadi, Zaid; Hamad, Y.M.; Aydın, Yusuf; Kucukyilmaz, A.; Basdogan, C.; Dincer, Enes Ulas
As artificial intelligence techniques become more sophisticated, we anticipate that robots collaborating with humans will develop their own intentions, leading to potential conflicts in interaction. This development calls for advanced conflict resolution strategies in physical human-robot interaction (pHRI), a key focus of our research. We use a machine learning (ML) classifier to detect conflicts during co-manipulation tasks to adapt the robot's behavior accordingly using an admittance controller. In our approach, we focus on two groups of interactions, namely "harmonious"and "conflicting,"corresponding respectively to the cases of the human and the robot working in harmony to transport an object when they aim for the same target, and human and robot are in conflict when human changes the manipulation plan, e.g. due to a change in the direction of movement or parking location of the object.Co-manipulation scenarios were designed to investigate the efficacy of the proposed ML approach, involving 20 participants. Task performance achieved by the ML approach was compared against three alternative approaches: (a) a rule-based (RB) Approach, where interaction behaviors were rule-derived from statistical distributions of haptic features; (b) an unyielding robot that is proactive during harmonious interactions but does not resolve conflicts otherwise, and (c) a passive robot which always follows the human partner. This mode of cooperation is known as "hand guidance"in pHRI literature and is frequently used in industrial settings for so-called "teaching"a trajectory to a collaborative robot.The results show that the proposed ML approach is superior to the others in task performance. However, a detailed questionnaire administered after the experiments, which contains several metrics, covering a spectrum of dimensions to measure the subjective opinion of the participants, reveals that the most preferred mode of interaction with the robot is surprisingly passive. This preference indicates a strong inclination toward an interaction mode that gives more control to humans and offers less demanding interaction, even if it is not the most efficient in task performance. Hence, there is a clear trade-off between task performance and the preferred mode of interaction of humans with a robot, and a well-balanced approach is necessary for designing effective pHRI systems in the future. © 2025 Copyright held by the owner/author(s).
A Meta-Analytic Review of the Association Between Theory of Mind and Aggression
(Elsevier, 2024) Imuta, Kana; Selçuk, Bilge; Yavuz-Müren, Melis; Turunç, Gamze; Ekerim-Akbulut, Müge
Although the association between theory of mind (ToM) and aggression has been theorized, empirical findings have not revealed a clear link between these constructs. In the current meta-analytic review, we integrated findings from 83 studies (141 effect sizes) involving 41,650 participants from 18 countries to elucidate the association between ToM and aggression in typically developing children, adolescents, and adults. We found a significant negative association between ToM and aggression overall (r = −0.15). Moreover, each type and function of aggression were negatively associated with Theory of Mind (ToM). Bullying—a distinct form of aggression—was not associated with ToM. The strength of the association between overall aggression and ToM varied as a function of methodological variables: First, studies that used self-report questionnaires to measure ToM and aggression yielded the strongest effect sizes, compared to those that used task-based assessments or questionnaires completed by others (parents, teachers, peers). Second, there was a difference in the ToM measurement with the measures examining ToM with non-false belief understanding tasks yielding a stronger mean effect than those that focused exclusively on false-belief understanding. Third, the magnitude of the negative association was found to increase with participants' age, though significant negative associations between ToM and aggression held across the lifespan. These results point to the critical link between ToM and aggressive tendencies and suggest the value in implementing interventions to improve mental state understanding across the age range to foster positive social interactions.
A New Approach for Measuring Viscoelastic Properties of Soft Materials Using the Dynamic Response of a Spherical Object Placed at the Sample Interface
(Springer, 2023) Besli, Ayça; Koç,Ömer Hayati; Körük,Hasan; Yurdaer, Berk Salih; Koc, H. O.; Yurdaer, S. B.; Pouliopoulos, A. N.
Background: There are several techniques to characterize the mechanical properties of soft materials, such as the indentation method and the method based on the application of a spherical object placed inside the sample. The indentation systems usually yield the elastic properties of materials and their mathematical models do not consider the inertia of the sample involved in motion and radiation damping, while placing an object inside the sample is not practical and this procedure can alter the mechanical properties of the sample for the method based on the application of a bubble/sphere placed inside the sample. Objective: A new approach for the identification of the viscoelastic properties of soft materials using the dynamic response of a spherical object placed at the sample interface was proposed. Methods: The spherical object placed at the sample interface was pressed using an electromagnet and the dynamic response of the spherical object was tracked using a high-speed camera, while the dynamic response of the spherical object placed at the sample interface was estimated using a comprehensive analytical model. The effects of the shear modulus, viscosity, Poisson’s ratio and density of the soft sample, the radius and density of the spherical object and the damping due to radiation were considered in this mathematical model. The shear modulus and viscosity of the soft sample were determined by matching the experimentally identified and theoretically estimated responses of the spherical object. Results: The shear moduli and viscosities of the three phantoms with the gelatin mass ratios of 0.20, 0.25 and 0.29 were measured to be 3450, 4300 and 4950 Pa and 12.5, 14.0 and 15.0 Pa⋅s, respectively. The shear modulus and viscosity of the phantom increases as the gelatin mass ratio increases. The frequency of oscillations of the hemisphere placed at the phantom interface increases as the gelatin mass ratio increases due to stiffness increase. Conclusions: After matching the experimental and theoretical steady-state displacements and amplitudes of oscillations of the hemisphere at the sample interface, the comparison of the experimentally identified and theoretically predicted frequency of oscillations further confirmed the identified material properties of the samples. The approach presented here is expected to provide valuable information on material properties in biomedical and industrial applications.