Altınbaş University Institutional Repository
Not a member yet
5805 research outputs found
Sort by
Developing robust machine learning models to defend against adversarial attacks in the field of cybersecurity
No full textDue to their vulnerability to malicious attacks, machine learning models utilized in cybersecurity applications necessitate robust safeguards. Despite previous research, there is still a lack of effective and practical protections for real-world circumstances. In order to tackle this issue, our work extensively investigates methods to enhance the robustness of machine learning models against malicious assaults. Our cutting-edge cybersecurity defensive tactics are derived on the extensive Edge-IIoTset cybersecurity dataset, specifically designed for Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications. Our methodology integrates sophisticated techniques like adversarial training, input preprocessing, and evaluating the robustness of models. The proposed defensive measures have shown to be highly successful in mitigating the impact of hostile attacks, as evidenced by substantial empirical research. Specifically, as compared to the baseline models, our defensive model exhibits a notable 15% enhancement in accuracy. Our research demonstrates that safeguarding machine learning systems in real-world cybersecurity scenarios necessitates taking proactive actions. This will enable further advancements in the development of unique defense measures. Training methods could be enhanced by including adversarial assaults employing generative adversarial networks (GANs), random forest ensembles, and a variety of scenario-specific hybrid approaches. Assess their effectiveness in dealing with the issue of models being vulnerable to complex manual attacks
Determining the impact of trust and perceived risk on consumers' online shopping behaviour: a case on Turkish online market
No full textOnline shopping has been increasing in demand and popularity ever since the pandemic
struck in 2020 and since then, the e-commerce market started to boom especially in Türkiye.
Consumers have become adept and familiar with the process of online shopping yet there are
still variables that cause a hindrance which online retailers fail to notice. Taking past
literature into consideration, there are two major factors that are essential to analyse online
shopping behaviour, Trust and Perceived Risk. The objective of this study is to determine
the effects of the factors Trust and Perceived Risk towards Online shopping Behaviour within
the Turkish market while having Trust as a mediator factor. The universal sample for this
study is the population of online users in Türkiye. The paper approaches the study using a
quantitative method where a survey is used to collect data. The analysis is conducted using
Structural Equation Method (SEM) to analyse the complex model and the results concluded
that Trust has a positive effect on Online shopping behaviour while Perceived Risk has a
negative effect towards Trust and online shopping behaviour
Changes in secondary structure of protein in skeletal muscle due to high-carbohydrate of high-fat diets
No full textObjective: Obesity, which arises from changes in lifestyle and feeding habits, poses a threat to human health. One essential contributor to the increase in obesity rates is the popularity of high-calorie diets. This study aims to investigate high-fat (HFD) and high-carbohydrate (HCD) diet-induced molecular changes in protein secondary structure in longissimus dorsi skeletal muscle tissues of female inbred C57BL/6J mice by utilizing Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy. Materials and Methods: Mice were fed a control diet, HCD, or HFD for 24 weeks. Their skeletal muscle tissues were collected, and their spectra were recorded using a Bruker Invenio S ATR-FTIR spectrometer in the 4000-400 cm-1 region. Results: The protein secondary structure profiles of the HCD group demonstrated a significant rise in antiparallel beta-sheet and beta-turn and a decline in parallel beta-sheets, together with the insignificant increase in aggregated beta-sheets and a decrease in alpha-helix. The impact of an HFD on protein conformation is less pronounced than HCD. The HFD diet led to an increase in antiparallel beta-sheets and a decrease in parallel beta sheets. Although insignificant, an increase was observed in beta-turn and alpha-helix. Conclusion: These results propose the appearance of protein aggregation and/or formation of protein- protein intermolecular interaction in skeletal muscle tissues of female inbred C57BL/6J mice. Collectively, these data suggest that both high-calorie diets impair secondary structures of protein in skeletal muscle that may affect its metabolic function
Arsa payı karşılığı inşaat sözleşmesinde ceza koşulu ve götürü tazminat
Get PDFArsa payı karşılığında kurulan inşaat sözleşmeleri, yüklenici tarafın yapıyı inşa ederek teslim
etmesi ile arsa sahibinin de bunun karşılığında belirli arsa paylarının yükleniciye devrini
taahhüt ettiği çifte tipli karma bir sözleşme türüdür. Ancak yüklenicinin inşaatı teslim
borcunu yerine getirmemesi ya da geç getirmesi nedeni ile bu durumu engellemek ve arsa
sahibinin zararlarını gidermek için sözleşmelerde ceza koşuluna ve götürü tazminata yer
verilmektedir.
Sözleşmelerde bulunan ceza koşulu ile götürü tazminat kayıtları karıştırıldığından dolayı bu
çalışmamızın amacı arsa payı karşılığı inşaat sözleşmelerinde bulunan götürü tazminat ve
ceza koşulunun amacının, niteliklerinin ve farklılıklarının kavranılmasıdır.
Çalışmamızın ilk bölümünde genel bir çerçevede arsa payı karşılığı inşaat sözleşmeleri
incelenmiştir.
Çalışmamızın ikinci bölümünde, ceza koşulu incelenmiş ve üçüncü bölümde götürü
tazminat ele alınarak götürü tazminat ve ceza koşulu arasındaki farklılıklar doktrin ve Yargı
kararları ışığında ele alınmıştır.The contract for construction in exchange for land share is a dual-type mixed contract in
which the contractor commits to building and delivering the structure, and the landowner, in
return, commits to transfer specific land shares to the contractor. However, to prevent the
contractor from failing to fulfill or delaying the delivery obligation of the construction, and
to compensate the the landowner’s losses, penalty clauses and lump-sum compensation are
included in the contracts.
Due to the confusion between penalty clauses and lump sum indemnities in contract records,
the purpose of this study is to comprehend the conditions, qualities, and differences of
penalty clauses and lump sum indemnities in land share agreement construction contracts.
In the first part of our study, construction contracts for land share were generally examined.
In the second part of the study, penalty clauses were examined, and in the third part, by
discussing the lump-sum compensation the differences between lump-sum compensation
and penalty clauses were analyzed in light of doctrine and judicial decisions
Resource management in cloud computing
Get PDFWhen it comes to cloud computing efficient resource management is important and crucial
to manage and to optimize resource and ensure that systems are performant. In this study
were using load balancing and VM provisioning to effectively manage IT resources. The
introduction and literature chapters outline what is cloud computing history of cloud and
what is resource management and challenges that business and organizations face when
managing IT resources so that they can effectively manage resource without the need of
investing capital in in-house IT resource. CloudSim is a popular simulation framework, we
used CloudSim simulation to simulate data of cloud infrastructure so that we can evaluate
and model the strategies were using in this study. The proposed techniques in this study
leverage dynamic and static load balancing algorithms and VM provisioning to optimize
resource utilization and minimize response time, reduce SLA violations and improve energy
consumption in cloud computing
Evaluation of the first Candida auris isolates reported from Türkiye in terms of identification by various methods and susceptibility to antifungal drugs
No full textPurpose: Candida auris is increasingly being isolated from patients all over the world. It has five clades. In this study, it was aimed to compare the results of biochemical tests obtained using different methods and the antifungal susceptibility profiles of C. auris strains isolated from the first seven cases reported in Türkiye, and evaluate whether this information could be useful as preliminary data in determining the clade of strains in centers that lack the opportunity to apply molecular methods.
Methods: Identification test results obtained using API ID 32 C, API 20 C AUX, VITEK-2 YST, and MALDI-TOF MS; colony color and morphology on Chromagar Candida, CHROMagar Candida Plus media, and cornmeal-Tween 80 agar; susceptibility to antifungals were tested and compared. Antifungal susceptibility test was studied using microdilution method according to the recommendations of EUCAST. Additionally, a pilot study was conducted to investigate the value of CHROMagar Candida Plus.
Results: All seven strains were identified as Lachancea kluyveri with API ID 32 C, Rhodotorula glutinis; Cryptococcus neoformans with API 20 C AUX, and C. auris with both VITEK-2 YST and MALDI-TOF MS. MIC values for fluconazole were very high (≥64 mg/L) for all seven strains. It was observed that 11 (37.9%) of 29 Candida parapsilosis strains formed colonies with morphology similar to C. auris on CHROMagar Candida Plus medium, leading to false positivity.
Conclusions: Although there have been many isolations of C. auris in our country in recent years, clade distribution of only a small number of strains is known yet. In this study, when the biochemical properties and antifungal susceptibility profiles of the seven strains were evaluated, it was concluded that they exhibited some characteristics compatible with clade I. It was also observed that strains 1 and 2 may belong to a different clade
Evaluation of Bacteriophage ?11 host recognition protein and its host-binding peptides for diagnosing/targeting of Saphylococcus aureus infections
No full textEvaluating the potential of using both synthetic and biological products as targeting agents for the diagnosis, imaging, and treatment of infections due to particularly antibiotic-resistant pathogens is important for controlling infections. We examined the interaction between Gp45, a receptor-binding protein of the ϕ11 lysogenic phage, and its host S. aureus, a common cause of nosocomial infections. Using molecular dynamics and docking simulations, we identified the peptides that bind to S. aureus wall teichoic acids via Gp45. We compared the binding affinity of Gp45 and the two highest-scoring peptide sequences (P1 and P3) and their scrambled forms using microscopy, spectroscopy, and ELISA. Our results revealed that rGp45 (recombinant Gp45) and chemically synthesized P1 had a higher binding affinity for S. aureus compared with all other peptides, with the exception of E. coli. Furthermore, rGp45 had a capture efficiency of over 86%; P1 had a capture efficiency of over 64%. Overall, our findings suggest that receptor-binding proteins such as rGp45, which provide a critical initiation of the phage life cycle for host adsorption, might play an important role in the diagnosis, imaging, and targeting of bacterial infections. Studying such proteins could accordingly enable the development of effective strategies for controlling infections
Detection methods for Legionella pneumophila in diverse environmental conditions: A comparative study of FISH, seminested PCR and conventional culture
Get PDFAims: Legionella bacteria cause Legionnaires' disease and Pontiac fever. It is commonly found in natural water resources and manmade water systems. Environmental conditions such as nutrient deficiency, temperature, pH, disinfectant and the presence of other bacteria can cause Legionella bacteria to pass into the viable but not-culturable (VBNC) phase. This study was aimed to determine appropriate methods to detect Legionella pneumophila bacteria living in water systems with wide temperature and pH ranges threatening human health. Methodology and results: In this study, water samples containing L. pneumophila at a concentration of 108 cell/L were exposed to different temperatures (5 degrees C, 50 degrees C, 55 degrees C and 60 degrees C) and pH (2.2, 5.8, 7.0 and 8.2) values. Conventional culture, FISH and seminested PCR methods were used to detect L. pneumophila. A comparison was made between the methods used in the study to determine the most appropriate method for detecting L. pneumophila bacteria. The results showed that the highest detection rates of L. pneumophila were at 5 degrees C for 24 h (100%) and at pH 2.2 for 0th min (100%) by using FISH method. All the samples could be determined by the seminested PCR method. The results of our study showed that the highest detection rates of L. pneumophila were at 5 degrees C for 24 h (100%) and at pH 2.2 for 0 min (100%) by FISH method. All of the samples could be determined by the seminested PCR method. It was determined that the detection rate was the lowest in the FISH method at 3 min at 60 degrees C and the highest was 24 h at 5 degrees C. The lowest detection rate was also observed by using FISH method in the samples exposed to 60 degrees C for 3 min. Results show that the FISH and seminested PCR methods are the most suitable for detecting L. pneumophila bacteria from water systems exposed to different environmental conditions. Conclusion, significance and impact of study: Different methods (conventional culture, FISH, seminested PCR) used to detect L. pneumophila bacteria were compared in this study. It was concluded that Legionella bacteria passed into the VBNC phase, and compared to molecular methods, the conventional culture method provides a low detection rate of these bacteria. Research findings suggest that it is insufficient to use the conventional culture method alone for the detection of Legionella bacteria from man-made water systems or human samples. This study is important as it is decisive for the determination of the most appropriate method for detecting the human pathogen L. pneumophila bacteria from water samples and the choice for a fast and effective method for the elimination of the infectious agent.İstanbul University, The Scientific Research Project (BAP) Department, project number: 23947
The comparison of Samuel P. Huntington's "Clash of Civilizations" and Immanuel Wallerstein's "World Systems Analysis"
Get PDFSince it has been published as an article in the journal “Foreign Affairs” in 1993, “The Clash
of Civilizations” has been the subject of social science studies. It has been examined under
many titles such as “Eurocentrism”, “dualism” “historic evolution” or as a “critical theory”.
Nowadays, civilization-based critiques are done more frequently. At the same time, the
world is going through a new economic crisis. Both "The Clash of Civilizations" and "The
World Systems Analysis" have vital importance to shape the policy of the future. In this
study, the civilizational division which is suggested by Samuel P. Huntington is going to be
compared to the work of Immanuel Wallerstein “world systems theory” which has an
economic stance to the conflicts. As a starting point, Samuel P. Huntington’s book "Clash
of Civilizations" is going to be analyzed, and next, Immanuel Wallerstein’s “World Systems
Analysis” is going to be summed up. Both approaches have their own claims, and both
approaches deal with the recent past. While Huntington takes matters from the window of
policy, Wallerstein’s approach is from an economic point of view. There are accurate cases
for both theses. The accuracy stems from the historic recurrence which means “history
repeats itself.
Enhancing maximum power point tracking through ensemble learning techniques
Get PDFMaximum Power Point Tracking (MPPT) is an essential method in photovoltaic (PV) solar
systems for optimizing the extraction of available power. This technique enhances energy
conversion efficiency and aligns with ongoing efforts to improve the effectiveness of
renewable energy sources. This thesis presents a systematic investigation into the predictive
modeling of solar energy phenomena, specifically focusing on solar power generation and
solar radiation prediction. Through the comprehensive evaluation of various individual
machine learning models, including Linear Regression (LR), Support Vector Regression
(SVR), and XGBoost Regressor, as well as an Ensemble Learning (EL) approach, the study
elucidates the complexities and nuances of modeling solar energy systems. The analysis was
conducted on two distinct datasets: Solar Power Generation and Solar Radiation Prediction.
The individual models were rigorously assessed using multiple statistical metrics, revealing
varying degrees of accuracy, fit, and performance. A remarkable discovery was the efficacy
of the Ensemble Learning model, employing techniques such as Bagging Regressor, which
consistently outperformed the individual models across both datasets. By adeptly
aggregating the predictions of multiple underlying models, the EL approach achieved
superior predictive accuracy, explaining an impressive proportion of the variance in both
solar power generation and solar radiation. The findings of this research contribute significantly to the understanding of solar energy modeling, endorsing ensemble learning as
a potent and versatile tool for enhancing prediction accuracy. Moreover, the comparative
analysis sheds light on the trade-offs between different modeling techniques, offering
guidance for future research and practical applications within the renewable energy sector.
This thesis not only sets a new benchmark in the field of solar energy forecasting but also
aligns with the broader imperatives of sustainable energy management and climate
stewardship