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1CONN Creative Reklam Ajansı
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Performance and Buffering Requirements of Internet Protocols over ATM ABR and UBR Services
The Asynchronous Transfer Mode (ATM) networks are quickly being adopted as backbones over various parts of the Internet. This paper analyzes the performance of TCP/IP protocols over ATM network's Available Bit Rate (ABR) and Unspecified Bit Rate (UBR) services. It is shown that ABR pushes congestion to the edges of the ATM network while UBR leaves it inside the ATM portion.
Multiobjective Logistics Optimization for Automated ATM Cash Replenishment Process
In the digital transformation era, integrating digital technology into every aspect of banking operations improves process automation, cost efficiency, and service level improvement. Although logistics for ATM cash is a crucial task that impacts operating costs and consumer satisfaction, there has been little effort to enhance it. Specifically, in Vietnam, with a market of more than 20,000 ATMs nationally, research and technological solutions that can resolve this issue remain scarce. In this paper, we generalized the vehicle routing problem for ATM cash replenishment, suggested a mathematical model and then offered a tool to evaluate various situations. When being evaluated on the simulated dataset, our proposed model and method produced encouraging results with the benefits of cutting ATM cash operating costs.
Study of $\ep\en$ Collisions in the 1.5-3 Gev C.M. Energy Region Using Isr at \babar
A preliminary analysis of low-energy $\ep\en$ collision data produced via initial state radiation (ISR) has been performed using 22 $fb^{-1}$ of \babar data. The selection of data samples corresponding to the $\mumu$, $\pipi$, $\kk$, $p \bar p$, $\kkπ^0$, 3$π$, 4$π$, 5$π$, 6$π$, 7$π$ final states accompanied by the emitted ISR hard photon has been demonstrated. The invariant mass of the hadronic final state defines the effective collision c.m. energy, and so \babar ISR data can be compared to the relevant direct $\ep\en$ measurements. The resulting distributions are already competitive with DCI and ADONE data in the 1.4-3.0 GeV energy range. In particular, they do not suffer from the relative normalization uncertainties observed for certain reactions when results from different experiments are combined. Eventually, such data may be used to measure the energy dependence of R, the ratio of the $\ep\en\to hadrons$ and $\ep\en\to\mumu$ cross sections, in the low-energy regime where precise measurements will have an impact on the interpretation of the new $(g-2)_μ$ measurements.
A Framework for the Adoption of Biometric ATM Authentication in the Kenyan Banks
The use of ATMs has become fundamental in the banking industry owing to the values transacted using these systems and their 24/7 usage. Although several researchers have studied the role of biometrics in security applications for financial institutions, no systematic empirical research has been applied to studying the role of organizational characteristics and contextual factors in the Kenyan financial sector. This study sought to develop a framework for the adoption of biometric ATMs in the Kenyan banking sector, apply the developed framework to study factors influencing adoption of biometric ATM authentication and validate the developed conceptual framework. A survey was used to collect quantitative data from the ATM users which was then analysed using factor analysis and multiple regression analysis. The study established that performance expectancy, effort expectancy, social influence and user privacy were key determinants for biometric ATMs acceptance, adoption and usage. The study further demonstrated that age, gender and experience were moderating factors on effort expectancy with experience further moderating performance expectancy, effort expectancy, social influence and …
Lasing in 15 atm CO2 cell optically pumped by a Fe:ZnSe laser
10 μm lasing is studied in a compact CO2-He cell pressurized up to 15 atm when optically pumped by a ~50 mJ Fe:ZnSe laser tunable around 4.3 μm. The optimal pump wavelength and partial pressure of CO2 for generating 10 μm pulses are found to be ~4.4 μm and 0.75 atm, respectively. Without cavity optimization, the optical-to-optical conversion efficiency reached ~10% at a total pressure of 7 atm. The gain lifetime is measured to be ~1 μs at pressures above 10 atm, indicating the feasibility of using high-pressure optically pumped CO2 for the efficient amplification of picosecond 10 μm pulses.
Location Optimization of ATM Networks
ATMs enable the public to perform financial transactions. Banks try to strategically position their ATMs in order to maximize transactions and revenue. In this paper, we introduce a model which provides a score to an ATM location, which serves as an indicator of its relative likelihood of transactions. In order to efficiently capture the spatially dynamic features, we utilize two concurrent prediction models: the local model which encodes the spatial variance by considering highly energetic features in a given location, and the global model which enforces the dominant trends in the entire data and serves as a feedback to the local model to prevent overfitting. The major challenge in learning the model parameters is the lack of an objective function. The model is trained using a synthetic objective function using the dominant features returned from the k-means clustering algorithm in the local model. The results obtained from the energetic features using the models are encouraging.
ATM: a Logic for Quantitative Security Properties on Attack Trees
Critical infrastructure systems - for which high reliability and availability are paramount - must operate securely. Attack trees (ATs) are hierarchical diagrams that offer a flexible modelling language used to assess how systems can be attacked. ATs are widely employed both in industry and academia but - in spite of their popularity - little work has been done to give practitioners instruments to formulate queries on ATs in an understandable yet powerful way. In this paper we fill this gap by presenting ATM, a logic to express quantitative security properties on ATs. ATM allows for the specification of properties involved with security metrics that include "cost", "probability" and "skill" and permits the formulation of insightful what-if scenarios. To showcase its potential, we apply ATM to the case study of a CubeSAT, presenting three different ways in which an attacker can compromise its availability. We showcase property specification on the corresponding attack tree and we present theory and algorithms - based on binary decision diagrams - to check properties and compute metrics of ATM-formulae.
Reachability is Decidable for ATM-Typable Finitary PCF with Effect Handlers
It is well known that the reachability problem for simply-typed lambda calculus with recursive definitions and finite base-type values (finitary PCF) is decidable. A recent paper by Dal Lago and Ghyselen has shown that the same problem becomes undecidable when the language is extended with algebraic effect and handlers (effect handlers). We show that, perhaps surprisingly, the problem becomes decidable even with effect handlers when the type system is extended with answer type modification (ATM). A natural intuition may find the result contradictory, because one would expect allowing ATM makes more programs typable. Indeed, this intuition is correct in that there are programs that are typable with ATM but not without it, as we shall show in the paper. However, a corollary of our decidability result is that the converse is true as well: there are programs that are typable without ATM but becomes untypable with ATM, and we will show concrete examples of such programs in the paper. Our decidability result is proven by a novel continuation passing style (CPS) transformation that transforms an ATM-typable finitary PCF program with effect handlers to a finitary PCF program without …
Smart Routing for EV Charge Point Operators in Mega Cities: Case Study of Istanbul
The rapidly increasing use of electric vehicles (EVs) has made it even more important to manage the charging infrastructure sustainably. The expansion of charging station networks, especially in large cities, creates serious logistical challenges for charging point operators (CPOs) in planning maintenance and repair activities. Inefficient field personnel management can lead to time loss, high operational costs, and resource waste. This study presents an integrated method to optimize the planning of EV charging network maintenance operations. The proposed approach groups charging stations according to geographical proximity using the K-means clustering algorithm and calculates the shortest routes between clusters using a genetic algorithm. The method was developed in Python and applied to a dataset consisting of 100 EV charging stations in Istanbul. Considering the population density, traffic density, and resource constraints of Istanbul, the route planning approach presented in this study has great potential, especially for such metropolises. According to the different parameter configurations tested, the most efficient scenario provided approximately 35\% distance savings …
Credit Risk Estimation with Non-Financial Features: Evidence from a Synthetic Istanbul Dataset
Financial exclusion constrains entrepreneurship, increases income volatility, and widens wealth gaps. Underbanked consumers in Istanbul often have no bureau file because their earnings and payments flow through informal channels. To study how such borrowers can be evaluated we create a synthetic dataset of one hundred thousand Istanbul residents that reproduces first quarter 2025 TÜİK (TURKSTAT) census marginals and telecom usage patterns. Retrieval augmented generation feeds these public statistics into the OpenAI o3 model, which synthesises realistic yet private records. Each profile contains seven socio demographic variables and nine alternative attributes that describe phone specifications, online shopping rhythm, subscription spend, car ownership, monthly rent, and a credit card flag. To test the impact of the alternative financial data CatBoost, LightGBM, and XGBoost are each trained in two versions. Demo models use only the socio demographic variables; Full models include both socio demographic and alternative attributes. Across five fold stratified validation the alternative block raises area under the curve by about one point three percentage and lifts balanced F 1 from …
Dentastik Klinik Yönetimi
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