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1CONN Creative Reklam Ajansı
Sektörünüzle ilgili genel ve yerel bilgileri büyük bir titizlikle araştırıyor, sizin için gerçekleştireceğimiz çalışmalarımıza bu bilgiler ışığında yön veriyoruz. İlk düşündüğümüz; “Biz, bu markaya ne katabiliriz?”
Analyzing Collaborative Forecast and Response Networks
Collaborative forecasting involves exchanging information on how much of an item will be needed by a buyer and how much can be supplied by a seller or manufacturer in a supply chain. This exchange allows parties to plan their operations based on the needs and limitations of their supply chain partner. The success of this system critically depends on the healthy flow of information. This paper focuses on methods to easily analyze and visualize this process. To understand how the information travels on this network and how parties react to new information from their partners, this paper proposes a Gaussian Graphical Model based method, and finds certain inefficiencies in the system. To simplify and better understand the update structure, a Continuum Canonical Correlation based method is proposed. The analytical tools introduced in this article are implemented as a part of a forecasting solution software developed to aid the forecasting practice of a large company.
Uncertainty Quantification in Neural-Network Based Pain Intensity Estimation
Improper pain management can lead to severe physical or mental consequences, including suffering, and an increased risk of opioid dependency. Assessing the presence and severity of pain is imperative to prevent such outcomes and determine the appropriate intervention. However, the evaluation of pain intensity is challenging because different individuals experience pain differently. To overcome this, researchers have employed machine learning models to evaluate pain intensity objectively. However, these efforts have primarily focused on point estimation of pain, disregarding the inherent uncertainty and variability present in the data and model. Consequently, the point estimates provide only partial information for clinical decision-making. This study presents a neural network-based method for objective pain interval estimation, incorporating uncertainty quantification. This work explores three algorithms: the bootstrap method, lower and upper bound estimation (LossL) optimized by genetic algorithm, and modified lower and upper bound estimation (LossS) optimized by gradient descent algorithm. Our empirical results reveal that LossS outperforms the other two by providing a narrower …
Reflexivity of Rings via Nilpotent Elements
An ideal $I$ of a ring $R$ is called left N-reflexive if for any $a\in$ nil$(R)$, $b\in R$, being $aRb \subseteq I$ implies $bRa \subseteq I$ where nil$(R)$ is the set of all nilpotent elements of $R$. The ring $R$ is called left N-reflexive if the zero ideal is left N-reflexive. We study the properties of left N-reflexive rings and related concepts. Since reflexive rings and reduced rings are left N-reflexive, we investigate the sufficient conditions for left N-reflexive rings to be reflexive and reduced. We first consider basic extensions of left N-reflexive rings. For an ideal-symmetric ideal $I$ of a ring $R$, $R/I$ is left N-reflexive. If an ideal $I$ of a ring $R$ is reduced as a ring without identity and $R/I$ is left N-reflexive, then $R$ is left N-reflexive. If $R$ is a quasi-Armendariz ring and the coefficients of any nilpotent polynomial in $R[x]$ are nilpotent in $R$, it is proved that $R$ is left N-reflexive if and only if $R[x]$ is left N-reflexive. We show that the concept of N-reflexivity is weaker than that of reflexivity and stronger than that of left N-right idempotent reflexivity and right idempotent reflexivity which are introduced in Section 5.
Dynamics of a mathematical model of virus spreading incorporating the effect of a vaccine
The COVID-19 pandemic led to widespread interest in epidemiological models. In this context the role of vaccination in influencing the spreading of the disease is of particular interest. There has also been a lot of debate on the role of non-pharmaceutical interventions such as the disinfection of surfaces. We investigate a mathematical model for the spread of a disease which includes both imperfect vaccination and infection due to virus in the environment. The latter is studied with the help of two phenomenological models for the force of infection. In one of these models we find that backward bifurcations take place so that for some parameter values an endemic steady state exists although the basic reproduction ratio $R_0$ is less than one. We also prove that in that case there can exist more than one endemic steady state. In the other model all generic transcritical bifurcations are forward bifurcations so that these effects cannot occur. Thus we see that the occurrence of backward bifurcations, which can be important for disease control strategies, is dependent on the details of the function describing the force of infection. By means of simulations the predictions of this …
Decorrelated Soft Actor-Critic for Efficient Deep Reinforcement Learning
The effectiveness of credit assignment in reinforcement learning (RL) when dealing with high-dimensional data is influenced by the success of representation learning via deep neural networks, and has implications for the sample efficiency of deep RL algorithms. Input decorrelation has been previously introduced as a method to speed up optimization in neural networks, and has proven impactful in both efficient deep learning and as a method for effective representation learning for deep RL algorithms. We propose a novel approach to online decorrelation in deep RL based on the decorrelated backpropagation algorithm that seamlessly integrates the decorrelation process into the RL training pipeline. Decorrelation matrices are added to each layer, which are updated using a separate decorrelation learning rule that minimizes the total decorrelation loss across all layers, in parallel to minimizing the usual RL loss. We used our approach in combination with the soft actor-critic (SAC) method, which we refer to as decorrelated soft actor-critic (DSAC). Experiments on the Atari 100k benchmark with DSAC shows, compared to the regular SAC baseline, faster training in five out of the seven …
An SIRS-model considering waning efficiency and periodic re-vaccination
In this paper, we extend the classical SIRS (Susceptible-Infectious-Recovered-Susceptible) model from mathematical epidemiology by incorporating a vaccinated compartment, V, accounting for an imperfect vaccine with waning efficacy over time. The SIRSV-model divides the population into four compartments and introduces periodic re-vaccination for waning immunity. The efficiency of the vaccine is assumed to decay with the time passed since the vaccination. Periodic re-vaccinations are applied to the population. We develop a partial differential equation (PDE) model for the continuous vaccination time and a coupled ordinary differential equation (ODE) system when discretizing the vaccination period. We analyze the equilibria of the ODE model and investigate the linear stability of the disease-free equilibrium (DFE). Furthermore, we explore an optimization framework where vaccination rate, re-vaccination time, and non-pharmaceutical interventions (NPIs) are control variables to minimize infection levels. The optimization objective is defined using different norm-based measures of infected individuals. A numerical analysis of the model's dynamic behavior under varying control parameters …
A Copula Approach to Inventory Pooling Problems with Newsvendor Products
This study focuses on the inventory pooling problem under the newsvendor framework. The specific focus is the change in inventory levels when product inventories are pooled. We provide analytical conditions under which an increase (or decrease) in the total inventory levels should be expected. We introduce the copula framework to model a wide range of dependence structures between pooled demands, and provide a numerical study that gives valuable insights into the effect of marginal demand distributions and dependence structure on the effect of pooling to inventory levels.
Implementation of Technology Acceptance Model (TAM) and Importance Performance Analysis (IPA) in Testing the Ease and Usability of E-wallet Applications
Digital payment innovation is currently increasingly needed by the community, especially in making non-cash payment transactions. The purpose of this research is to know and measure the ease and usefulness of e-wallet digital wallet services, especially in the GoPay application. The population in this study are users of the Go-Pay service on the GO-JEK platform. The sample of this study consisted of 124 respondents from distributing questionnaires in Depok, West Java using a modified Technology Acceptance Model (TAM) based on existing references. The data processing in this research uses Importance Performance Analysis (IPA) analysis. The results show that based on the gap analysis, it is found that in general Go-Pay users are not satisfied with the current service quality. Based on the IPA analysis, the priority scale of E-Wallet Go-Pay quality improvement can be mapped, where quadrant I is the highest priority scale according to the user's perspective: [1], [4], [5], and [6]. These three items must be upgraded immediately by the manager to meet user expectations. Areas that become the achievements or advantages of the GoPay E-Wallet that must be maintained are in quadrant II, …
Pseudo-spherical submanifolds with 1-type pseudo-spherical Gauss map
In this work, we study the pseudo-Riemannian submanifolds of a pseudo-sphere with 1-type pseudo-spherical Gauss map. First, we classify the Lorentzian surfaces in a 4-dimensional pseudo-sphere $\mathbb{S}^4_s(1)$ with index s, $s=1, 2$, and having harmonic pseudo-spherical Gauss map. Then we give a characterization theorem for pseudo-Riemannian submanifolds of a pseudo-sphere $\mathbb{S}^{m-1}_s(1)\subset\mathbb{E}^m_s$ with 1-type pseudo-spherical Gauss map, and we classify spacelike surfaces and Lorentzian surfaces in the de Sitter space $\mathbb{S}^4_1(1)\subset\mathbb{E}^5_1$ with 1-type pseudo-spherical Gauss map. Finally, according to the causal character of the mean curvature vector we obtain the classification of submanifolds of a pseudo-sphere having 1-type pseudo-spherical Gauss map with nonzero constant component in its spectral decomposition.
Review and Analysis of Pain Research Literature through Keyword Co-occurrence Networks
Pain is a significant public health problem as the number of individuals with a history of pain globally keeps growing. In response, many synergistic research areas have been coming together to address pain-related issues. This work conducts a review and analysis of a vast body of pain-related literature using the keyword co-occurrence network (KCN) methodology. In this method, a set of KCNs is constructed by treating keywords as nodes and the co-occurrence of keywords as links between the nodes. Since keywords represent the knowledge components of research articles, analysis of KCNs will reveal the knowledge structure and research trends in the literature. This study extracted and analyzed keywords from 264,560 pain-related research articles indexed in IEEE, PubMed, Engineering Village, and Web of Science published between 2002 and 2021. We observed rapid growth in pain literature in the last two decades: the number of articles has grown nearly threefold, and the number of keywords has grown by a factor of 7. We identified emerging and declining research trends in sensors/methods, biomedical, and treatment tracks. We also extracted the most frequently co-occurring keyword pairs …
Dentastik Klinik Yönetimi
Kliniğinizin tüm dünyası Tek bir akış. İlk temastan son kontrole. Satıştan tedaviye. Birbirine bağlı her an, tek ekosistemde.
1Klinik CMS Web Yönetim Sistemi
Yeni Nesil Klinik Deneyimi. Bilim, teknoloji ve estetiği modern hasta deneyimiyle bir araya getiriyoruz. Dijital planlama, kişiye özel tedavi yaklaşımı ve güçlü hasta iletişimi.
