190 research outputs found
Pengaruh Kualitas Produk Dan Pelayanan Terhadap Kepuasan Konsumen (Studi Kasus Toko Nikimi Mart Tebo)
This study aims to determine the effect of product and service quality on customer satisfaction and to determine which product and service quality has the most dominant influence on customer satisfaction. The research method uses multiple linear regression with the F test, t test and determination test. The results of the study concluded that based on the F test (simultaneous) used to determine the significance of the effect of the independent variables (product quality and service quality) on the dependent variable (customer satisfaction) simultaneously. The results can be concluded, H0 is rejected and H1 is accepted. Product quality and service quality simultaneously have a significant effect on Nikimi Mart customer satisfaction. Based on the results of individual (partial) tests, it can be seen that the variable that most influences consumer satisfaction at Nikimi Mart is the variable service quality (X2). H0 is accepted and H1 is rejected, in other words, product quality partially has no significant effect on Nikimi Mart customer satisfaction and on the service quality variable (X2), H0 is rejected and H2 is accepted, in other words, service quality partially has a significant effect on Nikimi Mart customer satisfaction
Public Financial management of the Sovereing Wealth Funds
I am interested in the role of national funds in forming the economic overview, and also, the role of these funds in integration and globalization processes. The significance of the problem requires the development of recommendations and mechanisms in order to form the transparency of available information for public following the international standards, as a consequence the improvement of processes of democratization through public control.
Contemporary economic conditions and positive tendencies in public financial management require special attention to develop methods and instruments. The purpose is to develop the public financial management.
Several studies exist on the oil industry of the Caspian Region but few focus on strategies for its long term grows. The gap of proposed study will seek to fill is the insufficiency of literature on ways to promote national funds role of the oil industry. The research thesis is that the oil industry our countries lack pure understanding about the role of the oil revenue for future
Spectral conditions for spherical two-distance sets
A set of points in -dimensional Euclidean space is
called a 2-distance set if the set of pairwise distances between the points has
cardinality two. The 2-distance set is called spherical if its points lie on
the unit sphere in . We characterize the spherical 2-distance
sets using the spectrum of the adjacency matrix of an associated graph and the
spectrum of the projection of the adjacency matrix onto the orthogonal
complement of the all-ones vector. We also determine the lowest dimensional
space in which a given spherical 2-distance set could be represented using the
graph spectrum.Comment: 12 pages, 2 table
Incidence of depression among nurses in Kashmir valley
Background: In 2017, 197 million Indians were suffering from mental disorders, of whom 46 million had depression. In Kashmir, 41% have been identified as having probable depression. Depression is one of the most frequently diagnosed mental illness which is characterized by feelings of sadness, loss of energy, motivation, concentration, changes in appetite, changes in sleep, etc. Depression is known to impact work performance, their colleagues and potentially on the quality of care provided to patients. Nursing, a loyal profession, is considered as one of the most susceptible profession to depression. This study was conducted with the aim of finding the incidence of depression among Nurses.Methods: A descriptive, cross sectional study was conducted on 200 Nurses collected by using convenient sampling from different hospitals in Srinagar district of Kashmir Valley in order to assess the incidence of Depression among them. Depression was diagnosed by following Diagnostic and Statistical Manual-5 (DSM-5) criteria and assessment was done on the bases of age, gender, marital status, family type and residence.Results: Majority of the Nurses were found to be females (68%), above 30 years (64%), belonged to nuclear family (69%), married (71%) and residing in rural areas (64%). As for as incidence of depression is concerned, 134 (67%) Nurses were found to be having symptoms of depression.Conclusions: Most of the Nurses were diagnosed with depression that has a negative impact on the patient care. Thus, there is a dire need for screening of the Nurses and thus early detection of affected one's
Computational Intelligence Approaches for Enhancing Biomedical Image Processing Applications Based on Breast Cancer
Recent advances in the cutting-edge technologies of biomedical sensing and image processing tools provide us with big data of biomedical and various types of images that can’t be processed within a finite period by professional clinicians. Various techniques for processing biomedical images comprise mathematical algorithms that extract vital diagnostic features from biomedical information and biological data. Because of the complexity and big size of the data computation, intelligence techniques have been applied in processing, visualizing, diagnostic, and classification tasks. This study will explore the effectiveness of the variously artificial intelligence approaches on biomedical signal and image processing applications. The researchers and community entirely will benefit from this study as a guide to the state-of-the-art artificial intelligence techniques for biomedical signal and image processing applications
Russie : un partenariat stratégique avec la Chine n'est pas d'actualité
Cet article propose une réflexion sur le positionnement de la Russie face à différentes alliances possibles en Asie. Il met l’accent sur les contraintes que fait peser la politique intérieure russe et souligne les difficultés de ces coopérations. La concrétisation d’un véritable partenariat stratégique avec la Chine paraît peu probable
Simulation of 2-dimensional Turbulent Flow Using Lattice-Gas Cellular Automata
V práci se studuje simulace dvojrozměrného toku nestlačitelné, ale viskózní kapaliny kolem libovolné překážky, zejména leteckého profilu. V teoretické části podáváme přehled dvou typu hydrodynamických celulárních automatu (HPP a FHP modely) a úvod do jejich statistické analýzy. V části "Výsledky" popisujeme program vytvořený v jazyce C++ implementující FHP model a prezentujeme výsledky, jež byly s jeho pomocí získány. Práce je doplněna dodatky s teorií rotací a s obrázky dokumentujícími provedené simulace.In this thesis, we study the simulations of two-dimensional flow of the incompressible, but viscid liquid past the obstacle of an arbitrary shape, in particular, past the airfoil. In the theoretical part, we review two types of the lattice-gas cellular automata (HPP and FHP models) and introduction to their statistical analysis. In the part "Results" we describe the program created in the C++ language which implements the FHP model and we present the results obtained with the help of this program. The work is supplemented with appendices devoted to the theory of rotations and with figures and images accompanying the simulations which were performed
Comparative Analysis of Some Prominent Machine Learning Algorithm for the Prediction of Chronic Kidney Disease
Chronic Kidney Disease (CKD) is a disorder against proper function regarding kidneys, as kidneys filter our blood whenever CKD gets worse, our blood receives wastes at a higher level, which results in sickness. It also has a substantial financial problem for families of subjects with a medical issue in Nigeria. Among the necessary measures that need action concerning the increase of CKD is detecting the disease early and with different data mining techniques. Data mining is gradually becoming more prevalent nowadays in healthcare, as also in fraud, abuse detection etc. Classification is a more useful data mining function to handle items in a collection to class or target categories. For obtaining essential information from medical database, machine learning and statistical analysis can assist in extracting hidden patterns and identify relationships from vast among of data. In this study, we compared five (5) different models namely: Deep Neural Network (DNN), Artificial Neural Network (ANN), Naïve Bayes (NB), Logistic Regression (LR), and K-Neighbor Nearest (KNN) to predict CKD on Gashua General Hospital (GGH) dataset. The study achieved an accuracy of 98% for DNN, KNN: 96%, NB: 97%, LR: 96% and ANN: 96%. The best performance was obtained with DNN with the highest accuracy and can be applied in real world application.  
Analyzing Facebook Mobile Usage: Efficacy and ESL Learners’ Writing Proficiency
Facebook has leveraged rapid technological and societal changes over the past decade and has emerged as the largest social networking platform. However, research on Facebook has been limited, particularly when examining its potential to improve English as a second language (ESL) writing in comparison to a control group. The study aims to explore the morphological, syntactic, and orthographical aspects of ESL writing through an experimental group [N = 30] using Facebook on mobile and a control group [N = 30] with a traditional teaching approach. The experimental and control groups undergo observation through twice-weekly, in-class-focused free writing sessions for 10 weeks. The progress of the learners’ writing was tracked using pre- and post-tests to assess its impact. The analysis of variance (ANOVA) test revealed that the experimental group made more significant advancements in writing by reducing morphological, syntactic, and orthographical errors compared to the control group. These results validate previous studies that support the use of Facebook on mobile devices in ESL courses and emphasize the need for further research comparing Facebook with other writing platforms
- …