2,454 research outputs found
Influencing Factors on Customer Satisfaction and Repurchase Intention Towards Moony and Myint Mo Online Shopping (May Thu Win Saung, 2025)
No full textThis study aims to investigate the factors affecting online shopping that influence
customer satisfaction, to explore how customer satisfaction impacts repurchase intention,
to evaluate the moderating role of relationship commitment on the connection between
customer satisfaction and repurchase intention, and to assess the moderating role of
switching costs on the link between customer satisfaction and repurchase intention in
relation to Moony and Myint Mo Online Shopping. This study utilizes both primary and
secondary data. Primary data were gathered from 377 customers of Moony and Myint Mo
Online Shopping through a systematic random sampling technique. Data will be gathered
from every 5th customer who buys a product from the Moony and Myint Mo online store.
A structured questionnaire utilizing a 5-point Likert scale is employed to gather primary
data through an online survey approach. Secondary data is collected from earlier research
studies, websites, and various other relevant sources. Descriptive statistics and regression
analysis are employed to examine the data. The regression analysis indicates that
information quality, product diversity, delivery, pricing, and reputation positively and
significantly influence customer satisfaction. There is no moderating influence of
relationship commitment and switching costs on customer satisfaction. Moony and Myint
Mo Online Shopping ought to effectively handle and encourage favorable customer
feedback on various platforms, including Facebook, Google, and online marketplaces
MassConf: Automatic Configuration Tuning By Leveraging User Community Information
No full textConfiguring modern enterprise software can be extremely difficult, because its behavior often depends on large numbers of configuration parameters. We argue that vendors can simplify the configuration process for new users of their software by collecting and using configuration information from the existing user community. Our proposed approach is based on the observations that (1) a “good” configuration may work well for many different users, and (2) multiple good configurations may work well for each user. We demonstrate our idea by designing MassConf, a system that collects and uses existing configurations to automatically configure new software installations. To evaluate MassConf, we use it to configure the Apache Web server to achieve a response-time target. Our results confirm our observations and show that MassConf successfully reaches the targets of many more new installations than an existing efficient optimization algorithm. Even when we consider only the installations that can be configured with this efficient algorithm, our results show that MassConf reaches the desired targets running many fewer experiments on average.Technical report DCS-TR-66
Quantifying and Improving I/O Predictability in Virtualized Systems
No full textVirtualization enables the consolidation of virtual machines (VMs) to increase the utilization of physical servers in Infrastructure-as-a-Service (IaaS) cloud providers. Unfortunately, our quantification of storage I/O performance across a range of workloads, virtual machine monitor (VMM) architectures, approaches to storage virtualization, and storage devices shows widespread performance unpredictability in the face of consolidation. Surprisingly, the use of solid-state drives (SSDs) can exacerbate the problem. Since many users may desire consistent performance, we argue that IaaS cloud providers should provide a class of predictable-performance service in addition to their existing (predictability-oblivious) services. Thus, we propose and evaluate VirtualFence, a storage system that provides predictable performance for this new class of service. VirtualFence uses three main techniques: (1) non-work-conserving time-division I/O scheduling, (2) a small SSD cache in front of a much larger hard disk drive (HDD), and (3) space-partitioning of both the SSD cache and the HDD. Our evaluation of a prototype VirtualFence implemented in the Xen VMM shows that VirtualFence improves predictability significantly. More fundamentally, our evaluation illustrates the tradeoff between predictability and performance. We conclude that current VMMs are far from providing predictability. Systems like VirtualFence can remedy this problem, while allowing the cloud provider to select an appropriate compromise between performance and predictability.Technical report DCS-TR-69
GreenCassandra: Using Renewable Energy in Distributed Structured Storage Systems
No full textOn-site generation of renewable (“green”) energy can help to significantly reduce grid (“brown”) energy consumption, and correspondingly the carbon footprint, of datacenters. However, it is challenging to use green energy generated from sources such as solar and wind because energy production is variable. In this paper, we investigate how to manage an interactive service, where response time is a critical performance metric, to maximize the benefits of green energy produced from these sources. Specifically, we design, prototype, and evaluate a distributed structured storage system, GreenCassandra, which is representative of a class of important subsystems underlying many interactive cloud services. Our proposed approach predicts the production of solar energy, and then controls the number of active nodes to manage energy consumption while respecting a response time SLA. When green energy is available, GreenCassandra may activate extra servers to build up slack with respect to the SLA. When using brown energy, GreenCassandra deactivates servers to reduce energy consumption, leveraging any built-up performance slack, while observing constraints imposed by the SLA. Evaluations show that GreenCassandra can use a heuristic green-energy-aware policy to decrease brown energy consumption and cost by up to 28% and 29%, respectively. Further, these savings are very close to those achievable by an optimizationbased policy that has perfect knowledge of future workload and green energy production.Technical report DCS-TR-71
Application-aware Traffic Engineering in Software Defined Networking
No full textThe integration of control and data planes into the same devices and lack theglobal centralization control that made the traditional networks may not meet therequirements of the emerging cloud computing, the tactile Internet, and the Internet ofThings (IoT) technology. Moreover, the traditional networks cannot provide thecomplexity of control protocols, complex traffic engineering (TE) tasks, andinterconnecting of a huge number of smart devices. Software Defined Networking(SDN) is an architecture that overcomes the above issues of the traditional networks bytaking advantage of global centralization control, decouples of the control and dataplanes, and enabling innovation through the network programmability.The shortest path-based routing cannot guarantee future traffic demandsbecause the routing only uses the minimum hop counts. The application-aware routingis more efficient than the traditional shortest path-based routing; however, classificationof application traffic and estimation of QoS parameters like link utilization and linkdelay are needed to perform such kind of routing. By taking the advantage of SDN,application-aware traffic engineering can perform more effectively in SDNenvironments.This dissertation presents an application-aware traffic engineering (App-TE) inSDN which generally involves three main modules: traffic classification, trafficmeasurement, and traffic management. Application traffic flows classified into thefollowing two classes: prioritized application traffic and non-prioritized applicationtraffic by using port number and protocol number with the help of traffic analyzer(sFlow-RT). The classified traffic flows are fed to the traffic measurement module tocalculate the link utilization, link delay, and Delay Weighted Capacity (DWC) values.Finally, prioritized application traffic flows are routed by using the DWC-aware routingand non-prioritized application traffic flows are routed by using shortest path routing(or) minimum hop-count based routing. The experimental results demonstrated that theaverage throughput results of the proposed App-TE outperformed the shortest pathrouting and LU-aware routing
Comparative evaluation of power loss in HVAC and HVDC transmission systems
No full textWorld energy consumption rate is ascending consistently over the past few decades and it is expected to continue rising in the future. Researches on renewable energy sources have been carried out and ways to reduce energy consumption and energy wastage have been discussed and studied to tackle the world’s power shortage problems. Therefore, this project presents a comparison of power loss for various transmission systems. Two different transmission systems are analysed in this project; HVAC and HVDC. High Voltage Alternating Current (HVAC) transmission system and High Voltage Direct Current (HVDC) transmission systems are simulated in PSCAD software. The major components; transmission station, transformer and transmission line are investigated to evaluate their influence on the power loss. The cable length is also varied to analyse its effect in term of power loss on these two transmission systems. The experimental findings and analysis are presented in this project. The research presented in this project identifies the key sources of power loss while transmitting power from generator to load through HVAC and HVDC transmission systems. These findings will ultimately assist in accessing the design and analysis on economic feasibility of the transmission system.Bachelor of Accountanc
Natural Scene Interactive Segmentation Using Edge Detection and Maximal Similarity Region Merging
No full textA fundamental problem in image processing isimage segmentation. The conventional imagesegmentation methods, to some extent, all suffer fromthe problem of inaccurate segmentation. A slightlyeasier and more approachable problem, interactivesegmentation, has also received a lot of attentions overthe years. In this paper, we propose a fast and simpleinteractive image segmentation technique. Thissegmentation process is conducted in two modules.First, the original image is detected by canny edgedetection method. Second, the object ofinterest issegmented by using the region merging based onmaximal similarity. In this work, color feature is usedto measure the closeness between two regions andaccordingly the label of the unmarked region isdecided. The proposed method extracts the object fromthe complex background in the image. Theeffectiveness of the proposed method is validated byexperimental results and compared with other method
Efficient Interactive Segmentation using Modified Maximal Similarity Region Merging
No full textInteractive image segmentation has manyapplications in image processing, computervision, computer graphics and medical imageanalysis. In medical applications, imagesegmentation is a fundamental process in mostsystems that support medical diagnosis, surgicalplanning and treatments. In many editing tasks,the aim is to separate a foreground object fromits background. Therefore, we propose a fast andsimple interactive image segmentation techniquein this paper. The proposed methodautomatically merges the regions that areinitially segmented by mean shift segmentation,and then effectively extracts the object contourby labeling all the non-marker regions as eitherbackground or object. Moreover, manyexperiments are tested and the results show thatthe proposed method is faster than the existingmethod. Therefore, the proposed method iseffective and can quickly and accurately segmentfor both medical and natural scene images with ease
Web-based Decision Support System with Group Buying using Analytic Hierarchy Process
No full textIn electronic market places, group buying is seen as an effective form of electronic commerce. When buyers cooperate with each other, a seller can discount the price of a good. In existing group buying sites, each buyer preference may not be reflected effectively. This system implements a decision support system (DSS) for group buying based on buyer’s preferences. DSS is an interactive system that provides the user with easy access to decision models and data in order to support semi-structure and/or unstructured decision making task. This system is intended to develop a computerized system for some functions of house trading. The aim of this paper is to develop the web-based decisions support system for house selection using Analytical Hierarchical Process (AHP). The AHP appears to be a flexible decision making tool for multi-criteria problems such as selection of the best house
The relationship between in situ and invasive melanoma: An epidemiological study of melanoma in New Zealand, 2001-2017
No full textFull Text is available to authenticated members of The University of Auckland only.Background:
Melanoma is diagnosed as either in situ or invasive disease. The relationship between in situ and invasive melanoma is unclear. If every in situ lesion is an early stage of invasive melanoma, diagnosis and removal of in situ melanoma should reduce the incidence of invasive melanoma and ultimately mortality from this disease. However, if disease progression is more complex, the excision of an early lesion may not prevent more advanced disease and may represent overdiagnosis.
Aim:
To compare the epidemiology of in situ melanoma and invasive melanoma in order to obtain a better understanding of the natural history of these diseases and their relationship to each other.
Method:
A systematic review (Part I) was carried out to describe the methods and results of published epidemiological studies that have compared the incidence, trends and characteristics of in situ and invasive melanoma.
A population-based cohort study (Part II) of people identified from the New Zealand Cancer Registry (NZCR) who had been diagnosed with either in situ or invasive melanoma between 2001 and 2017 was conducted. The in situ and invasive melanoma data were compared in terms of incidence of the two disease, trends and key patient’s characteristics (age at diagnosis, sex, body site, ethnicity and geography). In addition, the risk of invasive melanoma among those with in situ melanoma was assessed with survival analysis and observed and expected invasive melanoma were compared in this subgroup.
Results:
The systematic review noted a wide use of age-standardised incidence rate and annual percentage change to describe the incidence trend of in situ and invasive melanoma. Various univariate and multivariate analysis methods were employed to determine the similarities or differences between in situ and invasive melanoma by patient characteristics. The systematic review found a dramatic increase in the incidence of in situ melanoma with
no obvious decline in that of of invasive melanoma globally. Patients with in situ melanoma tended to be younger than those with invasive melanoma, and there were differences in in situ and invasive melanoma by ethnicity for incidence trends, but no consistent patterns in the two conditions were observed by sex or body site.
In New Zealand, the incidence of in situ melanoma was found to have increased annually by 3.77% whereas that of invasive melanoma was relatively stable over the study period (annual increase 0.04%). In situ and invasive melanoma were similar in terms of patient sex and ethnicity, but differed by body site. It was difficult to compare in situ and invasive melanoma by age at diagnosis because this was highly influenced by body site and sex. The observed risk of invasive melanoma among patients with in situ melanoma was four times higher than that expected among the general population. The cumulative risk of invasive melanoma among patients with in situ melanoma was 5.6% at 5 years and 9.46% at 10 years.
Conclusion:
The relationship between in situ and invasive melanoma is complex. Not every in situ lesion was a precursor of invasive melanoma, but some did progress to invasive lesions
- …
