Search results for " Market"

An Estimative Model of Automated Valuation Method in Italy

2017

The Automated Valuation Method (AVM) is a computer software program that analyzes data using an automated process. It is related to the process of appraising an universe of real estate properties, using common data and standard appraisal methodologies. Generally, the AVM is based on quantitative models (statistical, mathematical, econometric, etc.), related to the valuation of the properties gathered in homogeneous groups (by use and location) for which are collected samples of market data. The real estate data are collected regularly and systematically. Within the AVM, the proposed valuation scheme is an uniequational model to value properties in terms of widespread availability of sample …

The Impact of Forced Answering and Reactance on Answering Behavior in Online Surveys

2020

Forced answering (FA) is a frequent answer format in online surveys that forces respondents to answer each question in order to proceed through the questionnaire. The underlying rationale is to decrease the amount of missing data. Despite its popularity, empirical research on the impact of FA on respondents’ answering behavior is scarce and has generated mixed findings. In fact, some quasi-experimental studies showed that FA has detrimental consequences such as increased survey dropout rates and faking behavior. Notably, a theoretical psychological process driving these effects has hitherto not been identified. Therefore, the aim of the present study was twofold: First, we sought to experi…

Shopping with virtual hands

2020

Retailers can use virtual reality as a new touchpoint for their customers: within an existent channel or as a new sales channel. Thus, it is crucial to understand the differences and similarities between the physical and the virtual shopping environment. Shopping simulations make it possible to test, observe, and collect data in a controlled, low-cost, and fast way compared to field experiments. However, past studies might have provided biased results due to the characteristics of the sample used. This study analyzes how consumers behave in two virtual shopping tasks. The exploratory, experimental research uses an immersive VR shopping environment and a sample of participants balanced acros…

Bag-of-word based brand recognition using Markov Clustering Algorithm for codebook generation

2015

International audience; In order to address the issue of counterfeiting online, it is necessary to use automatic tools that analyze the large amount of information available over the Internet. Analysis methods that extract information about the content of the images are very promising for this purpose. In this paper, a method that automatically extract the brand of objects in images is proposed. The method does not explicitly search for text or logos. This information is implicitly included in the Bag-of-Words representation. In the Bag-of-Words paradigm, visual features are clustered to create the visual words. Despite its shortcomings, k-means is the most widely used algorithm. With k-mea…

MDP-based Resource Allocation for Uplink Grant-free Transmissions in 5G New Radio

2020

The diversity of application scenarios in 5G mobile communication networks calls for innovative initial access schemes beyond traditional grant-based approaches. As a novel concept for facilitating small packet transmission and achieving ultra-low latency, grant-free communication is attracting lots of interests in the research community and standardization bodies. However, when a network consists of both grant based and grant-free based end devices, how to allocate slot resources properly between these two categories of devices remains as an unanswered question. In this paper, we propose a Markov decision process based scheme which dynamically allocates grant-free resources based on a spec…

Information flow and WOM in social media and online communities

2017

Hidden Markov Model Based Machine Learning for mMTC Device Cell Association in 5G Networks

2019

Massive machine-type communication (mMTC) is expected to play a pivotal role in emerging 5G networks. Considering the dense deployment of small cells and the existence of heterogeneous cells, an MTC device can discover multiple cells for association. Under traditional cell association mechanisms, MTC devices are typically associated with an eNodeB with highest signal strength. However, the selected eNodeB may not be able to handle mMTC requests due to network congestion and overload. Therefore, reliable cell association would provide a smarter solution to facilitate mMTC connections. To enable such a solution, a hidden Markov model (HMM) based machine learning (ML) technique is proposed in …

Energy market segmentation for distributed energy resources implementation purposes

2007

The new power market scene has made its actors aware of the importance of offering customers a set of products according to their specific needs. At the same time, a desirable massive deployment of distributed energy resources would require that the products be designed for specific purposes for each type of customer. For these reasons, it is essential to identify the energy behaviour of different customer segments existing in the electricity market. This paper presents a segmentation methodology that allows the identification of different types of customers in accordance with their energy use. This segmentation is conceptually different from the one that is currently performed by the utili…

Students’ Redesign of Mandatory Assignments in Teacher Education

2017

This article explores specific aspects of literacy practices in teacher education in Norway, building upon data collected within the research project Digital literacy and use of learning resources in teacher education in Norway (DigiGLU). Our main aim is to explore how teachers in different subject courses in teacher education (TE) design mandatory assignments, and how students respond to these designs. After the extensive TE-reform in 2010, in revised plans and documents guiding professional training, mandatory assignments (both form and content) were considered more important for the students’ learning process. In our investigation, the concepts of design for learning and design in learni…

Accuracy and the role of experience in dynamic computer guided dental implant surgery: an in-vitro study

2019

Background To compare the accuracy of implant placement using the conventional freehand method and a dynamic navigation system; to assess the role of the surgeon’s experience in implant placement using these two methods. Material and Methods A randomized in-vitrostudy was conducted. Six resin mandible models and 36 implants were used. Two researchers with differing clinical experience (novice and experienced) placed implants using either the Navident dynamic navigation system (navigation group) or the conventional freehand method (freehand group). Accuracy was measured by overlaying the real position in the postoperative CBCT on the virtual presurgical placement of the implant in a CBCT ima…