scholarly journals Determining female consumer’s insight into products and shopping

2017 ◽  
Vol 10 (1) ◽  
pp. 14-23
Keyword(s):  
Product Development ◽  
Clothing Industry ◽  
South East Asia ◽  
Qualitative And Quantitative ◽  
Shopping Behaviour ◽  
Wide Range ◽  
Survey Results ◽  
The Right ◽  
Depth Interviews ◽  
Insight Into

This research explores consumer’s insight into the female sportswear segment for the purpose of improving product development in the clothing industry in South-East Asia, a consumer base consisting of 500 million people. The research aims to clarify the important parameters on which buying decisions are made. The parameters are based on price, function, fit, brand, and design. The methodology used in this research is qualitative and quantitative consisting of participative observations, in-depth interviews, and survey. Results shows a wide range of shopping approaches utilized by consumers. Shopping behaviour can be seen depending on products and location. Essential parameters for an exercising garment are fit and design. abundance of available options in the market can cause confusion amongst consumers. The over-availability of products contributed to the creation of such confusion or even fussiness amongst consumers. This is to suggest that the more alternatives available to consumers, the more difficult it will be to find “the right” product. Findings also suggests that consumer’s input and opinion is vital to product development and significantly contributes to product design and enhancement.

Interviews and Observation to Investigate Health Effects from Using Non-Keyboard Input Devices (NKID)

2000 ◽  
Vol 44 (30) ◽  
pp. 5-569-5-572 ◽  
Author(s):  
S Hastings ◽  
V Woods ◽  
R A Haslam ◽  
P Buckle
Keyword(s):  
Observational Data ◽  
Input Device ◽  
Input Devices ◽  
Keyboard Input ◽  
Video Recordings ◽  
Wide Range ◽  
Set Up ◽  
Depth Interviews ◽  
Initial Results ◽  
Insight Into

In-depth interviews and observations have been undertaken with intensive and non-intensive non-keyboard input device (NKID) users. Fifty individuals at ten organisations were interviewed to gain insight into how users arrange their workstations and use NKID in connection with different tasks. Observational data have also been collected on posture and workstation set-up, with video recordings at all sites. Initial results are presented here based on the first twenty-five interviews. A wide range of NKID was seen at the organisations visited including the mouse, touchscreen, joystick, trackball, and tablet and pen. Users reported a range of problems associated with the use of some devices: maintenance issues, device responsiveness and size of devices were some of those mentioned. Musculoskeletal pain and discomfort was also reported, particularly in mouse users n=9 (36%) with reports of weakness, stiffness and discomfort in the hands and wrist. An important observation was the variety of configurations of workstation furniture and equipment, which in some cases, constrained the position of the input device in relation to the user. This may result in the users having to work with the input device at some distance away from their body.

scholarly journals ANALYSIS OF CREATING BENCHMARK IMAGES METHODS TO TEST THE ACCURACY OF PHOTOGRAMMETRIC SOFTWARE

2021 ◽  
Vol 26 (2) ◽  
pp. 47-55
Author(s):  
Alexander V. Komissarov ◽  
◽  
Valeriya V. Dedkova ◽  
Keyword(s):  
Aerial Survey ◽  
High Price ◽  
Work Time ◽  
Wide Range ◽  
Processing Accuracy ◽  
Survey Results ◽  
Classi Fication ◽  
The Right ◽  
Imagery Processing ◽  
Selection Of

Digital photogrammetry is based on the use of specialized photogrammetric software (or digital photogrammetric systems) to solve problems related to the aerospace imagery processing. A wide range of programs and high price motivate consumers to choose the right software that responds to requirements of processing accuracy, amount of work, time of execution, etc. The main goal of this study is to analyze the existing methods of benchmark images creating to test photogrammetric pro-grams. The article carries out the analysis of existing techniques of creating benchmark images, classi-fication, selection of benchmark images types suitable for testing of photogrammetric software, and substantiates the necessity for checking of aerial survey results quality in specialized software.

Fashion-Technology and Change in Product Development and Consumption for the High-end Menswear Sector

2016 ◽  
pp. 231-260
Author(s):  
Frances Ross
Keyword(s):  
Longitudinal Study ◽  
3D Printing ◽  
Product Development ◽  
Design Process ◽  
Process Model ◽  
Digital Technologies ◽  
Virtual Design ◽  
Structural Template ◽  
Depth Interviews ◽  
Insight Into

This updates a longitudinal study of Bespoke/ High End tailoring (Ross, 2007) with a secondary focus on mid-market menswear. The discussion commences with a review of key literature and practices from digital menswear studies to-date and evaluates how in the last two decades a deeply entrenched traditional sector such as tailoring has embraced numerous fashion digital-technologies from the design process to multi-channel consumption in-store, e-commerce and apps. The author utilizes a 3D-4C's process model as a structural template. The research methodology is interpretive, qualitative, online structured-observation of tailors currently utilizing digital practices plus in-depth interviews with industry experts. Those interviewed include Bespoke/Designer tailors with current 3D- platforms and International researchers providing insight into the latest developments in digital fashion including virtual design, scanning, sizing, avatars, 3D-fabric-simulations, 3D-printing, virtual-try-on and customization to establish best practices and future forecasts for proactive fashion management.

scholarly journals Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1640 ◽  
Author(s):  
Amirhosein Mosavi ◽  
Yaser Faghan ◽  
Pedram Ghamisi ◽  
Puhong Duan ◽  
Sina Faizollahzadeh Ardabili ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
State Of The Art ◽  
High Dimensional ◽  
Economic Data ◽  
Economic Problems ◽  
Wide Range ◽  
Survey Results ◽  
Risk Parameters ◽  
Accuracy Performance ◽  
Insight Into

The popularity of deep reinforcement learning (DRL) applications in economics has increased exponentially. DRL, through a wide range of capabilities from reinforcement learning (RL) to deep learning (DL), offers vast opportunities for handling sophisticated dynamic economics systems. DRL is characterized by scalability with the potential to be applied to high-dimensional problems in conjunction with noisy and nonlinear patterns of economic data. In this paper, we initially consider a brief review of DL, RL, and deep RL methods in diverse applications in economics, providing an in-depth insight into the state-of-the-art. Furthermore, the architecture of DRL applied to economic applications is investigated in order to highlight the complexity, robustness, accuracy, performance, computational tasks, risk constraints, and profitability. The survey results indicate that DRL can provide better performance and higher efficiency as compared to the traditional algorithms while facing real economic problems in the presence of risk parameters and the ever-increasing uncertainties.

scholarly journals Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics

2020 ◽  
Author(s):  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Yaser Faghan ◽  
Puhong Duan ◽  
Sina Faizollahzadeh Ardabili ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Dynamic Systems ◽  
State Of The Art ◽  
Economic Data ◽  
Economic Problems ◽  
Wide Range ◽  
Survey Results ◽  
Risk Parameters ◽  
Accuracy Performance ◽  
Insight Into

The popularity of deep reinforcement learning (DRL) methods in economics have been exponentially increased. DRL, through a wide range of capabilities from reinforcement learning (RL) to deep learning (DL), offers vast opportunities for handling sophisticated economics dynamic systems. DRL is characterized by scalability with the potential to be applied to high-dimensional problems in conjunction with noisy and nonlinear patterns of economic data. In this paper, we initially consider a brief review of DL, RL, and deep RL methods in diverse applications in economics, providing an in-depth insight into state of the art. Furthermore, the architecture of DRL applied to economic applications is investigated in order to highlight the complexity, robustness, accuracy, performance, computational tasks, risk constraints, and profitability. The survey results indicate that DRL can provide better performance and higher efficiency as compared to the traditional algorithms while facing real economic problems at the presence of risk parameters and the ever-increasing uncertainties.

scholarly journals Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics

2020 ◽  
Author(s):  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Yaser Faghan ◽  
Puhong Duan ◽  
Sina Faizollahzadeh Ardabili ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Dynamic Systems ◽  
State Of The Art ◽  
Economic Data ◽  
Economic Problems ◽  
Wide Range ◽  
Survey Results ◽  
Risk Parameters ◽  
Accuracy Performance ◽  
Insight Into

The popularity of deep reinforcement learning (DRL) methods in economics have been exponentially increased. DRL, through a wide range of capabilities from reinforcement learning (RL) to deep learning (DL), offers vast opportunities for handling sophisticated economics dynamic systems. DRL is characterized by scalability with the potential to be applied to high-dimensional problems in conjunction with noisy and nonlinear patterns of economic data. In this paper, we initially consider a brief review of DL, RL, and deep RL methods in diverse applications in economics, providing an in-depth insight into state of the art. Furthermore, the architecture of DRL applied to economic applications is investigated in order to highlight the complexity, robustness, accuracy, performance, computational tasks, risk constraints, and profitability. The survey results indicate that DRL can provide better performance and higher efficiency as compared to the traditional algorithms while facing real economic problems at the presence of risk parameters and the ever-increasing uncertainties.

scholarly journals Legal Protection Against Children Being Victims Of Crimes Prosecution Stage In Kudus

2018 ◽  
Vol 1 (2) ◽  
pp. 405
Author(s):  
Dedy Nurjatmiko
Keyword(s):  
Descriptive Analysis ◽  
Legal Protection ◽  
Analysis Data ◽  
Empirical Method ◽  
Public Prosecutor ◽  
Child Victims ◽  
The Public ◽  
Survey Results ◽  
The Right ◽  
Depth Interviews

Protection of child victims in law enforcement process is essential to ensure the fairness of the essentials, in addition to criminal punishment to the perpetrators of the crime. This study aims to determine and analyze the consideration Requisitor prosecutors of the State Prosecutor of the case the defendant Child in Kudus of the rights of child victims. The method used in this research is juridical empirical method. Specifications research the authors use the descriptive analysis. Data collected in-depth interviews with the parties involved in research, direct observation and recording of documents. The survey results revealed the consideration of the Public Prosecutor in Requisitor yet fully protect the rights, rights of the victim, such as notifying the right to restitution.Keywords: Protection of Child Victims; Consideration Requisitor Public Prosecutor; �Restitution

scholarly journals The Conservation of Kali Pasir Jami’ Mosque in Tangerang, Banten

INSIST ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 52 ◽  
Author(s):  
Yulia Nurliani Lukito ◽  
Mushab Abdu Asy Syahid
Keyword(s):  
Local Government ◽  
Local Communities ◽  
Potential Threat ◽  
Conservation Program ◽  
Qualitative And Quantitative ◽  
Conservation Effort ◽  
The Right ◽  
Depth Interviews ◽  
Quantitative Approaches

Abstract—The aim of this study is to elaborate the conserving Kali Pasir Jami’ Mosque in Tangerang City, Banten Province that includes the participation of local communities. There is an initial conservation program proposed by the local government but it is not yet clear of how should the collaboration between communities who have done practical conservation and local government who slowly plans the conservation program. The lack of historical documentation of the building and unstructured research done by communities imply a potential threat to the conservation effort and loss of historical values of the mosque. This paper is the result of both qualitative and quantitative approaches such as observation and in-depth interviews in analyzing the conservation of the mosque. The finding of the research shows the important role of local communities in the sustainability of the mosque although there is also an urge to involve experts and government to create the right strategy in conserving the mosque.Keywords—conservation, Kali Pasir Jami’ Mosque, preservation 

scholarly journals Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics

2020 ◽  
Author(s):  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Yaser Faghan ◽  
Puhong Duan ◽  
Sina Faizollahzadeh Ardabili ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Dynamic Systems ◽  
State Of The Art ◽  
Economic Data ◽  
Economic Problems ◽  
Wide Range ◽  
Survey Results ◽  
Risk Parameters ◽  
Accuracy Performance ◽  
Insight Into

The popularity of deep reinforcement learning (DRL) methods in economics have been exponentially increased. DRL, through a wide range of capabilities from reinforcement learning (RL) to deep learning (DL), offers vast opportunities for handling sophisticated economics dynamic systems. DRL is characterized by scalability with the potential to be applied to high-dimensional problems in conjunction with noisy and nonlinear patterns of economic data. In this paper, we initially consider a brief review of DL, RL, and deep RL methods in diverse applications in economics, providing an in-depth insight into state of the art. Furthermore, the architecture of DRL applied to economic applications is investigated in order to highlight the complexity, robustness, accuracy, performance, computational tasks, risk constraints, and profitability. The survey results indicate that DRL can provide better performance and higher efficiency as compared to the traditional algorithms while facing real economic problems at the presence of risk parameters and the ever-increasing uncertainties.

Fashion-Technology and Change in Product Development and Consumption for the High-End Menswear Sector

3D Printing ◽  
2017 ◽  
pp. 251-280
Author(s):  
Frances Ross
Keyword(s):  
Longitudinal Study ◽  
3D Printing ◽  
Product Development ◽  
Design Process ◽  
Process Model ◽  
Digital Technologies ◽  
Virtual Design ◽  
Structural Template ◽  
Depth Interviews ◽  
Insight Into

This updates a longitudinal study of Bespoke/ High End tailoring (Ross, 2007) with a secondary focus on mid-market menswear. The discussion commences with a review of key literature and practices from digital menswear studies to-date and evaluates how in the last two decades a deeply entrenched traditional sector such as tailoring has embraced numerous fashion digital-technologies from the design process to multi-channel consumption in-store, e-commerce and apps. The author utilizes a 3D-4C's process model as a structural template. The research methodology is interpretive, qualitative, online structured-observation of tailors currently utilizing digital practices plus in-depth interviews with industry experts. Those interviewed include Bespoke/Designer tailors with current 3D- platforms and International researchers providing insight into the latest developments in digital fashion including virtual design, scanning, sizing, avatars, 3D-fabric-simulations, 3D-printing, virtual-try-on and customization to establish best practices and future forecasts for proactive fashion management.

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