scholarly journals Automated System for Restaurant Services

2021 ◽  
Vol 24 ◽  
pp. 15-25
Author(s):  
Liva Deksne ◽  
Arturs Kempelis ◽  
Toms Sniedzins ◽  
Armands Kozlovskis
Keyword(s):  
Customer Service ◽  
Service Time ◽  
Scientific Literature ◽  
Service System ◽  
Automated System ◽  
Service Load ◽  
Determine System

The study proposes a smart restaurant system and analyses its benefits to be able to determine system potential advantages in restaurants. Service time is one of the main criteria that can be improved to enhance the speed of the customer service as well as to increase the number of restaurant visitors. To develop the system, solutions found in scientific literature, software and their different architectures are analysed. It has been found out that it is possible to decrease the average restaurant service load time by 52.76 %. Two hypotheses have been proposed for further research in order to determine how a smart restaurant service system can increase chef’s efficiency and how the use of different algorithms can decrease chef’s workload during peak hours.

scholarly journals Sistem Informasi Pelayanan Jasa pada Lucky Photo

2021 ◽  
Vol 11 (1) ◽  
pp. 81-95
Author(s):  
T Pradita ◽  
A Mubarok
Keyword(s):  
Information System ◽  
Customer Service ◽  
Service System ◽  
The Internet ◽  
Application System ◽  
Web Based ◽  
Customer Data ◽  
Service Information ◽  
Internet Media ◽  
A Company

The development of services has developed into the internet media, to make it easier for customers and employees in managing a job. In the problem of Lucky Photo, which covers services including printing, sales, stock of goods, purchases, and reports are not effective properly. The researcher aims to develop a service system entitled Service Information Systems at Lucky Photo. By building a web-based application, a waterfall method is needed to become a benchmark for the creation of a service information system, so the results will be obtained on a web-based application system to demand progress in a company, including services that become easier, easier customer service in conduct transactions, generate reports, and process customer data. So it can be concluded that with the construction of a new Service Information System it will be easier to make transactions, make it easier for customers, create reports, and process customer data that is embedded in the Mysql database which will become a well-systemized report.

scholarly journals Diffusion-Scale Tightness of Invariant Distributions of a Large-Scale Flexible Service System

2015 ◽  
Vol 47 (01) ◽  
pp. 251-269 ◽  
Author(s):  
A. L. Stolyar
Keyword(s):  
Diffusion Process ◽  
Service Time ◽  
Large Scale ◽  
Service System ◽  
Arrival Rate ◽  
Asymptotic Regime ◽  
Invariant Distributions ◽  
Multiple Customer Classes ◽  
The Mean ◽  
Diffusion Scale

A large-scale service system with multiple customer classes and multiple server pools is considered, with the mean service time depending both on the customer class and server pool. The allowed activities (routeing choices) form a tree (in the graph with vertices being both customer classes and server pools). We study the behavior of the system under a leaf activity priority (LAP) policy, introduced by Stolyar and Yudovina (2012). An asymptotic regime is considered, where the arrival rate of customers and number of servers in each pool tend to ∞ in proportion to a scaling parameter r, while the overall system load remains strictly subcritical. We prove tightness of diffusion-scaled (centered at the equilibrium point and scaled down by r −1/2) invariant distributions. As a consequence, we obtain a limit interchange result: the limit of diffusion-scaled invariant distributions is equal to the invariant distribution of the limiting diffusion process.

scholarly journals Diffusion-Scale Tightness of Invariant Distributions of a Large-Scale Flexible Service System

2015 ◽  
Vol 47 (1) ◽  
pp. 251-269 ◽  
Author(s):  
A. L. Stolyar
Keyword(s):  
Diffusion Process ◽  
Service Time ◽  
Large Scale ◽  
Service System ◽  
Arrival Rate ◽  
Asymptotic Regime ◽  
Invariant Distributions ◽  
Multiple Customer Classes ◽  
The Mean ◽  
Diffusion Scale

A large-scale service system with multiple customer classes and multiple server pools is considered, with the mean service time depending both on the customer class and server pool. The allowed activities (routeing choices) form a tree (in the graph with vertices being both customer classes and server pools). We study the behavior of the system under a leaf activity priority (LAP) policy, introduced by Stolyar and Yudovina (2012). An asymptotic regime is considered, where the arrival rate of customers and number of servers in each pool tend to ∞ in proportion to a scaling parameter r, while the overall system load remains strictly subcritical. We prove tightness of diffusion-scaled (centered at the equilibrium point and scaled down by r−1/2) invariant distributions. As a consequence, we obtain a limit interchange result: the limit of diffusion-scaled invariant distributions is equal to the invariant distribution of the limiting diffusion process.

scholarly journals Customer’s spontaneous facial expression recognition

2021 ◽  
Vol 22 (3) ◽  
pp. 1436
Author(s):  
Golam Morshed ◽  
Hamimah Ujir ◽  
Irwandi Hipiny
Keyword(s):  
Facial Expression ◽  
Customer Service ◽  
Positive Emotion ◽  
Service System ◽  
Negative Emotion ◽  
Sliding Window ◽  
High Accuracy ◽  
Facial Features ◽  
Expression Recognition ◽  
Specific Product

<span lang="EN-US">In the field of consumer science, customer facial expression is often categorized either as negative or positive. Customer who portrays negative emotion to a specific product mostly means they reject the product while a customer with positive emotion is more likely to purchase the product. To observe customer emotion, many researchers have studied different perspectives and methodologies to obtain high accuracy results. Conventional neural network (CNN) is used to recognize customer spontaneous facial expressions. This paper aims to recognize customer spontaneous expressions while the customer observed certain products. We have developed a customer service system using a CNN that is trained to detect three types of facial expression, i.e. happy, sad, and neutral. Facial features are extracted together with its histogram of gradient and sliding window. The results are then compared with the existing works and it shows an achievement of 82.9% success rate on average.</span>

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