Reduce Service Time Research Articles

QR-based Canteen Management System

In recent years, the digitization of administrative and operational processes has transformed various sectors in the world, including food service management. This research presents the development and implementation of a QR-based canteen management system, designed to enhance the efficiency of canteen operations by leveraging contemporary technological advancements. The system employs a desktop application built with C# and the .NET framework, enabling users to order and pay for food items using a QR code-based login and cashless payment system. This solution addresses the inefficiencies of traditional pen-and-paper-based canteen management by automating order processing, payment, and sales record maintenance. The primary objective is to streamline canteen operations, reduce service time, and improve customer satisfaction through a user-friendly and reliable system.

Manajemen Komunikasi dalam Pelayanan Penerbitan Sertifikat Tanah di Kantor Pertanahan Kota Administrasi Jakarta Pusat

This research will focus on service communication, factors that support and inhibit services as well as the effectiveness of land certificate issuance service communication at the Central Jakarta City Administration Land Office. There were 7 informants who were sources in this research. Data collection techniques were carried out using library research and field research. This aims to make it easier for service users to access service information available at the Central Jakarta City Administration Land Office. (2) Factors that support land certificate issuance services at the Central Jakarta City Administration Land Office, include: the existence of regulations that make it easier, the availability of qualified human resources and personnel with integrity, the existence of technology that helps make work easier, and reform of the public service bureaucracy. implemented to reduce service time to be shorter. (3) Obstacles that are still encountered in land certificate issuance services at the Central Jakarta City Administration Land Office, namely: the status of the land is still in dispute, meaning that the issuance of land certificates must wait for legal certainty regarding the ownership of the land in question, incomplete land archives or documents, public ignorance In fulfilling the requirements for issuing land certificates, computer facilities to support public services sometimes experience errors so that service activities become hampered, and there are a handful of service officers who do not understand service SOPs. (4) The effectiveness of public services in issuing land certificates at the Central Jakarta City Administration Land Office still needs to be improved. For this reason, we have carried out various innovations through the Julapat Program (7 Quick Services) and the Landing Service, which is a service for people who do not have time to take care of land documents on weekdays and can take care of them on weekends. Apart from that, the Central Jakarta City Administration Land Office also continues to serve applicants during break times. This program aims to get closer to applicants directly and show service users that managing services is simple and cheap.

A Task Orchestration Strategy in a Cloud-Edge Environment Based on Intuitionistic Fuzzy Sets

In the context of the burgeoning cloud-edge collaboration paradigm, powered by advancements in the Internet of Things (IoT), cloud computing, and 5G technology, this paper proposes a task orchestrating strategy for cloud-edge collaborative environments based on intuitionistic fuzzy sets. The proposed strategy prioritizes efficient resource utilization, minimizes task failures, and reduces service time. First, WAN bandwidth, edge server virtual machine utilization, delay sensitivity of the task, and task length are used to determine whether the task should be executed on the cloud or edge device. Then, the cloud-edge collaborative decision-making algorithm is used to select the task’s target edge servers (either the local edge servers or the neighboring edge servers). Finally, simulation experiments are conducted to demonstrate the effectiveness and efficacy of the proposed algorithm.

Estimation of the Effect of Self-Driving and En Route Preparation in Urban Parcel Delivery: The Case in Seoul

Self-driving technology is on the verge of commercialization and is expected to be utilized in delivery services. At the same time, low efficiency and physical limitations of last mile robots (especially for non-standardized cargo, stairs, etc.) are being pointed out. In addition, as leading overseas companies design robots to complete delivery through interaction with the recipient, it may be difficult to implement the robots in delivery environments like South Korea, where most parcels are not delivered face-to-face. Therefore, this study considers a parcel delivery model in which a person, not a robot, is on-board an autonomous truck for door-to-door deliveries. This study takes three expected effects of a self-driving vehicle into consideration: (i) reduced travel time, owing to alleviation of traffic congestion; (ii) reduced service time, owing to relaxed parking restrictions; and (iii) benefits from en route preparation (planning and collecting in advance of arrival) that can be realized when a person is not required in the driver’s seat. The findings from a case study conducted in Seoul indicate that advanced self-driving capabilities and en route preparation can potentially lead to a doubling of the delivery capacity at a terminal, along with a reduction of over 40% in operating costs per box. As suggested in this study, the en route preparation activities are verified to bring benefits.

A futuristic green service computing approach for smart city: A fog layered intelligent service management model for smart transport system

With the widespread adoption of technologies like the Internet of Things (IoT), context awareness, and decentralized computing at the edge of the network, service delivery in smart city parlance has been rapidly evolved. Management of Information and Communication Technologies (ICT) infrastructure for such dynamic environment at scale brings about new challenges. Existing fog layer resource management involves context-sharing and migration for real-time vertical and cross-vertical services. However, improper context migration might affect performance negatively. In this paper, the authors have envisioned improving the Quality of Service (QoS) of smart transportation while employing context-aware computing and Artificial Intelligence, which helps alleviate massive data transfers among Fog nodes and intelligent vehicles in real-time. The proposed Context-Aware Intelligent Transportation System (CAITS) manages the services of intelligent vehicles and manages the road traffic of traditional vehicles in an effective manner, with a three-layered learning model that accounts for on-vehicle, on-co-vehicle, and on-fog-and-vehicle learning by means of a platoon control algorithm as well as federated learning at the Fog level. Simulations are carried out on CloudSim simulator under different scenarios and the results demonstrate that the proposed scheme improves prediction efficacy of contexts at the Fog layer by approximately 8%–24% than existing models which in turn reflects in reduced service time and energy consumption of EVs and reduces the CO2 of environment.

Outpatient Service Business Development in an Effort to Reduce Service Time

Hospital service quality should be developed based on customer needs and satisfaction. Long service time at Bhayangkara Kediri Hospital Outpatient Unit (267,62 ± 136,41 min) becomes a problem for management. The process is an asset for an organization, especially the core process should be well managed. Business process management has been viewed as an effective concept to improve processes continuously. It is an operational research combining document review, stakeholder interview, focused group discussion, quantitative and qualitative process analyze, prioritization, and root cause analysis to give process redesign recommendations. There are five core processes in the outpatient unit, and we focus our research on the dispensing process in pharmacy. Then we made a process model based on evidence and interview-based discovery. The cycle time efficiency of the prescription analysis process was the worst with a value of 0.31. With non-value activities reach to 40% of all activities with the waste are over processing, waiting, and transportation. The selected problem was the disposition of prescriptions to the dispensing unit as waste. Based on the root cause analysis, we suggest two recommendations. For the short-term redesign, we support the use of a basket to transport the prescription embedded in the operational procedures. And for the long-term redesign, we suggest the implementation of electronic prescribing. These redesigns are assumed to reduce waiting time by 2.5 – 16.2 % of service time.

Learning-Based Metaheuristic Approach for Home Healthcare Optimization Problem

This research focuses on the home health care optimization problem that involves staff routing and scheduling problems. The considered problem is an extension of multiple travelling salesman problem. It consists of finding the shortest path for a set of caregivers visiting a set of patients at their homes in order to perform various tasks during a given horizon. Thus, a mixed-integer linear programming model is proposed to minimize the overall service time performed by all caregivers while respecting the workload balancing constraint. Nevertheless, when the time horizon become large, practical-sized instances become very difficult to solve in a reasonable computational time. Therefore, a new Learning Genetic Algorithm for mTSP (LGA-mTSP) is proposed to solve the problem. LGA-mTSP is composed of a new genetic algorithm for mTSP, combined with a learning approach, called learning curves. Learning refers to that caregivers’ productivity increases as they gain more experience. Learning curves approach is considered as a way to save time and costs. Simulation results show the efficiency of the proposed approach and the impact of learning curve strategy to reduce service times.

Attitudes and perspectives of 534 Chinese pediatricians toward internet hospitals.

BackgroundInternet hospitals introduced in China have effectively reduced service time and space, promoted high-quality pediatric medical resources to grassroots areas, solved the contradiction between supply and demand of pediatric medical resources, and met patients’ increasing multi-level and diversified medical service needs. However, pediatricians’ attitudes toward and satisfaction with the use of internet hospitals remain unknown.ObjectiveThis study aimed to investigate pediatricians’ knowledge of, use of, and satisfaction with internet hospitals in order to identify major issues in internet hospital development, and to understand pediatricians’ attitudes and opinions on the construction, development, and use of internet hospitals.Materials and methodsA total of 625 pediatricians in 17 public tertiary hospitals in Shanghai were surveyed from November 1–30, 2021. Five hundred and thirty four pediatricians completed the survey, and the response rate was 85.44%. Pediatricians’ baseline demographic data were collected and information about their use of and satisfaction with internet hospitals.ResultsAbout 70.22% (375/534) of pediatricians knew about internet hospitals and about 54.68% (292/534) use internet hospitals for patient consultation, diagnosis, and treatment. Utilized services mainly focused on online consultation (271/292, 92.81%), online follow-up consultation (174/292, 59.59%), and health sciences (111/292, 38.01%). Online services were provided by 69.18% (202/292) of pediatricians for less than 1 h a day, and 75.00% (219/292) responded to fewer than five patient consultations online every day. Pediatricians’ overall satisfaction with internet hospitals was low (3.59 ± 0.92 points), user experience, systems functions, operation processes, service prices, and performance rewards of internet hospitals were main influencing factors. Pediatricians are enthusiastic about further development of internet hospitals, with 87.83% (469/534) willing to provide services on the internet hospital platform.ConclusionMost pediatricians view internet hospitals favorably and are eager to contribute to the development of online diagnosis and treatment services. The development of internet hospitals will be more strongly supported by improving pediatricians’ satisfaction and mobilizing their enthusiasm and initiative to participate in internet medical services.

UAV-Assisted Communication in Remote Disaster Areas Using Imitation Learning

The damage to cellular towers during natural and man-made disasters can disturb the communication services for cellular users. One solution to the problem is using unmanned aerial vehicles to augment the desired communication network. The paper demonstrates the design of a UAV-Assisted Imitation Learning (UnVAIL) communication system that relays the cellular users’ information to a neighbor base station. Since the user equipment (UEs) are equipped with buffers with limited capacity to hold packets, UnVAIL alternates between different UEs to reduce the chance of buffer overflow, positions itself optimally close to the selected UE to reduce service time, and uncovers a network pathway by acting as a relay node. UnVAIL utilizes Imitation Learning (IL) as a data-driven behavioral cloning approach to accomplish an optimal scheduling solution. Results demonstrate that UnVAIL performs similar to a human expert knowledge-based planning in communication timeliness, position accuracy, and energy consumption with an accuracy of 97.52% when evaluated on a developed simulator to train the UAV.

Fuzzy‐Based Mobile Edge Orchestrators in Heterogeneous IoT Environments: An Online Workload Balancing Approach

Online workload balancing guarantees that the incoming workloads are processed to the appropriate servers in real time without any knowledge of future resource requests. Currently, by matching the characteristics of incoming Internet of Things (IoT) applications to the current state of computing and networking resources, a mobile edge orchestrator (MEO) provides high‐quality service while temporally and spatially changing the incoming workload. Moreover, a fuzzy‐based MEO is used to handle the multicriteria decision‐making process by considering multiple parameters within the same framework in order to make an offloading decision for an incoming task of an IoT application. In a fuzzy‐based MEO, the fuzzy‐based offloading strategy leads to unbalanced loads among edge servers. Therefore, the fuzzy‐based MEO needs to scale its capacity when it comes to a large number of devices in order to avoid task failures and to reduce service times. In this paper, we investigate and propose an online workload balancing algorithm, which we call the fuzzy‐based (FuB) algorithm, for a fuzzy‐based MEO. By considering user configuration requirements, server geographic locations, and available resource capacities for achieving an online algorithm, our proposal allocates the proximate server for each incoming task in real time at the MEO. A simulation was conducted in augmented reality, healthcare, compute‐intensive, and infotainment applications. Compared to two benchmark schemes that use the fuzzy logic approach for an MEO in IoT environments, the simulation results (using EdgeCloudSim) show that our proposal outperforms the existing algorithms in terms of service time, the number of failed tasks, and processing times when the system is overloaded.

Latency Minimization in a Fuzzy-Based Mobile Edge Orchestrator for IoT Applications

Currently, matching the incoming Internet of Things applications to the current state of computing and networking resources of a mobile edge orchestrator (MEO) is critical for providing the high quality of service while temporally and spatially changing the incoming workload. However, MEO needs to scale its capacity concerning a large number of devices to avoid task failure and to reduce service time. To cope with this issue, we propose MEO with fuzzy-based logic that splits tasks from mobile devices and maps them onto the cloud and edge servers to reduce the latency of handling these tasks and task failures. A fuzzy-based MEO handles the multi-criteria decision-making process to decide where the offloaded task should run by considering multiple parameters in the same framework. Our approach selects the appropriate host for task execution and finds the optimal task-splitting strategy. Compared to the existing approaches, the service time using our proposal can achieve up to 7.6%, 22.6%, 38.9%, and 51.8% performance gains for augmented reality, healthcare, compute-intensive, and infotainment applications, respectively.

Dispatch and conflict-free routing of capacitated vehicles with storage stack allocation

Congested traffic networks impose great difficulties upon scheduling material transportation in industrial settings. Dispatching decisions become complex when, in addition to conflict-free routes, storage location must also be considered. The present paper integrates the dispatch and conflict-free routing of capacitated vehicles with the storage allocation problem and proposes a heuristic approach for minimising the total completion time of box pickup, delivery and relocation requests in a warehouse environment. The developed formulation models a warehouse setting in which boxes are stored in stacks and considers different forward and reverse speeds for the vehicles, real-world movement restrictions and a LIFO loading policy. The proposed approach is evaluated using two different metaheuristics and the results are compared against existing schedules prepared by an industry partner. Experimental results demonstrate the effectiveness of the proposed method for large-scale instances and highlight how improved storage allocation decisions can reduce service times.

Sustainability in Marketing through Customer Relationship Management in a Telecommunication Company

The idea of sustainable development links business, environmental and social objectives into one integrated effort aiming to meet a common goal. Due to the influence of current developments in customer behaviour companies revise their business strategies towards more sustainably oriented ways of production, business practices, resource efficiency, waste disposal, building partnerships, communication effectiveness etc. Market with telecommunication services is affected by technology development. Growing demands of customers result in re-evaluation of marketing routine. The main purpose of the research is to identify the change in customers’ approaches and satisfaction with offered products, enterprise processes, and business strategy as a result of implementing Customer Relationship Management in 2014 and subsequently in 2018 with the dependence on socio-demographic characteristics. Customers’ opinions were investigated using a questionnaire. Respondents were selected by direct sampling with contingent valuation. Sample set consisted of 3,282 respondents. Following the results, the fact that there are changes in approaches of customers in investigated areas in terms of gender and age as a result of implementing the Customer Relationship Management can be stated. The customers’ satisfaction with provided services improved. In order to serve the new and constantly evolving needs of the growing number of customers who care about social and environmental issues, the companies are required to permanently monitor their performance on the market and incorporate customer feedback as in input for evaluation of their internal processes. In terms of marketing, positive changes in approach, satisfaction with the quality of provided services and reduced service time were observed. In terms of business strategy, the changes in connection strategy, the effect of customer-driven strategy and services provided by call centres abroad are perceived in positive way. Keywords: sustainability, economical sustainability, marketing, Customer Relationship Management, telecommunication company.

Stochastic Analysis of Delayed Mobile Offloading in Heterogeneous Networks

Mobile cloud offloading that migrates heavy computation from mobile devices to powerful cloud servers through communication networks can alleviate the hardware limitations of mobile devices thus providing higher performance and saving energy. Different applications usually give different relative importance to response time and energy consumption. If a delay-tolerant job is deferred up to a given deadline, or until a fast and energy-efficient network becomes available, the transmission time will be extended, which can save energy because a more energy-efficient communication channel and a less energy-restricted computation platform may become available. However, if the reduced service time fails to cover the extra waiting time, this policy may not be competitive. In this paper, we investigate two types of delayed offloading policies, the partial offloading model where jobs can leave from the slow phase of the offloading process and be executed locally on the mobile device, and the full offloading model, where jobs can abandon the WiFi Queue and be offloaded via the Cellular Queue . In both models, we minimize the Energy-Response time Weighted Product (ERWP) metric. Not surprisingly, we find that jobs abandon the queue often when the availability of the WiFi network is low. In general, for delay-sensitive applications the partial offloading model is preferred under a suitable reneging rate, while for delay-tolerant applications the full offloading model shows very good results and outperforms the other offloading model when selecting a large deadline. From the perspective of energy consumption, the full offloading model will always be best, even if the deadline must be extremely long. Only if job response time is of high importance an optimal deadline to abort offloading in the partial offloading model or the WiFi transmission in the full offloading model can be found. For reduction of the energy consumption it will always be better to wait longer rather than compute locally or use the cellular network.

Time Is Not on Our Side: How Radiology Practices Should Manage Customer Queues

As health care shifts toward patient-centered care, wait times have received increasing scrutiny as an important metric for patient satisfaction. Long queues form when radiology practices inefficiently service their customers, leading to customer dissatisfaction and a lower perception of value. This article describes a four-step framework for radiology practices to resolve problematic queues: (1) analyze factors contributing to queue formation; (2) improve processes to reduce service times; (3) reduce variability; (4) address the psychology of queues.

Power and performance evaluation of Memcached on the TILEPro64 architecture

Power consumption of data centers had become an important factor in the economy and sustainability of large-scale Web services. Researchers and practitioners are spending considerable effort to characterize Web-scale workloads and evaluating their applicability to alternative, more power-efficient architectures. One such workload in particular is the caching layer, which stores expensive-to-regenerate data in fast storage to reduce service times. In this paper we look at one such application, the Memcached key-value store, which is widely deployed at Facebook and other Web services, and one alternative architecture, the TILEPro64 many-core system-on-chip. We explore the performance and power characteristics of Memcached under a variety of workload variations, implementation choices, and communication protocol, and compare them to a traditional implementation on x86-based servers. Our results suggest that the TILEPro64 architecture can significantly outperform x86-based architectures in terms of throughput per Watt for the evaluated version of Memcached.

ARC-H: Adaptive replacement cache management for heterogeneous storage devices

Heterogeneous storage architectures combine the strengths of different storage devices in a synergistically useful fashion, and are increasingly being used in mobile storage systems. In this paper, we propose ARC-H, an adaptive cache replacement algorithm for heterogeneous storage systems consisting of a hard disk and a NAND flash memory. ARC-H employs a dynamically adaptive management policy based on ghost buffers and takes account of recency, I/O cost per device, and workload patterns in making cache replacement decisions. Realistic trace-driven simulations show that ARC-H reduces service time by up to 88% compared with existing caching algorithms with a 20Mb cache. ARC-H also reduces energy consumption by up to 81%.

Vehicle routing with multiple deliverymen: Modeling and heuristic approaches for the VRPTW

In real life distribution of goods, relatively long service times may make it difficult to serve all requests during regular working hours. These difficulties are even greater if the beginning of the service in each demand site must occur within a time window and violations of routing time restrictions are particularly undesirable. We address this situation by considering a variant of the vehicle routing problem with time windows for which, besides routing and scheduling decisions, a number of extra deliverymen can be assigned to each route in order to reduce service times. This problem appears, for example, in the distribution of beverage and tobacco in highly dense Brazilian urban areas. We present a mathematical programming formulation for the problem, as well as a tabu search and an ant colony optimization heuristics for obtaining minimum cost routes. The performance of the model and the heuristic approaches are evaluated using instances generated from a set of classic examples from the literature.

Quality Management at Kentucky Fried Chicken

Kentucky Fried Chicken (KFC) Corporation, a member of the quick-service restaurant industry, uses a sophisticated program to manage the quality of service it offers to its customers. In the last quarter of 1989, the south central division of KFC launched a test program in four Oklahoma City restaurants to improve the speed of service at its drive-through-window operation. It proved extremely successful. The restaurants cut service time by more than half while improving labor productivity. They also dramatically outperformed other restaurants in the division in profits, sales growth, and growth in customer transactions. The improved processes in the test restaurants have served as benchmarks for other KFC restaurants aiming for continuous process improvement, while the reduced service time now serves as the revised specification in KFC’s quality measurement and management program.

Analysis of the periodic update write policy for disk cache

A disk cache is typically used in file systems to reduce average access time for data storage and retrieval. The 'periodic update' write policy, widely used in existing computer systems, is one in which dirty cache blocks are written to a disk on a periodic basis. The average response time for disk read requests when the periodic update write policy is used is determined. Read and write load, cache-hit ratio, and the disk scheduler's ability to reduce service time under load are incorporated in the analysis, leading to design criteria that can be used to decide among competing cache write policies. The main conclusion is that the bulk arrivals generated by the periodic update policy cause a traffic jam effect which results in severely degraded service. Effective use of the disk cache and disk scheduling can alleviate this problem, but only under a narrow range of operating conditions. Based on this conclusion, alternate write packages that retain the periodic update policy's advantages and provide uniformly better service are proposed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>