Flexible Service Research Articles

Software-Defined Networks for Optical Networks Using Flexible Orchestration: Advances, Challenges, and Opportunities

Optical networks offer a wide range of benefits to the telecommunication sector worldwide with their provision of higher bandwidth, which leads to faster data speed, longer transmission distance, and improved latency. Currently, the complexity associated with advancements in optical networks poses problems to network flexibility, reliability, and quality of service. Over the years, many reviews and proposals have been implemented by several literature studies to provide solutions for optical networks using software-defined networks and network service orchestrators. This study reviews the significant challenges in current optical network applications, the various solutions rendered by software-defined networks, and network service orchestration, impediments, and gaps in these software-defined networks. This study will go a step further to look into the various improvements and implementations of software-defined networks tailored to solve specific optical network problems. This study further proposes a flexible orchestration architecture for software-defined networks for solving flexibility and scalability problems in optical networks. This proposal uses an open network system (ONOS) SDN controller, leveraging on dockerisation and Kubernetes clusterisation and orchestration. This solution presents a more flexible, reliable, customable, and higher quality of service, which is an improvement upon current solutions in the literature.

Smart Tool Development for Customized Charging Services to EV Users

E-mobility is a key element in the future energy systems. The capabilities of EVs are many and vary since they can provide valuable system flexibility services, including management of congestion in transmission grids. According to the literature, leaving the charging process uncontrolled could hinder some of the present challenges in the power system. The development of a suitable charging management system is required to address different stakeholders’ needs in the electro-mobility value chain. This paper focuses on the design of such a system, the TwinEV module, that offers high-value services to electric vehicles (EV) users. This module is based on a Smart Charging Tool (SCT), aiming to deliver a more user-central and cooperative approach to the EV charging processes. The methodology of the SCT tool, as well as the supportive optimization algorithm, are explained thoroughly. The architecture and the web applications of TwinEV module are analyzed. Finally, the deployment and testing results are presented.

Expected service dimensions and service levels for paratransit considering future mobility needs in emerging countries

• Mobility-as-a-Service (MaaS) promises improved modal efficiency and integration among public transit and flexible paratransit services (FPS). • Key service dimensions and issues of flexible paratransit services are analysed in the context of MaaS. • Expected service level for these service dimensions are determined using the level of service (LOS) approach based on user perception. • Ride matching as per expected waiting time and service hours via MaaS agencies would ensure proper demand-supply match and fleet size determination. In emerging countries, flexible transport systems (FTS) are mostly informal and are provided by individual paratransit operators/drivers. These services are largely unregulated thus resulting in uncoordinated operations with poor service quality. Earnings and working conditions of paratransit drivers/operators are also poor due to loosely regulated fleet size and other operational and regulatory issues which results in further deterioration of service quality. This research identifies key service dimensions and issues of paratransit services and also determines the expected service level for these service dimensions using the level of service approach based on user perception. LOS scales are designed for different service attributes using a five-point satisfaction and importance rating system. For quantitative attributes, five-level LOS scales are determined by applying the Law of Successive Interval Scaling, whereas for qualitative attributes, the same has been developed using the frequency of response for each level of importance for each sub-attribute. Subsequently, we explore various policies and regulatory measures towards reform and redesign of paratransit services and other mobility needs. Operator profitability can be achieved both through the controlled entry of operators through the issue of permits and/or by relaxing the current service level of some service aspects which are at LOS B level of service. The LOS scales can help in future service design of paratransit services in emerging countries which can offer an affordable alternative to ridesourcing and ride-sharing using cars. The study is conducted in two medium-sized cities in India namely Rajkot and Vishakapatnam.

Threat Modeling and Risk Analysis for Miniaturized Wireless Biomedical Devices

The landscape of miniaturized wireless biomedical devices (MWBDs) is rapidly expanding as proactive mobile healthcare proliferates. MWBDs are diverse and include various injectable, ingestible, implantable, and wearable devices. While the growth of MWBDs increases the flexibility of medical services, the adoption of these technologies brings privacy and security risks for their users. MWBDs can operate with sensitive, private information and affect patients through the use of stimulation and drug delivery. Therefore, these devices require trust and need to be secure. Embedding protective mechanisms into MWBDs is challenging because they are restricted in size, power budget, as well as processing and storage capabilities. Nevertheless, MWBDs need to be at least minimally securable in the face of evolving threats. The main intent of this work is to make the primary stakeholders of MWBDs aware of associated risks and to help the architects and the manufacturers of MWBDs protect their emerging designs in a repeatable and structured manner. Making MWBDs securable begins with performing threat modeling. This paper introduces a domain-specific qualitative-quantitative threat model dedicated to MWBDs. The proposed model is then applied to representative case studies from each category of MWBDs.

Proposal of flexible service deployment environment for the edge processing system

Proposal of flexible service deployment environment for the edge processing system

Integration of conventional and customized bus services: An empirical study in Beijing

In recent years, customized bus (CB) service has become an innovative model for public transportation in China. Its ability to provide advanced, timely, personalized, and flexible service has made it very popular. However, previous studies have ignored its diversion effect: How can CB service help conventional buses reduce on-board crowding during rush hours? In this paper, we optimize conventional and CB buses as a whole based on an empirical study in Beijing. We propose a new model to compare the cost of single conventional buses (Single Con) and the integration of conventional and customized buses (Con+ CB). Passenger diversions from conventional buses to CB ones are specifically considered. To do this we explicitly measure the on-board crowding cost of conventional buses by load factor and distance factor. Real-world data from Beijing, China, are employed to assess the model. We obtained the departure arrangements and the corresponding costs under different demand cases. The results are analyzed and compared. Sensitivity analyses are then conducted to study the effects of line-haul distance and load factor on cost. The results show that (1) adding new modes of transportation does not always significantly reduce the total cost of bus service; (2) CB buses can effectively ease congestion on conventional buses only at high demand densities but not at low densities; (3) crowding cost increases caused by the distance factor far exceed those caused by the load factor.

Economic scheduling of mobile energy storage in distribution networks based on equivalent reconfiguration method

Compared with traditional stationary energy storage system (SESS), mobile energy storage system (MESS) has power transfer ability in both spatial and temporal dimensions. Thus, it can provide greater flexibility in power system auxiliary services. To simplify and clarify the optimal scheduling problem, a novel “virtual switch” indicator is defined to describe the scheduling of MESS and an equivalent reconfiguration method is proposed by analogy with distribution network reconfiguration. Based on the method proposed, the dynamic economic scheduling of MESS in distribution networks(DNs) can be formulated as a scenario-based stochastic optimization problem, where the uncertainties of traffic flow and renewable energy output are considered by generating scenarios using Monte Carlo simulation. The objective function is to maximize the profit of distribution network operator. The time and cost of MESS scheduling are transformed into those of virtual switch switching in distribution network reconfiguration. Therefore, the operation scheduling problem of a MESS is equivalent to a distribution network reconfiguration problem with a SESS and several virtual switches. In this way, a grid-traffic network coupling problem is simplified to a pure distribution network problem, which provides a novel way to solve the MESS scheduling problems. Finally, simulation results on the IEEE 33-bus distribution system and simple traffic network verify the validity and feasibility of the method proposed.

Path selection for link failure protection in hybrid SDNs

During the transition from traditional networks to pure Software-Defined Networks (SDNs), hybrid SDNs are derived to provide flexible services. Furthermore, developing effective failure protection algorithms is significantly urgent to improve the robustness and resilience of networks. In this paper, we propose several algorithms, including Straightforward Protection Path Selection with the Source and Destination-based Tunneling mechanism (S-PPSSDT), its simplification PPSSDT and Protection Path Selection with Load-Balancing (PPSLB) algorithms. Considering that the Protection Path Length (PPL) will affect the transmission delay of rerouted packets, S-PPSSDT leverages the source and destination-based tunneling mechanism to select optimum protection paths with the shortest length. Based on classification idea and optimization search, PPSSDT prunes unnecessary path searches in S-PPSSDT. Combining the tunneling mechanism with the priority-based Maximum Link Utilization (MLU) minimization approach, PPSLB also focuses on load balancing during failure protection to achieve potential congestion avoidance simultaneously. Besides, these algorithms redirect the traffic through various tunnels for affected paths by the non-shortest path routing capability of SDN switches. Extensive simulation results indicate that our proposed algorithms can effectively reduce the PPL and MLU of hybrid SDNs during failure protection, and have excellent performance under various network parameters compared with the state-of-the-art algorithms.

Factors influencing the success of telepractice during the COVID-19 pandemic and preferences for post-pandemic services: An interview study with clinicians and parents.

BackgroundThere has been a significant uptake in the use of telepractice during the coronavirus SARS‐CoV‐2 (COVID‐19) pandemic. This study explored the experiences of speech and language therapists (SLTs), assistants (SLTAs) and parents with telepractice during the COVID‐19 pandemic.Aims(1) To identify factors that influenced success of telepractice; and (2) to describe clinicians’ and parents’ preferences for the future mode of service delivery for preschoolers with communication disorders.Methods & ProceduresThe study was conducted in partnership with one publicly funded programme in Ontario, Canada, that offered services to preschoolers with speech, language and communication needs at no cost. SLTs (N = 13), assistants (N = 3) and parents (N = 13) shared their experiences and perspectives during semi‐structured videoconference interviews.Outcomes & ResultsFactors that influenced the success of telepractice were reported in three categories: the setting (i.e., where and how telepractice was being delivered); the nature of telepractice (i.e., the services that were provided via telepractice); and the individuals (i.e., who was involved in telepractice). These factors were reported to interact with each other. As the needs for each child and family are unique, parents and clinicians reported a preference for a hybrid and flexible service delivery model in the future.Conclusions & ImplicationsThe themes identified in this study can be used by clinicians and managers to consider factors that influence the success of telepractice for children and families.WHAT THIS PAPER ADDSWhat is already known on the subject? Studies conducted before the COVID‐19 pandemic showed that telepractice was an effective and acceptable service approach. However, some clinicians and parents reported wanting to resume in‐person visits. The provision of telepractice services to families with children with communication disorders increased significantly during COVID‐19. What this paper adds to existing knowledge? Parents and clinicians shared factors that influenced the success of telepractice during semi‐structured interviews. Factors were identified in three categories: the setting (i.e., where and how telepractice was being delivered); the nature of telepractice (i.e., the services that were provided via telepractice); and the individuals (i.e., who were involved in telepractice). As each child's and family's needs are unique, parents and clinicians reported a preference for a hybrid and flexible service delivery model in the future. What are the potential or actual clinical implications of this work? SLTs and SLT managers can use the factors identified to discuss with parents and decide whether telepractice may be well suited to the needs of each child and family.

Measured Indoor Environmental Data in a Retrofitted Multiapartment Building to Assess Energy Flexibility and Thermal Safety during Winter Power Outages

The article describes detailed measurements of indoor environmental parameters in a multiapartment housing block located in Milan, Italy, which has recently undergone a deep energy retrofit and is used as a thermal battery during the winter season. Two datasets are provided: one refers to a series of experimental tests conducted by the authors in an unoccupied flat, in which the thermal capacity of the building mass is exploited to act as an energy storage. The dataset reports, with a time step of 10 min, measurements of air temperature, globe temperature and surface temperatures in the analyzed room and data characterizing the adjacent spaces and the outdoor conditions. The second set of data refers to the air temperature monitoring carried out continuously in all the apartments of the apartment block, and hence also during two unplanned heating power outages. The analyzed data show the role of deep renovations in extending the time over which a building can remain in the thermal comfort range after an energy interruption and thus highlight the potential role of retrofitted buildings in delivering energy flexibility services to related stakeholders, such as the occupants, the building manager, the grid operator, and others. Furthermore, the dataset can be used to calibrate an energy simulation model to investigate different demand-side flexibility strategies and evaluate thermal safety under extreme weather events.

Diabetes mellitus prevalence in Northland New Zealand schizophrenia patients on clozapine.

Clozapine is a unique atypical anti-psychotic agent with best efficacy for treatment resistant schizophrenia compared to other agents, but with increased metabolic adverse effects. We sought to audit the prevalence of diabetes and pre-diabetes in Northland, New Zealand patients on clozapine. We captured all 287 patients in Northland, New Zealand who were prescribed clozapine in September 2021 and obtained demographic, clinical and laboratory data. We discovered that 26.48% had diabetes (one patient type one, 75 type two diabetes) and 14.63% had pre-diabetes that developed after a median of six years' clozapine treatment. Diabetes prevalence is approximately 6% in the general population. NZ Māori made up 65.85% of the entire cohort (35.8% of the general population) and 85.53% of the diabetes patients. NZ Europeans represented most of the remaining 30.66% on clozapine, consistent with the largely bicultural ethnic mix of our region. Māori on clozapine were younger: mean age 42 years, compared to NZ Europeans, mean age 49 years. The average BMI was 37kg/m2 for Māori, 32 for Europeans (range 21-63, SD 8); there was a moderate relationship between clozapine use and increasing BMI (correlation coefficient of 0.74). For the diabetes patients, glycaemic control was overall suboptimal with a mean Hba1c of 66mmol/mol (range 41-117). Culturally appropriate, flexible and accessible services which integrate both the mental and physical health needs of Northland, New Zealand people with treatment-resistant schizophrenia on clozapine are required to reduce the 41% rate of dysglycaemia in this predominantly Māori group.

Values and impacts of incorporating local flexibility services in transmission expansion planning

This paper presents a cost-based TSO-DSO coordination model to quantify the value of local flexibility services and analyze its impact on the transmission grid expansion and the system operation. Flexibility is provided to the DC power flow transmission grid model by microgrids within the integrated AC power flow distribution grid model. The model’s objective is to minimize the overall cost of transmission investments and procured flexibility and is achieved using a bilevel optimization approach where the power exchanges on all connected grid interfaces are controlled. Case studies using a combined test system of the IEEE RTS-96 transmission network interfacing multiple 33-bus distribution grids were performed to validate the model and assess the values and impacts of local flexibility on the transmission system expansion. The results showed that the proposed model modified the investment plan and dispatch of flexibility resources reducing the investment and operation cost of the transmission system.

HUBUNGAN KOMPONEN FLEXIBILITY TERHADAP AKURASI SERVIS PADA PERMAINAN SEPAK TAKRAW DI PSTI BOJONEGORO

In the game of sepak takraw, serve is very important because it can be the first attack. To produce a good service, there are supporting factors, one of which is the flexibility ability of a tekong. This study aims to determine the relationship between flexibility components and service accuracy in the sepak takraw game at PSTI Bojonegoro. This study uses two variables, namely the independent variable and the dependent variable. This type of research is quantitative with a correlational research design. The population in this study were all 5 tekong athletes at PSTI Bojonegoro. The test instruments in this study were sit and reach tests and service accuracy tests. The data analysis technique used simple correlation (bivariate correlation). The results of the statistical data analysis of the Pearson bivariate correlation, it is known that there is a significant relationship between flexibility and service accuracy with a significance value (p <0.05) and the Pearson correlation value (p = 0.987) which is included in the very strong Pearson correlation interpretation. From these results, it can be concluded that there is a significant relationship between flexibility and service accuracy at PSTI Bojonegoro.

Compact Dual Bandpass Filter Using Dual-Split Ring Resonator for 5G Upper Microwave Flexible Use Services

A novel, compact dual bandpass filter design is proposed for 5G upper microwave flexible use services. To realize the proposed design, a dual split-ring resonator structure coupled to the microstrip transmission line is used. The output responses have been validated using vector network analyzer N5222A. The measured filter records a frequency range of 23.8 GHz–25.98 GHz for the first passband and 28.05 GHz–28.7 GHz for the second band, with fractional bandwidths of 8.8% and 2.2%, respectively. The minimum insertion loss is observed to be 4.2 dB using microstrip technology, even at higher frequencies. The proposed design occupies the area of 0.4 λg×0.27 λg, where λg is guided wavelength at the lower band central frequency. Simulated and measured results are approximately compatible with each other. The proposed design is useful for fixed satellite service earth stations, terrestrial wireless operations, and 5G mobile communications applications.

Construction of Cloud Library Intelligent Service Platform Relying on Artificial Neural Network

With the advanced development of data center and network information technology, digital library has become a user sharing platform with a variety of digital information sources, providing users with flexible and diverse personalized services. However, the existing digital library lacks data analysis information and only publishes book information and related borrowing frequency and other information. As an ideal architecture model for library applications, cloud library can integrate distributed digital information sources, optimize digital libraries, and provide users with flexible, diverse, and personalized services. Therefore, based on the related research on cloud library and neural network algorithm, this paper not only focuses on the artificial network algorithm, but also focuses on the concept, features, and method of building the digital library platform based on the artificial network algorithm. Under the support of related theories and technologies of cloud library service platform, it also builds a cloud library intelligent service platform model based on artificial neural network. The research results showed that the time spent by BPNN in processing borrowed books was generally about 6 minutes, while the time required by RNN was 10 minutes. However, the processing of BPNN is not stable. Therefore, when building an intelligent service platform, different algorithms need to be selected according to individual needs.

Managing service flexibility in healthcare for improved customer experience: a data-driven approach

ABSTRACT The purpose of this paper is to explore how customers perceive service providers’ flexibility and evaluate the healthcare experience. The study applied a machine learning technique to develop a classification framework of service flexibility in healthcare where the studies are limited. The data mining was applied to 3600 stories from a healthcare firm using the Weka software. The study presents several facets of service flexibility in healthcare through topic modeling using Latent Dirichlet Allocation (LDA) theory. The relationship was gauged by utilizing structural equation modeling (PLS-SEM). This paper is a first step to designing the marketing strategies from the flexibility perspective by adopting a customer’s lens. The article demystifies a novel perspective on customer-perceived service flexibility by illuminating the underlying mechanisms through a data-driven approach. The implications are then discussed, emphasizing that healthcare service providers need to develop flexible competence to understand customer idiosyncrasies and enhance the service experience.

Community-based rehabilitation for adults with cognitive-communication disorders following traumatic brain injury: A mixed methods investigation

ABSTRACT Objective To investigate the experiences and perspectives of speech pathologists when delivering cognitive-communication therapy to adults following traumatic brain injury (TBI). Methods An explanatory sequential mixed methods design was used to explore the practices of speech pathologists working in community-based rehabilitation (CBR) settings. The first participant group completed an in-depth online survey, whilst the second group participated in an interview to discuss their processes and recommendations when managing adults following TBI. Results Participants highlighted the need for services to be client-centered and inclusive in their approaches to meet the rehabilitation needs of people following TBI in community-based settings. The key features identified to achieve this included utilizing a flexible service delivery approach, implementation of meaningful therapy, as well as inclusion of significant others. Conclusions These findings provide a snapshot of the current practices employed by a range of speech pathology services across Australia and New Zealand. Health professionals and rehabilitation service providers should consider the key factors highlighted by the participants when designing future CBR models of care for this client group.

Good or Bad Robots? Responsible Robo-Advising

FinTech has changed the way financial services are produced and delivered.1 As the Digital Finance Strategy for the EU put it: the future of finance is digital. Digital finance has also helped people and businesses tackle the unprecedented challenges caused by the COVID-19 pandemic. We increasingly rely on digital and remote technologies. The role of regulation is to make sure that these technologies are used in a responsible way.2 Robo-advising is one of the innovations relating to FinTech. This article addresses central challenges and risks in robo-advising, and the regulatory means to tackle them. When these challenges are resolved, robo-advising can provide customers with an easy-to-use, cost-effective and flexible service. FinTech, Investment advising, Robo-advising, MiFID II, Responsibility, Algorithm, Information security, Cybersecurity, Financial literacy, Legal Design

Techno-Economic Analysis and Optimal Operation of a Hydrogen Refueling Station Providing Frequency Ancillary Services

Following the urgency of climate change issues, investments in renewable energy sources and electrification of the transportation sector have enormously increased to facilitate the transition to a more sustainable future. However, as renewable resources like wind parks are replacing conventional power plants, new balancing solutions are required to strengthen grid stability. As responsive loads with quick dynamics, electrolyzers operating in hydrogen refueling stations (HRSs) can offer flexible balancing services to the power grid. To gain this benefit, this article examines the techno-economic features of providing different frequency grid services by an HRS, considering the possibility of hydrogen injection into the industrial and natural gas pipelines. The ratings of the subcomponents and dispatch plans are optimized to enhance the performance of the plant. A probabilistic mixed-integer linear programming problem is solved over one year with a time resolution of 1 h and using real-world historical data based on the European electricity market. The simulation results indicate that the economic profits can be increased significantly as a result of participating in the ancillary service markets and meeting its operation specifications while the stable performance of the HRS is guaranteed.

Online Trajectory and Resource Optimization for Stochastic UAV-Enabled MEC Systems

The recent development of unmanned aerial vehicle (UAV) and mobile edge computing (MEC) technologies provides flexible and resilient computation services to mobile users out of the terrestrial computing service coverage. In this paper, we consider a UAV-enabled MEC platform that serves multiple mobile ground users with random movements and task arrivals. We aim to minimize the average weighted energy consumption of all users subject to the average UAV energy consumption and data queue stability constraints. We formulate the problem as a multi-stage stochastic optimization, and adopt Lyapunov optimization to convert it into per-slot deterministic problems with fewer optimizing variables. We design two reduced-complexity methods that solve the resource allocation and the UAV movement either in two sequential steps or jointly in one step. Both methods can guarantee to satisfy the average UAV energy and queue stability constraints, meanwhile achieving a tradeoff between the user energy consumption and the length of queue backlog. Simulation results show that the two methods significantly outperform the other benchmark methods including a learning-based method in reducing the energy consumption of ground users. In between, the proposed joint optimization method achieves better performance than the two-stage method at the cost of higher computational complexity.