Different Types Of Services Research Articles

Policies for Building a Functioning Labour Market in Bulgaria

The reduction of the share of industry in creating GDP and in aggregate employment is a natural process which marks the transition from industrial to information society. This cardinal change in the structure of national economies is often accompanied by a radical change in the professional careers of employed people, a rise in unemployment and poverty and exacerbation of social conflicts. The transition from industrial production to the development of different types of services is difficult and often has a high cost.

Understanding Vulnerable Families in Multiple Service Systems Understanding Vulnerable Families.

We analyze Illinois families facing multiple barriers and their interactions with public-sector services. Using administrative data from five state agencies to identify families’ receipt of child welfare, mental health, and substance abuse services as well as adult and juvenile incarcerations, we identify individuals across systems using probabilistic record-linkage techniques, defining family clusters based on networks of individuals who share child welfare and food stamp cases. We show that 23 percent receive services in two or more of these areas. This concentration accounts for 86 percent of the funding for these services used by the entire sample. They experience more and more severe problems. This population is otherwise heterogeneous, engaging with different types of services and clustered in certain parts of the state.

A user preference awareness k-neighbour optimised selection algorithm: modelling and implementation

With the development of the massive amount of web services, the popular research area is involved with the solution to select the required services according to the personal preference for different users. To solve these urgent problems, a user preference awareness k-neighbour optimised selection algorithm is proposed in this paper. Initially, the potential interest of the user is explored by using association rules method of data mining technology. Then, an expanded LDA model is used to analyse the influence on user preference calculation for different types of services caused from the functional attributes of web services. To improve the accuracy of the service selection result, the ant colony algorithm is modified to optimise the service selection process of k-neighbours in traditional collaborative filtering. The experiment shows that our proposed method leads to a higher accuracy and coverage than the traditional web service selection methods based on the real service set.

A machine learning-based design of PRACH receiver in 5G

The physical random access channel (PRACH) in the uplink of cellular systems is used for the initial access requests from users. In fifth generation (5G) systems three different types of services are available, which are massive machine-type communication, enhanced mobile broadband communication, and ultra-reliable low-latency communication. Considering the tight requirements in terms of latency, a robust design of PRACH receiver is one of the priorities. In this paper we first explore the simple extension of a technique proposed for fourth generation (4G) systems to 5G. Then we propose the application of machine learning techniques to make the PRACH receiver more robust to false peaks, which are responsible of performance degradation in the extension of the 4G technique to 5G. Monte Carlo simulations are used to evaluate and compare the performance of the proposed algorithms.

Performance Measurement in Mental Health and Addictions Systems: A Scoping Review.

The purpose of this study was to evaluate how performance is defined, conceptualized, and measured in mental health and addiction service systems around the world. We conducted a systematic scoping review of English-language scientific and gray literature published from 2005 to 2015. Eligible documents (n = 222) described performance measurement systems and outlined the theory or empirical evidence for indicators. We used a structured approach for data extraction and descriptive and thematic analysis, supplemented with stakeholder consultation. We identified seven themes in the literature: similarity in performance domains across frameworks; the ability of frameworks to inform care quality at client, program/facility, and system levels; the predominance of indicators of process and outcome, over structure; the lack of evidence on the links between domains and/or indicators; common, but limited, evaluation of family/caregiver involvement; equity as a cross-cutting domain of performance; and limited attention to performance measurement in peer support services. The literature on performance measurement in mental health and addictions services is vast, and a wide variety of indicators is available to those designing a measurement system. Evaluations of commonly used performance indicators have yielded mixed evidence on their ability to discriminate high- and low-performing service providers, and their sensitivity to changes in policies and practices. As performance measurement efforts grow in scope and complexity, work will be needed to ensure that indicators are fair, appropriate, and suited to support quality improvement in services of different types.

Calculation of External Costs from Production of Direct and Indirect Emissions from Traffic Operation

Abstract The paper addresses the issue of the internalisation of the external costs of direct and indirect emissions from traffic operation on the transport route, on the section of the transport route as well as on the transport of one shipment in freight and one passenger in the bus transport. Existing emission calculators do not allow the calculation of external costs from traffic in the environmental impact of transport services. The article deals with design of methodology for calculator of direct and indirect emissions and the internalisation of external costs of transport services for different types of vehicles in road transport.

Evolution of Tuberculosis/Human Immunodeficiency Virus Services among Different Integrated Models in Myanmar: A Health Services Review.

Myanmar is one of the highly affected countries by tuberculosis (TB) and human immunodeficiency virus (HIV) co-infection. We aimed to review the coverage of TB/HIV integrated services as well as to document the performance of this integrated services. A retrospective program review was conducted using the aggregated data of the National TB Programme (NTP) from 2005 to 2016. In Myanmar, TB/HIV services were initiated in seven townships in 2005. Townships were slowly expanded until 2013. After that, the momentum was increased by increasing the government budget allocation for NTP. In 2016, the whole country was eventually covered by TB/HIV services in different types of integration. Antiretroviral therapy (ART) coverage among HIV-positive TB patients remained low and it was the only significant difference among the three types of integration. Barriers of low ART coverage need to be investigated to reduce the burden of TB/HIV.

Help Seeking Behavior in a Diverse Sample of Asian American Adults

We sought to characterize the help-seeking behavior of Asian Americans living in a Southeastern community in the U.S. by examining different types of services sought, help-seeking preferences, and how demographic characteristics and mental health problems (including domestic violence) predicted these behaviors. 610 Asian Americans (mean age = 39.43 years; 59.6% female; 75% immigrants) completed an anonymous, community survey that included measures of different types of help-seeking behaviors and preferences, mental health symptoms, and exposure to domestic violence. The two most-frequently help-seeking behaviors included seeking advice from friends, family members, or relatives (66.7%), and visiting a medical doctor (46.4%). In logistic regression models, older age, sex, immigrant status and symptomatic depression predicted different types of help-seeking behaviors and preferences. Neither domestic violence experience or symptomatic anxiety significantly predicted help-seeking.

A Multi-Armed Bandit Model-Based Vertical Handoff Algorithm for Heterogeneous Wireless Networks

Vertical handoff is widely accepted as an important issue for ensuring seamless communication in heterogeneous wireless networks. This letter proposes a multi-armed bandit model-based vertical handoff approach (MABA). First, the vertical handoff problem is formulated as a multi-armed bandit problem. Then, the terminal services are divided into real-time services and non-real-time services, and their reward functions are constructed respectively. Finally, the Gittins indices of networks in different states are calculated by the state-elimination algorithm (SEA). Based on the Gittins theorem, the handoff strategy for maximizing the benefit of the system is obtained. Simulation results indicate that the proposed approach could select optimal networks for users with different types of services and reduce blocking probability of the system, thereby improving the performance of the system.

Stochastic Modeling and Optimization of Stragglers

MapReduce framework is widely used to parallelize batch jobs since it exploits a high degree of multi-tasking to process them. However, it has been observed that when the number of servers increases, the map phase can take much longer than expected. This paper analytically shows that the stochastic behavior of the servers has a negative effect on the completion time of a MapReduce job, and continuously increasing the number of servers without accurate scheduling can degrade the overall performance. We analytically model the map phase in terms of hardware, system, and application parameters to capture the effects of stragglers on the performance. Mean sojourn time (MST), the time needed to sync the completed tasks at a reducer, is introduced as a performance metric and mathematically formulated. Following that, we stochastically investigate the optimal task scheduling which leads to an equilibrium property in a datacenter with different types of servers. Our experimental results show the performance of the different types of schedulers targeting MapReduce applications. We also show that, in the case of mixed deterministic and stochastic schedulers, there is an optimal scheduler that can always achieve the lowest MST.

Comparison of ecosystem services provided by grasslands with different utilization patterns in China’s Inner Mongolia Autonomous Region

Although several previous studies in Inner Mongolia examined the effects of ecological conservation on the delivery of ecosystem services, they were often limited in scope (few ecosystem services were assessed) and often suffered from confounding by spatial variation. In this study, we examined the impact of conservation measures (changes in grassland utilization patterns) on the provision of selected ecosystem services in three types of grasslands (meadow steppe in Hulun Buir, typical steppe in Xilin Gol, and semi-desert steppe in Ordos) in Inner Mongolia. We examined five utilization patterns: no use (natural grasslands), light use, moderate use, intensive use, and recovery sites (degraded sites protected from further use). Through household surveys and vegetation and soil surveys, we measured the differences in ecosystem services among the different grassland utilization patterns. We also identified spatial factors that confounded the quantification of ecosystem services in different types of grasslands. We found that light use generally provided high levels of ecosystem services in meadow steppe and typical steppe, with the main differences in the supporting ecosystem services. Surprisingly, we found no consistently positive impacts of strict conservation activities across the sites, since the results varied spatially and with respect to differences in the land-use patterns. Our study suggests that appropriate grassland utilization patterns can enhance the supply of ecosystem services and reduce negative effects on both household livelihoods and the environment.

Modular and deep QoE/QoS mapping for multimedia services over satellite networks

SummarySatellite networks are promising alternatives to deal with the increasing traffic volume and provide universal access for end users. Quality of experience (QoE) as an aggregate of user perception and network quality will be a critical success factor for multimedia service delivery over satellite networks. Quality of experience prediction based on quality of service (QoS) has received much attention recently, but it has been little investigated in satellite networks. In this paper, on the basis of the modular neural network and deep belief networks (DBNs), we design a QoE/QoS mapping method for multimedia services over satellite networks to translate QoS parameters into user QoE. The task of QoE/QoS mapping for multimedia services is decomposed into several different subtasks by using traffic classification. Heterogeneous DBNs are used to learn the mapping relationships between QoE and QoS for different types of services (ie, subtask) simultaneously. An integrative approach based on relative distance is exploited to select subneural network(s) to predict resulting QoE collaboratively. To determine the weight parameters of the QoE/QoS correlation model, the dataset composed of QoS parameters and subjective opinion scores is built on the basis of satellite network simulator and subjective test. Finally, the effectiveness of our QoE/QoS mapping method is validated, and the relationship between adoption rating and opinion scores is analyzed.

Development of resources, technologies and services at the China Zebrafish Resource Center

With the rapid growth of the Chinese zebrafish community, there is an increasing demand for various types of zebrafish-related resources and technologies. The China Zebrafish Resource Center (CZRC, web: http://zfish.cn) was established at the Institute of Hydrobiology (IHB), Chinese Academy of Sciences (CAS) in 2012. Till now, CZRC has built the largest zebrafish aquaculture unit in China, organized a resource bank containing more than 1200 zebrafish lines and more than 10 000 frozen sperm samples, among which over 200 mutant and transgenic lines were generated by CZRC. CZRC has established several technical supporting platforms, such as the zebrafish husbandry and health control program of international standard, a high-efficient gene manipulation technology platform, and a stable and efficient sperm cryopreservation technology platform. The main task of CZRC is to provide different types of services to zebrafish investigators in China and worldwide, such as resource services (e.g. zebrafish lines), technical services (e.g. gene knockout) and transgenic services, consultancy services (e.g. zebrafish husbandry and health consultation), and conference services [e.g. holding regular technical training courses and biennale Chinese Zebrafish Principal Investigator Meeting (CZPM)]. After five years' development, CZRC is now recognized as one of the three major resource centers in the global zebrafish community.

Service-differentiated QoS routing based on ant colony optimisation for named data networking

Named data networking (NDN) is an emerging network architecture for serving content-centric applications, which are intended to support diverse services that require various quality of service (QoS) levels. In this paper, an algorithm based on ant colony optimisation—the so-called service-differentiated QoS routing algorithm (SDQR)—is proposed for service-differentiated routing of different types of services in NDN. SDQR adds a control layer on top of NDN to manipulate the underlying forwarding information base (FIB). The FIB defines an evaluation matrix to achieve differentiated updates on pheromone concentrations for different types of services. Simulation results showed that SDQR achieves service-differentiated routing for different types of services with less delay and higher throughput than several conventional approaches.

Adaptive Fog Configuration for the Industrial Internet of Things

Industrial Fog computing deploys various industrial services, such as automatic monitoring/control and imminent failure detection, at the Fog Nodes (FNs) to improve the performance of industrial systems. Much effort has been made in the literature on the design of fog network architecture and computation offloading. This paper studies an equally important but much less investigated problem of service hosting where FNs are adaptively configured to host services for Sensor Nodes (SNs), thereby enabling corresponding tasks to be executed by the FNs. The problem of service hosting emerges because of the limited computational and storage resources at FNs, which limit the number of different types of services that can be hosted by an FN at the same time. Considering the variability of service demand in both temporal and spatial dimensions, when, where, and which services to host have to be judiciously decided to maximize the utility of the Fog computing network. Our proposed Fog configuration strategies are tailored to battery-powered FNs. The limited battery capacity of FNs creates a long-term energy budget constraint that significantly complicates the Fog configuration problem as it introduces temporal coupling of decision making across the timeline. To address all these challenges, we propose an online distributed algorithm, called Adaptive Fog Configuration (AFC), based on Lyapunov optimization and parallel Gibbs sampling. AFC jointly optimizes service hosting and task admission decisions, requiring only currently available system information while guaranteeing close-to-optimal performance compared to an oracle algorithm with full future information.

Trading and Ordering Patterns of Market Participants in High Frequency Trading Environment: Empirical Study in the Japanese Stock Market

In this study, we investigate ordering patterns of different types of market participants in Tokyo Stock Exchange (TSE) by examining order records of the listed stocks. Firstly, we categorize the virtual servers in the trading system of TSE, each of which is linked to a single trading participant, by the ratio of cancellation and execution in the order placement as well as the number of executions at the opening of the afternoon session. Then, we analyze ordering patterns of the servers in the categories in short intervals for the top 10 highest trading volume stocks. By classifying the intervals into four cases by returns, we observe how different types of market participants submit or execute orders in the market situations. Moreover, we investigate the shares of the executed volumes for the different types of servers in the swings and roundabouts of the Nikkei 225 index, which were observed in September in 2015. The main findings of this study are as follows: Server type A, which supposedly includes non-market making proprietary traders with high-speed algorithmic strategies, executes and places orders along with the direction of the market. The shares of the execution and order volumes along with the market direction increase when the stock price moves sharply. Server type B, which presumably includes servers employing a market making strategy with high cancellation and low execution ratio, shifts its market making price ranges in the rapid price movements. We observe that passive servers in Server type B have a large share and buy at low levels in the price falls. Also, Server type B, as well as Server type A, makes profit in the price falling days and particularly, the aggressive servers in the server type make most of the profit. Server type C, which is assumed to include servers receiving orders from small investors, constantly has a large share of execution and order volume.

$N$-in-One: A Novel Location-Based Service

Location-based services (LBSs) are becoming an increasingly important component in our social and business life. All existing LBS providers support the nearest place searching via a single point of interest (POI) query. That is, in one query, a user is allowed to search for only one type of service. However, in real life, people usually need to search multiple different types of services and hope that their locations are as close as possible for convenience. For example, one user would like to search for a restaurant with a KTV nearby. To support this application scenario, we propose a novel LBS termed “ $N$ -in-One,” which is the first scheme to extend the function of single-POI LBS to multiple-POI LBS such that a single query can be employed to request multiple POIs that are geographically close. Providing “ $N$ -in-One” is challenging because: 1) serving a “ $N$ -in-One” query is not equivalent to serving $N$ queries independently due to the distance correlation among the $N$ POIs; and 2) the cask effect is getting worse in the service area mode of “ $N$ -in-one” as most of the returned results may be rendered useless when some hot POIs are blocked. To overcome these challenges, we propose several algorithms using computational geometry techniques to identify the best $K$ POIs that are geographically close and the service area (denoted by a given-sized rectangle) that can cover as many the best $Q$ clusters as possible while reducing the cask effect in the service area mode. Extensive simulations based on both synthetic and real world data demonstrate the effectiveness of the proposed algorithms.

Nursing Now - why nurses and midwives will be even more important and influential in the future.

Nursing Now - why nurses and midwives will be even more important and influential in the future.

Spatial visitation prediction of on-demand ride services using the scaling law

The scaling law is a functional relationship between two quantities. The distributions of a wide variety of phenomena approximately follow scaling laws over a wide range of magnitudes, e.g., travel distance, spatial density, visitation frequency, etc. The spatial visitation frequency was confirmed following such empirical distributions, too, providing us a possibility for the spatial visitation prediction. This paper analyzes the scaling laws of dynamic spatial visitation frequencies using real on-demand ride service data from the platform of DiDi in Hangzhou, China. We predict the ranking of grids in terms of the densities of both points of interest (POIs) and different types of services provided by the platform (i.e., e-hailing taxi, DiDi Express, and Hitch). There are two main findings in the paper: Firstly, an exponential form of the scaling law does exist for the frequency–ranking relationship with the DiDi dataset, which has not been discussed in the research area of on-demand ride services. Secondly, the spatial visitation prediction model is proposed to explain the importance of POIs variables and service variables in different time periods. The results show that the weighting of variables is positively related to its attractiveness. The findings indicate that our model has good interpretability while predicting spatial–temporal arrivals with a high accuracy.

Capital social y asimilación ocupacional de los migrantes internos en Perú

La migración interna es uno de los fenómenos que más ha configurado la población, la economía y la geografía peruanas en el último siglo. En este estudio se parte de la premisa de que la migración es un proceso complejo que puede tener efectos diferenciados sobre las personas dependiendo de una diversidad de factores. Esto cobra particular relevancia si se busca evaluar el desempeño de los migrantes en un mercado rígido como el laboral. Así, se plantean mecanismos como la contribución de la sociedad civil y de otras disposiciones institucionales que pueden proveer una gama de beneficios y servicios a sus miembros cuando los mercados no son perfectos, como en el caso de las elecciones ocupacionales. Por lo anterior, el presente trabajo muestra cómo el capital social interviene en la asimilación ocupacional de los migrantes internos en Perú. Para ello, se presenta un modelo teórico en el cual se plantea que dos tipos de capital social (étnico y adquirido) pueden ofrecer distintos tipos de servicios, dependiendo del nivel de complementariedad de este con el nivel educativo y con el tiempo que el migrante lleve en su lugar de destino (migrantes recientes y establecidos). A partir de la Encuesta Nacional de Hogares (2014) y de una estimación mediante logit multinomial, se encuentra que el capital social étnico incrementa la probabilidad de desempeñar una ocupación elemental únicamente para los migrantes recientes y que el capital social adquirido incrementa la probabilidad de desempeñar una ocupación de alta calificación para los migrantes establecidos.