Service Aggregation Research Articles

Classifying the Political Leaning of News Articles and Users from User Votes

Social news aggregator services generate readers’ subjective reactions to news opinion articles. Can we use those as a resource to classify articles as liberal or conservative, even without knowing the self-identified political leaning of most users? We applied three semi-supervised learning methods that propagate classifications of political news articles and users as conservative or liberal, based on the assumption that liberal users will vote for liberal articles more often, and similarly for conservative users and articles. Starting from a few labeled articles and users, the algorithms propagate political leaning labels to the entire graph. In cross-validation, the best algorithm achieved 99.6% accuracy on held-out users and 96.3% accuracy on held-out articles. Adding social data such as users’ friendship or text features such as cosine similarity did not improve accuracy. The propagation algorithms, using the subjective liking data from users, also performed better than an SVM based text classifier, which achieved 92.0% accuracy on articles.

A Study on Federated Cloud Computing Environment

Federated cloud computing is the advancement in the area of the general cloud computing paradigm. In a federated cloud environment, multiple cloud service providers share their computing assets, servers, and various facilities to fulfill customer demands. Federated cloud computing terminology consists of the aggregation of services considered by interoperability characteristics and creates the integration of several cloud service providers regardless of any geographical location. It improves the performance, utilization of facilities, minimizes response time and pricing model by partial subcontracting various computing resources and facilities from the nearby cost-efficient province. Customers also get profited from service level agreements signed between the cloud service providers through intermediator cloud brokers. This work aims to survey the federated cloud environment, its various architectural types, advantages associated with the federation, challenges associated with a federated cloud environment, and future research directions in the federated cloud computing research area.

To pool or not to pool: Equilibrium, pricing and regulation

We study a transportation network company (TNC) that offers on-demand solo and pooling e-hail services in an aggregate mobility service market, while competing with transit for passengers. The market equilibrium is established based on a spatial driver–passenger matching model that determines the passenger wait time for both solo and pooling rides. We prove, under mild conditions, this system always has an equilibrium solution. Built on the market equilibrium, three variants of pricing problems are analyzed and compared, namely, (i) profit maximization, (ii) profit maximization subject to regulatory constraints, and (iii) social welfare maximization subject to a revenue-neutral constraint. A comprehensive case study is constructed using TNC data collected in the city of Chicago. We found pooling is desirable when demand is high but supply is scarce. However, its benefit diminishes quickly as the average en-route detour time (i.e., the difference between the average duration of solo and pooling trips) increases. Without regulations, a mixed strategy—providing both solo and pooling rides—not only achieves the highest profit and trip production in most scenarios, but also gains higher social welfare. The minimum wage policy can improve social welfare in the short term. However, in the long run, the TNC could react by limiting the size of the driver pool, and consequently, render the policy counterproductive, even pushing social welfare below the unregulated level. Moreover, by maintaining the supply and demand of ride-hail at an artificially high level, the minimum wage policy tends to exacerbate traffic congestion by depressing the use of collective modes (transit and pooling). A congestion tax policy that penalizes solo rides promotes pooling, but may harm social welfare. However, it promises to increase both social welfare and pooling ratio when jointly implemented with the minimum wage policy.

Field Experiments and Job Posting Sources: The Consequences of Job Database Selection for Estimates of Racial Discrimination

Field experiments have proliferated throughout the social sciences and have become a mainstay for identifying racial discrimination during the hiring process. To date, field experiments of labor market discrimination have generally drawn their sample of job postings from limited sources, often from a single major online job posting website. While providing a large pool of job postings across labor markets, this narrow sampling procedure leaves open questions about the generalizability of the findings from field experiments of racial discrimination in the extant literature. In this paper, we present evidence from a field experiment examining racial discrimination in the hiring process that draws its sample from two sources: (1) a national online job posting website that aligns with previous research, and (2) a job aggregator service that scrapes the web daily in an effort to obtain all online job postings in the United States. While differing in the types of information they collect, we find the job postings drawn from the two sources result in similar estimates of discrimination against Black applicants. In other words, we do not find evidence that racial discrimination varies by the source of the job posting. We conclude by discussing the implications of these findings for studies of racial discrimination, discrimination along other axes of social difference, as well as field-experimental methods more broadly.

Optimal sizing of energy communities with fair revenue sharing and exit clauses: Value, role and business model of aggregators and users

Energy communities (ECs) are essential tools to meet the Energy Transition goals but, to fully unleash their potential, they require a coordinated operation and design that the community itself may be ill-equipped to manage. Aggregators and Energy Service COmpanies (ESCOs) can perform this support role, but only provided that their goals are aligned to those of the community, not to incur in the agency problem. In this study, we propose a business model for aggregators of ECs, and its optimization problem, accounting for all crucial aspects: (i) alleviating the risk of the agency problem, (ii) fairly distributing the reward awarded to the EC, (iii) estimating the fair payment for the aggregator services, and (iv) defining appropriate exit clauses ruling what happens when a user leaves the EC. A mathematical model is developed, employing several fair game-theoretic reward distribution schemes, some of which are proposed here for the first time. A case study is developed, and results show that the aggregator enables reducing costs by 16% and improving renewable penetration and self/shared consumption by 35%–51% with respect to the base case. Our results suggest that the aggregator fair retribution is around 16%–24% the added benefit produced with respect to the base case, and that stable reward distribution schemes, such as Shapley/Core, Variance/Core or Nucleolus, are stable and recommended. Moreover, the results highlight the unwanted effect that some non-cooperative ECs may have an added benefit without providing any positive effect to the power system. Our work provides a methodology and preliminary results that can help policy makers and developers in tailoring national-level policies and market-offerings.

PADP: Efficient Privacy-Preserving Data Aggregation and Dynamic Pricing for Vehicle-to-Grid Networks

With the fast development of Internet of Things (IoT) especially for smart grid and electric vehicle (EV) networking, vehicle-to-grid (V2G) communications have been increasingly studied and recognized as one of the most convincing tools for general road transportation, to effectively reduce the oil demands and gas emissions. Unfortunately, a series of security and privacy issues have significantly impeded its wide adoption. The existing work mainly focused on the static environment, which cannot be directly applied to the mobile setting where EVs travel across regions. The dynamic pricing metric in V2G networks depends on the real-time electricity usage aggregation in one region. To address this issue, in this article, an efficient privacy-preserving data aggregation and dynamic pricing service PADP in V2G IoT is proposed, by designing an identity-based sequential aggregate signed data (SASD) based on factoring and a threshold homomorphic encryption. In the proposed threshold homomorphic encryption, a legal ciphertext can be generated if and only if no less than threshold k individual illegal ciphertexts are aggregated. Therefore, the aggregated power consumption data can be successfully decrypted while the individual power consumption privacy of honest EV users can be well protected against even the collusion between a malicious power charging station and compromised EVs. Furthermore, the technique of SASD guarantees entity authentication with a minimized amount of transmitted data. Finally, formal security proof and extensive performance evaluation demonstrate the effectiveness and practicability of our proposed PADP.

A work-unit level analysis of employees’ well-being and service performance in hospitality industry

In this manuscript, the relationship between hotel work-units’ aggregate well-being and service performance is examined in two different ways. First, by analysing the simultaneous relationship between two main facets of well-being at work (job satisfaction and emotional exhaustion) and service quality perceived by customers, at unit level of analysis. Second, by exploring the moderating role of within-unit dispersion in satisfaction and emotional exhaustion on these links, respectively. The study sample consisted of 398 service employees and 1233 customers from 42 hotels. Using Mplus 5, the results showed that at the unit level of analysis, job satisfaction was positively related to customer-shared perceptions of service quality, while emotional exhaustion was negatively related to it. Moreover, the results provided support for the idea that the positive or negative relationship was more pronounced in hotel work-units where there was less internal variability in satisfaction/exhaustion than in units where the variability was greater. Taken together, our findings highlight the importance of noticing the dispersion in satisfaction and emotional exhaustion in work-units in order to understand the relationship between well-being and service quality perceived by customers and, therefore, for the development of intervention programs aimed at increasing well-being at work and service quality in hospitality companies.

ORIGIN AND WEIGHT OF NEWS MEDIA OUTLETS INDEXED ON GOOGLE NEWS: An exploration of the editions from Brazil, Colombia, and Mexico

ABSTRACT – Google News is a controversial news aggregation service owned by Google. By analyzing 3,738,375 news stories added in the Brazil, Colombia, and Mexico editions from January to March of 2015, 2,246 news media outlets were identified. In these editions, specific to their countries, large, popular, and traditional news media such as G1 (under Globo.com), Terra Brasil, El Universal, ElTiempo.com, and Caracol Radio had the highest rates of news aggregation in their respective country edition. This meant that they had greater visibility as well as a higher probability of receiving traffic from it, above the other indexed news media outlets.RESUMO – O Google News é um serviço controverso de agregação de notícias de propriedade do Google. Ao analisar 3.738.375 notícias adicionadas nas edições Brasil, Colômbia e México, de janeiro a março de 2015, foram identificados 2.246 meios de comunicação. Nessas edições, específicas de seus países, grandes mídias, populares e tradicionais como G1 (sob Globo.com), Terra Brasil, El Universal, ElTiempo.com e Caracol Radio apresentaram as maiores taxas de agregação de notícias em suas respectivas edições de cada país. Isso significava que eles tinham maior visibilidade e maior probabilidade de receber tráfego deles, acima dos outros meios de comunicação indexados.RESUMEN – Google News es un servicio de agregación de noticias controvertido propiedad de Google. Al analizar 3.738.375 noticias agregadas en las ediciones de Brasil, Colombia y México, de enero a marzo de 2015, se identificaron 2.246 medios. En estas ediciones, específicas de sus países, grandes medios, populares y tradicionales como G1 (bajo Globo.com), Terra Brasil, El Universal, ElTiempo.com y Caracol Radio presentaron las tasas más altas de agregación de noticias en su respectiva edición por país. Esto significaba que eran más visibles y más propensos a recibir tráfico de éste, por encima de otros medios noticiosos indexados.

Heuristics for setting reorder levels in periodic review inventory systems with an aggregate service constraint

Inventory managers are responsible for the trade-off between inventory holding costs and customer service. In this paper we consider a periodic review multi-item inventory system with exogenous lot-sizes and backordering. The objective is to minimize the total inventory holding costs subject to the constraint that the aggregate fill rate should be at least equal to a target level. The aggregate fill rate is a weighted average of the fill rates of all items in the assortment. We consider three ways of defining this aggregate fill rate: using generic weights, weights based on the average demand (volume) or weights based on the average (monetary) turnover. We show that the definition of the aggregate service can have huge effects on the performance of the system. So, inventory managers should be very careful on which definition to apply. We also derive four heuristics to determine the reorder levels for all items. One heuristic is very generic and can be applied to many problems including multi-item multi-echelon inventory systems and systems with a constrained aggregate ready rate. Since multiple assumptions made to derive the heuristics are common assumptions made in the literature, we first test the accuracy of these approximations using simulation. Next, we evaluate the heuristics based on data from a large international reseller. The heuristic based on the most accurate approximation performs best, is close to optimal and very efficient. Savings compared to no service level differentiation are large (up to 28.7%) and depend on the definition of the aggregate service.

Improving Aggregate Utility and Service Differentiation of IEEE 802.11ah Restricted Access Window Mechanism Using ANFIS

Improving Aggregate Utility and Service Differentiation of IEEE 802.11ah Restricted Access Window Mechanism Using ANFIS

STRATEGIC MECHANISMS OF REGULATING THE EUROPEAN INTEGRATION DEVELOPMENT OF AIR TRANSPORT IN UKRAINE

The purpose of the paper is to substantiate the strategic mechanisms for regulating the European integration development of air transport in Ukraine. Methodology. The study is based on the imperatives of European integration development of air transport of Ukraine, defined in the Association Agreement between the European Union and the European Atomic Energy Community and their member states, on the one part, and Ukraine, on the other part. Quantitative research is based on the analysis of the volume and structure of Ukraine’s foreign trade in air transport services, calculation of the export-import coverage ratio, determination of the share of transport and air transport services in aggregate services in total foreign trade, including with the EU. Results of the paper consist in assessing the impact of the external environment on the European integration development of the Ukrainian aviation transport. The conclusion was reached on its turbulence, complexity and contradiction, while the advantageous geographical location and strategic positions of Ukraine in the region were determined as the main favorable factors. The research also singles out the following negative signs of the external environment: declining competitiveness of the Russian-Asian lanes for domestic air carriers, localization of air services in connection with hostilities in the East of Ukraine; restriction of air traffic in the context of preventive measures to combat the spread of coronavirus infection; insufficient material and technical base: lack of funding, outdated technologies, low level of innovation, environmental friendliness, safety, insufficient quality of transport services, limited social benefits; aimed at ratification of the CAA Agreement between Ukraine and the EU, as well as the draft Aviation Transport Strategy of Ukraine. The present research also identified such negative effects of COVID-19 on the development of air transport, as: a significant decrease in air passenger transport services and airlines’ revenues, a decrease in the rating of world aviation, termination and bankruptcy of a number of airlines and airports due to air traffic restrictions. It determined the place of air transport services in the system of foreign economic trade in services with the EU countries, and developed measures to increase them. Practical implications consist in the elaboration of the main strategic guidelines for the development of aviation: introduction of a simplified procedure for implementing the provisions of EU legislation into the legislation of Ukraine; ensuring environmental safety and energy saving of civil aviation facilities; innovative renewal of aircraft fleet and reduction of their harmful impact on the environment through the introduction of the latest technologies; settlement of issues relating to the establishment of airport charges for the servicing of aircraft and passengers at Ukrainian airports; development of airport infrastructure; creation of multimodal cargo complexes; approximation of SAAU and European Commission requirements to certification systems in the areas of primary airworthiness, airworthiness maintenance and maintenance of aircraft and its components; expansion of Ukraine’s voluntary participation in the program of compensation and reduction of carbon dioxide emissions from international aviation within the CORSIA program, introduction of administrative procedures for monitoring emissions by operators of civil aircraft on international flights under the MRV standards. Value/originality. The present research substantiates strategic foundations of the institutional transformations of the development of aviation transport in the context of the European integration choice of Ukraine and the transition to monovectorality, elimination of defects of dependence on the trajectory of the preceding traffic and polyvectorality. It also proposes legal, policy, investment and infrastructure integration mechanisms.

QUEUING THEORY APPLICATION AND CUSTOMERS’ TIME MANAGEMENT IN DEPOSIT MONEY BANKS IN NIGERIA

The study examined queuing theory, application and customers time management in deposit money banks in Nigeria.. A comparative analysis between Access Bank PLC branch in Ajilosun and First Bank PLC, Oke Isa, Ado Ekiti, Ekiti State were used as a case study. Data for the study were gathered through observation of the arrival time, time spent waiting in the queue, service time and time of departure customers from the banking hall. The observation time at Access Bank started by 2.30pm and ended 3.44pm which has been previously observed to be the peak period of the bank while the observation time of the First Bank PLC started 3.00pm and ended 4.57pm on different days. Data sourced were fitted into the single and multiple channel models and the results computed and analyzed manually. It was revealed that the mean service rate, the mean time spent in the queue by a customer, and aggregate service rate in the system by a customer at Access bank plc are substantially reduced compared to that of the first bank plc while the waiting line is short most especially for the multiple channels with the real time data processing enhancing the service delivery. It was concluded that despite these differences, queuing system and application of it in the banking industry, especially in the sampled banks is effective in achieving quality service delivery and this is also enhanced by the application of real time data processing adopted by the banks. Therefore, the study recommended that queue management should be employed by banks as it will enhance the quality of service delivery and time management for both banks and the customers. In addition, a single channel for banks that have high traffic intensity rate should be discouraged while a multiple channel should be encouraged as it reduces the waiting time of bank customers in the system. Lastly, idle time of the servers need to be checked as this could lead to more waiting time for customers.

Quantifying the effects of medium voltage–low voltage distribution network constraints and distributed energy resource reactive power capabilities on aggregators

Distributed energy resources (DER), such as, photovoltaic systems and batteries, are becoming common among households. Although the main objective is reducing electricity imports (bills), they could also provide system-level services via an aggregator. However, the more DER provide services, the more important is ensuring that the corresponding operation does not result in network issues. To help DER aggregators understand the implications of network constraints, an AC optimal power flow-based methodology is proposed to quantify the effects that three-phase low voltage (LV) and medium voltage (MV) network constraints can have on the volume of services that can be provided for a given horizon, and the potential benefits from using DER reactive power capabilities. Using a convex multi-period formulation that avoids binary variables for batteries and incorporates voltage-dependent load models, the methodology maximizes DER exports (services) for service-related periods and household self-consumption for other periods (reducing bills). Different service periods are assessed to explore the extent of services throughout the day. Results using a realistic UK MV-LV network with 2400+ households, show that aggregator services can be highly overestimated when neglecting MV-LV network constraints, are influenced by voltage-demand load characteristics, and that exploiting DER reactive power capabilities can significantly unlock further services.

Design of P2P-SIP System Network Structure Based on JXTA

Session Initiation Protocol (SIP) is one of the most important signaling connection protocols in the field of VoIP (Voice over Internet Protocol). However, the existing SIP network has some problems such as manual configuration, difficult maintenance and poor scalability. With the development of P2P (Peer-to-Peer) technology, the combination of SIP and P2P has become a trend. JXTA is an open peer-to-peer platform, which provides basic application services for building P2P network. The topic chooses JXTA development platform to build P2P network, and then constructs SIP soft terminal on it. Based on the in-depth study of JXTA structured network and SIP protocol, a P2P SIP system is designed and implemented. The system can maintain normal SIP communication without maintaining the central server. In this paper, the detailed design and implementation process of P2P-SIP system are given, including node join and leave, user join, user search and session establishment. This paper focuses on the implementation process of user search, that is, the collaborative process of discovery service, resolution service, aggregation service and endpoint routing service. Finally, the feasibility of the system is verified by functional test.

Do FDI inflows to Eastern Europe and Central Asia respond to the business cycle? A sector level analysis

This study aims at establishing the behavior of sectorial Foreign Direct Investments (FDI) inflows, i.e. FDI into the sectors of extractives, manufacturing, aggregate services, and financial and non-financial services, in relation to the business cycle. We construct a model that controls for established determinants of FDI, including income, human capital, quality of institutions, and natural resource endowments, and apply a dynamic panel GMM estimator to data for 19 Eastern European and Central Asian economies. The results suggest that aggregate services FDI inflows are countercyclical, increasing during economic contractions and decreasing during economic booms, while the rest of the FDI inflows are acyclical, i.e. do not respond to the business cycle.

Aid for Trade and Trade in Services

Existing research generally finds weak positive effects of aid for trade (AfT) on aggregate merchandise trade of recipients once endogeneity in the AfT-trade relationship is accounted for. In this paper, we confirm weak findings for both aggregate merchandise and services trade of recipients, using GMM and IV estimations. Moreover, estimates lose statistical significance if non-AfT explanatory variables are treated as endogenous in estimation suggesting identification issues may not have been adequately addressed in extant work. We then examine an alternative proposition: that effects of AfT and different categories of AfT may be observed along the conditional distributions of exports and imports. Our findings confirm this hypothesis. AfT allocated to economic infrastructure, productive capacity building in services and trade policies and regulation is more effective for smaller trading economies, especially in services. We also observe considerable heterogeneity in the trade effects of AfT allocated to individual services sectors, indicating the importance of country-specific diagnostics in targeting AfT allocation.

COVID-19 Impact on Exports of Services: Opportunities, Challenges and Suggestions for India

The COVID-19 outbreak has put the global economic scenario out of order. The mechanism of lockdown and social distancing has paved a grave situation for global trade in general and services in particular as they are inseparable and requires proximity between the supplier and the consumer. In view of the outstanding contribution of services in India’s foreign trade, this study examines the impact of the pandemic on aggregate, sectoral and mode-wise services exports from India. It ultimately seeks to highlight key opportunities, challenges and suggestions to protect and promote India’s services interest amid this global disruption. We review the quarterly and monthly services exports patterns from January to July 2020 based on the data obtained from the World Trade Organization and the Reserve Bank of India. The perspective on mode-wise services exports is derived from the Trade-in Services by Modes of Supply (TISMOS) data set of the WTO for 2017. The analysis highlights a severe drop in overall services exports, by over 10% during the second quarter of 2020. Travel, transport and financial services have been hit hardest. However, the decline in India’s services exports found as relatively much lower in comparison to other major services exporting economies. The comparative edge in digital or Mode 1 services offers greater opportunities for the country in the longer period if urgent policy initiatives and support are extended to potential online services sectors.

Throughput Maximization Based on Optimized Frame-Aggregation Levels for IEEE 802.11 WLANs

To improve the throughput via frame aggregation (FA), the number of aggregate medium access control service data unit (A-MSDU) and protocol data unit (A-MPDU) subframes must be set appropriately under the IEEE 802.11 standards. In this letter, we construct an optimization problem that maximizes theoretical throughput considering bit error in A-MSDU under the IEEE 802.11ac standard based on the detailed structure of FA. Further, we propose a scheme to determine the optimal subframe sets through an exhaustive search for not only A-MPDU but also A-MSDU. The proposed scheme is validated through numerical calculations and Monte Carlo computer simulations. Although the computational complexity of the proposed scheme is larger than that of the conventional scheme, it leads to a significant throughput improvement.

Show Me the (Data About the) Money

Information about consumers, their money, and what they do with it is the lifeblood of the flourishing financial technology (“FinTech”) sector. Historically, highly regulated banks jealously protected this data. However, consumers themselves now share their data with businesses more than ever before. These businesses monetize and use the data for countless prospects, often without the consumers’ actual consent. Understanding the dimensions of this recent phenomenon, more and more consumer groups, scholars, and lawmakers have started advocating for consumers to have the ability to control their data as a modern imperative. This ability is tightly linked to the concept of open banking—an initiative that allows consumers to control and share their banking data with service providers as they see fit. But in the U.S., banks have threatened to block the servers of tech companies and data aggregators—business entities that serve as the middlemen connecting FinTech companies and banks, enabling consumers to get more financial services—from accessing their customers’ data even if the customers agree to it. With no regulation or accepted standards for the ethical gathering and use of data, banks argue that limiting access helps them protect their clients’ privacy, improve their accounts’ safety, and promote consumer protection principles. Banks claim that FinTech apps collect more data than needed, store it insecurely, and sell it to others. But the motivation of the big banks in advocating for such limitations may not be so pure. Banks do not want to relinquish competitive advantages, lose customers, or be held liable for data or fund losses. Witnessing resistance, tech companies are not sitting idly by waiting for banks to limit their data access. Instead, they are working on ways to outsmart banks’ blocking technology and use data aggregation services as a middleman. They also extended the fight into Washington, where regulators such as the Federal Trade Commission (FTC) and the Consumer Financial Protection Bureau (CFPB) are noticing how technology impacts consumer data flows and credit reporting issues. Advocating for consumers’ rights to control data, tech companies lobby for open banking.

Exploring edge computing in artificial intelligence using service aggregation standards

Edge computing is to support physical impairment evaluation, execution monitoring, alarm message filter based on an On-board artificial intelligence approach. Now a day a smart approach called Artificial Intelligence is being developed to pretend thinking and learning ability of human beings. Since Machine Learning is incorporated with an advanced tool it has several industrial applications such as manufacturing, petrochemical, and power plants. An artificial intelligence which is a development of edge computing (EC) in fifth-generation (5G) networks can be meet the needs of everything as a service in the networks edge. Since the theory of edge-artificial intelligence is much useful in fulfillment of AI service. Cloud computing has more computational complexity and delay, so edge computing will be preferred in terms of back-up & restore data and reliability in internet of things (IoT) based industrial applications. In industrial devices the computational speed and range of internet of things (IoT) at edge can be enhanced with aid of artificial intelligence. In this paper an AI-based service aggregation problem using edge computing in various industrial applications will be implemented. The energy efficiency, good duty cycle, storage capacity and reliability can be achieved by using Service Aggregation Edge Computing (SAEC).