Concept Of Aggregation Research Articles

An Approach for Context-Aware Cyber-Physical Automation Systems

Abstract Future automation systems, operating under increasing dynamic conditions need to be equipped with methods to enhance their adaptability accordingly. Context-aware systems model and apply contextual parameters influencing the interpretation of situations to adapt their operation accordingly. Designing context-aware automation systems requires methods to acquire and process heterogeneous and distributed data in a dynamic and continuous manner. In this contribution, a methodology for processing multimodal data in a flexible and reusable context-model is demonstrated, using concepts of data aggregation and integration, semantic labeling and graph modeling. Based on this approach, the use case of a context-aware medication assistance system is subsequently presented.

A Lightweight Certificate-Based Aggregate Signature Scheme Providing Key Insulation

Recently, with the advancement of Information and Communications Technology (ICT), Internet of Things (IoT) has been connected to the cloud and used in industrial sectors, medical environments, and smart grids. However, if data is transmitted in plain text when collecting data in an IoT-cloud environment, it can be exposed to various security threats such as replay attacks and data forgery. Thus, digital signatures are required. Data integrity is ensured when a user (or a device) transmits data using a signature. In addition, the concept of data aggregation is important to efficiently collect data transmitted from multiple users (or a devices) in an industrial IoT environment. However, signatures based on pairing during aggregation compromise efficiency as the number of signatories increases. Aggregate signature methods (e.g., identity-based and certificateless cryptography) have been studied. Both methods pose key escrow and key distribution problems. In order to solve these problems, the use of aggregate signatures in certificate-based cryptography is being studied, and studies to satisfy the prevention of forgery of signatures and other security problems are being conducted. In this paper, we propose a new lightweight signature scheme that uses a certificate-based aggregate signature and can generate and verify signed messages from IoT devices in an IoT-cloud environment. In this proposed method, by providing key insulation, security threats that occur when keys are exposed due to physical attacks such as side channels can be solved. This can be applied to create an environment in which data is collected safely and efficiently in IoT-cloud is environments.

Investigations on scheduling algorithms in LTE-advanced networks with carrier aggregation

Third generation partnership project (3GPP) long-term evolution advanced (LTE-A) is the fastest growing technology, which supports variety of applications by using effective and efficient radio resource management (RRM) procedure. With carrier aggregation (CA) concepts included in LTE-advanced protocol, the complexity of the RRM and scheduling of data increases. In this paper, basic LTE-A concepts and a study of different methods of component carrier allocation is studied and performance evaluation is carried out. From the simulation results, it can be inferred that static methods of component carrier allocation is simple but it could not be able to satisfy various important scheduler metric to provide a better QoS to UE. The random method though for some cases it seen better but it is not reliable as the outputs are also random. The dynamic methods of component carrier allocation have been able to provide better scheduler performance metric compared to static and random methods. More over different dynamic approaches can be also combined to improve the overall system efficiency.

Розвиток креативно-активних студентів на шляху до формування персоналу всіх сфер економіки

The article is aimed at researching, studying and substantiating the advantages and problems regarding the creativity of students in the process of obtaining professional education. In accordance with the aim of the research, the following tasks are set: to define the concept of «creativity», the prerequisites for the emergence of creative abilities; to characterize the conditions for stimulating the creative abilities of students; to identify obstacles and reasons for the lack of a creative component in the process of higher education; to build up an algorithm for the development of creative abilities in students; to outline the conditions for creating a favorable environment wherein the student’s creative inclinations will be manifested. The object of research is the processes of reforming higher education in the direction of compliance with modern European trends in education development; formation of an environment favorable for the development of creativity of student in the process of obtaining higher education through the algorithm of purposeful pedagogical activity. The subject of the study are theoretical and applied provisions on the formation of an environment favorable for the development of the student’s creativity in the process of obtaining higher education. The scientific novelty of the research consists in the formation of a single aggregate concept of creativity of students and in the formation of ways to overcome problems in the process of developing the creativity of students in obtaining professional education. The practical implementation of the research results will allow reforming higher education in the direction of forming a creatively active environment for teachers and students; will allow to bring the system of national education closer to the formation of such specialists in the labor market, which will be in high demand among domestic and foreign employers.

무작위합역 절차의 다양성에 대한 시뮬레이션 연구

The main objectives of this study are to discuss on the diversity of random spatial aggregation, to compares pros and cons of the different random spatial aggregation procedures, and to recommend a procedure which is believed to be superior in validity. A basic procedure for random spatial aggregation is proposed and an implementation algorithm based on the spatial proximity matrix is introduced. All six distinctive algorithms are derived on the basis of two dimensions which facilitate the diversity of random spatial aggregation. A simulation experiment is carried out to compare pros and cons of the six procedures and its results are evaluated based on the contiguousness and compactness criteria. Main findings are as follows. First, Category B seems to be more consistent in terms of contiguousness in comparison to Category A and C. Second, Category 2 appears to generate more compact final zones in comparison to Category 1. Third, Category B and C (especially B) seem to be more consistent in terms of compactness. Based on all the experiment results, Type B2 seems to be the superior algorithm for random spatial aggregation. It tends to generate more compact final zones and more consistent results in terms of both contiguousness and compactness. This study can be seen as a significant achievement in the sense that it shows that the concept of random spatial aggregation can be considered in a diversified manner, and one out of a certain group of candidates can be chosen as superior on the basis of the degree of randomness and relevancy.

Вопросы типологии инфраструктуры муниципальных образований

The subject of this work is the uneven development of infrastructure in municipal districts of the Russian Federation. The article presents the author’s method of typology of municipalities by the level of infrastructure development, which allows overcoming the shortcomings of the information base of municipal statistics using the data imputation algorithm. The proposed approach solves the problem of weak population structure using a combination of four methods of multidimensional statistics (cluster analysis, factor analysis, metric multidimensional scaling and discriminant analysis) in the framework of a combination of variational and aggregate concepts of data typology. The idea of the considered method is that if an object falls into the same type as a result of applying different typology methods, then it is a stable representative (“core”) of this type. A set of such objects for each type is used as training samples for discriminant analysis, which allows you to typologize the remaining transition objects using mathematical tools. The methodology was tested on a set of municipal districts of the Russian Federation (in 2018). There are 4 types of municipal districts with high, satisfactory, insufficient and low level of infrastructure development. As of 2018, 89 (5.1%) municipal districts of the Russian Federation have a high level of infrastructure development, 308 (17.6%) – satisfactory, 570 (32.6%) – insufficient, 783 (44.7%) – low. The inverse relationship between the level of infrastructure development of municipal districts and the degree of urbanisation of the territory is shown: the largest number of districts with highly developed infrastructure is located in territories with a significant share of the rural population.

Dealing with Moral Uncertainty: Do Logical Properties Help?

If an agent is unsure about which moral theory or principle should guide her action in a decision situation, she faces moral uncertainty. In recent years, various strategies have been explored to deal with this type of uncertainty. In this paper, we briefly mention two strategies from the literature that make use of credence distributions over moral theories, namely “my favourite theory” and “maximizing expected choice-worthiness”. As an alternative, we propose a two-step procedure which uses the concept of aggregation over structural properties. It is standard in the theory of collective choice and has recently been applied to the Kuhnian problem of theory choice as well. The idea is to explore how a morally-motivated rational agent may assess different moral theories on the basis of fundamental properties. These properties are ranked on a common scale of qualitative verdicts. This method enables an outside observer to make comparisons across competing moral theories and then conclude to what degree these theories fulfil a set of postulated properties. By doing so, we try to render the reasons more transparent that lie behind different types of credence ascriptions.

Endodontic management of single rooted immature mandibular second molar with a single canal using MTA- A case report

An immature tooth with necrotic pulp and periapical pathology imposes a great difficulty to the endodontists. The case becomes more difficult when the clinician comes across a rare presentation of tooth morphology. Endodontic treatment options for such teeth consist of conventional apexification procedures. This article demonstrates the recent concept of mineral trioxide aggregate (MTA) apical plug technique, for the management of a single rooted immature second molar with a single continuous canal. Keywords: Apexification, apical plug, mineral trioxide aggregate, necrotic teeth with immature apices. Abbreviations: CH-Calcium Hydroxide, MTA-mineral trioxide aggregate.

Beyond state capacity: bureaucratic performance, policy implementation and reform

AbstractThere is a broad consensus that state capacity is central to economic and institutional development. But while the concept originated as a tool for macro-historical and comparative analysis, its success has led the term ‘capacity’ to become a default metaphor for discussing the quality of government bureaucracies. This paper discusses the limitations to conceiving of narrower questions of bureaucratic performance and policy implementation through the lens of the broad, aggregate concept of capacity. Whereas capacity refers to bureaucracies' hypothetical potential, this usually differs from their actual actions due to internal information and incentive problems created by bureaucracies' collective nature, and the constraints and uncertainty imposed by their multiple political principals. Capacity is a convenient shorthand term and is appropriate for some purposes, but it achieves this convenience by abstracting away from the mechanisms that determine bureaucratic performance and policy implementation. To advance the study of bureaucratic quality, researchers should seek to understand the implications of bureaucracies' collective nature, engage with contextual specificity and contingency in policy implementation, and focus measurement and reform efforts more towards actual performance than hypothetical capacity.

Preference relation based collaborative filtering with graph aggregation for group recommender system

Most of the group recommender systems (GRS) apply some aggregation strategy to the ratings given by the group members for generating recommendations. But this can be highly influenced by a few members of the group, which can lead to poor group recommendation. Further, rating based aggregation strategies do not provide efficient ranking of items. Keeping these things in mind, this paper proposes a preference relation (PR) based GRS, that uses matrix factorization (MF) for predicting unknown PRs for group members. The aggregation of preferences is done using a novel virtual user based weight aggregation strategy. The weight aggregation concept is derived from the graph aggregation process. The advantage of this process is that it does not ignore weak preferences and also contributes towards group recommendation. The proposed model is evaluated and compared using standard ranking measures for MovieLens and NetFlix datasets. Experimental results obtained using Top-K recommendation task indicates the superiority of the proposed GRS method over the others. The proposed GRS model provides the best performance when we balance the number of member in a group and the number of recommended items.

A new multiphase and dynamic asphaltene deposition tool (MAD-ADEPT) to predict the deposition of asphaltene particles on tubing wall

As expounded, the precipitation and deposition of asphaltene particles in pipelines has been proved to be the most challenging flow assurance problem due to its unknown and complex behaviors. In this work, a new multicomponent, multiphase and dynamic tool was developed to model the aggregation and deposition of asphaltene particles in a bulk medium. The multiphase and dynamic asphaltene deposition tool, shortened as MAD-ADEPT is, in fact, a modified version of the previously developed ADEPT. The new tool was developed to make the asphaltene deposition and aggregation concepts in oil production wells more predictable. To tackle the complexity of the asphaltene problem, a bespoke algorithm was developed to predict asphaltene precipitation, aggregation and deposition. The algorithm was made up of three main modules, i.e., thermodynamic, preprocessor and integrated time step adaptive modules. In the thermodynamic module, the Peng-Robinson equation of state was used and fine-tuned to estimate the fluid properties of multiphase hydrocarbon systems, while the PC-SAFT equation of state was used in order to obtain the asphaltene precipitation phase envelope (APE). In the preprocessor module, the sensitivity of the system to the reduction of wellbore inner diameter (ID) was examined. In the main module which could dynamically model the asphaltene aggregation and deposition, a non-isothermal multiphase mechanistic model, a convective-diffusive-reactive model and a non-convective volume of fluid model were solved simultaneously with an adaptive time step selection method. The new MAD-ADEPT was utilized to simulate a real field case to predict the asphaltene deposition in different time and space intervals along the production tubing. The results obtained from MAD-ADEPT was validated by those scant field data available in the literature. The results confirmed that the new tool can predict the asphaltene deposition reliably at various operating conditions within a production system. Also, the effects of multiphase flow as well as wellbore configurational parameters were studied on the amount of asphaltene deposition thickness on tubing wall. The accuracy of the results for the case studies, fast rate of convergence and less CPU computation time are the clearest advantages of the new asphaltene deposition dynamic tool over the previously developed ones.

From intelligence to political ideology: Socioeconomic paths

We study the role of socioeconomic status as a mediator of the effect of cognitive ability on ideology based on two large representative database (n = 25,203 and n = 7668). Rather than treating socioeconomic status as an aggregate concept, we examine the different roles of its two components – income and education – in mediating the effect of cognitive ability on ideology. We find that the education-mediated effect of cognitive ability is on liberal ideology is positive whereas the income-mediated effect is negative. The implications of these results for the processes that shape political ideology are discussed.

Forecasting of Sporadic Products: Practical and Theoretical Considerations

This paper focuses on forecasting of products with sporadic demand. The demand for such products is not continuous but diffused seemingly at random, with a large proportion of zero values in the analyzed time series. The sporadic character of demand patterns actually means that the information available on the demand for previous selling periods is patchy, resulting in lower quality of data available. Under such circumstances demand forecasting is a challenging task. We present the results of a case study, where forecasting practice of a pharmaceutical wholesaler firm –we call it Pharma– is analyzed and developed. We present state-of-the-art knowledge related to demand forecasting of sporadic products and test suggestions related to them. We show that these suggestions can only partly be backed. We extend therefore the suggested product classification scheme and recommend using the concept of demand data aggregation. This will reduce sporadicity and result in higher quality forecasting. Aggregation also helps to specify the recommended forecast period, the length of time recommended to calculate the forecast for. The managerial consequences of these suggestions are also discussed, and future research directions are highlighted.

Aggregate as a type of multiplicity of administrative offences: concept and legal formalization

The object of this research is social relations emerged on the basis of administrative-legal norms, which regulate the aggregate of administrative offences. The subject of this research is the scientific literature, normative legal acts and law enforcement practice related to the concept of the aggregate of administrative offences. The author examines approaches of the scientists of various law schools to the concept of aggregate of administrative offences, its development and transformation in time. The author indicated the flaws in the current administrative legislation in part of the absence of legislative consolidation of the concept of “aggregate” of offence, which results in occurrence of a number of problems. The article explores the legal norms that regulate aggregate of offences in administrative legislation of the Russian Federation. A comparative analysis is conducted on consolidation of the aggregate of offences in administrative and criminal law. The scientific novelty is defined by upcoming changes in administrative legislation. This is the reason why improvement of the Code of Administrative Offences of the Russian Federation with regards to regulation of the question of the aggregate of administrative offences gains more relevance. A conclusion is made on the need for establishing in law the unified detailed definition of the “aggregate” of administrative offences, which would allow ensuring more effective application of legal norms. A need is also underlined for the need of legislative consolidation of such feature of offences that are a part of the aggregate as “absence of bringing to accountability for earlier commission of an unlawful act”.  

Prediction of the elastic modulus of LLDPE/CNT nanocomposites by analytical modeling and finite element analysis

In the present work, the effective elastic modulus of carbon nanotube (CNT) polymer nanocomposites has been evaluated through micromechanics modeling and finite element analysis (FEA). In the micromechanics model, the inherent trend of CNTs to aggregate is taken into account, considering a two-phase material system, that of the matrix with the finely dispersed CNTs and the inclusions, involving agglomerated CNTs and matrix material. A new model is proposed for the elastic stiffness evaluation of the two phases and the elastic stiffness of the nanocomposite, introducing two aggregation parameters. It was proved that this analysis was rational and operative. The same aggregation concept has been investigated using FEA, and a comparative study between the two procedures was performed. Furthermore, an additional treatment with FEA was performed, based on a three-phase model, including the matrix, the CNTs and the interphase. A parametric analysis has been executed and a comparison with experimental data of linear low density polyethylene (LLDPE)/CNT nanocomposites has been performed.

Data-Driven Personas for Enhanced User Understanding: Combining Empathy with Rationality for Better Insights to Analytics

Persona is a common human-computer interaction technique for increasing stakeholders’ understanding of audiences, customers, or users. Applied in many domains, such as e-commerce, health, marketing, software development, and system design, personas have remained relatively unchanged for several decades. However, with the increasing popularity of digital user data and data science algorithms, there are new opportunities to progressively shift personas from general representations of user segments to precise interactive tools for decision-making. In this vision, the persona profile functions as an interface to a fully functional analytics system. With this research, we conceptually investigate how data-driven personas can be leveraged as analytics tools for understanding users. We present a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes. We apply this framework for an analysis of digital marketing use cases to demonstrate how data-driven personas can be leveraged in practical situations. We then present a functional overview of an actual data-driven persona system that relies on the concept of data aggregation in which the fundamental question defines the unit of analysis for decision-making. The system provides several functionalities for stakeholders within organizations to address this question.

Investigations on Scheduling Algorithms in LTE-Advanced Networks with Carrier Aggregation.

Third generation partnership project (3GPP) long-term evolution advanced (LTE-A) is the fastest growing technology, which supports variety of applications by using effective and efficient radio resource management (RRM) procedure. With carrier aggregation (CA) concepts included in LTE-advanced protocol, the complexity of the RRM and scheduling of data increases. In this paper, basic LTE-A concepts and a study of different methods of component carrier allocation is studied and performance evaluation is carried out. From the simulation results, it can be inferred that static methods of component carrier allocation is simple but it could not be able to satisfy various important scheduler metric to provide a better QoS to UE. The random method though for some cases it seen better but it is not reliable as the outputs are also random. The dynamic methods of component carrier allocation have been able to provide better scheduler performance metric compared to static and random methods. More over different dynamic approaches can be also combined to improve the overall system efficiency.

Collective behaviors mediated multifunctional black sand aggregate towards environmentally adaptive solar-to-thermal purified water harvesting

As a renewable and efficient technology, interfacial solar heating has emerged as a new and promising avenue for treating undrinkable water to clean one via a variety of well-designed solar absorbers. However, it is still urgent to develop an accessible material system in a simple, low-cost and effective way to easily tackle water shortage. Inspired by natural sand with highly important role in purifying water during the natural recycling, in this work, we demonstrate a concept of an all-round black sand aggregate with specific collective behaviors for environmentally adaptable clean water collection from seawater, polluted water and even atmospheric moisture. To endow the raw sand desirable photo-thermal features, polydopamine and Cl−-doped polypyyrole are successively modified onto the sand surface for a stable structure. Owing to the specific aggregative structure of the black sands, a self-channelled device combined adjustable 2D/3D solar-driven evaporation can be readily achieved, and yield a high evaporation performance (1.43 kg m−2 h−1) in comparison with other reported naturally derived materials. Notably, the black sand aggregate could handle with oil-contained polluted water (P-WA) to guarantee high-efficient and sustainable water purification. Furthermore, even if in some draughty areas or deserts, the collective black sands could also extract water from air by absorbing atmospheric moisture and sequentially realizing an in situ water evaporation by heat location. The successful demonstration of multifunctional black sand aggregate may provide a new avenue for purified water collection under changeable environments.

The curse of indecomposable aggregates for big data exploratory analysis with a case for frequent pattern cubes

Exploratory big data analytics requires the interaction delays to be kept at minimum. Although data cubes help this goal by pre-calculating the measures of interest, some aggregations are not decomposable and require runtime scans through the cube data which will cause the response time to exceed the real-time interaction limits. One of such costly aggregations is the calculation of the frequent patterns over data cube partitions. The existing inefficient merge-and-count approach used for solving this problem is not feasible in the world of big data. In this paper, an efficient approach is proposed for mining frequent patterns from cube data accompanied by a formal overview of decomposable and indecomposable data aggregates. A new concept of semi-decomposable aggregates is introduced that sits in between these two extremes. With the case of frequent pattern mining problem, we show that sometimes indecomposable aggregates are in fact semi-decomposable and exploratory data analysis can still be realized for them. The proposed FPCubes algorithm shows promising experimental results for aggregating frequent patterns which can help exploratory frequent itemset analysis on real-world multidimensional big datasets.

Liquefied Microcapsules as Dual-Microcarriers for 3D+3D Bottom-Up Tissue Engineering.

Cell encapsulation systems must ensure the diffusion of molecules to avoid the formation of necrotic cores. The architectural design of hydrogels, the gold standard tissue engineering strategy, is thus limited to a microsize range. To overcome such a limitation, liquefied microcapsules encapsulating cells and microparticles are proposed. Microcapsules with controlled sizes with average diameters of 608.5 ± 122.3 µm are produced at high rates by electrohydrodynamic atomization, and arginyl-glycyl-aspartic acid (RGD) domains are introduced in the multilayered membrane. While cells and microparticles interact toward the production of confined microaggregates, on the outside cell-mediated macroaggregates are formed due to the aggregation of microcapsules. The concept of simultaneous aggregation is herein termed as 3D+3D bottom-up tissue engineering. Microcapsules are cultured alone (microcapsule1 ) or on top of 2D cell beds composed of human umbilical vein endothelial cells (HUVECs) alone (microcapsule2 ) or cocultured with fibroblasts (microcapsule3 ). Microcapsules are able to support cell encapsulation shown by LiveDead, 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulphofenyl)-2H-tetrazolium (MTS), and dsDNA assays. Only microcapsule3 are able to form macroaggregates, as shown by F-actin immunofluorescence. The bioactive 3D system also presented alkaline phosphatase activity, thus allowing osteogenic differentiation. Upon implantation using the chick chorioallontoic membrane (CAM) model, microcapsules recruit a similar number of vessels with alike geometric parameters in comparison with CAMs supplemented with basic fibroblast growth factor (bFGF).