Reform of the Irrigation Sector and Creation of Functional and Sustainable Irrigation Water Users Associations (AUEI) in Niger: Capitalization of the Experience of the Konni AHA

During the 1980s, as part of a policy of liberalization, following budgetary cuts linked to the implementation of structural adjustment programs, management responsibilities for AHAs were transferred from ONAHA to cooperatives concerned. Due to lack of financial resources, but also because of poor management, everywhere in Niger we are witnessing an accelerated deterioration of the irrigation infrastructure of hydro-agricultural developments. Institutional studies carried out on this situation led the State of Niger to initiate a reform of the governance of hydro-agricultural developments, by streng-thening the status of ONAHA, by creating an Association of Irrigation Water Users (AUEI) and by restructuring the old cooperatives. Indeed, this research aims to analyze the creation of functional and sustainable Irrigation Water User Associations (AUEI) in Niger in a context of reform of the irrigation sector, and based on the experience of the Konni AHA. It is based on a methodological approach which takes into account documentary research and the collection of data from 115 farmers, selected by reasoned choice and directly concerned by the management of the irrigated area. The data collected was analyzed and the results were analyzed using the systemic approach and the diagnostic process. The results show that the main mission of the AUEI is to ensure better management of water, hydraulic equipment and infrastructure on the hydro-agricultural developments of Konni. The creation of the Konni AUEI was possible thanks to massive support from the populations and authorities in the implementation process. After its establishment, the AUEI experienced a certain lethargy for some time due to the rehabilitation work of the AHA but currently it is functional and operational in terms of associative life and governance. Thus, the constraints linked to the legal system, the delay in the completion of the work, the uncertainties of access to irrigation water but also the problems linked to the change in mentality of certain ONAHA agents constitute the challenges that must be resolved in the short term for the operationalization of the Konni AUEI.

Spectrum-Efficient User Association in Caching Enabled Dense Small Cell Network

In this paper,we reveal the fundamental limitation of network densification on the performance of caching enabled small cell network(CSCN)under two typical user association rules,namely,contentand distance-based rules.It indicates that immoderately caching content would significantly change the interference distribution in CSCN,which may degrade the network area spectral efficiency(ASE).Meanwhile,it is shown that content-based rule outperforms the distance-based rule in terms of network ASE only when small cell base stations(BSs)are sparsely deployed with low decoding thresholds.Moreover,it is proved that network ASE under distance-based user association serves as the upper bound of that under content-based rule in dense BS regime.To enable more spectrum-efficient user association in dense CSCN,we further optimize network ASE by designing a probabilistic content retrieving strategy based on distance-based rule.With the optimized retrieving probability,network ASE could be substantially enhanced and even increase with the growing BS density in dense BS regime.

Joint User Association and Caching Placement for Cache-Enabling UAV Networks

Cache-enabling unmanned aerial vehicles(UAVs)are considered for storing popular contents and providing downlink data offloading in cellular networks.In this context,we formulate a joint optimization problem of user association,caching placement,and backhaul bandwidth allocation for minimizing content acquisition delay with consideration of UAVs’energy constraint.We decompose the formulated problem into two subproblems:i)user association and caching placement and ii)backhaul bandwidth allocation.We first obtain the optimal bandwidth allocation with given user association and caching placement by the Lagrangian multiplier approach.After that,embedding the backhaul bandwidth allocation algorithm,we solve the user association and caching placement problem by a threedimensional(3D)matching method.Then we decompose it into two two-dimensional(2D)matching problems and develop low-complexity algorithms.The proposed scheme converges and exhibits a low computational complexity.Simulation results demonstrate that the proposed cache-enabling UAV framework outperforms the conventional UAV-assisted cellular networks in terms of content acquisition delay and the proposed scheme achieves significantly lower content acquisition delay compared with other two benchmark schemes.

Association Rule Analysis-Based Identification of Influential Users in the Social Media

The exchange of information is an innate and natural process that assist in content dispersal.Social networking sites emerge to enrich their users by providing the facility for sharing information and social interaction.The extensive adoption of social networking sites also resulted in user content generation.There are diverse research areas explored by the researchers to investigate the influence of social media on users and confirmed that social media sites have a significant impact on markets,politics and social life.Facebook is extensively used platform to share information,thoughts and opinions through posts and comments.The identification of influential users on the social web has grown as hot research field because of vast applications in diverse areas for instance political campaigns marketing,e-commerce,commercial and,etc.Prior research studies either uses linguistic content or graph-based representation of social network for the detection of influential users.In this article,we incorporate association rule mining algorithms to identify the top influential users through frequent patterns.The association rules have been computed using the standard evaluation measures such as support,confidence,lift,and conviction.To verify the results,we also involve conventional metrics for example accuracy,precision,recall and F1-measure according to the association rules perspective.The detailed experiments are carried out using the benchmark College-Msg dataset extracted by Facebook.The obtained results validate the quality and visibility of the proposed approach.The outcome of propose model verify that the association rule mining is able to generate rules to identify the temporal influential users on Facebook who are consistent on regular basis.The preparation of rule set help to create knowledge-based systems which are efficient and widely used in recent era for decision making to solve real-world problems.

Uplink Performance Analysis in Multi-Tier Heterogeneous Cellular Networks with Power Control and Biased User Association

A K-tier uplink heterogeneous cellular network is modelled and analysed by accounting for both truncated channel inversion power control and biased user association. Each user has a maximum transmit power constraint and transmits data when it has sufficient transmit power to perform channel inversion. With biased user association, each user is associated with a base station(BS) that provides the maximum received power weighted by a bias factor, but not their nearest BS. Stochastic geometry is used to evaluate the performances of the proposed system model in terms of the outage probability and ergodic rate for each tier as functions of the biased and power control parameters. Simulations validate our analytical derivations. Numerical results show that there exists a trade-off introduced by the power cut-off threshold and the maximum user transmit power constraint. When the maximum user transmit power becomes a binding constraint, the overall performance is independent of BS densities. In addition, we have shown that it is beneficial for the outage and rate performances by optimizing different network parameters such as the power cut-off threshold as well as the biased factors.

User Association in Heterogeneous Network with Dual Connectivity and Constrained Backhaul

A novel user association model for heterogeneous network(Het Net) with dual connectivity(DC) and constrained backhaul is proposed in this paper, where not only the best combination of serving macro cell and small cell for each user to associate is selected but also the optimal traffi c split between the macro cell and small cell is determined to enhance both radio resource effi ciency and backhaul capacity utilization. To solve this optimization problem, an intuitive algorithm based on iteratively solving two sub-problems is proposed. One sub-problem is a binary integer programming problem and a corresponding greedy algorithm is proposed, while the other sub-problem is a simple linear programming problem and can be easily solved. Numerical results show that the proposed model and algorithm can achieve better radio resource effi ciency and backhaul capacity utilization compared with user association in Het Net without DC, which validate the capacity enhancement potentials of radio resource coordination in Het Net with DC.

Joint User Association and Resource Allocation for Self-Backhaul Ultra-Dense Networks

In order to meet the exponentially increasing demand on mobile data traffic, self-backhaul ultra-dense networks(UDNs) combined with millimeter wave(mm Wave) communications are expected to provide high spatial multiplexing gain and wide bandwidths for multi-gigabit peak data rates. In selfbackhaul UDNs, how to make the radio access rates of small cells match their backhaul rates by user association and how to dynamically allocate bandwidth for the access links and backhaul links to balance two-hop link resources are two key problems on improving the overall throughputs. Based on this, a joint scheme of user association and resource allocation is proposed in self-backhaul ultra-dense networks. Because of the combinatorial and nonconvex features of the original optimization problem, it has been divided into two subproblems. Firstly, to make the radio access rates of small base stations match their backhaul rates and maximize sum access rates per Hz of all small cells, a proportional constraint is introduced, and immune optimization algorithm(IOA) is adopted to optimize the association indicator variables and the boresight angles of between users and base stations. Then, the optimal backhaul and access bandwidths are calculated by differentiating the general expression of overall throughput. Simulation results indicatethat the proposed scheme increases the overall throughputs significantly compared to the traditional minimum-distance based association scheme.

User Association and Power Allocation for UAV-Assisted Networks: A Distributed Reinforcement Learning Approach

Unmanned aerial vehicles(UAVs)can be employed as aerial base stations(BSs)due to their high mobility and flexible deployment.This paper focuses on a UAV-assisted wireless network,where users can be scheduled to get access to either an aerial BS or a terrestrial BS for uplink transmission.In contrast to state-of-the-art designs focusing on the instantaneous cost of the network,this paper aims at minimizing the long-term average transmit power consumed by the users by dynamically optimizing user association and power allocation in each time slot.Such a joint user association scheduling and power allocation problem can be formulated as a Markov decision process(MDP).Unfortunately,solving such an MDP problem with the conventional relative value iteration(RVI)can suffer from the curses of dimensionality,in the presence of a large number of users.As a countermeasure,we propose a distributed RVI algorithm to reduce the dimension of the MDP problem,such that the original problem can be decoupled into multiple solvable small-scale MDP problems.Simulation results reveal that the proposed algorithm can yield lower longterm average transmit power consumption than both the conventional RVI algorithm and a baseline algorithm with myopic policies.

Two-Timescale Online Learning of Joint User Association and Resource Scheduling in Dynamic Mobile Edge Computing

For the mobile edge computing network consisting of multiple base stations and resourceconstrained user devices,network cost in terms of energy and delay will incur during task offloading from the user to the edge server.With the limitations imposed on transmission capacity,computing resource,and connection capacity,the per-slot online learning algorithm is first proposed to minimize the time-averaged network cost.In particular,by leveraging the theories of stochastic gradient descent and minimum cost maximum flow,the user association is jointly optimized with resource scheduling in each time slot.The theoretical analysis proves that the proposed approach can achieve asymptotic optimality without any prior knowledge of the network environment.Moreover,to alleviate the high network overhead incurred during user handover and task migration,a two-timescale optimization approach is proposed to avoid frequent changes in user association.With user association executed on a large timescale and the resource scheduling decided on the single time slot,the asymptotic optimality is preserved.Simulation results verify the effectiveness of the proposed online learning algorithms.

Resource Allocation and User Association for HTTP Adaptive Streaming in Heterogeneous Cellular Networks with Small Cells

Video streaming,especially hypertext transfer protocol based(HTTP) adaptive streaming(HAS) of video,has been expected to be a dominant application over mobile networks in the near future,which brings huge challenge for the mobile networks.Although some works have been done for video streaming delivery in heterogeneous cellular networks,most of them focus on the video streaming scheduling or the caching strategy design.The problem of joint user association and rate allocation to maximize the system utility while satisfying the requirement of the quality of experience of users is largely ignored.In this paper,the problem of joint user association and rate allocation for HTTP adaptive streaming in heterogeneous cellular networks is studied,we model the optimization problem as a mixed integer programming problem.And to reduce the computational complexity,an optimal rate allocation using the Lagrangian dual method under the assumption of knowing user association for BSs is first solved.Then we use the many-to-one matching model to analyze the user association problem,and the joint user association and rate allocation based on the distributed greedy matching algorithm is proposed.Finally,extensive simulation results are illustrated to demonstrate the performance of the proposed scheme.

User Association and Wireless Backhaul Bandwidth Allocation for 5G Heterogeneous Networks in the Millimeter-Wave Band

The user association and wireless backhaul bandwidth allocation for a two-tier heterogeneous network （HetNet） in the mil- limeter wave （mmWave） band is proposed in this article. The two-tier HetNet is built up with a macro base station （MBS） and several small cell SBSs, where the MBS is assumed to be equipped with large-scale antenna arrays but the SBSs only have single-antenna capa- bility and they rely on the wireless link to the MBS for backhaul. The sum of logarithmic user rate, which is established according to the result of multi-user Multiple Input Mul- tiple Output （MIMO） downlink employing Zero-Force Beamforming （ZFBF）, is chosen as the network utility for the objective func- tion. And a distributed optimization algorithm based on primal and dual decomposition is used to jointly optimize the user association variable xj,z and the wireless backhaul band- width factor α. Simulation results reveal that the distributed optimization algorithm jointly optimizing two variables outperforms the con- ventional SINR-based user association strate- gies.

Delay-Based User Association in Heterogeneous Networks with Backhaul

The Internet of things(IoT) as an important application of future communication networks puts a high premium on delay issues. Thus when Io T applications meet heterogeneous networks(HetNets) where macro cells are overlaid with small cells, some traditional problems need rethinking. In this paper, we investigate the delay-addressed association problem in two-tier Het Nets considering different backhaul technologies. Specifically, millimeter wave and fiber links are used to provide high-capacity backhaul for small cells. We first formulate the user association problem to minimize the total delay which depends on the probability of successful transmission, the number of user terminals(UTs), and the number of base stations(BSs). And then two algorithms for active mode and mixed mode are proposed to minimize the network delay. Simulation results show that algorithms based on mutual selection between UTs and BSs have better performance than those based on distance. And algorithms for mixed modes have less delay than those for active mode when the number of BSs is large enough, compared to the number of UTs.

A Distributed User Association and Resource Allocation Method in Cache-Enabled Small Cell Networks

Cache-enabled small cell networks have been regarded as a promising approach for network operators to cope with the explosive data traffic growth in future 5 G networks. However, the user association and resource allocation mechanism has not been thoroughly studied under given content placement situation. In this paper, we formulate the joint optimization problem of user association and resource allocation as a mixed integer nonlinear programming(MINLP) problem aiming at deriving a balance between the total utility of data rates and the total data rates retrieved from caches. To solve this problem, we propose a distributed relaxing-rounding method. Simulation results demonstrate that the distributed relaxing-rounding method outperforms traditional max-SINR method and range-expansion method in terms of both total utility of data rates and total data rates retrieved from caches in practical scenarios. In addition, effects of storage and backhaul capacities on the performance are also studied.

Research on Association Analysis Technology of Network User Accounts

As large numbers of user information on various network services are becoming valuable resources for social computing,how to associate user information scattered in a variety of services turns to one of the key issues of user identity mining.First this paper outlines the difficulties of dealing with account association,then describes the basis of account association method.After that,this paper sums up account association methods mainly from five aspects which are user naming conventions,user profiles,user writing styles,user online behavior,and user community relationship.Finally,this paper points out the development direction and prospects of account association.

A study of the properties of hydrophobically associating water-soluble polymers used in drilling fluids

Hydrophobically associating water-soluble polymers (HPAP) have been synthesized from acrylamide(AM), acrylate (AA), 2-acrylamido-2-methyl propane sulfonic acid (AMPS) and hydrophobic monomer (AP) in aqueous solution by radical polymerization. New polymer drilling fluids are made up of HPAP, which is used as viscosifiers and encapsulation agents. Properties of this system are reported in this paper. Results indicate that this system has a high value of yield point to plastic viscosity (YP/PV≥0.7), high viscosity at a low-shear rate (LSRV≥30000mPa·s), excellent shear thinning behavior, good solid-carrying behavior, resistance to shear, good thermal stability (as high as 140℃) and salt resistance. The system has excellent behavior in high-density solution of NaCl and in calcium and magnesium rich saline solutions. Hence, HPAP also can be used in saltwater polymer drilling fluids.

Visualizing Association Rules Using Linked Matrix,Graph, and Detail Views

Although association rule mining is an important pattern recognition and data analysis technique, extracting and finding significant rules from a large collection has always been challenging. The ability of information visualization to enable users to gain an understanding of high dimensional and large-scale data can play a major role in the exploration, identification, and interpretation of association rules. In this paper, we propose a method that provides multiple views of the association rules, linked together through a filtering mechanism. A visual inspection of the entire association rule set is enabled within a matrix view. Items of interest can be selected, resulting in their corresponding association rules being shown in a graph view. At any time, individual rules can be selected in either view, resulting in their information being shown in the detail view. The fundamental premise in this work is that by providing such a visual and interactive representation of the association rules, users will be able to find important rules quickly and easily, even as the number of rules that must be inspected becomes large. A user evaluation was conducted which validates this premise.

Grey associated analysis of the underground water quality effected by the leaching water of dumping area or hillock of coal mine

The underground water has been contaminated seriously by the leaching water of dumping area or hillock. To determine the pollution limits of underground water, author took samples in the study area, analyzed samples for water quality, assessed the water quality of each monitoring point by the grey associated analysis method, and gave out the classifications of the underground water quality of the study area. Comparing with fuzzy comprehensive appraisal method, it is demonstrated that grey associated analysis method is applied easily, because of its clear concept, simple and convenient calculation and excellently operation.

Application of Grey Associative Analysis to the Assessment of Regional Water Security

The assessment of water security is an important content in the security management of water resources due to the fact that the state of water security directly affects both the sustainable development of regional economy and the improvement on the living quality of mankind. Grey associative analysis is introduced and applied to assessment of water security on the basis of grey characteristics of the assessment index system of water security. As a case study shows, grey associative analysis is used for evaluating water security of some provinces in China, and the satisfactory assessment results are obtained. The sequence of provinces in China with regard to water security from good to poor is obtained and, moreover, the water security level of each region is also confirmed. The results obtained accord with the actual state of each region. They are of practical significance and can be used to guide the management of regional water security and a sustainable development of the economy therein. At the same time, the results demonstrate that grey associative analysis provides a new method for assessing water

Bacterial Communities Associated with An Occurrence of Colored Water in An Urban Drinking Water Distribution System

This study aimed to investigate bacterial community in an urban drinking water distribution system （DWDS） during an occurrence of colored water. Variation in the bacterial community diversity and structure was observed among the different waters, with the predominance of Proteobacteria. While Verrucomicrobia was also a major phylum group in colored water. Limnobacter was the major genus group in colored water, but Undibacterium predominated in normal tap water. The coexistence of Limnobacter as well as Sediminibacterium and Aquobocterium might contribute to the formation of colored water.

Application of Association Rule Mining Theory in Sina Weibo

A user profile contains information about a user. A substantial effort has been made so as to understand users’ behavior through analyzing their profile data. Online social networks provide an enormous amount of such information for researchers. Sina Weibo, a Twitter-like microblogging platform, has achieved a great success in China although studies on it are still in an initial state. This paper aims to explore the relationships among different profile attributes in Sina Weibo. We use the techniques of association rule mining to identify the dependency among the attributes and we found that if a user’s posts are welcomed, he or she is more likely to have a large number of followers. Our results demonstrate how the relationships among the profile attributes are affected by a user’s verified type. We also put some efforts on data transformation and analyze the influence of the statistical properties of the data distribution on data discretization.