New reactive power flow tracing and loss allocation algorithms for[taliem.ir]

New reactive power flow tracing and loss allocation algorithms for power grids using matrix calculation

A novel simple method is suggested in this paper to evaluate the contributions of the sources (including the generators and branches’ charging capacitances) or the loads to the branches’ reactive flows and losses separately as well as to calculate the sources’ shares in providing the loads’ reactive powers. In the method, the study system is first converted to the system, each branch of which only has reactive loss, using a new technique for modeling the generating branches based on the AC load flow results. The properties of two new matrices (i.e. injection-bus and absorption-bus matrices), which are constituted for theobtained system, are then used to derive three other matrices. These matrices, which express reactivepower productions of the sources in terms of reactive power consumptions of the demands (viz. the loads and branches’ losses) and vice versa, contain the intended contributory factors. Three-bus system is applied to demonstrate the computing process of the method whereas several IEEE systems are used to show its capability to implement on the transmission systems with arbitrary topologies and sizes Some advantages of the method compared to the earlier methods are also illustrated.
Fuzzy based damping controller for TCSC using local measurements[taliem.ir]

Fuzzy based damping controller for TCSC using local measurements to enhance transient stability of power systems

This paper proposes a local fuzzy based damping controller (LFDC) for thyristor controlled series capacitor (TCSC) to improve transient stability of power systems. In order to implement the proposed scheme, detailed model of TCSC, based on actual behavior of thyristor valves, is adopted. The LFDC uses the frequency at the TCSC bus as a local feedback signal, to control the firing angle. The parameters of fuzzy controller are tuned using an off-line method through chaotic optimization algorithm (COA). To verify the proposed LFDC, numerical simulations are carried out in Matlab/Simpower toolbox for the following case studies: two-area two-machine (TATM), WSCC three-machine nine-bus and Kundur’s two-area fourmachine (TAFM) systems under various faults types. In this regard, to more evaluate the effectiveness of the proposed method, the simulation results are compared with the wide-area fuzzy based damping controller (WFDC). Moreover, the transient behavior of the detailed and phasor models of the TCSC is discussed in the TATM power system. The simulation results confirm that the proposed LFDC is an efficient tool for transient stability improvement since it utilizes only local signals, which are easily available.
An improved PSO-based charging strategy of electric vehicles[taliem.ir]

An improved PSO-based charging strategy of electric vehicles in electrical distribution grid

Driven by the desire to reduce environmental impacts and achieve energy independence, electric vehicles (EVs) are poised to receive mass acceptance from the general public. However, simultaneously connecting to electric distribution grid and charging with large number of EVs bring the necessity of optimizing the charging and discharging behaviors of EVs, due to the security and economy issue of the grid operation. To address this issue, we propose a novel EV charging model in this paper. The model concerns with following aspects, including optimal power flow (OPF), statistic characteristics of EVs, EV owners’ degree of satisfaction (DoS), and the power grid cost. An improved particle swarm optimization (PSO) algorithmis proposed for the model optimization. To evaluate our proposed optimal EV charging strategy, a 10-bus power distribution system simulation is performed for performance investigation. Simulation resultsshow that the proposed strategy can reduce the operational cost of the power grid considerately, while meeting the EV owner’s driving requirement. Also, better performance on the global search capability and optimal result of the improved particle swarm optimization algorithm is verified.
Design and development of logistics workflow systems for demand[taliem.ir]

Design and development of logistics workflow systems for demand management with RFID

This paper discusses demand and supply chain management and examines how artificial intelligence techniques and RFID technology can enhance the responsiveness of the logistics workflow. This proposed system is expected to have a significant impact on the performance of logistics networks by virtue of its capabilities to adapt unexpected supply and demand changes in the volatile marketplace with the unique feature of responsiveness with the advanced technology, Radio Frequency Identification (RFID). Recent studies have found that RFID and artificial intelligence techniques drive the development of total solution in logistics industry. Apart from tracking the movement of the goods, RFID is able to play an important role to reflect the inventory level of various distribution areas. In today’s globalized industrial environment, the physical logistics operations and the associated flow of information are the essential elements for companies to realize an efficient logistics workflow scenario. Basically, a flexible logistics workflow, which is characterized by its fast responsiveness in dealing with customer requirements through the integration of various value chain activities, is fundamental to leverage business performance of enterprises. The significance of this research is the demonstration of the synergy of using a combination of advanced technologies to form an integrated system that helps achieve lean and agile logistics workflow .
Distributed Key Management in Dynamic Outsourced Databases a Trie-Based[taliem.ir]

Distributed Key Management in Dynamic Outsourced Databases: a Trie-Based Approach

The decision to outsource databases is strategic in many organizations due to the increasing costs of internally managing large volumes of information. The sensitive nature ofthis information raises the need for powerful mechanisms to protect it against unauthorized disclosure. Centralized encryption to access control at the data owner level has been proposed as one way of handling this issue. However, its prohibitive costs renders it impractical and inflexible. A distributed cryptographic approach has been suggested as a promising alternative, where keys are distributed to users on the basis of their assigned privileges. But in this case, key management becomes problematic in the face of frequent database updates and remains an open issue. In this paper, we present a novel approach based on Binary Tries1. By exploiting the intrinsic properties of these data structures, key management complexity, and thus its cost, is significantly reduced. Changes to the Binary Triestructure remain limited in the face of frequent updates. Preliminary experimental analysis demonstrates the validity and the effectiveness of our approach.
An Economic-based Resource Management and[taliem.ir]

An Economic-based Resource Management and Scheduling for Grid Computing Applications

Resource management and scheduling plays a crucial role in achieving high utilization of resources in grid computingenvironments. Due to heterogeneity of resources, scheduling an application is significantly complicated and challenging task in grid system. Most of the researches in this area are mainly focused on to improve the performance of the grid system. There were some allocation model has been proposed based on divisible load theory with different type of workloads and a single originating processor. In this paper we introduce a new resource allocation model with multiple load originating processors as an economic model. Solutions for an optimal allocation of fraction of loads to nodes obtained to minimize the cost of the grid users via linear programming approach. It is found that the resource allocation model can efficiently and effectively allocate workloads to proper resources. Experimental results showed that the proposed model obtained the better solution in terms of cost and time.
NoSQL Systems for Big Data Management[taliem.ir]

NoSQL Systems for Big Data Management

The advent of Big Data created a need for out-of-the-box horizontal scalability for data management systems. This ushered in an array of choices for Big Data management under the umbrella term NoSQL. In this paper, we provide a taxonomy and unified perspective on NoSQL systems. Using this perspective, we compare and contrast various NoSQL systems using multiple facets including system architecture, data model, query language, client API, scalability, and availability. We group current NoSQL systems into seven broad categories: Key-Value,Table-type/Column, Document, Graph, Native XML, Native Object, and Hybrid databases. We also describe application scenarios for each category to help the reader in choosing an appropriate NoSQL system for a given application. We conclude the paper by indicating future research directions.
System of Systems Management A Network Management[taliem.ir]

System of Systems Management: A Network Management Approach

This paper presents a method of applying the International Organization for Standardization (ISO) Network Management Model to the Boardman-Sauser Distinguishing Characteristics ofSystem ofSystems (SoS). The ISO model defines five conceptual areas for managingnetworks: Performance, Configuration, Accounting, Fault, and Security. This model is both a standard and primary means for understanding the major functions of network management. The Boardman-Sauser characteristics of . Autonomy, Belonging, Connectivity, Diversity, and Emergence are used to recognize a SoS. These characteristics represent the fundamental "building blocks" ofSoS management. In this paper the five functional areas of network management are analyzed and mapped to each of the five "building blocks" of SoS management to create a SoS Operational Management Matrix (SoSOMM). The matrix will serve as a foundation for extracting network management 'best practices' into the realm of SoS management. The proposed method will increase the overall effectiveness ofSoS management practices.
Facial Action Unit Detection 3D versus 2D Modality[taliem.ir]

Facial Action Unit Detection: 3D versus 2D Modality

In human facial behavioral analysis, Action Unit (AU) coding is a powerful instrument to cope with the diversity of facial expressions. Almost all of the work in the literature for facial action recognition is based on 2D camera images. Given the performance limitations in AU detection with 2D data, 3D facial surface information appears as a viable alternative. 3D systems capture true facial surface data and are less disturbed by illumination and head pose. In this paper we extensively compare the use of 3D modality vis-a-vis 2D imaging modality for AU recognition. Surface ` data is converted into curvature data and mapped into 2D so that both modalities can be compared on a fair ground. Since the approach is totally data-driven, possible bias due to the design is avoided. Our experiments cover 25 AUs and is based on the comparison of Receiver Operating Characteristic (ROC) curves. We demonstrate that in general 3D data performs better, especially for lower face AUs. Furthermore it is more robust in detecting low intensity AUs. Also, we show that generative and discriminative classifiers perform on a par with 3D data. Finally, we evaluate fusion of the two modalities. The highest detection rate was achieved by fusion, which is 97.1 area under the ROC curve. This score was 95.4 for 3D and 93.5 for 2D modality.
Computational Models for Social Network Analysis[taliem.ir]

Computational Models for Social Network Analysis: A Brief Survey

With the exponential growth of online social network services such as Facebook and Twitter, social networks and social medias become more and more important, directly influencing politics, economics, and our daily life. Mining big social networks aims to collect and analyze web-scale social data to reveal patterns of individual and group behaviors. It is an inherently interdisciplinary academic field which emerged from sociology, psychology, statistics, and graph theory. In this article, I briefly survey recent progress on social network mining with an emphasis on understanding the interactions among users in the large dynamic social networks. I will start with some basic knowledge for social network analysis, including methodologies and tools for macro-level, meso-level and microlevel social network analysis. Then I will give an overall roadmap of social network mining. After that, I will describe methodologies for modeling user behavior including state-of-the-art methods forlearning user profiles, and introduce recent progress on modeling dynamics of user behaviors using deep learning. Then I will present models and algorithms for quantitative analysis on social interactions including homophily and social influence.Finally, I will introduce network structure model including social group formation, and network topology generation. We will introduce recent developed network embedding algorithms for modeling social networks with the embedding techniques. Finally, I will use several concrete examples from Alibaba, the largest online shopping website in the world, and WeChat, the largest social messaging service in China, to explain how online social networks influence our offline world.