An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs

This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.

A novel algorithm based on honey bee mating optimization for distribution harmonic state estimation including distributed generators

This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics by minimizing the error between the measured values from phasor measurement units (PMUs) and the values computed from the estimated parameters during the estimation process. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).

Amplified activism : transmedia storytelling and social change

The avenues through which communities and community organisations raise awareness about the issues they face and how they agitate for change have developed rapidly in the past ten years; and digital technology has provided community activists with the means to quickly create and widely disseminate stories. Perhaps the most influential and wide reaching of recent innovations in storytelling has been transmedia storytelling. This article explores a new breed of projects that utilise recognisable conventions of transmedia storytelling and borrow elements from other forms of storytelling that predate transmedia, such as digital storytelling and documentary film making. In addition to being hybrid in form these projects are independent and solely focused on raising awareness about particular social issues or telling the stories of marginalized groups, who otherwise do not have a voice in the public sphere.

Imagining social justice

This paper examines how creativity and the arts can assist teachers who teach from a social justice perspective, and how knowledge built through meaningful experiences of difference can make a difference. Just as imagining is central to visual arts practice, so too the capacity to imagine is a necessity for social justice. The authors ask what art can do, and how art can work, to bring about greater understandings and practices around social justice and the early years. A ‘recognitive justice’ (Fraser, 1997, 2000; Cazden, 2012) requires the capacity to be sensitive to the multiple voices that need to be heard, and the ability to imagine how lives might be lived differently. The arts can provide powerful means for thinking social justice, and the experiences described in this paper can have application in addressing social justice in the professional preparation of prospective teachers. Three teacher educators who teach from a social justice perspective apply a collective biography methodology to their stories of art activity. Data were collected from three sites: transcripts, notes and digital images from a salon evening; ethnographic observations, field notes and artefacts from a school classroom; and a/r/tographic data generated in a university art classroom. Data were analysed using Foucault and the conceptual work of other post-structuralist philosophies, to explore how aesthetic and creative artistic activity could excite imaginations and open up multiple possibilities for richer forms of educational outcomes – for teacher educators, their students, and ultimately for young children.

Distribution feeder reconfiguration for loss minimization based on modified honey bee mating optimization algorithm

This paper presents an efficient algorithm for multi-objective distribution feeder reconfiguration based on Modified Honey Bee Mating Optimization (MHBMO) approach. The main objective of the Distribution feeder reconfiguration (DFR) is to minimize the real power loss, deviation of the nodes’ voltage. Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective. So the metahuristic algorithm has been applied to this problem. This paper describes the full algorithm to Objective functions paid, The results of simulations on a 32 bus distribution system is given and shown high accuracy and optimize the proposed algorithm in power loss minimization.

Optimization of an integrated model for automatic reduction and expansion of long queries

A long query provides more useful hints for searching relevant documents, but it is likely to introduce noise which affects retrieval performance. In order to smooth such adverse effect, it is important to reduce noisy terms, introduce and boost additional relevant terms. This paper presents a comprehensive framework, called Aspect Hidden Markov Model (AHMM), which integrates query reduction and expansion, for retrieval with long queries. It optimizes the probability distribution of query terms by utilizing intra-query term dependencies as well as the relationships between query terms and words observed in relevance feedback documents. Empirical evaluation on three large-scale TREC collections demonstrates that our approach, which is automatic, achieves salient improvements over various strong baselines, and also reaches a comparable performance to a state of the art method based on user’s interactive query term reduction and expansion.

Ethnic diversity and its impact on community social cohesion and neighborly exchange

Putnam's “constrict theory” suggests that ethnic diversity creates challenges for developing and sustaining social capital in urban settings. He argues that diversity decreases social cohesion and reduces social interactions among community residents. While Putnam's thesis is the subject of much debate in North America, the United Kingdom, and Europe, there is a limited focus on how ethnic diversity impacts upon social cohesion and neighborly exchange behaviors in Australia. Employing multilevel modeling and utilizing administrative and survey data from 4,000 residents living in 148 Brisbane suburbs, we assess whether ethnic diversity lowers social cohesion and increases “hunkering.” Our findings indicate that social cohesion and neighborly exchange are attenuated in ethnically diverse suburbs. However, diversity is less consequential for neighborly exchange among immigrants when compared to the general population. Our results provide at least partial support for Putnam's thesis.

Habituated interaction and social objects

In this position paper we draw from critical approaches to the concept of habit from cultural theory to argue that considering the sociality of everyday objects might be productive for understanding and designing for habituated interaction within the emerging Internet of Things.

Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

A rule-based hybrid method for anomaly detection in online-social-network graphs

Detecting anomalies in the online social network is a significant task as it assists in revealing the useful and interesting information about the user behavior on the network. This paper proposes a rule-based hybrid method using graph theory, Fuzzy clustering and Fuzzy rules for modeling user relationships inherent in online-social-network and for identifying anomalies. Fuzzy C-Means clustering is used to cluster the data and Fuzzy inference engine is used to generate rules based on the cluster behavior. The proposed method is able to achieve improved accuracy for identifying anomalies in comparison to existing methods.

Social media and tacit knowledge sharing : physicians' perspectives and experiences

Tacit knowledge sharing amongst physicians is known to have a significant impact on the quality of medical decisions. This thesis posits that social media can provide new opportunities for tacit knowledge sharing amongst physicians, and demonstrates this by presenting findings from a review of relevant literature and a qualitative survey conducted with physicians. Using thematic analysis, the study revealed five major themes and over twenty sub-themes as potential contributions of social media to tacit knowledge flow amongst physicians.

Social tagging, guppy effect and the role of interference : a quantum-inspired model for tags combination

Social tagging systems are shown to evidence a well known cognitive heuristic, the guppy effect, which arises from the combination of different concepts. We present some empirical evidence of this effect, drawn from a popular social tagging Web service. The guppy effect is then described using a quantum inspired formalism that has been already successfully applied to model conjunction fallacy and probability judgement errors. Key to the formalism is the concept of interference, which is able to capture and quantify the strength of the guppy effect.

Producing while consuming: Social interaction around photos shared within private group

User-generated content plays a pivotal role in the current social media. The main focus, however, has been on the explicitly generated user content such as photos, videos and status updates on different social networking sites. In this paper, we explore the potential of implicitly generated user content, based on users’ online consumption behaviors. It is technically feasible to record users’ consumption behaviors on mobile devices and share that with relevant people. Mobile devices with such capabilities could enrich social interactions around the consumed content, but it may also threaten users’ privacy. To understand the potentials of this design direction we created and evaluated a low-fidelity prototype intended for photo sharing within private groups. Our prototype incorporates two design concepts, namely, FingerPrint and MoodPhotos that leverage users’ consumption history and emotional responses. In this paper, we report user values and user acceptance of this prototype from three participatory design workshops.

Evaluation and social impact measurement amongst small to medium social enterprises : process, purpose and value

In recent years, the imperative to communicate organisational impacts to a variety of stakeholders has gained increasing importance within all sectors. Despite growing external demands for evaluation and social impact measurement, there has been limited critically informed analysis about the presumed importance of these activities to organisational success and the practical challenges faced by organisations in undertaking such assessment. In this paper, we present the findings from an action research study of five Australian small to medium social enterprises’ practices and use of evaluation and social impact analysis. Our findings have implications for social enterprise operators, policy makers and social investors regarding when, why and at what level these activities contribute to organisational performance and the fulfilment of mission.