Optimal distributed generation placement in radial distribution systems

Distributed generation (DG) resources are commonly used in the electric systems to obtain minimum line losses, as one of the benefits of DG, in radial distribution systems. Studies have shown the importance of appropriate selection of location and size of DGs. This paper proposes an analytical method for solving optimal distributed generation placement (ODGP) problem to minimize line losses in radial distribution systems using loss sensitivity factor (LSF) based on bus-injection to branch-current (BIBC) matrix. The proposed method is formulated and tested on 12 and 34 bus radial distribution systems. The classical grid search algorithm based on successive load flows is employed to validate the results. The main advantages of the proposed method as compared with the other conventional methods are the robustness and no need to calculate and invert large admittance or Jacobian matrices. Therefore, the simulation time and the amount of computer memory, required for processing data especially for the large systems, decreases.

On the hardness of the sum of K mins problem

The sum of k mins protocol was proposed by Hopper and Blum as a protocol for secure human identification. The goal of the protocol is to let an unaided human securely authenticate to a remote server. The main ingredient of the protocol is the sum of k mins problem. The difficulty of solving this problem determines the security of the protocol. In this paper, we show that the sum of k mins problem is NP-Complete and W[1]-Hard. This latter notion relates to fixed parameter intractability. We also discuss the use of the sum of k mins protocol in resource-constrained devices.

Stagnancy in Indonesia’s reformed state asset management policies and practices : a wicked problem?

The policies and regulations governing the practice of state asset management have emerged as an urgent question among many countries worldwide for there is heightened awareness of the complex and crucial role that state assets play in public service provision. Indonesia is an example of such country, introducing a ‘big-bang’ reform in state asset management laws, policies, regulations, and technical guidelines. Indonesia exemplified its enthusiasm in reforming state asset management policies and practices through the establishment of the Directorate General of State Assets in 2006. The Directorate General of State Assets have stressed the new direction that it is taking state asset management laws and policies through the introduction of Republic of Indonesia Law Number 38 Year 2008, which is an amended regulation overruling Republic of Indonesia Law Number 6 Year 2006 on Central/Regional Government State Asset Management. Law number 38/2008 aims to further exemplify good governance principles and puts forward a ‘the highest and best use of assets’ principle in state asset management. The purpose of this study is to explore and analyze specific contributing influences to state asset management practices, answering the question why innovative state asset management policy implementation is stagnant. The methodology of this study is that of qualitative case study approach, utilizing empirical data sample of four Indonesian regional governments. Through a thematic analytical approach this study provides an in-depth analysis of each influencing factors to state asset management reform. Such analysis suggests the potential of an ‘excuse rhetoric’; whereby the influencing factors identified are a smoke-screen, or are myths that public policy makers and implementers believe in, as a means to ex-plain stagnant implementation of innovative state asset management practice. Thus this study offers deeper insights of the intricate web that influences state as-set management innovative policies to state asset management policy makers; to be taken into consideration in future policy writing.

Supplementary material : large scale read classification for next generation sequencing

Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

Do community-wide interventions increase physical activity? S1TEP

Background Not getting enough physical activity leads to poorer health. Regular physical activity can reduce the risk of chronic disease and improve one’s health and well-being. The lack of physical activity is a common and growing problem in many countries. We sought to evaluate the effects of community wide, multi-strategic interventions upon the physical activity patterns of populations. Method We undertook a Cochrane Systematic Review which included an extensive search of databases, including studies which met pre-determined criteria, and conducted independent risk of bias assessment and data extraction. Results After the selection process, 25 studies were included in the review. The strategies varied by the number and type of components and their intensity. No studies were identified as low risk of bias. Sixteen studies were identified as having a high risk of bias and thus untrustworthy. Nine studies were of considered to have an unclear risk of bias and some studies held back data they collected. The effects reported were inconsistent across the studies and the measures. Some of the better designed studies showed no improvement in measures of physical activity. Interventions which have an environmental change component seemed to be a promising direction. Those interventions which were primarily a mass media campaign were less likely to be successful. Conclusions Although numerous studies have been undertaken, there is considerable inconsistency in the findings of the available studies and this is confounded by serious methodological issues within the included studies. Simply combining interventions does not necessarily result in increased physical activity as many such studies, including some long term programs, failed to demonstrate efficacy. There is a clear need for well-designed studies and these studies should focus on the quality of measurement of physical activity. The review is currently being updated with newer studies.

A coding approach to the multicast stream authentication problem

We study the multicast stream authentication problem when an opponent can drop, reorder and introduce data packets into the communication channel. In such a model, packet overhead and computing efficiency are two parameters to be taken into account when designing a multicast stream protocol. In this paper, we propose to use two families of erasure codes to deal with this problem, namely, rateless codes and maximum distance separable codes. Our constructions will have the following advantages. First, our packet overhead will be small. Second, the number of signature verifications to be performed at the receiver is O(1). Third, every receiver will be able to recover all the original data packets emitted by the sender despite losses and injection occurred during the transmission of information.

Making media participatory: Digital storytelling

From journalism to social media, the practices of our professional storytellers continue to evolve and change along with our storytelling institutions and their functions. Comprehending these developments is a key problem of contemporary media and cultural studies. Are the politics of representation giving way to a new progressive politics of self-representation and direct participation? Or, instead, are these new genres of self-representation part of a more general demotic turn in the function of contemporary media? Do media merely mediate or amplify cultural identities, or is media functionality becoming, closer to that of a translator or even an author of identities? How can we know if the changing actor-networks of storytelling contribute to a wider democratisation, a reshaping of the hierarchies of voice and agency? This chapter considers the place of one specific critical participatory media production practice known as 'digital storytelling’ in addressing these larger questions of socio-cultural change.

A flexible optimisation model for the railway crew scheduling problem

Addressing the Crew Scheduling Problem (CSP) in transportation systems can be too complex to capture all details. The designed models usually ignore or simplify features which are difficult to formulate. This paper proposes an alternative formulation using a Mixed Integer Programming (MIP) approach to the problem. The optimisation model integrates the two phases of pairing generation and pairing optimisation by simultaneously sequencing trips into feasible duties and minimising total elapsed time of any duty. Crew scheduling constraints in which the crew have to return to their home depot at the end of the shift are included in the model. The flexibility of this model comes in the inclusion of the time interval of relief opportunities, allowing the crew to be relieved during a finite time interval. This will enhance the robustness of the schedule and provide a better representation of real-world conditions.

Supramolecular selection in molecular and framework co-crystals

An ongoing challenge in chemistry and crystal engineering is the synthesis of functional materials with predictable structures and customisable properties. This may be achieved by crystallising mixtures of different compounds. Co-crystals formed through this method have predictable structures and their properties may be tuned by varying the ratio of the compounds in the crystallising solution. This thesis examines single crystals formed by the co-crystallisation of metal complexes that have similar structures but different physical or chemical properties. A variety of new compounds with interesting properties were prepared, characterised and their significance in the context of crystal engineering was explored.

A more efficient and effective heuristic algorithm for the MapReduce placement problem in cloud computing

The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation in cloud computing. From the computational point of view, the mappers/reducers placement problem is a generalization of the classical bin packing problem, which is NP-complete. Thus, in this paper we propose a new heuristic algorithm for the mappers/reducers placement problem in cloud computing and evaluate it by comparing with other several heuristics on solution quality and computation time by solving a set of test problems with various characteristics. The computational results show that our heuristic algorithm is much more efficient than the other heuristics. Also, we verify the effectiveness of our heuristic algorithm by comparing the mapper/reducer placement for a benchmark problem generated by our heuristic algorithm with a conventional mapper/reducer placement. The comparison results show that the computation using our mapper/reducer placement is much cheaper while still satisfying the computation deadline.

A new grouping genetic algorithm for the MapReduce placement problem in cloud computing

MapReduce is a computation model for processing large data sets in parallel on large clusters of machines, in a reliable, fault-tolerant manner. A MapReduce computation is broken down into a number of map tasks and reduce tasks, which are performed by so called mappers and reducers, respectively. The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation. From the computational point of view, the mappers/reducers placement problem is a generation of the classical bin packing problem, which is NPcomplete. Thus, in this paper we propose a new grouping genetic algorithm for the mappers/reducers placement problem in cloud computing. Compared with the original one, our grouping genetic algorithm uses an innovative coding scheme and also eliminates the inversion operator which is an essential operator in the original grouping genetic algorithm. The new grouping genetic algorithm is evaluated by experiments and the experimental results show that it is much more efficient than four popular algorithms for the problem, including the original grouping genetic algorithm.

Secure computation of the vector dominance problem

Suppose two parties, holding vectors A = (a 1,a 2,...,a n ) and B = (b 1,b 2,...,b n ) respectively, wish to know whether a i  > b i for all i, without disclosing any private input. This problem is called the vector dominance problem, and is closely related to the well-studied problem for securely comparing two numbers (Yao’s millionaires problem). In this paper, we propose several protocols for this problem, which improve upon existing protocols on round complexity or communication/computation complexity.

Design-build contractor selection for public sustainable buildings

Design-build (DB) is regarded as an effective means of delivering high performance green buildings, and the selection of DB contractors is of critical importance. The objective of this study is to evaluate the selection of design-builders for public buildings seeking Leadership in Energy and Environmental Design (LEED) certification and compare the selection practices involved with those of non-LEED-seeking DB projects through a robust content analysis of 74 DB request for proposals (RFPs) for public DB projects. The results of the content analysis reveal that the level of LEED certification is the dominant means of conveying the sustainability requirements in RFPs for contractor selection, with the majority of RFPs (60%) including sustainability requirements as part of the contractor evaluation package. With the exception of contractors' past performance, there is no statistically significant difference in the importance weightings of selection criteria between LEED-seeking and non-LEED-seeking buildings, and DB owners tend to place more emphasis on innovative technical solutions rather than the past performance of DB contractors. Additionally, the research findings also indicate that owners of LEED-seeking building projects tend to provide less design decisions in RFPs in order to solicit innovative design alternatives from potential DB contractors. This study provides DB owners with a number of practical implications for selecting appropriate design-builders for green DB projects.

Mechanism‐based selection of a potent kallikrein‐related peptidase 7 inhibitor from a versatile library based on the sunflower trypsin inhibitor SFTI‐1

Potent and specific enzyme inhibition is a key goal in the development of therapeutic inhibitors targeting proteolytic activity. The backbone-cyclized peptide, Sunflower Trypsin Inhibitor (SFTI-1) affords a scaffold that can be engineered to achieve both these aims. SFTI-1's mechanism of inhibition is unusual in that it shows fast-on/slow-off kinetics driven by cleavage and religation of a scissile bond. This phenomenon was used to select a nanomolar inhibitor of kallikrein-related peptidase 7 (KLK7) from a versatile library of SFTI variants with diversity tailored to exploit distinctive surfaces present in the active site of serine proteases. Inhibitor selection was achieved through the use of size exclusion chromatography to separate protease/inhibitor complexes from unbound inhibitors followed by inhibitor identification according to molecular mass ascertained by mass spectrometry. This approach identified a single dominant inhibitor species with molecular weight of 1562.4 Da, which is consistent with the SFTI variant SFTI-WCTF. Once synthesized individually this inhibitor showed an IC50 of 173.9 ± 7.6 nM against chromogenic substrates and could block protein proteolysis. Molecular modeling analysis suggested that selection of SFTI-WCTF was driven by specific aromatic interactions and stabilized by an enhanced internal hydrogen bonding network. This approach provides a robust and rapid route to inhibitor selection and design.