More than money:developing an integrative multi-factorial measure of entrepreneurial success

This article conceptualises and operationalizes ‘subjective entrepreneurial success’ in a manner which reflects the criteria employed by entrepreneurs, rather than those imposed by researchers. Using two studies, a first qualitative enquiry investigated success definitions using interviews with 185 German entrepreneurs; five factors emerged from their reports: firm performance, workplace relationships, personal fulfilment, community impact, and personal financial rewards. The second study developed a questionnaire, the Subjective Entrepreneurial Success–Importance Scale (SES-IS), to measure these five factors using a sample of 184 entrepreneurs. We provide evidence for the validity of the SES-IS, including establishing systematic relationships of SES-IS with objective indicators of firm success, annual income and entrepreneur satisfaction with life and financial situation. We also provide evidence for the cross-cultural invariance of SES-IS using a sample of Polish entrepreneurs. The quintessence of our studies being that subjective entrepreneurial success is a multi-factorial construct, i.e. entrepreneurs value various indicators of success with money as only one possible option.

Sensing information modelling for smart city

Sensing technology is a key enabler of the Internet of Things (IoT) and could produce huge volume data to contribute the Big Data paradigm. Modelling of sensing information is an important and challenging topic, which influences essentially the quality of smart city systems. In this paper, the author discusses the relevant technologies and information modelling in the context of smart city and especially reports the investigation of how to model sensing and location information in order to support smart city development.

Parallel Problem Solving from Nature – PPSN XIV:14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings

This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.

Designing intrinsically photostable low band gap polymers:a smart tool combining EPR spectroscopy and DFT calculations

A rapid and efficient method to identify the weak points of the complex chemical structure of low band gap (LBG) polymers, designed for efficient solar cells, when submitted to light exposure is reported. This tool combines Electron Paramagnetic Resonance (EPR) using the 'spin trapping method' coupled with density functional theory modelling (DFT). First, the nature of the short life-time radicals formed during the early-stages of photo-degradation processes are determined by a spin-trapping technique. Two kinds of short life-time radical (R and R′O) are formed after 'short-duration' illumination in an inert atmosphere and in ambient air, respectively. Second, simulation allows the identification of the chemical structures of these radicals revealing the most probable photochemical process, namely homolytical scission between the Si atom of the conjugated skeleton and its pendent side-chains. Finally, DFT calculations confirm the homolytical cleavage observed by EPR, as well as the presence of a group that is highly susceptible to photooxidative attack. Therefore, the synergetic coupling of a spin trapping method with DFT calculations is shown to be a rapid and efficient method for providing unprecedented information on photochemical mechanisms. This approach will allow the design of LBG polymers without the need to trial the material within actual solar cell devices, an often long and costly screening procedure.

Do intelligent heating controls out-smart ordinary users?

Nearly a third of UK gas and electricity is used in homes, of which 80% is for space heating and hot water provision. Rising consumer bills, concerns about climate change and the surge in personal digital technology use has provoked the development of intelligent domestic heating controls. Whilst the need for having suitable control of the home heating system is essential for reducing domestic energy use, these heating controls rely on appropriate user interaction to achieve a saving and it is unclear whether these ‘smart’ heating controls enhance the use of domestic heating or reduce energy demand. This paper describes qualitative research undertaken with a small sample of UK householders to understand how people use new heating controls installed in their homes and what the requirements are for improved smart heating control design. The paper identifies, against Nielsen’s usability heuristics, the divergence between the householder’s use, understanding and expectations of the heating system and the actual design of the system. Digital and smart heating control systems should be designed to maximise usability so that they can be effectively used for efficient heating control by all users. The research highlights the need for development of new systems to readdress the needs of users and redefine the system requirements.

Matching theory based travel plan aware charging algorithms in V2G smart grid networks

The frequency, time and places of charging have large impact on the Quality of Experience (QoE) of EV drivers. It is critical to design effective EV charging scheduling system to improve the QoE of EV drivers. In order to improve EV charging QoE and utilization of CSs, we develop an innovative travel plan aware charging scheduling scheme for moving EVs to be charged at Charging Stations (CS). In the design of the proposed charging scheduling scheme for moving EVs, the travel routes of EVs and the utility of CSs are taken into consideration. The assignment of EVs to CSs is modeled as a two-sided many-to-one matching game with the objective of maximizing the system utility which reflects the satisfactory degrees of EVs and the profits of CSs. A Stable Matching Algorithm (SMA) is proposed to seek stable matching between charging EVs and CSs. Furthermore, an improved Learning based On-LiNe scheduling Algorithm (LONA) is proposed to be executed by each CS in a distributed manner. The performance gain of the average system utility by the SMA is up to 38.2% comparing to the Random Charging Scheduling (RCS) algorithm, and 4.67% comparing to Only utility of Electric Vehicle Concerned (OEVC) scheme. The effectiveness of the proposed SMA and LONA is also demonstrated by simulations in terms of the satisfactory ratio of charging EVs and the the convergence speed of iteration.

Rescission and substitute property:Bainbridge v Bainbridge [2016] EWHC 898 (Ch)

One of the unresolved issues concerning equity’s jurisdiction to set aside dispositions for mistake is the nature of the proprietary consequences that ensue. The decision in Bainbridge v Bainbridge sheds further light on this important issue, but also illustrates that some important aspects concerning the application of rescission needs further clarification. The key issue concerned the rescission of a trust, where parts of the land had been sold by the trustees who had used the proceeds of sale to buy two new plots of land. Part of the reasoning used by Master Matthews relied upon authorities, developed in the context of fraudulently induced transfers of money, which requires careful consideration of the relationship between the principle in Pitt v Holt and unjust enrichment.

Effectively positioning water loss event in smart water networks

With the eye-catching advances in sensing technologies, smart water networks have been attracting immense research interest in recent years. One of the most overarching tasks in smart water network management is the reduction of water loss (such as leaks and bursts in a pipe network). In this paper, we propose an efficient scheme to position water loss event based on water network topology. The state-of-the-art approach to this problem, however, utilizes the limited topology information of the water network, that is, only one single shortest path between two sensor locations. Consequently, the accuracy of positioning water loss events is still less desirable. To resolve this problem, our scheme consists of two key ingredients: First, we design a novel graph topology-based measure, which can recursively quantify the "average distances" for all pairs of senor locations simultaneously in a water network. This measure will substantially improve the accuracy of our positioning strategy, by capturing the entire water network topology information between every two sensor locations, yet without any sacrifice of computational efficiency. Then, we devise an efficient search algorithm that combines the "average distances" with the difference in the arrival times of the pressure variations detected at sensor locations. The viable experimental evaluations on real-world test bed (WaterWiSe@SG) demonstrate that our proposed positioning scheme can identify water loss event more accurately than the best-known competitor.