Purpose: Food waste occurs in every stage of the supply chain, but the value-added lost to waste is the highest when consumers waste food. The purpose of this paper is to understand the food waste behaviour of consumers to support policies for minimising food waste. Design/methodology/approach: Using the theory of planned behaviour (TPB) as a theoretical lens, the authors design a questionnaire that incorporates contextual factors to explain food waste behaviour. The authors test two models: base (four constructs of TPB) and extended (four constructs of TPB plus six contextual factors). The authors build partial least squares structural equation models to test the hypotheses. Findings: The data confirm significant relationships between food waste and contextual factors such as motives, financial attitudes, planning routines, food surplus, social relationships and Ramadan. Research limitations/implications: The data comes from an agriculturally resource-constrained country: Qatar. Practical implications: Food waste originating from various causes means more food should flow through the supply chains to reach consumers’ homes. Contextual factors identified in this work increase the explanatory power of the base model by 75 per cent. Social implications: Changing eating habits during certain periods of the year and food surplus have a strong impact on food waste behaviour. Originality/value: A country is considered to be food secure if it can provide its citizens with stable access to sufficient, safe and nutritious food. The findings and conclusions inform and impact upon the development of food waste and food security policies.
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First year undergraduate students at the Amsterdam University of Applied Sciences of two different departments, were asked to join self-reported surveys in two succeeding years. Along with background variables, effort and commitment, the surveys asked elements of engagement. The later was analysed with factor analysis. The data of the surveys together with the results of the exams from the first year, were investigated to find out if the mandatory study choice test (SCT) taken before entering the faculty, had any predictive effect on their success. Not only basic statistical analysis like correlation was performed, but also more advanced analysis such as structural equation modelling (SEM) was used to uncover the value of the SCT. After a model was built, the normed fit index (NFI), the comparative fit index (CFI), the Tucker-Lewis Index (TLI) and the root mean square error of approximation (RMSEA), were used to determine the fit of the model. By comparing the influence of the variables on the SCT, the benefits of the latter will be determined and ultimately enhance the knowledge about influences upon student success in higher education.
The integration of renewable energy resources, controllable devices and energy storage into electricity distribution grids requires Decentralized Energy Management to ensure a stable distribution process. This demands the full integration of information and communication technology into the control of distribution grids. Supervisory Control and Data Acquisition (SCADA) is used to communicate measurements and commands between individual components and the control server. In the future this control is especially needed at medium voltage and probably also at the low voltage. This leads to an increased connectivity and thereby makes the system more vulnerable to cyber-attacks. According to the research agenda NCSRA III, the energy domain is becoming a prime target for cyber-attacks, e.g., abusing control protocol vulnerabilities. Detection of such attacks in SCADA networks is challenging when only relying on existing network Intrusion Detection Systems (IDSs). Although these systems were designed specifically for SCADA, they do not necessarily detect malicious control commands sent in legitimate format. However, analyzing each command in the context of the physical system has the potential to reveal certain inconsistencies. We propose to use dedicated intrusion detection mechanisms, which are fundamentally different from existing techniques used in the Internet. Up to now distribution grids are monitored and controlled centrally, whereby measurements are taken at field stations and send to the control room, which then issues commands back to actuators. In future smart grids, communication with and remote control of field stations is required. Attackers, who gain access to the corresponding communication links to substations can intercept and even exchange commands, which would not be detected by central security mechanisms. We argue that centralized SCADA systems should be enhanced by a distributed intrusion-detection approach to meet the new security challenges. Recently, as a first step a process-aware monitoring approach has been proposed as an additional layer that can be applied directly at Remote Terminal Units (RTUs). However, this allows purely local consistency checks. Instead, we propose a distributed and integrated approach for process-aware monitoring, which includes knowledge about the grid topology and measurements from neighboring RTUs to detect malicious incoming commands. The proposed approach requires a near real-time model of the relevant physical process, direct and secure communication between adjacent RTUs, and synchronized sensor measurements in trustable real-time, labeled with accurate global time-stamps. We investigate, to which extend the grid topology can be integrated into the IDS, while maintaining near real-time performance. Based on topology information and efficient solving of power flow equation we aim to detect e.g. non-consistent voltage drops or the occurrence of over/under-voltage and -current. By this, centrally requested switching commands and transformer tap change commands can be checked on consistency and safety based on the current state of the physical system. The developed concepts are not only relevant to increase the security of the distribution grids but are also crucial to deal with future developments like e.g. the safe integration of microgrids in the distribution networks or the operation of decentralized heat or biogas networks.
Thermal batteries, which store and release energy by hydrating and dehydrating salt crystals, hold great promise for domestic heating. Such batteries can be charged from waste heat from industrial processes, and discharged to provide neighbourhood heating. Unlike hot water storage systems, the energy is stored at room temperature, so the thermal losses are very low, making a salt battery highly efficient. However, the electrochemical change of the salt due to hydration and dehydration is very small, making it difficult to measure how much energy is stored in a battery. One promising technique is to measure the absolute humidity of the inlet and outlet air flow. The difference in humidity, combined with a rate equation model allows the total mass of water stored in the battery to be calculated, which can then be used to calculate the energy storage and battery power flow. However, there are several uncertainties in this approach. Commercially available sensors age over time, sometimes quite suddenly. It is not yet known if software can be used to compensate for sensor aging, or if a different sensor type is required. In addition to aging, each measurement is subject to random noise, which will be integrated into the model used to calculate the charge of the battery. It is not yet known how the noise will influence charge estimates. On the other hand, the sensor system must be as durable as domestic heating systems (decades). Hence, it is required to understand sensor aging in order to validate the sensor system for its intended use.
