The maximum theoretical performance of unconcentrated solar photovoltaic and thermoelectric generator systems

The maximum efficiency for photovoltaic (PV) and thermoelectric generator (TEG) systems without concentration is investigated. Both a combined system where the TEG is mounted directly on the back of the PV and a tandem system where the incoming sunlight is split, and the short wavelength radiation is sent to the PV and the long wavelength to the TEG, are considered. An analytical model based on the Shockley-Queisser efficiency limit for PVs and the TEG figure of merit parameter $zT$ is presented. It is shown that for non-concentrated sunlight, even if the TEG operates at the Carnot efficiency and the PV performance is assumed independent of temperature, the maximum increase in efficiency is 4.5 percentage points (pp.) for the combined case and 1.8 pp. for the tandem case compared to a stand alone PV. For a more realistic case with a temperature dependent PV and a realistic TEG, the gain in performance is much lower. For the combined PV and TEG system it is shown that a minimum $zT$ value is needed in order for the system to be more efficient than a stand alone PV system.Comment: 6 pages, 5 figure

Turing Completeness of Finite, Epistemic Programs

In this note, we show the class of finite, epistemic programs to be Turing complete. Epistemic programs is a widely used update mechanism used in epistemic logic, where it such are a special type of action models: One which does not contain postconditions

FruitGrowth - Gasburning in orchards - Environment friendly weed control

Gas burning makes treatment of weed organic. The new ENVO-DAN burner saves 40% gas and treats 1/2 meter in width.It can be mounted on a standard lawn tractor, orchard tractor or a mobile robot. The modular burner system for burning weeds in orchards can be configurated to your needs

Understanding credit risk in Norwegian real estate crowdlending : Analysis of credit quality among Norwegian real estate crowdlending borrowers across FundingPartner, Kameo and Monio

The Norwegian crowdlending industry has grown rapidly in the last decade, resulting in the emergence of several platforms of notable sizes. Regulations are lagging, and government instances are discussing incorporating EU directives. This thesis aims to investigate risk differences in credit classifications across Norwegian crowdlending platforms. We identify risk factors and analyze potential differences in risk related to loans issued by FundingPartner, Kameo and Monio. We analyzed differences both for the platforms overall and within the credit classifications. The results provide an overview of differences in credit assessment that may benefit the decisions of both lenders and policymakers. The analysis is based on a manually assembled data set containing loan data, financial statements and policy rates. Our empirical analysis uses three bankruptcy models to evaluate borrowers' credit risk based on financial statements. The results from the bankruptcy models are tested to ensure significance. Moreover, we integrate project-specific risk elements such as collateral, loan size, loan term and interest rates to explain the differences we discovered. We also consider actual default rates and check if they are consistent with our empirical results. Despite having equal credit classification, we discovered significant differences between borrowers of such loans. FundingPartner issued A-classified loans with significantly riskier borrowers than Monio, despite Monio rewarding their lenders with higher interest rates. Borrowers of Monio are overall the least risky, yet the platform hosts the riskiest borrowers in our sample. Kameo borrowers with D-classified loans are significantly less risky than Monio's. Furthermore, we observe considerable differences in the use of collateral to secure lenders in the event of default. Lastly, we compare our empirical findings against confirmed defaults.nhhma

Location-Quality-aware Policy Optimisation for Relay Selection in Mobile Networks

Relaying can improve the coverage and performance of wireless access networks. In presence of a localisation system at the mobile nodes, the use of such location estimates for relay node selection can be advantageous as such information can be collected by access points in linear effort with respect to number of mobile nodes (while the number of links grows quadratically). However, the localisation error and the chosen update rate of location information in conjunction with the mobility model affect the performance of such location-based relay schemes; these parameters also need to be taken into account in the design of optimal policies. This paper develops a Markov model that can capture the joint impact of localisation errors and inaccuracies of location information due to forwarding delays and mobility; the Markov model is used to develop algorithms to determine optimal location-based relay policies that take the aforementioned factors into account. The model is subsequently used to analyse the impact of deployment parameter choices on the performance of location-based relaying in WLAN scenarios with free-space propagation conditions and in an measurement-based indoor office scenario.Comment: Accepted for publication in ACM/Springer Wireless Network