Nature-based entrepreneurship in private forests – The preconditions for the sustainable co-operation between private forest owners and entrepreneurs

Nature-based tourism is one of the fastest growing tourism sectors at the moment. It is also the form of tourism that often benefits the economy of rural areas. In addition to state owned forests, nature-based tourism is in many countries situated in private forests, which are not owned by entrepreneurs themselves. Therefore, the ownership issues and property rights form central challenges for the business activities. The maintenance of good relationships between private forest owners and entrepreneurs, as well as combining their interests, becomes vital. These relationships are typically exceptionally asymmetrical, granting the forest owner unilateral rights regulating the business activities in their forests. Despite this, the co-operation is typically very informal and the existing economic compensation models do not necessarily cover all the forest owners’ costs. The ownership issues bring their own characteristics to the relationship. Therefore, we argue that different aspects of ownership, especially psychological ones, have to be more critically examined and taken into consideration in order to build truly successful relations between these parties. This is crucial for sustaining the business activities. The core of psychological ownership is the sense of possession. Psychological ownership can be defined as a state, in which individuals perceive the target of ownership, the object or idea, as “theirs”. The concept of psychological ownership has so far been mainly used in the context of professional organizations. In this research, it has been used to explain the relationships between private forest owners and nature-based entrepreneurs. The aim of this study is to provide new information concerning the effect of psychological ownership on the collaboration and to highlight the good practices. To address the complexity of the phenomenon, qualitative case study methods were adopted to understand the role of ownership at the level of subjective experience. The empirical data was based on 27 in-depth interviews with private forest owners and nature-based tourism entrepreneurs. The data was analysed by using the methods of qualitative analysis to construct different typologies to describe the essence of successful collaboration. As a result of the study, the special characteristics and the practical level expressions of the psychological ownership in the privately owned forest context were analysed. Four different strategies to perceive these ownership characteristics in co-operation relationships were found. By taking the psychological ownership into consideration via these strategies, the nature-based entrepreneurs aim to balance the co-operation relationship and minimise the risks in long term activities based on privately owned forests.

Decision support requirements for intelligent operation of southern grid in India

Control centers (CC) play a very important role in power system operation. An overall view of the system with information about all existing resources and needs is implemented through SCADA (Supervisory control and data acquisition system) and an EMS (energy management system). As advanced technologies have made their way into the utility environment, the operators are flooded with huge amount of data. The last decade has seen extensive applications of AI techniques, knowledge-based systems, Artificial Neural Networks in this area. This paper focuses on the need for development of an intelligent decision support system to assist the operator in making proper decisions. The requirements for realization of such a system are recognized for the effective operation and energy management of the southern grid in India The application of Petri nets leading to decision support system has been illustrated considering 24 bus system that is a part of southern grid.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

Real-time multipurpose reservoir operation: a case study / Exploitation en temps reacuteel d'un reservoir agrave buts multiples: eacutetude d'un cas

A real-time operational methodology has been developed for multipurpose reservoir operation for irrigation and hydropower generation with application to the Bhadra reservoir system in the state of Karnataka, India. The methodology consists of three phases of computer modelling. In the first phase, the optimal release policy for a given initial storage and inflow is determined using a stochastic dynamic programming (SDP) model. Streamflow forecasting using an adaptive AutoRegressive Integrated Moving Average (ARIMA) model constitutes the second phase. A real-time simulation model is developed in the third phase using the forecast inflows of phase 2 and the operating policy of phase 1. A comparison of the optimal monthly real-time operation with the historical operation demonstrates the relevance, applicability and the relative advantage of the proposed methodology.

An automated thermal relaxation calorimeter for operation at low temperature (0.5 K

We describe an automated calorimeter for measurement of specific heat in the temperature range 10 K>T>0.5 K. It uses sample of moderate size (100–1000 mg), has a moderate precision and accuracy (2%–5%), is easy to operate and the measurements can be done quickly with He4 economy. The accuracy of this calorimeter was checked by measurement of specific heat of copper and that of aluminium near its superconducting transition temperature.

Decentralized Parallel Operation of Inverters Sharing Unbalanced and Nonlinear Loads

In this paper, a wireless control strategy for parallel operation of three-phase four-wire inverters is proposed. A generalized situation is considered where the inverters are of unequal power ratings and the loads are nonlinear and unbalanced in nature. The proposed control algorithm exploits the potential of sinusoidal domain proportional+multiresonant controller ( in the inner voltage regulation loop) to make the system suitable for nonlinear and unbalanced loads with a simple and generalized structure of virtual output-impedance loop. The decentralized operation is achieved by using three-phase P/Q droop characteristics. The overall control algorithm helps to limit the harmonic contents and the degree of unbalance in the output-voltage waveform and to achieve excellent power-sharing accuracy in spite of mismatch in the inverter output impedances. Moreover, a synchronized turn on with consequent change over to the droop mode is applied for the new incoming unit in order to limit the circulating current completely. The simulation and experimental results from-1 kVA and -0.5 kVA paralleled units validate the effectiveness of the scheme.

Design and development of a self-supported polymer electrolyte fuel cell system with anodic dead-end operation

Design and operational details for a self-supported polymer electrolyte fuel cell (PEFC) system with anodic dead-end fuel supply and internally humidified cathodic oxidant flow are described. During the PEFC operation, nitrogen and water back diffuse across the Nafion membrane from the cathode to the anode and accumulate in the anode flow channels affecting stack performance. The accumulated inert species are flushed from the stack by purging the fuel cell stack with a timer-activated purge valve to address the aforesaid problem. To minimize the system complexity, stack is designed in such a way that all the inert species accumulate in only one cell called the purge cell. A pulsed purge sequence comprises opening the valve for purge duration followed by purge-valve closing for the hold period and repeating the sequence in cycles. Since self-humidification is inadequate to keep the membrane wet, the anodic dead-end-operated PEFC stack with composite membrane comprising perflourosulphonic acid (Nafion) and silica is employed for keeping the membrane humidified even while operating the stack with dry hydrogen and internally humidified air.

An integrated model for optimal reservoir operation for irrigation of multiple crops

An integrated model is developed, based on seasonal inputs of reservoir inflow and rainfall in the irrigated area, to determine the optimal reservoir release policies and irrigation allocations to multiple crops. The model is conceptually made up of two modules, Module 1 is an intraseasonal allocation model to maximize the sum of relative yields of all crops, for a given state of the system, using linear programming (LP). The module takes into account reservoir storage continuity, soil moisture balance, and crop root growth with time. Module 2 is a seasonal allocation model to derive the steady state reservoir operating policy using stochastic dynamic programming (SDP). Reservoir storage, seasonal inflow, and seasonal rainfall are the state variables in the SDP. The objective in SDP is to maximize the expected sum of relative yields of all crops in a year. The results of module 1 and the transition probabilities of seasonal inflow and rainfall form the input for module 2. The use of seasonal inputs coupled with the LP-SDP solution strategy in the present formulation facilitates in relaxing the limitations of an earlier study, while affecting additional improvements. The model is applied to an existing reservoir in Karnataka State, India.

Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

Integrated Reservoir Operation Modeling for Irrigation Systems - A Multi-Objective Approach

An integrated reservoir operation model is presented for developing effective operational policies for irrigation water management. In arid and semi-arid climates, owing to dynamic changes in the hydroclimatic conditions within a season, the fixed cropping pattern with conventional operating policies, may have considerable impact on the performance of the irrigation system and may affect the economics of the farming community. For optimal allocation of irrigation water in a season, development of effective mathematical models may guide the water managers in proper decision making and consequently help in reducing the adverse effects of water shortage and crop failure problems. This paper presents a multi-objective integrated reservoir operation model for multi-crop irrigation system. To solve the multi-objective model, a recent swarm intelligence technique, namely elitist-mutated multi-objective particle swarm optimisation (EM-MOPSO) has been used and applied to a case study in India. The method evolves effective strategies for irrigation crop planning and operation policies for a reservoir system, and thereby helps farming community in improving crop benefits and water resource usage in the reservoir command area.

Pricing a Shared Access Link for Fair and Efficient Operation with Variable User Data Rates

The literature on pricing implicitly assumes an "infinite data" model, in which sources can sustain any data rate indefinitely. We assume a more realistic "finite data" model, in which sources occasionally run out of data; this leads to variable user data rates. Further, we assume that users have contracts with the service provider, specifying the rates at which they can inject traffic into the network. Our objective is to study how prices can be set such that a single link can be shared efficiently and fairly among users in a dynamically changing scenario where a subset of users occasionally has little data to send. User preferences are modelled by concave increasing utility functions. Further, we introduce two additional elements: a convex increasing disutility function and a convex increasing multiplicative congestion-penally function. The disutility function takes the shortfall (contracted rate minus present rate) as its argument, and essentially encourages users to send traffic at their contracted rates, while the congestion-penalty function discourages heavy users from sending excess data when the link is congested. We obtain simple necessary and sufficient conditions on prices for fair and efficient link sharing; moreover, we show that a single price for all users achieves this. We illustrate the ideas using a simple experiment.