The study targeted towards drying of cantaloupe slices with various thicknesses in a microwave dryer. The experiments were carried out at three microwave powers of 180, 360, and 540 W and three thicknesses of 2, 4, and 6 mm for cantaloupe drying, and the weight variations were determined. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were exploited to investigate energy and exergy indices of cantaloupe drying using various afore-mentioned input parameters. The results indicated that a rise in microwave power and a decline in sample thickness can significantly decrease the specific energy consumption (SEC), energy loss, exergy loss, and improvement potential (probability level of 5%). The mean SEC, energy efficiency, energy loss, thermal efficiency, dryer efficiency, exergy efficiency, exergy loss, improvement potential, and sustainability index ranged in 10.48–25.92 MJ/kg water, 16.11–47.24%, 2.65–11.24 MJ/kg water, 7.02–36.46%, 12.36–42.70%, 11.25–38.89%, 3–12.2 MJ/kg water, 1.88–10.83 MJ/kg water, and 1.12–1.63, respectively. Based on the results, the use of higher microwave powers for drying thinner samples can improve the thermodynamic performance of the process. The ANFIS model offers a more accurate forecast of energy and exergy indices of cantaloupe drying compare to ANN model.

Artificial intelligence (AI) has become increasingly popular as a tool to model, identify, optimize, forecast, and control renewable energy systems. This work aimed to evaluate the capability of the artificial neural network (ANN) procedure to model and forecast solar power outputs of photovoltaic power systems (PVPSs) by using meteorological data. For this purpose, based on the literature review, important factors affecting energy generation in a PVPS were selected as inputs, and a recurrent neural network (RNN) architecture was established. After completing the trained network, the RNN capability was assessed to predict the energy output of the PVPS for days not included in the training database. The performance evaluation of the trained RNN revealed a regression value of 0.97774 for test data, whereas the RMSE and the mean actual output power for a sample day were 0.0248 MJ and 0.538 MJ, respectively. In addition to RMSE, an error histogram and regression plots obtained by MATLAB were employed to evaluate the network’s capability, and validation results represented a sufficient prediction accuracy of the trained RNN.

This study was carried out to optimize a computational model of a new underground passive solar greenhouse to improve thermal performance, storage, and saving of heat solar energy. Optimized and conventional passive solar greenhouse were compared in regards of indoor air temperature, irradiation, and energy demand. Six different materials were used in the conventional model. In addition, TRNSYS software was employed to determine heat demand and irradiation in the greenhouse. The results showed that the annual total heating requirement in the optimized model was 30% lower than a conventional passive solar system. In addition, the resulting average air temperature in the optimized model ranged from −4 to 33.1 °C in the four days of cloud, snow, and sun. The average air temperature in the conventional passive solar greenhouse ranged from −8.4 to 24.7 °C. The maximum monthly heating requirement was 796 MJ/m² for the Wtype87 model (100-mm lightweight concrete block) and the minimum value was 190 MJ/m² for the Wtype45 model (50-mm insulation with 200-mm clay tile) in a conventional passive solar greenhouse while the monthly heating requirement estimated 126 MJ/m² for the optimized greenhouse model. The predictability of the TRNSYS model was calculated with a coefficient of determination (R²) of 95.95%.

Fereydounshahr experiences growing electricity shortfalls and an overreliance on polluting diesel generators. This analysis models renewable hybrid systems to electrify a local dairy operation using HOMER Pro 3.11 software. Despite higher upfront costs, adding just 5% solar photovoltaics maintained low net present costs while increasing clean energy penetration versus diesel generators alone. Furthermore, a combined diesel-solar-wind system reduced carbon dioxide and nitrogen oxide emissions by over 1%. Although diesel generators had the shortest payback period at 48 years, the capital recovery factor for a diesel–solar combination reached 62 years. Thus, tailored hybrid renewable systems could provide an affordable, low-emissions electricity solution for the Fereydounshahr livestock facility. With suitable wind and solar resources, the right policy incentives could also unlock substantial local renewable capacity to meet rising demand and mitigate dependence on imported, climate-harming fossil fuels.

New public management introduces a managerial approach to managing the public sector and administration from the perspective of human resources management. This approach assumes the adaptation of efficiency mechanisms and management methods and techniques used in the private sector to the conditions of managing public organizations. The model assumes effective implementation of public cost accounting, an approach based on achieving results, decentralization of management, wider consideration of public-private partnerships and extensive use of market mechanisms. This management model is intended to ensure the economy, efficiency and effectiveness of the organization, including the privatization of some public services. Streszczenie Nowe zarządzanie publiczne wprowadza podejście menedżerskie do zarządzania sektorem publicznym i administracją z perspektywy zarządzania zasobami ludzkim. Takie podejście zakłada adaptację mechanizmów efektywnościowych oraz metod i technik zarządzania stosowanych w sektorze prywatnym do warunków zarządzania organizacjami publicznymi. Model zakłada efektywne wdrożenie rachunku kosztów publicznych, podejście oparte o osiąganie wyników, decentralizację zarządzania, szersze uwzględnienie partnerstwa publiczo-prywatnego oraz szerokie wykorzystanie mechanizmów rynkowych. Ten model zarządzania ma zapewnić gospodarność, efektywność i skuteczność organizacji, w tym prywatyzację części usług publicznych.

W artykule zaprezentowano krytyczne stanowisko wobec aktualnych koncepcji mierzenia jakości i efektywności kapitału ludzkiego w organizacji. Wykazano, że zbieżności w stosowanych metodach i technikach pomiaru, analizy i oceny kapitału ludzkiego w organizacji mają swe źródło w praktyce selektywnego ujęcia zasobów ludzkich i przyjmowania wybiórczego kontekstu ich funkcjonowania w środowisku organizacyjnym. Na gruncie podjętej krytyki przedstawiono koncepcję analizy kapitału ludzkiego w układzie sprzężenia zwrotnego perspektyw: strategicznej aktywności i operacyjnej działal­ności organizacji. Kapitał ludzki integruje obie perspektywy i zarazem weryfikuje ich współzależność w modelu biznesowym każdej organizacji.