Analiza czynników decydujących o przyciąganiu turystów przez rząd w zarządzaniu publicznym z perspektywy ochrony środowiska

Tourism is a critical sustainable social and economic activity that can empower local communities. The current study strived to explore decisive factors that might be used it promotes environmental protection. Governments worldwide might employ to improve conservation and the tourism sector. There is a need to sponsor more publications on tourism and the environment that provide rigor, insight, and significance. There is also a need to address critical impacts, including greenhouse gases for airlines, liquid wastes for cruise ships, water and energy conservation for urban hotels, vegetation clearance, and wildlife displacement for rural resorts, and a range of direct and indirect local impacts on plants and animals for nature-based and adventure tourism in parks and wilderness areas. Governments need to work on economic models that address; currency exchange rates; airfares and taxes; land tenure and wildlife ownership laws; transport infrastructure; police, quarantine, and border security; investment law; public protected-area systems; and a variety of social pressures and fashions. The most effective means to improve environmental management in tourism is through laws and regulations for development planning, pollution control, and protected areas. In developed nations, tourism threatens conservation as property developers push to build private facilities inside public protected areas. In developing nations, tourism is a tool to fund conservation in public parks and private or communal lands. Visitors to the public, and protected areas contribute political and financial capital to park agencies. A few private tourism operators have converted areas of private and communal land to conservation.Turystyka jest kluczową zrównoważoną działalnością społeczną i gospodarczą, która może wzmocnić pozycję społeczności lokalnych. Celem niniejszego artykułu było zbadanie decydujących czynników, które można wykorzystać w promowaniu ochrony środowiska. Rządy na całym świecie mogą zastosować środki w celu poprawy ochrony środowiska i sektora turystycznego. Istnieje potrzeba sponsorowania większej liczby publikacji na temat turystyki i środowiska, które dostarczają dyscypliny, wnikliwości i znaczenia. Należy również zająć się krytycznymi skutkami, w tym gazami cieplarnianymi dla linii lotniczych, odpadami płynnymi dla statków wycieczkowych, oszczędzaniem wody i energii w hotelach miejskich, usuwaniem roślinności i wypieraniem dzikiej przyrody w ośrodkach wiejskich, a także szeregiem bezpośrednich i pośrednich skutków lokalnych, np. rośliny i zwierzęta dla turystyki przyrodniczej i przygodowej w parkach i na obszarach dzikiej przyrody. Rządy muszą pracować nad modelami gospodarczymi, które uwzględnią następujące czynniki: kursy wymiany walut; bilety lotnicze i podatki; prawa własności gruntów i własności dzikich zwierząt; infrastruktura transportowa; policja, kwarantanna i bezpieczeństwo granic; prawo inwestycyjne; systemy publicznych obszarów chronionych; oraz różnorodne mody społeczne. Najskuteczniejszym sposobem poprawy zarządzania środowiskiem w turystyce są przepisy ustawowe i wykonawcze dotyczące planowania rozwoju, kontroli zanieczyszczeń i obszarów chronionych. W krajach rozwiniętych turystyka zagraża ochronie przyrody, ponieważ deweloperzy nalegają na budowę prywatnych obiektów na publicznych obszarach chronionych. W krajach rozwijających się turystyka jest narzędziem finansowania ochrony przyrody w parkach publicznych oraz na terenach prywatnych lub komunalnych. Odwiedzający ludność i obszary chronione wnoszą kapitał polityczny i finansowy do agencji parkowych. Kilku prywatnych operatorów turystycznych przekształciło obszary gruntów prywatnych i komunalnych w obszary objęte ochroną

Topology-aware Debiased Self-supervised Graph Learning for Recommendation

In recommendation, graph-based Collaborative Filtering (CF) methods mitigate the data sparsity by introducing Graph Contrastive Learning (GCL). However, the random negative sampling strategy in these GCL-based CF models neglects the semantic structure of users (items), which not only introduces false negatives (negatives that are similar to anchor user (item)) but also ignores the potential positive samples. To tackle the above issues, we propose Topology-aware Debiased Self-supervised Graph Learning (TDSGL) for recommendation, which constructs contrastive pairs according to the semantic similarity between users (items). Specifically, since the original user-item interaction data commendably reflects the purchasing intent of users and certain characteristics of items, we calculate the semantic similarity between users (items) on interaction data. Then, given a user (item), we construct its negative pairs by selecting users (items) which embed different semantic structures to ensure the semantic difference between the given user (item) and its negatives. Moreover, for a user (item), we design a feature extraction module that converts other semantically similar users (items) into an auxiliary positive sample to acquire a more informative representation. Experimental results show that the proposed model outperforms the state-of-the-art models significantly on three public datasets. Our model implementation codes are available at https://github.com/malajikuai/TDSGL.Comment: 6 pages,8 figure

Image recognition, semantic segmentation and photo adjustment using deep neural networks

Deep Neural Networks (DNNs) have proven to be effective models for solving various problems in computer vision. Multi-Layer Perceptron Networks, Convolutional Neural Networks and Recurrent Neural Networks are representative examples of DNNs in the setting of supervised learning. The key ingredients in the successful development of DNN-based models include but not limited to task-specific designs of network architecture, discriminative feature representation learning and scalable training algorithms. In this thesis, we describe a collection of DNN-based models to address three challenging computer vision tasks, namely large-scale visual recognition, image semantic segmentation and automatic photo adjustment. For each task, the network architecture is carefully designed on the basis of the nature of the task. For large-scale visual recognition, we design a hierarchical Convolutional Neural Network to fully exploit a semantic hierarchy among visual categories. The resulting model can be deemed as an ensemble of specialized classifiers. We improve state-of-the-art results at an affordable increase of the computational cost. For image semantic segmentation, we integrate convolutional layers with novel spatially recurrent layers for incorporating global contexts into the prediction process. The resulting hybrid network is capable of learning improved feature representations, which lead to more accurate region recognition and boundary localization. Combined with a post-processing step involving a fully-connected conditional random field, our hybrid network achieves new state-of-the-art results on a large benchmark dataset. For automatic photo adjustment, we take a data-driven approach to learn the underlying color transforms from manually enhanced examples. We formulate the learning problem as a regression task, which can be approached with a Multi-Layer Perceptron network. We concatenate global contextual features, local contextual features as well as pixel-wise features and feed them into the deep network. State-of-the-art results are achieved on datasets with both global and local stylized adjustments

Research on Calculation of the IOL Tilt and Decentration Based on Surface Fitting

The tilt and decentration of intraocular lens (IOL) result in defocussing, astigmatism, and wavefront aberration after operation. The objective is to give a method to estimate the tilt and decentration of IOL more accurately. Based on AS-OCT images of twelve eyes from eight cases with subluxation lens after operation, we fitted spherical equation to the data obtained from the images of the anterior and posterior surfaces of the IOL. By the established relationship between IOL tilt (decentration) and the scanned angle, at which a piece of AS-OCT image was taken by the instrument, the IOL tilt and decentration were calculated. IOL tilt angle and decentration of each subject were given. Moreover, the horizontal and vertical tilt was also obtained. Accordingly, the possible errors of IOL tilt and decentration existed in the method employed by AS-OCT instrument. Based on 6–12 pieces of AS-OCT images at different directions, the tilt angle and decentration values were shown, respectively. The method of the surface fitting to the IOL surface can accurately analyze the IOL’s location, and six pieces of AS-OCT images at three pairs symmetrical directions are enough to get tilt angle and decentration value of IOL more precisely

Effects of Layering Milling Technology on Dough Properties of Highland Barley and Bread Qualities

Highland barley (Qingke) is rich in nutrients and has the nutrient composition of “three highs and two lows,” which are high vitamin, high soluble dietary fiber, high β-glucan, low fat, and low sugar. In this paper, it was proposed to remove the layers of different ratios with different peeling rates. Then, different peeled highland barley was milled into flour and added to bread flour in the same proportion to make wheat-highland barley bread. The results showed that the removal of the cortex of highland barley flour was beneficial to its fermentation characteristics, the comprehensive capacity of gas production and gas holding has been improved, and the maximum fermentation height and retention coefficient were both at QK2-35%, while the gas production at QK4-35% is higher than other samples. From QK0-35% to QK5-35%, the  significance of the highland barley bread increased, from 56.31 to 70.88. The results showed that choosing QK4-35% as the best peeling rate of highland barley flour blends could not only retain the nutritional value of highland barley bread but also optimize the quality of bread to a certain extent, which could attract consumers and has a good development prospect