دانلود و نمایش مقالات مرتبط با the Netherlands::صفحه 1
بلافاصله پس از پرداخت دانلود کنید

با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد). 

نتیجه جستجو - the Netherlands

تعداد مقالات یافته شده: 57
ردیف عنوان نوع
1 Monitoring crop phenology with street-level imagery using computer vision
پایش فنولوژی محصول با تصاویر سطح خیابان با استفاده از بینایی ماشین-2022
Street-level imagery holds a significant potential to scale-up in-situ data collection. This is enabled by combining the use of cheap high-quality cameras with recent advances in deep learning compute solutions to derive relevant thematic information. We present a framework to collect and extract crop type and phenological information from street level imagery using computer vision. Monitoring crop phenology is critical to assess gross primary productivity and crop yield. During the 2018 growing season, high-definition pictures were captured with side- looking action cameras in the Flevoland province of the Netherlands. Each month from March to October, a fixed 200-km route was surveyed collecting one picture per second resulting in a total of 400,000 geo-tagged pictures. At 220 specific parcel locations, detailed on the spot crop phenology observations were recorded for 17 crop types (including bare soil, green manure, and tulips): bare soil, carrots, green manure, grassland, grass seeds, maize, onion, potato, summer barley, sugar beet, spring cereals, spring wheat, tulips, vegetables, winter barley, winter cereals and winter wheat. Furthermore, the time span included specific pre-emergence parcel stages, such as differently cultivated bare soil for spring and summer crops as well as post-harvest cultivation practices, e.g. green manuring and catch crops. Classification was done using TensorFlow with a well-known image recognition model, based on transfer learning with convolutional neural network (MobileNet). A hypertuning methodology was developed to obtain the best performing model among 160 models. This best model was applied on an independent inference set discriminating crop type with a Macro F1 score of 88.1% and main phenological stage at 86.9% at the parcel level. Potential and caveats of the approach along with practical considerations for implementation and improvement are discussed. The proposed framework speeds up high quality in-situ data collection and suggests avenues for massive data collection via automated classification using computer vision.
keywords: Phenology | Plant recognition | Agriculture | Computer vision | Deep learning | Remote sensing | CNN | BBCH | Crop type | Street view imagery | Survey | In-situ | Earth observation | Parcel | In situ
مقاله انگلیسی
2 Ecosystem accounting to support the Common Agricultural Policy
حسابداری اکوسیستم برای حمایت از سیاست های کشاورزی مشترک-2021
The System of Environmental-Economic Accounting - Ecosystem Accounting (SEEA EA) provides an integrated statistical framework which organizes spatially explicit data on environmental quality, natural capital and ecosystem services and links this information to economic activities such as agriculture. In this paper we assess how the SEEA EA can support the monitoring and evaluation of environmental objectives of the Common Agricultural Policy (CAP). We focus on the Netherlands, for which an elaborate set of SEEA EA accounts has been published, and the themes of nitrogen pollution and farmland biodiversity. We studied the completeness of in- dicators included in the accounts, their quality and analysed how the accounts could support agri-environmental reporting, agri-environmental measures effectiveness assessments, and results-based payments to farmers. As a reference we used the Driving forces – Pressures – State – Impacts - Responses (DPSIR) framework. The Dutch SEEA EA accounts only include half of the indicators which we considered essential to assess the effects of farming on natural capital and ecosystem services for the two studied environmental themes. However, most gaps in the accounts could be filled with other publicly available environmental monitoring data. Regarding N pollution, the availability and reliability of indicators at landscape and farm scales are not sufficient to support the assessment of agri-environmental measures effectiveness and results-based payments to decrease N pollution. The accounts have a higher potential to support the assessment of measures to conserve farmland biodiversity, in particular due to high resolution maps of ecosystem extent and ecosystem services flows. The potential of the SEEA EA accounts may be more limited in other countries where ecosystem accounting has only recently started. However, the SEEA EA is also implemented at the European Union scale, so that SEEA EA indicators will gradually become available for all European countries. To enhance the relevance of the SEEA EA in the agri- environmental policy area, we recommend to integrate information on farming emissions (externalities) recor- ded in the SEEA Central Framework with SEEA EA accounts and evaluate the applicability of SEEA EA accounts for case studies at landscape and farm scales. Our research shows that the Dutch SEEA EA accounts, com- plemented with other data sources, have potential to strongly enhance the CAP monitoring and evaluation framework but further steps need to be taken to fill data gaps.
keywords: اقدامات زیست محیطی | کلاه لبه دار | رادیو | پایتخت طبیعی | خدمات محیط زیستی | زمینه های کشاورزی | Agri-environment measures | CAP | SEEA EA | Natural capital | Ecosystem services | Farming externalities
مقاله انگلیسی
3 Image-based body mass prediction of heifers using deep neural networks
پیش بینی توده بدن مبتنی بر تصویر تلیسه ها با استفاده از شبکه های عصبی عمیق-2021
Manual weighing of heifers is time-consuming, labour-intensive, expensive, and can be dangerous and risky for both humans and animals because it requires the animal to be stationary. To overcome this problem, automated approaches have been developed using computer vision techniques. In this research, the aim was to design a novel mass prediction model using deep learning algorithms for youngstock on dairy farms. The MaskRCNN segmentation algorithm was used to segment the images of heifers and remove the background. A convolutional neural networks (CNN) model was developed on the Keras platform to predict the body mass of heifers. For the case study, a new dataset based on images of 63 heifers was built. Animals were between the age of 0 and 365 days and lived on the same farm in the Netherlands. The range of body mass of the heifers was between 37 kg and 370 kg. The side-view model had a coefficient of determination (R2) of 0.91 and a Root Mean Squared Error (RMSE) of 27 kg, the top-view model had an R2 of 0.96 and an RMSE of 20 kg. The experimental results demonstrated that our proposed mass prediction model using the Mask-RCNN segmentation algorithm, together with a novel CNN-based model, provided remarkable results, and that the top view was more suitable than the side view for predicting the body mass of youngstock in dairy farms.
Keywords: Deep learning | Computer vision | Body weight prediction | Convolutional neural network
مقاله انگلیسی
4 Multidisciplinary and Interdisciplinary Teaching in the Utrecht AI Program: Why and How?
آموزش چند رشته ای و میان رشته ای در برنامه هوش مصنوعی Utrecht : چرا و چگونه؟-2020
MULTIDISCIPLINARY AND INTERDISCIPLINARY education can provide relevant insights into ubiquitous computing and other fields.1 In this article, we share our experience with multidisciplinary and interdisciplinary teaching in the twoyear Artificial Intelligence Research Master’s program at Utrecht University, the Netherlands. In particular, we zoom in on our motivation for, and experience with, revising courses in which nonengineering topics can be related to a more engineering inclined audience, and vice-versa.
مقاله انگلیسی
5 Using reinforcement learning for maximizing residential self-consumption - Results from a field test
استفاده از یادگیری تقویتی برای به حداکثر رساندن خود مصرفی مسکونی - نتایج یک آزمون میدانی-2020
This paper presents the results from a real residential field test in which one of the objectives was to maximize the instantaneous self-consumption of the local photovoltaic production. The field test was part of the REnnovates project and was conducted in different phases on houses in several residential districts located in Soesterberg, Heerhugowaard, Woerden and Soest, the Netherlands. To maximize self- consumption, buffered heat pump installations for domestic hot water and stationary residential battery systems were chosen due to their respective thermal and electrical storage capacities. The algorithm used to tackle the associated sequential decision-making problem was model-based reinforcement learning. The proposed algorithm learns the stochastic occupant behavior, uses predictions of local photovoltaic production and considers the dynamics of the system. The results show that this algorithm increased the average self-consumption percentage of the local PV generation (used instantaneously in situ ) on average by 14%, even if only buffered heat pump installations for domestic hot water were used. This increase was achieved without causing any perceived discomfort to the residential end users. The average energy shifted per day from the solar production period to the night by the 2 kW/3.6 kWh batteries was 1.5 kWh. The main contribution of this work was therefore the real field implementation of the proposed algorithm. The results demonstrate that it is possible to improve even further the integration of local production using flexible loads.
Keywords: Reinforcement learning | Q-Learning | Field test | Solar PV generation | Thermal storage | Thermostatically controlled loads | Electrical storage | Battery | Residential loads
مقاله انگلیسی
6 Coercive interventions under the new Dutch mental health law: Towards a CRPD-compliant law?
مداخلات قهری تحت قانون جدید سلامت روان هلند: به سوی قانون منطبق با CRPD؟-2020
The Netherlands became State Party to the United Nation Convention on the Rights of Persons with Disabilities (CRPD) in 2016, a treaty that holds great promise for promoting and protecting human rights of persons with mental disorders. Yet, the Dutch government also made explicit reservations to the Convention. On 1 January 2020, the Netherlands introduced a new mental health law, the Compulsory Mental Health Care Act (CMHCA), which aims to strengthen the legal status of persons with psychiatric illnesses. To which extent does the new Dutch mental health law comply with the regulations as outlined in the CRPD? In this article, we examine how coercive interventions, specifically the elements of competence, involuntary treatment and involuntary admis- sion are regulated in the domestic legislation and compare them to the CRPD approach. A normative analysis combined with literature review helps to understand the law, reveal the gaps and uncover the barriers that remain. Is there a need to reassess the domestic legal provisions allowing for coercive treatment, and if so, what advancements are required? After all, should the CRPD be strictly adhered to at all times?
Keywords: CRPD | Mental health legislation | Capacity | Psychiatric coercion | Coercive interventions
مقاله انگلیسی
7 Legal Remedies For a Forgiving Society: Children’s rights, data protection rights and the value of forgiveness in AI-mediated risk profiling of children by Dutch authorities
راه حل های قانونی برای یک جامعه بخشنده: حقوق کودکان ، حقوق محافظت از داده ها و ارزش بخشش در مشخصات ریسک کودکان با استفاده از هوش مصنوعی توسط مقامات هلندی-2020
30 years after the United Nations Convention on the Right of the Child (CRC) and two years after the new EU data protection regime, the social value of forgiveness is not part of these legal instruments. The lack of this value within these legal instruments and the lack of re- search on the subject of forgiveness in relation to improving the legal position of children require urgent addressing especially when children are exposed to artificial intelligence (AI)- mediated risk profiling practices by Dutch government authorities. Developmental psychol- ogists underline that the erosion of this value could hamper children’s ability to develop flourishing human relationships. This article contributes to fill this niche. It investigates how this value can be enforced in order to benefit children below the age of 12 years that are exposed to risk profiling by Dutch law enforcement and youth care authorities. Children who are victims, witnesses, or falsely accused provide a particular narrowing of focus in this article as these groups cannot be held responsible for their correlations to crime. Strengthening children’s legal position is crucial because their position is much weaker compared to adults when it comes to question a risk correlation about themselves. These children correlated to crime, as this paper argues, not only can feel unjustifiably punished, ‘unforgiven’, and hampered in their choices, but can also develop low self-worth and (negative) judgmental attitudes towards others. Based on input from developmental psychology, empirical material, and legal desk research, this article seeks to answer: What remedies can the Law Enforcement Directive (LED) 2016/680, the General Data Protection Regulation (GDPR), and the United Nations Convention on the Right of the Child (CRC) offer against the detrimental implications of risk profiling children by the ProKid 12- SI system and the Crime Anticipation System (CAS) in The Netherlands? How can the social value of forgiveness strengthen these instruments and the legal position of children in light of security interests and the best interests of the child? The analysis concludes that the CRC offers the broadest room for incorporating the principle of forgiveness into balancing tests, but certain LED and GDPR prescriptions could also support the value of forgiveness for children, such as the right to erasure. The analysis concludes that incorporating forgiveness into the mentioned legal instruments would not only benefit individual children but would also foster public safety as a result.
Keywords: Forgiveness | Risk profiles | Children rights | Data protection | AI | Correlations
مقاله انگلیسی
8 Self-binding directives under the new Dutch Law on Compulsory Mental Health Care: An analysis of the legal framework and a proposal for reform
دستورالعمل های خودالزام آور تحت قانون جدید هلند در مورد مراقبت اجباری بهداشت روان: تجزیه و تحلیل چارچوب قانونی و پیشنهادی برای اصلاح-2020
Self-binding directives (SBDs) are a special type of psychiatric advance directive by means of which mental health service users can give advance consent to compulsory hospital admission or treatment during a future mental health crisis. SBDs are legally binding in the Netherlands since 2008. On the 1st of January 2020, the Dutch Law on Special Admissions to Psychiatric Hospitals (Wet bijzondere opnemingen in psychiatrische zie- kenhuizen; Bopz) was replaced by the new Law on Compulsory Mental Health Care (Wet verplichte geestelijke gezondheidszorg; Wvggz). This replacement brought with it various changes in the legal arrangement for SBDs. In this article, we expound the changes in the legal arrangement and assess the implications of these changes for the practical feasibility of SBDs. We argue that the procedures for arranging compulsory care based on an SBD in the new law are too complex and time-intensive for SBDs to yield their potential benefits. We close by proposing a workable mechanism of legal authorisation of compulsory care on the basis of an SBD.
Keywords: Self-binding directive | Ulysses contract | Psychiatric advance directive | The Netherlands | Wvggz | Coercion | Compulsory admission | Involuntary treatment | Psychiatry
مقاله انگلیسی
9 Data protection law beyond identifiability? Atmospheric profiles, nudging and the Stratumseind Living Lab
قانون حفاظت از داده ها فراتر از قابلیت شناسایی؟ پروفایل های جوی، تلنگر زدن و آزمایشگاه زنده Stratumseind-2020
The deployment of pervasive information and communication technologies (ICTs) within smart city initiatives transforms cities into extraordinary apparatuses of data capture. ICTs such as smart cameras, sound sensors and lighting technology are trying to infer and affect persons’ interests, preferences, emotional states, and behaviour. It should be no surprise then that contemporary legal and policy debates on privacy in smart cities are dominated by a debate focused on data and, therefore, on data protection law. In other words, data protection law is the go-to legal framework to regulate data processing activities within smart cities and similar initiatives. While this may seem obvious, a number of important hurdles might prevent data protection law to be (successfully) applied to such initiatives. In this contribution, we examine one such hurdle: whether the data processed in the context of smart cities actually qualifies as personal data, thus falling within the scope of data protection law. This question is explored not only through a theoretical discussion but also by taking an illustrative example of a smart city-type initiative – the Stratumseind 2.0 project and its living lab in the Netherlands (the Stratumseind Living Lab; SLL). Our analysis shows that the requirement of ‘identifiability’ might be difficult to satisfy in the SLL and similar initiatives. This is so for two main reasons. First, a large amount of the data at stake do not qualify as personal data, at least at first blush. Most of it relates to the environment, such as, data about the weather, air quality, sound and crowding levels, rather than to identified or even likely identifiable individuals. This is connected to the second reason, according to which, the aim of many smart city initiatives (including the SLL) is not to identify and target specific individuals but to manage or nudge them as a multiplicity – a combination of the environment, persons and all of their interactions. This is done by trying to affect the ‘atmosphere’ on the street. We thus argue that a novel type of profiling operations is at stake; rather than relying on individual or group profiling, the SLL and similar initiatives rely upon what we have called ‘atmospheric profiling’. We conclude that it remains highly uncertain, whether smart city initiatives like the SLL actually process personal data. Yet, they still pose risks for a wide variety of rights and freedoms, which data protection law is meant to protect, and a need for regulation remains.
Keywords: Data protection | Personal data | Smart city | Profiling | Nudging | Stratumseind
مقاله انگلیسی
10 Co-ownership shares in condominium : A comparative analysis for selected civil law jurisdictions
سهام مالکیت مشترک در آپارتمان: یک تحلیل مقایسه ای برای حوزه های قضایی منتخب قانون مدنی-2020
Condominium is a special and relatively new type of property right emerged in the last century to be a remedy for the management problems in multi-unit buildings. There are many types of condominium regimes, as described in EUI (2005), UNECE (2005) and van der Merwe (2016). The common elements include: (a) Individual right to an apartment, (b) co-ownership (joint ownership) of the common property or the whole property, and (c) membership of an incorporated or unincorporated owners association (van der Merwe, 2015, p. 5). The ownership shares in the common property are here referred to as co-ownership shares; yet, alternative terms include ownership fraction, condominium share, participation quota, share value, and unit entitlement. Generally, these shares will determine the proportional contribution to the common expenses and the share of common profits, as well as the voting power of each condominium unit owner in the administration of the condominium. The most common approaches to the determination of the co-ownership shares are based on equality, relative size or relative value of each condominium unit, or a combination of such (van der Merwe, 1994, p. 57–58). The literature presents detailed descriptions and comparative analysis related to condominium systems in different jurisdictions (e.g. van der Merwe, 2015; 2016; Paulsson, 2007; EUI, 2005; UNECE, 2005); however, the procedural aspects related to the allotment of co-ownership shares still need to be further investigated. This article aims to describe condominium systems in the Netherlands, Sweden and Turkey, and compare legal provisions and procedures related to the allotment of co-ownership shares in these jurisdictions. The main purpose is to clarify the methodologies behind the determination of the co-ownership shares in national systems to bring new insights to countries, which are trying to revise their national provisions.
Keywords: Condominium | Co-ownership share | Ownership fraction | Participation quota | Share value | Unit entitlement
مقاله انگلیسی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 624 :::::::: بازدید دیروز: 0 :::::::: بازدید کل: 624 :::::::: افراد آنلاین: 45