The experience of law enforcement officers interfacing with suspects who have an intellectual disability : A systematic review
تجربه مامورین اجرای قانون با مظنونینی که ناتوانی ذهنی دارند: بررسی منظم-2020
There is a high prevalence of people with intellectual disability (ID) among those in police custody. Consequently, law enforcement officers (LEOs) at the frontline of the criminal justice system are commonly required to interact with people who have ID. Notwithstanding the frequency of these interactions, research indicates that police exchanges with persons with ID frequently take place against a backdrop of tenuouslyresourced disability awareness training. At the time of writing, a paucity of research data exists with respect to the experiences of LEOs operating within this training vacuum at an international level. A better understanding of their experiences could meaningfully inform research, training and improve support programmes for LEOs. We systematically reviewed six databases to identify studies published up to 1st December 2019 reporting the experience of LEOs interfacing with suspects who have an ID. Following a review of 670 abstracts, 16 studies were identified from five countries involving 983 LEOs. LEOs identified 1) a need for specialised training; 2) challenges in identifying people with ID; 3) a need to improve safeguards and 4) challenges in supporting/ communicating with individuals who have ID through the investigation process.
Keywords: Intellectual disabilities | Police | Law enforcement officer | Vulnerability | United Nations convention on the rights of | persons with disabilities
Security-preserving social data sharing methods in modern social big knowledge systems
روشهای به اشتراک گذاری داده های اجتماعی حفظ سیستم در سیستم های دانش اجتماعی بزرگ مدرن-2020
In recent decades, the development of social computing systems has realized the efficient information exchange between large groups of people. Nowadays, social computing sys- tems are rather complex platforms supported by not only traditional sociology theory but also computer science and big data based applications. With the increase of the social computing systems’ complexities, serious issues of social digital security and privacy have shown up since, in recent years, more and more social data leakage incidents are happen- ing. This fact is due to reasons on many different aspects since there are many sources threatening the security and privacy of the social data in such a complex social comput- ing system. In this paper, we improve the traditional social data protection schemes by combining the information fragmentation concepts with the distributed system architec- tures to build a novel social data protection scheme. We use social photo protection as the fundamental scenario and deploy our novel scheme to illustrate the improvement on the protection level with the protection analysis in detail. A security analysis of practically realizing such a scheme is also evaluated in this paper.
Keywords: Data security | Social computing | Big knowledge | Selective encryption
Comparative study on the annual performance between loop thermosyphon solar water heating system and conventional solar water heating system
بررسی مقایسه ای عملکرد سالانه بین سیستم گرمایش آب خورشیدی حلقه ترموسیفون و سیستم گرمایش آب خورشیدی معمولی-2020
Loop thermosyphon (LT) is usually introduced to overcome the freezing and corrosion problems associated with the conventional solar water heating (SWH) system. Compared with the conventional SWH system, the LT-SWH system possesses a lower nighttime heat loss because of the thermal diode property of loop thermpsyphon but bigger daytime heat loss because of the secondary heat exchange. However, the effect of above interaction to the system performance is rarely reported based on long-term running. In this study, based on the typical meteorological year data of Fuzhou city, annual performances of above two systems, including the effective number of supplying days, effective heat gain and nighttime heat loss, are comparatively analyzed under two different operational modes. Variations of above mentioned variables with the increment in the set temperature are discussed. The results indicate that, under the discontinuous heating mode, the effective numbers of supplying days of SWH system and LT-SWH system are 139 and 153, respectively. While the numbers of days are respectively 168 and 173 under the continuous heating mode. The SWH system possesses an expected bigger nighttime heat loss ratio with an average annual value of 15.07% corresponding to 6.15% for the LT-SWH system. Particularly, for the LT-SWH system, the different relative magnitudes of heat loss coefficients functioning at different times leads to a smaller temperature drop at night and also a smaller temperature rise at the subsequent day. It generates an unanticipated results that corresponds to the same month from November to April, the two systems have the approximate effective heat gain. The set temperature significantly influences the relative magnitudes of annual effective number of supplying days and annual effective heat gain, the superiority of LT-SWH system gradually diminishes and even reverses with the increment in the set temperature. The bigger daytime heat loss dominating the dominance is responsible for that transition. Combining with a longer static payback period, it is conditional to substitute the conventional SWH system with the LT-SWH system, especially when the water temperature on demand is high.
Keywords: Solar water heating system | Loop thermosyphon solar water heating system | Typical meteorological year | Effective heat gain | Nighttime heat loss
Optimized energy management strategy for grid connected double storage (pumped storage-battery) system powered by renewable energy resources
استراتژی مدیریت انرژی بهینه سازی شده برای سیستم ذخیره دوگانه متصل به شبکه (پمپ باتری ذخیره شده) که از منابع انرژی تجدید پذیر استفاده می شود-2020
This paper presents a grid-connected double storage system (DSS) consisting of pumped-storage hydropower (PSH) and battery. The system is supplied by photovoltaics and wind turbines. In the proposed hybrid system, batteries absorb excess renewable energy that cannot be stored in PSH and they cover loads that cannot be supplied from the water turbine. To improve the system performance, a novel energy management strategy for the DSS is proposed. The strategy is based on an optimized factor that governs the charging process of the DSS. The problem of the optimal system design is solved by a nondominated sorting genetic algorithm (NSGA-II). The multi-objective function considers simultaneously the minimal investment cost and minimal CO2 emissions. A comparative study of photovoltaic/wind/ pumped-storage hydropower and photovoltaic/wind/double storage system is performed to show the effectiveness of the proposed strategy in terms of system economic and environmental performance. The considered location of the PSH station is on Attaqa Mountain at Suez (Egypt). The results indicate the effectiveness of the proposed energy management strategy for the storage system from economic and environmental perspectives. Coupling the battery with the PSH reduces the electricity cost by 22.2% and results in minimal energy exchange with the national grid (5% of the annual demand). A sensitivity analysis shows the largest variation of the electricity cost with changing the capital cost of the solar and wind generators. Also, it is observed that when the load increases, the optimal size of the system components increases, but it isn’t proportional with the demand increase as could be expected.
Keywords: Pumped-storage hydropower | Battery | Double storage system | Renewable energy sources | NSGA-II | Hybrid energy system
Ecological and environmental consequences of ecological projects in the Beijing–Tianjin sand source region
پیامدهای محیطی و زیست محیطی از پروژه های زیست محیطی در منطقه منبع شن و ماسه پکن - تیانجین-2020
Evaluation of influences of the Beijing–Tianjin Sand Source Control Project on soil wind erosion and ecosystem services is imperative for mastering the benefits and drawbacks of the program, as well as for distinguishing more reasonable estimations to evaluate regional sustainable development. Within the Beijing–Tianjin Sand Source Region, we quantified the spatiotemporal patterns of land use/cover changes (LUCCs), soil wind erosion modulus (SWEM), and essential ecosystem services throughout 2000–2015 by utilizing field investigations, remotely sensed data, meteorological data, and modeling. The influences of ecological projects on wind erosion and ecosystem services has been subsequently assessed by using those modifications brought on via the LUCCs (e.g., conversion from cropland to grassland/woodland) during the ecological construction. The results indicated that the SWEM showed a decline and ecosystem services which included carbon storage, water retention, and air quality regulation exhibited growth driven by using both local climate exchanges and human activities such as ecological projects. Excluding the effects of climate factors, the LUCCs stemming from ecological projects caused a total SWEM decrease of 3.77 million tons during 2000–2015, of which approximately 70% was prompted by the way of the transition from desert to sparse grassland. And from this transition, ecosystem services including both water retention and aboveground net primary productivity manifest a general increase. The sub-regions of desert grassland in Bayannur, Ordos Sandy Land, and Otindag Sandy Land were hot spots for wind erosion declines and ecosystem service enhancements induced by the ecological projects. We recommend that endeavors be coordinated toward the scientific management of the degraded lands and distribution of the local populace, as well as the implementation of diverse measures in the expected hotter and drier future.
Keywords: Wind erosion Ecosystem services | Sustainability | Spatiotemporal pattern | Land use/cover change | Ecological project
Decoding earth’s plate tectonic history using sparse geochemical data
رمزگشایی تاریخ زمین ساختی صفحه با استفاده از داده های نادر ژئوشیمیایی-2020
Accurately mapping plate boundary types and locations through time is essential for understanding the evolution of the plate-mantle system and the exchange of material between the solid Earth and surface environments. However, the complexity of the Earth system and the cryptic nature of the geological record make it difficult to discriminate tectonic environments through deep time. Here we present a new method for identifying tectonic paleo-environments on Earth through a data mining approach using global geochemical data. We first fingerprint a variety of present-day tectonic environments utilising up to 136 geochemical data attributes in any available combination. A total of 38301 geochemical analyses from basalts aged from 5e0 Ma together with a well-established plate reconstruction model are used to construct a suite of discriminatory models for the first order tectonic environments of subduction and mid-ocean ridge as distinct from intraplate hotspot oceanic environments, identifying 41, 35, and 39 key discriminatory geochemical attributes, respectively. After training and validation, our model is applied to a global geochemical database of 1547 basalt samples of unknown tectonic origin aged between 1000 e410 Ma, a relatively ill-constrained period of Earth’s evolution following the breakup of the Rodinia supercontinent, producing 56 unique global tectonic environment predictions throughout the Neoproterozoic and Early Paleozoic. Predictions are used to discriminate between three alternative published Rodinia configuration models, identifying the model demonstrating the closest spatio-temporal consistency with the basalt record, and emphasizing the importance of integrating geochemical data into plate reconstructions. Our approach offers an extensible framework for constructing full-plate, deeptime reconstructions capable of assimilating a broad range of geochemical and geological observations, enabling next generation Earth system models..
Keywords: Plate tectonics | Geochemistry | Geodynamics | Supercontinents | Rodinia | Big data
Research on the application of block chain big data platform in the construction of new smart city for low carbon emission and green environment
تحقیق در مورد کاربرد بستر داده های بزرگ بلاک چین در ساخت شهر هوشمند جدید برای انتشار کربن کم و محیط سبز-2020
The sharing of government information resources is significant for improving the level of governance and social information. However, due to the existence of cross-domain security and trust islands, government departments are hindering the sharing of government information resources with other organizations and the public. To this end, the blockchain technology is used to construct a decentralized distributed peer-to-peer trust service system, which is integrated with the existing PKI/CA security system to establish a new trust model that supports multi-CA coexistence. Based on this, the structural composition and functional data flow of the blockchain smart city information resource sharing and exchange model designed in this paper. This paper launched a study on the role of the smart big data platform, and selected the development of smart cities in Hefei as an empirical analysis. From the connotation of smart city, block chain and big data technology combined, and the positive effects of relevant information technology summarized on the construction of smart city big data platform. Based on this, the smart city development level evaluation model of TOPSIS method constructed. The evaluation model constructed to make a vertical comparison from 2012 to 2017, the scale of smart cities is growing at an average annual rate of more than 30%, saving 20% of urban resource allocation and becoming a new pillar industry. Therefore, Hefei City should further increase environmental supervision and promote the use of low-carbon environmental protection new energy. The improvement of government management level has a positive effect on the construction of smart Hefei
Keywords: Block chain | PKI/CA | New smart city | Government information
Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework
مدیریت انرژی بهینه برای برنامه های پاسخ تقاضا با توجه به برنامه های چند ریز شبکه : یک چارچوب تصادفی چند هدف-2020
This paper presents a cooperative multi-objective optimization for the networked microgrids energy management. We introduce the Independence Performance Index (IPI) for the MGs to reduce energy exchange with the main grid. The system losses, voltage drop, and greenhouse gas emissions are improved when the independence of MMG is increased. Besides, the MMG operator seeks to reduce its total daily costs. For this reason, MGs can participate in Demand Response Programs (DRPs). MGs have two types of loads, namely flexible and inflexible loads. The flexible loads can response to price signals and participate in the DR Programs. The uncertainty of renewable generation is modeled as a stochastic optimization that a scenario generation and reduction decision-making method is employed. This stochastic multi-objective optimization is solved by Compromised Program (CP) method that is used to combine non-homogeneous objective functions. This technique converts the original multi-objective problem into a single-objective problem. The proposed model is tested on a standard case study for two different conditions. The simulation results show the proposed model improves CO2 emission about 13.4 and 9.2% in the case studies. Besides, the proposed model brings 17 and 11.7% improvements for the independence of MMG in the case studies.
Keywords: Demand response programs | Independence performance index | Multi-objective optimization | Multi-microgrid
Implementation of sensor based on neural networks technique to predict the PEM fuel cell hydration state
اجرای حسگر بر اساس تکنیک شبکه های عصبی برای پیش بینی وضعیت هیدراتاسیون سلول سوختی PEM-2020
Proton exchange hydrogen fuel cells have the potential to produce clean and environmentally friendly energy. However, this technique should be adapted to technical challenges, such as performance and durability prior to its marketing. These challenges are closely related to water management. In this research, a PEM fuel cell simulation model was designed for water management. This model consisted of a voltage evolution model based on electrochemical and dynamics gases. It also comprised a model of water activity to estimate the relative humidity. Meanwhile, in identifying the PEMFC hydration state, impedance was estimated by the humidity sensor model, which was based on neural network technology for diagnosis. This model predicted the changes of behaviour in the step response of load demand and the rate of water which flowed into the fuel cell. In the case of flooding or drying, the proposed neural network sensor model was executed through the estimation of internal resistance and biasing resistance values at high and low frequencies. These frequencies corresponded to the model of PEMFC electrical performance. As a result, it was found that the efficacy of this new neural network sensor model led to improved PEMFC hydration and a controlled humid airflow in the fuel cell. Overall, it was indicated that the proposed model can be used in the control system to improve water management by adjusting the relative humidity of supplied air.
Keywords: PEMFC | Neural networks | Sensor model | Flooding | Drying
Interorganizational cooperation and supplier performance in high-technology supply chains
همکاری بین سازمانی و عملکرد تأمین کننده در زنجیره های تأمین فن آوری بالا-2020
Never in history have global supply-chain relationships in high-tech electronics firms been more sophisticated, complicated, and almost always tied in some major aspect to China. This research examines how interorganizational (IO) cooperation impacts performance and what role relationship learning and information technology (IT) integration play in the value-creation process for Chinese suppliers in business-to-business (B2B) supply chains. We examine this issue using data collected from face-to-face interviews with supply chain managers and executives from 1,004 Chinese high-tech electronic component suppliers. The results strongly support the hypothesis that IO cooperation improves a suppliers performance regarding both its major customer and overall marketplace. Relationship learning and IT integration are important mediating variables that drive performance. The strongest effect in our study was the influence of IO cooperation on relationship learning. A unique aspect of this study is that it focuses on a large sample of a specific supplier type—high-tech Chinese suppliers. This, combined with the fact that the sampled companies were involved in manufacturing 13 different product groups, greatly increases the generalizability of the results.
Keywords: Supply chain performance | Buyer-supplier relationships | Relationship marketing theory | Social exchange theory | Collaboration | Electronics industry | Global supply chain | Business | Globalization | Operations management | Technology adoption | Technology management