Search results for: systems integration

Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee

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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems

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Authors: Ramazan Bakir, Gizem Kayar

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It is known that Alzheimer and Dementia are the two most common types of Neurodegenerative diseases and their visibility is getting accelerated for the last couple of years. As the population sees older ages all over the world, researchers expect to see the rate of this acceleration much higher. However, unfortunately, there is no known pharmacological cure for both, although some help to reduce the rate of cognitive decline speed. This is why we encounter with non-pharmacological treatment and tracking methods more for the last five years. Many researchers, including well-known associations and hospitals, lean towards using non-pharmacological methods to support cognitive function and improve the patient’s life quality. As the dementia symptoms related to mind, learning, memory, speaking, problem-solving, social abilities and daily activities gradually worsen over the years, many researchers know that cognitive support should start from the very beginning of the symptoms in order to slow down the decline. At this point, life of a patient and caregiver can be improved with some daily activities and applications. These activities include but not limited to basic word puzzles, daily cleaning activities, taking notes. Later, these activities and their results should be observed carefully and it is only possible during patient/caregiver and M.D. in-person meetings in hospitals. These meetings can be quite time-consuming, exhausting and financially ineffective for hospitals, medical doctors, caregivers and especially for patients. On the other hand, digital support systems are showing positive results for all stakeholders of healthcare systems. This can be observed in countries that started Telemedicine systems. The biggest potential of our system is setting the inter-user communication up in the best possible way. In our project, we propose Machine Learning based digitalization of validated traditional cognitive tests (e.g. MOCA, Afazi, left-right hemisphere), their analyses for high-quality follow-up and communication systems for all stakeholders. R. Bakir and G. Kayar are with Gefeasoft, Inc, R&D – Software Development and Health Technologies company. Emails: ramazan, gizem @ gefeasoft.com This platform has a high potential not only for patient tracking but also for making all stakeholders feel safe through all stages. As the registered hospitals assign corresponding medical doctors to the system, these MDs are able to register their own patients and assign special tasks for each patient. With our integrated machine learning support, MDs are able to track the failure and success rates of each patient and also see general averages among similarly progressed patients. In addition, our platform also supports multi-player technology which helps patients play with their caregivers so that they feel much safer at any point they are uncomfortable. By also gamifying the daily household activities, the patients will be able to repeat their social tasks and we will provide non-pharmacological reminiscence therapy (RT – life review therapy). All collected data will be mined by our data scientists and analyzed meaningfully. In addition, we will also add gamification modules for caregivers based on Naomi Feil’s Validation Therapy. Both are behaving positively to the patient and keeping yourself mentally healthy is important for caregivers. We aim to provide a therapy system based on gamification for them, too. When this project accomplishes all the above-written tasks, patients will have the chance to do many tasks at home remotely and MDs will be able to follow them up very effectively. We propose a complete platform and the whole project is both time and cost-effective for supporting all stakeholders.

Keywords: alzheimer’s, dementia, cognitive functionality, cognitive tests, serious games, machine learning, artificial intelligence, digitalization, non-pharmacological, data analysis, telemedicine, e-health, health-tech, gamification

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Authors: Carmen Pena-Díaz

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Linguistic and cultural difficulties regarding the access and use of public services, as well as facilitating communication at all levels, are problems which have not yet been tackled by authorities in Spain. In fact, linguistic and cultural issues are often not recognised as an integral part of migratory movements or social integration. While professionals of interlinguistic and intercultural communication (translators, interpreters, mediators) know that language and culture are key components to achieve immigrant integration and consolidate a truly multilingual society, policymakers at local, national, or supranational levels do not always seem aware of the risks and costs of not providing interpreting and translation services, particularly those affecting the health of users. Regarding the services currently used to cover the communication-related needs between the non-Spanish speaking population and healthcare professionals, evidence proves that there are no effective provisions for communication problems at present in Spanish hospitals. An example that suggests the poor management of the situation in relation to the migrants’ access to public healthcare is the fact that relying on a family member (often a minor) in medical consultations is one of the main practices that affects communication. At present, most medical professionals will explain that in their consultations with migrants who do not speak Spanish, they ask them to bring along a family member or friend who speaks Spanish. In fact, an abundant body of literature describes situations in which family members, children, friends, or anyone who speaks or understands a language helps to break language barriers in hospitals, not only in Spain. It is not difficult to see the problems this may cause, from ethical issues to comprehension problems and misunderstandings. This paper will present the results of Narrative Inquiry from a sample of eight clinicians about their perceptions and experiences using child language brokers in their appointments with non-Spanish speaking families. The main aim is to collect information about child language brokering as recalled and perceived by clinicians who present CLB as a routine practice and express their concerns and worries about using children to convey negative news to their parents or family members.

Keywords: child language brokering, community interpreting, healthcare, PSIT

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Authors: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi

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Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.

Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process

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Authors: Mohamed Omar

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Steel bracing members are widely used in steel structures to reduce lateral displacement and dissipate energy during earthquake motions. Concentric steel bracing provide an excellent approach for strengthening and stiffening steel buildings. Using these braces the designer can hardly adjust the stiffness together with ductility as needed because of buckling of braces in compression. In this study the use of SMA bracing and steel bracing (Mega) utilized in steel frames are investigated. The effectiveness of these two systems in rehabilitating a mid-rise eight-storey steel frames were examined using time-history nonlinear analysis utilizing Seismo-Struct software. Results show that both systems improve the strength and stiffness of the original structure but due to excellent behavior of SMA in nonlinear phase and under compressive forces this system shows much better performance than the rehabilitation system of Mega bracing.

Keywords: finite element analysis, seismic response, shapes memory alloy, steel frame, mega bracing

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Authors: Alhasan Hakami, Arun Kumar, Sung J. Shim, Yousef Abu Nahleh

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In recent years, many high intensity earthquakes have occurred around the world, such as the 2011 earthquake in Tohoku, Japan. These large-scale disasters caused huge casualties and losses. In addition, inefficient disaster response operations also caused the second wave of casualties and losses, and expanded the damage. Effective disaster management can be used to respond to the chaotic situation, and reduce the damage. However, some inefficient disaster response operations are still used. Therefore, this case study chose the 921 earthquakes for analysing disaster emergency logistics problems and proposed the Soft Systems Methodology (SSM) to solve disaster emergency logistics problems. Moreover, it analyses the effect of human factors on system operation, and suggests a solution to improve the system.

Keywords: soft systems methodology, emergency logistics, earthquakes, Japan, system operation

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Yiwei Li, Boyu Tian, Mingyu Gao

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Hybrid main memory systems combine both performance and capacity advantages from heterogeneous memory technologies. With larger capacities, higher associativities, and finer granularities, hybrid memory systems currently exhibit significant metadata storage and lookup overheads for flexibly remapping data blocks between the two memory tiers. To alleviate the inefficiencies of existing designs, we propose Trimma, the combination of a multi-level metadata structure and an efficient metadata cache design. Trimma uses a multilevel metadata table to only track truly necessary address remap entries. The saved memory space is effectively utilized as extra DRAM cache capacity to improve performance. Trimma also uses separate formats to store the entries with non-identity and identity mappings. This improves the overall remap cache hit rate, further boosting the performance. Trimma is transparent to software and compatible with various types of hybrid memory systems. When evaluated on a representative DDR4 + NVM hybrid memory system, Trimma achieves up to 2.4× and on average 58.1% speedup benefits, compared with a state-of-the-art design that only leverages the unallocated fast memory space for caching. Trimma addresses metadata management overheads and targets future scalable large-scale hybrid memory architectures.

Keywords: memory system, data cache, hybrid memory, non-volatile memory

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Authors: Helge Rupprich, Elke Knisel

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In a time of mediazation and reduced physical movement, it is important to change passivity (akinesa) into physical activity to improve health. The approach is to encourage children, junior athletes, recreational athletes, and semi-professional athletes to do sports while attending a top sport event. The concept has the slogan: get out off your seat and move! A top sport event of a series of professional beach volleyball tournaments with 330.000 life viewers, 13,70 million cumulative reach viewers and 215,13 million advertising contacts is used as framework for different sports didactic approaches, social integrative approaches and migration valuations. An important aim is to use the big radiant power of the top sport event to extract active participants from the viewers of the top sport event. Even if it is the goal to improve physical activity, it is necessary to differentiate between the didactic approaches. The first approach contains psycho motoric exercises with children (N=158) between two and five years which was used in the project ‘largest sandbox of the city’. The second approach is social integration and promotion of activity of students (N=54) in the form of a student beach volleyball tournament. The third approach is activity in companies. It is based on the idea of health motivation of employees (N=62) in a big beach volleyball tournament. Fourth approach is to improve the sports leisure time activities of recreational athletes (N=292) in different beach volleyball tournaments. Fifthly approach is to build a foreign friendly measure which is implemented in junior athlete training with the French and German junior national team (N=16). Sixthly approach is to give semi professional athletes a tournament to develop their relation to active life. Seventh approach is social integration for disadvantaged people (N=123) in form of training with professional athletes. The top sport beach volleyball tournament had 80 athletes (N=80) and 34.000 viewers. In sum 785 athletes (N=785) did sports in 13 days. Over 34.000 viewers where counted in the first three days of top sport event. The project was evaluated positively by the City of Dresden, Politics of Saxony and the participants and will be continued in Dresden and expanded for the season 2015 in Jena.

Keywords: beach volleyball, event, sports didactic, sports project

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Authors: Sohail Bawani, Kausar S. Khan, Rozina Karmaliani, Shehnaz Mir

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Action research (AR) is one of the types of health systems research (HSR), and participatory action research (PAR) is known for being effective in health systems strengthening (HSS). The current literature on PAR for HSS cites numerous examples and case studies that led to improve health services; build child health information system; increase knowledge and awareness of people about health problems, and identify pathways for institutional and policy change by engaging people in research. But examples of marginalized communities being agents of change in health governance are not common in health systems research (HSR). This approach to PAR is at the heart of Paolo Freire’s Social Transformation Theory and Critical Consciousness building, which was used to design a community-based PAR study in the Northern/mountainous areas of Pakistan. The purpose of the study was to understand the place and role of marginalized communities in strengthening existing health governance structure (health facility and village health committees and health boards) by taking marginalized communities as partners. Community meetings were carried out to identify who is living at the social, political, cultural and economic margins in 40 different villages. Participatory reflection and analysis (PRA) tools were used during the meeting to facilitate identification. Focus group discussions were conducted with marginalized groups using PRA tools and family ethnographies with marginalized families identified through group discussions. Findings of the study revealed that for the marginalized health systems constitute more than just delivery of health services, but it also embraces social determinants that surround systems and its governance. The paper argues that from Frerian perspective people’s participation should not only be limited to knowledge generation. People must be seen active users of the knowledge that they generate for achieving better health outcomes that they want to achieve in the time to come. PAR provides a pathway to the marginalized in playing a role in health governance. The study dissemination planned shall engage the marginalized in a dialogue with service providers so that together a role for the marginalized can be outlined.

Keywords: participatory action research, health systems, marginalized, health services

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Authors: Kausar Harun, Ahmad Azmin Mohamad

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Zinc oxide (ZnO) has been extensively used in optoelectronic devices, with recent interest as photoanode material in dye-sensitize solar cell. Numerous methods employed to experimentally synthesized ZnO, while some are theoretically-modeled. Both approaches provide information on ZnO properties, but theoretical calculation proved to be more accurate and timely effective. Thus, integration between these two methods is essential to intimately resemble the properties of synthesized ZnO. In this study, experimentally-grown ZnO nanoparticles were prepared by sol-gel storage method with zinc acetate dihydrate and methanol as precursor and solvent. A 1 M sodium hydroxide (NaOH) solution was used as stabilizer. The optimum time to produce ZnO nanoparticles were recorded as 12 hours. Phase and structural analysis showed that single phase ZnO produced with wurtzite hexagonal structure. Further work on quantitative analysis was done via Rietveld-refinement method to obtain structural and crystallite parameter such as lattice dimensions, space group, and atomic coordination. The lattice dimensions were a=b=3.2498Å and c=5.2068Å which were later used as main input in first-principles calculations. By applying density-functional theory (DFT) embedded in CASTEP computer code, the structure of synthesized ZnO was built and optimized using several exchange-correlation functionals. The generalized-gradient approximation functional with Perdew-Burke-Ernzerhof and Hubbard U corrections (GGA-PBE+U) showed the structure with lowest energy and lattice deviations. In this study, emphasize also given to the modification of valence electron energy level to overcome the underestimation in DFT calculation. Both Zn and O valance energy were fixed at Ud=8.3 eV and Up=7.3 eV, respectively. Hence, the following electronic and optical properties of synthesized ZnO were calculated based on GGA-PBE+U functional within ultrasoft-pseudopotential method. In conclusion, the incorporation of Rietveld analysis into first-principles calculation was valid as the resulting properties were comparable with those reported in literature. The time taken to evaluate certain properties via physical testing was then eliminated as the simulation could be done through computational method.

Keywords: density functional theory, first-principles, Rietveld-refinement, ZnO nanoparticles

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Authors: H. Chabalala, A. Grootboom, M. Tang

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The innovative development, production, and clinical utilisation of African natural medicines requires frameworks from systematisation, innovation, registration. Afrika faces challenges when it comes to these sectors. The opposite is the case as is is evident in ancient Asian (Traditional Chinese Medicine and Indian Ayurveda and Siddha) medical systems, which are interfaced into their respective national health and educational systems. Afrikan Natural Medicines (ANMs) are yet to develop systematisation frameworks, i.e. disease characterisation and medicines classification. This paper explores classical medical systems drawn from Afrikan and Chinese experts in natural medicines. An Afrikological research methodology was used to conduct in-depth interviews with 20 key respondents selected through purposeful sampling technique. Data was summarised into systematisation frameworks for classical disease theories, patient categorisation, medicine classification, aetiology and pathogenesis of disease, diagnosis and prognosis techniques and treatment methods. It was discovered that ancient Afrika had systematic medical cosmologies, remnants of which are evident in most Afrikan cultural health practices. Parallels could be drawn from classical medical concepts of antiquity, like Chinese Taoist and Indian tantric health systems. Data revealed that both the ancient and contemporary ANM systems were based on living medical cosmologies. The study showed that African Natural Healing Systems have etiological systems, general pathogenesis knowledge, differential diagnostic techniques, comprehensive prognosis and holistic treatment regimes. Systematisation models were developed out of these frameworks, and this could be used for evaluation of clinical research, medical application including development of curriculum for high-education. It was envisaged that frameworks will pave way towards the development, production and commercialisation of ANMs. This was piloted in inclusive innovation, technology transfer and commercialisation of South African natural medicines, cosmeceuticals, nutraceuticals and health infusions. The central model presented here in will assist in curriculum development and establishment of Afrikan Medicines Hospitals and Pharmaceutical Industries.

Keywords: African Natural Medicines, Indigenous Knowledge Systems, Medical Cosmology, Clinical Application

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Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov

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We have conducted the optimal synthesis of root-mean-squared objective filter to estimate the state vector in the case if within the observation channel with memory the anomalous noises with unknown mathematical expectation are complement in the function of the regular noises. The synthesis has been carried out for linear stochastic systems of continuous-time.

Keywords: mathematical expectation, filtration, anomalous noise, memory

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Authors: Andrey V. Timofeev, Dmitry Egorov

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This paper describes an effective solution to the task of a remote monitoring of super-extended objects (oil and gas pipeline, railways, national frontier). The suggested solution is based on the principle of simultaneously monitoring of seismoacoustic and optical/infrared physical fields. The principle of simultaneous monitoring of those fields is not new but in contrast to the known solutions the suggested approach allows to control super-extended objects with very limited operational costs. So-called C-OTDR (Coherent Optical Time Domain Reflectometer) systems are used to monitor the seismoacoustic field. Far-CCTV systems are used to monitor the optical/infrared field. A simultaneous data processing provided by both systems allows effectively detecting and classifying target activities, which appear in the monitored objects vicinity. The results of practical usage had shown high effectiveness of the suggested approach.

Keywords: C-OTDR monitoring system, bimodal processing, LPboost, SVM

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Authors: T. Parhizkar, H. Jafarian, F. Aramoun, Y. Saboohi

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Applying motorized shades have substantial effect on reducing energy consumption in building sector. Moreover, the combination of motorized shades with lighting systems and PV panels can lead to considerable reduction in the energy demand of buildings. In this paper, a model is developed to assess and find an optimum combination from shade designs, lighting control systems (dimming and on/off) and implementing PV panels in shades point of view. It is worth mentioning that annual saving for all designs is obtained during hourly simulation of lighting, solar heat flux and electricity generation with the use of PV panel. From 12 designs in general, three designs, two lighting control systems and PV panel option is implemented for a case study. The results illustrate that the optimum combination causes a saving potential of 792kW.hr per year.

Keywords: motorized shades, daylight, cooling load, shade control, hourly simulation

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Authors: Savvas Rogotis, Nikolaos Kalatzis, Stergios Dimou-Sakellariou, Nikolaos Marianos

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As precision holds the key for the introduction of distinct benefits in agriculture (e.g., energy savings, reduced labor costs, optimal application of inputs, improved products, and yields), it steadily becomes evident that new initiatives should focus on rendering Precision Agriculture (PA) more accessible to the average farmer. PA leverages on technologies such as the Internet of Things (IoT), earth observation, robotics and positioning systems (e.g., the Global Navigation Satellite System – GNSS - as well as individual positioning systems like GPS, Glonass, Galileo) that allow: from simple data georeferencing to optimal navigation of agricultural machinery to even more complex tasks like Variable Rate Applications. An identified customer pain point is that, from one hand, typical triangulation-based positioning systems are not accurate enough (with errors up to several meters), while on the other hand, high precision positioning systems reaching centimeter-level accuracy, are very costly (up to thousands of euros). Within this paper, a Ground-Based Augmentation System (GBAS) is introduced, that can be adapted to any existing IoT field-sensing station infrastructure. The latter should cover a minimum set of requirements, and in particular, each station should operate as a fixed, obstruction-free towards the sky, energy supplying unit. Station augmentation will allow them to function in pairs with GNSS rovers following the differential GNSS base-rover paradigm. This constitutes a key innovation element for the proposed solution that encompasses differential GNSS capabilities into an IoT field-sensing infrastructure. Integrating this kind of information supports the provision of several additional PA beneficial services such as spatial mapping, route planning, and automatic field navigation of unmanned vehicles (UVs). Right at the heart of the designed system, there is a high-end GNSS toolkit with base-rover variants and Real-Time Kinematic (RTK) capabilities. The GNSS toolkit had to tackle all availability, performance, interfacing, and energy-related challenges that are faced for a real-time, low-power, and reliable in the field operation. Specifically, in terms of performance, preliminary findings exhibit a high rover positioning precision that can even reach less than 10-centimeters. As this precision is propagated to the full dataset collection, it enables tractors, UVs, Android-powered devices, and measuring units to deal with challenging real-world scenarios. The system is validated with the help of Gaiatrons, a mature network of agro-climatic telemetry stations with presence all over Greece and beyond ( > 60.000ha of agricultural land covered) that constitutes part of “gaiasense” (www.gaiasense.gr) smart farming (SF) solution. Gaiatrons constantly monitor atmospheric and soil parameters, thus, providing exact fit to operational requirements asked from modern SF infrastructures. Gaiatrons are ultra-low-cost, compact, and energy-autonomous stations with a modular design that enables the integration of advanced GNSS base station capabilities on top of them. A set of demanding pilot demonstrations has been initiated in Stimagka, Greece, an area with a diverse geomorphological landscape where grape cultivation is particularly popular. Pilot demonstrations are in the course of validating the preliminary system findings in its intended environment, tackle all technical challenges, and effectively highlight the added-value offered by the system in action.

Keywords: GNSS, GBAS, precision agriculture, RTK, smart farming

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Authors: Giada Feletti, Daniela Tedesco, Paolo Trucco

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The present study aims to develop a dashboard of Key Performance Indicators (KPI) to enhance information and predictive capabilities in Emergency Medical Services (EMS) systems, supporting both operational and strategic decisions of different actors. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning the indicators currently used for the performance measurement of EMS systems. From this literature analysis, it emerged that current studies focus on two distinct perspectives: the ambulance service, a fundamental component of pre-hospital health treatment, and the patient care in the Emergency Department (ED). The perspective proposed by this study is to consider an integrated view of the ambulance service process and the ED process, both essential to ensure high quality of care and patient safety. Thus, the proposal focuses on the entire healthcare service process and, as such, allows considering the interconnection between the two EMS processes, the pre-hospital and hospital ones, connected by the assignment of the patient to a specific ED. In this way, it is possible to optimize the entire patient management. Therefore, attention is paid to the dependency of decisions that in current EMS management models tend to be neglected or underestimated. In particular, the integration of the two processes enables the evaluation of the advantage of an ED selection decision having visibility on EDs’ saturation status and therefore considering the distance, the available resources and the expected waiting times. Starting from a critical review of the KPIs proposed in the extant literature, the design of the dashboard was carried out: the high number of analyzed KPIs was reduced by eliminating the ones firstly not in line with the aim of the study and then the ones supporting a similar functionality. The KPIs finally selected were tested on a realistic dataset, which draws us to exclude additional indicators due to the unavailability of data required for their computation. The final dashboard, which was discussed and validated by experts in the field, includes a variety of KPIs able to support operational and planning decisions, early warning, and citizens’ awareness of EDs accessibility in real-time. By associating each KPI to the EMS phase it refers to, it was also possible to design a well-balanced dashboard covering both efficiency and effective performance of the entire EMS process. Indeed, just the initial phases related to the interconnection between ambulance service and patient’s care are covered by traditional KPIs compared to the subsequent phases taking place in the hospital ED. This could be taken into consideration for the potential future development of the dashboard. Moreover, the research could proceed by building a multi-layer dashboard composed of the first level with a minimal set of KPIs to measure the basic performance of the EMS system at an aggregate level and further levels with KPIs that can bring additional and more detailed information.

Keywords: dashboard, decision support, emergency medical services, key performance indicators

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Authors: Batuhan Kocaoglu

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Although using powerful systems like ERP (Enterprise Resource Planning), companies still cannot benchmark their processes and measure their process performance easily based on predefined SCOR (Supply Chain Operation References) terms. The purpose of this research is to identify common and corresponding processes to present a conceptual model to model and measure the purchasing process of an organization. The main steps for the research study are: Literature review related to 'procure to pay' process in ERP system; Literature review related to 'sourcing' process in SCOR model; To develop a conceptual model integrating 'sourcing' of SCOR model and 'procure to pay' of ERP model. In this study, we examined the similarities and differences between these two models. The proposed framework is based on the assumptions that are drawn from (1) the body of literature, (2) the authors’ experience by working in the field of enterprise and logistics information systems. The modeling framework provides a structured and systematic way to model and decompose necessary information from conceptual representation to process element specification. This conceptual model will help the organizations to make quality purchasing system measurement instruments and tools. And offered adaptation issues for ERP systems and SCOR model will provide a more benchmarkable and worldwide standard business process.

Keywords: SCOR, ERP, procure to pay, sourcing, reference model

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Authors: Amy Bromley

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Child protection practitioners are a vital part of systems designed to protect children from abuse and neglect. Reforms in Anglo-American systems have shown a trend towards compliance-culture that reduces practitioner autonomy and empowerment, increasing staff turnover and negatively impacting outcomes for children. This explanatory mixed-methods study examined psychological empowerment in a national sample of child protection practitioners in Australia (n=109) using the Psychological Empowerment Instrument followed by semi-structured interviews (n=19). The results show that practitioners experience the sub-dimensions of psychological empowerment differently, perceiving themselves to have high levels of competence and satisfaction in their work but limited opportunities for self-determination and low levels of impact on decision-making in their organizations. The qualitative data revealed that practitioners do not trust systemic reforms and have experienced them as ineffective, politically driven, and bureaucratic. The increased compliance demanded from these reforms has left practitioners feeling that their expertise is not valued, leading many to leave their organizations. The practitioners who remain employed in child protection identified their use of advocacy, curiosity, and child-centered values as ways of protecting their psychological empowerment. The findings highlight the ways psychological empowerment can be promoted within child protection systems, improving staff retention and building expertise.

Keywords: child protection, implementation, psychological empowerment, systems theory

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Authors: Gechbaia Badri

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The paper discusses in today's world of economic globalization and development of innovative economic integration is one of the issues of the day in the world. The article analyzes the innovation economy development trends in EU, showed the innovation economy formation of the main problems and results, also the development of innovative potential of the economy. The author reckons that the European economy will contribute to the development of innovative economic space of speech in recent years developed a financial and economic crisis.

Keywords: European Union, innovative system, innovative development, innovations

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Authors: Muhammad Umar Kiani, Muhammad Shahbaz, Hassan Akbar

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Simulation of a high speed inviscid steady ideal air flow around a 2D/axial-symmetry body was carried out by the use of mb_cns code. mb_cns is a program for the time-integration of the Navier-Stokes equations for two-dimensional compressible flows on a multiple-block structured mesh. The flow geometry may be either planar or axisymmetric and multiply-connected domains can be modeled by patching together several blocks. The main simulation code is accompanied by a set of pre and post-processing programs. The pre-processing programs scriptit and mb_prep start with a short script describing the geometry, initial flow state and boundary conditions and produce a discretized version of the initial flow state. The main flow simulation program (or solver as it is sometimes called) is mb_cns. It takes the files prepared by scriptit and mb_prep, integrates the discrete form of the gas flow equations in time and writes the evolved flow data to a set of output files. This output data may consist of the flow state (over the whole domain) at a number of instants in time. After integration in time, the post-processing programs mb_post and mb_cont can be used to reformat the flow state data and produce GIF or postscript plots of flow quantities such as pressure, temperature and Mach number. The current problem is an example of supersonic inviscid flow. The flow domain for the current problem (strake configuration wing) is discretized by a structured grid and a finite-volume approach is used to discretize the conservation equations. The flow field is recorded as cell-average values at cell centers and explicit time stepping is used to update conserved quantities. MUSCL-type interpolation and one of three flux calculation methods (Riemann solver, AUSMDV flux splitting and the Equilibrium Flux Method, EFM) are used to calculate inviscid fluxes across cell faces.

Keywords: steady flow simulation, processing programs, simulation code, inviscid flux

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Authors: C. P. Chukwuka, E. V. Chukwuka, F. Ukwadi

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This paper focuses on the advancement and societal impact of artificial intelligence (AI) systems. It explores the need for a theoretical framework in corporate governance, specifically in the context of 'hybrid' companies that have a mix of private and government ownership. The paper emphasizes the potential of AI to address challenges faced by these companies and highlights the importance of the less-explored state model in corporate governance. The aim of this research is to enhance AI systems for global impact and positive societal outcomes. It aims to explore the role of AI in refining corporate governance in hybrid companies and uncover nuanced insights into complex ownership structures. The methodology involves leveraging the capabilities of AI to address the challenges faced by hybrid companies in corporate governance. The researchers will analyze existing theoretical frameworks in corporate governance and integrate AI systems to improve problem-solving and understanding of intricate systems. The paper suggests that improved AI systems have the potential to shape a more informed and responsible corporate landscape. AI can uncover nuanced insights and navigate complex ownership structures in hybrid companies, leading to greater efficacy and positive societal outcomes. The theoretical importance of this research lies in the exploration of the role of AI in corporate governance, particularly in the context of hybrid companies. By integrating AI systems, the paper highlights the potential for improved problem-solving and understanding of intricate systems, contributing to a more informed and responsible corporate landscape. The data for this research will be collected from existing literature on corporate governance, specifically focusing on hybrid companies. Additionally, data on AI capabilities and their application in corporate governance will be collected. The collected data will be analyzed through a systematic review of existing theoretical frameworks in corporate governance. The researchers will also analyze the capabilities of AI systems and their potential application in addressing the challenges faced by hybrid companies. The findings will be synthesized and compared to identify patterns and potential improvements. The research concludes that AI systems have the potential to enhance corporate governance in hybrid companies, leading to greater efficacy and positive societal outcomes. By leveraging AI capabilities, nuanced insights can be uncovered, and complex ownership structures can be navigated, shaping a more informed and responsible corporate landscape. The findings highlight the importance of integrating AI in refining problem-solving and understanding intricate systems for global impact.

Keywords: advancement, artificial intelligence, challenges, societal impact

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Authors: Ezio Bassi, Francesco Vercesi, Francesco Benzi

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The aim of this study is to evaluate the potentiality of synchronous reluctance motors for lift systems by also evaluating the vibroacoustic behaviour of the motor. Two types of synchronous machines are designed, analysed, and compared with an equivalent induction motor, which is the more common solution in such gearbox applications. The machines' performance are further improved with optimization procedures based on multiobjective optimization genetic algorithm (MOGA). The difference between the two synchronous motors consists in the rotor geometry; a symmetric and an asymmetric rotor design were investigated. The evaluation of the vibroacoustic performance has been conducted with a multi-variable model and finite element software taking into account electromagnetic, mechanical, and thermal features of the motor, therefore carrying out a multi-physics analysis of the electrical machine.

Keywords: synchronous reluctance motor, vibro-acoustic, lift systems, genetic algorithm

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Authors: Sih-Li Chen, Chih-Hao Chen, Chi-Tong Chan

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Poor ventilation and high carbon dioxide (CO2) concentrations lead to the formation of sick buildings. This problem cannot simply be resolved by introducing fresh air from outdoor environments because this creates extra loads on indoor air-conditioning systems. Desiccants are widely used in air conditioning systems in tropical and subtropical regions with high humidity to reduce the latent heat load from fresh air. Desiccants are usually used as a packed-bed type, which is low cost, to combine with air-conditioning systems. Nevertheless, the pressure drop of a packed bed is too high, and the heat of adsorption caused by the adsorption process lets the temperature of the outlet air increase, bringing about an extra heat load, so the high pressure drop and the increased temperature of the outlet air are energy consumption sources needing to be resolved. For this reason, the gas-solid fluidised beds that have high heat and mass transfer rates, uniform properties and low pressure drops are very suitable for use in air-conditioning systems.This study experimentally investigates the performance of silica gel fluidized bed device which applying to an air conditioning system. In the experiments, commercial silica gel particles were filled in the two beds and to form a fixed packed bed and a fluidized bed. The results indicated that compared to the fixed packed bed device, the total adsorption and desorption by amounts of fluidized bed for 40 minutes increased 20.6% and 19.9% respectively when the bed height was 10 cm and superficial velocity was set to 2 m/s. In addition, under this condition, the pressure drop and outlet air temperature raise were reduced by 36.0% and 30.0%. Given the above results, application of the silica gel fluidized bed to air conditioning systems has great energy-saving potential.

Keywords: fluidized bed, packed bed, silica gel, adsorption, desorption, pressure drop

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Authors: Kawai Nobuaki

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This paper describes the design and implementation of web system for continuable and viable collaboration. This study proposes the improvement of the system based on a result of a certain practice. As contemporary higher education information environments transform, this study highlights the significance of university identity and college identity that are formed continuously through independent activities of the students. Based on these discussions, the present study proposes a practical media environment design which facilitates the processes of organizational identity formation based on a continuous and cyclical model. Even if users change by this system, the communication system continues operation and cooperation. The activity becomes the archive and produces new activity. Based on the result, this study elaborates a plan with a re-design by a system from the viewpoint of second-order cybernetics. Systems theory is a theoretical foundation for our study.

Keywords: collaborative work, learning management system, second-order cybernetics, systems theory, user generated contents, viable system model

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Authors: Oliver Marunțălu, Elena Elisabeta Manea, Lăcrămioara Diana Robescu, Mihai Necșoiu, Gheorghe Lăzăroiu, Dana Andreya Bondrea

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In order to obtain efficient pollutants removal in small-scale wastewater treatment plants, uniform water flow has to be achieved. The experimental setup, designed for treating high-load wastewater (leachate), consists of two aerobic biological reactors and a lamellar settler. Both biological tanks were aerated by using three different types of aeration systems - perforated pipes, membrane air diffusers and tube ceramic diffusers. The possibility of homogenizing the water mass with each of the air diffusion systems was evaluated comparatively. The oxygen concentration was determined by optical sensors with data logging. The experimental data was analyzed comparatively for all three different air dispersion systems aiming to identify the oxygen concentration variation during different operational conditions. The Oxygenation Capacity was calculated for each of the three systems and used as performance and selection parameter. The global mass transfer coefficients were also evaluated as important tools in designing the aeration system. Even though using the tubular porous diffusers leads to higher oxygen concentration compared to the perforated pipe system (which provides medium-sized bubbles in the aqueous solution), it doesn’t achieve the threshold limit of 80% oxygen saturation in less than 30 minutes. The study has shown that the optimal solution for the studied configuration was the radial air diffusers which ensure an oxygen saturation of 80% in 20 minutes. An increment of the values was identified when the air flow was increased.

Keywords: flow, aeration, bioreactor, oxygen concentration

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Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: Andhika Danesjvara

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Governance of the Republic of Indonesia should be based on the principle of sovereignty and the rule of law. Based on these principles, all forms of decisions and/or actions of government administration should be based on the sovereignty of the people and the law. Decisions and/or actions for citizens should be based on the provisions of the legislation and the general principles of good governance. Control of the decisions and/or actions is a part of administrative review and also judicial control. The control is part of the administrative justice system, which is intended for people affected by the decisions or administrative actions. This control is the duty and authority of the government or independent administrative court. Therefore, systems and procedures for the implementation of the task of governance and development must be regulated by law. Systems and procedures of governance is a subject studied in administrative law, therefore, the research also includes a review of the principles of law in administrative law. The administrative law procedure is important for the government to make decisions, the question is whether the procedures are part of the justice system itself.

Keywords: administrative court, administrative justice, administrative law, administrative procedures

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Authors: Yixun Shi

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Many interior point methods for convex programming solve an (n+m)x(n+m)linear system in each iteration. Many implementations solve this system in each iteration by considering an equivalent mXm system (4) as listed in the paper, and thus the job is reduced into solving the system (4). However, the system(4) has to be solved exactly since otherwise the error would be entirely passed onto the last m equations of the original system. Often the Cholesky factorization is computed to obtain the exact solution of (4). One Cholesky factorization is to be done in every iteration, resulting in higher computational costs. In this paper, two iterative methods for solving linear systems using vector division are combined together and embedded into interior point methods. Instead of computing one Cholesky factorization in each iteration, it requires only one Cholesky factorization in the entire procedure, thus significantly reduces the amount of computation needed for solving the problem. Based on that, a hybrid algorithm for solving convex programming problems is proposed.

Keywords: convex programming, interior point method, linear systems, vector division

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Authors: Courtney Evans, Yuto Morimitsu, Tsubasa Hisadome, Futo Inomoto, Masahiro Yoshida, Takayuki Takei

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Hydrogels are useful biomaterials due to their highly biocompatible nature and their ability to absorb large quantities of liquid and mimic soft tissue. They are often used as therapeutic drug delivery systems. However, it is sometimes difficult to sustain controlled release when using hydrophobic medicines, as hydrogels are frequently hydrophilic. As such, this research shows the success of chitosan hydrogels modified through hydrophobic interaction. This was done through the imide bonding of the alkyl groups in fatty aldehydes and the amino groups in chitosan, followed by reductive animation. The resulting cryogels could be optimized for strength as well as sorption and desorption (of a hydrophobic dye used to mimic hydrophobic medicine) by varying the alkyl chain length and the substitution degree of the fatty aldehyde. Optimized cryogels showed potential as biomedical materials, particularly as drug delivery systems.

Keywords: biomedical materials, chitosan, drug carriers, hydrophobic modification

Procedia PDF Downloads 234