Search results for: batched delivery system

Authors: Semyachkina-Glushkovskaya Oxana, Fedosov Ivan, Blokhina Inna, Terskov Andrey, Evsukova Arina, Elovenko Daria, Adushkina Viktoria, Dubrovsky Alexander, Jürgen Kurths

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In modern neurobiology, sleep is considered a novel biomarker and a promising therapeutic target for brain diseases. This is due to recent discoveries of the nighttime activation of the brain lymphatic system (BLS), playing an important role in the removal of wastes and toxins from the brain and contributes neuroprotection of the central nervous system (CNS). In our review, we discuss that night stimulation of BLS might be a breakthrough strategy in a new treatment of Alzheimer’s and Parkinson’s disease, stroke, brain trauma, and oncology. Although this research is in its infancy, however, there are pioneering and promising results suggesting that night transcranial photostimulation (tPBM) stimulates more effectively lymphatic removal of amyloid-beta from mouse brain than daily tPBM that is associated with a greater improvement of the neurological status and recognition memory of animals. In our previous study, we discovered that tPBM modulates the tone and permeability of the lymphatic endothelium by stimulating NO formation, promoting lymphatic clearance of wastes and toxins from the brain tissues. We also demonstrate that tPBM can also lead to angio- and lymphangiogenesis, which is another mechanism underlying tPBM-mediated stimulation of BLS. Thus, photo-augmentation of BLS might be a promising therapeutic target for preventing or delaying brain diseases associated with BLS dysfunction. Here we present pioneering technology for simultaneous tPBM in humans and sleep monitoring for stimulation of BLS to remove toxins from CNS and modulation of brain immunity. The wireless-controlled gadget includes a flexible organic light-emitting diode (LED) source that is controlled directly by a sleep-tracking device via a mobile application. The designed autonomous LED source is capable of providing the required therapeutic dose of light radiation at a certain region of the patient’s head without disturbing of sleeping patient. To minimize patients' discomfort, advanced materials like flexible organic LEDs were used. Acknowledgment: This study was supported by RSF project No. 23-75-30001.

Keywords: brain diseases, brain lymphatic system, phototherapy, sleep

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Authors: C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar

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In this paper using smart materials we have proposed a specially manufactured variable volume spin tub for loading clothes for negating the vibration to a certain extent for getting better operating performance. Additionally, we have recommended a variable spinning speed rotor for handling varieties of garments for an efficient washing, aiming for increasing the life span of both the garments and the machine. As a part of the conflicting dynamic constraints and demands of the customer friendly design optimization of a lucrative and cosmetic washing machine we have proposed a drier and a desalination system capable to supply desirable heat and a pleasing fragrance to the garments. We thus concluded that while incorporating variable volume and variable spinning speed tub integrated with a drier and desalination system, the washing machine could meet the varieties of domestic requirements of the customers cost-effectively.

Keywords: customer friendly washing machine, drier design, quick cloth cleaning, variable tub volume washing machine, variable spinning speed washing machine

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Authors: Nivedha Rajaram

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Hybrid Quantum solvers have been given prime focus in recent days by computation problem-solving domain industrial applications. D’Wave Quantum Computers are one such paragon of systems built using quantum annealing mechanism. Discrete Quadratic Models is a hybrid quantum computing model class supplied by D’Wave Ocean SDK - a real-time software platform for hybrid quantum solvers. These hybrid quantum computing modellers can be employed to solve classic problems. One such problem that we consider in this paper is finding a network connectivity knowledge hub in a huge network of systems. Using this quantum solver, we try to find out the prime system hub, which acts as a supreme connection point for the set of connected computers in a large network. This paper establishes an innovative problem approach to generate a connectivity system hub plot for a set of systems using DWave ocean SDK hybrid quantum solvers.

Keywords: quantum computing, hybrid quantum solver, DWave annealing, network knowledge graph

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Authors: Joseph Roberson, Carina Kleynhans, Willie Coetzee

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The low entry barriers of the restaurant industry lead to an extremely competitive business environment. In this volatile business sector it is of the utmost importance to implement a strategy of quality differentiation. Vital aspects of a quality differentiation strategy are total quality management, benchmarking and service quality management. Ultimately, restaurant success depends on the continuous support of customers. Customers select restaurants based on their expectations of quality. If the customers' expectations are met, they perceive quality service and will re-patronize the restaurant. The restaurateur can manage perceptions of quality by influencing expectations while ensuring that those expectations are not inflated. The management of expectations can be done by communicating service quality to customers. The aim of this research paper is to describe the development of a grading process for restaurants. An assessment of the extensive body of literature on grading was conducted through content analysis. A standardized method for developing a grading system would assist in successful grading systems that could inform both customers and restaurateurs of restaurant quality.

Keywords: benchmarking, restaurants, grading, service quality, total quality management

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Authors: Mahmoud M. Othman, Almoataz Y. Abdelaziz, Yasser G. Hegazy

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This paper presents a load control strategy based on modification of the Big Bang Big Crunch optimization method. The proposed strategy aims to determine the optimal load to be controlled and the corresponding time of control in order to minimize the energy purchased from substation. The presented strategy helps the distribution network operator to rely on the renewable energy sources in supplying the system demand. The renewable energy sources used in the presented study are modeled using the diagonal band Copula method and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithm.

Keywords: big bang big crunch, distributed generation, load control, optimization, planning

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Authors: John Tarus, Zhendong Niu, Bakhti Khadidja

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In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.

Keywords: collaborative filtering, e-learning, ontology, recommender system

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Authors: E. V. Fakhrutdinova, K. R. Maksimova, P. B. Chursin

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At the present stage of the society progress the health care is an integral part of both the economic system and social, while in the second case the medicine is a major component of a number of basic and necessary social programs. Since the foundation of the health system are highly qualified health professionals, it is logical proposition that increase of doctor`s professionalism improves the effectiveness of the system as a whole. Professionalism of the doctor is a collection of many components, essential role played by such personal-psychological factors as honesty, willingness and desire to help people, and motivation. A number of researchers consider motivation as an expression of basic human needs that have passed through the “filter” which is a worldview and values learned in the process of socialization by the individual, to commit certain actions designed to achieve the expected result. From this point of view a number of researchers propose the following classification of highly skilled employee’s needs: 1. the need for confirmation the competence (setting goals that meet the professionalism and receipt of positive emotions in their decision), 2. The need for independence (the ability to make their own choices in contentious situations arising in the process carry out specialist functions), 3. The need for ownership (in the case of health care workers, to the profession and accordingly, high in the eyes of the public status of the doctor). Nevertheless, it is important to understand that in a market economy a significant motivator for physicians (both legal and natural persons) is to maximize its own profits. In the case of health professionals duality motivational structure creates an additional contrast, as in the public mind the image of the ideal physician; usually a altruistically minded person thinking is not primarily about their own benefit, and to assist others. In this context, the question of the real motivation of health workers deserves special attention. The survey conducted by the American researcher Harrison Terni for the magazine "Med Tech" in 2010 revealed the opinion of more than 200 medical students starting courses, and the primary motivation in a profession choice is "desire to help people", only 15% said that they want become a doctor, "to earn a lot". From the point of view of most of the classical theories of motivation this trend can be called positive, as intangible incentives are more effective. However, it is likely that over time the opinion of the respondents may change in the direction of mercantile motives. Thus, it is logical to assume that well-designed system of motivation of doctor`s labor should be based on motivational foundations laid during training in higher education.

Keywords: motivation, quality of working life, health system, personal-psychological factors, motivational structure

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Authors: Hamed Saremi, Suzan Taghavy, Seyed Mohammad Hanif Sanjari, Mostafa Kahali

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One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study, the identified indicators of brand equity are based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: brand, cosmetic product, ANFIS, DEMATEL

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Authors: Margaret S. Gumisiriza, Ernest. R. Mbega, Patrick Ndakidemi, Businge K. Edward

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The purpose of the paper was to assess existing literature regarding hydroponics in both the developing and developed countries. Furthermore, relate it to the context of African countries, how they can implement it and benefit from it in the face of climate change, high population growth rates, and reduced food production. Agriculture remains the major economic activity for a number of African countries. It is the source of income for most peasants, and still contributes to the Gross Domestic Product in most of these African countries. Unfortunately, climate change coupled with the increasing rates of population growth; rural-urban migration; and urbanization have led to food insecurity due to a reduction of available land for agriculture. This has further intensified the food security dilemma in Africa, especially in urban areas, where land is already limited. Considering the aforementioned state of affairs, there is an increasing demand for interventions that can help farmers in Africa to cope with climate change and increase food production. This review explores hydroponic farming and how it can be used as a climate-smart farming system in Africa’s rural and urban areas. Specifically, the review focuses on hydroponics, requirements for hydroponic farming and the state of hydroponic farming in LDCs and Developed countries (DCs). From the review, it was observed that African countries especially those that receive a lot of sunlight would highly benefit from the solar-powered hydroponic farming systems. Further, still, this farming system will help African countries cope with the challenges of high population pressure in urban areas and climate change as it qualifies to be an urban farming system.

Keywords: Africa, climate-smart agriculture, solar-powered-hydroponics, urban-farming

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Authors: Vikas Kumar

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The present study is carried out to investigate the magneto-viscous effects on incompressible ferrofluid flow over a porous rotating disc with suction or injection on the surface of the disc subjected to a magnetic field. The flow under consideration is axi-symmetric steady ferrofluid flow of electrically non-conducting fluid. Karman’s transformation is used to convert the governing boundary layer equations involved in the problem to a system of non linear coupled differential equations. The solution of this system is obtained by using power series approximation. The flow characteristics i.e. radial, tangential, axial velocities and boundary layer displacement thickness are calculated for various values of MFD (magnetic field dependent) viscosity and for different values of suction injection parameter. Besides this, skin friction coefficients are also calculated on the surface of the disk. Thus, the obtained results are presented numerically and graphically in the paper.

Keywords: axi-symmetric, ferrofluid, magnetic field, porous rotating disk

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Authors: Mohamed Abdel-Monem, Gamal Sowilam, Omar Hegazy

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This paper presents a technical assessment of an electric vehicle with two independent rear-wheel motor and an improved traction control system. The electric differential and the control strategy have been implemented to assure that in a straight trajectory, the two rear-wheels run exactly at the same speed, considering the same/different road conditions under the left and right side of the wheels. In case of turning to right/left, the difference between the two rear-wheels speeds assures a vehicle trajectory without sliding, thanks to a harmony between the electric differential and the control strategy. The present article demonstrates a complete model and analysis of a traction control system, considering four different traction scenarios, for two independent rear-wheels motors for electric vehicles. Furthermore, the vehicle model, including wheel dynamics, load forces, electric differential, and control strategy, is designed and verified by using MATLAB/Simulink environment.

Keywords: electric vehicle, energy saving, multi-motor, electric differential, simulation and control

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Authors: Marcello De Falco, Gianluca Natrella, Mauro Capocelli

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CO₂ capture and utilization (CCU) is a promising approach to reduce GHG(greenhouse gas) emissions. Many technologies in this field are recently attracting attention. However, since CO₂ is a very stable compound, its utilization as a reagent is energetic intensive. As a consequence, it is unclear whether CCU processes allow for a net reduction of environmental impacts from a life cycle perspective and whether these solutions are sustainable. Among the tools to apply for the quantification of the real environmental benefits of CCU technologies, exergy analysis is the most rigorous from a scientific point of view. The exergy of a system is the maximum obtainable work during a process that brings the system into equilibrium with its reference environment through a series of reversible processes in which the system can only interact with such an environment. In other words, exergy is an “opportunity for doing work” and, in real processes, it is destroyed by entropy generation. The exergy-based analysis is useful to evaluate the thermodynamic inefficiencies of processes, to understand and locate the main consumption of fuels or primary energy, to provide an instrument for comparison among different process configurations and to detect solutions to reduce the energy penalties of a process. In this work, the exergy analysis of a process for the production of Dimethyl Ether (DME) from green hydrogen generated through an electrolysis unit and pure CO₂ captured from flue gas is performed. The model simulates the behavior of all units composing the plant (electrolyzer, carbon capture section, DME synthesis reactor, purification step), with the scope to quantify the performance indices based on the II Law of Thermodynamics and to identify the entropy generation points. Then, a plant optimization strategy is proposed to maximize the exergy efficiency.

Keywords: green DME production, exergy analysis, energy penalties, exergy efficiency

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Authors: Tao Lin, Shanghong Zhao, Yufu Yin, Zihang Zhu, Wei Jiang, Xuan Li, Qiurong Zheng

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A simple operated, stable and compact multi-band frequency conversion and multi-phase shift is proposed to satisfy the demands of multi-band communication and radar phase array system. The dual polarization quadrature phase shift keying (DP-QPSK) modulator is employed to support the LO sideband and the optical frequency comb simultaneously. Meanwhile, the fiber is also used to introduce different phase shifts to different sidebands. The simulation result shows that by controlling the DC bias voltages and a C band microwave signal with frequency of 4.5 GHz can be simultaneously converted into other signals that cover from C band to K band with multiple phases. It also verifies that the multi-band and multi-phase frequency conversion system can be stably performed based on current manufacturing art and can well cope with the DC drifting. It should be noted that the phase shift of the converted signal also partly depends of the length of the optical fiber.

Keywords: microwave photonics, multi-band frequency conversion, multi-phase shift, conversion efficiency

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Authors: Seyed Mohammad Mahdi Zamani, Kamran Behdinan

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In this study, a multiscale framework is performed to model the strength of Nextel fibers in presence of an atomistic scale pre-crack at finite temperatures. The bridging cell method (BCM) is the multiscale technique applied in this study, which decomposes the system into the atomistic, bridging and continuum domains; solves the whole system in a finite element framework; and incorporates temperature dependent calculations. Since Nextel is known to be structurally stable and retain 70% of its initial strength up to 1100°C; simulations are conducted at both of the room temperatures, 25°C, and fire temperatures, 1200°C. Two cases are modeled for a pre-crack present in either phases of alumina or mullite of the Nextel structure. The materials’ response is studied with respect to deformation behavior and ultimate tensile strength. Results show different crack growth trends for the two cases, and as the temperature increases, the crack growth resistance and material’s strength decrease.

Keywords: Nextel fibers, multiscale modeling, pre-crack, ultimate tensile strength

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Authors: Jhu-Wei Ji, Fa-Shian Chang, Lih-Tyng Hwang, Chih-Feng Liu, Jeng-Nan Lee, Shun-Min Wang, Kai-Yi Cho

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This paper presents a tracked robot with blade arms powered to assist movement in difficult environments. As a result, the tracked robot is able to pass a ramp or climb stairs. The main feature is a pair of blade arms on both sides of the vehicle body working in collaboration with previously validated transformable track system. When the robot encounters an obstacle in a terrain, it enlists the blade arms with power to overcome the obstacle. In disaster areas, there usually will be terrains that are full of broken and complicated slopes, broken walls, rubbles, and ditches. Thereupon, a robot, which is instructed to pass through such disaster areas, needs to have a good off-road capability for such complicated terrains. The robot with crawling-assisting blade arms would overcome the obstacles along the terrains, and possibly become to be a rescue robot. A prototype has been developed and built; experiments were carried out to validate the enhanced crawling capability of the robot.

Keywords: tracked robot, rescue robot, blade arm, crawling ability, control system

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Authors: Yung-Gi Chen, Pei-Leun Kang, Yu-Hsin Lin, Shwu-Jen Chang

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Myocardial tissue has limited self-repair ability due to its loss of differentiation characteristic for most mature cardiomyocytes. Therefore, the effective use of stem cell technology in regenerative medicine is an important development to alleviate the current difficulties in cardiac disease treatment. The main purpose of this project was to develop a 3-D hydrogel electrical stimulating system for promoting the differentiation of stem cells into myocardial cells, and the patch will be used to repair damaged myocardial tissue. This project was focused on the preparation of the electrical stimulation system with carbon/CaCl₂ electrodes covered with carbon nanotube-hydrogel. In this study, we utilized screen imprinting techniques and used Poly(lactic-co-glycolic acid)(PLGA) membranes as printing substrates to fabricate a carbon/CaCl₂ interdigitated electrode that covered with alginate/carbon nanotube hydrogels. The single-walled carbon nanotube was added in the hydrogel to enhance the mechanical strength and conductivity of hydrogel. In this study, we used PLGA (85:15) as electrode preparing substrate. The CaCl₂/ EtOH solution (80% w/v) was mixed into carbon paste to prepare various concentration calcium-containing carbon paste (2.5%, 5%, 7.5%, 10% v/v). Different concentrations of alginate (1%, 1.5%, 2% v/v) and SWCNT(Diameter < 2nm, length between 5-15μm) (1, 1.5, 3 mg/ml) are gently immobilized on the electrode by cross-linking with calcium chloride. The three-dimensional hydrogel electrode was tested for its redox efficiency by cyclic voltammetry to determine the optimal parameters for the hydrogel electrode preparation. From the result of the final electrodes, it indicated that the electrode was not easy to maintain the pattern of the interdigitated electrode when the concentration of calcium of chloride was more than 10%. According to the gel rate test and cyclic voltammetry experiment results showed the SWCNT could increase the electron conduction of hydrogel electrodes significantly. So far the 3D electrode system has been completed, 2% alginate mixed with 3mg SWCNT is the optimal condition to construct the most complete structure for the hydrogel preparation.

Keywords: myocardial tissue engineering, screen printing technology, poly (lactic-co-glycolic acid), alginate, single walled carbon nanotube

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Majda Al Salti

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Tourism industry is considered globally as one of the leading industries due to its noticeable contribution to countries' gross domestic product (GDP) and job creation. However, tourism is vulnerable to crisis and disaster that requires its preparedness. With its limited capabilities, there is a need to improve links and the understanding between the tourism industry and the emergency services, thus facilitating future emergency response to any potential incident. This study aims to develop the concept of an integrated emergency management system for the tourism industry. The study used face-to-face semi-structured interviews to evaluate the level of crisis and disaster preparedness of the tourism industry in Oman. The findings suggested that there is a lack of understanding of crisis and disaster management, and hence preparedness level among Oman Tourism Authorities appears to be under-expectation. Therefore, a clear need for tourism sector inter- and intra-integration and collaboration is important in the pre-disaster stage. The need for such integrations can help the tourism industry in Oman to prepare for future incidents as well as identifying its requirements in time of crisis for effective response.

Keywords: tourism, emergency services, crisis, disaster

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Authors: Florian Kleber, Martin Kampel

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The increasing demand of gallium, indium and rare-earth elements for the production of electronics, e.g. solid state-lighting, photovoltaics, integrated circuits, and liquid crystal displays, will exceed the world-wide supply according to current forecasts. Recycling systems to reclaim these materials are not yet in place, which challenges the sustainability of these technologies. This paper proposes a multispectral imaging system as a basis for a vision based recognition system for valuable components of electronics waste. Multispectral images intend to enhance the contrast of images of printed circuit boards (single components, as well as labels) for further analysis, such as optical character recognition and entire printed circuit board recognition. The results show that a higher contrast is achieved in the near infrared compared to ultraviolet and visible light.

Keywords: electronics waste, multispectral imaging, printed circuit boards, rare-earth elements

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Authors: Imtiaz Sarwar

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Air conditioning in homes may account for one-third of the electricity during period in summer when most of the energy is required in large cities. It is not consuming only electricity but also has a serious impact on environment including greenhouse effect. Circular polarizer filter can be used to selectively absorb or pass clockwise or counter-clock wise circularly polarized light. My research is about putting two circular polarized glasses parallel to each other and make a circular window with it. When we will place two circular polarized glasses exactly same way (0 degree to each other) then nothing will be noticed rather it will work as a regular window through which all light and heat can pass on. While we will keep rotating one of the circular polarized glasses, the angle between the glasses will keep increasing and the window will keep blocking more and more lights. It will completely block all the lights and a portion of related heat when one of the windows will reach 90 degree to another. On the other hand, we can just open the window when fresh air is necessary. It will reduce the necessity of using Air condition too much or consumer will use electric fan rather than air conditioning system. Thus, we can save a significant amount of electricity and we can go green.

Keywords: circular polarizer, window, air condition, light, energy

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Authors: Matteo Nicoli, Gianvito Colucci, Valeria Di Cosmo, Daniele Lerede, Laura Savoldi

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The transport sector is currently responsible for approximately 1/3 of greenhouse gas emissions in Europe. In the wider context of achieving carbon neutrality of the global energy system, different alternatives are available to decarbonizethe transport sector. In particular, while electricity is already the most consumed energy commodity in rail transport, battery electric vehicles are one of the zero-emissions options on the market for road transportation. On the other hand, hydrogen-based fuel cell vehicles are available for road and non-road vehicles. The European Commission is strongly pushing toward the integration of hydrogen in the energy systems of European countries and its widespread adoption as an energy vector to achieve the Green Deal targets. Furthermore, the Italian government is defining hydrogen-related objectives with the publication of a dedicated Hydrogen Strategy. The adoption of energy system optimization models to study the possible penetration of alternative zero-emitting transport technologies gives the opportunity to perform an overall analysis of the effects that the development of innovative technologies has on the entire energy system and on the supply-side, devoted to the production of energy carriers such as hydrogen and electricity. Using an open-source modeling framework such as TEMOA, this work aims to compare the role of hydrogen and electric vehicles in the decarbonization of the transport sector. The analysis investigates the advantages and disadvantages of adopting the two options, from the economic point of view (costs associated with the two options) and the environmental one (looking at the emissions reduction perspectives). Moreover, an analysis on the profitability of the investments in hydrogen and electric vehicles will be performed. The study investigates the evolution of energy consumption and greenhouse gas emissions in different transportation modes (road, rail, navigation, and aviation) by detailed analysis of the full range of vehicles included in the techno-economic database used in the TEMOA model instance adopted for this work. The transparency of the analysis is guaranteed by the accessibility of the TEMOA models, based on an open-access source code and databases.

Keywords: battery electric vehicles, decarbonization, energy system optimization models, fuel cell vehicles, hydrogen, open-source modeling, TEMOA, transport

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Authors: Rajesh Kumar, Roopali Dogra, Puneet Aggarwal

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In the era of technological advancement, use of computer technology has become inevitable. Hence it has become the need of the hour to integrate software methods in engineering curriculum as a part to boost pedagogy techniques. Simulations software is a great help to graduates of disciplines such as electrical engineering. Since electrical engineering deals with high voltages and heavy instruments, extra care must be taken while operating with them. The viable solution would be to have appropriate control. The appropriate control could be well designed if engineers have knowledge of kind of waveforms associated with the system. Though these waveforms can be plotted manually, but it consumes a lot of time. Hence aid of simulation helps to understand steady state of system and resulting in better performance. In this paper computer, aided teaching of transformer is carried out using MATLAB/Simulink. The test carried out on a transformer includes open circuit test and short circuit respectively. The respective parameters of transformer are then calculated using the values obtained from open circuit and short circuit test respectively using Simulink.

Keywords: computer aided teaching, open circuit test, short circuit test, simulink, transformer

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Authors: Shasline Gedeon, Tiffany W. Ardley, Ying Wang, Nathan J. Gesmundo, Katarina A. Sarris, Ana L. Aguirre

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Drug discovery and delivery involve drug targeting, an approach that helps find a drug against a chosen target through high throughput screening and other methods by way of identifying the physical properties of the potential lead compound. Physical properties of potential drug candidates have been an imperative focus since the unveiling of Lipinski's Rule of 5 for oral drugs. Throughout a compound's journey from discovery, clinical phase trials, then becoming a classified drug on the market, the desirable properties are optimized while minimizing/eliminating toxicity and undesirable properties. In the pharmaceutical industry, the ability to generate molecules in parallel with maximum efficiency is a substantial factor achieved through sp²-sp² carbon coupling reactions, e.g., Suzuki Coupling reactions. These reaction types allow for the increase of aromatic fragments onto a compound. More recent literature has found benefits to decreasing aromaticity, calling for more sp³-sp² carbon coupling reactions instead. The objective of this project is to provide a comparison between various sp³-sp² carbon coupling methods and reaction conditions, collecting data on production of the desired product. There were four different coupling methods being tested amongst three cores and 4-5 installation groups per method; each method ran under three distinct reaction conditions. The tested methods include the Photoredox Decarboxylative Coupling, the Photoredox Potassium Alkyl Trifluoroborate (BF3K) Coupling, the Photoredox Cross-Electrophile (PCE) Coupling, and the Weix Cross-Electrophile (WCE) Coupling. The results concluded that the Decarboxylative method was very difficult in yielding product despite the several literature conditions chosen. The BF3K and PCE methods produced competitive results. Amongst the two Cross-Electrophile coupling methods, the Photoredox method surpassed the Weix method on numerous accounts. The results will be used to build future libraries.

Keywords: drug discovery, high throughput chemistry, photoredox chemistry, sp³-sp² carbon coupling methods

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Authors: Tebikew Yeneabat, Tefera Belachew, Muluneh Haile

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Background: Exclusive breast-feeding (EBF) is the practice of feeding only breast milk (including expressed breast milk) during the first six months and no other liquids and solid foods except medications. The time to cessation of exclusive breast-feeding, however, is different in different countries depending on different factors. Studies showed the risk of diarrhea morbidity and mortality is higher among none exclusive breast-feeding infants, common during starting other foods. However, there is no study that evaluated the time to cessation of exclusive breast-feeding in the study area. The aim of this study was to show time to cessation of EBF and its predictors among mothers of index infants less than twelve months old. Methods: We conducted a community-based cross-sectional study from February 13 to March 3, 2012 using both quantitative and qualitative methods. This study included a total of 592 mothers of index infant using multi-stage sampling method. Data were collected by using interviewer administered structured questionnaire. Bivariate and multivariate Cox regression analyses were performed. Results: Cessation of exclusive breast-feeding occurred in 392 (69.63%) cases. Among these, 224 (57.1%) happened before six months, while 145 (37.0%) and 23 (5.9%) occurred at six months and after six months of age of the index infant respectively. The median time for infants to stay on exclusive breast-feeding was 6.36 months in rural and 5.13 months in urban, and this difference was statistically significant on a Log rank (Cox-mantel) test. Maternal and paternal occupation, place of residence, postnatal counseling on exclusive breast-feeding, mode of delivery, and birth order of the index infant were significant predictors of cessation of exclusive breast-feeding. Conclusion: Providing postnatal care counseling on EBF, routine follow-up and support of those mothers having infants stressing for working mothers can bring about implementation of national strategy on infant and young child feeding.

Keywords: exclusive breastfeeding, cessation, median duration, Ankesha Guagusa Woreda

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Authors: Thorsten Prante, Robert Schöch, Ruth Fleisch, Vaheh Khachatouri, Alexander Walch

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The development of industrial plant control software is a complex and often very expensive task. One of the core problems is that a lot of the implementation and adaptation work can only be done after the plant hardware has been installed. In this paper, we present our approach to virtually developing and validating plant-level control software of production plants. This way, plant control software can be virtually commissioned before actual ramp-up of a plant, reducing actual commissioning costs and time. Technically, this is achieved by linking the actual plant-wide process control software (often called plant server) and an elaborate virtual plant model together to form an emulation system. Method-wise, we are suggesting a four-step iterative process with well-defined increments and time frame. Our work is based on practical experiences from planning to commissioning and start-up of several cut-to-size plants.

Keywords: iterative system design, virtual plant engineering, plant control software, simulation and emulation, virtual commissioning

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Authors: Samar Raffoul, Martin Heywood, Dimitrios Moutaftsis, Michael Rowell

Abstract:

This paper comprises an experimental investigation into the structural performance of cold formed steel (CFS) and timber board composite floor systems. The tests include a series of small-scale pushout tests and full-scale bending tests carried out using a refined loading system to simulate uniformly distributed constant load. The influence of connection details (screw spacing and adhesives) on floor performance was investigated. The results are then compared to predictions from relevant existing models for composite floor systems. The results of this research demonstrate the significant benefits of considering the composite action of the boards in floor design. Depending on connection detail, an increase in flexural stiffness of up to 40% was observed in the floor system, when compared to designing joists individually.

Keywords: cold formed steel joists, composite action, flooring systems, shear connection

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

Abstract:

We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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Authors: Taddese Alemu Zerfu, Melaku Umeta Deressa, Kaleab Baye

Abstract:

Background: Maternal and child under-nutrition is the underlying cause of 3•5 million annual deaths, globally. Anemia during pregnancy is among the leading nutritional disorders with serious short and long term consequences to both the mother and fetus. Objective: Examine the effect of dietary diversity on maternal anemia, nutritional status and key pregnancy outcomes of pregnancy. Methods: A prospective cohort study design, involving a total of 432 eligible pregnant women, in their second antenatal care visit was conducted between August 2014 to March, 2015. The individual dietary diversity status of mothers was used as the exposure variable to select, enroll and follow the mothers. All mothers were enrolled during second antenatal care visit and followed until delivery. Epi-data, SPSS and STATA software are used to enter and analyze the data. Chi-square test, independent 't'-test, and GLM are used to calculate risk, association and differences between key variables at P < 0.05. Results: Study participants did not differ in many of the basic characteristics (p < 0.05). The incidence of maternal anemia increased significantly from 28.6% to 32.1% between baseline and term. Pregnant mothers with inadequate dietary diversity groups had more (56% at baseline and 68% at term) risk of anemia than the comparison (adequate) groups, (RR, 1.56 and 1.68; 95% CI, 1.24 - 1.83 and 1.39 - 2.04). The overall incidence of still birth, low birth weight and pre-term birth was 4.5%, 9.1% and 13.6%, respectively. The variation of these outcomes was significant across study groups (P < 0.05). Conclusion and recommendations: Dietary diversity status of pregnant mothers has significant effect on the incidence of anemia and key pregnancy outcomes in resource limited settings, like rural Ethiopia. Therefore, apart from the ongoing routine IFA supplementation, special emphasis should be given to dietary diversity of mothers to improve related outcomes of pregnancy and maternal health.

Keywords: anemia, birth weight, dietary diversity, pregnancy, pregnancy outcome

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Authors: Hossam E. Emam

Abstract:

Metal–organic frameworks (MOFs) are new hybrid materials investigated from 15 years ago; they synthesized from metals as inorganic center joined with multidentate organic linkers to form a 1D, 2D or 3D network structure. MOFs have unique properties such as pore crystalline structure, large surface area, chemical tenability and luminescent characters. These significant properties enable MOFs to be applied in many fields such like gas storage, adsorption/separation, drug delivery/biomedicine, catalysis, polymerization, magnetism and luminescence applications. Recently, many of published reports interested in superiority of MOFs for functionalization of textiles to exploit the unique properties of MOFs. Incorporation of MOFs is found to acquire the textiles some additional formidable functions to be used in considerable fields such like water treatment and fuel purification. Modification of textiles with MOFs could be easily performed by two main techniques; Ex-situ (preparation of MOFs then applied onto textiles) and in-situ (ingrowth of MOFs within textiles networks). Uniqueness of MOFs could be assimilated in acquirement of decorative color, antimicrobial character, anti-mosquitos character, ultraviolet radiation protective, self-clean, photo-luminescent and sensor character. Additionally, textiles treatment with MOFs make it applicable as filter in the adsorption of toxic gases, hazardous materials (such as pesticides, dyes and aromatics molecules) and fuel purification (such as removal of oxygenated, nitrogenated and sulfur compounds). Also, the porous structure of MOFs make it mostly utilized in control release of insecticides from the surface of the textile. Moreover, MOF@textiles as recyclable materials lead it applicable as photo-catalyst composites for photo-degradation of different dyes in the day light. Therefore, MOFs is extensively considered for imparting textiles with formidable properties as ingeniousness way for textile functionalization.

Keywords: MOF, functional textiles, water treatment, fuel purification, environmental applications

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Authors: Karima Qayumi, Alex Norta

Abstract:

The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets.

Keywords: agent-oriented modeling (AOM), business intelligence model (BIM), distributed data mining (DDM), multi-agent system (MAS)

Procedia PDF Downloads 432