Search results for: industrial wireless network (IWN)

Authors: Akshay Suhas Phalke, Manohar S. Chaudhari

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In this paper, we have discussed the multipath routing with its variants. Our purpose is to discuss the different types of the multipath routing mechanism. Here we also put the taxonomy of the multipath routing. Multipath routing is used for the alternate path routing, reliable transmission of data and for better utilization of network resources. We also discussed the multipath routing for topology hiding such as TOHIP. In multipath routing, different parameters such as energy efficiency, packet delivery ratio, shortest path routing, fault tolerance play an important role. We have discussed a number of multipath routing protocol based on different parameters lastly.

Keywords: multi-path routing, WSN, topology, fault detection, trust

Procedia PDF Downloads 356

Authors: Paul Shize Li, Frank Alber

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A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

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Authors: Radwa Mabrook

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Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: collaborative culture, content creation, experimental culture, virtual reality

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Authors: Sewon Kim, Changyeop Lee

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A noble low NOx combustion technology, based on partial oxidation combustion concept in a fuel rich combustion zone, is successfully applied in this research. The burner is designed such that a portion of fuel is heated and pre-vaporized in the furnace then injected into a fuel rich combustion zone so that a partial oxidation reaction occurs. The effects of equivalence ratio, thermal load, and fuel distribution ratio on the emissions of NOx and CO are experimentally investigated. This newly developed combustion technology is successfully applied to industrial furnace, and showed extremely low NOx emission levels.

Keywords: low NOx, combustion, burner, fuel rich

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Authors: Aldona Kluczek

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Energy efficient process have become a pressing research field in manufacturing. The arguments for having an effective industrial energy efficiency processes are interacted with factors: economic and environmental impact, and energy security. Improvements in energy efficiency are most often achieved by implementation of more efficient technology or manufacturing process. Current processes of electricity production represents the biggest consumption of energy and the greatest amount of emissions to the environment. The goal of this study is to improve the potential energy-savings and reduce greenhouse emissions related to improvement scenarios for the treatment of hardwood lumber produced by an industrial plant operating in the U.S. through the application of green balancing procedure, in order to find the preferable efficient technology. The green procedure for energy is based on analysis of energy efficiency data. Three alternative scenarios of the cogeneration systems plant (CHP) construction are considered: generation of fresh steam, the purchase of a new boiler with the operating pressure 300 pounds per square inch gauge (PSIG), an installation of a new boiler with a 600 PSIG pressure. In this paper, the application of a bottom-down modelling for energy flow to devise a streamlined Energy and Emission Flow Analyze method for the technology of producing electricity is illustrated. It will identify efficiency or technology of a given process to be reached, through the effective use of energy, or energy management. Results have shown that the third scenario seem to be the efficient alternative scenario considered from the environmental and economic concerns for treating hardwood lumber. The energy conservation evaluation options could save an estimated 6,215.78 MMBtu/yr in each year, which represents 9.5% of the total annual energy usage. The total annual potential cost savings from all recommendations is $143,523/yr, which represents 30.1% of the total annual energy costs. Estimation have presented that energy cost savings are possible up to 43% (US$ 143,337.85), representing 18.6% of the total annual energy costs.

Keywords: alternative scenario improvements, cogeneration system, energy and emission flow analyze, energy balancing, green procedure, hardwood lumber manufacturing process

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Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

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Authors: Wasif Mughees, Malik Al-Ahmad, Muhammad Naeem

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This research involves the design and analysis of pinch-based water/wastewater networks to minimize water utility in the petrochemical and petroleum industries. A study has been done on Tehran Oil Refinery to analyze feasibilities of regeneration, reuse and recycling of water network. COD is considered as a single key contaminant. Amount of freshwater was reduced about 149m3/h (43.8%) regarding COD. Re-design (or retrofitting) of water allocation in the networks was undertaken. The results were analyzed through graphical method and mathematical programming technique which clearly demonstrated that amount of required water would be determined by mass transfer of COD.

Keywords: minimization, water pinch, water management, pollution prevention

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Authors: Ravi Kiran Jaladi, Ezz I. El-Masry

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Emerging technologies such as ultra-wide band wireless access technology that operate at ultra-low power present several challenges due to their inherent design that limits the use of voltage-mode filters. Therefore, Continuous-time current-mode (CTCM) filters have become very popular in recent times due to the fact they have a wider dynamic range, improved linearity, and extended bandwidth compared to their voltage-mode counterparts. The goal of this research is to develop analog filters which are suitable for the current scaling CMOS technologies. Bulk-driven MOSFET is one of the most popular low power design technique for the existing challenges, while other techniques have obvious shortcomings. In this work, a CTCM Gate-driven (GD) differentiator has been presented with a frequency range from dc to 100MHz which operates at very low supply voltage of 0.7 volts. A novel CTCM Bulk-driven (BD) differentiator has been designed for the first time which reduces the power consumption multiple times that of GD differentiator. These GD and BD differentiator has been simulated using CADENCE TSMC 65nm technology for all the bilinear and biquadratic band-pass frequency responses. These basic building blocks can be used to implement the higher order filters. A 6th order cascade CTCM Chebyshev band-pass filter has been designed using the GD and BD techniques. As a conclusion, a low power GD and BD 6th order chebyshev stagger-tuned band-pass filter was simulated and all the parameters obtained from all the resulting realizations are analyzed and compared. Monte Carlo analysis is performed for both the 6th order filters and the results of sensitivity analysis are presented.

Keywords: bulk-driven (BD), continuous-time current-mode filters (CTCM), gate-driven (GD)

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Authors: Fatemeh Babaeian, Nemai Chandra Karmakar

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Chipless RFID system is a wireless system for tracking and identification which use passive tags for encoding data. The advantage of using chipless RFID tag is having a planar tag which is printable on different low-cost materials like paper and plastic. The printed tag can be attached to different items in the labelling level. Since the price of chipless RFID tag can be as low as a fraction of a cent, this technology has the potential to compete with the conventional optical barcode labels. However, due to the passive structure of the tag, data processing of the reflection signal is a crucial challenge. The captured reflected signal from a tag attached to an item consists of different components which are the reflection from the reader antenna, the reflection from the item, the tag structural mode RCS component and the antenna mode RCS of the tag. All these components are summed up in both time and frequency domains. The effect of reflection from the item and the structural mode RCS component can distort/saturate the frequency domain signal and cause difficulties in extracting the desired component which is the antenna mode RCS. Therefore, it is required to study the reflection of the tag in both time and frequency domains to have a better understanding of the nature of the captured chipless RFID signal. The other benefits of this study can be to find an optimised encoding technique in tag design level and to find the best processing algorithm the chipless RFID signal in decoding level. In this paper, the reflection from a typical backscattered chipless RFID tag with six resonances is analysed, and different components of the signal are separated in both time and frequency domains. Moreover, the time domain signal corresponding to each resonator of the tag is studied. The data for this processing was captured from simulation in CST Microwave Studio 2017. The outcome of this study is understanding different components of a measured signal in a chipless RFID system and a discovering a research gap which is a need to find an optimum detection algorithm for tag ID extraction.

Keywords: antenna mode RCS, chipless RFID tag, resonance, structural mode RCS

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Authors: Hemant Kumar, Nilendu Das

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A study based on ANN structure gives us the information to predict the size of the future in realizing a past event. ANN, IMD (Indian meteorological department) data and remote sensing were used to enable a number of parameters for calculating the size that may occur in the future. A threshold selected specifically above the high-frequency harvest reached the area during the selected seismic activity. In the field of human and local biodiversity it remains to obtain the right parameter compared to the frequency of impact. But during the study the assumption is that predicting seismic activity is a difficult process, not because of the parameters involved here, which can be analyzed and funded in research activity.

Keywords: ANN, Bayesion class, earthquakes, IMD

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Authors: Mahnaz Khalafehnilsaz, Rozina Rahnama

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Introduction: The aging process has been linked to a wide range of non-communicable diseases that cause a loss of health-related quality of life. This process can be worsened if an active and healthy lifestyle is not followed by adults, especially in the workplace. This setting not only may create a sedentary lifestyle but will lead to obesity and overweight in the long term and create unhealthy and inactive aging. In addition, eating habits are always known to be associated with active aging. Therefore, it is very valuable to know the eating patterns of people at work in order to detect and prevent diseases in the coming years. This study aimed to design and test a model to improve eating habits among employees at an industrial complex as a practical strategy. Material and method: The present research was a mixed-method study with a subsequent exploratory design which was carried out in two phases, qualitative and quantitative, in 2018 year. In the first step, participants were selected by purposive sampling (n=34) to ensure representation of different job roles; hours worked, gender, grade, and age groups, and semi-structured interviews were used. All interviews were conducted in the workplace and were audio recorded, transcribed verbatim, and analyzed using the Strauss and Corbin approach. The interview question was, “what were their experiences of eating at work, and how could these nutritional habits affect their health in old age.” Finally, a total of 1500 basic codes were oriented at the open coding step, and they were merged together to create the 17 classes, and six concepts and a conceptual model were designed. The second phase of the study was conducted in the form of a cross-sectional study. After verification of the research tool, the developed questionnaire was examined in a group of employees. In order to test the conceptual model of the study, a total of 500 subjects were included in psychometry. Findings: Six main concepts have been known, including 1. undesirable control of stress, 2. lack of eating knowledge, 3. effect of the social network, 4. lack of motivation for healthy habits, 5. environmental-organizational intensifier, 6. unhealthy eating behaviors. The core concept was “Motivation Loss to do preventive behavior.” The main constructs of the motivational-based model for the promotion of eating habits are “modification and promote of eating habits,” increase of knowledge and competency, convey of healthy nutrition behavior culture and effecting of behavioral model especially in older age, desirable of control stress. Conclusion: A key factor for unhealthy eating behavior at the workplace is a lack of motivation, which can be an obstacle to conduct preventive behaviors at work that can affect the healthy aging process in the long term. The motivational-based model could be considered an effective conceptual framework and instrument for designing interventions for the promotion to create healthy and active aging.

Keywords: aging, eating habits, older age, workplace

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Authors: M. Moyzykh, I. Klichuk, L. Sabirov, D. Kolomentseva, E. Magommedov

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Modern city electrical grids are forced to increase their density due to the increasing number of customers and requirements for reliability and resiliency. However, progress in this direction is often limited by the capabilities of existing network equipment. New energy sources or grid connections increase the level of short-circuit currents in the adjacent network, which can exceed the maximum rating of equipment–breaking capacity of circuit breakers, thermal and dynamic current withstand qualities of disconnectors, cables, and transformers. Superconducting fault current limiter (SFCL) is a modern solution designed to deal with the increasing fault current levels in power grids. The key feature of this device is its instant (less than 2 ms) limitation of the current level due to the nature of the superconductor. In 2019 Moscow utilities installed SuperOx SFCL in the city power grid to test the capabilities of this novel technology. The SFCL became the first SFCL in the Russian energy system and is currently the most powerful SFCL in the world. Modern SFCL uses second-generation high-temperature superconductor (2G HTS). Despite its name, HTS still requires low temperatures of liquid nitrogen for operation. As a result, Moscow SFCL is built with a cryogenic system to provide cooling to the superconductor. The cryogenic system consists of three cryostats that contain a superconductor part and are filled with liquid nitrogen (three phases), three cryocoolers, one water chiller, three cryopumps, and pressure builders. All these components are controlled by an automatic control system. SFCL has been continuously operating on the city grid for over three years. During that period of operation, numerous faults occurred, including cryocooler failure, chiller failure, pump failure, and others (like a cryogenic system power outage). All these faults were eliminated without an SFCL shut down due to the specially designed cryogenic system backups and quick responses of grid operator utilities and the SuperOx crew. The paper will describe in detail the results of SFCL operation and cryogenic system maintenance and what measures were taken to solve and prevent similar faults in the future.

Keywords: superconductivity, current limiter, SFCL, HTS, utilities, cryogenics

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Authors: Prince Suka Neekia Momta, Rita Iheoma Achonyeulo

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Ant Tracking seismic attribute applied over 4-seconds seismic volume revealed structural features triggered by clay diapirism, growth fault development, rapid deltaic sedimentation and intense drilling. The attribute was extracted on vertical seismic sections and time slices. Mega tectonic structures such as growth faults and clay diapirs are visible on vertical sections with obscured minor lineaments or fractures. Fractures are distinctively visible on time slices yielding recognizable patterns corroborating established geologic models. This model seismic attribute enabled the understanding of fluid flow characteristics and production responses. Three structural patterns recognized in the field include: major growth faults, minor faults or lineaments and network of fractures. Three growth faults mapped on seismic section form major deformation bands delimiting the area into three blocks or depocenters. The growth faults trend E-W, dip down-to-south in the basin direction, and cut across the study area. The faults initiating from about 2000ms extended up to 500ms, and tend to progress parallel and opposite to the growth direction of an upsurging diapiric structure. The diapiric structures form the major deformational bands originating from great depths (below 2000ms) and rising to about 1200ms where series of sedimentary layers onlapped and pinchout stratigraphically against the diapir. Several other secondary faults or lineaments that form parallel streaks to one another also accompanied the growth faults. The fracture networks have no particular trend but form a network surrounding the well area. Faults identified in the study area have potentials for structural hydrocarbon traps whereas the presence of fractures created a fractured-reservoir condition that enhanced rapid fluid flow especially water. High aquifer flow potential aided by possible fracture permeability resulted in rapid decline in oil rate. Through the application of Ant Tracking attribute, it is possible to obtain detailed interpretation of structures that can have direct influence on oil and gas production.

Keywords: seismic, attributes, production, structural

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Authors: L. Janská, J. Kubrický

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The article describes a research focused on the influence of the information and communication technology (ICT) on the pupils' learning. The investigation deals with the influences that distinguish between the group of pupils influenced by ICT and the group of pupils not influenced by ICT. The group influenced by ICT should evince a different approach in number of areas (in managing of two and more activities at once, in a quick orientation and searching for information on the Internet, in an ability to quickly and effectively assess the data sources, in the assessment of attitudes and opinions of the other users of the network, in critical thinking, in the preference to work in teams, in the sharing of information and personal data via the virtual social networking, in insisting on the immediate reaction on their every action etc.).

Keywords: ICT influence, digital natives, pupil´s learning

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Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: Miss Suparada Prapawong

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The objectives were to analyze the using of new media in the form of set up candid clip that affects the product and presenter, to study the effectiveness of using new media in the form of set up candid clip in order to increase the circulation and audience satisfaction and to use the earned information and knowledge to develop the communication for publicizing and advertising via new media. This research is qualitative research based on questionnaire and in-depth interview from experts. The findings showed the advantages and disadvantages of communication for publicizing and advertising via new media in the form of set up candid clip including with the specific target group for this kind of advertising. It will be useful for fields of publicizing and advertising in the new media forms at the present.

Keywords: candid clip, communication, new media, social network

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Authors: Mohammed Sabbah, Asmaa Al-Asmar, Doaa Abu-Hani, Fuad Al-Rimawi

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Plant extracts are an increasingly popular natural product with a wide range of potential applications in food, industrial, and health care industries. They are rich in polyphenolic compounds and flavonoids, which have been demonstrated to possess a variety of beneficial properties, including antimicrobial and antioxidant activity. Plant extracts have been found to possess antimicrobial activity against a variety of foodborne pathogens and can be used as a natural preservative to extend the shelf life of food products. They have also strong antioxidant activity, which can reduce the formation of free radicals and oxidation of food components. Recently there is an increase interest in bio-based polymers to be used as innovative “bioplastics” for industrial exploitation e.g. packaging materials for food products. Additionally, incorporation of active compounds (e.g. antioxidants and antimicrobials) in bio-polymer materials is of particular interest since such active polymers can be used as active packaging materials (with antimicrobial and antioxidant activity). In this work, different plant extracts have been characterized for their phenolic compounds, flavonoids content, antioxidant activity (both as free radical scavenging ability and reducing ability), and antimicrobial activity against gram positive and negative bacteria (Escherichia coli; Staphylococcus aureus, and Pseudomonas aeruginosa) as well as antifungal activities (against yeast, mold and Botrytis cinera/a plant pathogen). Results showed that many extracts are rich with polyphenolic compounds and flavonoids and have strong antioxidant activities, and rich with phytochemicals (e.g. rutin, quercetin, oleuropein, tyrosol and hydroxytyrosol). Some extracts showed antibacterial activity against both gram positive and negative bacteria as well as antifungal activities and can work, therefore, as preservatives for food or pharmaceutical industries. As an application, two extracts were used as additive to pectin-based packaging film, and results showed that the addition of these extracts significantly improve their functionality as antimicrobial and antioxidant activity. These biomaterials, therefore can be used in food packaging materials to extend the shelf life of food products.

Keywords: plant extracts, antioxidants, flavonoids, bioplastic, edible biofilm, packaging materials

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Authors: Autumn Rooms Cypres, Barbara Driver

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The purpose of this study is to extend discussions about innovations and career politics. Research questions that grounded this effort were: How does an academic learn the unspoken rules of the academy? What happens politically to an academic’s career when their research speaks against the grain of society? Do professors perceive signals that it is time to move on to another institution or even to another career? Epistemology and Methods: This qualitative investigation was focused on examining perceptions of academics. Therefore an open-ended field study, based on Grounded Theory, was used. This naturalistic paradigm (Lincoln & Guba,1985) was selected because it tends to understand information in terms of whole, of patterns, and in relations to the context of the environment. The technique for gathering data was the process of semi-structured, in-depth interviewing. Twenty five academics across the United States were interviewed relative to their career trajectories and the politics and opportunities they have encountered in relation to their research efforts. Findings: The analysis of interviews revealed four themes: Academics are beholden to 2 specific networks of power that influence their sense of job security; the local network based on their employing university and the national network of scholars who share the same field of research. The fights over what counts as research can and does drift from the intellectual to the political, and personal. Academic were able to identify specific instances of shunning and or punishment from their colleagues related directly to the dissemination of research that spoke against the grain of the local or national networks. Academics identified specific signals from both of these networks indicating that their career was flourishing or withering. Implications: This research examined insights from those who persevered when the fights over what and who counts drifted from the intellectual to the political, and the personal. Considerations of why such drifts happen were offered in the form of a socio-political construct called Fit, which included thoughts on hegemony, discourse, and identity. This effort reveals the importance of understanding what professional capital is relative to job security. It also reveals that fear is an enmeshed and often unspoken part of the culture of Academia. Further research to triangulate these findings would be helpful within international contexts.

Keywords: politics, academia, job security, context

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Authors: Adriana Diaz Triana, Wolfgang Wimmer, Sebastian Glaser, Rainer Pamminger

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SUSTAINEXT is a pioneer initiative in Extremadura, Spain under the EU Biobased industries. SUSTANEXT will scale-up and validate an industrial facility to produce botanical extracts, based on three key pillars. First, the whole valorization of bio-based feedstocks with a zero-waste and zero-emissions ambition. SUSTAINEXT will be deployed with six feedstocks. Three medicinal and aromatic plants (Rosemary, Chamomile, and Lemon verbena) will be locally sourced from disused tobacco fields with installed agri-voltaics; and three underexploited agro-industrial side streams will be further valorized (Olive, artichoke-cardoon, and pomegranate). Second, a dynamic, analytical biorefinery (DYANA) will isolate polyphenol and tri-terpenes from feedstocks in a disruptive and circular way. SUSTAINEXT explores 12 valorization routes (VRs) to extract and purify 46 functional ingredients, of which 13 are new in the market and 12 are newly produced in Europe. Third, the integrated and versatile value chain engages all actors, from feedstocks suppliers to extract users in the industries of food, animal feed, nutraceuticals, cosmetics, chemical performance, soil enhancers and fertilizers. This paper addresses SUTAINEXT activities towards zero impacts and full regulatory compliance. A comprehensive Life Cycle Thinking approach is proposed, with four complementary assessments running iteratively along the project duration (4,5 years). These are the Life Cycle Cost (LCCA), Life Cycle (LCA), Social Life Cycle (S-LCA) and Circularity (CA) assessments. The LCA will help evaluate the feedstock suitability parameters and intrinsic characteristics that quantify the feedstock´s grade for a determined use, and the feedstock´s suitability index for a specific VR. The LCA will also study the emissions, land use change, energy generation and consumption, and other environmental aspects and impacts of the VRs, to identify the most resource efficient and less impactful distribution of products from the circular biorefinery model used in SUSTAINEXT. Challenges to complete the LCA include the definition of the system boundaries, carrying out a robust inventory, and the proper allocation of impacts to the different VRs.

Keywords: biorefinery, botanical extracts, life cycle assessment, valorization routes.

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Authors: Michal Malik, Jiri Primas, Darina Jasikova, Michal Kotek, Vaclav Kopecky

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This paper is a case study dealing with the viability of using Electrical Impedance Tomography for measuring cavitation clouds in a pipe setup. The authors used a simple passive cavitation generator to cause a cavitation cloud, which was then recorded for multiple flow rates using electrodes in two measuring planes. The paper presents the results of the experiment, showing the used industrial grade tomography system ITS p2+ is able to measure the cavitation cloud and may be particularly useful for identifying the inception of cavitation in setups where other measuring tools may not be viable.

Keywords: cavitation cloud, conductivity measurement, electrical impedance tomography, mechanically induced cavitation

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Authors: Zeyad Abdelmageid, Xianbin Wang

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Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterward. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed, and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due to the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With the proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and, at times, better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead

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Authors: P. Suparada, D. Eakapotch

Abstract:

The objectives were to analyze the using of new media in the form of set up candid clip that affects the product and presenter, to study the effectiveness of using new media in the form of set up candid clip in order to increase the circulation and audience satisfaction and to use the earned information and knowledge to develop the communication for publicizing and advertising via new media. This research is qualitative research based on questionnaire and in-depth interview from experts. The findings showed the advantages and disadvantages of communication for publicizing and advertising via new media in the form of set up candid clip including with the specific target group for this kind of advertising. It will be useful for fields of publicizing and advertising in the new media forms at the present.

Keywords: candid clip, communication, new media, social network

Procedia PDF Downloads 249

Authors: Giovanni Incerti

Abstract:

The paper presents a method for a simple and immediate motion planning of a SCARA robot, whose end-effector has to move along a given trajectory; the calculation procedure requires the user to define in analytical form or by points the trajectory to be followed and to assign the curvilinear abscissa as function of the time. On the basis of the geometrical characteristics of the robot, a specifically developed program determines the motion laws of the actuators that enable the robot to generate the required movement; this software can be used in all industrial applications for which a SCARA robot has to be frequently reprogrammed, in order to generate various types of trajectories with different motion times.

Keywords: motion planning, SCARA robot, trajectory tracking, analytical form

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Authors: Xiaohong Xu, Tianchu Zhang, Yangfan Chen, Rongtai Tan

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In Canada, Air Quality Health Index (AQHI) is a scale designed to help residences understand the impact of air quality on human health. In Ontario, Canada, AQHI was implemented in June 2015. This study investigated temporal variability of daily AQHI and impact of regional transport on AQHI in Windsor, Ontario, Canada from 2016 to 2019. During 2016–2019, 1428 daily AQHIs were recorded in Windsor Downtown Station. Among those, the AQHIs were at the low health risk level (AQHI = 1, 2 or 3) in 82% of days, only a few days at high risk level (AQHI = 7), the rest were at moderate health risk level (AQHI = 4, 5, 6), indicating air quality in Windsor was fairly good with relatively low health risk. The annual mean AQHI value decreased from 2.95 in 2016 to 2.81 in 2019, demonstrating the improvement of air quality. Half of the days, AQHI were 3 regardless of season. AQHI was higher in the warm season (3.1) than in the cold season (2.6) due to more frequent moderate risk days (27%, AQHI = 4) in warm season and more frequent low risk days (42%, AQHI = 2) in the cold season. Among the three pollutants considered in AQHI calculation, O3 was the most frequently reported dominant contributor to daily AQHI (88% of days), followed by NO2 (12%), especially in the cold season, with small contribution from PM2.5 (<1%). In the past two decades, NO2 concentrations had decreased significantly and O3 concentrations had increased, resulting in daily AQHI being less reliance on NO2 (from 51% of days being the primary contributor during 2003–2010 to 12% during 2016–2019) and more on O3 concentrations (49% to 88%). Trajectory analysis found that AQHI ≤ 3 days were closely associated with air masses from the north and northwest, whereas AQHI > 3 days were closely associated with air masses from the west and southwest. This is because northerly flows brought in clear air mass owing to less industrial facilities, while polluted air masses were transported from the south of Windsor, where several industrial states of the US were located. Overall, O3 concentrations dictate the daily AQHI values, the seasonal variability of AQHI, and the impact of regional transport on AQHI in Windsor. This makes further reductions of AQHI challenging because O3 concentrations are likely to continue increasing due to weakened consumption of O3 by NO owing to decreasing NO emissions and more hot days because of climate change. The predominant and increasing contribution of O3 to AQHI calls for more effective control measures to mitigate O3 pollution and its impact on human health and the environment.

Keywords: air quality, Air Quality Health Index (AQHI), hysplit, regional transport, windsor

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Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

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To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

Procedia PDF Downloads 87

Authors: Ibrahim Mostafa El-Mongy, Abdelmegid Allam

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In this article analysis and investigation of the effect of loading a horn antenna with frequency selective surface (FSS) of crossed dipoles of finite size is presented. It is fabricated on Rogers RO4350 (lossy) of relative permittivity 3.33, thickness 1.524 mm and loss tangent 0.004. Basically it is applied for filtering and minimizing the interference and noise in the desired band. The filtration is carried out using a finite FSS of crossed dipoles of overall dimensions 98x58 mm2. The filtration is shown by limiting the transmission bandwidth from 4 GHz (8–12 GHz) to 0.25 GHz (10.75–11 GHz). It is simulated using CST MWS and measured using network analyzer. There is a good agreement between the simulated and measured results.

Keywords: antenna, filtenna, frequency selective surface (FSS), horn

Procedia PDF Downloads 459

Authors: Kayne Uriel K. Rodrigo, Jerriane Hillary Heart S. Marcial, Samuel C. Brillo

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Rice leaf diseases significantly impact yield production in rice-dependent countries, affecting their agricultural sectors. As part of precision agriculture, early and accurate detection of these diseases is crucial for effective mitigation practices and minimizing crop losses. Hence, this study proposes an enhancement to the Convolutional Neural Network (CNN), a widely-used method for Rice Leaf Disease Image Classification, by incorporating MobileViTV2—a recently advanced architecture that combines CNN and Vision Transformer models while maintaining fewer parameters, making it suitable for broader deployment on edge devices. Our methodology utilizes a publicly available rice disease image dataset from Kaggle, which was validated by a university structural biologist following the guidelines provided by the Philippine Rice Institute (PhilRice). Modifications to the dataset include renaming certain disease categories and augmenting the rice leaf image data through rotation, scaling, and flipping. The enhanced dataset was then used to train the MobileViTV2 model using the Timm library. The results of our approach are as follows: the model achieved notable performance, with 98% accuracy in both training and validation, 6% training and validation loss, and a Receiver Operating Characteristic (ROC) curve ranging from 95% to 100% for each label. Additionally, the F1 score was 97%. These metrics demonstrate a significant improvement compared to a conventional CNN-based approach, which, in a previous 2022 study, achieved only 78% accuracy after using 5 convolutional layers and 2 dense layers. Thus, it can be concluded that MobileViTV2, with its fewer parameters, outperforms traditional CNN models, particularly when applied to Rice Leaf Disease Image Identification. For future work, we recommend extending this model to include datasets validated by international rice experts and broadening the scope to accommodate biotic factors such as rice pest classification, as well as abiotic stressors such as climate, soil quality, and geographic information, which could improve the accuracy of disease prediction.

Keywords: convolutional neural network, MobileViTV2, rice leaf disease, precision agriculture, image classification, vision transformer

Procedia PDF Downloads 30

Authors: Salah Ghamari

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In this study, the ability of self organizing map artificial (SOM) neural networks in clustering the wheat seeds varieties according to morphological properties of them was considered. The SOM is one type of unsupervised competitive learning. Experimentally, five morphological features of 300 seeds (including three varieties: gaskozhen, Md and sardari) were obtained using image processing technique. The results show that the artificial neural network has a good performance (90.33% accuracy) in classification of the wheat varieties despite of high similarity in them. The highest classification accuracy (100%) was achieved for sardari.

Keywords: artificial neural networks, clustering, self organizing map, wheat variety

Procedia PDF Downloads 659

Authors: Thomas Chinedu Aniokete, Gordian Onyebuchukwu Mbah, Michael Daramola

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A sustainable NaOH integrated hydrothermal protocol was developed for the synthesis of waste-derived hydroxy sodalite catalysts for transesterification of waste animal fat (WAF) with a high per cent free fatty acid (FFA) to biodiesel. In this work, hydroxy sodalite catalyst was synthesized from two complex waste materials namely coal fly ash (CFA) and waste industrial brine (WIB). Measured amounts of South African CFA and WIB obtained from a coal mine field were mixed with NaOH solution at different concentrations contained in secured glass vessels equipped with magnetic stirrers and formed consistent slurries after aging condition at 47 oC for 48 h. The slurries were then subjected to hydrothermal treatments at 140 oC for 48 h, washed thoroughly and separated by the action of a centrifuge on the mixture. The resulting catalysts were calcined in a muffle furnace for 2 h at 200 oC and subsequently characterized for different effects using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FT-IR), and Bennett Emmet Teller (BET) adsorption-desorption techniques. The produced animal fat methyl ester (AFME) was analyzed using the gas chromatography-mass spectrometry (GC-MS) method. Results of the investigation indicate profoundly an enhanced catalyst purity, textural property and desired morphology due to the action of NaOH. Similarly, the performance evaluation with respect to catalyst activity reveals a high catalytic conversion efficiency of 98 % of the high FFA WAF to biodiesel under the following reaction conditions; a methanol-to-WAF ratio of 15:1, amount of SOD catalyst of 3 wt % with a stirring speed of 300-500 rpm, a reaction temperature of 60 oC and a reaction time of 8 h. There was a recovered 96 % stable catalyst after reactions and potentially recyclable, thus contributing to the economic savings to the process that had been a major bottleneck to the production of biodiesel. This NaOH route for synthesizing waste-derived hydroxy sodalite (SOD) catalyst is a sustainable and eco-friendly technology that speaks directly to the global quest for renewable-fossil fuel controversy enforcing sustainable development goal 7.

Keywords: coal fly ash, waste industrial brine, waste-derived hydroxy sodalite catalyst, sodium hydroxide, biodiesel, transesterification, biomass conversion

Procedia PDF Downloads 35

Authors: H. Parveen Begam, M. A. Maluk Mohamed

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Mobile Grid Computing is an environment that allows sharing and coordinated use of diverse resources in dynamic, heterogeneous and distributed environment using different types of electronic portable devices. In a grid environment the security issues are like authentication, authorization, message protection and delegation handled by GSI (Grid Security Infrastructure). Proving better security between mobile devices and grid infrastructure is a major issue, because of the open nature of wireless networks, heterogeneous and distributed environments. In a mobile grid environment, the individual computing devices may be resource-limited in isolation, as an aggregated sum, they have the potential to play a vital role within the mobile grid environment. Some adaptive methodology or solution is needed to solve the issues like authentication of a base station, security of information flowing between a mobile user and a base station, prevention of attacks within a base station, hand-over of authentication information, communication cost of establishing a session key between mobile user and base station, computing complexity of achieving authenticity and security. The sharing of resources of the devices can be achieved only through the trusted relationships between the mobile hosts (MHs). Before accessing the grid service, the mobile devices should be proven authentic. This paper proposes the dynamic certificate based mutual authentication protocol between two mobile hosts in a mobile grid environment. The certificate generation process is done by CA (Certificate Authority) for all the authenticated MHs. Security (because of validity period of the certificate) and dynamicity (transmission time) can be achieved through the secure service certificates. Authentication protocol is built on communication services to provide cryptographically secured mechanisms for verifying the identity of users and resources.

Keywords: mobile grid computing, certificate authority (CA), SSL/TLS protocol, secured service certificates

Procedia PDF Downloads 308