Search results for: neural signal recording

Authors: Maria Arechavaleta, Mark Halpin

Abstract:

In the United States, costs of solar energy systems have declined to the point that they are viable options for most consumers. However, there are no consistent procedures for specifying sufficient systems. The factors that must be considered are energy consumption, potential solar energy production, and cost. The traditional method of specifying solar energy systems is based on assumed daily levels of available solar energy and average amounts of daily energy consumption. The mismatches between energy production and consumption are usually mitigated using battery energy storage systems, and energy use is curtailed when necessary. The main consumer decision question that drives the total system cost is how much unserved (or curtailed) energy is acceptable? Of course additional solar conversion equipment can be installed to provide greater peak energy production and extra energy storage capability can be added to mitigate longer lasting low solar energy production periods. Each option increases total cost and provides a benefit which is difficult to quantify accurately. An approach to quantify the cost-benefit of adding additional resources, either production or storage or both, based on the statistical concepts of loss-of-energy probability and expected unserved energy, is presented in this paper. Relatively simple calculations, based on site-specific energy availability and consumption data, can be used to show the value of each additional increment of production or storage. With this incremental benefit-cost information, consumers can select the best overall performance combination for their application at a cost they are comfortable paying. The approach is based on a statistical analysis of energy consumption and production characteristics over time. The characteristics are in the forms of curves with each point on the curve representing an energy consumption or production value over a period of time; a one-minute period is used for the work in this paper. These curves are measured at the consumer location under the conditions that exist at the site and the duration of the measurements is a minimum of one week. While greater accuracy could be obtained with longer recording periods, the examples in this paper are based on a single week for demonstration purposes. The weekly consumption and production curves are overlaid on each other and the mismatches are used to size the battery energy storage system. Loss-of-energy probability and expected unserved energy indices are calculated in addition to the total system cost. These indices allow the consumer to recognize and quantify the benefit (probably a reduction in energy consumption curtailment) available for a given increase in cost. Consumers can then make informed decisions that are accurate for their location and conditions and which are consistent with their available funds.

Keywords: battery energy storage systems, loss of load probability, residential renewable energy, solar energy systems

Procedia PDF Downloads 221

Authors: Suzanne Strauss, Leandi Steenkamp

Abstract:

The Finnish symphonic metal band Nightwish is the brainchild of songwriter and lyricist TuomasHolopainen and the band recorded their first demonstration recording in 1996. The band has since produced nine full-length studio albums, the most recent being the 2020 album Human. :||: Nature., and has reached massive international success. The band is well known for songs about fantasy and escapism and employs many sonic, visual and branding tools and techniques to communicate these constructs to the audience. Among these, is the band’s creation of the so-called “Nightwish world and mythology” with a set of recurring characters and narratives which, in turn, creates a psychological anchor and safe space for Nightwish fans around the globe. Nature and the reverence of nature are central themes in Nightwish’s self-created mythology.Swiss psychologist Carl Jung’s theory of the collective unconscious identified a mysterious reservoir of psychological constructs common to all people, being derived from ancestral memory and experience, common to all humankind, and distinct from the individual’s personal unconscious. Furthermore, he defined archetypes as timeless collective patterns and images that springs forth from the collective unconscious. Archetypes can be actualized when they enter consciousness as images in interaction with the outside world. Archetypal patterns or images can manifest in different ways across world cultures, but follow common patterns, also known as archetypal themes and symbols. The Jungian approach to the psyche places great emphasis on nature, positing a direct link betweenthe concept of wholeness and responsible care for nature and the environment.In our proposed paper, we examine, by means of thematic content analysis, how Nightwish makes use of archetypal themes and symbols referring to nature and the environment in selected songs from their ninth full-length album Human. II Nature. Furthermore, we argue that the longing for and reverence of nature in selected Nightwish songs may serve as a type of “social intervention” and social critique on modern capitalist society. The type of social critique that the band offers is generally connoted intertextually and is not equally explicit in their songs. The band uses a unique combination of escapism, fantasy, and nature narratives to inspire a sense of wonder, enchantment, and magic in the listener. In this way, escapism, fantasy, and nature serve as postmodern frames of reference that aim to “re-enchant” the disenchanted and de-spiritualized. In this way, re-enchantment could also refer to spiritual and/or psychological healing and rebirth.

Keywords: archetypes, metal music, nature, Nightwish, social interventions

Procedia PDF Downloads 96

Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

Abstract:

The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

Procedia PDF Downloads 163

Authors: Tünde Puskás, Anita Andersson

Abstract:

This study is part of a research project about whether religion is considered as part of Swedish cultural heritage in Swedish preschools. Our aim in this paper is to explore how a Swedish preschool balance between keeping the education non-confessional and at the same time teaching children about a particular tradition, Easter.The paper explores how in a Swedish preschool with a religious profile teachers balance between keeping education non-confessional and teaching about a tradition with religious roots. The point of departure for the theoretical frame of our study is that practical considerations in pedagogical situations are inherently dilemmatic. The dilemmas that are of interest for our study evolve around formalized, intellectual ideologies, such us multiculturalism and secularism that have an impact on everyday practice. Educational dilemmas may also arise in the intersections of the formalized ideology of non-confessionalism, prescribed in policy documents and the common sense understandings of what is included in what is understood as Swedish cultural heritage. In this paper, religion is treated as a human worldview that, similarly to secular ideologies, can be understood as a system of thought. We make use of Ninian Smart's theoretical framework according to which in modern Western world religious and secular ideologies, as human worldviews, can be studied from the same analytical framework. In order to be able to study the distinctive character of human worldviews Smart introduced a multi-dimensional model within which the different dimensions interact with each other in various ways and to different degrees. The data for this paper is drawn from fieldwork carried out in 2015-2016 in the form of video ethnography. The empirical material chosen consists of a video recording of a specific activity during which the preschool group took part in an Easter play performed in the local church. The analysis shows that the policy of non-confessionalism together with the idea that teaching covering religious issues must be purely informational leads in everyday practice to dilemmas about what is considered religious. At the same time what the adults actually do with religion fulfills six of seven dimensions common to religious traditions as outlined by Smart. What we can also conclude from the analysis is that whether it is religion or a cultural tradition that is thought through the performance the children watched in the church depends on how the concept of religion is defined. The analysis shows that the characters of the performance themselves understood religion as the doctrine of Jesus' resurrection from the dead. This narrow understanding of religion enabled them indirectly to teach about the traditions and narratives surrounding Easter while avoiding teaching religion as a belief system.

Keywords: non-confessional education, preschool, religion, tradition

Procedia PDF Downloads 148

Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon

Abstract:

We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particle­based multiplexing, using patented Firefly hydrogel particles, with single­ step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target­-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.

Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry

Procedia PDF Downloads 347

Authors: Min Kyung An

Abstract:

In this paper, we study the data collection problem in Wireless Sensor Networks (WSNs) adopting the two interference models: The graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR). The main issue of the problem is to compute schedules with the minimum number of timeslots, that is, to compute the minimum latency schedules, such that data from every node can be collected without any collision or interference to a sink node. While existing works studied the problem with unit-sized and unbounded-sized message models, we investigate the problem with the bounded-sized message model, and introduce a constant factor approximation algorithm. To the best known of our knowledge, our result is the first result of the data collection problem with bounded-sized model in both interference models.

Keywords: data collection, collision-free, interference-free, physical interference model, SINR, approximation, bounded-sized message model, wireless sensor networks

Procedia PDF Downloads 204

Authors: Surajit Bhattacharya, Daniel Veltri, Atit A. Patel, Daniel N. Cox

Abstract:

miRNAs have emerged as key post-transcriptional regulators of gene expression, however identification of biologically-relevant target genes for this epigenetic regulatory mechanism remains a significant challenge. To address this knowledge gap, we have developed a novel tool in R, Intra-miR-ExploreR, that facilitates integrated discovery of miRNA targets by incorporating target databases and novel target prediction algorithms, using statistical methods including Pearson and Distance Correlation on microarray data, to arrive at high confidence intragenic miRNA target predictions. We have explored the efficacy of this tool using Drosophila melanogaster as a model organism for bioinformatics analyses and functional validation. A number of putative targets were obtained which were also validated using qRT-PCR analysis. Additional features of the tool include downloadable text files containing GO analysis from DAVID and Pubmed links of literature related to gene sets. Moreover, we are constructing interaction maps of intragenic miRNAs, using both micro array and RNA-seq data, focusing on neural tissues to uncover regulatory codes via which these molecules regulate gene expression to direct cellular development.

Keywords: miRNA, miRNA:mRNA target prediction, statistical methods, miRNA:mRNA interaction network

Procedia PDF Downloads 488

Authors: Koichi Kurita

Abstract:

In this study, an effective non-contact technique for the detection of human physical activity is proposed. The technique is based on detecting the electrostatic induction current generated by the walking motion under non-contact and non-attached conditions. A theoretical model for the electrostatic induction current generated because of a change in the electric potential of the human body is proposed. By comparing the obtained electrostatic induction current with the theoretical model, it becomes obvious that this model effectively explains the behavior of the waveform of the electrostatic induction current. The normal walking motions are recorded using a portable sensor measurement located in a passageway　of office building. The obtained results show that detailed information regarding physical activity such as a walking cycle can be estimated using our proposed technique. This suggests that the proposed technique which is based on the detection of the walking signal, can be successfully applied to the detection of human walking motion in a secured building.

Keywords: human walking motion, access control, electrostatic induction, alarm monitoring

Procedia PDF Downloads 346

Authors: Harriet Jane R. Caleja, Joel I. Ballesteros, Florian R. Del Mundo

Abstract:

The dengue fever belongs to the world’s major cause of death, especially in the tropical areas. In the Philippines, the number of dengue cases during the first half of 2015 amounted to more than 50,000. In 2012, the total number of cases of dengue infection reached 132,046 of which 701 patients died. Dengue Nonstructural 1 virus (Dengue NS1 virus) is a recently discovered biomarker for the early detection of dengue virus. It is present in the serum of the dengue virus infected patients even during the earliest stages prior to the formation of dengue virus antibodies. A biosensor for the dengue detection using NS1 virus was developed for faster and accurate diagnostic tool. Biotinylated anti-dengue virus NS1 was used as the receptor for dengue virus NS1. Using the Diffractive Optics Technology (dotTM) technique, real time binding of the NS1 virus to the biotinylated anti-NS1 antibody is observed. The dot®-Avidin sensor recognizes the biotinylated anti-NS1 and this served as the capture molecule to the analyte, NS1 virus. The increase in the signal of the diffractive intensity signifies the binding of the capture and the analyte. The LOD was found to be 3.87 ng/mL while the LOQ is 12.9 ng/mL. The developed biosensor was also found to be specific for the NS1 virus.

Keywords: avidin-biotin, diffractive optics technology, immunosensor, NS1

Procedia PDF Downloads 312

Authors: Amit Kumar Verma

Abstract:

The present study deals with fire prediction model in Terai Arc Landscape, one of the most dramatic ecosystems in Asia where large, wide-ranging species such as tiger, rhinos, and elephant will thrive while bringing economic benefits to the local people. Forest fires cause huge economic and ecological losses and release considerable quantities of carbon into the air and is an important factor inflating the global burden of carbon emissions. Forest fire is an important factor of behavioral cum ecological habit of tiger in wild. Post fire changes i.e. micro and macro habitat directly affect the tiger habitat or land. Vulnerability of fire depicts the changes in microhabitat (humus, soil profile, litter, vegetation, grassland ecosystem). Microorganism like spider, annelids, arthropods and other favorable microorganism directly affect by the forest fire and indirectly these entire microorganisms are responsible for the development of tiger (Panthera tigris) habitat. On the other hand, fire brings depletion in prey species and negative movement of tiger from wild to human- dominated areas, which may leads the conflict i.e. dangerous for both tiger & human beings. Early forest fire prediction through mapping the risk zones can help minimize the fire frequency and manage forest fires thereby minimizing losses. Satellite data plays a vital role in identifying and mapping forest fire and recording the frequency with which different vegetation types are affected. Thematic hazard maps have been generated by using IDW technique. A prediction model for fire occurrence is developed for TAL. The fire occurrence records were collected from state forest department from 2000 to 2014. Disciminant function models was used for developing a prediction model for forest fires in TAL, random points for non-occurrence of fire have been generated. Based on the attributes of points of occurrence and non-occurrence, the model developed predicts the fire occurrence. The map of predicted probabilities classified the study area into five classes very high (12.94%), high (23.63%), moderate (25.87%), low(27.46%) and no fire (10.1%) based upon the intensity of hazard. model is able to classify 78.73 percent of points correctly and hence can be used for the purpose with confidence. Overall, also the model works correctly with almost 69% of points. This study exemplifies the usefulness of prediction model of forest fire and offers a more effective way for management of forest fire. Overall, this study depicts the model for conservation of tiger’s natural habitat and forest conservation which is beneficial for the wild and human beings for future prospective.

Keywords: fire prediction model, forest fire hazard, GIS, landsat, MODIS, TAL

Procedia PDF Downloads 340

Authors: Mohammed Fakehy, Mohammed Haggag

Abstract:

The problem of test anxiety considered as one of the most important and most complex psychological problems faced by students of King Saud University, where university students in a need to bring their reassurance and psychological comfort, relieves feeling pain and difficulties of the study. Recently, there are programs and science that help human to change, including the science Linguistic Programming this neural science stems from not just the tips of the need to make the effort or continue to work, but provides the keys in which one can be controlled in the internal environment. Even human potential energy is extracted seeking to achieve success and happiness and excellence. Through the work of the researchers as members of the teaching staff at King Saud University and specialists in the field of psychology noticed the suffering of some students of King Saud University, test anxiety. In an attempt by the researchers to mitigate as much as possible of the unity of this concern, students will have a training program in Neuro Linguistic Programming. The main Question of this study is What is the effectiveness of the impact of a training program using NLP to reduce test anxiety by using a biological feedback. Therefore, the results of this study might serve as a good announcement about the usefulness of NLP programs which influence future research to significant effect of NLP on test anxiety.

Keywords: neuro linguistic programming, test anxiety, biological feedback, king saud

Procedia PDF Downloads 502

Authors: Cristina Felipeto, Catherine Bore, Eduardo Calil

Abstract:

This work aims to analyze and compare the punctuation marks (PM) in school texts of Brazilian and French students and the comments on these PM made spontaneously by the students during the ongoing text. Assuming textual genetics as an investigative field within a dialogical and enunciative approach, we defined a common methodological design in two 1st year classrooms (7 years old) of the primary school, one classroom in Brazil (Maceio) and the other one in France (Paris). Through a multimodal capture system of writing processes in real time and space (Ramos System), we recorded the collaborative writing proposal in dyads in each of the classrooms. This system preserves the classroom’s ecological characteristics and provides a video recording synchronized with dialogues, gestures and facial expressions of the students, the stroke of the pen’s ink on the sheet of paper and the movement of the teacher and students in the classroom. The multimodal register of the writing process allowed access to the text in progress and the comments made by the students on what was being written. In each proposed text production, teachers organized their students in dyads and requested that they should talk, combine and write a fictional narrative. We selected a Dyad of Brazilian students (BD) and another Dyad of French students (FD) and we have filmed 6 proposals for each of the dyads. The proposals were collected during the 2nd Term of 2013 (Brazil) and 2014 (France). In 6 texts written by the BD there were identified 39 PMs and 825 written words (on average, a PM every 23 words): Of these 39 PMs, 27 were highlighted orally and commented by either student. In the texts written by the FD there were identified 48 PMs and 258 written words (on average, 1 PM every 5 words): Of these 48 PM, 39 were commented by the French students. Unlike what the studies on punctuation acquisition point out, the PM that occurred the most were hyphens (BD) and commas (FD). Despite the significant difference between the types and quantities of PM in the written texts, the recognition of the need for writing PM in the text in progress and the comments have some common characteristics: i) the writing of the PM was not anticipated in relation to the text in progress, then they were added after the end of a sentence or after the finished text itself; ii) the need to add punctuation marks in the text came after one of the students had ‘remembered’ that a particular sign was needed; iii) most of the PM inscribed were not related to their linguistic functions, but the graphic-visual feature of the text; iv) the comments justify or explain the PM, indicating metalinguistic reflections made by the students. Our results indicate how the comments of the BD and FD express the dialogic and subjective nature of knowledge acquisition. Our study suggests that the initial learning of PM depends more on its graphic features and interactional conditions than on its linguistic functions.

Keywords: collaborative writing, erasure, graphic marks, learning, metalinguistic awareness, textual genesis

Procedia PDF Downloads 147

Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

Abstract:

In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove

Procedia PDF Downloads 280

Authors: M. Lghoul, N. El Goumi, M. Guernouche

Abstract:

In order to predict the structural and tectonic framework of the Bahira basin and to have a 3D geological modeling of the basin, an integrated multidisciplinary work has been conducted using gravity, magnetic and geological data. The objective of the current study is delineating the subsurfacefeatures, faults, and geological limits, using airborne magnetic and gravity data analysis of the Bahira basin. To achieve our goal, we have applied different enhanced techniques on magnetic and gravity data: power spectral analysis techniques, reduction to pole (RTP), upward continuation, analytical signal, tilt derivative, total horizontal derivative, 3D Euler deconvolutionand source parameter imagining. The major lineaments/faults trend are: NE–SW, NW-SE, ENE–WSW, and WNW–ESE. The 3D Euler deconvolution analysis highlighted a number of fault trend, mainly in the ENE-WSW, WNW-ESE directions. The depth tothe top of the basement sources in the study area ranges between 200 m, in the southern and northern part of the Bahira basin, to 5000 m located in the Eastern part of the basin.

Keywords: magnetic, gravity, structural trend, depth to basement

Procedia PDF Downloads 117

Authors: Mohammad Sabbagh

Abstract:

Anyone who reads the Torah or the Quran learns that GOD created everything that is around us, seen and unseen, in six days. Within HIS plan of creation, HE placed for us a key proof of HIS existence which is essentially computers and the ability to program them. Digital computer programming began with binary instructions, which eventually evolved to what is known as high-level programming languages. Any programmer in our modern time can attest that you are essentially giving the computer commands by words and when the program is compiled, whatever is processed as output is limited to what the computer was given as an ability and furthermore as an instruction. So one can deduce that GOD created everything around us with HIS words, programming everything around in six days, just like how we can program a virtual world on the computer. GOD did mention in the Quran that one day where GOD’s throne is, is 1000 years of what we count; therefore, one might understand that GOD spoke non-stop for 6000 years of what we count, and gave everything it’s the function, attributes, class, methods and interactions. Similar to what we do in object-oriented programming. Of course, GOD has the higher example, and what HE created is much more than OOP. So when GOD said that everything is already predetermined, it is because any input, whether physical, spiritual or by thought, is outputted by any of HIS creatures, the answer has already been programmed. Any path, any thought, any idea has already been laid out with a reaction to any decision an inputter makes. Exalted is GOD!. GOD refers to HIMSELF as The Fastest Accountant in The Quran; the Arabic word that was used is close to processor or calculator. If you create a 3D simulation of a supernova explosion to understand how GOD produces certain elements and fuses protons together to spread more of HIS blessings around HIS skies; in 2022 you are going to require one of the strongest, fastest, most capable supercomputers of the world that has a theoretical speed of 50 petaFLOPS to accomplish that. In other words, the ability to perform one quadrillion (1015) floating-point operations per second. A number a human cannot even fathom. To put in more of a perspective, GOD is calculating when the computer is going through those 50 petaFLOPS calculations per second and HE is also calculating all the physics of every atom and what is smaller than that in all the actual explosion, and it’s all in truth. When GOD said HE created the world in truth, one of the meanings a person can understand is that when certain things occur around you, whether how a car crashes or how a tree grows; there is a science and a way to understand it, and whatever programming or science you deduce from whatever event you observed, it can relate to other similar events. That is why GOD might have said in The Quran that it is the people of knowledge, scholars, or scientist that fears GOD the most! One thing that is essential for us to keep up with what the computer is doing and for us to track our progress along with any errors is we incorporate logging mechanisms and backups. GOD in The Quran said that ‘WE used to copy what you used to do’. Essentially as the world is running, think of it as an interactive movie that is being played out in front of you, in a full-immersive non-virtual reality setting. GOD is recording it, from every angle to every thought, to every action. This brings the idea of how scary the Day of Judgment will be when one might realize that it’s going to be a fully immersive video when we would be getting and reading our book.

Keywords: programming, the Quran, object orientation, computers and humans, GOD

Procedia PDF Downloads 95

Authors: Mmatladi D. Mnguni, Mustapha Mohammed, George Y. Mahama, Alhassan L. Abdulai, Felix D. Dakora

Abstract:

Industrial-based nitrogen (N) fertilizers are justifiably credited for the current state of food production across the globe, but their continued use is not sustainable and has an adverse effect on the environment. The search for greener and sustainable technologies has led to an increase in exploiting biological systems such as legumes and organic amendments for plant growth promotion in cropping systems. Although the benefits of legume rotation with cereal crops have been documented, the full benefits of soybean-sorghum rotation systems have not been properly evaluated in Africa. This study explored the benefits of soybean-sorghum rotation through assessing N₂ fixation and water-use efficiency of soybean in rotation with sorghum with and without organic and inorganic amendments. The field trials were conducted from 2017 to 2020. Sorghum was grown on plots previously cultivated to soybean and vice versa. The succeeding sorghum crop received fertilizer amendments [organic fertilizer (5 tons/ha as poultry litter, OF); inorganic fertilizer (80N-60P-60K) IF; organic + inorganic fertilizer (OF+IF); half organic + inorganic fertilizer (HIF+OF); organic + half inorganic fertilizer (OF+HIF); half organic + half inorganic (HOF+HIF) and control] and was arranged in a randomized complete block design. The soybean crop succeeding fertilized sorghum received a blanket application of triple superphosphate at 26 kg P ha⁻¹. Nitrogen fixation and water-use efficiency were respectively assessed at the flowering stage using the ¹⁵N and ¹³C natural abundance techniques. The results showed that the shoot dry matter of soybean plants supplied with HOF+HIF was much higher (43.20 g plant-1), followed by OF+HIF (36.45 g plant⁻¹), and HOF+IF (33.50 g plant⁻¹). Shoot N concentration ranged from 1.60 to 1.66%, and total N content from 339 to 691 mg N plant⁻¹. The δ¹⁵N values of soybean shoots ranged from -1.17‰ to -0.64‰, with plants growing on plots previously treated to HOF+HIF exhibiting much higher δ¹⁵N values, and hence lower percent N derived from N₂ fixation (%Ndfa). Shoot %Ndfa values varied from 70 to 82%. The high %Ndfa values obtained in this study suggest that the previous year’s organic and inorganic fertilizer amendments to sorghum did not inhibit N₂ fixation in the following soybean crop. The amount of N-fixed by soybean ranged from 106 to 197 kg N ha⁻¹. The treatments showed marked variations in carbon (C) content, with HOF+HIF treatment recording the highest C content. Although water-use efficiency varied from -29.32‰ to -27.85‰, shoot water-use efficiency, C concentration, and C:N ratio were not altered by previous fertilizer application to sorghum. This study provides strong evidence that previous HOF+HIF sorghum residues can enhance N nutrition and water-use efficiency in nodulated soybean.

Keywords: ¹³C and ¹⁵N natural abundance, N-fixed, organic and inorganic fertilizer amendments, shoot %Ndfa

Procedia PDF Downloads 155

Authors: Rovina Kobun, Shafiquzzaman Siddiquee

Abstract:

A novel and simple electrochemical sensor for the determination of melamine was developed based on modified gold electrode (AuE) with chitosan (CHIT) nanocomposite membrane, zinc oxide nanoparticles (ZnONPs) and ionic liquids ([EMIM][Otf]) to enhance the potential current response of melamine. Cyclic voltammetry and differential pulse voltammetry were used to investigate the electrochemical behaviour between melamine and modified AuE in the presence of methylene blue as a redox indicator. The experimental results indicated that the interaction of melamine with CHIT/ZnONPs/([EMIM][Otf])/AuE were based on the strong interaction of hydrogen bonds. The morphological characterization of modified AuE was observed under scanning electron microscope. Under optimal conditions, the current signal was directly proportional to the melamine concentration ranging from 9.6 x 10-5 to 9.6 x 10-11 M, with a correlation coefficient of 0.9656. The detection limit was 9.6 x 10-12 M. Finally, the proposed method was successfully applied and displayed an excellent sensitivity in the determination of melamine in milk samples.

Keywords: melamine, gold electrode, zinc oxide nanoparticles, cyclic voltammetries, differential pulse voltammetries

Procedia PDF Downloads 405

Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

Abstract:

Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

Procedia PDF Downloads 72

Authors: Belkadi Adel, Beboucha Wahib, Cherara lalia

Abstract:

Objective: The aim of this study was to investigate the characteristics of Kumi-kata in elite judokas and characterize the kinematic and temporal parameters of different types of handgrip (HG). Method: fourteen participated in this study male athlete (23.5±2.61 years; 1.81±0.37 0 m; 87.25±22.75 kg), members of the Georgian Judo team. To characterize the dominance and types of kumi-kata used, videos of international competitions from each athlete were analyzed, and to characterize kinematic and temporal parameters and handgrip, and the volunteers pressed a digital dynamometer with each hand for 30 seconds(s) after a visual signal. Results: The values of 0.26±0.69s and 0.31±0.03s for reaction time were obtained, respectively, in the full grip and pinch grip; 19.62±18.83N/cm/s and 6.17±3.48N/cm/s for the rate of force development; 475,21 ± 101,322N and 494,65±112,73 for the FDR; 1,37 ± 0,521s and 1,45 ± 0,824s for the time between the force onset to the TFP; and 41,27±4,54N/cm/s and 45,16 ± 5,64N/cm/s for the fall index, in the dominant hand. There was no significant difference between hands for any variable, except for the dominance of Kumi-kata (p<0.05) used in combat. Conclusion: The dominance of application of the Kumi-kata is a technical option, as it does not depend on the kinetic-temporal parameters of the handgrip.

Keywords: hand grip, judo, athletes, Kumi-Kata

Procedia PDF Downloads 170

Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

Abstract:

Image restoration in the process of communication is one of the emerging fields in the image processing. The motion analysis processing is the simplest case to detect motion in an image. Applications of motion analysis widely spread in many areas such as surveillance, remote sensing, film industry, navigation of autonomous vehicles, etc. The scene may contain multiple moving objects, by using motion analysis techniques the blur caused by the movement of the objects can be enhanced by filling-in occluded regions and reconstruction of transparent objects, and it also removes the motion blurring. This paper presents the design and comparison of various motion detection and enhancement filters. Median filter, Linear image deconvolution, Inverse filter, Pseudoinverse filter, Wiener filter, Lucy Richardson filter and Blind deconvolution filters are used to remove the blur. In this work, we have considered different types and different amount of blur for the analysis. Mean Square Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the performance of the filters. The designed system has been implemented in Matlab software and tested for synthetic and real-time images.

Keywords: image enhancement, motion analysis, motion detection, motion estimation

Procedia PDF Downloads 273

Authors: Yassa Nacera, Badji Abderrezak, Saidoune Abdelmalek, Houassine Hamza

Abstract:

Several kinds of faults can occur in a permanent magnet synchronous machine (PMSM) systems: bearing faults, electrically short/open faults, eccentricity faults, and demagnetization faults. Demagnetization fault means that the strengths of permanent magnets (PM) in PMSM decrease, and it causes low output torque, which is undesirable for EVs. The fault is caused by physical damage, high-temperature stress, inverse magnetic field, and aging. Motor current signature analysis (MCSA) is a conventional motor fault detection method based on the extraction of signal features from stator current. a simulation model of the PMSM under partial demagnetization and uniform demagnetization fault was established, and different degrees of demagnetization fault were simulated. The harmonic analyses using the Fast Fourier Transform (FFT) show that the fault diagnosis method based on the harmonic wave analysis is only suitable for partial demagnetization fault of the PMSM and does not apply to uniform demagnetization fault of the PMSM.

Keywords: permanent magnet, diagnosis, demagnetization, modelling

Procedia PDF Downloads 48

Authors: Leah Wright, Trevor Townsend

Abstract:

Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.

Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty

Procedia PDF Downloads 367

Authors: Tatiana R. Simonyan, Elena A. Protasova, Anastasia V. Mamontova, Eugene G. Maksimov, Konstantin A. Lukyanov, Alexey M. Bogdanov

Abstract:

Here, we describe two variants of the calcium indicators based on the GCaMP sensitive core and BrUSLEE fluorescent protein (GCaMP-BrUSLEE and GCaMP-BrUSLEE-145). In contrast to the conventional GCaMP6-family indicators, these fluorophores are characterized by the well-marked responsiveness of their fluorescence decay kinetics to external calcium concentration both in vitro and in cellulo. Specifically, we show that the purified GCaMP-BrUSLEE and GCaMP-BrUSLEE-145 exhibit three-component fluorescence decay kinetics, with the amplitude-normalized lifetime component (t3*A3) of GCaMP-BrUSLEE-145 changing four-fold (500-2000 a.u.) in response to a Ca²⁺ concentration shift in the range of 0—350 nM. Time-resolved fluorescence microscopy of live cells displays the two-fold change of the GCaMP-BrUSLEE-145 mean lifetime upon histamine-stimulated calcium release. The aforementioned Ca²⁺-dependence calls considering the GCaMP-BrUSLEE-145 as a prospective Ca²⁺-indicator with the signal read-out in the time domain.

Keywords: calcium imaging, fluorescence lifetime imaging microscopy, fluorescent proteins, genetically encoded indicators

Procedia PDF Downloads 139

Authors: Fuchun Li, Hong Xiao

Abstract:

We propose a new early warning model for predicting financial stress events for a given future time. In this model, we examine whether credit conditions play an important role as a nonlinear propagator of shocks when predicting the likelihood of occurrence of financial stress events for a given future time. This propagation takes the form of a threshold regression in which a regime change occurs if credit conditions cross a critical threshold. Given the new early warning model for financial stress events, we evaluate the performance of this model and currently available alternatives, such as the model from signal extraction approach, and linear regression model. In-sample forecasting results indicate that the three types of models are useful tools for predicting financial stress events while none of them outperforms others across all criteria considered. The out-of-sample forecasting results suggest that the credit-regime switching model performs better than the two others across all criteria and all forecasting horizons considered.

Keywords: cut-off probability, early warning model, financial crisis, financial stress, regime-switching model, forecasting horizons

Procedia PDF Downloads 422

Authors: Li Yuchen, Wu Qingxin, Jin Yuxing, Yang Qian

Abstract:

Interleukin-11 (IL-11), a well-known anti-inflammatory factor, helps to protect against intestinal epithelium damage caused by physical or chemical factors. However, little is known about the role of IL-11 during viral infection. Herein, high mRNA and protein levels of IL-11 were found in epithelial cells and jejunum of piglets during porcine epidemic diarrhea virus (PEDV) infection, and IL-11 expression was positively correlated with the level of viral infection. Pretreatment with recombinant porcine IL-11 (pIL-11) suppressed PEDV replication in Vero E6 cells, while IL-11 knockdown promoted viral infection. Furthermore, pIL-11 inhibited viral infection by preventing PEDV-mediated apoptosis of cells through activating the IL-11/STAT3 signal pathway. Conversely, application of a STAT3 phosphorylation inhibitor significantly antagonized the anti-apoptosis function of pIL-11 and counteracted its inhibition of PEDV. Our data suggested that that IL-11 is a novel PEDV-inducible cytokine, and its production enhances the anti-apoptosis ability of epithelial cells against PEDV infection. The potential uses of IL-11 as a novel therapeutic against devastating viral diarrhea in piglets deserves more attention and study.

Keywords: Interleukin-11, Porcine epidemic diarrhea virus, STAT3, anti-apoptosis

Procedia PDF Downloads 120

Authors: Elnaz Lashgari, Emel Demircan

Abstract:

Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: electromyography, manifold learning, ISOMAP, Laplacian Eigenmaps, locally linear embedding

Procedia PDF Downloads 348

Authors: Vishant Gahlaut, A Mercy Latha, Sanjay Kumar Ghosh

Abstract:

Multi-stage depressed collectors (MDC) are used as an efficiency enhancement technique in traveling wave tubes the high-energy electron beam, after its interaction with the RF signal, gets velocity sorted and collected at various depressed electrodes of the MDC. The ultimate goal is to identify an optimum thermal management scheme (cooling mechanism) that could extract the heat efficiently from the electrodes. Careful thermal analysis, incorporating the cooling mechanism is required to ensure that the maximum temperature does not exceed the safe limits. A simple analytical model for quick prediction of the thermal has been developed. The model has been developed for the worst-case un-modulated DC condition, where all the thermal power is dissipated in the last electrode (typically, fourth electrode in the case of the four-stage depressed collector). It considers the thermal contact resistances at various braze joints accounting for the practical non-uniformities. Analytical results obtained from the model have been validated with simulated and experimental results.

Keywords: multi-stage depressed collector, TWTs, thermal contact resistance, thermal management

Procedia PDF Downloads 209

Authors: Farhad Asadi, Mohammad Javad Mollakazemi

Abstract:

In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

Procedia PDF Downloads 412

Authors: Mrinmoy Majumder, Apu Kumar Saha

Abstract:

The ever-increasing human population and its demand for energy is placing stress upon conventional energy sources; and as demand for power continues to outstrip supply, the need to optimize energy distribution and utilization is emerging as an important focus for various stakeholders. The distribution of available energy must be achieved in such a way that the needs of the consumer are satisfied. However, if the availability of resources is not sufficient to satisfy consumer demand, it is necessary to find a method to select consumers based on factors such as their socio-economic or environmental impacts. Weighting consumer types in this way can help separate them based on their relative importance, and cognitive optimization of the allocation process can then be carried out so that, even on days of particularly scarce supply, the socio-economic impacts of not satisfying the needs of consumers can be minimized. In this context, the present study utilized fuzzy logic to assign weightage to different types of consumers based at an educational campus in India, and then established optimal allocation by applying the non-linear mapping capability of neuro-genetic algorithms. The outputs of the algorithms were compared with similar outputs from particle swarm optimization and differential evolution algorithms. The results of the study demonstrate an option for the optimal utilization of available energy based on the socio-economic importance of consumers.

Keywords: power allocation, optimization problem, neural networks, environmental and ecological engineering

Procedia PDF Downloads 461

Authors: Toni Maristela C. Estabillo, Michaela V. Matienzo, Mikaela L. Sabangan, Rosette M. Tienzo, Justine L. Bahinting

Abstract:

This study is about blind watermarking on images with different categories and properties using two algorithms namely, Discrete Wavelet Transform and Patchwork Algorithm. A program is created to perform watermark embedding, extraction and evaluation. The evaluation is based on three watermarking criteria namely: image quality degradation, perceptual transparency and security. Image quality is measured by comparing the original properties with the processed one. Perceptual transparency is measured by a visual inspection on a survey. Security is measured by implementing geometrical and non-geometrical attacks through a pass or fail testing. Values used to measure the following criteria are mostly based on Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The results are based on statistical methods used to interpret and collect data such as averaging, z Test and survey. The study concluded that the combined DWT and Patchwork algorithms were less efficient and less capable of watermarking than DWT algorithm only.

Keywords: blind watermarking, discrete wavelet transform algorithm, patchwork algorithm, digital watermark

Procedia PDF Downloads 254