Search results for: control area network (CAN)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21898

Search results for: control area network (CAN)

17518 Causes, Consequences, and Alternative Strategies of Illegal Migration in Ethiopia: The Case of Tigray Region

Authors: Muuz Abraha Meshesha

Abstract:

Illegal Migration, specifically Trafficking in person is one of the primary issues of the day affecting all states of the world with variation on the extent of the root causes and consequences that led people to migrate irregularly and the consequences it is costing on humanity. This paper intends to investigate the root causes and consequences of illegal migration in Ethiopia’s Tigray Regional state and come up with alternative intervening strategy. To come up with pertinent and robust research finding, this study employed mixed research approach involving qualitative and quantitative data in line with purposive and snow ball sampling selection technique. The study revealed that, though poverty is the most commonly sensed pushing factor for people to illegally migrate, the issue of psycho-social orientation and attitudinal immersion of the local community for illegal migration, both in thinking and action is the most pressing problem that urges serious intervention. Trafficking in persons and Illegal migration in general, is becoming the norm of the day in the study area that overtly reveal illegal migration is an issue beyond livelihood securing demand in practice. Basically, parties engaged in illegal migration and the accomplice with human traffickers these days in the study area are found to be more than urgency for food security and a need to escape from livelihood impoverishment. Therefore, this study come up with a new paradigm insight indicating that illegal migration is believed by the local community members as an optional path way of doing business in illegal way while the attitude of the community and officials authorized to regulate is being part of the channel or to the least tolerant of this grave global danger. The study also found that the effect of illegal migration is significantly manifested in long run than in short term periods. Therefore, a need for critical consideration on attitudinal based intervention and youth oriented and enforceable legal and policy framework accountability framework is required to face and control illegal migration by international, national, local stakeholders. Besides this, economy based development interventions that could engage and reorient the youth, as primary victims of trafficking, and expansion of large scale projects that can employ large number of youths at a time.

Keywords: human traficking, illegal migration, migration, tigray region

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17517 Extended Kalman Filter Based Direct Torque Control of Permanent Magnet Synchronous Motor

Authors: Liang Qin, Hanan M. D. Habbi

Abstract:

A robust sensorless speed for permanent magnet synchronous motor (PMSM) has been presented for estimation of stator flux components and rotor speed based on The Extended Kalman Filter (EKF). The model of PMSM and its EKF models are modeled in Matlab /Sirnulink environment. The proposed EKF speed estimation method is also proved insensitive to the PMSM parameter variations. Simulation results demonstrate a good performance and robustness.

Keywords: DTC, Extended Kalman Filter (EKF), PMSM, sensorless control, anti-windup PI

Procedia PDF Downloads 654
17516 The Effectiveness of an Educational Program on Awareness of Cancer Signs, Symptoms, and Risk Factors among School Students in Oman

Authors: Khadija Al-Hosni, Moon Fai Chan, Mohammed Al-Azri

Abstract:

Background: Several studies suggest that most school-age adolescents are poorly informed on cancer warning signs and risk factors. Providing adolescents with sufficient knowledge would increase their awareness in adulthood and improve seeking behaviors later. Significant: The results will provide a clear vision in assisting key decision-makers in formulating policies on the students' awareness programs towards cancer. So, the likelihood of avoiding cancer in the future will be increased or even promote early diagnosis. Objectives: to evaluate the effectiveness of an education program designed to increase awareness of cancer signs and symptoms risk factors, improve the behavior of seeking help among school students in Oman, and address the barriers to obtaining medical help. Methods: A randomized controlled trial with two groups was conducted in Oman. A total of 1716 students (n=886/control, n= 830/education), aged 15-17 years, at 10th and 11th grade from 12 governmental schools 3 in governorates from 20-February-2022 to 12-May-2022. Basic demographic data were collected, and the Cancer Awareness Measure (CAM) was used as the primary outcome. Data were collected at baseline (T0) and 4 weeks after (T1). The intervention group received an education program about cancer's cause and its signs and symptoms. In contrast, the control group did not receive any education related to this issue during the study period. Non-parametric tests were used to compare the outcomes between groups. Results: At T0, the lamp was the most recognized cancer warning sign in control (55.0%) and intervention (55.2%) groups. However, there were no significant changes at T1 for all signs in the control group. In contrast, all sign outcomes were improved significantly (p<0.001) in the intervention group, the highest response was unexplained pain (93.3%). Smoking was the most recognized risk factor in both groups: (82.8% for control; 84.1% for intervention) at T0. However, there was no significant change in T1 for the control group, but there was for the intervention group (p<0.001), the highest identification was smoking cigarettes (96.5%). Too scared was the largest barrier to seeking medical help by students in the control group at T0 (63.0%) and T1 (62.8%). However, there were no significant changes in all barriers in this group. Otherwise, being too embarrassed (60.2%) was the largest barrier to seeking medical help for students in the intervention group at T0 and too scared (58.6%) at T1. Although there were reductions in all barriers, significant differences were found in six of ten only (p<0.001). Conclusion: The intervention was effective in improving students' awareness of cancer symptoms, warning signs (p<0.001), and risk factors (p<0.001 reduced the most addressed barriers to seeking medical help (p<0.001) in comparison to the control group. The Ministry of Education in Oman could integrate awareness of cancer within the curriculum, and more interventions are needed on the sociological part to overcome the barriers that interfere with seeking medical help.

Keywords: adolescents, awareness, cancer, education, intervention, student

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17515 Acquisition of Murcian Lexicon and Morphology by L2 Spanish Immigrants: The Role of Social Networks

Authors: Andrea Hernandez Hurtado

Abstract:

Research on social networks (SNs) -- the interactions individuals share with others has shed important light in helping to explain differential use of variable linguistic forms, both in L1s and L2s. Nevertheless, the acquisition of nonstandard L2 Spanish in the Region of Murcia, Spain, and how learners interact with other speakers while sojourning there have received little attention. Murcian Spanish (MuSp) was widely influenced by Panocho, a divergent evolution of Hispanic Latin, and differs from the more standard Peninsular Spanish (StSp) in phonology, morphology, and lexicon. For instance, speakers from this area will most likely palatalize diminutive endings, producing animalico [̩a.ni.ma.ˈli.ko] instead of animalito [̩a.ni.ma.ˈli.to] ‘little animal’. Because L1 speakers of the area produce and prefer salient regional lexicon and morphology (particularly the palatalized diminutive -ico) in their speech, the current research focuses on how international residents in the Region of Murcia use Spanish: (1) whether or not they acquire (perceptively and/or productively) any of the salient regional features of MuSp, and (2) how their SNs explain such acquisition. This study triangulates across three tasks -recognition, production, and preference- addressing both lexicon and morphology, with each task specifically created for the investigation of MuSp features. Among other variables, the effects of L1, residence, and identity are considered. As an ongoing dissertation research, data are currently being gathered through an online questionnaire. So far, 7 participants from multiple nationalities have completed the survey, although a minimum of 25 are expected to be included in the coming months. Preliminary results revealed that MuSp lexicon and morphology were successfully recognized by participants (p<.001). In terms of regional lexicon production (10.0%) and preference (47.5%), although participants showed higher percentages of StSp, results showed that international residents become aware of stigmatized lexicon and may incorporate it into their language use. Similarly, palatalized diminutives (production 14.2%, preference 19.0%) were present in their responses. The Social Network Analysis provided information about participants’ relationships with their interactants, as well as among them. Results indicated that, generally, when residents were more immersed in the culture (i.e., had more Murcian alters) they produced and preferred more regional features. This project contributes to the knowledge of language variation acquisition in L2 speakers, focusing on a stigmatized Spanish dialect and exploring how stigmatized varieties may affect L2 development. Results will show how L2 Spanish speakers’ language is affected by their stay in Murcia. This, in turn, will shed light on the role of SNs in language acquisition, the acquisition of understudied and marginalized varieties, and the role of immersion on language acquisition. As the first systematic account on the acquisition of L2 Spanish lexicon and morphology in the Region of Murcia, it lays important groundwork for further research on the connection between SNs and the acquisition of regional variants, applicable to Murcia and beyond.

Keywords: international residents, L2 Spanish, lexicon, morphology, nonstandard language acquisition, social networks

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17514 Tower Crane Selection and Positioning on Construction Sites

Authors: Dirk Briskorn, Michael Dienstknecht

Abstract:

Cranes are a key element in construction projects as they are the primary lifting equipment and among the most expensive construction equipment. Thus, selecting cranes and locating them on-site is an important factor for a project's profitability. We focus on a site with supply and demand areas that have to be connected by tower cranes. There are several types of tower cranes differing in certain specifications such as costs or operating radius. The objective is to select cranes and determine their locations such that each demand area is connected to its supply area at minimum cost. We detail the problem setting and show how to obtain a discrete set of candidate locations for each crane type without losing optimality. This discretization allows us to reduce our problem to the classic set cover problem. Despite its NP-hardness, we achieve good results employing a standard solver and a greedy heuristic, respectively.

Keywords: positioning, selection, standard solver, tower cranes

Procedia PDF Downloads 365
17513 Porosity and Surface Chemistry of Functionalized Carbonaceous Materials from Date Palm Leaflets

Authors: El-Said I. El-Shafey, Syeda Naheed F. Ali, Saleh S. Al-Busafi, Haider A. J. Al-Lawati

Abstract:

Date palm leaflets were utilized as a precursor for activated carbon (AC) preparation using KOH activation. AC produced was oxidized using nitric acid producing oxidized activated carbon (OAC). OAC that possesses acidic surface was surface functionalized to produce basic activated carbons using linear diamine compounds (ethylene diamine and propylene diamine). OAC was also functionalized to produce hydrophobic activated carbons using ethylamine (EA) and aniline (AN). Dehydrated carbon was also prepared from date palm leaflets using sulfuric acid dehydration/ oxidation and was surface functionalized in the same way as AC. Nitric acid oxidation was not necessary for DC as it is acidic carbon. The surface area of AC is high (823 m2/g) with microporosity domination, however, after oxidation and surface functionalization, both the surface area and surface microporosity decrease tremendously. DC surface area was low (15 m2/g) with mesoporosity domination. Surface functionalization has decreased the surface area of activated carbons. FTIR spectra show that -COOH group on DC and OAC almost disappeared after surface functionalization. The surface chemistry of all carbons produced was tested for pHzpc, basic sites, boehm titration, thermogravimetric analysis and zeta potential measurement. Scanning electron microscopy and energy dispersive spectroscopy in addition to CHN elemental analysis were also carried out. DC and OAC possess low pHzpc and high surface functionality, however, basic and hydrophobic carbons possess high pHzpc and low surface functionality. The different behavior of carbons is related to their different surface chemistry. Methylene blue adsorption was found to be faster on hydrophobic carbons based on AC and DC. The Larger adsorption capacity of methylene blue was found for hydrophobic carbons. Dominating adsorption forces of methylene blue varies from carbon to another depending on its surface nature. Sorption forces include hydrophobic forces, H-bonding, electrostatic interactions and van der Waals forces.

Keywords: carbon, acidic, basic, hydrophobic

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17512 Reading and Writing Memories in Artificial and Human Reasoning

Authors: Ian O'Loughlin

Abstract:

Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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17511 Using Hidden Markov Chain for Improving the Dependability of Safety-Critical Wireless Sensor Networks

Authors: Issam Alnader, Aboubaker Lasebae, Rand Raheem

Abstract:

Wireless sensor networks (WSNs) are distributed network systems used in a wide range of applications, including safety-critical systems. The latter provide critical services, often concerned with human life or assets. Therefore, ensuring the dependability requirements of Safety critical systems is of paramount importance. The purpose of this paper is to utilize the Hidden Markov Model (HMM) to elongate the service availability of WSNs by increasing the time it takes a node to become obsolete via optimal load balancing. We propose an HMM algorithm that, given a WSN, analyses and predicts undesirable situations, notably, nodes dying unexpectedly or prematurely. We apply this technique to improve on C. Lius’ algorithm, a scheduling-based algorithm which has served to improve the lifetime of WSNs. Our experiments show that our HMM technique improves the lifetime of the network, achieved by detecting nodes that die early and rebalancing their load. Our technique can also be used for diagnosis and provide maintenance warnings to WSN system administrators. Finally, our technique can be used to improve algorithms other than C. Liu’s.

Keywords: wireless sensor networks, IoT, dependability of safety WSNs, energy conservation, sleep awake schedule

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17510 Polyphytopharmaca Improving Asthma Control Test Value, Biomarker (Eosinophils and Malondialdehyde): Quasi Experimental Test in Patients with Asthma

Authors: Andri Andri, Susanthy Djajalaksana, Iin Noor Chozin

Abstract:

Background: Despite advances in asthma therapies, a proportion of patients with asthma continue to have difficulty in gaining adequate asthma control. Complex immunological mechanisms and oxidative stress affect this condition, including the role of malondialdehyde (MDA) as a marker of inflammation. This research aimed to determine the effect of polyphytopharmaca administration on the value of asthma control test (ACT), blood eosinophils level and markers of MDA serum inflammation in patients with asthma. Method: Quasi experimental approach was conducted toward 15 stable asthma patients who were not fully controlled in outpatient pulmonary clinic, Public Hospital of Dr. Saiful Anwar Malang. Assessments of ACT values, eosinophil levels, and serum MDA levels were carried out before and after administration of polyphytopharmaca which contained a combination of 100 mg Nigella sativa extract, Kleinhovia hospita 100 mg, Curcuma xanthorrhiza 75 mg, and Ophiocephalus striatus 100 mg, three times daily with two capsules for 12 weeks. The ACT value was determined by the researcher by asking the patient directly, blood eosinophil levels were calculated by analyzing blood type counts, and serum MDA levels were detected by the qPCR method. Result: There was a significant enhancement of ACT value (18.07 ± 2.57 to 22.06 ± 1.83, p = 0.001) (from 60% uncontrolled ACT to 93.3% controlled ACT), a significant decrease in blood eosinophils levels (653.15 ± 276.15 pg/mL to 460.66 ± 202.04 pg/mL, p = 0.038), and decreased serum MDA levels (109.64 ± 53.77 ng / ml to 78.68 ± 64.92 ng/ml, p = 0.156). Conclusion: Administration of polyphytopharmaca can increase ACT value, decrease blood eosinophils levels and reduce MDA serum in stable asthma patients who are not fully controlled.

Keywords: asthma control test, eosinophils levels, malondialdehyde, polyphytopharmaca

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17509 Two Lessons Learnt in Defining Intersections and Interfaces in Numerical Modeling with Plaxis

Authors: Mahdi Sadeghian, Somaye Sadeghian, Reza Dinarvand

Abstract:

This paper is going to discuss two issues encountered in using PLAXIS. Both issues were monitored during application of PLAXIS to estimate the excavation-induced displacement. Column Soil Mixing (CSM) was applied to stabilise the excavation. It was understood that the estimated excavation induced deformation at the top of the CSM blocks highly depends on the material type defining pavement material adjacent to the CSM blocks. Cohesive material for pavement will result in the unrealistic connection between pavement and CSM even by defining an interface element. To find the most realistic approach, the interface defined in three different manners (1) no interface elements were applied (2) a non-cohesive soil layer was defined between pavement and CSM block to represent the friction between these materials (3) built-in interface elements in PLAXIS was used to define the boundary between the pavement and the CSM block. The result showed that the option 2 would result in more realistic results. The second issue was in the modelling of the contact line between the CSM block and an inclined layer underneath. The analysis result showed that the excavation-induced deformation highly depends on how the PLAXIS user defines the contact area. It was understood that if the contact area had defined as a point in which CSM block had intersected the layer underneath the estimated lateral displacement of CSM block would be unrealistically lower than the model in which the contact area was defined as a line.

Keywords: PLAXIS, FEM, CSM, Excavation-Induced Deformation

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17508 An Evaluation of Impact of Video Billboard on the Marketing of GSM Services in Lagos Metropolis

Authors: Shola Haruna Adeosun, F. Adebiyi Ajoke, Odedeji Adeoye

Abstract:

Video billboard advertising by networks and brand switching was conceived out of inquisition at the huge billboard advertising expenditures made by the three major GSM network operators in Nigeria. The study was anchored on Lagos State Metropolis with a current census population over 1,000,000. From this population, a purposive sample of 400 was adopted, and the questionnaire designed for the survey was carefully allocated to members of this ample in the five geographical zones of the city so that each rung of the society was well represented. The data obtained were analyzed using tables and simple percentages. The results obtained showed that subscribers of these networks were hardly influenced by the video billboard advertisements. They overwhelmingly showed that rather than the slogans of the GSM networks carried on the video billboards, it was the incentives to subscribers as well as the promotional strategies of these organizations that moved them to switch from one network to another. These switching lasted only as long as the incentives and promotions were in effect. The results of the study also seemed to rekindle the age-old debate on media effects, by the unyielding schools of the theory of ‘all-powerful media’, ‘the limited effects media’, ‘the controlled effects media’ and ‘the negotiated media influence’.

Keywords: evaluation, impact, video billboard, marketing, services

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17507 Analyzing and Predicting the CL-20 Detonation Reaction Mechanism Based on Artificial Intelligence Algorithm

Authors: Kaining Zhang, Lang Chen, Danyang Liu, Jianying Lu, Kun Yang, Junying Wu

Abstract:

In order to solve the problem of a large amount of simulation and limited simulation scale in the first-principle molecular dynamics simulation of energetic material detonation reaction, we established an artificial intelligence model for analyzing and predicting the detonation reaction mechanism of CL-20 based on the first-principle molecular dynamics simulation of the multiscale shock technique (MSST). We employed principal component analysis to identify the dominant charge features governing molecular reactions. We adopted the K-means clustering algorithm to cluster the reaction paths and screen out the key reactions. We introduced the neural network algorithm to construct the mapping relationship between the charge characteristics of the molecular structure and the key reaction characteristics so as to establish a calculation method for predicting detonation reactions based on the charge characteristics of CL-20 and realize the rapid analysis of the reaction mechanism of energetic materials.

Keywords: energetic material detonation reaction, first-principle molecular dynamics simulation of multiscale shock technique, neural network, CL-20

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17506 Effect of Dietary Supplementation of Ashwagandha (Withania somnifera) on Performance of Commercial Layer Hens

Authors: P. Arun Subhash, B. N. Suresh, M. C. Shivakumar, N. Suma

Abstract:

An experiment was conducted to study the effect of dietary supplementation of ashwagandha (Withania somnifera) root powder on the egg production performance and egg quality in commercial layer birds. A practical type layer diet was prepared as per Bureau of Indian Standards (1992) to serve as the control, and the test diet was prepared by supplementing control diet with ashwagandha powder at 1kg/ton of feed. Each diet was assigned to twenty replicate groups of 5 laying hens each for duration of 84 days. The result revealed that cumulative egg production (%) was comparable between control and test group. The feed consumption and its conversion efficiency were similar among both the groups. The egg weight and egg characteristics viz., yolk index, yolk color, haugh unit score, albumen index, egg shape index and eggshell thickness were also remained similar between both the groups. It was concluded that supplementation of ashwagandha powder at 1kg/ton in layer diets has no beneficial effect on egg production and egg quality parameters.

Keywords: ashwagandha, egg production, egg quality, layers

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17505 Identification of the Parameters of a AC Servomotor Using Genetic Algorithm

Authors: J. G. Batista, K. N. Sousa, ¬J. L. Nunes, R. L. S. Sousa, G. A. P. Thé

Abstract:

This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measured and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

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17504 Hand Gesture Recognition Interface Based on IR Camera

Authors: Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park, Kwang-Mo Jung

Abstract:

Vision based user interfaces to control TVs and PCs have the advantage of being able to perform natural control without being limited to a specific device. Accordingly, various studies on hand gesture recognition using RGB cameras or depth cameras have been conducted. However, such cameras have the disadvantage of lacking in accuracy or the construction cost being large. The proposed method uses a low cost IR camera to accurately differentiate between the hand and the background. Also, complicated learning and template matching methodologies are not used, and the correlation between the fingertips extracted through curvatures is utilized to recognize Click and Move gestures.

Keywords: recognition, hand gestures, infrared camera, RGB cameras

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17503 F-VarNet: Fast Variational Network for MRI Reconstruction

Authors: Omer Cahana, Maya Herman, Ofer Levi

Abstract:

Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach, such as compress sensing (CS) or parallel imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy.

Keywords: MRI, deep learning, variational network, computer vision, compress sensing

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17502 Microfluidic Construction of Responsive Photonic Microcapsules for Microsensors

Authors: Lingling Shui, Shuting Xie

Abstract:

As alternatives to electronic devices, optically active structures from responsive nanomaterials offer great opportunity buildup smart functional sensors. Hereby, we report on droplet microfluidics enabled construction and application of photonic microcapsules (PMCs) for colorimetric temperature microsensors, enabling miniaturization for injectable local micro-area sensing and integration for large-area sensing. Monodispersed PMCs are produced by in-situ photopolymerization of hydrogel shells of cholesteric liquid crystal (CLC)-in-water-in-oil double emulsion droplets prepared using microfluidic devices, with controllable physical structures and chemical compositions. Constructed PMCs exhibit thermal responsive structural color according to the selective Bragg reflection of CLC’s periodical helical structures within the microdroplet’s spherical confinement. Constructed PMCs with tunable size and composition have been successfully applied for monitoring the living cell extracellular temperature via co-incubation with cell suspension, and for detecting human body temperature via a flexible device from assembled PMCs. These PMCs could be flexibly applied in either micro-environment or large-area surface, enabling wide applications for precision temperature monitoring biological activities (e.g. cells or organs), optoelectronic devices working conditions (e.g. temperature indicators under extreme conditions), and etc.

Keywords: droplet, microfluidics, assembly, soft materials, microsensor

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17501 Optimized Renewable Energy Mix for Energy Saving in Waste Water Treatment Plants

Authors: J. D. García Espinel, Paula Pérez Sánchez, Carlos Egea Ruiz, Carlos Lardín Mifsut, Andrés López-Aranguren Oliver

Abstract:

This paper shortly describes three main actuations over a Waste Water Treatment Plant (WWTP) for reducing its energy consumption: Optimization of the biological reactor in the aeration stage by including new control algorithms and introducing new efficient equipment, the installation of an innovative hybrid system with zero Grid injection (formed by 100kW of PV energy and 5 kW of mini-wind energy generation) and an intelligent management system for load consumption and energy generation control in the most optimum way. This project called RENEWAT, involved in the European Commission call LIFE 2013, has the main objective of reducing the energy consumptions through different actions on the processes which take place in a WWTP and introducing renewable energies on these treatment plants, with the purpose of promoting the usage of treated waste water for irrigation and decreasing the C02 gas emissions. WWTP is always required before waste water can be reused for irrigation or discharged in water bodies. However, the energetic demand of the treatment process is high enough for making the price of treated water to exceed the one for drinkable water. This makes any policy very difficult to encourage the re-use of treated water, with a great impact on the water cycle, particularly in those areas suffering hydric stress or deficiency. The cost of treating waste water involves another climate-change related burden: the energy necessary for the process is obtained mainly from the electric network, which is, in most of the cases in Europe, energy obtained from the burning of fossil fuels. The innovative part of this project is based on the implementation, adaptation and integration of solutions for this problem, together with a new concept of the integration of energy input and operative energy demand. Moreover, there is an important qualitative jump between the technologies used and the alleged technologies to use in the project which give it an innovative character, due to the fact that there are no similar previous experiences of a WWTP including an intelligent discrimination of energy sources, integrating renewable ones (PV and Wind) and the grid.

Keywords: aeration system, biological reactor, CO2 emissions, energy efficiency, hybrid systems, LIFE 2013 call, process optimization, renewable energy sources, wasted water treatment plants

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17500 The Estimation of Bird Diversity Loss and Gain as an Impact of Oil Palm Plantation: Study Case in KJNP Estate Riau Province

Authors: Yanto Santosa, Catharina Yudea

Abstract:

The rapid growth of oil palm industry in Indonesia raised many negative accusations from various parties, who said that oil palm plantation is damaging the environment and biodiversity, including birds. Since research on oil palm plantation impacts on bird diversity is still limited, this study needs to be developed in order to gain further learning and understanding. Data on bird diversity were collected in March 2018 in KJNP Estate, Riau Province using strip transect method on five different land cover types (young, intermediate, and old growth of oil palm plantation, high conservation value area, and crops field or the baseline). The observations were conducted simultaneously, with three repetitions. The result shows that the baseline has 19 species of birds and land cover after the oil palm plantation has 39 species. HCV (high conservation value) area has the highest increase in diversity value. Oil palm plantation has changed the composition of bird species. The highest similarity index is shown by young growth oil palm land cover with total score 0.65, meanwhile the lowest similarity index with total score 0.43 is shown by HCV area. Overall, the existence of oil palm plantation made a positive impact by increasing bird species diversity, with total 23 species gained and 3 species lost.

Keywords: bird diversity, crops field, impact of oil palm plantation, KJNP estate

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17499 Revealing the Potential of Geotourism and Geoheritage of Gedangsari Area, Yogyakarta

Authors: Cecilia Jatu, Adventino

Abstract:

Gedangsari is located in Gunungkidul, Yogyakarta Province, which has several criteria to be used as a new geosite object. The research area is located in the southern mountain zone of Java, composed of 5 rock formations with Oligocene up to Middle Miocene age. The purpose of this study is to reveal the potential of geotourism and the geoheritage to be proposed as a new geosite and to make a geosite map of Gedangsari. The research method used is descriptive data collection and which includes quantitative geological data collection, geotourism, and heritage sites, then supported by petrographic analysis, geological structure, geological mapping, and SWOT analysis. The geological data proved that Gedangsari consists of igneous rock (intrusion), pyroclastic rock, and sediment rock. This condition caused many varieties and particular geomorphological platform. Geotourism that include in Gedangsari are Luweng Sampang Canyon, Gedangsari Bouma Sequence, Watugajah Columnar Joint, Gedangsari Marine Fan Sediment, and Tegalrejo Waterfall. There is also Tegalrejo Village, which can be considered as geoheritage site because of its culture and batik traditional cloth. The results of the SWOT analysis, Gedangsari geosite must be developed and appropriately promoted in order to improve the existence. The development of geosite area will have a significant impact that improve the economic growth of the surrounding community and can be used by the government as base information for sustainable development. In addition, the making of an educational map about the geological conditions and geotourism location of the Gedangsari geosite can increase the people's knowledge about Gedangsari.

Keywords: Gedangsari, geoheritage, geotourism, geosite

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17498 Comparison of Authentication Methods in Internet of Things Technology

Authors: Hafizah Che Hasan, Fateen Nazwa Yusof, Maslina Daud

Abstract:

Internet of Things (IoT) is a powerful industry system, which end-devices are interconnected and automated, allowing the devices to analyze data and execute actions based on the analysis. The IoT technology leverages the technology of Radio-Frequency Identification (RFID) and Wireless Sensor Network (WSN), including mobile and sensor. These technologies contribute to the evolution of IoT. However, due to more devices are connected each other in the Internet, and data from various sources exchanged between things, confidentiality of the data becomes a major concern. This paper focuses on one of the major challenges in IoT; authentication, in order to preserve data integrity and confidentiality are in place. A few solutions are reviewed based on papers from the last few years. One of the proposed solutions is securing the communication between IoT devices and cloud servers with Elliptic Curve Cryptograhpy (ECC) based mutual authentication protocol. This solution focuses on Hyper Text Transfer Protocol (HTTP) cookies as security parameter.  Next proposed solution is using keyed-hash scheme protocol to enable IoT devices to authenticate each other without the presence of a central control server. Another proposed solution uses Physical Unclonable Function (PUF) based mutual authentication protocol. It emphasizes on tamper resistant and resource-efficient technology, which equals a 3-way handshake security protocol.

Keywords: Internet of Things (IoT), authentication, PUF ECC, keyed-hash scheme protocol

Procedia PDF Downloads 250
17497 Impact of Using Peer Instruction and PhET Simulations on the Motivation and Physics Anxiety

Authors: Jaypee Limueco

Abstract:

This research focused on the impact of Peer Instruction and PhET Simulations on the level of motivation and Physics anxiety of Grade 9 students. Two groups of students were used in the study. The experimental group involved 65 registered students while the control group has 64 registered students. To determine the level of motivation of students in learning physics, the Physics Motivation Questionnaire was administered. On the other hand, to determine the level of Physics anxiety of the students in each group, Physics Anxiety Rating Scale was used. Peer Instruction supplemented with PhET simulations was implemented in the experimental group while the traditional lecture method was used in the control group. Both instruments were again administered after the implementation of the two different teaching approaches. “Wilcoxon Signed Rank test” was used to test the significant difference between pretest and posttest of each group. “Mann Whitney U” was used to test if significant differences exist between each group before and after instruction. Results showed that there is no significant difference between the level of motivation and anxiety of the experimental and control group before the implementation at p<0.05 significance level. It implies that the students have the same level of motivation and physics anxiety before instruction. However, the results of both tests have significant differences between the groups after instruction. It is also found that there is a significant positive change in the responses of the students in the experimental group while no change was evident on the control. The result of the analysis of the Mann Whitney U shows that the change in the attributes of the students is caused by the treatment. Therefore, it is concluded that Peer Instruction and PhET simulation helped in alleviating motivation of students and minimizing their anxiety towards Physics.

Keywords: anxiety, motivation, peer instruction, PhET simulations

Procedia PDF Downloads 345
17496 Downscaling Seasonal Sea Surface Temperature Forecasts over the Mediterranean Sea Using Deep Learning

Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

Abstract:

This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

Procedia PDF Downloads 65
17495 Chemopreventive Efficacy Of Cdcl2(C14H21N3O2) in Rat Colon Carcinogenesis Model Using Aberrant Crypt Foci (ACF) as Endpoint Marker

Authors: Maryam Hajrezaie, Mahmood Ameen Abdulla, Nazia AbdulMajid, Maryam Zahedifard

Abstract:

Colon cancer is one of the most prevalent cancers in the world. Cancer chemoprevention is defined as the use of natural or synthetic compounds capable of inducing biological mechanisms necessary to preserve genomic fidelity. New schiff based compounds are reported to exhibit a wide spectrum of biological activities of therapeutic importance. To evaluate inhibitory properties of CdCl2(C14H21N3O2) complex on colonic aberrant crypt foci, five groups of 7-week-old male rats were used. Control group was fed with 10% Tween 20 once a day, cancer control group was intra-peritoneally injected with 15 mg/kg Azoxymethan, drug control group was injected with 15 mg/kg azoxymethan and 5-Flourouracil, experimental groups were fed with 2.5 and 5 mg/kg CdCl2(C14H21N3O2) compound each once a day. Administration of compound were found to be effectively chemoprotective. Andrographolide suppressed total colonic ACF formation up to 72% to 74%, respectively, when compared with control group. The results also showed a significant increase in glutathione peroxidase, superoxide dismutase, catalase activities and a decrease in malondialdehyde level. Immunohistochemical staining demonstrated down-regulation of PCNA protein. According to the Western blot comparison analysis, COX-2 and Bcl2 is up-regulated whilst the Bax is down-regulated. according to these data, this compound plays promising chemoprotective activity, in a model of AOM-induced in ACF.

Keywords: chemopreventive, Schiff based compound, aberrant crypt foci (ACF), immunohistochemical staining

Procedia PDF Downloads 389
17494 Spatial Scale of Clustering of Residential Burglary and Its Dependence on Temporal Scale

Authors: Mohammed A. Alazawi, Shiguo Jiang, Steven F. Messner

Abstract:

Research has long focused on two main spatial aspects of crime: spatial patterns and spatial processes. When analyzing these patterns and processes, a key issue has been to determine the proper spatial scale. In addition, it is important to consider the possibility that these patterns and processes might differ appreciably for different temporal scales and might vary across geographic units of analysis. We examine the spatial-temporal dependence of residential burglary. This dependence is tested at varying geographical scales and temporal aggregations. The analyses are based on recorded incidents of crime in Columbus, Ohio during the 1994-2002 period. We implement point pattern analysis on the crime points using Ripley’s K function. The results indicate that spatial point patterns of residential burglary reveal spatial scales of clustering relatively larger than the average size of census tracts of the study area. Also, spatial scale is independent of temporal scale. The results of our analyses concerning the geographic scale of spatial patterns and processes can inform the development of effective policies for crime control.

Keywords: inhomogeneous K function, residential burglary, spatial point pattern, spatial scale, temporal scale

Procedia PDF Downloads 334
17493 A Safety Analysis Method for Multi-Agent Systems

Authors: Ching Louis Liu, Edmund Kazmierczak, Tim Miller

Abstract:

Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.

Keywords: multi-agent system, safety analysis, safety model, integration map

Procedia PDF Downloads 409
17492 Changes in Serum Neopterin in Workers Exposed to Different Mineral Dust

Authors: Gospodinka Prakova, Pavlina Gidikova, Gergana Sandeva, Kamelia Haracherova, Emil Slavov

Abstract:

Neopterin was demonstrated to be a sensitive marker of cell-mediated immune reactions which plays a key role in the interaction of monocyte / macrophage activation. The purpose of this work was to investigate changes in serum neopterin in workers exposed to different composition of mineral dust. Material and Methods: Serum neopterin was studied in 193 exposed workers, divided into three groups, depending on the mineral dust and content of the quartz in the respirable fraction. The I-st group-coal dust containing less than 2% free crystalline silica (n=44), II-nd group-coal dust containing over 2% free crystalline silica (n=94) and the III-rd group-mixed dust with corundum and carborundum (n=55). The control group was composed of 21 individuals without exposure to dust. Serum neopterin was investigated by Elisa method in ng/ml according to the instructions of the manufacturer. Results and Discussion: It was found significantly higher level of serum neopterin in exposed workers of mineral dust (2,10 ± 0,62 ng / ml), compared with that of the control group (1,10 ± 0,85 ng/ml; p < 0,05). Neopterin levels in workers exposed to coal dust (1,87 ± 0,42 ng / ml-I-st and 3,32 ± 0,77 ng / ml-II-nd group) were significantly higher compared with those exposed to a mixed dust (1,31±0,68 mg / ml-third) and control group (p < 0,05). No significant difference in serum neopterin when exposed to a mixed dust composed of corundum and carborundum (III-rd) and a control group. Conclusion: The results of this study indicate activates a cell-mediated immune response when exposed to a mineral dust. The level of that activation depends mainly on the composition of the dust and is significantly highest in workers exposed to coal dust.

Keywords: mineral dust, neopterin, occupational exposure, respirable crystalline silica

Procedia PDF Downloads 259
17491 Place and Importance of Goats in the Milk Sector in Algeria

Authors: Tennah Safia, Azzag Naouelle, Derdour Salima, Hafsi Fella, Laouadi Mourad, Laamari Abdalouahab, Ghalmi Farida, Kafidi Nacerredine

Abstract:

Currently, goat farming is widely practiced among the rural population of Algeria. Although milk yield of goats is low (110 liters per goat and per year on average), this milk partly ensures the feeding of small children and provides raw milk, curd, and fermented milk to the whole family. In addition, given its investment cost, which is ten times lower than that of a cow, this level of production is still of interest. This interest is reinforced by the qualities of goat's milk, highly sought after for its nutritional value superior to that of cow's milk. In the same way, its aptitude for the transformation, in particular in quality cheeses, is very sought after. The objective of this study is to give the situation of goat milk production in rural areas of Algeria and to establish a classification of goat breeds according to their production potential. For this, a survey was carried out with goat farmers in Algerian steppe. Three indigenous breeds were encountered in this study: the breed Arabia, Mozabite, and Mekatia; Arabia being the most dominant. The Mekatia breed and the Mozabite breed appear to have higher production and milking abilities than other local breeds. They are therefore indicated to play the role of local dairy breeds par excellence. The other breed that could be improved milk performance is the Arabia breed. There, however, the milk performance of this breed is low. However, in order to increase milk production, uncontrolled crosses with imported breeds (mainly Saanen and Alpine) were carried out. The third population that can be included in the category for dairy production is the dairy breed group of imported origin. There are farms in Algeria composed of Alpine and Saanen breeds born locally. Improved milk performance of local goats, Crusader population, and dairy breeds of imported origin could be done by selection. For this, it is necessary to set up a milk control to detect the best animals. This control could be carried out among interested farmers in each large goat breeding area. In conclusion, sustained efforts must be made to enable the sustainable development of the goat sector in Algeria. It will, therefore, be necessary to deepen the reflection on a national strategy to valorize goat's milk, taking into account the specificities of the environment, the genetic biodiversity, and the eating habits of the Algerian consumer.

Keywords: goat, milk, Algeria, biodiversity

Procedia PDF Downloads 172
17490 DNpro: A Deep Learning Network Approach to Predicting Protein Stability Changes Induced by Single-Site Mutations

Authors: Xiao Zhou, Jianlin Cheng

Abstract:

A single amino acid mutation can have a significant impact on the stability of protein structure. Thus, the prediction of protein stability change induced by single site mutations is critical and useful for studying protein function and structure. Here, we presented a deep learning network with the dropout technique for predicting protein stability changes upon single amino acid substitution. While using only protein sequence as input, the overall prediction accuracy of the method on a standard benchmark is >85%, which is higher than existing sequence-based methods and is comparable to the methods that use not only protein sequence but also tertiary structure, pH value and temperature. The results demonstrate that deep learning is a promising technique for protein stability prediction. The good performance of this sequence-based method makes it a valuable tool for predicting the impact of mutations on most proteins whose experimental structures are not available. Both the downloadable software package and the user-friendly web server (DNpro) that implement the method for predicting protein stability changes induced by amino acid mutations are freely available for the community to use.

Keywords: bioinformatics, deep learning, protein stability prediction, biological data mining

Procedia PDF Downloads 451
17489 In-Farm Wood Gasification Energy Micro-Generation System in Brazil: A Monte Carlo Viability Simulation

Authors: Erich Gomes Schaitza, Antônio Francisco Savi, Glaucia Aparecida Prates

Abstract:

The penetration of renewable energy into the electricity supply in Brazil is high, one of the highest in the World. Centralized hydroelectric generation is the main source of energy, followed by biomass and wind. Surprisingly, mini and micro-generation are negligible, with less than 2,000 connections to the national grid. In 2015, a new regulatory framework was put in place to change this situation. In the agricultural sector, the framework was complemented by the offer of low interest rate loans to in-farm renewable generation. Brazil proposed to more than double its area of planted forests as part of its INDC- Intended Nationally Determined Contributions to the UNFCCC-U.N. Framework Convention on Climate Change (UNFCCC). This is an ambitious target which will be achieved only if forests are attractive to farmers. Therefore, this paper analyses whether planting forests for in-farm energy generation with a with a woodchip gasifier is economically viable for microgeneration under the new framework and at if they could be an economic driver for forest plantation. At first, a static case was analyzed with data from Eucalyptus plantations in five farms. Then, a broader analysis developed with the use of Monte Carlo technique. Planting short rotation forests to generate energy could be a viable alternative and the low interest loans contribute to that. There are some barriers to such systems such as the inexistence of a mature market for small scale equipment and of a reference network of good practices and examples.

Keywords: biomass, distribuited generation, small-scale, Monte Carlo

Procedia PDF Downloads 277