Search results for: monitoring tool

Authors: D. Courault, L. Hossard, V. Demarez, E. Ndikumana, D. Ho Tong Minh, N. Baghdadi, F. Ruget

Abstract:

In the global change context, efficient management of the available resources has become one of the most important topics, particularly for sustainable crop development. Timely assessment with high precision is crucial for water resource and pest management. Rice cultivated in Southern France in the Camargue region must face a challenge, reduction of the soil salinity by flooding and at the same time reduce the number of herbicides impacting negatively the environment. This context has lead farmers to diversify crop rotation and their agricultural practices. The objective of this study was to evaluate this crop diversity both in crop systems and in agricultural practices applied to rice paddy in order to quantify the impact on the environment and on the crop production. The proposed method is based on the combined use of crop models and multispectral data acquired from the recent Sentinel 2 satellite sensors launched by the European Space Agency (ESA) within the homework of the Copernicus program. More than 40 images at fine spatial resolution (10m in the optical range) were processed for 2016 and 2017 (with a revisit time of 5 days) to map crop types using random forest method and to estimate biophysical variables (LAI) retrieved by inversion of the PROSAIL canopy radiative transfer model. Thanks to the high revisit time of Sentinel 2 data, it was possible to monitor the soil labor before flooding and the second sowing made by some farmers to better control weeds. The temporal trajectories of remote sensing data were analyzed for various rice cultivars for defining the main parameters describing the phenological stages useful to calibrate two crop models (STICS and SAFY). Results were compared to surveys conducted with 10 farms. A large variability of LAI has been observed at farm scale (up to 2-3m²/m²) which induced a significant variability in the yields simulated (up to 2 ton/ha). Observations on more than 300 fields have also been collected on land use. Various maps were elaborated, land use, LAI, flooding and sowing, and harvest dates. All these maps allow proposing a new typology to classify these paddy crop systems. Key phenological dates can be estimated from inverse procedures and were validated against ground surveys. The proposed approach allowed to compare the years and to detect anomalies. The methods proposed here can be applied at different crops in various contexts and confirm the potential of remote sensing acquired at fine resolution such as the Sentinel2 system for agriculture applications and environment monitoring. This study was supported by the French national center of spatial studies (CNES, funded by the TOSCA).

Keywords: agricultural practices, remote sensing, rice, yield

Procedia PDF Downloads 265

Authors: A. Kudrev

Abstract:

The duplex Poly(A)-Poly(U) denaturation in an aqueous solutions in mixtures with the tetracationic MeTMPyP4 (Me = 2H, Zn(II); TMPyP4 is 5,10,15,20-tetrakis(N-methylpyridinium-4-yl)porphyrin), was investigated by monitoring the changes in the UV-Vis absorbance spectrum with increasing temperatures from 20°С to 70°С (рН 7.0, I=0.15M). The absorbance data matrices were analyzed with a versatile chemometric procedure that provides the melting profile (distribution of species) and the pure spectrum for each chemical species present along the heating experiment. As revealed by the increase of Tm, the duplex structure was stabilized by these porphyrins. The values of stabilization temperature ΔTm in the presence of these porphyrins are relatively large, 1.2-8.4 °C, indicating that the porphyrins contribute differently in stabilizing the duplex Poly(A)-Poly(U) structure. Remarkable is the fact that the porphyrin TMPyP4 was less effective in the stabilization of the duplex structure than the metalloporphyrin Zn(X)TMPyP4 which suggests that metallization play an important role in porphyrin-RNA binding. Molecular Dynamics Simulations has been used to illustrate melting of the duplex dsRNA bound with a porphyrin molecule.

Keywords: melting, Poly(A)-Poly(U), TMPyP4, Zn(X)TMPyP4

Procedia PDF Downloads 135

Authors: Christine F. Boos, Fernando M. Azevedo

Abstract:

Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

Procedia PDF Downloads 513

Authors: Shashikant R. Kuchekar, Somnath D. Bhumkar, Haribhau R. Aher, Bhaskar H. Zaware, Ponnadurai Ramasami

Abstract:

A precise, sensitive, rapid and selective method for the solvent extraction, spectrophotometric determination of palladium(II) using para-methylphenyl thiourea (PMPT) as an extractant is developed. Palladium(II) forms yellow colored complex with PMPT which shows an absorption maximum at 300 nm. The colored complex obeys Beer’s law up to 7.0 µg ml^-1 of palladium. The molar absorptivity and Sandell’s sensitivity were found to be 8.486 x 10³ l mol^-1cm^-1 and 0.0125 μg cm^-2 respectively. The optimum conditions for the extraction and determination of palladium have been established by monitoring the various experimental parameters. The precision of the method has been evaluated and the relative standard deviation has been found to be less than 0.53%. The proposed method is free from interference from large number of foreign ions. The method has been successfully applied for the determination of palladium from alloy, synthetic mixtures corresponding to alloy samples.

Keywords: solvent extraction, PMPT, Palladium (II), spectrophotometry

Procedia PDF Downloads 447

Authors: Saeeda Nadir Ali, Najma Sultana, Muhammad Saeed Arayne, Amtul Qayoom

Abstract:

Present study describes a simple and a fast liquid chromatographic method using ultraviolet detector for simultaneous determination of anxiety relief medicine alprazolam with ACE inhibitors i.e; lisinopril, captopril and enalapril employing purospher star C18 (25 cm, 0.46 cm, 5 µm). Separation was achieved within 5 min at ambient temperature via methanol: water (8:2 v/v) with pH adjusted to 2.9, monitoring the detector response at 220 nm. Optimum parameters were set up as per ICH (2006) guidelines. Calibration range was found out to be 0.312-10 µg mL-1 for alprazolam and 0.625-20 µg mL-1 for all the ACE inhibitors with correlation coefficients > 0.998 and detection limits 85, 37, 68 and 32 ng mL-1 for lisinopril, captopril, enalapril and alprazolam respectively. Intra-day, inter-day precision and accuracy of the assay were in acceptable range of 0.05-1.62% RSD and 98.85-100.76% recovery. Method was determined to be robust and effectively useful for the estimation of studied drugs in dosage formulations and human serum without obstruction of excipients or serum components.

Keywords: alprazolam, ACE inhibitors, RP HPLC, serum

Procedia PDF Downloads 499

Authors: H. Boucheloukh, N. Aoun, S. Rouissa, T. Sehili, F. Parrino, V. Loddo

Abstract:

Photocatalysis has made a revolution in wastewater treatment and the elimination of persistent organic pollutants. This process is based on the use of semiconductors as photocatalysts. In this study, nickel ferrite spinel (NiFe2O4) nanoparticles were successfully synthesized by the sol-gel route. The structural, morphological, elemental composition, chemical state, particle size, optical and electrochemical characterizations using powder X-ray diffraction (P-XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy(SEM), energy-dispersive X-ray spectroscopy (EDAX ). We tested the prepared NiFe2O4(NPS)by monitoring the degradation of Rose Bengal (RB) dye in an aqueous solution under direct sunlight irradiation. The effects of catalyst dosage and dye concentration were also considered for the effective degradation of RB dye. The optimum catalyst dosage and concentration of dye were found to be 1 g/L and 10 μM, respectively. A maximum of 80% photocatalytic degradation efficiency (DE%) was achieved at 120 min of direct sunlight irradiation.

Keywords: Rose Bengal, Nickelate, photocatalysis, irradiation

Procedia PDF Downloads 195

Authors: Nune Ayvazyan

Abstract:

Since the proclamation of monolingual foreign-language learning methods (the Berlitz Method in the early 20ᵗʰ century and the like), the dilemma has been to allow or not to allow learners’ mother tongue in the foreign-language learning process. The reason for not allowing learners’ mother tongue is reported to create a situation of immersion where students will only use the target language. It could be argued that this artificial monolingual situation is defective, mainly because there are very few real monolingual situations in the society. This is mainly due to the fact that societies are nowadays increasingly multilingual as plurilingual speakers are the norm rather than an exception. More recently, the use of learners’ mother tongue and translation has been put under the spotlight as valid foreign-language teaching tools. The logic dictates that if learners were permitted to use their mother tongue in the foreign-language learning process, that would not only be natural, but also would give them additional means of participation in class, which could eventually lead to learning. For example, when learners’ metalinguistic skills are poor in the target language, a question they might have could be asked in their mother tongue. Otherwise, that question might be left unasked. Attempts at empirically testing the role of translation as a didactic tool in foreign-language teaching are still very scant. In order to fill this void, this study looks into the interaction patterns between students in two kinds of English-learning classes: one with translation and the other in English only (immersion). The experiment was carried out with 61 students enrolled in a second-year university subject in English grammar in Spain. All the students underwent the two treatments, classes with translation and in English only, in order to see how they interacted under the different conditions. The analysis centered on four categories of interaction: teacher talk, teacher-initiated student interaction, student-initiated student-to-teacher interaction, and student-to-student interaction. Also, pre-experiment and post-experiment questionnaires and individual interviews gathered information about the students’ attitudes to translation. The findings show that translation elicited more student-initiated interaction than did the English-only classes, while the difference in teacher-initiated interactional turns was not statistically significant. Also, student-initiated participation was higher in comprehension-based activities (into L1) as opposed to production-based activities (into L2). As evidenced by the questionnaires, the students’ attitudes to translation were initially positive and mainly did not vary as a result of the experiment.

Keywords: foreign language, learning, mother tongue, translation

Procedia PDF Downloads 144

Authors: Purva Joshi, Rohit Thanki, Omar Hanif

Abstract:

Unmanned aerial vehicles (UAVs) are becoming increasingly important in various industrial applications and sectors. Nowadays, a multi UAV network is used for specific types of communication (e.g., military) and monitoring purposes. Therefore, it is critical to reducing propagation delay during communication between UAVs, which is essential in a multi UAV network. This paper presents how the propagation delay between the base station (BS) and the UAVs is reduced using a searching algorithm. Furthermore, the iterative-based K-nearest neighbor (k-NN) algorithm and Travelling Salesmen Problem (TSP) algorthm were utilized to optimize the distance between BS and individual UAV to overcome the problem of propagation delay in multi UAV networks. The simulation results show that this proposed method reduced complexity, improved reliability, and reduced propagation delay in multi UAV networks.

Keywords: multi UAV network, optimal distance, propagation delay, K - nearest neighbor, traveling salesmen problem

Procedia PDF Downloads 180

Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

Abstract:

Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

Procedia PDF Downloads 264

Authors: Paola Millare, Nelinda Catherine Pangilinan

Abstract:

Background and Aim: Cervical cancer is the most commonly diagnosed gynecological malignancy during pregnancy. Owing to the rarity of the disease, and the complexity of all factors that have to be taken into consideration, standardization of treatment is very difficult. Cervical cancer is the second most common malignancy among women. The treatment of cancer during pregnancy is most challenging in the case of cervical cancer, since the pregnant uterus itself is affected. This report aims to present a case of cervical cancer in a pregnant woman and how to manage this case and several issues accompanied with it. Methods: This is a case of a 28 year-old, Gravida 4 Para 2 (1111), who presented with watery to mucoid, whitish, non-foul smelling and increasing in amount. Internal examination revealed normal external genitalia, parous outlet, cervix was transformed into a fungating mass measuring 5x4 cm, with left parametrial involvement, body of uterus was enlarged to 24 weeks size, no adnexal mass or tenderness. She had cervical punch biopsy, which revealed, adenocarcinoma, well-differentiated cervical tissue. Standard management for cases with stage 2B cervical carcinoma was to start radiation or radical hysterectomy. In the case of patients diagnosed with cervical cancer and currently pregnant, these kind of management will result to fetal loss. The patient still declined the said management and opted to delay the treatment and wait for her baby to reach at least term and proceed to cesarean section as route of delivery. Results: The patient underwent an elective cesarean section at 37th weeks age of gestation, with an outcome of a term, live baby boy APGAR score 7,9 birthweight 2600 grams. One month postpartum, the patient followed up and completed radiotherapy, chemotherapy and brachytherapy. She was advised to go back after 6 months for monitoring. On her last check up, an internal examination was done which revealed normal external genitalia, vagina admits 2 fingers with ease, there is a palpable fungating mass at the cervix measuring 2x2 cm. A repeat gynecologic oncologic ultrasound was done revealing cervical mass, endophytic, grade 1 color score with stromal invasion 35% post radiation reactive lymph nodes with intact paracolpium, pericervical, and parametrial involvement. The patient was then advised to undergo pelvic boost and for close monitoring of the cervical mass. Conclusion: Cervical cancer in pregnancy is rare but is a dilemma for women and their physicians. Treatment should be multidisciplinary and individualized following careful counseling. In this case, the treatment was clearly on the side of preventing the progression of cervical cancer while she is pregnant, however due to ethical reasons, the management deviates on the right of the patient to decide for her own health and her unborn child. The collaborative collection of data relating to treatment and outcome is strongly encouraged.

Keywords: cancer, cervical, ethical, pregnancy

Procedia PDF Downloads 228

Authors: Y. Kourd, D. Lefebvre

Abstract:

The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

Procedia PDF Downloads 611

Authors: Anisa Suraya Ab Razak, Izza Hayat

Abstract:

Introduction: The diagnosis and management of severe hyponatremia in neuropsychiatric patients present a significant challenge to physicians. Several factors contribute, including diagnostic shadowing and attributing abnormal behavior to intellectual disability or psychiatric conditions. Hyponatraemia is the commonest electrolyte abnormality in the inpatient population, ranging from mild/asymptomatic, moderate to severe levels with life-threatening symptoms such as seizures, coma and death. There are several documented fatal case reports in the literature of severe hyponatremia secondary to psychogenic polydipsia, often diagnosed only in autopsy. This paper presents a case study of acute severe hyponatremia in a neuropsychiatric patient with early diagnosis and admission to intensive care. Case study: A 21-year old Caucasian male with known epilepsy and learning disability was admitted from residential living with generalized tonic-clonic self-terminating seizures after refusing medications for several weeks. Evidence of superficial head injury was detected on physical examination. His laboratory data demonstrated mild hyponatremia (125 mmol/L). Computed tomography imaging of his brain demonstrated no acute bleed or space-occupying lesion. He exhibited abnormal behavior - restlessness, drinking water from bathroom taps, inability to engage, paranoia, and hypersexuality. No collateral history was available to establish his baseline behavior. He was loaded with intravenous sodium valproate and leveritircaetam. Three hours later, he developed vomiting and a generalized tonic-clonic seizure lasting forty seconds. He remained drowsy for several hours and regained minimal recovery of consciousness. A repeat set of blood tests demonstrated profound hyponatremia (117 mmol/L). Outcomes: He was referred to intensive care for peripheral intravenous infusion of 2.7% sodium chloride solution with two-hourly laboratory monitoring of sodium concentration. Laboratory monitoring identified dangerously rapid correction of serum sodium concentration, and hypertonic saline was switched to a 5% dextrose solution to reduce the risk of acute large-volume fluid shifts from the cerebral intracellular compartment to the extracellular compartment. He underwent urethral catheterization and produced 8 liters of urine over 24 hours. Serum sodium concentration remained stable after 24 hours of correction fluids. His GCS recovered to baseline after 48 hours with improvement in behavior -he engaged with healthcare professionals, understood the importance of taking medications, admitted to illicit drug use and drinking massive amounts of water. He was transferred from high-dependency care to ward level and was initiated on multiple trials of anti-epileptics before achieving seizure-free days two weeks after resolution of acute hyponatremia. Conclusion: Psychogenic polydipsia is often found in young patients with intellectual disability or psychiatric disorders. Patients drink large volumes of water daily ranging from ten to forty liters, resulting in acute severe hyponatremia with mortality rates as high as 20%. Poor outcomes are due to challenges faced by physicians in making an early diagnosis and treating acute hyponatremia safely. A low index of suspicion of water intoxication is required in this population, including patients with known epilepsy. Monitoring urine output proved to be clinically effective in aiding diagnosis. Early referral and admission to intensive care should be considered for safe correction of sodium concentration while minimizing risk of fatal complications e.g. central pontine myelinolysis.

Keywords: epilepsy, psychogenic polydipsia, seizure, severe hyponatremia

Procedia PDF Downloads 112

Authors: Chiqian Zhang, Kyle D. McIntosh, Nathan Sienkiewicz, Ian Struewing, Erin A. Stelzer, Jennifer L. Graham, Jingrang Lu

Abstract:

Phytoplankton plays an essential role in freshwater aquatic ecosystems and is the primary group synthesizing organic carbon and providing food sources or energy to ecosystems. Therefore, the identification and quantification of phytoplankton are important for estimating and assessing ecosystem productivity (carbon fixation), water quality, and eutrophication. Microscopy is the current gold standard for identifying and quantifying phytoplankton composition and abundance. However, microscopic analysis of phytoplankton is time-consuming, has a low sample throughput, and requires deep knowledge and rich experience in microbial morphology to implement. To improve this situation, quantitative polymerase chain reaction (qPCR) was considered for phytoplankton identification and quantification. Using qPCR to assess phytoplankton composition and abundance, however, has not been comprehensively evaluated. This study focused on: 1) conducting a comprehensive performance comparison of qPCR and microscopy techniques in identifying and quantifying phytoplankton and 2) examining the use of qPCR as a tool for assessing eutrophication. Twelve large rivers located throughout the United States were evaluated using data collected from 2017 to 2019 to understand the relation between qPCR-based phytoplankton abundance and eutrophication. This study revealed that temporal variation of phytoplankton abundance in the twelve rivers was limited within years (from late spring to late fall) and among different years (2017, 2018, and 2019). Midcontinent rivers had moderately greater phytoplankton abundance than eastern and western rivers, presumably because midcontinent rivers were more eutrophic. The study also showed that qPCR- and microscope-determined phytoplankton abundance had a significant positive linear correlation (adjusted R² 0.772, p-value < 0.001). In addition, phytoplankton abundance assessed via qPCR showed promise as an indicator of the eutrophication status of those rivers, with oligotrophic rivers having low phytoplankton abundance and eutrophic rivers having (relatively) high phytoplankton abundance. This study demonstrated that qPCR could serve as an alternative tool to traditional microscopy for phytoplankton quantification and eutrophication assessment in freshwater rivers.

Keywords: phytoplankton, eutrophication, river, qPCR, microscopy, spatiotemporal variation

Procedia PDF Downloads 81

Authors: Siham Boulaknadel

Abstract:

Every culture has its share of a rich history of storytelling in oral, visual, and textual form. The Amazigh language, as many languages, has its own which has entertained and informed across centuries and cultures, and its instructional potential continues to serve teachers. According to many researchers, listening to stories draws attention to the sounds of language and helps children develop sensitivity to the way language works. Stories including repetitive phrases, unique words, and enticing description encourage students to join in actively to repeat, chant, sing, or even retell the story. This kind of practice is important to language learners’ oral language development, which is believed to correlate completely with student’s academic success. Today, with the advent of multimedia, digital storytelling for instance can be a practical and powerful learning tool. It has the potential in transforming traditional learning into a world of unlimited imaginary environment. This paper reports on a research project on development of multimedia Storytelling Website using traditional Amazigh oral narratives called “tell me a story”. It is a didactic tool created for the learning of good moral values in an interactive multimedia environment combining on-screen text, graphics and audio in an enticing environment and enabling the positive values of stories to be projected. This Website developed in this study is based on various pedagogical approaches and learning theories deemed suitable for children age 8 to 9 year-old. The design and development of Website was based on a well-researched conceptual framework enabling users to: (1) re-play and share the stories in schools or at home, and (2) access the Website anytime and anywhere. Furthermore, the system stores the students work and activities over the system, allowing parents or teachers to monitor students’ works, and provide online feedback. The Website contains following main feature modules: Storytelling incorporates a variety of media such as audio, text and graphics in presenting the stories. It introduces the children to various kinds of traditional Amazigh oral narratives. The focus of this module is to project the positive values and images of stories using digital storytelling technique. Besides development good moral sense in children using projected positive images and moral values, it also allows children to practice their comprehending and listening skills. Reading module is developed based on multimedia material approach which offers the potential for addressing the challenges of reading instruction. This module is able to stimulate children and develop reading practice indirectly due to the tutoring strategies of scaffolding, self-explanation and hyperlinks offered in this module. Word Enhancement assists the children in understanding the story and appreciating the good moral values more efficiently. The difficult words or vocabularies are attached to present the explanation, which makes the children understand the vocabulary better. In conclusion, we believe that the interactive multimedia storytelling reveals an interesting and exciting tool for learning Amazigh. We plan to address some learning issues, in particularly the uses of activities to test and evaluate the children on their overall understanding of story and words presented in the learning modules.

Keywords: Amazigh language, e-learning, storytelling, language teaching

Procedia PDF Downloads 386

Authors: Ajit Brindhaban

Abstract:

Background and Purpose: Computed Tomography (CT) scans have become the largest source of radiation in radiological imaging. The purpose of this study was to compare the quality of pediatric Computed Tomography (CT) images reconstructed using Filtered Back Projection (FBP) with images reconstructed using different strengths of Iterative Reconstruction (IR) technique, and to perform a feasibility study to assess the use of IR techniques as a dose reduction tool. Materials and Methods: An anthropomorphic phantom representing a 5-year old child was scanned, in two stages, using a Siemens Somatom CT unit. In stage one, scans of the head, chest and abdomen were performed using standard protocols recommended by the scanner manufacturer. Images were reconstructed using FBP and 5 different strengths of IR. Contrast-to-Noise Ratios (CNR) were calculated from average CT number and its standard deviation measured in regions of interest created in the lungs, bone, and soft tissues regions of the phantom. Paired t-test and the one-way ANOVA were used to compare the CNR from FBP images with IR images, at p = 0.05 level. The lowest strength value of IR that produced the highest CNR was identified. In the second stage, scans of the head was performed with decreased mA(s) values relative to the increase in CNR compared to the standard FBP protocol. CNR values were compared in this stage using Paired t-test at p = 0.05 level. Results: Images reconstructed using IR technique had higher CNR values (p < 0.01.) in all regions compared to the FBP images, at all strengths of IR. The CNR increased with increasing IR strength of up to 3, in the head and chest images. Increases beyond this strength were insignificant. In abdomen images, CNR continued to increase up to strength 5. The results also indicated that, IR techniques improve CNR by a up to factor of 1.5. Based on the CNR values at strength 3 of IR images and CNR values of FBP images, a reduction in mA(s) of about 20% was identified. The images of the head acquired at 20% reduced mA(s) and reconstructed using IR at strength 3, had similar CNR as FBP images at standard mA(s). In the head scans of the phantom used in this study, it was demonstrated that similar CNR can be achieved even when the mA(s) is reduced by about 20% if IR technique with strength of 3 is used for reconstruction. Conclusions: The IR technique produced better image quality at all strengths of IR in comparison to FBP. IR technique can provide approximately 20% dose reduction in pediatric head CT while maintaining the same image quality as FBP technique.

Keywords: filtered back projection, image quality, iterative reconstruction, pediatric computed tomography imaging

Procedia PDF Downloads 131

Authors: Minakshi Goswami, M. V. Khire

Abstract:

The urban land use is an outcome of geographical and socio economic factors over the decades. Hence, spatial information on land use and possibilities of alternate use is essential for the selection, planning and implementation to meet the increasing demands of human needs and welfare of the urban area. This information assists in monitoring the land use resulting out of charging demands of increasing urban population over the decades. So in this paper, a detailed work on urban land use pattern, with a special reference to build up land in Bangalore city is analyzed in view of the various master plans from 1975to 2011. An attempt has been made to study the status of urban land use of Bangalore city during this period to detect the changes on land utilization rate that has taken place in each master plan period, particularly in the built-up land. The set of measures taken by the city corporation to contain the problems regarding the extremely bothering existing land use in Bangalore city is analyzed.

Keywords: built up land, land use changes, master plan, population

Procedia PDF Downloads 441

Authors: P. Góes, J. Manzi

Abstract:

This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.

Keywords: energy, efficiency, entropy, reactive

Procedia PDF Downloads 392

Authors: Hyeon-Seung Kim, Sang-Mi Park, Min-Seo Kim, Jong-Myeung Shin, Leen-Seok Kang

Abstract:

Recently, the use of Building Information Modeling (BIM) in public construction works has become mandatory in some countries and it is anticipated that BIM will be applied to the actual field of civil engineering projects. However, the BIM system is still focused on the architectural project and the design phase. Because the civil engineering project is linear type project and is focused on the construction phase comparing with architectural project, 3D simulation is difficult to visualize them. This study suggests a method and a prototype system to solve workspace conflictions among construction activities using BIM simulation tool.

Keywords: BIM, workspace, confliction, visualization

Procedia PDF Downloads 386

Authors: Nelvin Joseph, K. Krishna Milan Rao, Praveen Dwarakanath

Abstract:

The explosive growth of Smart phones around the world has led to the shift of the primary engagement tool for entertainment from traditional consoles and music players to an all integrated device. Augmented Reality is the next big shift in bringing in a new dimension to the play. The paper explores the construct and working of the community engine in Delta T – an Augmented Reality game that allows users to evolve rules in the game basis collective bargaining mirroring democracy even in a gaming world.

Keywords: augmented reality, artificial neural networks, mobile application, human computer interaction, community engine

Procedia PDF Downloads 308

Authors: Sheelagh Heugh, Michael Upton, Kriya Kalidas, Stephen Breen

Abstract:

This article aims to create awareness of the opportunities and issues the artificial intelligence (AI) tool GPT-3 (Generative Pre-trained Transformer-3) brings to higher education. Technological disruptors have featured in higher education (HE) since Konrad Klaus developed the first functional programmable automatic digital computer. The flurry of technological advances, such as personal computers, smartphones, the world wide web, search engines, and artificial intelligence (AI), have regularly caused disruption and discourse across the educational landscape around harnessing the change for the good. Accepting AI influences are inevitable; we took mixed methods through participatory action research and evaluation approach. Joining HE communities, reviewing the literature, and conducting our own research around Chat GPT-3, we reviewed our institutional approach to changing our current practices and developing policy linked to assessments and the use of Chat GPT-3. We review the impact of GPT-3, a high-powered natural language processing (NLP) system first seen in 2020 on HE. Historically HE has flexed and adapted with each technological advancement, and the latest debates for educationalists are focusing on the issues around this version of AI which creates natural human language text from prompts and other forms that can generate code and images. This paper explores how Chat GPT-3 affects the current educational landscape: we debate current views around plagiarism, research misconduct, and the credibility of assessment and determine the tool's value in developing skills for the workplace and enhancing critical analysis skills. These questions led us to review our institutional policy and explore the effects on our current assessments and the development of new assessments. Conclusions: After exploring the pros and cons of Chat GTP-3, it is evident that this form of AI cannot be un-invented. Technology needs to be harnessed for positive outcomes in higher education. We have observed that materials developed through AI and potential effects on our development of future assessments and teaching methods. Materials developed through Chat GPT-3 can still aid student learning but lead to redeveloping our institutional policy around plagiarism and academic integrity.

Keywords: artificial intelligence, Chat GPT-3, intellectual property, plagiarism, research misconduct

Procedia PDF Downloads 75

Authors: Dian Zhang, Brendan Heery, Maria O’Neill, Ciprian Briciu-Burghina, Noel E. O’Connor, Fiona Regan

Abstract:

Recent developments in sensors, wireless data communication and the cloud computing have brought the sensor web to a whole new generation. The introduction of the concept of ‘Internet of Thing (IoT)’ has brought the sensor research into a new level, which involves the developing of long lasting, low cost, environment friendly and smart sensors; new wireless data communication technologies; big data analytics algorithms and cloud based solutions that are tailored to large scale smart sensor network. The next generation of smart sensor network consists of several layers: physical layer, where all the smart sensors resident and data pre-processes occur, either on the sensor itself or field gateway; data transmission layer, where data and instructions exchanges happen; the data process layer, where meaningful information is extracted and organized from the pre-process data stream. There are many definitions of smart sensor, however, to summarize all these definitions, a smart sensor must be Intelligent and Adaptable. In future large scale sensor network, collected data are far too large for traditional applications to send, store or process. The sensor unit must be intelligent that pre-processes collected data locally on board (this process may occur on field gateway depends on the sensor network structure). In this case study, three smart sensing methods, corresponding to simple thresholding, statistical model and machine learning based MoPBAS method, are introduced and their strength and weakness are discussed as an introduction to the smart sensing concept. Data fusion, the integration of data and knowledge from multiple sources, are key components of the next generation smart sensor network. For example, in the water level monitoring system, weather forecast can be extracted from external sources and if a heavy rainfall is expected, the server can send instructions to the sensor notes to, for instance, increase the sampling rate or switch on the sleeping mode vice versa. In this paper, we describe the deployment of 11 affordable water level sensors in the Dublin catchment. The objective of this paper is to use the deployed river level sensor network at the Dodder catchment in Dublin, Ireland as a case study to give a vision of the next generation of a smart sensor network for flood monitoring to assist agencies in making decisions about deploying resources in the case of a severe flood event. Some of the deployed sensors are located alongside traditional water level sensors for validation purposes. Using the 11 deployed river level sensors in a network as a case study, a vision of the next generation of smart sensor network is proposed. Each key component of the smart sensor network is discussed, which hopefully inspires the researchers who are working in the sensor research domain.

Keywords: smart sensing, internet of things, water level sensor, flooding

Procedia PDF Downloads 367

Authors: Joshefina Bengoechea Fernandez, Alex Bell

Abstract:

In its 2021 guidance for policy makers, the UNESCO has proposed 4 areas where AI can be applied in educational settings: These are: 1) Education management and delivery; 2) Learning and assessment; 3) Empowering teachers and facilitating teaching, and 4) Providing lifelong learning possibilities (UNESCO, 2021). Like with wblockchain technologies, AI will automate the management of educational institutions. These include, but are not limited to admissions, timetables, attendance, and homework monitoring. Furthermore, AI will be used to select relevant learning content across learning platforms for each student, based on his or her personalized needs. A problem educators face is the “one-size-fits-all” approach that does not work with a diverse student population. The purpose of this paper is to illustrate if the implementation of Technology is the solution to the Problems faced in Higher Education. The paper builds upon a constructivist approach, combining a literature review and research on key publications and academic reports.

Keywords: artificial intelligence, learning platforms, students personalised needs, life- long learning, privacy, ethics

Procedia PDF Downloads 85

Authors: AmirHossein Mohajerzadeh, Mohammad Alishahi, Saeed Aslishahi, Mohsen Zabihi

Abstract:

In this paper, we consider sensor nodes with the capability of measuring the bearings (relative angle to the target). We use geometric methods to select a set of observer nodes which are responsible for collecting data from the target. Considering the characteristics of target tracking applications, it is clear that significant numbers of sensor nodes are usually inactive. Therefore, in order to minimize the total network energy consumption, a set of sensor nodes, called sentinel, is periodically selected for monitoring, controlling the environment and transmitting data through the network. The other nodes are inactive. Furthermore, the proposed algorithm provides a joint scheduling and routing algorithm to transmit data between network nodes and the fusion center (FC) in which not only provides an efficient way to estimate the target position but also provides an efficient target tracking. Performance evaluation confirms the superiority of the proposed algorithm.

Keywords: coverage, routing, scheduling, target tracking, wireless sensor networks

Procedia PDF Downloads 365

Authors: Elisabetta Ceretti, Silvia Bonizzoni, Alberto Bonetti, Milena Villarini, Marco Verani, Maria Antonella De Donno, Sara Bonetta, Umberto Gelatti

Abstract:

Introduction: Air pollution is a global problem. In 2013, the International Agency for Research on Cancer (IARC) classified air pollution and particulate matter as carcinogenic to human. The study of the health effects of air pollution in children is very important because they are a high-risk group in terms of the health effects of air pollution and early exposure during childhood can increase the risk of developing chronic diseases in adulthood. The MAPEC_LIFE (Monitoring Air Pollution Effects on Children for supporting public health policy) is a project founded by EU Life+ Programme which intends to evaluate the associations between air pollution and early biological effects in children and to propose a model for estimating the global risk of early biological effects due to air pollutants and other factors in children. Methods: The study was carried out on 6-8-year-old children living in five Italian towns in two different seasons. Two biomarkers of early biological effects, primary DNA damage detected with the comet assay and frequency of micronuclei, were investigated in buccal cells of children. Details of children diseases, socio-economic status, exposures to other pollutants and life-style were collected using a questionnaire administered to children’s parents. Child exposure to urban air pollution was assessed by analysing PM0.5 samples collected in the school areas for PAHs and nitro-PAHs concentration, lung toxicity and in vitro genotoxicity on bacterial and human cells. Data on the chemical features of the urban air during the study period were obtained from the Regional Agency for Environmental Protection. The project created also the opportunity to approach the issue of air pollution with the children, trying to raise their awareness on air quality, its health effects and some healthy behaviors by means of an educational intervention in the schools. Results: 1315 children were recruited for the study and participate in the first sampling campaign in the five towns. The second campaign, on the same children, is still ongoing. The preliminary results of the tests on buccal mucosa cells of children will be presented during the conference as well as the preliminary data about the chemical composition and the toxicity and genotoxicity features of PM0.5 samples. The educational package was tested on 250 children of the primary school and showed to be very useful, improving children knowledge about air pollution and its effects and stimulating their interest. Conclusions: The associations between levels of air pollutants, air mutagenicity and biomarkers of early effects will be investigated. A tentative model to calculate the global absolute risk of having early biological effects for air pollution and other variables together will be proposed and may be useful to support policy-making and community interventions to protect children from possible health effects of air pollutants.

Keywords: air pollution exposure, biomarkers of early effects, children, public health policy

Procedia PDF Downloads 313

Authors: E. S. Johal, M. S. Saini, M. K. Jha

Abstract:

Currently, 1.1 billion people are at risk due to lack of clean water and about 35 % of people in the developed world die from water related problem. To alleviate these problems water purification technology requires new approaches for effective management and conservation of water resources. Electrospun nanofibres membrane has a potential for water purification due to its high large surface area and good mechanical strength. In the present study PAMAM dendrimers composite nynlon-6 nanofibres membrane was prepared by crosslinking method using Glutaraldehyde. Further, the efficacy of the modified membrane can be renewed by mere exposure of the saturated membrane with the solution having acidic pH. The modified membrane can be used as an effective tool for water purification.

Keywords: dendrimer, nanofibers, nanocomposite membrane, water purification

Procedia PDF Downloads 337

Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

Abstract:

A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

Procedia PDF Downloads 172

Authors: Oxana Lukoshus

Abstract:

The methods of corpus linguistics, a well-established field of research, are being increasingly applied in cognitive linguistics. Corpora data are especially useful for different quantitative studies of grammatical and other aspects of language. The main objective of this paper is to demonstrate how present-day corpora can be applied in semantic studies in general and in semantic studies of adjectives in particular. Polysemantic adjectives have been the subject of numerous studies. But most of them have been carried out on dictionaries. Undoubtedly, dictionaries are viewed as one of the basic data sources, but only at the initial steps of a research. The author usually starts with the analysis of the lexicographic data after which s/he comes up with a hypothesis. In the research conducted three polysemantic synonyms true, loyal, faithful have been analyzed in terms of differences and similarities in their semantic structure. A corpus-based approach in the study of the above-mentioned adjectives involves the following. After the analysis of the dictionary data there was the reference to the following corpora to study the distributional patterns of the words under study – the British National Corpus (BNC) and the Corpus of Contemporary American English (COCA). These corpora are continually updated and contain thousands of examples of the words under research which make them a useful and convenient data source. For the purpose of this study there were no special needs regarding genre, mode or time of the texts included in the corpora. Out of the range of possibilities offered by corpus-analysis software (e.g. word lists, statistics of word frequencies, etc.), the most useful tool for the semantic analysis was the extracting a list of co-occurrence for the given search words. Searching by lemmas, e.g. true, true to, and grouping the results by lemmas have proved to be the most efficient corpora feature for the adjectives under the study. Following the search process, the corpora provided a list of co-occurrences, which were then to be analyzed and classified. Not every co-occurrence was relevant for the analysis. For example, the phrases like An enormous sense of responsibility to protect the minds and hearts of the faithful from incursions by the state was perceived to be the basic duty of the church leaders or ‘True,’ said Phoebe, ‘but I'd probably get to be a Union Official immediately were left out as in the first example the faithful is a substantivized adjective and in the second example true is used alone with no other parts of speech. The subsequent analysis of the corpora data gave the grounds for the distribution groups of the adjectives under the study which were then investigated with the help of a semantic experiment. To sum it up, the corpora-based approach has proved to be a powerful, reliable and convenient tool to get the data for the further semantic study.

Keywords: corpora, corpus-based approach, polysemantic adjectives, semantic studies

Procedia PDF Downloads 303

Authors: Gilbert Omorodion Osayemwenre, Edson Meyer, R. T. Taziwa

Abstract:

The electrical analysis of single junction amorphous silicon solar modules is carried out using outdoor monitoring technique. Like crystalline silicon PV modules, the electrical characterisation and performance of single junction amorphous silicon modules are best described by its current-voltage (IV) characteristic. However, IV curve has a direct dependence on the type of PV technology and material properties used. The analysis reveals discrepancies in the modules performance parameter even though they are of similar technology. The aim of this work is to compare the electrical performance output of each module, using electrical parameters with the aid of PVPM 100040C IV tracer. These results demonstrated the relevance of standardising the performance parameter for effective degradation analysis of a-Si:H.

Keywords: PVPM 100040C IV tracer, SolarWatt part, single junction amorphous silicon module (a-Si:H), Staebler-Wronski (S-W) degradation effect

Procedia PDF Downloads 302

Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

Abstract:

The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

Procedia PDF Downloads 407

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 26