Search results for: coping techniques

Authors: Ebenezer Amoquandoh, Daniel Bruce Sarpong, Godfred K. Ofosu-Budu, Andreas Fliessbach

Abstract:

Soil quality is at stake globally, but under tropical conditions, the loss of soil fertility may be existential. The current rates of soil nutrient depletion, erosion and environmental degradation in most of Africa’s farmland urgently require methods for soil fertility restoration through affordable agricultural management techniques. The study assessed the effects of locally available organic resources to improve soil fertility, crop yield and profitability compared to business as usual on farms in the Eastern and Greater Accra regions of Ghana. Apart from this, we analyzed the change of farmers’ perceptions and knowledge upon the experience with the new techniques; the effect of using locally available organic resource on farmers’ yield and determined the factors influencing the profitability of farming. Using the Difference in Mean Score and Proportion to estimate the extent to which farmers’ perceptions, knowledge and practices have changed, the study showed that farmers’ perception, knowledge and practice on the use of locally available organic resources have changed significantly. This paves way for the sustainable use of locally available organic resource for soil fertility improvement. The Propensity Score Matching technique and Endogenous Switching Regression model used showed that using locally available organic resources have the potential to increase crop yield. It was also observed that using the Profit Margin, Net Farm Income and Return on Investment analysis, it is more profitable to use locally available organic resources than other soil fertility amendments techniques studied. The results further showed that socioeconomic, farm characteristics and institutional factors are significant in influencing farmers’ decision to use locally available organic resources and profitability.

Keywords: soil fertility, locally available organic resources, perception, profitability, sustainability

Procedia PDF Downloads 148

Authors: S. B. Mayil Vealan, C. Sekar

Abstract:

Bisphenol A (BIS A) and 4 Nitrophenol (4N) are the most prevalent environmental endocrine-disrupting chemicals which mimic hormones and have a direct relationship to the development and growth of animal and human reproductive systems. Moreover, intensive exposure to the compound is related to prostate and breast cancer, infertility, obesity, and diabetes. Hence, accurate and reliable determination techniques are crucial for preventing human exposure to these harmful chemicals. Lanthanum Copper Oxide (La₂Cu₂O₅) nanoparticles were synthesized and investigated through various techniques such as scanning electron microscopy, high-resolution transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and electrochemical impedance spectroscopy. Cyclic voltammetry and square wave voltammetry techniques are employed to evaluate the electrochemical behavior of as-synthesized samples toward the electrochemical detection of Bisphenol A and 4-Nitrophenol. Under the optimal conditions, the oxidation current increased linearly with increasing the concentration of BIS A and 4-N in the range of 0.01 to 600 μM with a detection limit of 2.44 nM and 3.8 nM. These are the lowest limits of detection and the widest linear ranges in the literature for this determination. The method was applied to the simultaneous determination of BIS A and 4-N in real samples (food packing materials and river water) with excellent recovery values ranging from 95% to 99%. Better stability, sensitivity, selectivity and reproducibility, fast response, and ease of preparation made the sensor well-suitable for the simultaneous determination of bisphenol and 4 Nitrophenol. To the best of our knowledge, this is the first report in which La₂Cu₂O₅ nano particles were used as efficient electron mediators for the fabrication of endocrine disruptor (BIS A and 4N) chemical sensors.

Keywords: endocrine disruptors, electrochemical sensor, Food contacting materials, lanthanum cuprates, nanomaterials

Procedia PDF Downloads 86

Authors: Vahid Rashedi, Banafsheh Ebrahimi, Mahtab Sharif Mohseni, Mohammadali Hosseini

Abstract:

Introduction: One of the metrics used to evaluate health status is life expectancy. This index alters as people age as a result of several events, illnesses, stress, and anxiety. One of the issues that might develop into a lethal phobia is death anxiety. This study looked at older persons in Tehran, Iran, to see if there was any correlation between life expectancy and fear of dying. Methods: Cluster random sampling was used to select 208 older persons (age 60) who had been sent to adult daycare facilities in Tehran for this correlational descriptive study. A demographic questionnaire, Temper's death anxiety scale, and Snyder's life expectancy scale were used to gather the data. Statistical Package for the Social Sciences softwear version 22 was used to conduct the data analysis. Results: The average age of the senior citizens was 66.60 (6.58) years. With a mean life expectancy of 24.94, it was discovered that the average death anxiety was 12.21. Additionally, Pearson's correlation coefficient demonstrated a bad correlation between fear of dying and life expectancy. Age, residential status, and death fear were the three primary predictors of a decline in life expectancy, according to multiple regression analysis. Conclusion: The findings suggest that there is a link between death fear and a lower life expectancy, which calls for the use of appropriate strategies to increase older individuals' life expectancies as well as the teaching of anxiety coping mechanisms.

Keywords: aged, frailty, death, anxiety, life

Procedia PDF Downloads 85

Authors: Salam Yaghi, Saleh Abu Dabous

Abstract:

Government reports and published research have flagged and brought to public attention the deteriorating condition of a large percentage of bridges in Canada and the United States. With the increasing number of deteriorated bridges in the US, Canada, and around the globe, condition assessment techniques of concrete bridges are evolving. Investigation for bridges’ defects such as cracks, spalls, and delamination and their level of severity are the main objectives of condition assessment. Inspection and rehabilitation programs are being implemented to monitor and maintain deteriorated bridge infrastructure. This paper highlights the state-of-the art of current practices being performed for concrete bridge inspection. The information is gathered from the literature and through a distributed questionnaire. The current practices in concrete bridge inspection rely on the use of hummer sounding and chain dragging tests. Non-Destructive Testing (NDT) techniques are not being utilized fully in the process. Nonetheless, they are being partially utilized by the recommendation of the bridge inspector after conducting the visual inspection. Lanes are usually closed during the performance of visual inspection and bridge inspection in general.

Keywords: bridge inspection, condition assessment, questionnaire, non-destructive testing

Procedia PDF Downloads 280

Authors: Shinen B., Bavor J., Dorjkhand B., Suvd B., Maitsetseg B.

Abstract:

A number of remediation techniques are available for the treatment of soils and sediments contaminated by heavy metals. However, some of these techniques are expensive and environmentally disruptive. Nanomaterials are used in the environment as environmental catalysts to convert toxic substances from water, soil, and sediment into environmentally benign compounds. This study was carried out to scrutinize the feasibility of vivianite nanoparticles for remediation of soils contaminated with heavy metals. Column experiments were performed in the laboratory to examine nanoparticle sequestration of metal in soil amended with vivianite nanoparticle suspension. The effect of environmental parameters such as temperature, pH and redox potential on metal leachability and bioavailability of soil amended with nanoparticle suspension was examined and compared with non-amended soils. The vivianite was effective in reducing the leachability of metals in soils. It is suggested that vivianite nanoparticles could be applied for the remediation of contaminated sites polluted by heavy metals due to mining activities, particularly in Mongolia, where mining industries have been developing rapidly in the last decade.

Keywords: bioavailability, heavy metals, nanoparticles, remediation

Procedia PDF Downloads 191

Authors: Ibrahim Watad, Ibrahim Abdulhalim

Abstract:

Conventional spectroscopic surface plasmon resonance (SPR) sensors are widely used, both in fundamental research and environmental monitoring as well as healthcare diagnostics. However, they still lack the low limit of detection (LOD) and there still a place for improvement. SPR conventional sensors are based on the detection of a dip in the reflectivity spectrum which is relatively wide. To improve the performance of these sensors, many techniques and methods proposed either to reduce the width of the dip or to increase the sensitivity. Together with that, profiting from the sharp jump in the phase spectrum under SPR, several works suggested the extraction of the phase of the reflected wave. However, existing phase measurement setups are in general more complicated compared to the conventional setups, require more stability and are very sensitive to external vibrations and noises. In this study, a simple polarimetric technique for phase extraction under SPR is presented, followed by a theoretical error analysis and an experimental verification. The advantages of the proposed technique upon existing techniques will be elaborated, together with conclusions regarding the best polarimetric function, and its corresponding optimal metal layer range of thicknesses to use under the conventional Kretschmann-Raether configuration.

Keywords: plasmonics, polarimetry, thin films, optical sensors

Procedia PDF Downloads 404

Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

Abstract:

River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: cluster analysis, multivariate statistical techniques, river Hindon, water quality

Procedia PDF Downloads 467

Authors: Johana Jaramillo, Robin Kalfat, Dmitriy A. Dikin

Abstract:

The cement production process is one of the major sources of carbon dioxide (CO₂), a potent greenhouse gas. Indeed, as a result of its cement manufacturing process, concrete contributes approximately 8% of global greenhouse gas emissions. In addition to environmental concerns, concrete also has a low tensile and ductility strength, which can lead to cracks. Graphene nanoplatelets (GNPs) have proven to be an eco-friendly solution for improving the mechanical and durability properties of concrete. The current research investigates the effects of preparing concrete enhanced with GNPs by using different wet dispersions techniques and mixing methods on its mechanical properties. Concrete specimens were prepared with 0.00 wt%, 0.10 wt%, 0.20 wt%, 0.30 wt% and wt% GNPs. Compressive and flexural strength of concrete at age 7 days were determined. The results showed that the maximum improvement in mechanical properties was observed when GNPs content was 0.20 wt%. The compressive and flexural were improved by up to 17.5% and 8.6%, respectively. When GNP dispersions were prepared by the combination of a drill and an ultrasonic probe, mechanical properties experienced maximum improvement.

Keywords: concrete, dispersion techniques, graphene nanoplatelets, mechanical properties, mixing methods

Procedia PDF Downloads 124

Authors: Varsha Singh, Shraddha Prajapati, M. B. Kiran

Abstract:

Texture identification is useful in predicting the functionality of a component. Many of the existing texture identification methods are of contact in nature, which limits its measuring speed. These contact measurement techniques use a diamond stylus and the diamond stylus being sharp going to damage the surface under inspection and hence these techniques can be used in statistical sampling. Though these contact methods are very accurate, they do not give complete information for full characterization of surface. In this context, the presented method assumes special significance. The method uses a relatively low cost vision system for image acquisition. Software is developed based on wavelet transform, for analyzing texture images. Specimens are made using different manufacturing process (shaping, grinding, milling etc.) During experimentation, the specimens are illuminated using proper lighting and texture images a capture using CCD camera connected to the vision system. The software installed in the vision system processes these images and subsequently identify the texture of manufacturing processes.

Keywords: diamond stylus, manufacturing process, texture identification, vision system

Procedia PDF Downloads 289

Authors: Gizem Akcan, Erdinc Ozturk

Abstract:

When it is examined as historically, it has caught attention that homosexual people try to behave as heterosexual or come out to have a place in community. Homosexual people have identity confusion during identity development, they have high levels of need for absolute truth and their psychological well being is affected negatively because of high levels of need for absolute truth and they have problems about self concept clarity. People who have problems about self concept clarity have problems on problem solving and show lots of symptoms of stress. People who have clear self concept use healthier coping strategies to solve problems. The purpose of this study is to show whether need for absolute truth predicts problem solving and symptoms of stress via mediator effect of self concept clarity or not on homosexual men. The participants of this study were 200 homosexual men. The ages of participants were 20-50. In addition, Demographic Information Form, Self Concept Clarity Scale, Need for Absolute Truth Scale, Stres Self-Assessment Checklist and Problem Solving Inventory were applied to the participants. The assessment of the data was made with confirmatory factor analysis and structural equation modeling analysis. According to the results of this study, need for absolute truth predicts problem solving and symptoms of stress via mediator effect of self concept clarity on homosexual men.

Keywords: need for absolute truth, self concept clarity, symptoms of stress, problem solving

Procedia PDF Downloads 224

Authors: Juan David Sepulveda

Abstract:

This article reflects the current stage of progress in the project “Determining technological trends in energy generation”. At first it was oriented towards finding out those trends by employing such tools as the scientometrics community had proved and accepted as effective for getting reliable results. Because a documented methodological guide for this purpose could not be found, the decision was made to reorient the scope and aim of this project, changing the degree of interest in pursuing the objectives. Therefore it was decided to propose and implement a novel guide from the elements and techniques found in the available literature. This article begins by explaining the elements and considerations taken into account when implementing and applying this methodology, and the tools that led to the implementation of a software application for patent revision. Univariate analysis helped recognize the technological leaders in the field of energy, and steered the way for a multivariate analysis of this sample, which allowed for a graphical description of the techniques of mature technologies, as well as the detection of emerging technologies. This article ends with a validation of the methodology as applied to the case of fuel cells.

Keywords: energy, technology mapping, patents, univariate analysis

Procedia PDF Downloads 476

Authors: Fatema Akram, Mohammad Golam Rasul, Mohammad Masud Kamal Khan, Md. Sharif Imam Ibne Amir

Abstract:

A variety of routing techniques are available to develop surface runoff hydrographs from rainfall. The selection of runoff routing method is very vital as it is directly related to the type of watershed and the required degree of accuracy. There are different modelling softwares available to explore the rainfall-runoff process in urban areas. XPSTORM, a link-node based, integrated storm-water modelling software, has been used in this study for developing surface runoff hydrograph for a Golf course area located in Rockhampton in Central Queensland in Australia. Four commonly used methods, namely SWMM runoff, Kinematic wave, Laurenson, and Time-Area are employed to generate runoff hydrograph for design storm of this study area. In runoff mode of XPSTORM, the rainfall, infiltration, evaporation and depression storage for sub-catchments were simulated and the runoff from the sub-catchment to collection node was calculated. The simulation results are presented, discussed and compared. The total surface runoff generated by SWMM runoff, Kinematic wave and Time-Area methods are found to be reasonably close, which indicates any of these methods can be used for developing runoff hydrograph of the study area. Laurenson method produces a comparatively less amount of surface runoff, however, it creates highest peak of surface runoff among all which may be suitable for hilly region. Although the Laurenson hydrograph technique is widely acceptable surface runoff routing technique in Queensland (Australia), extensive investigation is recommended with detailed topographic and hydrologic data in order to assess its suitability for use in the case study area.

Keywords: ARI, design storm, IFD, rainfall temporal pattern, routing techniques, surface runoff, XPSTORM

Procedia PDF Downloads 453

Authors: Muhammad Aown Sammar Raza, Salman Ahmad, Muhammad Farrukh Saleem, Muhammad Saqlain Zaheer, Rashid Iqbal, Imran Haider, Muhammad Usman Aslam, Muhammad Adnan Nazar

Abstract:

One of the main negative effects of climate change is the increasing scarcity of water worldwide, especially for irrigation purpose. In order to ensure food security with less available water, there is a need to adopt easy and economic techniques. Two of the effective techniques are; use of ground covers and partial root zone drying (PRD). A field experiment was arranged to find out the most suitable mulch for PRD irrigation system in wheat. The experiment was comprised of two irrigation methods (I0 = irrigation on both sides of roots and I1= irrigation to only one side of the root as alternate irrigation) and four ground covers (M0= open ground without any cover, M1= black plastic cover, M2= wheat straw cover and M4= cotton sticks cover). More plant height, spike length, number of spikelets and number of grains were found in full irrigation treatment. While water use efficiency and grain nutrient (NPK) contents were more in PRD irrigation. All soil covers suppress the weeds and significantly influenced the yield attributes, final yield as well as the grain nutrient contents. However black plastic cover performed the best. It was concluded that joint use of both techniques was more effective for water conservation and increasing grain yield than their sole application and combination of PRD with black plastic mulch performed the best than other ground covers combination used in the experiment.

Keywords: ground covers, partial root zone drying, grain yield, quality traits, WUE, weed control efficiency

Procedia PDF Downloads 249

Authors: Khalid A. Al-Afandy, El-Sayyed El-Rabaie, Osama Salah, Ahmed El-Mhalaway

Abstract:

This paper presents a high secure data hiding technique using image cropping and Least Significant Bit (LSB) steganography. The predefined certain secret coordinate crops will be extracted from the cover image. The secret text message will be divided into sections. These sections quantity is equal the image crops quantity. Each section from the secret text message will embed into an image crop with a secret sequence using LSB technique. The embedding is done using the cover image color channels. Stego image is given by reassembling the image and the stego crops. The results of the technique will be compared to the other state of art techniques. Evaluation is based on visualization to detect any degradation of stego image, the difficulty of extracting the embedded data by any unauthorized viewer, Peak Signal-to-Noise Ratio of stego image (PSNR), and the embedding algorithm CPU time. Experimental results ensure that the proposed technique is more secure compared with the other traditional techniques.

Keywords: steganography, stego, LSB, crop

Procedia PDF Downloads 269

Authors: Nermeen Elbeltagy, Sara Hassan, Tamer Hosny, Mostafa Abdelaziz

Abstract:

Introduction: Adequate postoperative analgesia after caesarean section (CS) is crucial as it impacts the distinct surgical recovery needs of the parturient. Over recent years, there has been increased interest in regional nerve block techniques with promising results on efficacy. These techniques reduce the need for additional analgesia, thereby lowering the incidence of drug-related side effects. As postoperative pain after cesarean is mainly due to abdominal incision, the transverses abdomenis plane ( TAP ) block is a relatively new abdominal nerve block with excellent efficacy after different abdominal surgeries, including cesarean section. Objective: The main objective is to compare ultrasound-guided TAP block provided by the anesthesiologist with TAP provided by the surgeon through a caesarean incision regarding the duration of postoperative analgesia, intensity of analgesia, timing of mobilization, and easiness of the procedure. Method: Ninety pregnant females at term who were scheduled for delivery by elective cesarean section were randomly distributed into two groups. The first group (45) received spinal anesthesia and postoperative ultrasound guided TAP block using 20ml on each side of 0.25% bupivacaine which was provided by the anesthesiologist. The second group (45) received spinal anesthesia plus a TAP block using 20ml on each side of 0.25% bupivacaine, which was provided by the surgeon through the cesarean incision. Visual Analogue Scale (VAS) was used for the comparison between the two groups. Results: VAS score after four hours was higher among the TAP block group provided by the surgeon through the surgical incision than the postoperative analgesic profile using ultrasound-guided TAP block provided by the anesthesiologist (P=0.011). On the contrary, there was no statistical difference in the patient’s dose of analgesia after four hours of the TAP block (P=0.228). Conclusion: TAP block provided through the surgical incision is safe and enhances early patient’s mobilization.

Keywords: TAP block, CS, VAS, analgesia

Procedia PDF Downloads 49

Authors: R. Maher, D. Marchant, F. Fazel

Abstract:

The initial aim of the study was to capitalize on the depth of athletes’ and coaches’ knowledge pertaining to the phenomenon of choking in basketball, free-throw shooting in particular, from an ‘insiders’ perspective. The findings of this study have developed a deeper understanding of how basketball players and coaches deal with choking and potentially contribute new knowledge relevant to designing useful interventions for alleviating choking. A key element was thus, knowledge, transfer, and exchange (KTE). KTE is the process of acquiring, developing, sharing and applying knowledge. Semi-structured interviews were conducted employing a composed sample of eight elite basketball players and four elite coaches who have been experiencing the choking episode previously. All interviews have been digitally recorded and later transcribed verbatim. Then the interviews have been content analyzed. Participants of the present study have provided useful information regarding the underlying mechanisms and antecedents of choking and also suggested applicable antidotes to conquer the phenomenon of choking. According to the results of the present study, self-confidence, mental and physical preparation, and coping styles should be considered as influential factors in athletes’ performance under pressure. Moreover, using all noteworthy information and preventative strategies suggested by participants of the present study, an effective multi-modal intervention has been introduced that should be taken into account by sports psychologists, coaches and athletes.

Keywords: anxiety, basketball, choking, free-throw shooting, psychological intervention

Procedia PDF Downloads 262

Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

Abstract:

Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

Procedia PDF Downloads 72

Authors: Merry Pearl Rupinta, Rivika Alda

Abstract:

Inclusive education provides the same opportunity for all students regardless of the difficulties they encounter. Teaching English to learners with special education needs (LSENs) is a significant factor for learners to cope with the academic demands in the regular class. However, these special education (SPED) teachers lack specialized training to teach specific skills in English. Using purposive sampling, this study explored the lived experience of nine SPED teachers handling English to learners with intellectual disabilities from the four divisions of Region 10. An interview schedule, validated by experts, was used in conducting the investigation, where a semi-structured one-on-one interview was employed. The data were analyzed using Smith's (2009) five-step data analysis. The study highlighted themes on challenges in teaching English, coping strategies, adjusted classroom management, and inclusivity. The results suggest that SPED teachers' experience teaching English is a continuous and indefinite loop that continues until the primary goal of mainstreaming LSENs into the regular class is achieved. This study recommends that policymakers and curriculum developers focus their efforts on professional development through a series of training on various strategies and approaches in teaching English that can help SPED teachers provide a more effective and efficient teaching-learning experience.

Keywords: English language teaching, inclusive education, intellectual disability, special education

Procedia PDF Downloads 28

Authors: Mohd Ridzwan Yaakub, Muhammad Iqbal Abu Latiffi

Abstract:

Online business has become popular recently due to the massive amount of information and medium available on the Internet. This has resulted in the huge number of reviews where the consumers share their opinion, criticisms, and satisfaction on the products they have purchased on the websites or the social media such as Facebook and Twitter. However, to analyze customer’s behavior has become very important for organizations to find new market trends and insights. The reviews from the websites or the social media are in structured and unstructured data that need a sentiment analysis approach in analyzing customer’s review. In this article, techniques used in will be defined. Definition of the ontology and description of its possible usage in sentiment analysis will be defined. It will lead to empirical research that related to mobile phones used in research and the ontology used in the experiment. The researcher also will explore the role of preprocessing data and feature selection methodology. As the result, ontology-based approach in sentiment analysis can help in achieving high accuracy for the classification task.

Keywords: feature selection, ontology, opinion, preprocessing data, sentiment analysis

Procedia PDF Downloads 200

Authors: Elmahdi Elgharbaoui, Tamou Nasser, Ahmed Essadki

Abstract:

In the era of sustainable development, photovoltaic (PV) technology has shown significant potential as a renewable energy source. Photovoltaic generators (GPV) have a non-linear current-voltage characteristic, with a maximum power point (MPP) characterized by an optimal voltage, and depends on environmental factors such as temperature and irradiation. To extract each time the maximum power available at the terminals of the GPV and transfer it to the load, an adaptation stage is used, consisting of a boost chopper controlled by a maximum power point tracking technique (MPPT) through a stage of pulse width modulation (PWM). Our choice has focused on three techniques which are: the perturbation and observation method (P&O), the incremental conductance method (InCond) and the last is that of control using the fuzzy logic. The implementation and simulation of the system (photovoltaic generator, chopper boost, PWM and MPPT techniques) are then performed in the Matlab/Simulink environment.

Keywords: photovoltaic generator, technique MPPT, boost chopper, PWM, fuzzy logic, P&O, InCond

Procedia PDF Downloads 323

Authors: Saima Noreen, Malcolm D. MacLeod

Abstract:

Different types of forgiveness (emotional and decisional) have been shown to have differential effects on incidental forgetting of information related to a prior transgression. The present study explored the extent to which emotional and decisional forgiveness also influenced intentional forgetting; that is, the extent to which forgetting occurs following an explicit instruction to forget. Using the List-Method Directed Forgetting (LMDF) paradigm, 236 participants were presented with a hypothetical transgression and then assigned to an emotional forgiveness, a decisional forgiveness, or a no-forgiveness manipulation. Participants were then presented with two-word lists each comprising transgression-relevant and transgression-irrelevant words. Following the presentation of the first list, participants were told to either remember or forget the previously learned list of words. Participants in the emotional forgiveness condition were found to remember fewer relevant and more irrelevant transgression-related words, while the opposite was true for both decisional forgiveness and no-forgiveness conditions. Furthermore, when directed to forget words in List 1, participants in the decisional and no-forgiveness conditions were less able to forget relevant transgression-related words in comparison to participants in the emotional forgiveness condition. This study suggests that emotional forgiveness plays a pivotal role in the intentional forgetting of transgression-related information. The potential implications of these findings for coping with unpleasant incidents will be considered.

Keywords: decisional forgiveness, directed forgetting, emotional forgiveness, executive control, forgiveness

Procedia PDF Downloads 234

Authors: Ammarah Irum, Muhammad Ali Tahir

Abstract:

Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

Procedia PDF Downloads 72

Authors: Rupali Bhatia, Deepthi Nair, Geetika Khanna, Seema Singhal

Abstract:

Introduction: Genital tract tuberculosis is a chronic disease (caused by reactivation of organisms from systemic distribution of Mycobacterium tuberculosis) that often presents with low grade symptoms and non-specific complaints. Patients with genital tuberculosis are usually young women seeking workup and treatment for infertility. Infertility is the commonest presentation due to involvement of the fallopian tubes, endometrium and ovarian damage with poor ovarian volume and reserve. The diagnosis of genital tuberculosis is difficult because of the fact that it is a silent invader of genital tract. Since tissue cannot be obtained from fallopian tubes, the diagnosis is made by isolation of bacilli from endometrial tissue obtained by endometrial biopsy curettage and/or aspiration. Problems are associated with sampling technique as well as diagnostic modality due to lack of adequate sample volumes and the segregation of the sample for various diagnostic tests resulting in non-uniform distribution of microorganisms. Moreover, lack of an efficient sampling technique universally applicable for all specific diagnostic tests contributes to the diagnostic challenges. Endometrial sampling plays a key role in accurate diagnosis of female genital tuberculosis. It may be done by 2 methods viz. endometrial curettage and endometrial aspiration. Both endometrial curettage and aspirate have their own limitations as curettage picks up strip of the endometrium from one of the walls of the uterine cavity including tubal osteal areas whereas aspirate obtains total tissue with exfoliated cells present in the secretory fluid of the endometrial cavity. Further, sparse and uneven distribution of the bacilli remains a major factor contributing to the limitations of the techniques. The sample that is obtained by either technique is subjected to histopathological examination, AFB staining, culture and PCR. Aim: Comparison of the sampling techniques viz. endometrial biopsy curettage and endometrial aspiration using different laboratory methods of histopathology, cytology, microbiology and molecular biology. Method: In a hospital based observational study, 75 Indian females suspected of genital tuberculosis were selected on the basis of inclusion criteria. The women underwent endometrial tissue sampling using Novaks biopsy curette and Karmans cannula. One part of the specimen obtained was sent in formalin solution for histopathological testing and another part was sent in normal saline for acid fast bacilli smear, culture and polymerase chain reaction. The results so obtained were correlated using coefficient of correlation and chi square test. Result: Concordance of results showed moderate agreement between both the sampling techniques. Among HPE, AFB and PCR, maximum sensitivity was observed for PCR, though the specificity was not as high as other techniques. Conclusion: Statistically no significant difference was observed between the results obtained by the two sampling techniques. Therefore, one may use either EA or EB to obtain endometrial samples and avoid multiple sampling as both the techniques are equally efficient in diagnosing genital tuberculosis by HPE, AFB, culture or PCR.

Keywords: acid fast bacilli (AFB), histopatholgy examination (HPE), polymerase chain reaction (PCR), endometrial biopsy curettage

Procedia PDF Downloads 327

Authors: Chijindu Okpalaoka, Charles Chinedu Onuselogu

Abstract:

COVID-19, humanity's coronavirus disease caused by SARS-CoV-2, was first detected in late 2019 in Wuhan, China. COVID-19 lacked an established conventional pharmaceutical therapy, and as a result, the outbreak quickly became an epidemic affecting the entire World. Only a qPCR assay is reliable for diagnosing COVID-19. Clustered, regularly interspaced short palindromic repeats (CRISPR) technology is being researched for speedy and specific identification of COVID-19, among other therapeutic techniques. Apart from its therapeutic capabilities, the CRISPR technique is being evaluated to develop antiviral therapies; nevertheless, no CRISPR-based medication has been approved for human use to date. Prophylactic antiviral CRISPR in living being cells, a Cas 13-based approach against coronavirus, has been developed. While this method can be evolved into a treatment approach, it may face substantial obstacles in human clinical trials for licensure. This study discussed the potential applications of CRISPR-based techniques for developing a speedy and accurate feasible treatment alternative for the COVID-19 virus.

Keywords: COVID-19, CRISPR technique, Cas13, SARS-CoV-2, prophylactic antiviral

Procedia PDF Downloads 130

Authors: Sudha T., Naveen C.

Abstract:

Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

Procedia PDF Downloads 65

Authors: Hadjer Chellia

Abstract:

In the light of the recent global pandemic, different issues in educational research seem to invite careful considerations. Following this perspective, this study sets out to question the concept of classroom management in an EFL higher education context during Covid-19. In order to gain an in-depth understanding of their experiences, 6 EFL teachers from different Algerian universities took part in semi-structured interviews. The main emerging themes revealed that EFL teachers have different pedagogical practices in relation to classroom management during the global crisis than those of normal times. In relation to flexible education theory, the teachers’ experiences suggest flexible classroom management during Covid-19; flexibility in the teaching methods, approach and design, flexibility in time, flexibility in space and pace (speed), flexibility in assessment modes and flexibility in coping with students’ well-being. The flexibility awareness helps them to develop readiness towards the future, mainly in terms of maintaining an appropriate pedagogy to face the future crisis. In terms of theoretical concepts, working on classroom management under unusual circumstances in relation to flexible education helped come out with the concept of flexible classroom management (FCM) and virtual classroom management (VCM). It is then important for educators and researchers to rethink different pedagogical concepts and mind a careful application in the case of unusual times.

Keywords: Covid-19, EFL educators, flexible classroom management, flexible education, virtual classroom management

Procedia PDF Downloads 163

Authors: Rose Mini Agoes Salim, Shahnaz Safitri

Abstract:

The aim of this study is to test the effectiveness of teaching kindness in preschool children by using several techniques. Kindness is a physical act or emotional support aimed to build or maintain relationships with others. Kindness is known to be essential in the development of moral reasoning to distinguish between the good and bad things. In this study, kindness is operationalized as several acts including helping friends, comforting sad friends, inviting friends to play, protecting others, sharing, saying hello, saying thank you, encouraging others, and apologizing. It is mentioned that kindness is crucial to be developed in preschool children because this is the time the children begin to interact with their social environment through play. Furthermore, preschool children's cognitive development makes them begin to represent the world with words, which then allows them to interact with others. On the other hand, preschool children egocentric thinking makes them still need to learn to consider another person's perspective. In relation to social interaction, preschool children need to be stimulated and assisted by adult to be able to pay attention to other and act with kindness toward them. On teaching kindness to children, the quality of interaction between children and their significant others is the key factor. It is known that preschool children learn about kindness by imitating adults on their two way interaction. Specifically, this study examines two types of teaching techniques that can be done by parents as a way to teach kindness, namely the picture-storybook reading and hand-puppet storytelling. These techniques were examined because both activities are easy to do and both also provide a model of behavior for the child based on the character in the story. To specifically examine those techniques effectiveness in teaching kindness, two studies were conducted. Study I involves 31 children aged 5-6 years old with picture-storybook reading technique, where the intervention is done by reading 8 picture books for 8 days. In study II, hand-puppet storytelling technique is examined to 32 children aged 3-5 years old. The treatments effectiveness are measured using an instrument in the form of nine colored cards that describe the behavior of kindness. Data analysis using Wilcoxon Signed-rank test shows a significant difference on the average score of kindness (p < 0.05) before and after the intervention has been held. For daily observation, a ‘kindness tree’ and observation sheets are used which are filled out by the teacher. Two weeks after interventions, an improvement on all kindness behaviors measured is intact. The same result is also gained from both ‘kindness tree’ and observational sheets.

Keywords: kindness, moral teaching, storytelling, hand puppet

Procedia PDF Downloads 252

Authors: Khunsa Fatima, Umar K. Khattak, Allah Bakhsh Kausar

Abstract:

Satellite images interpretation and analysis assist geologists by providing valuable information about geology and minerals of an area to be surveyed. A test site in Fatejang of district Attock has been studied using Landsat ETM+ and ASTER satellite images for lithological mapping. Five different supervised image classification techniques namely maximum likelihood, parallelepiped, minimum distance to mean, mahalanobis distance and spectral angle mapper have been performed on both satellite data images to find out the suitable classification technique for lithological mapping in the study area. Results of these five image classification techniques were compared with the geological map produced by Geological Survey of Pakistan. The result of maximum likelihood classification technique applied on ASTER satellite image has the highest correlation of 0.66 with the geological map. Field observations and XRD spectra of field samples also verified the results. A lithological map was then prepared based on the maximum likelihood classification of ASTER satellite image.

Keywords: ASTER, Landsat-ETM+, satellite, image classification

Procedia PDF Downloads 394

Authors: A. A. Adekunle, A. M. Omoare, W. O. Oyediran

Abstract:

This study was carried out to assess rural women’s skill acquisition in the processing of locust bean in Ipokia Local Government Area of Ogun State, Nigeria. Simple random sampling technique was used to select 90 women locust bean processors for this study. Data were analyzed with descriptive statistics and Pearson Product Moment Correlation. The result showed that the mean age of respondents was 40.72 years. Most (70.00%) of the respondents were married. The mean processing experience was 8.63 years. 93.30% of the respondents relied on information from fellow locust beans processors and friends. All (100%) the respondents did not acquire improved processing skill through trainings and workshops. It can be concluded that the rural women’s skill acquisition on modernized processing techniques was generally low. It is hereby recommend that the rural women processors should be trained by extension service providers through series of workshops and seminars on improved processing techniques.

Keywords: locust bean, processing, skill acquisition, rural women

Procedia PDF Downloads 461

Authors: Yuhanis Yusof, Zuriani Mustaffa, Siti Sakira Kamaruddin

Abstract:

Data mining is a fundamental technique in identifying patterns from large data sets. The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical. Prior to that, data are consolidated so that the resulting mining process may be more efficient. This study investigates the effect of different data normalization techniques, which are Min-max, Z-score, and decimal scaling, on Swarm-based forecasting models. Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC). Forecasting models are later developed to predict the daily spot price of crude oil and gasoline. Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max. Nevertheless, the GWO is more superior that ABC as its model generates the highest accuracy for both crude oil and gasoline price. Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.

Keywords: artificial bee colony, data normalization, forecasting, Grey Wolf optimizer

Procedia PDF Downloads 476