Search results for: forest fire detection

Authors: Sirajdin Olagoke Adeshina, Haidi Ibrahim, Akeem Salawu

Abstract:

large lecture theatres cannot be covered by a single camera but rather by a multicamera setup because of their size, shape, and seating arrangements. Although, classroom capture is achievable through a single camera. Therefore, a design and implementation of a multicamera setup for a large lecture hall were considered. Researchers have shown emphasis on the impact of class attendance taken on the academic performance of students. However, the traditional method of carrying out this exercise is below standard, especially for large lecture theatres, because of the student population, the time required, sophistication, exhaustiveness, and manipulative influence. An automated large classroom attendance system is, therefore, imperative. The common approach in this system is face detection and recognition, where known student faces are captured and stored for recognition purposes. This approach will require constant face database updates due to constant changes in the facial features. Alternatively, face counting can be performed by cropping the localized faces on the video or image into a folder and then count them. This research aims to develop a face localization-based approach to detect student faces in classroom images captured using a multicamera setup. A selected Haar-like feature cascade face detector trained with an asymmetric goal to minimize the False Rejection Rate (FRR) relative to the False Acceptance Rate (FAR) was applied on Raspberry Pi 4B. A relationship between the two factors (FRR and FAR) was established using a constant (λ) as a trade-off between the two factors for automatic adjustment during training. An evaluation of the proposed approach and the conventional AdaBoost on classroom datasets shows an improvement of 8% TPR (output result of low FRR) and 7% minimization of the FRR. The average learning speed of the proposed approach was improved with 1.19s execution time per image compared to 2.38s of the improved AdaBoost. Consequently, the proposed approach achieved 97% TPR with an overhead constraint time of 22.9s compared to 46.7s of the improved Adaboost when evaluated on images obtained from a large lecture hall (DK5) USM.

Keywords: automatic attendance, face detection, haar-like cascade, manual attendance

Procedia PDF Downloads 73

Authors: Reggie Chandra

Abstract:

Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

Procedia PDF Downloads 172

Authors: Shaik Asha Begum, S. Joshna Rani, Shaik Abdul Rahaman

Abstract:

INTRODUCTION: Breast cancer is a disease that creates in breast cells. "KAP" study estimates the Knowledge, Attitude, and Practices of a local area. More than 1.5 million ladies (25% of all ladies with malignancy) are determined to have bosom disease consistently all through the world. Understanding the degrees of Knowledge, Attitude and Practice will empower a more effective cycle of mindfulness creation as it will permit the program to be custom-made all the more properly to the necessities of the local area. OBJECTIVES: The objective of this study is to assess the knowledge on signs and symptoms, risk factors, provide awareness on the practicing of the early detection techniques of breast cancer and provide knowledge on the overall breast cancer including preventive techniques. METHODOLOGY: This is an expressive cross-sectional investigation. This investigation of KAP was done in the Nirmala Educational Institutions from January to April 2021. A total of 300 participants are included from women students in pharmacy graduates & lecturers, and also from graduates other than the pharmacy. The examiners are taken from the BCAM (Breast Cancer Awareness Measure), tool compartment (Version 2). RESULT: According to the findings of the study, the majority of the participants were not well informed about breast cancer. A lump in the breast was the most commonly mentioned sign of breast cancer, followed by pain in the breast or nipple. The percentage of knowledge related to the breast cancer risk factors was also very less. The correct answers for breast cancer risk factors were radiation exposure (58.20 percent), a positive family history (47.6 percent), obesity (46.9 percent), a lack of physical activity (43.6 percent), and smoking (43.2 percent). Breast cancer screening, on the other hand, was uncommon (only 30 and 11.3 percent practiced clinical breast examination and mammography respectively). CONCLUSION: In this study, the knowledge on the signs and symptoms, risk factors of breast cancer - pharmacy graduates have more knowledge than the non-pharmacy graduates but in the preventive techniques and early detective tools of breast cancer -had poor knowledge in the pharmacy and non-pharmacy graduate. After the awareness program, pharmacy and non-pharmacy graduates got supportive knowledge on the preventive techniques and also practiced the early detective techniques of breast cancer.

Keywords: breast cancer, mammography, KAP study, early detection

Procedia PDF Downloads 138

Authors: Sangseung Kang, Kyekyung Kim, Suyoung Chi

Abstract:

A good posture is the most important factor in riding. In this paper, we present an effective posture correction system for a riding simulator environment to provide position error detection and customized training functions. The proposed system detects and analyzes the rider's posture using depth data and inertial sensing data. Our experiments show that including these functions will help users improve their seat for a riding.

Keywords: posture correction, posture training, riding posture, riding simulator

Procedia PDF Downloads 477

Authors: Helena M. Wilhelm, Paulo O. Fernandes, Laís P. Dill, Kethlyn G. Moscon

Abstract:

The use of vegetable oil (or natural ester) as an insulating fluid in electrical transformers is a trend that aims to contribute to environmental preservation since it is biodegradable and non-toxic. Besides, vegetable oil has high flash and combustion points, being considered a fire safety fluid. However, vegetable oil is usually less stable towards oxidation than mineral oil. Both insulating fluids, mineral and vegetable oils, need to be tested periodically according to specific standards. Oxidation stability can be determined by the induction period measured by conductivity method (Rancimat) by monitoring the effectivity of oil’s antioxidant additives, a methodology already developed for food application and biodiesel but still not standardized for insulating fluids. Besides adequate oxidation stability, fluids must be compatible with transformer's construction materials under normal operating conditions to ensure that damage to the oil and parts of the transformer does not occur. ASTM standard and Brazilian normative differ in parameters evaluated, which reveals the need to regulate tests for each oil type. The aim of this study was to assess oxidation stability and compatibility of vegetable oils to suggest the best way to assure a viable performance of vegetable oil as transformer insulating fluid. The determination of the induction period for several vegetable insulating oils from the local market by using Rancimat was carried out according to BS EN 14112 standard, at different temperatures (110, 120, and 130 °C). Also, the compatibility of vegetable oil was assessed according to ASTM and ABNT NBR standards. The main results showed that the best temperature for use in the Rancimat test is 130 °C, which allows a better observation of conductivity change. The compatibility test results presented differences between vegetable and mineral oil standards that should be taken into account in oil testing since materials compatibility and oxidation stability are essential for equipment reliability.

Keywords: compatibility, Rancimat, natural ester, vegetable oil

Procedia PDF Downloads 212

Authors: Francisca Margarita Ocran

Abstract:

Underwear, and more particularly bras and panties, are defined as intimate clothing. Strictly speaking, they enhance the place of women in the public or private satchel. Therefore, women's lingerie is a complex garment with a high involvement profile, motivating consumers to buy it not only by its functional utility but also by the multisensory experience it provides them. Customer behavior models are generally based on customer data mining, and each model is designed to answer questions at a specific time. Predicting the customer experience is uncertain and difficult. Thus, knowledge of consumers' tastes in lingerie deserves to be treated as an experiential product, where the dimensions of the experience motivating consumers to buy a lingerie product and to remain faithful to it must be analyzed in detail by the manufacturers and retailers to engage and retain consumers, which is why this research aims to identify the variables that push consumers to choose their lingerie product, based on an in-depth analysis of the types of fabrics used to make lingerie. The data used in this study comes from online purchases. Machine learning approach with the use of Python programming language and Pycaret gives us a precision of 86.34%, 85.98%, and 84.55% for the three algorithms to use concerning the preference of a buyer in front of a range of lingerie. Gradient Boosting, random forest, and K Neighbors were used in this study; they are very promising and rich in the classification of preference in the textile industry.

Keywords: consumer behavior, data mining, lingerie, machine learning, preference

Procedia PDF Downloads 92

Authors: J. Zekri, N. Souilah, W. Abdelaziz, D. Alatou

Abstract:

Our study shall focus on the ability of trees cork oak that showed vis-à-vis sensitivity to climate change, including late spring frosts. The combination of these factors resulted in damage alarmed, therefore forest ecosystems weakened trees that can affect their ability to support other abiotic and biotic stresses, For this we tested its tolerance to thermal variations and cold weather conditions by estimating some stress markers (quantification of proteins, RNA, soluble sugars) that are quantified to evaluate the cold tolerance of seedlings. Sowing of cork oak (Quercus suber L.) is grown in controlled conditions at 25° C ± 2° C in long days 16h. These seedlings are transferred at low temperatures between 5° C and -6° C for a period of 3 hours. Biochemical analyzes were performed in the various organs of the cork oak seedlings. Cool temperatures induced a significant accumulation of proline in different organs of seedlings and the optimum concentrations were observed in the roots with very high concentrations (4 times larger than those of the control). The accumulation of soluble sugars is significantly in stems and roots at 0° C. Protein concentrations are very high in leaves of both growth and high waves in rod at -4° C to -2° C. Tolerance cork oak seems to be at the thermal limit of -2°C. The concentration of these metabolites in the various organs showed the ability oak cork hardening during the winter.

Keywords: climate change, thermal change, semi-aride, biochemical markers, heat stress

Procedia PDF Downloads 250

Authors: Idowu Olugbenga Adewumi, Foluke Iyabo Oluwatoyinbo

Abstract:

Presently, there are several discussions on the food security with increase in yield of arable crop throughout the world. This article, briefly present research efforts to create digital interfaces to nature, in particular to area of crop production in agriculture with increase in yield with interest on pervasive computing. The approach goes beyond the use of sensor networks for environmental monitoring but also by emphasizing the development of a system architecture that detect intruder (Intrusion Process) which reduce the yield of the farmer at the end of the planting/harvesting period. The objective of the work is to set a model for setting up the hand held or portable device for increasing the quality and quantity of arable crop. This process incorporates the use of infrared motion image sensor with security alarm system which can send a noise signal to intruder on the farm. This model of the portable image sensing device in monitoring or scaring human, rodent, birds and even pests activities will reduce post harvest loss which will increase the yield on farm. The nano intelligence technology was proposed to combat and minimize intrusion process that usually leads to low quality and quantity of produce from farm. Intranet system will be in place with wireless radio (WLAN), router, server, and client computer system or hand held device e.g PDAs or mobile phone. This approach enables the development of hybrid systems which will be effective as a security measure on farm. Since, precision agriculture has developed with the computerization of agricultural production systems and the networking of computerized control systems. In the intelligent plant production system of controlled greenhouses, information on plant responses, measured by sensors, is used to optimize the system. Further work must be carry out on modeling using pervasive computing environment to solve problems of agriculture, as the use of electronics in agriculture will attracts more youth involvement in the industry.

Keywords: pervasive computing, intrusion detection, precision agriculture, security, arable crop

Procedia PDF Downloads 406

Authors: Hamza Zidoum

Abstract:

This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

Procedia PDF Downloads 379

Authors: Liping Qiu, Xiaofeng Zhang

Abstract:

The ion chromatography method for the rapid determination of four anions (F⁻、Cl⁻、SO₄²⁻、NO₃⁻) in burial ground poles was optimized. The L₉(₃⁴) orthogonal test was used to determine the optimal parameters of sample pretreatment: accurately weigh 2.000g of sample, add 10mL of ultrapure water, and extract for 40min under the conditions of shaking temperature 40℃ and shaking speed 180 r·min-1. The eluent was 25 mmol/L KOH solution, the analytical column was Ion Pac® AS11-SH (250 mm × 4.0 mm), and the purified filtrate was measured by a conductivity detector. Under this method, the detection limit of each ion is 0.066～0.078mg/kg, the relative standard deviation is 0.86%～2.44% (n=7), and the recovery rate is 94.6～101.9.

Keywords: ion chromatography, tomb, anion (F⁻, Cl⁻, SO₄²⁻, NO₃⁻), environmental protection

Procedia PDF Downloads 104

Authors: Jean Pierre Kabue, Emma Meader, Afsatou Ndama Traore, Paul R. Hunter, Natasha Potgieter

Abstract:

Norovirus is now considered the most common cause of outbreaks of nonbacterial gastroenteritis. Limited data are available for Norovirus strains in Africa, especially in rural and peri-urban areas. Despite the excessive burden of diarrhea disease in developing countries, Norovirus infections have been to date mostly reported in developed countries. There is a need to investigate intensively the role of viral agents associated with diarrhea in different settings in Africa continent. To determine the prevalence and genetic diversity of Norovirus strains circulating in the rural communities in the Limpopo Province, South Africa and investigate the genetic relationship between Norovirus strains, a cross-sectional study was performed on human stools collected from rural communities. Between July 2014 and April 2015, outpatient children under 5 years of age from rural communities of Vhembe District, South Africa, were recorded for the study. A total of 303 stool specimens were collected from those with diarrhea (n=253) and without (n=50) diarrhea. NoVs were identified using real-time one-step RT-PCR. Partial Sequence analyses were performed to genotype the strains. Phylogenetic analyses were performed to compare identified NoVs genotypes to the worldwide circulating strains. Norovirus detection rate was 41.1% (104/253) in children with diarrhea. There was no significant difference (OR=1.24; 95% CI 0.66-2.33) in Norovirus detection between symptomatic and asymptomatic children. Comparison of the median CT values for NoV in children with diarrhea and without diarrhea revealed significant statistical difference of estimated GII viral load from both groups, with a much higher viral burden in children with diarrhea. To our knowledge, this is the first study reporting on the differences in estimated viral load of GII and GI NoV positive cases and controls. GII.Pe (n=9) were the predominant genotypes followed by GII.Pe/GII.4 Sydney 2012 (n=8) suspected recombinant and GII.4 Sydney 2012 variants(n=7). Two unassigned GII.4 variants and an unusual RdRp genotype GII.P15 were found. With note, the rare GIIP15 identified in this study has a common ancestor with GIIP15 strain from Japan previously reported as GII/untypeable recombinant strain implicated in a gastroenteritis outbreak. To our knowledge, this is the first report of this unusual genotype in the African continent. Though not confirmed predictive of diarrhea disease in this study, the high detection rate of NoV is an indication of subsequent exposure of children from rural communities to enteric pathogens due to poor sanitation and hygiene practices. The results reveal that the difference between asymptomatic and symptomatic children with NoV may possibly be related to the NoV genogroups involved. The findings emphasize NoV genetic diversity and predominance of GII.Pe/GII.4 Sydney 2012, indicative of increased NoV activity. An uncommon GII.P15 and two unassigned GII.4 variants were also identified from rural settings of the Vhembe District/South Africa. NoV surveillance is required to help to inform investigations into NoV evolution, and to support vaccine development programmes in Africa.

Keywords: asymptomatic, common, outpatients, norovirus genetic diversity, sporadic gastroenteritis, South African rural communities, symptomatic

Procedia PDF Downloads 196

Authors: Gabriela Borilova, Monika Petrakova, Petr Kralik

Abstract:

Nowadays, European producers are increasingly interested in the production of halal meat products. Halal meat has been increasingly appearing in the EU's market network and meat products from European producers are being exported to Islamic countries. Halal criteria are mainly related to the origin of muscle used in production, and also to the way products are obtained and processed. Although the EU has legislatively addressed the question of food authenticity, the circumstances of previous years when products with undeclared horse or poultry meat content appeared on EU markets raised the question of the effectiveness of control mechanisms. Replacement of expensive or not-available types of meat for low-priced meat has been on a global scale for a long time. Likewise, halal products may be contaminated (falsified) by pork or food components obtained from pigs. These components include collagen, offal, pork fat, mechanically separated pork, emulsifier, blood, dried blood, dried blood plasma, gelatin, and others. These substances can influence sensory properties of the meat products - color, aroma, flavor, consistency and texture or they are added for preservation and stabilization. Food manufacturers sometimes access these substances mainly due to their dense availability and low prices. However, the use of these substances is not always declared on the product packaging. Verification of the presence of declared ingredients, including the detection of undeclared ingredients, are among the basic control procedures for determining the authenticity of food. Molecular biology methods, based on DNA analysis, offer rapid and sensitive testing. The PCR method and its modification can be successfully used to identify animal species in single- and multi-ingredient raw and processed foods and qPCR is the first choice for food analysis. Like all PCR-based methods, it is simple to implement and its greatest advantage is the absence of post-PCR visualization by electrophoresis. qPCR allows detection of trace amounts of nucleic acids, and by comparing an unknown sample with a calibration curve, it can also provide information on the absolute quantity of individual components in the sample. Our study addresses a problem that is related to the fact that the molecular biological approach of most of the work associated with the identification and quantification of animal species is based on the construction of specific primers amplifying the selected section of the mitochondrial genome. In addition, the sections amplified in conventional PCR are relatively long (hundreds of bp) and unsuitable for use in qPCR, because in DNA fragmentation, amplification of long target sequences is quite limited. Our study focuses on finding a suitable genomic DNA target and optimizing qPCR to reduce variability and distortion of results, which is necessary for the correct interpretation of quantification results. In halal products, the impact of falsification of meat products by the addition of components derived from pigs is all the greater that it is not just about the economic aspect but above all about the religious and social aspect. This work was supported by the Ministry of Agriculture of the Czech Republic (QJ1530107).

Keywords: food fraud, halal food, pork, qPCR

Procedia PDF Downloads 247

Authors: Eray Ozbek, Ilker Kalkan, S. Oguzhan Akbas, Sabahattin Aykac

Abstract:

The contribution of the infill walls to the overall earthquake response of a structure is limited and this contribution is generally ignored in the analyses. Strengthening of the infill walls through different techniques has been and is being studied extensively in the literature to increase this limited contribution and the ductilities and energy absorption capacities of the infill walls to create non-structural components where the earthquake-induced energy can be absorbed without damaging the bearing components of the structural frame. The present paper summarizes an extensive research project dedicated to investigate the effects of strengthening the brick infill walls of a reinforced concrete (RC) frame on its lateral earthquake response. Perforated steel plates were used in strengthening due to several reasons, including the ductility and high deformation capacity of these plates, the fire resistant, recyclable and non-cancerogenic nature of mild steel, and the ease of installation and removal of the plates to the wall with the help of anchor bolts only. Furthermore, epoxy, which increases the cost and amount of labor of the strengthening process, is not needed in this technique. The individual behavior of the strengthened walls under monotonic diagonal and lateral reversed cyclic loading was investigated within the scope of the study. Upon achieving brilliant results, RC frames with strengthened infill walls were tested and are being tested to examine the influence of this strengthening technique on the overall behavior of the RC frames. Tests on the wall and frame specimens indicated that the perforated steel plates contribute to the lateral strength, rigidity, ductility and energy absorption capacity of the wall and the infilled frame to a major extent.

Keywords: infill wall, strengthening, external plate, earthquake behavior

Procedia PDF Downloads 451

Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

Abstract:

Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

Procedia PDF Downloads 75

Authors: Victoria L. Chester, Usha Kuruganti

Abstract:

The forest industry is a major economic sector of Canada and also one of the most dangerous industries for workers. The use of mechanized mobile forestry harvesting machines has successfully reduced the incidence of injuries in forest workers related to manual labor. However, these machines have also created additional concerns, including a high machine operation learning curve, increased the length of the workday, repetitive strain injury, cognitive load, physical and mental fatigue, and increased postural loads due to sitting in a confined space. It is critical to obtain objective performance data for employers to develop appropriate work practices for this industry, however ergonomic field studies of this industry are lacking mainly due to the difficulties in obtaining comprehensive data while operators are cutting trees in the woods. The purpose of this study was to establish a measurement and experimental protocol to examine the effects of worker skill level and movement training speed (joystick crane speed) on harvesting performance using a forestry simulator. A custom wrist angle measurement device was developed as part of the study to monitor Euler angles during operation of the simulator. The device of the system consisted of two accelerometers, a Bluetooth module, three 3V coin cells, a microcontroller, a voltage regulator and an application software. Harvesting performance and crane data was provided by the simulator software and included tree to frame collisions, crane to tree collisions, boom tip distance, number of trees cut, etc. A pilot study of 3 operators with various skill levels was tested to identify factors that distinguish highly skilled operators from novice or intermediate operators. Dependent variables such as reaction time, math skill, past work experience, training movement speed (e.g. joystick control speeds), harvesting experience level, muscle activity, and wrist biomechanics were measured and analyzed. A 10-channel wireless surface EMG system was used to monitor the amplitude and mean frequency of 10 upper extremity muscles during pre and postperformance on the forestry harvest stimulator. The results of the pilot study showed inconsistent changes in median frequency pre-and postoperation, but there was the increase in the activity of the flexor carpi radialis, anterior deltoid and upper trapezius of both arms. The wrist sensor results indicated that wrist supination and pronation occurred more than flexion and extension with radial-ulnar rotation demonstrating the least movement. Overall, wrist angular motion increased as the crane speed increased from slow to fast. Further data collection is needed and will help industry partners determine those factors that separate skill levels of operators, identify optimal training speeds, and determine the length of training required to bring new operators to an efficient skill level effectively. In addition to effective and employment training programs, results of this work will be used for selective employee recruitment strategies to improve employee retention after training. Further, improved training procedures and knowledge of the physical and mental demands on workers will lead to highly trained and efficient personnel, reduced risk of injury, and optimal work protocols.

Keywords: EMG, forestry, human factors, wrist biomechanics

Procedia PDF Downloads 148

Authors: Ali Ghorbanipour

Abstract:

The aim of this study is to investigate the drug resistance pattern and the value of the MIC (minimum inhibitory concentration)method to reduce the impact of infectious diseases and the slow development of resistance. Method: The study was conducted on clinical specimens collected between 2018 to 2021. identification of isolates and antibiotic susceptibility testing were performed using conventional biochemical tests. Antibiotic resistance was determined using kibry-Bauer disk diffusion and MIC by E-test methods comparative with microdilution plate elisa method. Results were interpreted according to CLSI. Results: Out of 249600 different clinical specimens, 18720 different pathogenic bacteria by overall detection ratio 7.7% were detected. Among pathogen bacterial were Gram negative bacteria (70%,n=13000) and Gram positive bacteria(30%,n=5720).Medically relevant gram-negative bacteria include a multitude of species such as E.coli , Klebsiella .spp , Pseudomonas .aeroginosa , Acinetobacter .spp , Enterobacterspp ,and gram positive bacteria Staphylococcus.spp , Enterococcus .spp , Streptococcus .spp was isolated . Conclusion: Our results highlighted that the resistance ratio among Gram Negative bacteria and Gram positive bacteria with different infection is high it suggest constant screening and follow-up programs for the detection of antibiotic resistance and the value of MIC drug susceptibility reporting that provide a new way to the usage of resistant antibiotic in combination with other antibiotics or accurate weight of antibiotics that inhibit or kill bacteria. Evaluation of wrong medication in the expansion of resistance and side effects of over usage antibiotics are goals. Ali ghorbanipour presently working as a supervision at the microbiology department of Massoud medical laboratory. Iran. Earlier, he worked as head department of pulmonary infection in firoozgarhospital, Iran. He received master degree in 2012 from Fergusson College. His research prime objective is a biologic wound dressing .to his credit, he has Published10 articles in various international congresses by presenting posters.

Keywords: antimicrobial profile, MIC & MBC Method, microplate antimicrobial assay, E-test

Procedia PDF Downloads 134

Authors: Abrar Ajmal

Abstract:

This quantitative study explored elementary school teachers' pedagogical content knowledge and effects on grade 8 students' achievement in Punjab, Pakistan. A teacher sample (N=100) rated competencies across inquiry-focused teaching, conceptual building, interaction practices and peer collaboration promotion. A student sample (N=120) self-reported academic abilities, intrinsic motivation, help-seeking and accountability. Findings reveal teachers highly endorse learner-centric strategies, although peer interaction promotion seems less common currently. Meanwhile, significant gender disparities in self-perceived expertise emerge, favouring female over male educators across all facets measured. Additionally, teachers' knowledge positively—and significantly—correlates with student achievement overall and for both genders, highlighting the importance of professional enrichment. However, female pupils demonstrate greater confidence, drive, utilization of academic support, and ownership over learning than male counterparts. Recommendations include ongoing teacher training, targeted competency building for male students and teachers, leveraging gender peer collaboration similarities, and holistic female support amid widening divides. Sustaining instructional quality through empowering, equitable practices that nurture disadvantaged and gifted learners alike can spur systemic improvements. Ultimately, the fire line confirms the interrelations between teachers' multifaceted knowledge and student success.

Keywords: pedagogical knowledge, academic achievement, teacher gender differences, student gender differences, empowering instruction

Procedia PDF Downloads 48

Authors: Ali Bahkali, Rayan Yousef Booq, Mohammad Khiyami

Abstract:

Soil samples were collected from five different regions in the Kingdom of Saudi Arabia. Microbiological methods included dilution methods and pour plates to isolate and purify bacteria soil. The ability of isolates to develop biopolymer was investigated on petri dishes containing elements and substance concentrations stimulating developing biopolymer. Fluorescent stains, Nile red and Nile blue were used to stain the bacterial cells developing biopolymers. In addition, Sudan black was used to detect biopolymers in bacterial cells. The isolates which developed biopolymers were identified based on their gene sequence of 1 6sRNA and their ability to grow and synthesize PHAs on mineral medium supplemented with 1% dates molasses as the only carbon source under nitrogen limitation. During the study 293 bacterial isolates were isolated and detected. Through the initial survey on the petri dishes, 84 isolates showed the ability to develop biopolymers. These bacterial colonies developed a pink color due to accumulation of the biopolymers in the cells. Twenty-three isolates were able to grow on dates molasses, three strains of which showed the ability to accumulate biopolymers. These strains included Bacillus sp., Ralstonia sp. and Microbacterium sp. They were detected by Nile blue A stain with fluorescence microscopy (OLYMPUS IX 51). Among the isolated strains Ralstonia sp. was selected after its ability to grow on molasses dates in the presence of a limited nitrogen source was detected. The optimum conditions for formation of biopolymers by isolated strains were investigated. Conditions studied included, best incubation duration (2 days), temperature (30°C) and pH (7-8). The maximum PHB production was raised by 1% (v1v) when using concentrations of dates molasses 1, 2, 3, 4 and 5% in MSM. The best inoculated with 1% old inoculum (1= OD). The ideal extraction method of PHA and PHB proved to be 0.4% sodium hypochlorite solution, producing a quantity of polymer 98.79% of the cell's dry weight. The maximum PHB production was 1.79 g/L recorded by Ralstonia sp. after 48 h, while it was 1.40 g/L produced by R.eutropha ATCC 17697 after 48 h.

Keywords: bacteria forming polyhydroxyalkanoate, detection, molecular, Saudi Arabia

Procedia PDF Downloads 347

Authors: Reham Banwair, Lana Alshehri, Sara Hadrawi

Abstract:

The purpose of this project is to identify user satisfaction with the AI functions on Snapchat, in order to generate improvement proposals that allow its development within the app. To achieve this, a qualitative analysis was carried out through interviews to people who usually use the application, revealing their satisfaction or dissatisfaction with the usefulness of the AI. In addition, the background of the company and its introduction in these algorithms were analyzed. Furthermore, the characteristics of the three main functions of AI were explained: identify songs, solve mathematical problems, and recognize plants. As a result, it was obtained that 50% still do not know the characteristics of AI, 50% still believe song recognition is not always correct, 41.7% believe that math problems are usually accurate and 91.7% believes the plant detection tool is working properly.

Keywords: artificial intelligence, scanning, Snapchat, machine learning

Procedia PDF Downloads 135

Authors: Osayande Pascal Omondiagbe, Sherlock a Licorish

Abstract:

Stack Overflow is a popular community question and answer portal which is used by practitioners to solve technology-related challenges during software development. Previous studies have shown that this forum is becoming a substitute for official software programming languages documentation. While tools have looked to aid developers by presenting interfaces to explore Stack Overflow, developers often face challenges searching through many possible answers to their questions, and this extends the development time. To this end, researchers have provided ways of predicting acceptable Stack Overflow answers by using various modeling techniques. However, less interest is dedicated to examining the performance and quality of typically used modeling methods, and especially in relation to models’ and features’ complexity. Such insights could be of practical significance to the many practitioners that use Stack Overflow. This study examines the performance and quality of various modeling methods that are used for predicting acceptable answers on Stack Overflow, drawn from 2014, 2015 and 2016. Our findings reveal significant differences in models’ performance and quality given the type of features and complexity of models used. Researchers examining classifiers’ performance and quality and features’ complexity may leverage these findings in selecting suitable techniques when developing prediction models.

Keywords: feature selection, modeling and prediction, neural network, random forest, stack overflow

Procedia PDF Downloads 132

Authors: H. K. Ramaraju

Abstract:

World is in deep trouble and deeper denial. Worse, the denial is now entirely on the side of action. It is well accepted that climate change is a reality. Scientists say we need to cap temperature increases at 2°C to avoid catastrophe, which means capping emissions at 450 ppm .We know global average temperatures have already increased by 0.8°C and there is enough green house gas in the atmosphere to lead to another 0.8°C increase. There is still a window of opportunity, a tiny one, to tackle the crisis. But where is the action? In the 1990’s, when the world did even not understand, let alone accept, the crises, it was more willing to move to tackle climate change. Today we are in reverse in gear. The rich world has realized it is easy to talk big, but tough to take steps to actually reduce emissions. The agreement was that these countries would reduce so that the developing World could increase. Instead, between 1990 and 2006, their carbon dioxide emissions increased by a whopping 14.5 percent, even green countries of Europe are unable to match words with action. Stop deforestation and take a 20 percent advantage in our carbon balance sheet, with out doing anything at home called REDD (reducing emissions from deforestation and forest degradation) and push for carbon capture and storage (CCS) technologies. There are warning signs elsewhere and they need to be read correctly and acted up on , if not the cases like flood –act of nature or manmade disaster. The full length paper orient in proper understanding of the issues and identifying the most appropriate course of action.

Keywords: catastrophe, deforestation, emissions, waste water

Procedia PDF Downloads 287

Authors: Saiakhil Chilaka

Abstract:

Juvenile recidivism presents a significant challenge to the criminal justice system, impacting both the individuals involved and broader societal safety. This study aims to identify the key factors influencing recidivism and successful rehabilitation outcomes by utilizing a dataset of over 25,000 individuals from the NIJ Recidivism Challenge. We employed machine learning techniques, particularly Random Forest Classification, combined with SHAP (SHapley Additive exPlanations) for model interpretability. Our findings indicate that supervision risk score, percent days employed, and education level are critical factors affecting recidivism, with higher levels of supervision, successful employment, and education contributing to lower recidivism rates. Conversely, Gang Affiliation emerged as a significant risk factor for reoffending. The model achieved an accuracy of 68.8%, highlighting its utility in identifying high-risk individuals and informing targeted interventions. These results suggest that a comprehensive approach involving personalized supervision, vocational training, educational support, and anti-gang initiatives can significantly reduce recidivism and enhance rehabilitation outcomes for juveniles, providing critical insights for policymakers and juvenile justice practitioners.

Keywords: juvenile, justice system, data analysis, SHAP

Procedia PDF Downloads 25

Authors: Sahar Shams

Abstract:

Coeliac disease (CD) is a widely reported disease particularly in countries with predominant Caucasian populations. It presents with many signs and symptoms including iron deficiency (ID) and iron deficiency anaemia/anaemia (IDA/A). The exact association between ID, IDA/A and CD and how accurate these signs are in diagnosing CD is not fully known. This systematic review was conducted to investigate the accuracy of both ID & IDA/A as a diagnostic indicator for CD and whether it warrants point of care testing. A systematic review was performed looking at studies published in MEDLINE, Embase, Cochrane Library, and Web of Science. QUADAS-2 tool was used to assess risk of bias in each study. ROC curve and forest plots were generated as part of the meta-analysis after data extraction. 16 studies were identified in total, 13 of which were IDA/A studies and 3 ID studies. The prevalence of CD regardless of diagnostic indicator was assumed as 1%. The QUADAS-2 tool indicated most of studies as having high risk of bias. The PPV for CD was higher in those with ID than for those with IDA/A. Meta-analysis showed the overall odds of having CD is 5 times higher in individuals with ID & IDA/A. The ROC curve showed that there is definitely an association between both diagnostic indicators and CD, the association is not a particularly strong one due to great heterogeneity between studies. Whilst an association between IDA/A & ID and coeliac disease was evident, the results were not deemed significant enough to prompt coeliac disease testing in those with IDA/A & ID.

Keywords: anemia, iron deficiency anemia, coeliac disease, point of care testing

Procedia PDF Downloads 133

Authors: Linjie Zhang, Baifen Ren, Xi Zhang, Genwang Liu

Abstract:

Ship detection is of great significance for both military and civilian applications. Synthetic aperture radar (SAR) with all-day, all-weather, ultra-long-range characteristics, has been used widely. In view of the low time resolution of low orbit SAR and the needs for high time resolution SAR data, GEO (Geosynchronous orbit) SAR is getting more and more attention. Since GEO SAR has short revisiting period and large coverage area, it is expected to be well utilized in marine ship targets monitoring. However, the height of the orbit increases the time of integration by almost two orders of magnitude. For moving marine vessels, the utility and efficacy of GEO SAR are still not sure. This paper attempts to find the feasibility of GEO SAR by giving a GEO SAR simulator of moving ships. This presented GEO SAR simulator is a kind of geometrical-based radar imaging simulator, which focus on geometrical quality rather than high radiometric. Inputs of this simulator are 3D ship model (.obj format, produced by most 3D design software, such as 3D Max), ship's velocity, and the parameters of satellite orbit and SAR platform. Its outputs are simulated GEO SAR raw signal data and SAR image. This simulating process is accomplished by the following four steps. (1) Reading 3D model, including the ship rotations (pitch, yaw, and roll) and velocity (speed and direction) parameters, extract information of those little primitives (triangles) which is visible from the SAR platform. (2) Computing the radar scattering from the ship with physical optics (PO) method. In this step, the vessel is sliced into many little rectangles primitives along the azimuth. The radiometric calculation of each primitive is carried out separately. Since this simulator only focuses on the complex structure of ships, only single-bounce reflection and double-bounce reflection are considered. (3) Generating the raw data with GEO SAR signal modeling. Since the normal ‘stop and go’ model is not available for GEO SAR, the range model should be reconsidered. (4) At last, generating GEO SAR image with improved Range Doppler method. Numerical simulation of fishing boat and cargo ship will be given. GEO SAR images of different posture, velocity, satellite orbit, and SAR platform will be simulated. By analyzing these simulated results, the effectiveness of GEO SAR for the detection of marine moving vessels is evaluated.

Keywords: GEO SAR, radar, simulation, ship

Procedia PDF Downloads 178

Authors: K. N. Dinesh Babu, P. K. Gargava

Abstract:

Energization of a transformer results in sudden flow of current which is an effect of core magnetization. This current will be dominated by the presence of second harmonic, which in turn is used to segregate fault and inrush current, thus guaranteeing proper operation of the relay. This additional security in the relay sometimes obstructs or delays differential protection in a specific scenario, when the 2^nd harmonic content was present during a genuine fault. This kind of scenario can result in isolation of the transformer by Buchholz and pressure release valve (PRV) protection, which is acted when fault creates more damage in transformer. Such delays involve a huge impact on the insulation failure, and chances of repairing or rectifying fault of problem at site become very dismal. Sometimes this delay can cause fire in the transformer, and this situation becomes havoc for a sub-station. Such occurrences have been observed in field also when differential relay operation was delayed by 10-15 ms by second harmonic blocking in some specific conditions. These incidences have led to the need for an alternative solution to eradicate such unwarranted delay in operation in future. Modern numerical relay, called as intelligent electronic device (IED), is embedded with advanced protection features which permit higher flexibility and better provisions for tuning of protection logic and settings. Such flexibility in transformer protection IEDs, enables incorporation of alternative methods such as dynamic switching of second harmonic feature for blocking the differential protection with additional security. The analysis and precautionary measures carried out in this case, have been simulated and discussed in this paper to ensure that similar solutions can be adopted to inhibit analogous issues in future.

Keywords: differential protection, intelligent electronic device (IED), 2nd harmonic inhibit, inrush inhibit

Procedia PDF Downloads 300

Authors: Tesfaye Mengistu

Abstract:

Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

Procedia PDF Downloads 114

Authors: Laurenn Borges de Macedo, Fabiane Salles Ferro, Tiago Hendrigo de Almeida, Gérson Moreira de Lima, André Luiz Christoforo, Francisco Antonio Rocco Lahr

Abstract:

The growth of the furniture manufacturing industry is one of the fundamental factors contributing to the growth of the particleboard industry. The use of recycled products into particleboards can contribute to the forest conservation, in addition to achieve a high quality sustainable product with low-cost production. This work investigates the effect of bi-oriented polypropylene (BOPP) waste particles and sealing product on the physical and mechanical properties of Eucalyptus sp. particleboards fabricated with a castor oil based polyurethane resin. Among the factors, only the seal coating was statistically significant. The wood panels of Treatment 2 were classified as H1, based on the internal bond strength and elastic modulus results data required by ANSI A208.1:1999. The bending strength data did not reach the minimum values recommended by NBR 14810:2006 and ANSI A208.1:1999. The thickness swelling data for 2h immersed in water achieved the standard requirement levels. High-density panels were achieved revealing their potential use in variety of particleboard applications.

Keywords: BOPP, mechanical properties, particleboards, physical properties

Procedia PDF Downloads 372

Authors: Ifigeneia V. Mavragani, Zacharenia Nikitaki, George Kalantzis, George Iliakis, Alexandros G. Georgakilas

Abstract:

Complex DNA damage consisting of a combination of DNA lesions, such as Double Strand Breaks (DSBs) and non-DSB base lesions occurring in a small volume is considered as one of the most important biological endpoints regarding ionizing radiation (IR) exposure. Strong theoretical (Monte Carlo simulations) and experimental evidence suggests an increment of the complexity of DNA damage and therefore repair resistance with increasing linear energy transfer (LET). Experimental detection of complex (clustered) DNA damage is often associated with technical deficiencies limiting its measurement, especially in cellular or tissue systems. Our groups have recently made significant improvements towards the identification of key parameters relating to the efficient detection of complex DSBs and non-DSBs in human cellular systems exposed to IR of varying quality (γ-, X-rays 0.3-1 keV/μm, α-particles 116 keV/μm and 36Ar ions 270 keV/μm). The induction and processing of DSB and non-DSB-oxidative clusters were measured using adaptations of immunofluorescence (γH2AX or 53PB1 foci staining as DSB probes and human repair enzymes OGG1 or APE1 as probes for oxidized purines and abasic sites respectively). In the current study, Relative Biological Effectiveness (RBE) values for DSB and non-DSB induction have been measured in different human normal (FEP18-11-T1) and cancerous cell lines (MCF7, HepG2, A549, MO59K/J). The experimental results are compared to simulation data obtained using a validated microdosimetric fast Monte Carlo DNA Damage Simulation code (MCDS). Moreover, this simulation approach is implemented in two realistic clinical cases, i.e. prostate cancer treatment using X-rays generated by a linear accelerator and a pediatric osteosarcoma case using a 200.6 MeV proton pencil beam. RBE values for complex DNA damage induction are calculated for the tumor areas. These results reveal a disparity between theory and experiment and underline the necessity for implementing highly precise and more efficient experimental and simulation approaches.

Keywords: complex DNA damage, DNA damage simulation, protons, radiotherapy

Procedia PDF Downloads 327

Authors: Iván Castelló, Georgiana Stoica, Emilio Palomares, Fernando Bravo

Abstract:

We present herein two colour encoded silica nanospheres (2nanoSi) for the fluorescence quantitative ratiometric determination of trypsin in humans. The system proved to be a faster (minutes) method, with two times higher sensitivity than the state-of-the-art biomarkers based sensors for cystic fibrosis (CF), allowing the quantification of trypsin concentrations in a wide range (0-350 mg/L). Furthermore, as trypsin is directly related to the development of cystic fibrosis, different human genotypes, i.e. healthy homozygotic (> 80 mg/L), CF homozygotic (< 50 mg/L), and heterozygotic (> 50 mg/L), respectively, can be determined using our 2nanoSi nanospheres.

Keywords: cystic fibrosis, trypsin, quantum dots, biomarker, homozygote, heterozygote

Procedia PDF Downloads 486

Authors: James Taylor

Abstract:

This paper considers the political, geo-philosophical musings of Deleuze and Guattari on spatialisation, place and movement in relation to the religious nomad (wandering ascetics and reclusive forest monks) inhabiting the borderlands of Thailand. A nomadic science involves improvised ascetic practices between the molar lines striated by modern state apparatuses. The wandering ascetics, inhabiting a frontier political ecology, stand in contrast to the appropriating, sedentary metaphysics and sanctifying arborescence of statism and its corollary place-making, embedded in rootedness and territorialisation. It is argued that the religious nomads, residing on the endo-exteriorities of the state, came to represent a rhizomatic and politico-ontological threat to centre-nation and its apparatus of capture. The paper also theorises transitions and movement at the borderlands in the context of the state’s monastic reforms. These reforms, and its pervasive royal science, problematised the interstitial zones of the early ascetic wanderers in their radical cross-cutting networks and lines, moving within and across demarcated frontiers. Indeed, the ascetic wanderers and their allegorical war machine were seen as a source of wild, free-floating charisma and mystical power, eventually appropriated by the centre-nation in it’s becoming unitary and fixed.

Keywords: Deleuze and Guattari, religious nomad, centre-nation, borderlands, Buddhism

Procedia PDF Downloads 87