Search results for: plant disease classification

Authors: Salman Obaidoon, Mohamed Hassan, Omer Bakather

Abstract:

As environmental regulations increase, the need for a clean and inexpensive energy is becoming necessary these days using an available raw material with high efficiency and low emissions of toxic gases. This paper presents a study on modifying a gas turbine power plant fired by diesel, which is located in Saudi Arabia in order to increase the efficiency and capacity of the station as well as decrease the rate of emissions. The studied power plant consists of 30 units with different capacities and total net power is 1470 MW. The study was conducted on unit number 25 (GT-25) which produces 72.3 MW with 29.5% efficiency. In the beginning, the unit was modeled and simulated by using WinSim Design II software. In this step, actual unit data were used in order to test the validity of the model. The net power and efficiency obtained from software were 76.4 MW and 32.2% respectively. A difference of about 6% was found in the simulated power plant compared to the actual station which means that the model is valid. After the validation of the model, the simple gas turbine power plant was converted to a combined cycle power plant (CCPP). In this case, the exhausted gas released from the gas turbine was introduced to a heat recovery steam generator (HRSG), which consists of three heat exchangers: an economizer, an evaporator and a superheater. In this proposed model, many scenarios were conducted in order to get the optimal operating conditions. The net power of CCPP was increased to 116.4 MW while the overall efficiency of the unit was reached to 49.02%, consuming the same amount of fuel for the gas turbine power plant. For the purpose of comparing the rate of emissions of carbon dioxide on each model. It was found that the rate of CO₂ emissions was decreased from 15.94 kg/s to 9.22 kg/s by using the combined cycle power model as a result of reducing of the amount of diesel from 5.08 kg/s to 2.94 kg/s needed to produce 76.5 MW. The results indicate that the rate of emissions of carbon dioxide was decreased by 42.133% in CCPP compared to the simple gas turbine power plant.

Keywords: combined cycle power plant, efficiency, heat recovery steam generator, simulation, validation, WinSim design II software

Procedia PDF Downloads 273

Authors: Rosa L. Figueroa, Christopher A. Flores, Qing Zeng-Treitler

Abstract:

A regular expression consists of sequence characters which allow describing a text path. Usually, in clinical research, regular expressions are manually created by programmers together with domain experts. Lately, there have been several efforts to investigate how to generate them automatically. This article presents a text classification algorithm based on regexes. The algorithm named REX was designed, and then, implemented as a simplified method to create regexes to classify Spanish text automatically. In order to classify ambiguous cases, such as, when multiple labels are assigned to a testing example, REX includes an information gain method Two sets of data were used to evaluate the algorithm’s effectiveness in clinical text classification tasks. The results indicate that the regular expression based classifier proposed in this work performs statically better regarding accuracy and F-measure than Support Vector Machine and Naïve Bayes for both datasets.

Keywords: information gain, regular expressions, smith-waterman algorithm, text classification

Procedia PDF Downloads 319

Authors: Teja Koduru

Abstract:

Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

Procedia PDF Downloads 239

Authors: N. R. Prasannakumar, M. N. Maruthi

Abstract:

The whitefly, Bemisia tabaci (Gennadius) (Hemiptera; Aleyrodidae) is a highly polyphagous pest reported to infest over 600 plant hosts globally. About 42 genetic groups/cryptic species of B. tabaci exist in the world on different hosts. The species have variable behaviour with respect to feeding, development and transmission of viral diseases. Feeding on diverse host plants affect both whitefly development and the population of the endosymbionts harboured by the insects. Due to changes in the level of endosymbionts, the virus transmission efficiency by the vector also gets affected. We investigated these interactions on five host plants – egg plant, tomato, beans, okra and cotton - using a single whitefly species Asia 1 infected with three different bacteria Portiera, Wolbachia and Arsenophonus. The Asia 1 transmits the Tomato leaf curl Bangalore virus (ToLCBV) effectively and thus was used in the interaction studies. We found a significant impact of hosts on whitefly growth and development; eggplant was most favourable host, while okra and tomato were least favourable. Among the endosymbiotic bacteria, the titre of Wolbachia was significantly affected by feeding of B. tabaci on different host plants whereas Arsenophonus and Portiera were unaffected. When whitefly fed on ToLCBV-infected tomato plants, the Arsenophonus population was significantly increased, indicating its previously confirmed role in ToLCBV transmission. Further, screening of total proteins of B. tabaci Asia 1 genetic group interacting with ToLCBV coat protein was carried out using Y2H system. Some of the proteins found to be interacting with ToLCBV CP were HSPs 70kDa, GroEL, nucleoproteins, vitellogenins, apolipophorins, lachesins, enolase. The reported protein thus would be the potential targets for novel whitefly control strategies such as RNAi or novel insecticide target sites for sustainable whitefly management after confirmation of genuine proteins.

Keywords: cDNA, whitefly, ToLCBV, endosymbionts, Y2H

Procedia PDF Downloads 115

Authors: Zahra Rakhshan Masoudi, Sona Rostampour Yasouri

Abstract:

Considering that the only way to save the lives of patients and healthy people who have suffered sudden accidents is blood transfusion, what is important is the presence of the known HCV virus as the most important cause of the disease after blood transfusion. HCV is one of the major global problems, and its transmission through blood causes life-threatening complications and extensive legal, social and economic consequences. On the one hand, unfortunately, there is still no effective vaccine available to prevent HCV. In Iran, the exact statistics of the prevalence of this disease have not yet been fully announced. The main purpose of this study is to investigate the prevalence rate and rapid diagnosis of HCV among those who refer to laboratory centers in Tehran. From spring to winter of 1401 (2022-2023), 2166 blood samples were collected from laboratory centers in Tehran. Blood samples were evaluated for the presence of HCV by Electrochemiluminescence (ECL) and PCR techniques along with specific HCV primers. In general, 36 samples (1.6%) were tested positive by the mentioned techniques. The results indicated that the ECL technique is a sensitive and specific diagnostic method for detecting HCV in the early stages of the disease and can be very helpful and provide the possibility of starting the treatment steps to prevent the exacerbation of the disease earlier. Also, the results of PCR technique showed that PCR is an accurate, sensitive and fast method for definitive diagnosis of HCV. It seems that the incidence rate of this disease is increasing in Iran, and investigating the spread of the disease throughout Iran for a longer period of time in the continuation of our research can be helpful in the future to take the necessary measures to prevent the transmission of the disease to people and the rapid onset Treatment steps for patients with HCV should be carried out.

Keywords: electrochemiluminescence, HCV, PCR, prevalence

Procedia PDF Downloads 67

Authors: Abdullah Bal

Abstract:

This paper presents a one-class classification (OCC) technique based on Fukunaga-Koontz Transform (FKT) for binary classification problems. The FKT is originally a powerful tool to feature selection and ordering for two-class problems. To utilize the standard FKT for data domain description problem (i.e., one-class classification), in this paper, a set of non-class samples which exist outside of positive class (target class) describing boundary formed with limited training data has been constructed synthetically. The tunnel-like decision boundary around upper and lower border of target class samples has been designed using statistical properties of feature vectors belonging to the training data. To capture higher order of statistics of data and increase discrimination ability, the proposed method, termed one-class FKT (OC-FKT), has been extended to its nonlinear version via kernel machines and referred as OC-KFKT for short. Multiple kernel learning (MKL) is a favorable family of machine learning such that tries to find an optimal combination of a set of sub-kernels to achieve a better result. However, the discriminative ability of some of the base kernels may be low and the OC-KFKT designed by this type of kernels leads to unsatisfactory classification performance. To address this problem, the quality of sub-kernels should be evaluated, and the weak kernels must be discarded before the final decision making process. MKL/OC-FKT and selective MKL/OC-FKT frameworks have been designed stimulated by ensemble learning (EL) to weight and then select the sub-classifiers using the discriminability and diversities measured by eigenvalue ratios. The eigenvalue ratios have been assessed based on their regions on the FKT subspaces. The comparative experiments, performed on various low and high dimensional data, against state-of-the-art algorithms confirm the effectiveness of our techniques, especially in case of small sample size (SSS) conditions.

Keywords: ensemble methods, fukunaga-koontz transform, kernel-based methods, multiple kernel learning, one-class classification

Procedia PDF Downloads 19

Authors: Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K. M.

Abstract:

Online handwritten character recognition is a challenging field in Artificial Intelligence. The classification success rate of current techniques decreases when the dataset involves similarity and complexity in stroke styles, number of strokes and stroke characteristics variations. Malayalam is a complex south indian language spoken by about 35 million people especially in Kerala and Lakshadweep islands. In this paper, we consider the significant feature extraction for the similar stroke styles of Malayalam. This extracted feature set are suitable for the recognition of other handwritten south indian languages like Tamil, Telugu and Kannada. A classification scheme based on support vector machines (SVM) is proposed to improve the accuracy in classification and recognition of online malayalam handwritten characters. SVM Classifiers are the best for real world applications. The contribution of various features towards the accuracy in recognition is analysed. Performance for different kernels of SVM are also studied. A graphical user interface has developed for reading and displaying the character. Different writing styles are taken for each of the 44 alphabets. Various features are extracted and used for classification after the preprocessing of input data samples. Highest recognition accuracy of 97% is obtained experimentally at the best feature combination with polynomial kernel in SVM.

Keywords: SVM, matlab, malayalam, South Indian scripts, onlinehandwritten character recognition

Procedia PDF Downloads 574

Authors: Ritu Nambiar, Shazia Tariq, Sumaira Jamil, Farida Munawar, Imelda Israell

Abstract:

GBS has emerged as a leading cause of neonatal infections worldwide and clinical trials have demonstrated that giving IAP was effective in reducing early onset GBS (EOGBS) disease of the newborn. There is no available data on the prevalence of GBS in the UAE, therefore, a retrospective chart analysis of our parturients were done to look at our prevalence. The aim of this study is: 1. To study the prevalence of GBS colonization of parturients at al Rahba Hospital following universal screening between 35-37 week. 2. To look at efficacy of GBS intrapartum antibiotic prophylaxis by NICU admission for EO GBS disease of the newborn. 1) The prevalence of GBS in our patient population is 24.15%. 2) Incidence of EO GBS disease of the newborn was 0.6%.

Keywords: GBS Screening, universal intrapartum antibiotic prophylaxis, parturients, newborn

Procedia PDF Downloads 394

Authors: P. U. S. Peiris

Abstract:

The butterflies are ecologically very important insects. The adults generally feed on nectar and are important as pollinators of flowering plants. However, these pollinators are under threat with their habitat loss. One reason for habitat loss is spread of invasive plants. However, there are even beneficial exotic plants which can directly support for Butterfly Conservation Action Plan of Sri Lanka by attracting butterflies for nectar. Stachytarpheta jamaicensis (L.) is an important nectar plant which attracts a diverse set of butterflies in higher number. It comprises a violet color inflorescence which last for about 37 hours where it attracted a peak of butterflies around 9.00am having around average of 15 butterflies. There were no butterflies in early and late hours where the number goes to very low values as 2 at 1.00pm. it was found that a diverse group of butterflies were attracted from around 15 species including 01 endemic species, 02 endemic subspecies and 02 vulnerable species. Therefore, this is a beneficial exotic plant that could be used in butterfly attraction and conservation however with adequate monitoring of the plant population.

Keywords: butterflies, exotic plants, pollinators, Stachytarpheta jamaicensis (L.)

Procedia PDF Downloads 242

Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

Abstract:

Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

Procedia PDF Downloads 197

Authors: Anush Patric, M. Jadeyegowda, M. N. Ramesh, M. Ravikumar, C. R. Ajay

Abstract:

Kodagu district which is situated in Central Western Ghats regions falls in one of the hottest of hot spots of biodiversity which is recognised by UNESCO. The district has one of the highest densities of community managed sacred forests in the world with rich floral and faunal diversity. It is a habitat for more than ten different types of Ethnic Indigenous tribal groups commonly called ‘Girijanas’ (Soligas, Yarvas, Jenukuruba, Bettakuruba etc.), who are having the rich knowledge of medicinal value of the plants that are commonly available in the forest. The tribal men of this region are the treasure house of the traditional plant knowledge and health care practices. An ethnobotanical survey was undertaken in tribal areas of the district to collect information about some of the indigenous medicinal plant knowledge of tribal people by semi-structured interviews, ranking exercises and field observations on their native habitat in order to evaluate the potential medicinal uses of local plants. The study revealed that, the ethnobotanical information of 83 plant species belonging to 45 families, of the total 83 species documented, most plants used in the treatment were trees (11 species), shrubs (41 species), herbs (22 species) and rarely climbers (9 species) which are used in the treatment of Hyperacidity, Respiratory disorders, Snake bite Abortifacient, Anthelmintic, Paralysis, Antiseptic, Fever, Chest pain, Stomachic, Jaundice, Piles, Asthma, Malaria, Renal disorders, Malaria and many other diseases. Maximum of 6 plant species each of Acanthaceae, Apiaceae and were used for drug preparation, followed by Asclepiadaceae, Liliaceae, Fabaceae, Verbenaceae, Caesalpinaceae, Bombaceae, Papilonaceae, Solanaceae, Rubiaceae, Myrtaceae, Amaranthaceae, Asteraceae, Ascelepidaceae, Cucurbitaceae, Apocyanaceae, and Solanaceae etc. In our present study, only medicinal plants and their local medicinal uses are recorded and presented. Information was obtained by local informants having the knowledge about medicinal plants. About 23 local tribes were interviewed. For each plant, necessary information like botanical name, family of plant species, local name and uses are given. Recent trend shows a decline in the number of traditional herbal healers in the tribal areas since the younger generation is not interested to continue this tradition. Hence, there is an urgent need to record and preserve all information on plants used by different ethnic/tribal communities for various purposes before it reaches to verge of extinction. In addition, several wild medicinal plants are declining in numbers due to deforestation and forest fires. There is need for phytochemical analysis and conservation measures to be taken for conserving medicinal plant species which is far better than allopathic medicines and these do not cause any side effects as they are the natural disease healers. So, conservation strategies have to be practiced in all levels and sectors by creating awareness about the value of such medicinal plants, and it is necessary to save the disappearing plants to strengthen the document and to conserve them for future generation.

Keywords: diseases, ethnic groups, folk medicine, Kodagu, medicinal plants

Procedia PDF Downloads 260

Authors: Rezvan Hosseinian

Abstract:

Aim: Systemic sclerosis (SSc) is a chronic connective tissue disease with the clinical hallmark of skin thickening and tethering. The correlation of musculoskeletal features with other parameters should be considered in SSc patients. Methods: We reviewed the records of all patients who had more than one visit and standard anteroposterior radiography of hand. We used univariate analysis, and factors with p<0.05 were included in logistic regression to find out dependent factors. Results: Overall, 180 SSc patients were enrolled in our study, 161 (89.4%) of whom were women. The median age (IQR) was 47.0 years (16), and 52% had a diffuse subtype of the disease. In multivariate analysis, tendon friction rubs (TFRs) were associated with the presence of calcinosis, muscle tenderness, and flexion contracture (FC) on physical examination (p<0.05). Arthritis showed no differences in the two subtypes of the disease (p=0.98), and in multivariate analysis, there were no correlations between radiographic arthritis and serological and clinical features. The radiographic results indicated that disease duration correlated with joint erosion, acro-osteolysis, resorption of the distal ulna, calcinosis and radiologic FC (p< 0.05). Acro-osteolysis was more frequent in the dcSSc subtype, TFRs, and anti-TOPO I antibody. Radiologic FC showed an association with skin score, calcinosis and haematocrit <30% (p<0.05). Joint flexion on radiography was associated with disease duration, modified Rodnan skin score, calcinosis, and low hematocrit (P<0.01). Conclusion: Disease duration was a main dependent factor for developing joint erosion, acro-osteolysis, bone resorption, calcinosis, and flexion contracture on hand radiography. Acro-osteolysis presented in the severe form of the disease. Acro-osteolysis was the only dependent variable associated with bone demineralization.

Keywords: disease subsets, hand radiography, joint erosion, sclerosis

Procedia PDF Downloads 88

Authors: Nasrin Azarbani

Abstract:

Aim: Systemic sclerosis (SSc) is a chronic connective tissue disease with the clinical hallmark of skin thickening and tethering. Correlation of musculoskeletal features with other parameters should be considered in SSc patients. Methods: We reviewed the records of all patients who had more than one visit and standard anteroposterior radiography of hand. We used univariate analysis, and factors with p<0.05 were included in logistic regression to find out dependent factors. Results: Overall, 180 SSc patients were enrolled in our study, 161 (89.4%) of whom were women. Median age (IQR) was 47.0 years (16), and 52% had diffuse subtype of the disease. In multivariate analysis, tendon friction rubs (TFRs) was associated with the presence of calcinosis, muscle tenderness, and flexion contracture (FC) on physical examination (p<0.05). Arthritis showed no differences in the two subtypes of the disease (p=0.98), and in multivariate analysis, there were no correlations between radiographic arthritis and serological and clinical features. The radiographic results indicated that disease duration correlated with joint erosion, acro-osteolysis, resorption of distal ulna, calcinosis and radiologic FC (p< 0.05). Acro-osteolysis was more frequent in the dcSSc subtype, TFRs, and anti-TOPO I antibody. Radiologic FC showed an association with skin score, calcinosis and haematocrit <30% (p<0.05). Joint flexion on radiography was associated with disease duration, modified Rodnan skin score, calcinosis, and low haematocrit (P<0.01). Conclusion: Disease duration was a main dependent factor for developing joint erosion, acro-osteolysis, bone resorption, calcinosis, and flexion contracture on hand radiography. Acro-osteolysis presented in the severe form of the disease. Acro-osteolysis was the only dependent variable associated with bone demineralization.

Keywords: sclerosis, disease subsets, joint erosion, musculoskeletal

Procedia PDF Downloads 64

Authors: Muhammad Xaaceph Khan, Abida Butt, Farah Kausar

Abstract:

Due to geogenic and anthropogenic factors, heavy metals concentrations increased throughout the world and deposit into soil. Thus available to different plants and travel in different food chains. The present study was designed to achieve bioaccumulation of Cd and Zn in the wheat-aphid-beetle food chain. For this purpose, wheat plants were grown in three different treatments: Cd, Zn, Cd+Zn. Data showed that Cd content in soil and wheat plant increases with increase in Cd concentration while plant weighs, panicle weight, seed number per panicle and seed weight per panicle decreases with increase in Cd content in the soil. Zn content in soil and wheat plant increases with increase in Cd concentration while plant weighs, panicle weight, seed number per panicle, and seed weight per panicle increase with an increase in Zn content in the soil. With the addition of Zn in Cd-treated soil, the uptake of Cd decreases in all parts of wheat plants. Bioaccumulation from wheat plant to aphids and then its predators were also studied. Cd concentration increases from low to high concentration in all arthropods. Same was observed in Zn concentrations, while in Cd+Zn, Cd accumulation decreases but Zn accumulates increases. Health risk index (HRI) also showed that in the presence of Zn, the HRI improves and can help to reduce health risks associated with Cd.

Keywords: aphid, beetle, bioaccumulation, cadmium, wheat, zinc

Procedia PDF Downloads 160

Authors: Richa Bhardwaj

Abstract:

Tecomella undulata (Sm.) Seem is a monotypic genus belonging to family Bignoniaceae. The plant holds tremendous potential of medicinal value and has been traditionally used in various ailments like syphilis, leukoderma, blood disorders to name a few. The plant has gained prominence due to the presence of some prominent secondary metabolites. The present study focuses on the GC-MS analysis of leaf extracts of T. undulata which revealed the presence of certain bioactive compounds like stigmasterol, sitosterol, thiazoline, phytol, pthalic acid, methyl alpha ketopalmitate and so forth. A total of about 20 bioactive compounds were identified from the leaf extract spectra. Antimicrobial activity of the leaf extract was assayed against pathogenic bacteria and fungi. The alkaloids from leaf extracts showed antimicrobial activity against E.coli and B.subtilis. The flavonoids from leaves showed positive activity against Penicillium species and Candida albicans. The study thus infers that the presence of bioactive components may be the principle behind the antimicrobial property of different plant parts and therefore Tecomella forms a potential plant for herbal drug formulation.

Keywords: Tecomella undulata, bioactive compounds, GC-MS, antimicrobial activity

Procedia PDF Downloads 148

Authors: Priyanka Jain, Meera Srivastava

Abstract:

Among important insect pests of stored grains, the pulse beetle Callosobruchus chinensis Linn. (Coleoptera: Bruchidae) is one such pest causing considerable damage to stored pulses. An effort was made to screen plant Tephrosia purpurea (Family: Fabaceae) for its efficacy against the said pest. The pulse beetle C. chinensis was raised on green gram Vigna radiata in incubators maintained at 28 ± 2°C and 70% RH. Different formulations using plant parts (root, stem, leaf and fruit) were employed in the form of aqueous suspension, aqueous extract and ether extract and the treatments were made using different dose concentrations, namely 1%, 2.5%, 5% and 10%, besides normal and control. Specific number of adult insects were released in muslin cloth covered beakers containing weighed green gram grains and treated with different dose concentrations (w/v). Observations for the number of eggs laid by the pest insect C. chinensis was recorded after three days of treatment and it was observed that in general all the treatments of the plant resulted in significant decrease in the eggs laid (no/pair) by the insect, suggesting that the selected plant has a potential to be used against C. chinensis.

Keywords: Callosobruchus chinensis, egg laying, Tephrosia purpurea, Fabaceae, plant formulations

Procedia PDF Downloads 339

Authors: Pradipta Risang Ratna Sambawa, Driya Herseta, Mahendra Fajri Nugraha

Abstract:

In 2020, PT Petrokimia Gresik implemented a program to increase the ROP (Run Of Pile) production rate at the Phosphate Fertilizer 1 plant, causing an increase in scrubbing water consumption in the 100/200 area unit. This increase in water consumption causes a higher discharge of wastewater, which can further cause local flooding, especially during the rainy season. The 100/200 area of the Phosphate Fertilizer 1 plant is close to the warehouse and is often a passing area for trucks transporting raw materials. This causes the pH in the wastewater to become acidic (the worst point is up to pH 1). The problem of flooding and exposure to acidic wastewater in the 100/200 area of Phosphate Fertilizer Plant 1 was then resolved by PT Petrokimia Gresik through wastewater optimization steps called the 3R program (Reduce, Reuse, and Recycle). The 3R (Reduce, reuse, and recycle) program consists of an air consumption reduction program by considering the liquid/gas ratio in scrubbing unit of 100/200 Phosphate Fertilizer 1 plant, creating a wastewater interconnection line so that wastewater from unit 100/200 can be used as scrubbing water in the Phonska 1, Phonska 2, Phonska 3 and unit 300 Phosphate Fertilizer 1 plant and increasing scrubbing effectiveness through scrubbing effectiveness simulations. Through a series of wastewater optimization programs, PT Petrokimia Gresik has succeeded in reducing NaOH consumption for neutralization up to 2,880 kg/day or equivalent in saving up to 314,359.76 dollars/year and reducing process water consumption up to 600 m3/day or equivalent in saving up to 63,739.62 dollars/year.

Keywords: fertilizer, phosphate fertilizer, wastewater, wastewater treatment, water management

Procedia PDF Downloads 24

Authors: Degri M. M, Samaila A. E., Simon L., Joly G. A.

Abstract:

The amaranth leaf webber caterpillar (Hymenia recurvalis Fab.) was found to cause serious leaf damage by perforation and reduce amaranth growth and yield. It is a major limiting factor in amaranth production. Field experiments were conducted during 2022 and 2023 with the aim of assessing insecticidal potential of five selected plant leaf extracts, namely Moringa oleifera, Azadiractha indica A. Juss , Balanites aegyptiaca Del., Momordica balsamina and Hyptis suaveolens using Lambda.cyhalothrin 2.5 EC, a synthetic insecticide as a check. The experiment was conducted in a randomized complete block design (RCBD) replicated three times. Results showed that A.indica and H.suaveolous were more effective in reducing H .recurvalis population, leaf perforation, leaf damaged and improved amaranth plant growth and yield. This was closely followed by B. aegyptiaca and M. balsamina while M. oleifera had the lowest effect on the use of pest population and damage. Lambda.cyhalothrin, a synthetic insecticide, was found to be superior to the five plant extracts. The result showed that A. indica and H. suaveolens improved the growth and yield of amaranth during the study period. The study, therefore, recommended the two plant extracts for the control of leaf webber caterpillar (H. recurvalis) to limited resource farmers and as a good alternative to Lambda.cyhalothrin 2.5EC in the study area.

Keywords: Amaranth, leaf Webber plant extracts, Lambda cyhalothrin, rainfed

Procedia PDF Downloads 15

Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

Abstract:

High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

Procedia PDF Downloads 230

Authors: A. U. Adamu, E. D Paul, C. E. Gimba, I. G. Ndukwe

Abstract:

The phytochemical and proximate composition of Aspillia kotschyi belonging to Compositae family which is commonly used as medicinal plant in Nigeria was determined on both the Methanolic and Petroleum sprit extract of the plant. The Methanolic extract of the plant revealed the presence of carbohydrates, cardiac glyscosides, flavonoids, triterpene, and alkaloids. The Petroleum sprit extract showed the presence of only carbohydrates and alkaloid. Proximate composition analysis shows moisture content of 5.7%, total ash of 4.03%, crude protein 10.94%, fibre 9.06%, fat value 0.83%, and nitrogen free extract of 70.19%. The results of this study suggest some merit in the popular use of Aspillia kotschi in herbal medicine.

Keywords: Aspillia kotschyi, herbal medicine, phytochemical, proximate composition

Procedia PDF Downloads 363

Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

Abstract:

Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

Procedia PDF Downloads 64

Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

Abstract:

Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

Procedia PDF Downloads 349

Authors: Kenan Morani, Esra Kaya Ayana

Abstract:

This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

Procedia PDF Downloads 129

Authors: Guoliang Lu, Changhou Lu, Xueyong Li

Abstract:

In action recognition, previous studies have demonstrated the effectiveness of using multiple features to improve the recognition performance. We focus on two practical issues: i) most studies use a direct way of concatenating/accumulating multi features to evaluate the similarity between two actions. This way could be too strong since each kind of feature can include different dimensions, quantities, etc; ii) in many studies, the employed classification methods lack of a flexible and effective mechanism to add new feature(s) into classification. In this paper, we explore an unified scheme based on recently-proposed multi-dimensional dynamic time warping (MD-DTW). Experiments demonstrated the scheme's effectiveness of combining multi-feature and the flexibility of adding new feature(s) to increase the recognition performance. In addition, the explored scheme also provides us an open architecture for using new advanced classification methods in the future to enhance action recognition.

Keywords: action recognition, multi features, dynamic time warping, feature combination

Procedia PDF Downloads 436

Authors: Junjie Wu, Hongjuan Hou, Eric Hu, Yongping Yang

Abstract:

Solar aided power generation (SAPG) technology has been proven as an efficient way to make use of solar energy for power generation purpose. In an SAPG plant, a solar field consisting of parabolic solar collectors is normally used to supply the solar heat in order to displace the high pressure/temperature extraction steam. To understand the performance of such a SAPG plant, a new simulation model was developed by the authors recently, in which the boiler was treated, as a series of heat exchangers unlike other previous models. Through the simulations using the new model, it was found the outlet properties of reheated steam, e.g. temperature, would decrease due to the introduction of the solar heat. The changes make the (lower stage) turbines work under off-design condition. As a result, the whole plant’s performance may not be optimal. In this paper, the second solar filed was proposed to increase the inlet temperature of steam to be reheated, in order to bring the outlet temperature of reheated steam back to the designed condition. A 600MW SAPG plant was simulated as a case study using the new model to understand the impact of the second solar field on the plant performance. It was found in the study, the 2nd solar field would improve the plant’s performance in terms of cycle efficiency and solar-to-electricity efficiency by 1.91% and 6.01%. The solar-generated electricity produced by per aperture area under the design condition was 187.96W/m2, which was 26.14% higher than the previous design.

Keywords: solar-aided power generation system, off-design performance, coal-saving performance, boiler modelling, integration schemes

Procedia PDF Downloads 289

Authors: Kingston Rajiah, Mari Kannan Maharajan, Si Jen Yeen, Sara Lew

Abstract:

Parkinson’s disease (PD) is a progressive neurodegenerative disorder with evolving layers of complexity. Both motor and non-motor symptoms of PD may affect patients’ quality of life (QoL). Life expectancy for an individual with Parkinson’s disease depends on the level of care the individual has access to, can have a direct impact on length of life. Therefore, improvement of the QoL is a significant part of therapeutic plans. Patients with PD, especially those who are in advanced stages, are in great need of assistance, mostly from their family members or caregivers in terms of medical, emotional, and social support. The role of a caregiver becomes increasingly important with the progression of PD, the severity of motor impairment and increasing age of the patient. The nature and symptoms associated with PD can place significant stresses on the caregivers’ burden. As the prevalence of PD is estimated to more than double by 2030, it is important to recognize and alleviate the burden experienced by caregivers. This study focused on the impact of the clinical features on the QoL of PD patients, and of their caregivers. This study included PD patients along with their caregivers and was undertaken at the Malaysian Parkinson's Disease Association from June 2016 to November 2016. Clinical features of PD patients were assessed using the Movement Disorder Society revised Unified Parkinson Disease Rating Scale (MDS-UPDRS); the Hoehn and Yahr Staging of Parkinson's Disease were used to assess the severity and Parkinson's disease activities of daily living scale were used to assess the disability of Parkinson’s disease patients. QoL of PD patients was measured using the Parkinson's Disease Questionnaire-39 (PDQ-39). The revised version of the Zarit Burden Interview assessed caregiver burden. At least one of the clinical features affected PD patients’ QoL, and at least one of the QoL domains affected the caregivers’ burden. Clinical features ‘Saliva and Drooling’, and ‘Dyskinesia’ explained 29% of variance in QoL of PD patients. The QoL domains ‘stigma’, along with ‘emotional wellbeing’ explained 48.6% of variance in caregivers’ burden. Clinical features such as saliva, drooling and dyskinesia affected the QoL of PD patients. The PD patients’ QoL domains such as ‘stigma’ and ‘emotional well-being’ influenced their caregivers’ burden.

Keywords: carers, quality of life, clinical features, Malaysia

Procedia PDF Downloads 243

Authors: Sabir Hussain, Muhammad Naeem, Yousif Aldryhim, Susan E. Halbert, Qingjun Wu

Abstract:

Plant viruses annually cause severe economic losses in crop production and globally, different aphid species are responsible for the transmission of such viruses. Additionally, aphids are also serious pests of trees, and agricultural crops. Al Bahah Province, Kingdom of Saudi Arabia (KSA) has a high native and introduced plant species with a temperate climate that provides ample habitats for aphids. In this study, we surveyed virus-transmitting aphids from the Province to highlight their spatial distributions and hot spot areas for their target control strategies. During our fifteen month's survey in Al Bahah Province, three hundred and seventy samples of aphids were collected using both beating sheets and yellow water pan traps. Consequently, fifty-four aphid species representing 30 genera belonging to four families were recorded from Al Bahah Province. Alarmingly, 35 aphid species from our records are virus transmitting species. The most common virus transmitting aphid species based on number of collecting samples, were Macrosiphum euphorbiae (Thomas, 1878), Brachycaudus rumexicolens (Patch, 1917), Uroleucon sonchi (Linnaeus, 1767), Brachycaudus helichrysi (Kaltenbach, 1843), and Myzus persicae (Sulzer, 1776). The numbers of samples for the forementioned species were 66, 24, 23, 22, and 20, respectively. The widest range of plant hosts were found for M. euphorbiae (39 plant species), B. helichrysi (12 plant species), M. persicae (12 plant species), B. rumexicolens (10 plant species), and U. sonchi (9 plant species). The hottest spot areas were found in Al-Baha, Al Mekhwah and Biljarashi cities of the province on the basis of their abundance. This study indicated that Al Bahah Province has relatively rich aphid diversity due to the relatively high plant diversity in a favorable climatic condition. ArcGIS tools can be helpful for biologists to implement the target control strategies against these pests in the integrated pest management, and ultimately to save money and time.

Keywords: Al Bahah province, aphid-virus interaction, biodiversity, global information system

Procedia PDF Downloads 182

Authors: Mohammed Abdullah Alshahrani

Abstract:

The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

Procedia PDF Downloads 49

Authors: H. N. Agiza, M. A. Sohaly, M. A. Elfouly

Abstract:

Parkinson's disease (PD) is a heterogeneous disorder with common age of onset, symptoms, and progression levels. In this paper we will solve analytically the PD model as a non-linear delay differential equation using the steps method. The step method transforms a system of delay differential equations (DDEs) into systems of ordinary differential equations (ODEs). On some numerical examples, the analytical solution will be difficult. So we will approximate the analytical solution using Picard method and Taylor method to ODEs.

Keywords: Parkinson's disease, step method, delay differential equation, two delays

Procedia PDF Downloads 202

Authors: G. Martino, F. Silva, E. Marchal

Abstract:

The control over delivered iron ore blend characteristics is one of the most important aspects of the mining business. The iron ore price is a function of its composition, which is the outcome of the beneficiation process. So, end-to-end integrated planning of mine operations can reduce risks of penalties on the iron ore price. In a standard iron mining company, the production chain is composed of mining, ore beneficiation, and client supply. When mine planning and client supply decisions are made uncoordinated, the beneficiation plant struggles to deliver the best blend possible. Technological improvements in several fields allowed bridging the gap between departments and boosting integrated decision-making processes. Clusterization and classification algorithms over historical production data generate reasonable previsions for quality and volume of iron ore produced for each pile of run-of-mine (ROM) processed. Mathematical modeling can use those deterministic relations to propose iron ore blends that better-fit specifications within a delivery schedule. Additionally, a model capable of representing the whole production chain can clearly compare the overall impact of different decisions in the process. This study shows how flexibilization combined with a planning optimization model between the mine and the ore beneficiation processes can reduce risks of out of specification deliveries. The model capabilities are illustrated on a hypothetical iron ore mine with magnetic separation process. Finally, this study shows ways of cost reduction or profit increase by optimizing process indicators across the production chain and integrating the different plannings with the sales decisions.

Keywords: clusterization and classification algorithms, integrated planning, mathematical modeling, optimization, penalty minimization

Procedia PDF Downloads 122