Search results for: normalization gain

Authors: Tomas Premoli, Sareh Rowlands

Abstract:

In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

Procedia PDF Downloads 47

Authors: B. Yermekbayeva, A. Gulyayaev, T. Nurgozhin, C. Bektur

Abstract:

Cytisine aminophosphonate under the name "Cytafat" was approved for clinical trials in Republic of Kazakhstan as a putative liver protecting drug for the treatment of acute toxic hepatitis. A method of conducting the clinical trial is a double blind study. Total number of patients -71, aged from 16 to 56 years. Research on healthy volunteers determined the maximal tolerable doze of "Cytafat" as 200 mg/kg. Side effects when administered at high dozes (100-200 mg/kg) are tachycardia and increase of arterial blood pressure. The drug is tested in the treatment of 28 patients with a syndrome of hepatocellular failure (a poisoning with substitutes of alcohol, rat poison, or medical products). "Cytafat" was intravenously administered at a dose of 10 mg/kg in 200 ml of 5 % glucose solution once daily. The number of administrations: 1-3. In the comparison group, 23 patients were treated intravenously once a day with “Essenciale H” at a dose of 10 ml. 20 patients received a placebo (10 ml of glucose intravenously). In all cases of toxic hepatopathology the significant positive clinical effect of the testing drug distinguishable from placebo and surpassing the alternative was observed. Within a day after administration a sharp reduction of cytolitic syndrome parameters (ALT, AST, alkaline phosphatase, thymol turbidity test, GGT) was registered, a reduction of the severity of cholestatic syndrome (bilirubin decreased) was recorded, significantly decreased indices of lipid peroxidation. The following day, in all cases the positive dynamics was determined with ultrasound study (reduction of diffuse changes and events of reactive pancreatitis), hepatomegaly disappeared. Normalization of all parameters occurred in 2-3 times faster, than when using the drug "Essenciale H" and placebo. Average term of elimination of toxic hepatopathy when using the drug "Cytafat" -2,8 days, "Essenciale H" -7,2 days, and placebo -10,6 days. The new drug "Cytafat" has expressed cytoprotective properties.

Keywords: cytisine, cytoprotection, hepatopathy, hepatoprotection

Procedia PDF Downloads 340

Authors: Muneeb Ullah, Daishihan, Xiadong Young

Abstract:

Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

Procedia PDF Downloads 55

Authors: Michalis Michael, Mauro Overend

Abstract:

Buildings, in which we spend 87-90% of our time, act as a shelter protecting us from environmental conditions and weather phenomena. The building's overall performance is significantly dependent on the envelope’s glazing part, which is particularly critical as it is the most vulnerable part to heat gain and heat loss. However, conventional glazing technologies have relatively low-performance thermo-optical characteristics. In this regard, during winter, the heat losses due to the glazing part of a building envelope are significantly increased as well as the heat gains during the summer period. In this study, the contribution of an innovative glazing technology, namely Closed Cavity Façade (CCF) in improving energy efficiency and IEQ in office buildings is examined, aiming to optimize various design configurations of CCF. Using Energy Plus and IDA ICE packages, the performance of several CCF configurations and geometries for various climate types were investigated, aiming to identify the optimum solution. The model used for the simulations and optimization process was MATELab, a recently constructed outdoor test facility at the University of Cambridge (UK). The model was previously experimentally calibrated. The study revealed that the use of CCF technology instead of conventional double or triple glazing leads to important benefits. Particularly, the replacement of the traditional glazing units, used as the baseline, with the optimal configuration of CCF led to a decrease in energy consumption in the range of 18-37% (depending on the location). This mainly occurs due to integrating shading devices in the cavity and applying proper glass coatings and control strategies, which lead to improvement of thermal transmittance and g-value of the glazing. Since the solar gain through the façade is the main contributor to energy consumption during cooling periods, it was observed that a higher energy improvement is achieved in cooling-dominated locations. Furthermore, it was shown that a suitable selection of the constituents of a closed cavity façade, such as the colour and type of shading devices and the type of coatings, leads to an additional improvement of its thermal performance, avoiding overheating phenomena and consequently ensuring temperatures in the glass cavity below the critical value, and reducing the radiant discomfort providing extra benefits in terms of Indoor Environmental Quality (IEQ).

Keywords: building energy efficiency, closed cavity façade, optimization, occupants comfort

Procedia PDF Downloads 45

Authors: Kumar Sambhav Pandey, Anamika Singh

Abstract:

The continuous researches in the field of computer architecture basically aims at accelerating the computational speed and to gain enhanced performance. In this era, the superscalar, sub-scalar concept has not gained enough attention for improving the computation performance. In this paper, we have presented a sub-scalar approach to utilize the parallelism present with in the data while processing. The main idea is to split the data into individual smaller entities and these entities are processed with a defined known set of instructions. This sub-scalar approach to the MIPS architecture can bring out significant improvement in the computational speedup. MIPS-I is the basic design taken in consideration for the development of sub-scalar MIPS64 for increasing the instruction level parallelism (ILP) and resource utilization.

Keywords: dataword, MIPS, processor, sub-scalar

Procedia PDF Downloads 512

Authors: Y. Smirlis, G. Koronakos, S. Plitsos

Abstract:

Shipbrokers assist the ship companies in chartering or selling and buying vessels, acting as intermediates between them and the market. They facilitate deals, providing their expertise, negotiating skills, and knowledge about ship market bargains. Their role is very important as it affects the profitability and market position of a shipping company. Due to their significant contribution, the shipping companies have to employ systematic procedures to evaluate the shipbrokers’ services in order to select the best and, consequently, to achieve the best deals. Towards this, in this paper, we consider shipbrokers as financial service providers, and we formulate the problem of evaluating and selecting shipbrokers’ services as a multi-criteria decision making (MCDM) procedure. The proposed methodology comprises a first normalization step to adjust different scales and orientations of the criteria and a second step that includes the mathematical model to evaluate the performance of the shipbrokers’ services involved in the assessment. The criteria along which the shipbrokers are assessed may refer to their size and reputation, the potential efficiency of the services, the terms and conditions imposed, the expenses (e.g., commission – brokerage), the expected time to accomplish a chartering or selling/buying task, etc. and according to our modelling approach these criteria may be assigned different importance. The mathematical programming model performs a comparative assessment and estimates for the shipbrokers involved in the evaluation, a relative score that ranks the shipbrokers in terms of their potential performance. To illustrate the proposed methodology, we present a case study in which a shipping company evaluates and selects the most suitable among a number of sale and purchase (S&P) brokers. Acknowledgment: This study is supported by the OptiShip project, implemented within the framework of the National Recovery Plan and Resilience “Greece 2.0” and funded by the European Union – NextGenerationEU programme.

Keywords: shipbrokers, multi-criteria decision making, mathematical programming, service-provider selection

Procedia PDF Downloads 52

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

Procedia PDF Downloads 368

Authors: Mikiyas Adugna

Abstract:

Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

Procedia PDF Downloads 27

Authors: Soumaya Mrabet, Imen Akkari, Amira Atig, Elhem Ben Jazia

Abstract:

Introduction: Celiac disease (CD) is a chronic autoimmune inflammatory enteropathy caused by gluten. The clinical presentation is very variable. Malabsorption in the MC is responsible for an alteration of the bone metabolism. Our purpose is to study the osteoarticular manifestations related to this condition. Material and methods: It is a retrospective study of 41 cases of CD diagnosed on clinical, immunological, endoscopic and histological arguments, in the Internal Medicine and Gastroenterology Department of Farhat Hached Hospital between September 2005 and January 2016. Results: Osteoarticular manifestations were found in 9 patients (22%) among 41 patients presenting CD. These were 7 women and 2 men with an average age of 35.7 years (25 to 67 years). These manifestations were revelatory of CD in 3 cases. Abdominal pain and diarrhea were present in 6 cases. Inflammatory polyarthralgia of wrists and knees has been reported in 7 patients. Mechanical mono arthralgia was noted in 2 patients. Biological tests revealed microcytic anemia by iron deficiency in 7 cases, hypocalcemia in 5 cases, Hypophosphatemia in 3 cases and elevated alkaline phosphatases in 3 cases. Upper gastrointestinal endoscopy with duodenal biopsy found villous atrophy in all cases. In immunology, Anti-transglutaminase antibodies were positive in all patients, Anti-endomysium in 7 cases. Measurement of bone mineral density (BMD) by biphotonic X-ray absorptiometer with evaluation of the T-score and the Z-score was performed in Twenty patients (48.8%). It was normal in 7 cases (33%) and showed osteopenia in 5 patients (25%) and osteoporosis in 2 patients (10%). All patients were treated with a Gluten-free diet associated with vitamin D and calcium substitution in 5 cases. The evolution was favorable in all cases with reduction of bone pain and normalization of the phosphocalcic balance. Conclusion: The bone impact of CD is frequent but often asymptomatic. Patients with CD should be evaluated by the measurement of bone mineral density and monitored for calcium and vitamin D deficiencies.

Keywords: bone mineral density, celiac disease, osteoarticular manifestations, vitamin D and calcium

Procedia PDF Downloads 300

Authors: Valeriya Tyo, Serikbolat Yessengabulov

Abstract:

Regions with extreme climate conditions such as Astana city require energy saving measures to increase the energy performance of buildings which are responsible for more than 40% of total energy consumption. Identification of optimal building geometry is one of the key factors to be considered. The architectural form of a building has the impact on space heating and cooling energy use, however, the interrelationship between the geometry and resultant energy use is not always readily apparent. This paper presents a comparative case study of two prototypical buildings with compact building shape to assess its impact on energy performance.

Keywords: building geometry, energy efficiency, heat gain, heat loss

Procedia PDF Downloads 473

Authors: Zihuan (Dylan) Wang

Abstract:

This paper analyzes the formation of human food aversion from a biological perspective. It points out that this biased behavior is formed through the accumulation of long-term survival and life experiences. By introducing the "Food Chain Energy Pyramid" model and the analogous deduction of the "Human Food Aversion Pyramid," with energy conversion efficiency as the primary reason, it analyzes the underlying reasons for the formation of food preferences. Food industry professionals can gain inspiration from this article to combine the theory presented with their expertise in order to leverage product quality and promote environmentally conscious practices.

Keywords: food aversion, food preference, energy conversion efficiency, food and culture, nutrition, research and development

Procedia PDF Downloads 27

Authors: Alaa Osman, Sara Elgazzar, Breksal Elmiligy

Abstract:

The Supply Chain Operation Reference (SCOR) model is considered one of the most widely implemented supply chain performance measurement systems (SCPMSs). Several studies have been proposed on the SCOR model adaptation in developed countries context; while there is a limited availability of previous work on the SCPMSs application generally and the SCOR model specifically in developing nations. This paper presents a research agenda on the SCOR model adaptation in the developing countries. It aims at investigating the challenges of adapting the SCOR model to manage and measure supply chain performance in developing countries. The research will exemplify the system in the Egyptian automotive sector to gain a comprehensive understanding of how the application of the SCOR model can affect the performance of automotive companies in Egypt, with a necessary understanding of challenges and obstacles faced the adaptation of the model in the Egyptian supply chain context. An empirical study was conducted on the Egyptian automotive sector in three companies considering three different classes: BMW, Hyundai and Brilliance. First, in-depth interviews were carried out to gain an insight into the implementation and the relevance of the concepts of supply chain management and performance measurement in the Egyptian automotive industry. Then, a formal survey was designed based on the SCOR model five main processes (plan, source, make, deliver and return) and best practices to investigate the challenges and obstacles faced the adaptation of the SCOR model in the Egyptian automotive supply chain. Finally, based on the survey results, the appropriate best practices for each process were identified in order to overcome the SCOR model adaptation challenges. The results showed that the implementation of the SCOR model faced different challenges and unavailability of the required enablers. The survey highlighted the low integration of end-to-end supply chain, lacks commitment for the innovative ideas and technologies, financial constraints and lack of practical training and support as the main challenges faced the adaptation of the SCOR model in the Egyptian automotive supply chain. The research provides an original contribution to knowledge by proposing a procedure to identify challenges encountered during the process of SCOR model adoption which can pave a way for further research in the area of SCPMSs adaptation, particularly in the developing countries. The research can help managers and organizations to identify obstacles and difficulties of the SCOR model adaptation, subsequently this can facilitate measuring the improved performance or changes in the organizational performance.

Keywords: automotive sector, developing countries, SCOR model, supply chain performance

Procedia PDF Downloads 341

Authors: N. C. Ghosh, Niladri Das, Prolay Mondal, Ranajit Ghosh

Abstract:

Groundwater quality deterioration due to human activities has become a prime factor of modern life. The major concern of the study is to access spatial variation of groundwater quality and to identify the sources of groundwater chemicals and its impact on human health of the concerned area. Multivariate statistical techniques, cluster, principal component analysis, and hydrochemical fancies are been applied to measure groundwater quality data on 14 parameters from 107 sites distributed randomly throughout the Birbhum district. Five factors have been extracted using Varimax rotation with Kaiser Normalization. The first factor explains 27.61% of the total variance where high positive loading have been concentrated in TH, Ca, Mg, Cl and F (Fluoride). In the studied region, due to the presence of basaltic Rajmahal trap fluoride contamination is highly concentrated and that has an adverse impact on human health such as fluorosis. The second factor explains 24.41% of the total variance which includes Na, HCO₃, EC, and SO₄. The last factor or the fifth factor explains 8.85% of the total variance, and it includes pH which maintains the acidic and alkaline character of the groundwater. Hierarchical cluster analysis (HCA) grouped the 107 sampling station into two clusters. One cluster having high pollution and another cluster having less pollution. Moreover hydromorphological facies viz. Wilcox diagram, Doneen’s chart, and USSL diagram reveal the quality of the groundwater like the suitability of the groundwater for irrigation or water used for drinking purpose like permeability index of the groundwater, quality assessment of groundwater for irrigation. Gibb’s diagram depicts that the major portion of the groundwater of this region is rock dominated origin, as the western part of the region characterized by the Jharkhand plateau fringe comprises basalt, gneiss, granite rocks.

Keywords: correlation, factor analysis, hydrological facies, hydrochemistry

Procedia PDF Downloads 185

Authors: Amir Mahdavi

Abstract:

In this paper a highly linear CMOS low noise amplifier (LNA) for ultra-wideband (UWB) applications is proposed. The proposed LNA uses a linearization technique to improve second and third-order intercept points (IIP3). The linearity is cured by repealing the common-mode section of all intermodulation components from the cascade topology current with optimization of biasing current use symmetrical and asymmetrical circuits for biasing. Simulation results show that maximum gain and noise figure are 6.9dB and 3.03-4.1dB over a 3.1–10.6 GHz, respectively. Power consumption of the LNA core and IIP3 are 2.64 mW and +4.9dBm respectively. The wideband input impedance matching of LNA is obtained by employing a degenerating inductor (|S11|<-9.1 dB). The circuit proposed UWB LNA is implemented using 0.18 μm based CMOS technology.

Keywords: highly linear LNA, low-power LNA, optimal bias techniques

Procedia PDF Downloads 257

Authors: Zichun Chu

Abstract:

The issue of tribal poverty has always attracted attentions. Due to social and economic difficulties, the indigenous people's personal development and tribal development have been greatly restricted. Past studies have pointed out that poverty may come from a lack of education. The United Nations Sustainable Development Goals (SDGs) also stated that if we are to solve the poverty problem, providing education widely is an important key. According to the theory of intellectual capital adaptation, “being capable” and “willing to do” are the keys of development. Therefore, we can say that the "ability" and "will" of tribal residents for their tribal development is the core concern of the tribal development. This research was designed to investigate the career choice development model of indigenous tribe people by investigating the current status of human capital, social capital, and cultural capital of tribal residents. This study collected 327 questionnaires (70% of total households) from Truku tribe to answer the research question: Did education help them for job choosing decisions from the aspects of human capital, social capital, and cultural capital in tribal status. This project highlighted the ‘single tribal research approach’ to gain an in-depth understanding of the human capital formed under the unique culture of the tribe (Truku tribe). The results show that the education level of most research participants was high school, very few high school graduates chose to further their education to college level; due to the lack of education of their parents, the social capital was limited to support them for jobs choice, most of them work for labor and service industries; however, their culture capital was comparably rich for works, the sharing culture of Taiwanese indigenous people made their work status stable. The results suggested that we should emphasize more on the development of vocational education based on the tribe’s location and resources. The self-advocacy of indigenous people should be developed so that they would gain more power on making career decisions. This research project is part of a pilot project called “INDIGENOUS PEOPLES, POVERTY, AND DEVELOPMENT,” sponsored by the National Science and Technology Council of Taiwan. If this paper were accepted to present in the 2023 ICIP, it would be lovely if a panel is formed for me and other co-researchers (Chuanju Cheng, Chih-Yuan Weng, and YiXuan Chen), for the audience will be able to get a full picture of this pilot project.

Keywords: career choices, career model, indegenous career development, indigenous education, tribe

Procedia PDF Downloads 57

Authors: Ana Paola Echavarria, Mariuxi Medina, Haydelba D'Armas, Carmita Jaramillo, Diana San Martin

Abstract:

The use of medicinal plants is one of the oldest and most extended medical therapies that goes back to prehistoric times, and nowadays, they are also used in the preparation of phytopharmaceuticals with options to cure diseases. The test for the determination of fungi was carried out in the Pharmacy Pilot Plant (treatment of the leaves of the plant species) and the Microbiology Laboratory (determination of fungi of the plant species, using growth medium called Sabouraud agar plus the vegetal sample), of the Academic Unit of Chemical Sciences and Health, of the Universidad Tecnica de Machala. Subsequently, colony counting was performed, both macroscopic, which is determined in the growth medium of the seeding, and microscopic, to identify the germinative forms using blue lactophenol. The procedure was repeated in duplicate to replicate the results data. The determination of the total fungal content of the following plant species was evaluated: Cymbopogon citratus (lemon verbena), Melissa officinalis (lemon balm), Taraxacum officinale (dandelion), Artemisia absinthium (absinthe), Piper carpunya (guaviduca), Moringa oleifera (moringa), Coriandrum sativum (coriander), Momordica charantia (achochilla), Borago officinalis (borage), Aloysia citriodora (cedron), Ambrosia artemisifolia (altamisa) and Ageratum conyzoides (mastrante). The results obtained showed that all the samples of the twelve plant species studied developed filamentous fungi, with great variability of them, within the permissible limits and contemplated by the Ecuadorian Institute of Normalization (INEN), being suitable as raw material for its use in the preparation of nutraceuticals and medicinal products or phytodrugs; with the exception of A. conyzoides (mastranto) which is the only species that exceeds the regulation in the average of dilutions.

Keywords: colonies, fungi, medicinal plants, microbiological quality, Sabouraud agar

Procedia PDF Downloads 119

Authors: Nur Aziza Luxfiati

Abstract:

Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.

Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development

Procedia PDF Downloads 132

Authors: Zakarya Kourdi, Mohammed Khaouani, Benyounes Bouazza, Ahlam Guen-Bouazza, Amine Boursali

Abstract:

In this paper, we have evaluated the thermal effect for high electron mobility transistors (HEMTs) heterostructure InAlN/GaN with a gate length 30nm high-performance. It also shows the analysis and simulated these devices, and how can be used in different application. The simulator Tcad-Silvaco software has used for predictive results good for the DC, AC and RF characteristic, Devices offered max drain current 0.67A; transconductance is 720 mS/mm the unilateral power gain of 180 dB. A cutoff frequency of 385 GHz, and max frequency 810 GHz These results confirm the feasibility of using HEMTs with InAlN/GaN in high power amplifiers, as well as thermal places.

Keywords: HEMT, Thermal Effect, Silvaco, InAlN/GaN

Procedia PDF Downloads 441

Authors: Heejung Lee

Abstract:

In a highly competitive environment, it becomes more important to shorten the whole business process while delivering or even enhancing the business value to the customers and suppliers. Although the workflow management systems receive much attention for its capacity to practically support the business process enactment, the effective workflow modeling method remain still challenging and the high degree of process complexity makes it more difficult to gain the short lead time. This paper presents a workflow structuring method in a holistic way that can reduce the process complexity using activity-needs and formal concept analysis, which eventually enhances the key performance such as quality, delivery, and cost in business process.

Keywords: workflow management, re-engineering, formal concept analysis, business process

Procedia PDF Downloads 384

Authors: Sandro Samir Nasief, Hussein Hamed Ghouz, Mohamed Fathy

Abstract:

A compact ultra-wide band micro-strip MIMO antenna is introduced. The antenna consists of two elements each of size 24X24 mm2 (square millimetre) while the total MIMO size is 58X24 mm2 after the spacing between MIMO elements and adding a decouple circuit. The first one covers from 3.29 to 6.9 GHZ using digital ground and the second antenna covers from 8.76 to 13.27 GHZ using defective ground. This type of antenna is used for 3G and 4G applications. The introduction for the antenna structure and the parametric study (reflection coefficients, gain, coupling and decoupling) will be introduced.

Keywords: micro-strip antenna, MIMO, digital ground, defective ground, decouple circuit, bandwidth

Procedia PDF Downloads 329

Authors: Gunnar Oskarsson, Gudjon Helgi Egilsson

Abstract:

Due to globalization, small and medium-sized enterprises (SME) increasingly offer their products and services in foreign markets. The main reasons are either to compensate for a decreased market share in their home market or to exploit opportunities in foreign markets, which are becoming less distant and better accessible than before. International markets are particularly important for companies located in a small economy and offering specialized products. Although more accessible, entering international markets is both expensive and difficult. In order to select the most appropriate markets, it is, therefore, important to gain an insight into the factors that have an impact on success, or potential failure. Although there has been a reasonable volume of research into the theory of internationalization, there is still a need to gain further understanding of the decision-making process of SMEs in small economies and the most important characteristics that distinguish between success and failure. The main objective of this research is to enhance knowledge on the internationalization of SMEs, including the drivers for the decision to internationalize, and the most important factors contributing to success in their internationalization activities. A qualitative approach was found to be most appropriate for this kind of research, with the objective of gaining a deeper understanding and discovering factors which impact a company’s decision-making and potential success. In-depth interviews were conducted with 14 companies in different industries located in Iceland, a country extensively dependent on export revenues. The interviews revealed several factors as drivers of internationalization and, not surprisingly, the most frequently mentioned source of motivation was that the local market is inadequate to maintain a sustainable operation. Good networking relationships were seen as a particular priority for potential success, searching for new markets was mainly carried out through the internet, although sales exhibitions and sales trips were also considered important. When it comes to the final decision as to whether a market should be considered for further analysis, economy, labor cost, legal environment, and cultural barriers were the most common factors to be weighted. The ultimate answer to successful internationalization, however, is largely dependent on a coordinated and experienced management team. The main contribution of this research is offering an insight into factors affecting decision-making in the internationalization process of SMEs, based on the opinion and experience of managers of SMEs in a small economy.

Keywords: internationalization, success factors, small and medium-sized enterprises (SMEs), drivers, decision making

Procedia PDF Downloads 217

Authors: Samir Kittaniy

Abstract:

The “Mirrors of Princes” is considered one of the most important literary types in Arabic and Islamic heritage. The term can be found in various types of “Adab”. The paper deals with the phrase: “Mirrors of princes” itself, showing its nature and the extent of its spread among researchers. Thus, the article relates to one of the main cultural pillars of the literary heritage. Creative individuals within the framework of this type of “Adab” have viewed the rulers as the ultimate goal they try to reach in their classification efforts, with the aim of educating, entertaining and amusing. Most literary classifications were submitted as a gift to the rulers, in an attempt to get closer to them. Pragmatic moral and political advices were among the most prominent issues to gain the approval of rulers.

Keywords: Islam, Arabic, literature, Middle East, mirrors of princes

Procedia PDF Downloads 500

Authors: Mannahel Iftikhar, Sara Saeed, Iqra Faryad, Muhammad Subhan

Abstract:

This paper describes the design of a low-cost dual-band stacked rhombus-shaped slot patch antenna. The antenna is designed on L-band with a GPS (L2) bandwidth of 0.08 GHz centered at 1.207 GHz and a GPS (L1) bandwidth of 0.23 GHz centered at 1.575 GHz. The antenna’s dimensions are 8.02×8.02 cm². The antenna has a 3 dB beamwidth of 100° at 1.204 GHz and 117° at 1.575 GHz. The gain of this antenna is 6.5 dBi at 1.575 GHz and 6.43 dBi at 1.207 GHz. The antenna is designed using commercial off-the-shelf components and can be used in any global navigation satellite system receiver covering L1 and L2 communication bands.

Keywords: circular polarization, enhanced beamwidth, stacked patches, GNSS, satellite communication

Procedia PDF Downloads 79

Authors: Zineb Benouahmane, Zhang Lifeng

Abstract:

Experimental oxidation tests at high temperature (1300°C-1500°C) on α-SiC samples have been performed with different holding times and atmosphere (air, argon). Oxidized samples were then analyzed using X-ray photoelectron spectroscopy coupled to SEM and DAKTEK surface profiler verification. The oxidation rate and the mas gain were found to increase with temperature and holding times, corresponding to a passive oxidation regime which lead to the formation of SiO2 layer. The sessile drop method is employed in order to measure the wetting angles between Si/SiC system at high temperature (1430°C-1550°C). Contact angle can be varied between 44 °C to 85°C, by controlling the oxygen content in α-SiC. Increasing the temperature occurred the infiltration of liquid silicon and deoxidation of the coating.

Keywords: oxidation, wettability, silicon, SiC

Procedia PDF Downloads 432

Authors: Alejandro Arnaldo Barroso Martinez

Abstract:

Unlike sex, which is constituted by anatomic-physiological differences, gender is a social construction. Our thoughts and behaviors as females and males are not etched in stone by our biology but rather from how society expects us to think and behave based on our sex assignment in the womb. Social expectations, values, and roles are taken on by individuals and shape the ways considered acceptable and linked to our bodies, feelings, and interpersonal relationships. Furthermore, these evolve into dire consequences for those who do not meet these disciplinary, economic, and cultural standards. Then, the social learning of gender identity implies the individual’s psychological sense of being, and it might be highly linked to a sense of life and suicide attempts. As a result, suicide has been considered a gender issue with differences in the rates and means used by men and women worldwide. Nevertheless, there has been a misunderstanding of the meaning of being male or female in a particular context and how it becomes a risk process for suicide attempts. For this reason, the general objective of the current research is to explain how this process occurs in Cuba. From a Critical Sociology and Social Psychology, a qualitative methodology was developed through six case studies and qualitative in-depth interviews. The analysis is focused on the sequence and interplay between two dimensions of meaning: signifiers and voices. Findings show that the risk process of suicide attempts in Cuba means some patriarchal beliefs and practices as part of informal educational models and some positivist practices in mental health attention. Findings also show that community relations create a sense of belonging, and it is a protection against suicide attempts in Cuba. Those frames of signifiers and voices explain in both males and females but differently when and how they are suffering from isolation, violence, the normalization of emotional awareness, and emotional distress expression. Suicide prevention programs should take gender learning into account as a cultural process.

Keywords: social constructions, gender identity, meanings, suicide attempt

Procedia PDF Downloads 186

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

Abstract:

In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

Procedia PDF Downloads 78

Authors: Hediyeh Talebi, Shokoofeh Ghiam, Changiz Eslahchi

Abstract:

Traditionally, Alzheimer’s disease research has focused on genes with significant fold changes, potentially neglecting subtle but biologically important alterations. Our study introduces an integrative approach that highlights genes crucial to underlying biological processes, regardless of their fold change magnitude. Alzheimer's Single-cell RNA-seq data related to the peripheral blood mononuclear cells (PBMC) was extracted from the Gene Expression Omnibus (GEO). After quality control, normalization, scaling, batch effect correction, and clustering, differentially expressed genes (DEGs) were identified with adjusted p-values less than 0.05. These DEGs were categorized based on cell-type, resulting in four datasets, each corresponding to a distinct cell type. To distinguish between cells from healthy individuals and those with Alzheimer's, an adversarial autoencoder with a classifier was employed. This allowed for the separation of healthy and diseased samples. To identify the most influential genes in this classification, the weight matrices in the network, which includes the encoder and classifier components, were multiplied, and focused on the top 20 genes. The analysis revealed that while some of these genes exhibit a high fold change, others do not. These genes, which may be overlooked by previous methods due to their low fold change, were shown to be significant in our study. The findings highlight the critical role of genes with subtle alterations in diagnosing Alzheimer's disease, a facet frequently overlooked by conventional methods. These genes demonstrate remarkable discriminatory power, underscoring the need to integrate biological relevance with statistical measures in gene prioritization. This integrative approach enhances our understanding of the molecular mechanisms in Alzheimer’s disease and provides a promising direction for identifying potential therapeutic targets.

Keywords: alzheimer's disease, single-cell RNA-seq, neural networks, blood biomarkers

Procedia PDF Downloads 35

Authors: Gaurav Upadhyay, Nand Kishore, Prashant Ranjan, V. S. Tripathi, Shivesh Tripathi

Abstract:

A frequency reconfigurable multiband antenna for intelligent transportation system (ITS) applications is proposed in this paper. A PIN-diode is used for reconfigurability. Centre frequencies are 1.38, 1.98, 2.89, 3.86, and 4.34 GHz in “ON” state of Diode and 1.56, 2.16, 2.88, 3.91 and 4.45 GHz in “OFF” state. Achieved maximum bandwidth is 18%. The maximum gain of the proposed antenna is 2.7 dBi in “ON” state and 3.95 dBi in “OFF” state of the diode. The antenna is simulated, fabricated, and tested in the lab. Measured and simulated results are in good confirmation.

Keywords: ITS, multiband antenna, PIN-diode, reconfigurable

Procedia PDF Downloads 317

Authors: Mingde Du, Dong Han

Abstract:

A low profile, dual polarized, slot coupled patch antenna is designed and developed in this paper. The antenna has a measured bandwidth of 17.2% for return loss > 15 dB and pair ports isolation >23 dB. The gain of the antenna is over 10 dBi and the half power beam widths (HPBW) of the antenna are 80±3^o in the horizontal plane and 39±2^o in the vertical plane. The cross polarization discrimination (XPD) is less than 20 dB in HPBW. Within the operating band, the performances of good impedance match, high ports isolation, low cross polarization, and stable radiation patterns are achieved.

Keywords: dual polarized, patch antenna, slot coupled, base station antenna

Procedia PDF Downloads 426

Authors: Huseyin Guler, Cigdem Kosar

Abstract:

The aim of this study is to propose Bridge estimator for seasonal unit root tests. Seasonality is an important factor for many economic time series. Some variables may contain seasonal patterns and forecasts that ignore important seasonal patterns have a high variance. Therefore, it is very important to eliminate seasonality for seasonal macroeconomic data. There are some methods to eliminate the impacts of seasonality in time series. One of them is filtering the data. However, this method leads to undesired consequences in unit root tests, especially if the data is generated by a stochastic seasonal process. Another method to eliminate seasonality is using seasonal dummy variables. Some seasonal patterns may result from stationary seasonal processes, which are modelled using seasonal dummies but if there is a varying and changing seasonal pattern over time, so the seasonal process is non-stationary, deterministic seasonal dummies are inadequate to capture the seasonal process. It is not suitable to use seasonal dummies for modeling such seasonally nonstationary series. Instead of that, it is necessary to take seasonal difference if there are seasonal unit roots in the series. Different alternative methods are proposed in the literature to test seasonal unit roots, such as Dickey, Hazsa, Fuller (DHF) and Hylleberg, Engle, Granger, Yoo (HEGY) tests. HEGY test can be also used to test the seasonal unit root in different frequencies (monthly, quarterly, and semiannual). Another issue in unit root tests is the lag selection. Lagged dependent variables are added to the model in seasonal unit root tests as in the unit root tests to overcome the autocorrelation problem. In this case, it is necessary to choose the lag length and determine any deterministic components (i.e., a constant and trend) first, and then use the proper model to test for seasonal unit roots. However, this two-step procedure might lead size distortions and lack of power in seasonal unit root tests. Recent studies show that Bridge estimators are good in selecting optimal lag length while differentiating nonstationary versus stationary models for nonseasonal data. The advantage of this estimator is the elimination of the two-step nature of conventional unit root tests and this leads a gain in size and power. In this paper, the Bridge estimator is proposed to test seasonal unit roots in a HEGY model. A Monte-Carlo experiment is done to determine the efficiency of this approach and compare the size and power of this method with HEGY test. Since Bridge estimator performs well in model selection, our approach may lead to some gain in terms of size and power over HEGY test.

Keywords: bridge estimators, HEGY test, model selection, seasonal unit root

Procedia PDF Downloads 302