Search results for: classification tree

Authors: Daniel Assefa, Engeda Dessalegn, Chetan Chauhan

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Moringa stenopetala is a socioeconomic valued tree that is widely available and cultivated in the Southern part of Ethiopia. The leaves have been traditionally used as a food source with high nutritional and medicinal values. The present work was carried out to evaluate the effect of thermal treatment on the total phenolic content, antioxidant and alpha-amylase inhibition activities of aqueous leaf extracts during maceration and different decoction time interval (5, 10 and 15 min). The total phenolic content was determined by the Folin-ciocalteu methods whereas antioxidant activities were determined by 2,2-diphenyl-1-picryl-hydrazyl(DPPH) radical scavenging, reducing power and ferrous ion chelating assays and alpha-amylase inhibition activity was determined using 3,5-dinitrosalicylic acid method. Total phenolic content ranged from 34.35 to 39.47 mgGAE/g. Decoction for 10 min extract showed ferrous ion chelating (92.52), DPPH radical scavenging (91.52%), alpha-amylase inhibition (69.06%) and ferric reducing power (0.765), respectively. DPPH, reducing power and alpha-amylase inhibition activities showed positive linear correlation (R2=0.853, R2= 0.857 and R2=0.930), respectively with total phenolic content but ferrous ion chelating activity was found to be weakly correlated (R2=0.481). Based on the present investigation, it could be concluded that major loss of total phenolic content, antioxidant and alpha-amylase inhibition activities of the crude leaf extracts of Moringa stenopetala leaves were observed at decoction time for 15 min. Therefore, to maintain the total phenolic content, antioxidant, and alpha-amylase inhibition activities of leaves, cooking practice should be at the optimum decoction time (5-10 min).

Keywords: alpha-amylase inhibition, antioxidant, Moringa stenopetala, total phenolic content

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

Procedia PDF Downloads 344

Authors: Sangbok Lee

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There has been much effort on process improvement for outpatient clinics to provide quality and acute care to patients. One of the efforts is no-show analysis or prediction. This work analyzes patient no-shows along with patient health conditions. The health conditions refer to clinical symptoms that each patient has, out of the followings; hyperlipidemia, diabetes, metastatic solid tumor, dementia, chronic obstructive pulmonary disease, hypertension, coronary artery disease, myocardial infraction, congestive heart failure, atrial fibrillation, stroke, drug dependence abuse, schizophrenia, major depression, and pain. A dataset from a regional hospital is used to find the relationship between the number of the symptoms and no-show probabilities. Additional analysis reveals how each symptom or combination of symptoms affects no-shows. In the above analyses, cross-classification of patients by age and gender is carried out. The findings from the analysis will be used to take extra care to patients with particular health conditions. They will be forced to visit clinics by being informed about their health conditions and possible consequences more clearly. Moreover, this work will be used in the preparation of making institutional guidelines for patient reminder systems.

Keywords: healthcare system, no show analysis, process improvment, statistical data analysis

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Authors: Agata Zakrzewska, Dominik Kopeć, Adrian Ochtyra

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The growing number of new cameras, sensors, and research methods allow for a broader application of thermal data in remote sensing vegetation studies. The aim of this research was to check whether it is possible to use thermal infrared data with a spectral range (3.6-4.9 μm) obtained during the day and the night to assess the health condition of selected species of deciduous trees in an urban environment. For this purpose, research was carried out in the city center of Warsaw (Poland) in 2020. During the airborne data acquisition, thermal data, laser scanning, and orthophoto map images were collected. Synchronously with airborne data, ground reference data were obtained for 617 studied species (Acer platanoides, Acer pseudoplatanus, Aesculus hippocastanum, Tilia cordata, and Tilia × euchlora) in different health condition states. The results were as follows: (i) healthy trees are cooler than trees in poor condition and dying both in the daytime and nighttime data; (ii) the difference in the canopy temperatures between healthy and dying trees was 1.06oC of mean value on the nighttime data and 3.28oC of mean value on the daytime data; (iii) condition classes significantly differentiate on both daytime and nighttime thermal data, but only on daytime data all condition classes differed statistically significantly from each other. In conclusion, the aerial thermal data can be considered as an alternative to hyperspectral data, a method of assessing the health condition of trees in an urban environment. Especially data obtained during the day, which can differentiate condition classes better than data obtained at night. The method based on thermal infrared and laser scanning data fusion could be a quick and efficient solution for identifying trees in poor health that should be visually checked in the field.

Keywords: middle wave infrared, thermal imagery, tree discoloration, urban trees

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Authors: Song Xinze, Cai Kejian

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To further explore the application of waste plastics in asphalt pavement, this paper begins with the classification and characteristics of waste plastics. It then provides a state-of-the-art review of the preparation methods and processes of waste plastic modifiers, waste plastic-modified asphalt, and waste plastic-modified asphalt mixtures. The paper also analyzes the factors influencing the compatibility between waste plastics and asphalt and summarizes the performance evaluation indicators for waste plastic-modified asphalt and its mixtures. It explores the research approaches and findings of domestic and international scholars and presents examples of waste plastics applications in pavement engineering. The author believes that there is a basic consensus that waste plastics can improve the high-temperature performance of asphalt. The use of cracking processes to solve the storage stability of waste plastic polymer-modified asphalt is the key to promoting its application. Additionally, the author anticipates that future research will concentrate on optimizing the recycling, processing, screening, and preparation of waste plastics, along with developing composite plastic modifiers to improve their compatibility and long-term performance in asphalt pavements.

Keywords: waste plastics, asphalt pavement, asphalt performance, asphalt modification

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Authors: Siao-Wei Jiang, Boy-Young Hsieh, Ching-Liang Hsieh, Cheng-Yung Lin

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The problems of multiple drug resistance in the pig farming industry have been emphasized in recent years. Diarrhea syndrome is common in weaning piglets and often treated with antibiotics as a feed additive, leading to the rapid spread of antibiotic resistance and posing high health risks to humans. The study aimed to alleviate diarrhea syndrome with traditional herbal medicine, Xiang Sha Liu Jun Zi Tang, whose effects enhanced digestive function. Piglets at 4 weeks old with stool classified to Bristol stool classification type 6 or type 7 were randomly divided into the control group, group A (1% of Xiang Sha Liu Jun Zi Tang) and group B (0.1% Colistin). The piglets were administrated for 7 days, and their weight, feed intake, and stool score were recorded daily before and after the trial. The results showed that the diarrhea index score in group A and group B improved significantly compared to the control group, indicating that Xiang Sha Liu Jun Zi Tang may have the same effect on alleviating diarrhea syndrome as Colistin, and it may be another replacement for antibiotics.

Keywords: pig, diarrhea, herbal medicine, Xiang Sha Liu Jun Zi Tang

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Authors: Blessing Mavhuru, Nthaduleni Nethengwe, Hector Chikoore, Onyango Beneah Daniel Odhiambo

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The main objective of this study was to classify land use/cover and how it has changed in Nzhelele Valley Limpopo Province, South Africa. The study aimed to identify and analyse the types of land use/cover in the years 2005, 2010, and 2015 with a view to assess the impact on soil erosion over time. Using GIS, the changes within land use/cover were assessed through the classification of satellite images. The study area was classified into four major land cover/use classes, which are vegetation, gravel road, built up land and agricultural fields. Over the period 2005-2015 the resultant land use/cover demonstrated (i) a significant increase (12%) for vegetation cover, (ii) a significant decrease in agriculture (16%) land use/cover, (iii) increase in built-up land (1%), as well as (iv) an increase in gravel roads (3%). This study envisages assisting policy makers in decision making on land use management for Nzhelele Valley.

Keywords: land use, land cover, change, soil erosion

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Authors: Sabra Saeidi

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This research focuses on the historical techniques associated with the lajevardina and Haft-Rangi production methods in creating tiles, with emphasis on the identification of the techniques of inserting gold sheets on the surface of such historical glazed tiles. In this regard, firstly, the history of the production of enamel, gold plated, and Lajevardina glazed pottery work made during the Khwarizmanshahid and Mongol era (eleventh to the thirteenth century) have been assessed to reach a better understanding of the background and the history associated with historical glazing methods. After the historical overview of the production technique of glazed pottery work and introductions of the civilizations using those techniques, we focused on the niches production methods of enamel and Lajevardina glazing, which are two categories of decorations usually found in tiles. Next, a general classification method for various types of gilt tiles has been introduced, which is applicable to the tile works up to Safavid period (Sixteenth to the seventeenth century). Gilded lajevardina glazed tiles, gilt Haft-Rangi tiles, monolithic glazed gilt tiles, and gilt mosaic tiles are included in the categories.

Keywords: gilt tiles, Islamic art, Iranian art, historical studies, gilding

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Authors: D. Madhushanka, Y. Liu, H. C. Fernando

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Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

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Authors: Qiang Zhang, Xiaojian Hu1

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Intersection is the place where vehicles and pedestrians must pass through, turn and evacuate. Obtaining the motion data of vehicles near the intersection is of great significance for transportation research. Since there are usually many targets and there are more conflicts between targets, this makes it difficult to obtain vehicle motion parameters in traffic videos of intersections. According to the characteristics of traffic videos, this paper applies video technology to realize the automated track, count and trajectory extraction of vehicles to collect traffic data by roadside surveillance cameras installed near the intersections. Based on the video recognition method, the vehicles in each lane near the intersection are tracked with extracting trajectory and counted respectively in various degrees of occlusion and visibility. The performances are compared with current recognized CPU-based algorithms of real-time tracking-by-detection. The speed of the presented system is higher than the others and the system has a better real-time performance. The accuracy of direction has reached about 94.99% on average, and the accuracy of classification and statistics has reached about 75.12% on average.

Keywords: tracking and statistics, vehicle, signalized intersection, motion parameter, trajectory

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Authors: S. Bayona, J. Nunez, D. Paez, C. Diaz

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The application of Lean manufacturing tools continues to be an effective solution for increasing productivity, reducing costs and eliminating waste in the manufacture of goods and services. This article analyzes the production process of a hot asphalt manufacturing company from an administrative and technical perspective. Three main phases were analyzed, the first phase was related to the determination of the risk priority number of the main operations in asphalt mix production process by an FMEA (Failure Mode Effects Analysis), in the second phase the Value Stream Mapping (VSM) of the production line was performed and in the third phase a SWOT (Strengths, Weaknesses Opportunities, Threats) matrix was constructed. Among the most valued failure modes were the lack training of workers in occupational safety and health issues, the lack of signaling and classification of granulated material, and the overweight of vehicles loaded. The analysis of the results in the three phases agree on the importance of training operational workers, improve communication with external actors in order to minimize delays in material orders and strengthen control suppliers.

Keywords: asphalt, lean manufacturing, productivity, process

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Authors: Arun Jyothi Bheemagani, Chakrapani Pullagummi, Anupalli Roja Rani

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Exploration of the chemical constituents of the plants and pharmacological screening may provide us the basis for the development of novel agents. Plants have provided us some of the very important life saving drugs used in the modern medicine. The aim of our work was to screen the phytochemical constituents and antimicrobial and antioxidant activities of methanol extract of leaves of Annona cherimola Mill plant from Tirumala forest, Tirupathi. It was originally called Chirimuya by the Inca people who lived where it was growing in the Andes of South America, is an edible fruit-bearing species of the genus Annona from the family Annonaceae. Annona cherimola Mill is a multipurpose tree with edible fruits and is one of the sources of the medicinal products. The antibacterial activity was measured by agar well diffusion method; the diameter of the zone of bacterial growth inhibition was measured after incubation of plates. The inhibitory effect was studied against the pathogenic bacteria (Klebsiella pneumonia, Bacillus subtilis, Staphylococcus aureus and Escherichia coli (E. coli). Antioxidant assays were also performed for the same extracts by spectrophotometric methods using known standard antioxidants as reference. The studied plant extracts were found to be very effective against the pathogenic microorganisms tested. The methanolic extract of Annona cherimola Mill from showed maximum activity against Escherichia coli and Staphylococcus aureus and the least concentration required showing the activity was 0.5mg/ml. Phytochemical screening of the plants revealed the presence of flavonoids, alkaloids, steroids and carbohydrates. Good presence of antioxidants was also found in the methanolic extracts.

Keywords: annona cherimola, phytochemicals, antioxidant and antibacterial activity, methanol extract

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Authors: Lindelwa Mngomezulu, Tonderai Muchenje

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Over the decades, E-mails provide easy, fast and timely communication enabling businesses and state owned agencies to communicate with their stakeholders and with their own employees in real-time. Moreover, since the launch of Microsoft office 365 and many other clouds based E-mail services, many businesses have been migrating from the on premises E-mail services to the cloud and more precisely since the beginning of the Covid-19 pandemic, there has been a significant increase of E-mails utilization, which then leads to the increase of cyber-attacks. In that regard, E-mail security has become very important in the E-mail transportation to ensure that the E-mail gets to the recipient without the data integrity being compromised. The classification of the features to enhance E-mail security for further from the enhanced cyber-attacks as we are aware that since the technology is advancing so at the cyber-attacks. Therefore, in order to maximize the data integrity we need to also maximize security of the E-mails such as enhanced E-mail authentication. The successful enhancement of E-mail security in the future may lessen the frequency of information thefts via E-mails, resulting in the data of South African State-owned agencies not being compromised.

Keywords: e-mail security, cyber-attacks, data integrity, authentication

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Authors: Eugene Stepanov, Arkadi Ponossov

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Many mathematical models used in biological and other applications are ill-posed. The reason for that is the nature of differential equations, where the nonlinearities are assumed to be step functions, which is done to simplify the analysis. Prominent examples are switched systems arising from gene regulatory networks and neural field equations. This simplification leads, however, to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid feedback controls to regularize the problem. Roughly speaking, one attaches a finite state control (‘automaton’), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. This ‘hybridization’ is shown to regularize the original switched system and gives rise to efficient hybrid numerical schemes. Several examples are provided in the presentation, which supports the suggested analysis. The method can be of interest in other applied fields, where differential equations contain step-like nonlinearities.

Keywords: hybrid feedback control, ill-posed problems, singular perturbation analysis, step-like nonlinearities

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Authors: Y. Cochet, A. Achim, Tom Flatman, J-C. Domec, J. Ogée, L. Wingate, Ram Oren

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It is accepted that atmospheric CO2 concentration will increase in the future. For the past 30 years, researchers have used FACE (Free-Air Carbon Dioxide Enrichment) facilities to study the development of terrestrial ecosystems under elevated CO2 (eCO2). Forest responses to eCO2 are likely to impact timber industries with potential feedbacks towards the atmosphere. The main objectives of this study were to examine whether eCO2 alone or in combination with N-fertilization alter wood properties and to identify changes in wood anatomy related to water transport. Wood disks were sampled at breast height from mature loblolly pine trees (Pinus taeda L.) harvested at the Duke FACE site (NC, USA). By measuring ring width and intra-ring changes in density (X-ray densitometry) and tracheid size (lumen and cell wall thickness) from pith to bark, the following hypotheses were tested: 1) eCO2 and N-fertilization interact positively to increase significantly above-ground primary productivity; 2) eCO2 and N-fertilization lead to a decrease in density; 3) eCO2 and N-fertilization increase lumen diameter and decrease cell wall thickness, thus affecting water transport capacity. Our results revealed a boost in earlywood tracheid production induced by eCO2 lasting a few years. The following decrease seemed to be buffered by N-fertilization. X-ray profiles did not show a marked decrease in wood density under eCO2 or N-fertilization, although there were changes in cell anatomical properties such as a reduction in cell-wall thickness and an increase in lumen diameter. If such effects of eCO2 are confirmed, forest management strategies for example N-fertilization should be redesigned.

Keywords: wood density, Duke FACE (free-air carbon dioxide enrichment), N fertilization, tree ring

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Authors: Ram Manohar Singh, Meenakshi Gupta

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Various terms such as ‘learning style’, ‘cognitive style’, ‘conceptual style’, ‘thinking style’, ‘intellectual style’ are used in literature to refer to an individual’s characteristic and consistent approach to organizing and processing information. However, style concepts are criticized for mutually overlapping definitions and confusing classification. This confusion should be addressed at the conceptual as well as empirical level. This paper is an attempt to bridge this gap in literature by proposing a new concept: expansive-restrictive intellectual style based on phenomenological analysis of an auto-ethnography and interview of 26 information technology (IT) professionals working in knowledge intensive organizations (KIOs) in India. Expansive style is an individual’s preference to expand his/her horizon of knowledge and understanding by gaining real meaning and structure of his/her work. On the contrary restrictive style is characterized by an individual’s preference to take minimalist approach at work reflected in executing a job efficiently without an attempt to understand the real meaning and structure of the work. The analysis suggests that expansive-restrictive style has three dimensions: (1) field dependence-independence (2) cognitive involvement and (3) epistemological beliefs.

Keywords: expansive, knowledge workers, restrictive, style

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Authors: Maria Konstadinou, Etienne Alderlieste, Anderson Peccin da Silva, Ben Arntz, Leonard van der Bijl, Wouter Verschueren

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The shear strength and compression properties of stiff Boom clay from Belgium at the depth of about 30 m has been investigated by means of cone penetration and laboratory testing. The latter consisted of index classification, constant rate of strain, direct, simple shear, and unconfined compression tests. The Boom clay samples exhibited strong swelling tendencies. The suction pressure was measured via different procedures and has been compared to the expected in-situ stress. The undrained shear strength and OCR profile determined from CPTs is not compatible with the experimental measurements, which gave significantly lower values. The observed response can be attributed to the presence of pre-existing discontinuities, as shown in microscale CT scans of the samples. The results of this study demonstrate that the microstructure of the clay prior to testing has an impact on the mechanical behaviour and can cause inconsistencies in the comparison of the laboratory test results with in-situ data.

Keywords: boom clay, laboratory testing, overconsolidation ratio, stress-strain response, swelling, undrained shear strength

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Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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Authors: F. O. Danquah, F. Frimpong, E. Owusu Danquah, T. Frimpong, J. Adu, S. K. Amposah, P. Amankwaa-Yeboah, N. E. Amengor

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In the face of global concerns such as population increase, climate change, and limited natural resources, sustainable agriculture practices are critical for ensuring food security and environmental stewardship. The study was conducted in the Forest zones of Ghana during the major and minor seasons of 2023 cropping seasons to evaluate maize yield productivity improvement and profitability of integrating Cajanus cajan (pigeonpea) into a maize production system described as a pigeonpea-maize cropping system. This is towards an integrated soil fertility management (ISFM) with a legume shrub pigeonpea for sustainable maize production while improving smallholder farmers' resilience to climate change. A split-plot design with maize-pigeonpea (Pigeonpea-Maize intercrop – MPP and No pigeonpea/ Sole maize – NPP) and inorganic fertilizer rate (250 kg/ha of 15-15-15 N-P2O5-K2O + 250 kg/ha Sulphate of Ammonia (SoA) – Full rate (FR), 125 kg/ha of 15-15-15 N-P2O5-K2O + 125 kg/ha Sulphate of Ammonia (SoA) – Half rate (HR) and no inorganic fertilizer (NF) as control) was used as the main plot and subplot treatments respectively. The results indicated a significant interaction of the pigeonpea-maize cropping system and inorganic fertilizer rate on the growth and yield of the maize with better and similar maize productivity when HR and FR were used with pigeonpea biomass. Thus, the integration of pigeonpea and its biomass would result in the reduction of recommended fertiliser rate to half. This would improve farmers’ income and profitability for sustainable maize production in the face of climate change.

Keywords: agroforestry tree, climate change, integrated soil fertility management, resource use efficiency

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Authors: Elnaz Lashgari, Emel Demircan

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Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: electromyography, manifold learning, ISOMAP, Laplacian Eigenmaps, locally linear embedding

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Authors: Abdul Rochim, Didier Marot, Luc Sibille

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This paper studies the characterization of soil sensibility due to suffusion process by carrying out a series of one-dimensional downward seepage flow tests realized with an erodimeter. Tests were performed under controlled hydraulic gradient in sandy gravel soils. We propose the analysis based on energy induced by the seepage flow to characterize the hydraulic loading and the cumulative eroded dry mass to characterize the soil response. With this approach, the effect of hydraulic loading histories and initial fines contents to soil sensibility are presented. It is found that for given soils, erosion coefficients are different if tests are performed under different hydraulic loading histories. For given initial fines fraction contents, the sensibility may be grouped in the same classification. The lower fines content soils tend to require larger flow energy to the onset of erosion. These results demonstrate that this approach is effective to characterize suffusion sensibility for granular soils.

Keywords: erodimeter, sandy gravel, suffusion, water seepage energy

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Zukhrof Romadhon, Nani Kurniati

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Availability of Spare parts is critical to support maintenance tasks and the production system. Managing spare part inventory deals with some parameters and objective functions, as well as the tradeoff between inventory costs and spare parts availability. Several mathematical models and methods have been developed to optimize the spare part policy. Many researchers who proposed optimization models need to be considered to identify other potential models. This work presents a review of several pertinent literature on spare part inventory optimization and analyzes the gaps for future research. Initial investigation on scholars and many journal database systems under specific keywords related to spare parts found about 17K papers. Filtering was conducted based on five main aspects, i.e., replenishment policy, objective function, echelon network, lead time, model solving, and additional aspects of part classification. Future topics could be identified based on the number of papers that haven’t addressed specific aspects, including joint optimization of spare part inventory and maintenance.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenance

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Authors: Masoud Soltanialvar, Ali Bagherpour

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Documented cases of human infection with H9N2 avian influenza viruses, first detected in 1999 in Hong Kong and China, indicate that these viruses can be directly transmitted from birds to humans. In this study, we characterized the mutation in the Hemagglutinin (HA) genes and proteins that correlates with a shift in affinity of the Hemagglutinin (HA) protein from the “avian” type sialic receptors to the “human” type in 10 Iranian isolates. We delineated the genomes and receptor binding profile of HA gene of some field isolates and established their phylogenetic relationship to the other Asian H9N2 sub lineages. A total of 1200 tissue samples collected from 40 farms located in various states of Iran during 2008 – 2010 as part of a program to monitor Avian Influenza Viruses (AIV) infection. To determine the genetic relationship of Iranian viruses, the Hemagglutinin (HA) genes from ten isolates were amplified and sequenced (by RT-PCR method). Nucleotide sequences (orf) of the (HA) genes were used for phylogenetic tree construction. Deduced amino acid sequences showed the presence of L226 (234 in H9 numbering) in all ten Iranian isolates which indicates a preference to binding of α (2–6) sialic acid receptors, so these Iranian H9N2 viruses have the potential to infect human beings. These isolates showed high degree of homology with 2 human H9N2 isolates A/HK/1073/99, A/HK/1074/99. Phylogenetic analysis of showed that all the HA genes of the Iranian H9N2 viruses fall into a single group within a G1-like sublineage which had contributed as donor of six internal genes to H5N1 highly pathogenic avian influenza. The results of this study indicated that all Iranian viruses have the potential to emerge as highly pathogenic influenza virus, and considering the homology of these isolates with human H9N2 strains, it seems that the potential of these avian influenza isolates to infect human should not be overlooked.

Keywords: influenza virus, hemagglutinin, neuraminidase, Iran

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Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

Abstract:

Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Grzegorz Sierpiński, Ireneusz Celiński, Marcin Staniek

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The article discusses multi modal mobility in contemporary societies as a main planning and organization issue in the functioning of administrative bodies, a problem which really exists in the space of contemporary cities in terms of shaping modern transport systems. The article presents classification of available resources and initiatives undertaken for developing multi modal mobility. Solutions can be divided into three groups of measures–physical measures in the form of changes of the transport network infrastructure, organizational ones (including transport policy) and information measures. The latter ones include in particular direct support for people travelling in the transport network by providing information about ways of using available means of transport. A special measure contributing to this end is a trip planner. The article compares several selected planners. It includes a short description of the Green Travelling Project, which aims at developing a planner supporting environmentally friendly solutions in terms of transport network operation. The article summarizes preliminary findings of the project.

Keywords: mobility, modal split, multimodal trip, multimodal platforms, sustainable transport

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Authors: Siddique Ullah Baig, Alisha Manzoor

Abstract:

The remotest, mountainous, and icy Broghil Valley is a high-profile protected area as a national park, which hosts one of the highest altitude permanent human settlements on the earth. This park hosts a distributed but diverse range of habitats. Due to a lack of infrastructures, higher altitudes, and harsh environmental conditions, poverty-stricken inhabitants mostly rely on its resources, causing ecological dis-balance. This study aims to investigate the environmental degradation of natural resources of the park based on empirical evidence from stakeholders and geoinformatics. The result shows that one-fourth of the park is a gently undulating basin dotted with water bodies / grass, and agricultural land and three fourth is entirely rugged with steep mountains and glaciers. There are virtually no forests as the arid cold tundra climate and high altitude prevent tree growth. Rapid three-decadal land cover changes have led to ecological disequilibrium of the park, narrowing the traditional diverse food base, decreasing the resilience of biodiversity and local livelihoods as crop-land has shifted towards fallow, alpine-grass to peat-land and snow/glacial ice area to bare-soil/rocks. The local community believes in exploiting whatever vegetation or organic material is available for use as food, fodder, and fuel. The permanent presence of the community and limited cost-effective options in the park will be a challenge forever to maintain undisturbed natural processes as the objective of a national park.

Keywords: Broghil National Park, natural resources, environmental degradation, land cover

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Authors: Miguel Ramirez, Ivan Lizarazo

Abstract:

The emergence of various interpretations of sustainability, including weak and strong paradigms, can be traced back to the definition of sustainable development provided in the 1987 Brundtland report and the subsequent evolution of the sustainability concept. However, there has been limited scholarly attention given to clarifying the concept of sustainability within the theoretical and conceptual framework of geography. The discipline has predominantly been focused on understanding the diverse conceptions of sustainability within its epistemological boundaries, resulting in tensions between sustainability paradigms and their associated dimensions, including the incorporation of political perspectives, with particular emphasis on environmental geography's epistemology. In response to this gap, a conceptual framework for sustainability is proposed, effectively integrating spatial and territorial concepts. This framework aims to enhance geography's role in contributing to sustainability by utilizing the land system theory, which is based on the dynamics of land use change. Such an integrated conceptual framework enables incorporating methodological tools such as remote sensing, encompassing various earth observations and fusion methods, and supervised classification techniques. Additionally, it looks for better integration of socioecological information, thereby capturing essential population-related features.

Keywords: geography, sustainability, land change science, territorial sustainability

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Authors: Pei-Jun Xue, Ming-Yu Hsiao

Abstract:

Chinese characters, or hanzi, represent a process of simplifying three-dimensional signs into plane signifiers. From pictograms at the beginning to logograms today, a Han linguist thus classified them into six categories known as the six categories of Chinese characters. Design is a process of signification, and cultural-creative design is a process translating ideas into design with creativity upon culture. Aiming to investigate the process of cultural-creative design transforming cultural text into cultural signs, this study analyzed existing cultural-creative products with the six categories of Chinese characters by treating such products as representations which accurately communicate the designer’s ideas to users through the categorization, simplification, and interpretation of sign features. This is a two-phase pilot study on designing cultural-creative products with the six categories of Chinese characters. Phase I reviews the related literature on the theory of the six categories of Chinese characters investigated and concludes with the process and principles of character evolution. Phase II analyzes the design of existing cultural-creative products with the six categories of Chinese characters and explores the conceptualization of product design.

Keywords: six categories of Chinese characters, cultural-creative product design, cultural signs, cultural product

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