Search results for: hybrid ventilation techniques

Authors: HebatAllah Tarek, Zeyad El-Sayad, Ali F. Bakr

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Surface coating can permit the bulk materials to remain unchanged, whereas the surface functionality is engineered to afford a more required characteristic. Nano-Ceramic coatings are considered ideal coatings on materials that can significantly improve the surface properties, including anti-fouling, self-cleaning, corrosion resistance, wear resistance, anti-scratch, waterproof, anti-acid rain and anti-asphalt. Furthermore, various techniques have been utilized to fabricate a range of different ceramic coatings with more desirable properties on Nano-ceramics, which make the materials usually used in in-service environments and worth mentioning that the practical part of this study will be applied in one of the most important architectural applications due to the contamination-free conditions provided by it in the manufacturing industry. Without cleanrooms, products will become contaminated and either malfunction or infect people with bacteria. Cleanrooms are used for the manufacture of items used in computers, cars, airplanes, spacecraft, televisions, disc players and many other electronic and mechanical devices, as well as the manufacture of medicines, medical devices, and foods. The aim of this study will be to examine the Nano-ceramics on porcelain and glass panels. The investigation will be included fabrications, methods, surface properties and applications in clean rooms. The unfamiliarity in this study is using Nano-ceramics in clean rooms instead of using them on metallic materials.

Keywords: nano-ceramic coating, clean rooms, porcelain, surface properties

Procedia PDF Downloads 109

Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load.

Keywords: cross-organization process mining, process behaviour, path of execution, polynomial regression model

Procedia PDF Downloads 334

Authors: H. Al-Baghli, F. Al-Asfour

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The current applied asphalt technology for Kuwait roads pavement infrastructure is the hot mix asphalt (HMA) pavement, including both pen grade and polymer modified bitumen (PMBs), that is produced and compacted at high temperature levels ranging from 150 to 180 °C. There are no current specifications for warm and cold mix asphalts in Kuwait’s Ministry of Public Works (MPW) asphalt standard and specifications. The process of the conventional HMA is energy intensive and directly responsible for the emission of greenhouse gases and other environmental hazards into the atmosphere leading to significant environmental impacts and raising health risk to labors at site. Warm mix asphalt (WMA) technology, a sustainable alternative preferred in multiple countries, has many environmental advantages because it requires lower production temperatures than HMA by 20 to 40 °C. The reduction of temperatures achieved by WMA originates from multiple technologies including foaming and chemical or organic additives that aim to reduce bitumen and improve mix workability. This paper presents a literature review of WMA technologies and techniques followed by an experimental study aiming to compare the results of produced WMA samples, using a water containing additive (foaming process), at different compaction temperatures with the HMA control volumetric properties mix designed in accordance to the new MPW’s specifications and guidelines.

Keywords: warm-mix asphalt, water-bearing additives, foaming-based process, chemical additives, organic additives

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Authors: Nartan Rajpriya

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City is a multiplex ecological system made up of social, economic and natural sub systems. Green space system is the foundation of the natural system. It is also suitable part of natural productivity in the urban structure. It is dispensable for constructing a high quality human settlements and a high standard ecocity. Ahmedabad is the fastest growing city of India. Today urban green space is under strong pressure in Ahmedabad city. Due to increasing urbanization, combined with a spatial planning policy of densification, more people face the prospect of living in less green residential environments. In this research analyzes the importance of available Green Space at Bodakdev Park, Ahmedabad, using remote sensing and GIS technologies. High resolution IKONOS image and LISS IV data has been used in this project. This research answers the questions like: • Temporal changes in urban green space area. • Proximity to heavy traffic or roads or any recreational facilities. • Importance in terms of health. • Availability of quality infrastructure. • Available green space per area, per sq. km and per total population. This projects incorporates softwares like ArcGIS, Ecognition and ERDAS Imagine, GPS technologies etc. Methodology includes the field work and collection of other relevant data while preparation of land use maps using the IKONOS imagery which is corrected using GPS.

Keywords: urban green space, ecocity, IKONOS, LISS IV

Procedia PDF Downloads 386

Authors: Pankhuri Dagaonkar, Charumani Singh, Poornima Krothapalli, Krishna Karthik

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The backbone of any retail e-commerce success story is a unique design of supply chain network, providing the business an unparalleled speed and scalability. Primary goal of the supply chain strategy is to meet customer expectation by offering fastest deliveries while keeping the cost minimal. Meeting this objective at the large market that India provides is the problem statement that we have targeted here. There are many models and optimization techniques focused on network design to identify the ideal facility location and size, optimizing cost and speed. In this paper we are presenting a tactical approach to optimize cost of an existing network for a predefined speed. We have considered both forward and reverse logistics of a retail e-commerce supply chain consisting of multiple fulfillment (warehouse) and delivery centers, which are connected via sortation nodes. The mathematical model presented here determines if the shipment from a node should get sorted directly for the last mile delivery center or it should travel as consolidated package to another node for further sortation (resort). The objective function minimizes the total cost by varying the resort percentages between nodes and provides the optimal resource allocation and number of sorts at each node.

Keywords: distribution strategy, mathematical model, network design, supply chain management

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Authors: Trias Setiawati, Rizkika Awalia

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The study title is “In Working, Career is not everything: A Case Study of Family Friendly Policies (FFP) on Bank Company.” This study aims to describe the application of FFP in the banking, especially Bank Rakyat Indonesia or BRI (Indonesian People Bank) in Katamso Branch Office in Yogyakarta Katamso Branch Office in Yogyakarta (KBOY) as a support company to create a work-life balance, as well as the achievement of career and family harmony is seen from the work-family conflict faced by the employees. The importance of the application of FFP in an organization is basically to build competitive advantage of a company. This study used qualitative research methods with a case study approach in BRI in KBOY. Data collection techniques used non-participant observation and in-depth structured interviews with three employees. The results showed that FFP is in general adoption and not optimal yet. Optimal FFP policy is not yet implemented; it just in the in-formal policies such as the lack of flexible-time, the lack of daycare, the lack of counseling for employees of personal nature, despite it was the availability of lactation rooms for feeding. The employees found difficulties in balancing between achieving careers at work and reaching family harmony. Not pursued a career does not mean that they do not want to reach a better position, but they do not want to ignore the family harmony because of the hours of work overload.

Keywords: career, family friendly policies, work-family balance, work-family conflict

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Djouhou Fowe Michelle Carole

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In the last few decades, there have been considerable efforts by the international community to develop strategies that reduce global poverty and hunger. Despite the modest success in reducing food insecurity, there are still around 795 million people worldwide who remain undernourished, the majority of whom are in sub-Saharan Africa. In many of these impoverished communities, agriculture still remains one of the most important sectors in driving economic growth and reducing poverty. For the growing population, with higher food demand and fixed agricultural land, sustainable intensification is proposed as an important strategy to respond to the challenges of low yields, environmental degradation, and adaptation to climate change. Adoption of agroforestry technologies is increasingly being promoted as a promising solution. This study was conducted to determine the perceptions of the Cameroonian population and farmers on agroforestry. The methodology used was based on a survey to determine their knowledge level of agroforestry, their representation of its advantages and disadvantages, and the reasons that might motivate them whether or not to adopt agroforestry. Participants were randomly selected and received a questionnaire. Data were subjected to a descriptive analysis using SPSS software. The obtained results showed that less than 50% of the general population had already heard about agroforestry at least once; they have basic knowledge about this concept and its advantages. Farmers had been particularly sensitive to tree's food production function and seemed to value their environmental assets. However, various constraints could affect the possible adoption of agroforestry techniques.

Keywords: agroforestry, quality and sustainable agriculture, perceptions, advantages, limits

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Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

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In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy

Procedia PDF Downloads 441

Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Soo Hong Da, Ng Zheng Yao, Burra Venkata Durga Kumar

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The Healthcare sector is a business that consists of providing medical services, manufacturing medical equipment and drugs as well as providing medical insurance to the public. Most of the time, the data stored in the healthcare database is to be related to patient’s information which is required to be accurate when it is accessed by authorized stakeholders. In distributed systems, one important issue is concurrency in the system as it ensures the shared resources to be synchronized and remains consistent through multiple read and write operations by multiple clients. The problems of concurrency in the healthcare sector are who gets the access and how the shared data is synchronized and remains consistent when there are two or more stakeholders attempting to the shared data simultaneously. In this paper, a framework that is beneficial to distributed healthcare sector concurrent environment is proposed. In the proposed framework, four different level nodes of the database, which are national center, regional center, referral center, and local center are explained. Moreover, the frame synchronization is not symmetrical. There are two synchronization techniques, which are complete and partial synchronization operation are explained. Furthermore, when there are multiple clients accessed at the same time, synchronization types are also discussed with cases at different levels and priorities to ensure data is synchronized throughout the processes.

Keywords: resources, healthcare, concurrency, synchronization, stakeholders, database

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Authors: César Oliveira, Ana M. S. Bettencourt, Luciano Vilas Boas, Luís Gonçalves, Carlo Bottaini

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Funerary megalithic monuments are probably under the most remarkable remains of the Neolithic period of western Europe. Some monuments are well known for their paintings, sometimes associated with engraved motifs, giving the funerary crypts a character of great symbolic value. The engraved and painted motifs, the colors used in the paintings, and the offerings associated with the deposited corpses are archaeological data that, being part of the funeral rites, also reveal the ideological world of these communities and their way of interacting with the world. In this sense, the choice of colors to be used in the paintings, the pigments collected, and the proceeds for making the paints would also be significant performances. The present study will focus on the characterization of painted art from megalithic monuments located in different areas of North-Western Portugal (coastal and inland). The colorant composition of megalithic barrows decorated with rock art motifs was studied using a multi-analytical approach (XRD, SEM-EDS, FTIR, and GC-MS), allowing the characterization of the painting techniques, pigments, and the organic compounds used as binders. Some analyses revealed that the pigments used for painting were produced using a collection of mined or quarried organic and inorganic substances. The results will be analyzed from the perspective of contingencies and regularity among the different case studies in order to interpret more or less standardized behaviors.

Keywords: funerary megalithic monuments, painting motifs, archaeometrical studies, Northwest Iberia, behaviors

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Authors: Natapol Pumipuntu

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Staphylococcus argenteus is the emerging species of S. aureus complex. It was generally misidentified as S. aureus by standard techniques and their features. S. argenteus is possibly emerging in both humans and animals, as well as increasing worldwide distribution. The objective of this study was to differentiate and identify S. argenteus from S. aureus, which has been collected and isolated from milk samples of subclinical bovine mastitis cases in Maha Sarakham province, Northeastern of Thailand. Twenty-one isolates of S. aureus, which confirmed by conventional methods and immune-agglutination method were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and multilocus sequence typing (MLST). The result from MALDI-TOF MS and MLST showed 6 from 42 isolates were confirmed as S. argenteus, and 36 isolates were S. aureus, respectively. This study indicated that the identification and classification method by using MALDI-TOF MS and MLST could accurately differentiate the emerging species, S. argenteus, from S. aureus complex which usually misdiagnosed. In addition, the identification of S. argenteus seems to be very limited despite the fact that it may be the important causative pathogen in bovine mastitis as well as pathogenic bacteria in food and milk. Therefore, it is very necessary for both bovine medicine and veterinary public health to emphasize and recognize this bacterial pathogen as the emerging disease of Staphylococcal bacteria and need further study about S. argenteus infection.

Keywords: Staphylococcus argenteus, subclinical bovine mastitis, Staphylococcus aureus complex, mass spectrometry, MLST

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Authors: Mohamed Noureldin, Jinkoo Kim

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The sensitivity of the seismic response parameters to the uncertain modeling variables of pile-founded fixed steel jacket platforms are investigated using tornado diagram, first-order second-moment, and static pushover analysis techniques. The effects of both aleatory and epistemic uncertainty on seismic response parameters have been investigated for an existing offshore platform. The sources of uncertainty considered in the present study are categorized into three different categories: the uncertainties associated with the soil-pile modeling parameters in clay soil, the platform jacket structure modeling parameters, and the uncertainties related to ground motion excitations. It has been found that the variability in parameters such as yield strength or pile bearing capacity has almost no effect on the seismic response parameters considered, whereas the global structural response is highly affected by the ground motion uncertainty. Also, some uncertainty in soil-pile property such as soil-pile friction capacity has a significant impact on the response parameters and should be carefully modeled. Based on the results, it is highlighted that which uncertain parameters should be considered carefully and which can be assumed with reasonable engineering judgment during the early structural design stage of fixed steel jacket platforms.

Keywords: fixed jacket offshore platform, pile-soil structure interaction, sensitivity analysis

Procedia PDF Downloads 375

Authors: Abdulbaset Saad, Adel Younis, Zuomin Dong

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For design optimization with high-dimensional expensive problems, an effective and efficient optimization methodology is desired. This work proposes a series of modification to the Differential Evolution (DE) algorithm for solving computation Intensive Black-Box Problems. The proposed methodology is called Radial Basis Meta-Model Algorithm Assisted Differential Evolutionary (RBF-DE), which is a global optimization algorithm based on the meta-modeling techniques. A meta-modeling assisted DE is proposed to solve computationally expensive optimization problems. The Radial Basis Function (RBF) model is used as a surrogate model to approximate the expensive objective function, while DE employs a mechanism to dynamically select the best performing combination of parameters such as differential rate, cross over probability, and population size. The proposed algorithm is tested on benchmark functions and real life practical applications and problems. The test results demonstrate that the proposed algorithm is promising and performs well compared to other optimization algorithms. The proposed algorithm is capable of converging to acceptable and good solutions in terms of accuracy, number of evaluations, and time needed to converge.

Keywords: differential evolution, engineering design, expensive computations, meta-modeling, radial basis function, optimization

Procedia PDF Downloads 396

Authors: Talat Baran

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Palladium-catalyzed Suzuki coupling reactions are powerful ways for synthesis of biaryls compounds and so far different palladium sources as have been used in catalyst systems. However, the high cost of the ligands using as support materials for palladium ion and so researchers have explored alternative low-cost support materials such as silica, cellule and zeolite. A natural polymer chitosan is suitable for support material because of it unique properties such as eco-friendly, renewable, abundant, low cost, biodegradable and it has free reactive -NH2 and –OH groups. Especially, pendant amino groups of chitosan can easily react with carbonyl groups of aldehyde or ketone by Schiff base formation and thus palladium ions can coordinate with imine groups of Schiff base. This purpose, in this study, firstly a new chitosan Schiff base supported palladium (II) catalyst was synthesized and its chemical structure was characterized with FT-IR, SEM/EDAX, XRD, TG-DTG, ICP-OES and magnetic moment techniques. Then catalytic performance of the catalyst was investigated in Suzuki cross coupling reactions under simple and fast microwave heating methods. Also, recycle activity of palladium catalyst was tested under optimum condition and the catalyst showed long life time. At the end of catalytic performance tests of chitosan supported palladium (II) catalysts indicated high turnover numbers, turnover frequency and selectivity with very small loading catalyst

Keywords: catalyst, chitosan, Schiff base, Suzuki coupling

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Authors: Tahir Mehmood, Mumtaz Akhter

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The global need for conflict management is greater now in the early 21st century than ever before. According to UNESCO, half of the world’s 195 countries will have to expand their stock of educationist significantly, some by tens of thousands, if the goal development targets are desired to achieve. Socioeconomic inequities, political instability, demographic changes and crises such as the HIV/AIDs epidemic have engendered huge shortfalls in teacher supply and low teacher quality in many developing countries. Education serves as back bone in development process. Open learning and distance education programs are serving as pivotal part of development process. It is now clear that ‘bricks and mortar’ approaches to expanding teacher education may not be adequate if the current and projected shortfalls in teacher supply and low teacher quality are to be properly addressed. The study is designed to measure the perceptions of teaching learning community about conflict management with special reference to open and distance learning. It was descriptive study which targeted teachers, students, community members and experts. Data analysis was carried out by using statistical techniques served by SPSS. Findings reflected that audience perceives open and distance learning as change agent and as development tool. It is noticed that target audience has driven prominent performance by using facility of open and distance learning.

Keywords: conflict management, open and distance learning, teachers, students

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Authors: F. Kashanian, M. M. Masoudi, A. Akbari, A. Shamloo, M. R. Zand, S. S. Salehi

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Nano-sized materials present new opportunities in biology and medicine and they are used as biomedical tools for investigation, separation of molecules and cells. To achieve more effective cancer therapy, it is essential to select cancer cells exactly. This research suggests that using the antibody-functionalized nontoxic Arginine-doped magnetic nanoparticles (A-MNPs), has been prosperous in detection, capture, and magnetic separation of circulating tumor cells (CTCs) in tumor tissue. In this study, A-MNPs were synthesized via a simple precipitation reaction and directly immobilized Ep-CAM EBA-1 antibodies over superparamagnetic A-MNPs for Mucin BCA-225 in breast cancer cell. The samples were characterized by vibrating sample magnetometer (VSM), FT-IR spectroscopy, Tunneling Electron Microscopy (TEM) and Scanning Electron Microscopy (SEM). These antibody-functionalized nontoxic A-MNPs were used to capture breast cancer cell. Through employing a strong permanent magnet, the magnetic separation was achieved within a few seconds. Antibody-Conjugated nontoxic Arginine-doped Fe₃O₄ nanoparticles have the potential for the future study to capture CTCs which are released from tumor tissue and for drug delivery, and these results demonstrate that the antibody-conjugated A-MNPs can be used in magnetic hyperthermia techniques for cancer treatment.

Keywords: tumor tissue, antibody, magnetic nanoparticle, CTCs capturing

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Jawad Alzeer

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Natural products are well recognized as sources of drugs in several human ailments. To investigate the impact of variable extraction techniques on the cytotoxic effects of medicinal plant extracts, 5 well-known medicinal plants from Palestine were extracted with 90% ethanol, 80% methanol, acetone, coconut water, apple vinegar, grape vinegar or 5% acetic acid. The resulting extracts were screened for cytotoxic activities against three different cancer cell lines (B16F10, MCF-7, and HeLa) using a standard resazurin-based cytotoxicity assay and Nile Blue A as the positive control. Highly variable toxicities and tissue sensitivity were observed, depending upon the solvent used for extraction. Acetone consistently gave lower extraction yields but higher cytotoxicity, whereas other solvent systems gave much higher extraction yields with lower cytotoxicity. Interestingly, coconut water was found to offer a potential alternative to classical organic solvents; it gave consistently highest extraction yields, and in the case of S. officinalis L., highly toxic extracts towards MCF-7 cells derived from human breast cancer. These results demonstrate how the cytotoxicity of plant extracts can be inversely proportional to the yield, and that solvent selection plays an important role in both factors.

Keywords: plant extract, natural products, anti cancer drug, cytotoxicity

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Authors: Mokhtar Kouki Inès Rekik

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This paper focuses on the assessment of the air pollution and morbidity relationship in Tunisia. Air pollution is measured by ozone air concentration and the morbidity is measured by the number of respiratory-related restricted activity days during the 2-week period prior to the interview. Socioeconomic data are also collected in order to adjust for any confounding covariates. Our sample is composed by 407 Tunisian respondents; 44.7% are women, the average age is 35.2, near 69% are living in a house built after the 1980, and 27.8% have reported at least one day of respiratory-related restricted activity. The model consists on the regression of the number of respiratory-related restricted activity days on the air quality measure and the socioeconomic covariates. In order to correct for zero-inflation and heterogeneity, we estimate several models (Poisson, Negative binomial, Zero inflated Poisson, Poisson hurdle, Negative binomial hurdle and finite mixture Poisson models). Bootstrapping and post-stratification techniques are used in order to correct for any sample bias. According to the Akaike information criteria, the hurdle negative binomial model has the greatest goodness of fit. The main result indicates that, after adjusting for socioeconomic data, the ozone concentration increases the probability of positive number of restricted activity days.

Keywords: bootstrapping, hurdle negbin model, overdispersion, ozone concentration, respiratory-related restricted activity days

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Authors: R. Kanthavel, R. Yogesh Kumar, T. Narendrakumar, B. Santhosh, S. Surya Prakash

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This paper primarily focuses on developing an affordable personal assistant and the implementation of it in the field of Artificial Intelligence (AI) to create a virtual assistant/friend. The problem in existing home automation techniques is that it requires the usage of exact command words present in the database to execute the corresponding task. Our proposed work is ATOM a.k.a ‘Artificial intelligence Talking Omnipresent Machine’. Our inspiration came from an unlikely source- the movie ‘Iron Man’ in which a character called J.A.R.V.I.S has omnipresence, and device controlling capability. This device can control household devices in real time and send the live information to the user. This device does not require the user to utter the exact commands specified in the database as it can capture the keywords from the uttered commands, correlates the obtained keywords and perform the specified task. This ability to compare and correlate the keywords gives the user the liberty to give commands which are not necessarily the exact words provided in the database. The proposed work has a higher flexibility (due to its keyword extracting ability from the user input) comparing to the existing work Intelligent Home automation System (IHAS), is more accurate, and is much more affordable as it makes use of WI-FI module and raspberry pi 2 instead of ZigBee and a computer respectively.

Keywords: home automation, speech recognition, voice control, personal assistant, artificial intelligence

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Authors: M. Najib Osman, Hanafizan Hussain, Sri Kusuma Wati Mohd Daud

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Avatar was used as user’s symbol of identity in online communications such as Facebook, Twitter, online game, and portal community between unknown people. The development of this symbol is the use of animated character or avatar, which can engage learners in a way that draws them into the e-Learning experience. Immersive learning is one of the most effective learning techniques, and animated characters can help create an immersive environment. E-learning is an ideal learning environment using modern means of information technology, through the effective integration of information technology and the curriculum to achieve, a new learning style which can fully reflect the main role of the students to reform the traditional teaching structure thoroughly. Essential in any e-learning is the degree of interactivity for the learner, and whether the learner is able to study at any time, or whether there is a need for the learner to be online or in a classroom with other learners at the same time (synchronous learning). Ideally, e-learning should engage the learners, allowing them to interact with the course materials, obtaining feedback on their progress and assistance whenever it is required. However, the degree of interactivity in e-learning depends on how the course has been developed and is dependent on the software used for its development, and the way the material is delivered to the learner. Therefore, users’ accessibility that allows access to information at any time and places and their positive attitude towards e-learning such as having interacting with a good teacher and the creation of a more natural and friendly environment for e-learning should be enhanced. This is to motivate their learning enthusiasm and it has been the responsibility of educators to incorporate new technology into their ways of teaching.

Keywords: avatar, e-learning, higher education, students' perception

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Authors: Abdul Salam Turkmani

Abstract:

The Lower Cretaceous rocks are exposed only in the mountains regions of Syria, such as the Anti- Lebanon mountain on the western side of Damascus. The lower cretaceous sequences are made up of different rocks. The upper and middle parts of the section are composed mainly of carbonate sediments and, less frequently, gypsum and anhydrite. The lower beds are mainly composed of sandstone, conglomerate and clay. Clay samples were collected from the study area, which is located about 45 km west of the city of Damascus, near the border village of Kfer Yabous and to the left of the Damascus -Beirut International Road, within the lower Cretaceous upper Aptian deposits. The properties of clay were carried out by X-ray diffraction (XRD) and, X-ray fluorescence (XRF) and Thermal Analysis (DTA-TG-DSC) techniques. The studied samples of clay were mainly composed of kaolinite, quartz, illite. Chemical analysis shows the content of SiO₂ varied between 46.06 to 73 % Al₂O₃ 14.55-26.56%, about the staining oxides (Fe₂O₃ + TiO₂), the total content is about 4.3 to 12.5%. The physical properties were determined by studying the behavior of the body before and after firing, showed low bending strength values (22.5 kg/cm²) after drying, and (about 247 kg/cm²) after firing at 1180°C, water absorption value was about 10%. The cubic thermal expansion coefficient at 1140°C is 213.77 x 10-7 /°C. All of the presented results confirm the suitability of this clay for the ceramic industry.

Keywords: anti-Lebanon, Damascus, ceramic, clay, thermal analysis, thermal expansion coefficient

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

Abstract:

Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: Khalil Ibrahim, Ahmed Ramadan, Mohamed Fanni, Yo Kobayashi, Ahmed Abo-Ismail, Masakatus G. Fujie

Abstract:

This paper deals with the design process and the dynamic control simulation of a new type of 4-DOFs parallel mechanism that can be used as an endoscopic surgical manipulator. The proposed mechanism, 2-PUU_2-PUS, is designed based on the screw theory and the parallel virtual chain type synthesis method. Based on the structure analysis of the 4-DOF parallel mechanism, the inverse position equation is studied using the inverse analysis theory of kinematics. The design and the stress analysis of the mechanism are investigated using SolidWorks software. The virtual prototype of the parallel mechanism is constructed, and the dynamic simulation is performed using ADAMS TM software. The system model utilizing PID and PI controllers has been built using MATLAB software. A more realistic simulation in accordance with a given bending angle and point to point control is implemented by the use of both ADAMS/MATLAB software. The simulation results showed that this control method has solved the coordinate control for the 4-DOF parallel manipulator so that each output is feedback to the four driving rods. From the results, the tracking performance is achieved. Other control techniques, such as intelligent ones, are recommended to improve the tracking performance and reduce the numerical truncation error.

Keywords: parallel mechanisms, medical robotics, tracjectory control, virtual chain type synthesis method

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Authors: Lynn Lehmann, Dinorah Leyva, Ana Lazic, Stefan Duhr, Philipp Baaske

Abstract:

Characterization of biomolecular interactions, such as protein-protein, protein-nucleic acid or protein-small molecule, provides critical insights into cellular processes and is essential for the development of drug diagnostics and therapeutics. Here we present a novel, label-free, and tether-free technology to analyze picomolar to millimolar affinities of biomolecular interactions by Microscale Thermophoresis (MST). The entropy of the hydration shell surrounding molecules determines thermophoretic movement. MST exploits this principle by measuring interactions using optically generated temperature gradients. MST detects changes in the size, charge and hydration shell of molecules and measures biomolecule interactions under close-to-native conditions: immobilization-free and in bioliquids of choice, including cell lysates and blood serum. Thus, MST measures interactions under close-to-native conditions, and without laborious sample purification. We demonstrate how MST determines the picomolar affinities of antibody::antigen interactions, and protein::protein interactions measured from directly from cell lysates. MST assays are highly adaptable to fit to the diverse requirements of different and complex biomolecules. NanoTemper´s unique technology is ideal for studies requiring flexibility and sensitivity at the experimental scale, making MST suitable for basic research investigations and pharmaceutical applications.

Keywords: biochemistry, biophysics, molecular interactions, quantitative techniques

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Authors: Mladen Jankovic, Biljana Djuric, Djurdja Oljaca, Vladimir Damjanovic, Radislav Filipovic, Zoran Obrenovic

Abstract:

One of the key characteristics of zeolites with ZSM-5 crystalline form is the possibility of synthesis in a wide range of molar ratios, from the relatively low ratio of about 20 to highly silicate forms with a Si/Al ratio over 1000. For industrial production and commercial use of this type of zeolite, it is very important to know the influence of the molar Si/Al ratio on the characteristics of zeolite powders. In this paper, the influence of the Si/Al ratio on the characteristics of H-ZSM-5 zeolites synthesized in the presence of tetrapropylammonium bromide is questioned, including the possibility of conversion to the H-form using different acids. The quality of the samples is characterized in terms of crystallinity, chemical composition, morphology, granulometry, specific surface area (BET), pore size and acidity. XRD, FT-IR, EDX, ICP, SEM and TPD instrumental techniques were used to characterize the samples. In most of the performed syntheses, zeolite has been obtained with very good properties. It was shown that the examined conditions have a significant influence on the characteristics of the synthesized powders. The different chemical composition of the starting mixture, ie. the Si/Al ratio, has a very significant influence on the crystal structure of the synthesized powders, and thus on the other tested characteristics. It has been observed that optimal ion exchange results for powders of different Si/Al ratios are achieved by using different acids. Also, the dependence of the specific surface on the concentration of H+ or Na+ ions was confirmed.

Keywords: Characterisation, H-ZSM-5, molar ratio, synthesis, tetrapropylammonium bromide

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Authors: Eric Morettin

Abstract:

Cybersecurity and digital literacy are pressing issues among Canadian citizens, yet formal education does not provide today’s students with the necessary knowledge and skills needed to adapt to these challenging issues within the physical and digital labor-market. Canada’s current education systems do not highlight the importance of these respective fields, aside from using technology for learning management systems and alternative methods of assignment completion. Educators are not properly trained to integrate technology into the compulsory courses within public education, to better prepare their learners in these topics and Canada’s digital economy. ICTC addresses these gaps in education and training through cross-Canadian educational programming in digital literacy and competency, cybersecurity and coding which is bridged with Canada’s provincially regulated K-12 curriculum guidelines. After analyzing Canada’s provincial education, it is apparent that there are gaps in learning related to technology, as well as inconsistent educational outcomes that do not adequately represent the current Canadian and global economies. Presently only New Brunswick, Nova Scotia, Ontario, and British Columbia offer curriculum guidelines for cybersecurity, computer programming, and digital literacy. The remaining provinces do not address these skills in their curriculum guidelines. Moreover, certain courses across some provinces not being updated since the 1990’s. The three territories respectfully take curriculum strands from other provinces and use them as their foundation in education. Yukon uses all British Columbia curriculum. Northwest Territories and Nunavut respectfully use a hybrid of Alberta and Saskatchewan curriculum as their foundation of learning. Education that is provincially regulated does not allow for consistency across the country’s educational outcomes and what Canada’s students will achieve – especially when curriculum outcomes have not been updated to reflect present day society. Through this, ICTC has aligned Canada’s provincially regulated curriculum and created opportunities for focused education in the realm of technology to better serve Canada’s present learners and teachers; while addressing inequalities and applicability within curriculum strands and outcomes across the country. As a result, lessons, units, and formal assessment strategies, have been created to benefit students and teachers in this interdisciplinary, cross-curricular, practice - as well as meeting their compulsory education requirements and developing skills and literacy in cyber education. Teachers can access these lessons and units through ICTC’s website, as well as receive professional development regarding the assessment and implementation of these offerings from ICTC’s education coordinators, whose combines experience exceeds 50 years of teaching in public, private, international, and Indigenous schools. We encourage you to take this opportunity that will benefit students and educators, and will bridge the learning and curriculum gaps in Canadian education to better reflect the ever-changing public, social, and career landscape that all citizens are a part of. Students are the future, and we at ICTC strive to ensure their futures are bright and prosperous.

Keywords: cybersecurity, education, curriculum, teachers

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