Search results for: automated cleaning machines

Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

Procedia PDF Downloads 151

Authors: Girts Zageris, Vadims Geza, Andris Jakovics

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Gasification processes are of great interest due to their generation of renewable energy in the form of syngas from biodegradable waste. It is, therefore, important to study the factors that play a role in the efficiency of gasification and the longevity of the machines in which gasification takes place. This study focuses on the latter, aiming to optimize an entrained-flow gasifier by reducing slag formation on its walls to reduce maintenance costs. A CFD mathematical model for an entrained-flow gasifier is constructed – the model of an actual gasifier is rendered in 3D and appropriately meshed. Then, the turbulent gas flow in the gasifier is modeled with the realizable k-ε approach, taking devolatilization, combustion and coal gasification into account. Various such simulations are conducted, obtaining results for different air inlet positions and by tracking particles of varying sizes undergoing devolatilization and gasification. The model identifies potential problematic zones where most particles collide with the gasifier walls, indicating risk regions where ash deposits could most likely form. In conclusion, the effects on the formation of an ash layer of air inlet positioning and particle size allowed in the main gasifier tank are discussed, and possible solutions for decreasing a number of undesirable deposits are proposed. Additionally, an estimate of the impact of different factors such as temperature, gas properties and gas content, and different forces acting on the particles undergoing gasification is given.

Keywords: biomass particles, gasification, slag formation, turbulence k-ε modelling

Procedia PDF Downloads 274

Authors: Abdul Musaweer Habib, Habibul Hasan Mazumder, Saiful Islam, Sohel Sikder, Omar Faruk Sikder

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The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1499 proteins of Fusobacterium nucleatum, which has no homolog in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the KEGG Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the 3-D structure of these three proteins. Finally, determination of ligand binding sites of the key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against Fusobacterium nucleatum.

Keywords: colorectal cancer, drug target, Fusobacterium nucleatum, homology modeling, ligands

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Authors: Abduselam Faris, Rijalu Negash, Zera Kedir

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This study was initiated to identify constraints and opportunities of the wood production value chain in Southwest Ethiopia. About 385 wood trees growing farmers were randomly interviewed. Similarly, about 30 small-scale wood processors, 30 retailers, 15 local collectors and 5 wholesalers were purposively included in the study. The results of the study indicated that 98.96 % of the smallholder farmers that engaged in the production of wood trees which is used for wood were male-headed, with an average age of 46.88 years. The main activity that the household engaged was agriculture (crop and livestock) which accounts for about 61.56% of the sample respondents. Through value chain mapping of actors, the major value chain participant and supporting actors were identified. On average, the tree-growing farmers generated gross income of 9385.926 Ethiopian birr during the survey year. Among the critical constraints identified along the wood production value chain was limited supply of credit, poor market information dissemination, high interference of brokers, and shortage of machines, inadequate working area and electricity. The availability of forest resources is the leading opportunity in the wood production value chain. Reinforcing the linkage among wood production value chain actors, providing skill training for small-scale processors, and developing suitable policy for wood tree wise use is key recommendations forward.

Keywords: value chain analysis, wood production, southwest Ethiopia, constraints and opportunities

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

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Authors: Parameshwaran Nair

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Filling and packaging lines for bottling of beverages into glass, PET or aluminum containers require specialized expertise and a different configuration of equipment like – Filler, Warmer, Labeller, Crater/Recrater, Shrink Packer, Carton Erector, Carton Sealer, Date Coder, Palletizer, etc. Over the period of time, the packaging industry has evolved from manually operated single station machines to highly automized high-speed lines. Human factor and ergonomics have gained significant consideration in this course of transformation. A pre-requisite for such bottling lines, irrespective of the container type and size, is to be suitable for multi-format applications. It should also be able to handle format changeovers with minimal adjustment. It should have variable capacity and speeds, for providing great flexibility of use in managing accumulation times as a function of production characteristics. In terms of layout as well, it should demonstrate flexibility for operator movement and access to machine areas for maintenance. Packaging technology during the past few decades has risen to these challenges by a series of major breakthroughs interspersed with periods of refinement and improvement. The milestones are many and varied and are described briefly in this paper. In order to have a brief understanding of the human factor and ergonomics in the modern packaging lines, this paper, highlights the various technologies, design considerations and statutory requirements in packaging equipment for different types of containers used in India.

Keywords: human-factor, ergonomics, bottling lines, automized high-speed lines

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Authors: Hafizah Che Hasan, Fateen Nazwa Yusof, Maslina Daud

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Internet of Things (IoT) is a powerful industry system, which end-devices are interconnected and automated, allowing the devices to analyze data and execute actions based on the analysis. The IoT technology leverages the technology of Radio-Frequency Identification (RFID) and Wireless Sensor Network (WSN), including mobile and sensor. These technologies contribute to the evolution of IoT. However, due to more devices are connected each other in the Internet, and data from various sources exchanged between things, confidentiality of the data becomes a major concern. This paper focuses on one of the major challenges in IoT; authentication, in order to preserve data integrity and confidentiality are in place. A few solutions are reviewed based on papers from the last few years. One of the proposed solutions is securing the communication between IoT devices and cloud servers with Elliptic Curve Cryptograhpy (ECC) based mutual authentication protocol. This solution focuses on Hyper Text Transfer Protocol (HTTP) cookies as security parameter.  Next proposed solution is using keyed-hash scheme protocol to enable IoT devices to authenticate each other without the presence of a central control server. Another proposed solution uses Physical Unclonable Function (PUF) based mutual authentication protocol. It emphasizes on tamper resistant and resource-efficient technology, which equals a 3-way handshake security protocol.

Keywords: Internet of Things (IoT), authentication, PUF ECC, keyed-hash scheme protocol

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Authors: Yinghui Shang, Ziqing Zhou, Rong Han, Hang Wang, Xiaodi Liu, Yong Yang

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The design of advanced amorphous solids, such as metallic glasses, with targeted properties through artificial intelligence signifies a paradigmatic shift in physical metallurgy and materials technology. Here, we developed a machine-learning architecture that facilitates the generation of metallic glasses with targeted multifunctional properties. Our architecture integrates the state-of-the-art unsupervised generative adversarial network model with supervised models, allowing the incorporation of general prior knowledge derived from thousands of data points across a vast range of alloy compositions, into the creation of data points for a specific type of composition, which overcame the common issue of data scarcity typically encountered in the design of a given type of metallic glasses. Using our generative model, we have successfully designed copper-based metallic glasses, which display exceptionally high hardness or a remarkably low modulus. Notably, our architecture can not only explore uncharted regions in the targeted compositional space but also permits self-improvement after experimentally validated data points are added to the initial dataset for subsequent cycles of data generation, hence paving the way for the customized design of amorphous solids without human intervention.

Keywords: metallic glass, artificial intelligence, mechanical property, automated generation

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Authors: Hollie M. Lewis

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A large body of corroborating research provides evidence that traditional undergraduate engineering education fails to provide students with a role and identity that requires social concern and moral reasoning. Engineering students demonstrate a low level of engagement with social and political contexts, which further declines over the course of engineering education. This detachment is thought to stem from beliefs that the role of the engineer is purely to design machines, systems, and structures. In effect, engineers objectify the world. The purpose of this paper is to provide an ecofeminist critique of engineering education and pose the benefits of social justice pedagogies incorporating ecofeminist discourse. The challenges currently facing the world stem from anthropocentric industrialization, an agenda that is historically absent of Environmental, Feminist, People of Color, and Indigenous voices. A future in which the global collective achieves its Sustainable Development Goals requires its engineers to have a solid understanding of the broader social and political contexts in which they manage projects. Engineering education must convey the influence of the professional role of engineer and encourage the practice of critical reflection and social perspective-taking, priming students with the skills to engage with varying perspectives and discourses. There will be discussed the facets of social justice pedagogies that aid students in surpassing threshold concepts in social justice.

Keywords: feminism in engineering, sustainable development, engineering education, social justice pedagogies

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Authors: Arun Goel

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The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free over-fall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, support vector machine (Polynomial and rbf) models, and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free over-fall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: air entrainment rate, dissolved oxygen, weir, SVM, regression

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Authors: Sridhar S, Govinda Raj Mandela, Aruna Mangalpady

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In the present day scenario, Indian underground mines are moving towards full scale mechanisation for improvement of production and productivity levels. These mines are employing a wide variety of earth moving machines for the transportation of ore and overburden (waste). Low Profile Dump Trucks (LPDTs) have proven more advantageous towards improvement of production levels in underground mines through quick transportation. During the operation of LPDT, different kinds of vibrations are generated which can affect the health condition of the operator. Keeping this in view, the present research work focuses on measurement and evaluation of Hand Arm Vibrations (HAVs) from the steering system of LPDTs. The study also aims to evaluate the HAVs of different job components of a work cycle in operating LPDTs. The HAVs were measured and evaluated according to ISO 5349-2: 2001 standards, and the daily vibration exposures A(8) were calculated. The evaluated A(8) results show that LPDTs of 60 and 50 tons capacity have vibration levels more than that of the Exposure Action Value (EAV) of 2.5 m/s2 in every job component of the work cycle. Further, the results show that the vibration levels were more during empty haulage especially during descending journey when compared to other job components in all LPDTs considered for the study.

Keywords: low profile dump trucks, hand arm vibrations, exposure action value, underground mines

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Christiana Ebobo

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Cybercrime consists of numerous crimes that are perpetrated on the internet on daily basis. The forms include but not limited to Identity theft, Pretentious dating, Desktop counterfeiting, Internet chat room, Cyber harassment, Fraudulent electronic mails, Automated Teller Machine Spoofing, Pornography, Piracy, Hacking, Credit card frauds, Phishing and Spamming. The general term used among the youths for this type of crime in Nigeria is ‘Yahoo Yahoo’. Cybercrime is on the increase among the youths at all levels as such this study aims at examining the impact of cybercrime on youth development in Nigeria. The study examines the impact of cybercrime on youths’ academic performance, integrity, employment and religious practices. The study is a survey which made use of questionnaire and focus group discussion among 150 randomly selected youths in Gwagwalada LCDA, Federal Capital Territory, Nigeria. The study adopts the systems theory as its theoretical framework. The study also adopts the simple frequency table and percentage for its data analysis. The study reveals that cybercrime has eaten deep into the minds of some youths and some of them are practicing diabolic means to succeed in it. It is also reveals that majority (68%) of the respondents believe that cybercrime impacts negatively on youths’ academic performance in Nigeria. The major recommendation of this study is that cybercrime offenders should be treated like armed robbers in order to discourage other youths from getting involved in it.

Keywords: armed robber, cybercrime, integrity, youth

Procedia PDF Downloads 509

Authors: Andres Portocarrero Bonifaz, Caterina Sandra Camarena Rodriguez, Ricardo Palma Esparza, Nicolas Antonio Romero Carlos

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Reference levels for common X-rays procedures have been set in many protocols. In Peru, during quality control tests, the dose tolerance is set by these international recommendations. Nevertheless, further studies can be made to assess the national reality and relate dose levels with different parameters such as kV, mA/mAs, exposure time, type of processing (digital, digitalized or conventional), etc. In this paper three radiologic procedures were taken into account for study, general X-rays (fixed and mobile), intraoral X-rays (fixed, mobile and portable) and mammography. For this purpose, an Unfors Xi detector was used; the dose was measured at a focus - detector distance which varied depending on the procedure, and was corrected afterward to find the surface entry dose. The data used in this paper was gathered over a period of over 3 years (2015-2018). In addition, each X-ray machine was taken into consideration only once. The results hope to achieve a new standard which reflects the local practice, and address the issues of the ‘Bonn Call for Action’ in Peru. For this purpose, the 75% percentile of the dose of each radiologic procedure was calculated. In future quality control services, those machines with dose values higher than the selected threshold should be informed that they surpass the reference dose levels established in comparison other radiological centers in the country.

Keywords: general X-rays, intraoral X-rays, mammography, reference dose levels

Procedia PDF Downloads 145

Authors: Hossain A., Chowdhury S. I.

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Introduction: The use of a gamma camera is a standard procedure in nuclear medicine facilities or hospitals to diagnose chronic kidney disease (CKD), but the gamma camera does not precisely stage the disease. The authors sought to determine whether they could use an artificial neural network to determine whether CKD was in normal or abnormal stages based on GFR values (ANN). Method: The 250 kidney patients (Training 188, Testing 62) who underwent an ultrasonography test to diagnose a renal test in our nuclear medical center were scanned using a gamma camera. Before the scanning procedure, the patients received an injection of ⁹⁹ᵐTc-DTPA. The gamma camera computes the pre- and post-syringe radioactive counts after the injection has been pushed into the patient's vein. The artificial neural network uses the softmax function with cross-entropy loss to determine whether CKD is normal or abnormal based on the GFR value in the output layer. Results: The proposed ANN model had a 99.20 % accuracy according to K-fold cross-validation. The sensitivity and specificity were 99.10 and 99.20 %, respectively. AUC was 0.994. Conclusion: The proposed model can distinguish between normal and abnormal stages of CKD by using an artificial neural network. The gamma camera could be upgraded to diagnose normal or abnormal stages of CKD with an appropriate GFR value following the clinical application of the proposed model.

Keywords: artificial neural network, glomerular filtration rate, stages of the kidney, gamma camera

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Authors: Abhimanyu Pati, Krishna Kumar Veluri

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The paper intends to bring out a real life experience encountered during actual implementation of a large scale Tier-1 Enterprise Resource Planning (ERP) system in a multi-location, discrete manufacturing organization in India, involved in manufacturing of auto components and aggregates. The business complexities, prior to the implementation of ERP, include multi-product with hierarchical product structures, geographically distributed multiple plant locations with disparate business practices, lack of inter-plant broadband connectivity, existence of disparate legacy applications for different business functions, and non-standardized codifications of products, machines, employees, and accounts apart from others. On the other hand, the manufacturing environment consisted of processes like Assemble-to-Order (ATO), Make-to-Stock (MTS), and Engineer-to-Order (ETO) with a mix of discrete and process operations. The paper has highlighted various business plan areas and concerns, prior to the implementation, with specific focus on strategic issues and objectives. Subsequently, it has dealt with the complete process of ERP implementation, starting from strategic planning, project planning, resource mobilization, and finally, the program execution. The step-by-step process provides a very good learning opportunity about the implementation methodology. At the end, various organizational challenges and lessons emerged, which will act as guidelines and checklist for organizations to successfully align and implement ERP and achieve their business objectives.

Keywords: ERP, ATO, MTS, ETO, discrete manufacturing, strategic planning

Procedia PDF Downloads 237

Authors: Tariq Aljuneidi, Akif Asil Bulgak

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Remanufacturing may be defined as the process of bringing used products to “like-new” functional state with warranty to match, and it is one of the most popular product end-of-life scenarios. An efficient remanufacturing network lead to an efficient design of sustainable manufacturing enterprise. In remanufacturing network, products are collected from the customer zone, disassembled and remanufactured at a suitable remanufacturing facility. In this respect, another issue to consider is how the returned product to be remanufactured, in other words, what is the best layout for such facility. In order to achieve a sustainable manufacturing system, Cellular Manufacturing System (CMS) designs are highly recommended, CMSs combine high throughput rates of line layouts with the flexibility offered by functional layouts (job shop). Introducing the CMS while designing a remanufacturing network will benefit the utilization of such a network. This paper presents and analyzes a comprehensive mathematical model for the design of Dynamic Cellular Remanufacturing Systems (DCRSs). In this paper, the proposed model is the first one to date that consider CMS and remanufacturing system simultaneously. The proposed DCRS model considers several manufacturing attributes such as multi-period production planning, dynamic system reconfiguration, duplicate machines, machine capacity, available time for workers, worker assignments, and machine procurement, where the demand is totally satisfied from a returned product. A numerical example is presented to illustrate the proposed model.

Keywords: cellular manufacturing system, remanufacturing, mathematical programming, sustainability

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Authors: M. Azadi, M. Kalhor

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Excavation of shallow tunnels such as subways in urban areas plays a significant role as a life line and investigation of the soil behavior against tunnel construction is one of the vital subjects studied in the geotechnical scope. Nowadays, urban tunnels are mostly drilled by T.B.Ms and changing the applied forces to tunnel lining is one of the most risky matters while drilling tunnels by these machines. Variation of soil cementation can change the behavior of these forces in the tunnel lining. Therefore, this article is designed to assess the impact of tunnel excavation in different soils and several amounts of cementation on applied loads to tunnel lining under static and dynamic loads. According to the obtained results, changing the cementation of soil will affect the applied loadings to the tunnel envelope significantly. It can be determined that axial force in tunnel lining decreases considerably when soil cementation increases. Also, bending moment and shear force in tunnel lining decreases as the soil cementation increases and causes bending and shear behavior of the segments to improve. Based on the dynamic analyses, as cohesion factor in soil increases, bending moment, axial and shear forces of segments decrease but lining behavior of the tunnel is the same as static state. The results show that decreasing the overburden applied to lining caused by cementation is different in two static and dynamic states.

Keywords: seismic behavior, twin tunnels, tunnel positions, TBM, optimum distance

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Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

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Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Mahmoud Meckawey

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This research is dealing with one of the most important aspects of maintenance fields, that is Maintenance Strategy. It's the branch which concerns the concepts and the schematic thoughts in how to manage maintenance and how to deal with the defects in the engineering products (buildings, machines, etc.) in general. Through the papers we will act with the followings: i) The Engineering Product & the Technical Systems: When we act with the maintenance process, in a strategic view, we act with an (engineering product) which consists of multi integrated systems. In fact, there is no engineering product with only one system. We will discuss and explain this topic, through which we will derivate a developed definition for the maintenance process. ii) The factors or basis of the functionality efficiency: That is the main factors affect the functional efficiency of the systems and the engineering products, then by this way we can give a technical definition of defects and how they occur. iii) The legality of occurrence of defects (Legal defects and Illegal defects): with which we assume that all the factors of the functionality efficiency been applied, and then we will discuss the results. iv) The Guarantee, the Functional Span Age and the Technical surplus concepts: In the complementation with the above topic, and associated with the Reliability theorems, where we act with the Probability of Failure state, with which we almost interest with the design stages, that is to check and adapt the design of the elements. But in Maintainability we act in a different way as we act with the actual state of the systems. So, we act with the rest of the story that means we have to act with the complementary part of the probability of failure term which refers to the actual surplus of the functionality for the systems.

Keywords: engineering product and technical systems, functional span age, legal and illegal defects, technical and functional surplus

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Authors: Peter Križan, Juraj Beniak, Ľubomír Šooš, Miloš Matúš

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Biomass treatment through densification is very suitable and important technology before its effective energy recovery. Densification process of biomass is significantly influenced by various technological and also material parameters which are ultimately reflected on the final solid Biofuels quality. The paper deals with the experimental research of the relationship between technological and material parameters during densification of fast-growing trees, roundly fast-rowing willow. The main goal of presented experimental research is to determine the relationship between pressing pressure raw material fraction size from a final briquettes density point of view. Experimental research was realized by single-axis densification. The impact of fraction size with interaction of pressing pressure and stabilization time on the quality properties of briquettes was determined. These parameters interaction affects the final solid biofuels (briquettes) quality. From briquettes production point of view and also from densification machines constructions point of view is very important to know about mutual interaction of these parameters on final briquettes quality. The experimental findings presented here are showing the importance of mentioned parameters during the densification process.

Keywords: briquettes density, densification, fraction size, pressing pressure, stabilization time

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: A. Kamel Abd Elaziz Mohamed, B. Sameh Kamal el Maraghi

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Introduction: Adaptive support ventilation (ASV) is an improved closed-loop ventilation mode that provides both pressure-controlled ventilation and PSV according to the patient’s needs. Aim of the work: To compare the short-term effects of Adaptive support ventilation (ASV), with conventional Pressure support ventilation (PSV) in weaning of intubated COPD patients. Patients and methods: Fifty patients admitted in the intensive care with acute exacerbation of COPD and needing intubation were included in the study. All patients were initially ventilated with control/assist control mode, in a stepwise manner and were receiving standard medical therapy. Patients were randomized into two groups to receive either ASV or PSV. Results: Out of fifty patients included in the study forty one patients in both studied groups were weaned successfully according to their ABG data and weaning indices. APACHE II score showed no significant difference in both groups. There were statistically significant differences between the groups in term of, duration of mechanical ventilation, weaning hours and length of ICU stay being shorter in (group 1) weaned by ASV. Re-intubation and mortality rate were higher in (group 11) weaned by conventional PSV, however the differences were not significant. Conclusion: ASV can provide automated weaning and achieve shorter weaning time for COPD patients hence leading to reduction in the total duration of MV, length of stay, and hospital costs.

Keywords: COPD patients, ASV, PSV, mechanical ventilation (MV)

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Authors: M. Etezadi, A. Fahimifar

Abstract:

In many geotechnical designs in rocks and rock masses, tensile strength of rock and rock mass is needed. The difficulties associated with performing a direct uniaxial tensile test on a rock specimen have led to a number of indirect methods for assessing the tensile strength that in the meantime the Brazilian test is more popular. Brazilian test is widely applied in rock engineering because specimens are easy to prepare, the test is easy to conduct and uniaxial compression test machines are quite common. This study compares experimental results of direct and Brazilian tensile tests carried out on two rock types and three concrete types using 39 cylindrical and 28 disc specimens. The tests are performed using Servo-Control device. The relationship between direct and indirect tensile strength of specimens is extracted using linear regression. In the following, tensile strength of direct and indirect test is evaluated using finite element analysis. The results are analyzed and effective factors on results are studied. According to the experimental results Brazilian test is shown higher tensile strength than direct test. Because of decreasing the contact surface of grains and increasing the uniformity in concrete specimens with fine aggregate (largest grain size= 6mm), higher tensile strength in direct test is shown. The experimental and numerical results of tensile strength are compared and empirical relationship witch is obtained from experimental tests is validated.

Keywords: tensile strength, brittle materials, direct and indirect tensile test, numerical modeling

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Authors: A. Kampker, K. Kreisköther, C. Reinders

Abstract:

Since additive manufacturing technologies constantly advance, the use of this technology in mold making seems reasonable. Many manufacturers of additive manufacturing machines, however, do not offer any suggestions on how to parameterize the machine to achieve optimal results for mold making. The purpose of this research is to determine the interdependencies of different materials and parameters within the PolyJet process by using design of experiments (DoE), to additively manufacture molds, e.g. for thermoforming and injection molding applications. Therefore, the general requirements of thermoforming molds, such as heat resistance, surface quality and hardness, have been identified. Then, different materials and parameters of the PolyJet process, such as the orientation of the printed part, the layer thickness, the printing mode (matte or glossy), the distance between printed parts and the scaling of parts, have been examined. The multifactorial analysis covers the following properties of the printed samples: Tensile strength, tensile modulus, bending strength, elongation at break, surface quality, heat deflection temperature and surface hardness. The key objective of this research is that by joining the results from the DoE with the requirements of the mold making, optimal and tailored molds can be additively manufactured with the PolyJet process. These additively manufactured molds can then be used in prototyping processes, in process testing and in small to medium batch production.

Keywords: additive manufacturing, design of experiments, mold making, PolyJet, 3D-Printing

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Authors: Siyabonga Aubrey Mhlongo, Linda Lunga Sibali, Phumlane Selby Mdluli, Peter Papoh Ndibewu, Kholofelo Clifford Malematja

Abstract:

This paper reports on the successful extraction and quantification of an antibacterial and antifungal agent present in some consumer products (Triclosan: C₁₂H₇Cl₃O₂)generally found in wastewater or effluents using molecularly imprinted membrane adsorbent (MIMs) followed by quantification and removal on a high-performance liquid chromatography (HPLC). Triclosan is an antibacterial and antifungal agent present in some consumer products like toothpaste, soaps, detergents, toys, and surgical cleaning treatments. The MIMs was fabricated usingpolyvinylidene fluoride (PVDF) polymer with selective micro composite particles known as molecularly imprinted polymers (MIPs)via a phase inversion by immersion precipitation technique. This resulted in an improved hydrophilicity and mechanical behaviour of the membranes. Wastewater samples were collected from the Umbogintwini Industrial Complex (UIC) (south coast of Durban, KwaZulu-Natal in South Africa). central UIC effluent treatment plant and pre-treated before analysis. Experimental parameters such as sample size, contact time, stirring speed were optimised. The resultant MIMs had an adsorption efficiency of 97% of TCS with reference to NIMs and bare membrane, which had 92%, 88%, respectively. The analytical method utilized in this review had limits of detection (LoD) and limits of quantification (LoQ) of 0.22, 0.71µgL-1 in wastewater effluent, respectively. The percentage recovery for the effluent samples was 68%. The detection of TCS was monitored for 10 consecutive days, where optimum TCS traces detected in the treated wastewater was 55.0μg/L inday 9 of the monitored days, while the lowest detected was 6.0μg/L. As the concentrations of analytefound in effluent water samples were not so diverse, this study suggested that MIMs could be the best potential adsorbent for the development and continuous progress in membrane technologyand environmental sciences, lending its capability to desalination.

Keywords: molecularly imprinted membrane, triclosan, phase inversion, wastewater

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Authors: Pouyan Jahanbin, Mahmoud Houshmand, Omid Fatahi Valilai

Abstract:

A flexible manufacturing system (FMS) is a manufacturing system having the capability of handling the variations of products features that is the result of ever-changing customer demands. The flexibility of the manufacturing systems help to utilize the resources in a more effective manner. However, the control of such systems would be complicated and challenging. FMS needs CNC machines and robots and other resources for establishing the flexibility and enhancing the efficiency of the whole system. Also it needs to integrate the resources to reach required efficiency and flexibility. In order to reach this goal, an integrator framework is proposed in which the machining data of CNC machine tools is received through a STEP-NC file. The interoperability of the system is achieved by the information system. This paper proposes an information system that its data model is designed based on object oriented approach and is implemented through a knowledge-based system. The framework is connected to a database which is filled with robot’s control commands. The framework programs the robots by rules embedded in its knowledge based system. It also controls the interactions of CNC machine tools for loading and unloading actions by robot. As a result, the proposed framework improves the integration of manufacturing resources in Flexible Manufacturing Systems.

Keywords: CNC machine tools, industrial robots, knowledge-based systems, manufacturing recourses integration, flexible manufacturing system (FMS), object-oriented data model

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Authors: Lorena Caires Moreira, Marcos Kauffman

Abstract:

This paper outlines the results of experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance of highly customized and high-risk manual operations. The focus is on operators’ training capabilities and the aim is to test if such technologies can support achieving higher levels of knowledge retention and accuracy of task execution to improve health and safety (H and S) levels. The proposed solution is tested and validated using a real-world case study of electric vehicles’ battery module assembly. The experimental results revealed that the proposed AR method improved the training practices by increasing the knowledge retention levels from 40% to 84% and improved the accuracy of task execution from 20% to 71%, compared to the traditional paper-based method. The results of this research can be used as a demonstration of how emerging technologies are advancing the choice of manual, hybrid, or fully automated processes by promoting the connected worker (Industry 5.0) and supporting manufacturing in becoming more resilient in times of constant market changes.

Keywords: augmented reality, extended reality, connected worker, XR-assisted operator, manual assembly, industry 5.0, smart training, battery assembly

Procedia PDF Downloads 110