Search results for: universal testing machine

Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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Authors: Sahil Kumar, Surinder Pal, Rahul Kapoor

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This paper is focused on to define the basic difference between hot and cold chamber high pressure die casting process which is not fully defined in a research before paper which we have studied. The pressure die casting is basically defined into two types (1) Hot chamber Die Casting (2) Cold chamber Die Casting. Cold chamber die casting is used for casting alloys that require high pressure and have a high melting temperature, such as brass, aluminum, magnesium, copper based alloys and other high melting point nonferrous alloys. Hot chamber die casting is suitable for casting zinc, tin, lead, and low melting point alloys. In hot chamber die casting machine, the molten metal is an integral pan of the machine. It mainly consists of hot chamber and gooseneck type metal container made of cast iron. This machine is mainly used for low melting alloys and alloys of metals like zinc, lead etc. Metals and alloys having a high melting point and those which are having an affinity for iron cannot be cast by this machine, which could otherwise attack the shot sleeve and damage the machine.

Keywords: hot chamber die casting, cold chamber die casting, metals and alloys, casting technology

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Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

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Authors: Sławomir Lasota, Tomasz Kajdanowicz

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This study explores the development of human-centric decision support systems tailored for Industry 5.0 production paradigms. By leveraging machine learning-based recommender systems, the proposed solution optimizes real-time production settings, accounting for both machine parameters and individual operator preferences. Integrating key performance indicators (KPIs) such as Overall Equipment Effectiveness (OEE) ensures sector-independent applicability and eco-efficiency. This paper also investigates how the ”Tweeting Factory” framework enhances communication between system components, facilitating adaptive and human-aware process improvements. Experimental results demonstrate the potential for increased operational efficiency and reduced resource consumption, paving the way for autonomous production systems.

Keywords: decision support systems, industry 5.0, machine learning, human-centric

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Authors: Yessica Nataliani, Miin-Shen Yang

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Cell formation (CF) is an important step in group technology. It is used in designing cellular manufacturing systems using similarities between parts in relation to machines so that it can identify part families and machine groups. There are many CF methods in the literature, but there is less spectral clustering used in CF. In this paper, we propose a spectral clustering algorithm for machine-part CF. Some experimental examples are used to illustrate its efficiency. Overall, the spectral clustering algorithm can be used in CF with a wide variety of machine/part matrices.

Keywords: group technology, cell formation, spectral clustering, grouping efficiency

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Authors: A. Hassannia, S. Ramezani

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The technology of superconductivity has developed in many power system devices such as transmission cable, transformer, current limiter, motor and generator. Superconducting wires can carry high density current without loss, which is the capability that is used to design the compact, lightweight and more efficient electrical machines. Superconducting motors have found applications in marine and air propulsion systems as well as superconducting generators are considered in low power hydraulic and wind generators. This paper presents a rim-driven superconducting synchronous generator for hydraulic power plant. The rim-driven concept improves the performance of hydro turbine. Furthermore, high magnetic field that is produced by superconducting windings allows replacing the rotor core. As a consequent, the volume and weight of the machine is decreased significantly. In this paper, a 1 MW coreless rim-driven superconducting synchronous generator is designed. Main performance characteristics of the proposed machine are then evaluated using finite elements method and compared to an ordinary similar size synchronous generator.

Keywords: coreless machine, electrical machine design, hydraulic generator, rim-driven machine, superconducting generator

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Authors: Harish Aryal

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The safe and reliable operation of nuclear reactors has always been one of the topmost priorities in the nuclear industry. Transient testing allows us to understand the time-dependent behavior of the neutron population in response to either a planned change in the reactor conditions or unplanned circumstances. These unforeseen conditions might occur due to sudden reactivity insertions, feedback, power excursions, instabilities, and accidents. To study such behavior, we need transient testing, which is like car crash testing, to estimate the durability and strength of a car design. In nuclear designs, such transient testing can simulate a wide range of accidents due to sudden reactivity insertions and helps to study the feasibility and integrity of the fuel to be used in certain reactor types. This testing involves a high neutron flux environment and real-time imaging technology with advanced instrumentation with appropriate accuracy and resolution to study the fuel slumping behavior. With the aid of transient testing and adequate imaging tools, it is possible to test the safety basis for reactor and fuel designs that serves as a gateway in licensing advanced reactors in the future. To that end, it is crucial to fully understand advanced imaging techniques both analytically and via simulations. This paper presents an innovative method of supporting real-time imaging of fuel pins and other structures during transient testing. The major fuel-motion detection device that is studied in this dissertation is the Hodoscope which requires collimators. This paper provides 1) an MCNP model and simulation of a Transient Reactor Test (TREAT) core with a central fuel element replaced by a slotted fuel element that provides an open path between test samples and a hodoscope detector and 2) a choice of good filter to improve image resolution.

Keywords: hodoscope, transient testing, collimators, MCNP, TREAT, hodogram, filters

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Authors: Angen May T. Fabro

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This study analyzed how the form and content in Adonis Durado’s select poems revealed universal realities for a proposed integrated teaching guide. The study employed discourse analysis that generates verbal interpretation of data to answer the variables under study in order to satisfy the main problem. This method used analyses and interpretations of discourse texts of the literary work under study. This research made use of studies and research investigations relevant to the present investigation. Findings of the study showed that form and content play a significant role in identifying the universal realities found in the select poems of Adonis Durado.

Keywords: poems, poesy, integrated teaching guide, Adonis Durado’s poesy

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Mann Rattana-Areeyagon, Wutichai Namjaiprasert

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G-code is the main factor in computer numerical control (CNC) machine for controlling the tool-paths and generating the profile of the object’s features. For obtaining high surface accuracy of the surface finish, non-stop operation is required for CNC machine. Recently, to design a new product, the strategy that concerns about a change that has low impact on business and does not consume lot of resources has been introduced. Cost and time for designing minor changes can be reduced since the traditional geometric details of the existing models are applied. In order to support this strategy as the alternative channel for machining operation, this research proposes the automatic generating codes for CNC milling operation. Using this technique can assist the manufacturer to easily change the size and the geometric shape of the product during the operation where the time spent for setting up or processing the machine are reduced. The algorithm implemented on MATLAB platform is developed by analyzing and evaluating the geometric information of the part. Codes are created rapidly to control the operations of the machine. Comparing to the codes obtained from CAM, this developed algorithm can shortly generate and simulate the cutting profile of the part.

Keywords: geometric shapes, milling operation, minor changes, CNC Machine, G-code, cutting parameters

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Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Gyoutae Park, Woosuk Kim, Sangguk Ahn, Seungmo Kim, Minjun Kim, Jinhan Lee, Youngdo Jo, Jongsam Moon, Hiesik Kim

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In this research, we designed a remote system to test parameters of gas detectors such as gas concentration and initial response time. This testing system is available to measure two gas instruments simultaneously. First of all, we assembled an experimental jig with a square structure. Those parts are included with a glass flask, two high-quality cameras, and two Ethernet modems for transmitting data. This remote gas detector testing system extracts numerals from videos with continually various gas concentrations while LCDs show photographs from cameras. Extracted numeral data are received to a laptop computer through Ethernet modem. And then, the numerical data with gas concentrations and the measured initial response speeds are recorded and graphed. Our remote testing system will be diversely applied on gas detector’s test and will be certificated in domestic and international countries.

Keywords: gas leak detector, inspection instrument, extracting numerals, concentration

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Authors: Fuad M. Alkoot

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The main component of a machine learning system is the classifier. Classifiers are mathematical models that can perform classification tasks for a specific application area. Additionally, many classifiers are combined using any of the available methods to reduce the classifier error rate. The benefits gained from the combination of multiple classifier designs has motivated the development of diverse approaches to multiple classifiers. We aim to investigate using fractal geometry to develop an improved classifier combiner. Initially we experiment with measuring the fractal dimension of data and use the results in the development of a combiner strategy.

Keywords: fractal geometry, machine learning, classifier, fractal dimension

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Authors: Ahmad B. Musamih, Ahmad A. Albloushi, Ahmed H. Alshemeili, Abdulaziz Y. Alfili, Ala A. Hussien

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This paper proposes a universal wireless battery charger design for portable electronic devices. As the number of portable electronics devices increases, the demand for more flexible and reliable charging techniques is becoming more urgent. A wireless battery charger differs from a traditional charger in the way the power transferred to the battery. In the latter, the power is transferred through electrical wires that connect the charger terminals to the battery terminals, while in the former; the power is transferred by induction without electrical connections. With a detection algorithm that detects the battery size and chemistry, the proposed charger will be able to accommodate a wide range of applications, and will allow a more flexible and reliable option to most of today’s portable electronics.

Keywords: efficiency, magnetically-coupled resonators, resonance frequency, wireless power transfer

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Authors: Muhammad Fathurridho

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Grammar as a rule used by every language to be understood by everyone is always related to syntax and morphology. Arabic grammar is different with another languages’ grammars. It has more rules and difficulties. This paper aims to investigate and describe the English grammatical errors of machine translation systems in translating Arabic sentences, including declarative, exclamation, imperative, and interrogative sentences, specifically in year 2018 which can be supported with artificial intelligence’s role. The Arabic sample sentences which are divided into two; verbal and nominal sentence of several Arabic published texts will be examined as the source language samples. The translated sentences done by several popular online machine translation systems, including Google Translate, Microsoft Bing, Babylon, Facebook, Hellotalk, Worldlingo, Yandex Translate, and Tradukka Translate are the material objects of this research. Descriptive method that will be taken to finish this research will show the grammatical errors of English target language, and classify them. The conclusion of this paper has showed that the grammatical errors of machine translation results are varied and generally classified into morphological, syntactical, and semantic errors in all type of Arabic words (Noun, Verb, and Particle), and it will be one of the evaluations for machine translation’s providers to correct them in order to improve their understandable results.

Keywords: Arabic, Arabic-English translation, machine translation, grammatical errors

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Authors: Xueying Zhao, Ke Ma, Hui Li, Yu Cao, Fan Yang, Qingwen Xu, Wenbin Liu

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Massively parallel sequencing (MPS) technologies allow high-throughput sequencing analyses with a relatively affordable price and have gradually been applied to forensic casework. MPS technology identifies short tandem repeat (STR) loci based on sequence so that repeat motif variation within STRs can be detected, which may help one to infer the origin of the mutation in some cases. Here, we report on one case with one three-step mismatch (D18S51) in family trios based on both capillary electrophoresis (CE) and MPS typing. The alleles of the alleged father (AF) are [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₁₅. The mother’s alleles are [AGAA]₁₉ and [AGAA]₉AGGA[AGAA]₃. The questioned child’s (QC) alleles are [AGAA]₁₉ and [AGAA]₁₂. Given that the sequence variants in repeat regions of AF and mother are not observed in QC’s alleles, the QC’s allele [AGAA]₁₂ was likely inherited from the AF’s allele [AGAA]₁₅ by loss of three repeat [AGAA]. Besides, two new alleles of D18S51 in this study, [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₉AGGA[AGAA]₃, have not been reported before. All the results in this study were verified using Sanger-type sequencing. In summary, the MPS typing method can offer valuable information for forensic genetics research and play a promising role in paternity testing.

Keywords: family trios analysis, forensic casework, ion torrent personal genome machine (PGM), massively parallel sequencing (MPS)

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

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Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

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Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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Authors: Martyna Ekiert, Natalia Grzechnik, Joanna Karbowniczek, Urszula Stachewicz, Andrzej Mlyniec

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Tendon grafting is a common procedure performed to treat tendon rupture. Before the surgical procedure, tissues intended for grafts (i.e., Achilles tendon) are stored in ultra-low temperatures for a long time and also may be subjected to unfavorable conditions, such as repetitive freezing (F) and thawing (T). Such storage protocols may highly influence the graft mechanical properties, decrease its functionality and thus increase the risk of complications during the transplant procedure. The literature reports on the influence of multiple F/T cycles on internal structure and mechanical properties of tendons stay inconclusive, confirming and denying the negative influence of multiple F/T at the same time. An inconsistent research methodology and lack of clear limit of F/T cycles, which disqualifies tissue for surgical graft purposes, encouraged us to investigate the issue of multiple F/T cycles by the mean of biomechanical tensile tests supported with Scanning Electron Microscope (SEM) imaging. The study was conducted on male bovine Achilles tendon-derived from the local abattoir. Fresh tendons were cleaned of excessive membranes and then sectioned to obtained fascicle bundles. Collected samples were randomly assigned to 6 groups subjected to 1, 2, 4, 6, 8 and 12 cycles of freezing-thawing (F/T), respectively. Each F/T cycle included deep freezing at -80°C temperature, followed by thawing at room temperature. After final thawing, thin slices of the side part of samples subjected to 1, 4, 8 and 12 F/T cycles were collected for SEM imaging. Then, the width and thickness of all samples were measured to calculate the cross-sectional area. Biomechanical tests were performed using the universal testing machine (model Instron 8872, INSTRON®, Norwood, Massachusetts, USA) using a load cell with a maximum capacity of 250 kN and standard atmospheric conditions. Both ends of each fascicle bundle were manually clamped in grasping clamps using abrasive paper and wet cellulose wadding swabs to prevent tissue slipping while clamping and testing. Samples were subjected to the testing procedure including pre-loading, pre-cycling, loading, holding and unloading steps to obtain stress-strain curves for representing tendon stretching and relaxation. The stiffness of AT fascicles bundle samples was evaluated in terms of modulus of elasticity (Young’s modulus), calculated from the slope of the linear region of stress-strain curves. SEM imaging was preceded by chemical sample preparation including 24hr fixation in 3% glutaraldehyde buffered with 0.1 M phosphate buffer, washing with 0.1 M phosphate buffer solution and dehydration in a graded ethanol solution. SEM images (Merlin Gemini II microscope, ZEISS®) were taken using 30 000x mag, which allowed measuring a diameter of collagen fibrils. The results confirm a decrease in fascicle bundles Young’s modulus as well as a decrease in the diameter of collagen fibrils. These results confirm the negative influence of multiple F/T cycles on the mechanical properties of tendon tissue.

Keywords: biomechanics, collagen, fascicle bundles, soft tissue

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Authors: Suhani Srivastava

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This research delves into the classification of orbital debris through machine learning (ML): it will categorize the intensity of the threat orbital debris poses through multiple ML models to gain an insight into effectively estimating the danger specific orbital debris can pose to future space missions. As the space industry expands, orbital debris becomes a growing concern in Low Earth Orbit (LEO) because it can potentially obfuscate space missions due to the increased orbital debris pollution. Moreover, detecting orbital debris and identifying its characteristics has become a major concern in Space Situational Awareness (SSA), and prior methods of solely utilizing physics can become inconvenient in the face of the growing issue. Thus, this research focuses on approaching orbital debris concerns through machine learning, an efficient and more convenient alternative, in detecting the potential threat certain orbital debris pose. Our findings found that the Logistic regression machine worked the best with a 98% accuracy and this research has provided insight into the accuracies of specific machine learning models when classifying orbital debris. Our work would help provide space shuttle manufacturers with guidelines about mitigating risks, and it would help in providing Aerospace Engineers facilities to identify the kinds of protection that should be incorporated into objects traveling in the LEO through the predictions our models provide.

Keywords: aerospace, orbital debris, machine learning, space, space situational awareness, nasa

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Authors: Nigar Hussain

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It is a subset of big data. Dark data means those data in which we fail to use for future decisions. There are many issues in existing work, but some need powerful tools for utilizing dark data. It needs sufficient techniques to deal with dark data. That enables users to exploit their excellence, adaptability, speed, less time utilization, execution, and accessibility. Another issue is the way to utilize dark data to extract helpful information to settle on better choices. In this paper, we proposed upgrade strategies to remove the dark side from dark data. Using a supervised model and machine learning techniques, we utilized dark data and achieved an F1 score of 89.48%.

Keywords: big data, dark data, machine learning, heatmap, random forest

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Authors: Mohammed Benmostefa

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In the industrial production of large series or even medium series, there are vibration problems. In continuous operations, technical devices result in vibrations in solid bodies and machine components, which generate solid noise and/or airborne noise. This is because vibrations are the mechanical oscillations of an object near its equilibrium point. In response to the problems resulting from these vibrations, a number of remedial acts and solutions have been put forward. These include insulation of machines, insulation of concrete masses, insulation under screeds, insulation of sensitive equipment, point insulation of machines, linear insulation of machines, full surface insulation of machines, and the like. Following this, the researcher sought not only to raise awareness on the possibility of lowering the vibration frequency in industrial machines but also to stress the significance of procedures involving the pre-installation process of machinery, namely, setting appropriate installation and start-up methods of the machine, allocating and updating imprint folders to each machine, and scheduling maintenance of each machine all year round to have reliable equipment, gain cost reduction and maintenance efficiency to eventually ensure the overall economic performance of the company.

Keywords: maintenance, vibration, efficiency, production, machinery

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Authors: Asra Yousuf, Ajaykumar Tannirkulum

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Inferring rural-urban migration trends can help design effective policies that promote better urban planning and rural development. In this paper, we describe how machine learning algorithms can be applied to predict internal migration decisions of people. We consider data collected from household surveys in Tamil Nadu to train our model. To measure the performance of the model, we use data on past migration from National Sample Survey Organisation of India. The factors for training the model include socioeconomic characteristic of each individual like age, gender, place of residence, outstanding loans, strength of the household, etc. and his past migration history. We perform a comparative analysis of the performance of a number of machine learning algorithm to determine their prediction accuracy. Our results show that machine learning algorithms provide a stronger prediction accuracy as compared to statistical models. Our goal through this research is to propose the use of data science techniques in understanding human decisions and behaviour in developing countries.

Keywords: development, migration, internal migration, machine learning, prediction

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Authors: Berfu Guley Goren, Ayse Lale Berkoz

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The aim of the study is to analyze the concept of universal design and accessibility to make the city which allows equality and independence for individuals. In the content of the study, literature researches and observations of samples in Istanbul, Turkey are analyzed. As a result proposals are going to be developed to create the cities which are designed for everyone. In globalization process, in cities, population have been increasing dramatically with social and economic activities. Medical developments have been effective in prolonging human life and the disability that comes with aging has also increased in parallel with the disabled population. Nowadays disability is an important phenomenon. Because approximately 1 billion people live with disabilities. The heterogeneous structure formed by the rapid gathering of individuals with different social, economic and physical characteristics in the cities creates great spatial diversity and richness in the cities with different needs brought together. Unlike the cultural and physical wealth in these places and the potential to integrate and diversify the urban people, unfortunately, the designs in practice cause the urban areas to break apart, the urbanities to tear themselves apart, to interfere with their communication and interactions. The social and physical structure of the city is important to feel belonging to the urban society. In most cities when an observation is made, obstructions for people with disabilities can be seen in urban physical structure and design. With these obstructions, people with disabilities cannot live in urban space, and they are desolated in urban life. The city, which offers equal opportunity, the relation between economic development, social justice and built environment must be planned synchronous. Isolation and stigmatization must be abolished by regulations, activities of awareness and universal urban design. Without regard to social, economical and physical features every individual has the same right, which is using the freedom of movement. Supporting freedom of movement of every individual may be ensured by universal design and its principles. So urban spaces are going to be for every individual. For equal opportunity in urban services, urban design must be the focus on every individual including people with disabilities. In built environment practices, democratic suitable spaces should be created. In this respect, urban planners, architects, political decision-makers and other relevant actors should work together and should think very versatile.

Keywords: disability, equality, universal design, urban design

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Authors: Usman Abubakar, Xiaoyuan Wang, Sayyed Haleem Shah, Sadiq Ur Rahman, Rabiu Saleh Zakariyya

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High-speed Permanent magnet synchronous machine (HSPMSM) uses in different industrial applications like blowers, compressors as a result of its superb performance. Nevertheless, the over-temperature rise of both winding and PM is one of their substantial problem for a high-power HSPMSM, which affects its lifespan and performance. According to the literature, HSPMSM with a Hybrid cooling configuration has a much lower temperature rise than non-hybrid cooling. This paper presents the design 185kW, 26K rpm with two different cooling configurations, i.e., hybrid cooling configuration (forced air and housing spiral water jacket) and non-hybrid (forced air cooling assisted with winding’s potting material and sleeve’s material) to enhance the heat dissipation of winding and PM respectively. Firstly, the machine’s electromagnetic design is conducted by the finite element method to accurately account for machine losses. Then machine’s cooling configurations are introduced, and their effectiveness is validated by lumped parameter thermal network (LPTN). Investigation shows that using potting, sleeve materials to assist non-hybrid cooling configuration makes the machine’s winding and PM temperature closer to hybrid cooling configuration. Therefore, the machine with non-hybrid cooling is prototyped and tested due to its simplicity, lower energy consumption and can still maintain the lifespan and performance of the HSPMSM.

Keywords: airflow network, axial ventilation, high-speed PMSM, thermal network

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Authors: Michael Lousis

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The kind of the most important and conspicuous errors the students made during the three-years of testing of their progress in Algebra are presented in this article. The way these students’ errors changed over three-years of school Algebra learning also is shown. The sample is comprised of two hundred (200) English students and one hundred and fifty (150) Greek students, who were purposefully culled according to their participation in each occasion of testing in the development of the three-year Kassel Project in England and Greece, in both domains at once of Arithmetic and Algebra. Hence, for each of these English and Greek students, six test-scripts were available and corresponded to the three occasions of testing in both Arithmetic and Algebra respectively.

Keywords: algebra, errors, Kassel Project, progress of learning

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Authors: María Laura Guevara Campos

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The increasing number of vending machines makes it easy for people to find them more frequently in stores, universities, workplaces, and even hospitals. These machines usually offer products with high contents of sugar and fat, which, if consumed regularly, can result in serious health threats, as overweight and obesity. Additionally, the energy consumption of these machines tends to be high, which has an impact on the environment as well. In order to promote the consumption of healthy food, a vending machine was designed to give the customer the opportunity to choose between a customized fruit salad and a customized fruit juice, both of them prepared instantly with the ingredients selected by the customer. The main parameters considered to design the machine were: the storage of the preferred fruits in a salad and/or in a juice according to a survey, the size of the machine, the use of ecologic recipients, and the overall energy consumption. The methodology used for the design was the one proposed by the German Association of Engineers for mechatronics systems, which breaks the design process in several stages, from the elaboration of a list of requirements through the establishment of the working principles and the design concepts to the final design of the machine, which was done in a 3D modelling software. Finally, with the design of this machine, the aim is to contribute to the development and implementation of healthier vending machines that offer freshly-made products, which is not being widely attended at present.

Keywords: design, design methodology, mechatronics systems, vending machines

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Authors: Y. Galerkin, K. Soldatova, A. Drozdov

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The 6th version of Universal modeling method for centrifugal compressor stage calculation is described. Identification of the new mathematical model was made. As a result of identification the uniform set of empirical coefficients is received. The efficiency definition error is 0,86 % at a design point. The efficiency definition error at five flow rate points (except a point of the maximum flow rate) is 1,22 %. Several variants of the stage with 3D impellers designed by 6th version program and quasi three-dimensional calculation programs were compared by their gas dynamic performances CFD (NUMECA FINE TURBO). Performance comparison demonstrated general principles of design validity and leads to some design recommendations.

Keywords: compressor design, loss model, performance prediction, test data, model stages, flow rate coefficient, work coefficient

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Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh

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Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.

Keywords: universal filter, image enhancement, neural networks, computer vision

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Authors: M. Kollar, A. Zieba

Abstract:

In this paper, we present a method for a time synchronization between the two eNodeBs (eNBs) in E-UTRAN (Evolved Universal Terrestrial Radio Access) network. The two eNBs are cooperating in so-called inter eNB CA (Carrier Aggregation) case and connected via asymmetrical IP network. We solve the problem by using broadcasting signals generated in E-UTRAN as synchronization signals. The results show that the time synchronization with the proposed method is possible with the error significantly less than 1 ms which is sufficient considering the time transmission interval is 1 ms in E-UTRAN. This makes this method (with low complexity) more suitable than Network Time Protocol (NTP) in the mobile applications with generated broadcasting signals where time synchronization in asymmetrical network is required.

Keywords: IP scheduled throughput, E-UTRAN, Evolved Universal Terrestrial Radio Access Network, NTP, Network Time Protocol, assymetric network, delay

Procedia PDF Downloads 361

Authors: Lidya Hailu, Ramesh Duraisamy, Masood Akhtar Khan, Belete Yilma

Abstract:

Disposable food packaging is a single-use plastics that can include any disposable plastic item which could be designed and use only once. In this context, this study aimed to prepare and evaluate bioplastic food packaging material from avocado seed starch and sugarcane bagasse cellulose and to characterise avocado seed starch. Performed the physicomechanical, structural, thermal properties, and biodegradability of raw materials and readily prepared bioplastic using the universal tensile testing machine, FTIR, UV-Vis spectroscopy, TGA, XRD, and SEM. Results have shown that an increasing amount of glycerol (3-5 mL) resulted in increases in water absorption, density, water vapor permeability, and elongation at the break of prepared bioplastic. However, it causes decreases in % transmittance, thermal degradation, and the tensile strength of prepared bioplastic. Likewise, the addition of cellulose fiber (0-15 %) increases % transmittance ranged (91.34±0.12-63.03±0.05 %), density (0.93±0.04-1.27±0.02 g/cm3), thermal degradation (310.01-321.61°C), tensile strength (2.91±6.18-4.21±6.713 MPa) of prepared bioplastic. On the other hand, it causes decreases in water absorption (14.4±0.25-9.40±0.007 %), water vapor permeability (9.306x10-12±0.3-3.57x10-12±0.15 g•s−1•m−1•Pa−1) and elongation at break (34.46±3.37-27.63±5.67 %) of prepared bioplastic. All the readily prepared bioplastic films rapidly degraded in the soil in the first 6 days and decompose within 12 days with a diminutive leftover and completely degraded within 15 days under an open soil atmosphere. Studied results showed starch derived bioplastic reinforced with 15 % cellulose fiber that plasticized with 3 mL of glycerol had improved results than other combinations of glycerol and bagasse cellulose with avocado seed starch. Thus, biodegradable disposable food packaging cup has been successfully produced in the lab-scale level using the studied approach. Biodegradable disposable food packaging materials have been successfully produced by employing avocado seed starch and sugarcane bagasse cellulose. The future study should be done on nano scale production since this study was done at the micro level.

Keywords: avocado seed, food packaging, glycerol, sugarcane bagasse

Procedia PDF Downloads 339