Search results for: small signal model

Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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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: Ioanna H. Lioliou, Despoina D. Zavraka

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The radical reformation that Greek urban space, has undergone over the last century, due to the socio-historical developments, technological development and political–geographic factors, has left its imprint on the urban landscape. While the big cities struggle to regain urban landscape balance, small towns are considered to offer high quality lifescapes, ensuring sustainable development potential. However, their unplanned urbanization process led to the loss of significant areas of nature, lack of essential infrastructure, chaotic built environment, incompatible land uses and urban cohesiveness. Natural environment reference points, such as springs, streams, rivers, forests, suburban greenbelts, and etc.; seems to be detached from urban space, while the public, open and green spaces, unequally distributed in the built environment, they are no longer able to offer a complete experience of nature in the city. This study focuses on Greek mainland, a small town Elassona, and aims to restore spatial coherence between the city’s homonymous river and its urban space surroundings. The existence of a linear aquatic ecosystem, is considered a precious greenway, also referred as blueway, able to initiate natural penetrations and ecosystems empowering. The integration of disconnected natural ecosystems forms the basis of a strategic intervention scheme, where the river becomes the urban integration tool / feature, constituting the main urban corridor and an indispensible part of a wider green network that connects open and green spaces, ensuring the function of all the established networks (transportation, commercial, social) of the town. The proposed intervention, introduces a green network highlighting the old stone bridge at the ‘entrance’ of the river in the town and expanding throughout the town with strategic uses and activities, providing accessibility for all the users. The methodology used, is based on the collection of design tools used in related urban river-design interventions around the world. The reinstallation/reactivation of the balance between natural and urban landscape, besides the environmental benefits, contributes decisively to the illustration/projection of urban green identity and re-enhancement of the quality of lifescape qualities and social interaction.

Keywords: green network, rehabilitation scheme, urban landscape, urban streams

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Authors: Liu-Chao Qiu

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The damage caused by surge waves generated in water bodies by flow-like landslides can be very high in terms of human lives and economic losses. The complicated phenomena occurred in this highly unsteady process are difficult to model because three interacting phases: air, water and sediment are involved. The problem therefore is challenging since the effects of non-Newtonian fluid describing the rheology of the flow-like landslides, multi-phase flow and free surface have to be included in the simulation. In this work, the commercial computational fluid dynamics (CFD) package FLUENT is used to model the surge waves due to flow-like landslides. The comparison between the numerical results and experimental data reported in the literature confirms the accuracy of the method.

Keywords: flow-like landslide, surge wave, VOF, non-Newtonian fluids, multi-phase flows, free surface flow

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Authors: Tappei Yotsumoto, Atsushi Nomura, Kozo Tanigawa, Kenichi Takahashi, Takao Kawamura, Kazunori Sugahara

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In a human tracking system, expanding a monitoring range of one system is complicating the management of devices and increasing its cost. Therefore, we propose a method to realize a wide-range human tracking by connecting small systems. In this paper, we examined an agent deploy method and information contents across the heterogeneous human tracking systems. By implementing the proposed method, we can construct a human tracking system across heterogeneous systems, and the system can track a target continuously between systems.

Keywords: human tracking system, mobile agent, monitoring, heterogeneous systems

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Authors: Gongbing Shan, Shiming Li, Zhao Zhang, Bingjun Wan

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Badminton originated in ancient civilizations in Europe and Asia more than 2000 years ago. Presently, it is played almost everywhere with estimated 220 million people playing badminton regularly, ranging from professionals to recreational players; and it is the second most played sport in the world after soccer. In Asia, the popularity of badminton and involvement of people surpass soccer. Unfortunately, scientific researches on badminton skills are hardly proportional to badminton’s popularity. A search of literature has shown that the literature body of biomechanical investigations is relatively small. One of the dominant skills in badminton is the forehand overhead smash, which consists of 1/5 attacks during games. Empirical evidences show that one has to adjust the body position in relation to the coming shuttlecock to produce a powerful and accurate smash. Therefore, positioning is a fundamental aspect influencing smash quality. A search of literature has shown that there is a dearth/lack of study on this fundamental aspect. The goals of this study were to determine the influence of positioning and training experience on smash quality in order to discover information that could help learn/acquire the skill. Using a 10-camera, 3D motion capture system (VICON MX, 200 frames/s) and 15-segment, full-body biomechanical model, 14 skilled and 15 novice players were measured and analyzed. Results have revealed that the body positioning has direct influence on the quality of a smash, especially on shuttlecock release angle and clearance height (passing over the net) of offensive players. The results also suggest that, for training a proper positioning, one could conduct a self-selected comfort position towards a statically hanged shuttlecock and then step one foot back – a practical reference marker for learning. This perceptional marker could be applied in guiding the learning and training of beginners. As one gains experience through repetitive training, improved limbs’ coordination would increase smash quality further. The researchers hope that the findings will benefit practitioners for developing effective training programs for beginners.

Keywords: 3D motion analysis, biomechanical modeling, shuttlecock release speed, shuttlecock release angle, clearance height

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Authors: Salina Yahya Saddick

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Ovarian cancer remains the most lethal gynecological malignancy due to the lack of highly sensitive and specific screening tools for detection of early-stage disease. The OSE provides the progenitor cells for 90% of human ovarian cancers. Recent morphologic, immunohistochemical and molecular genetic studies have led to the development of a new paradigm for the pathogenesis and origin of epithelial ovarian cancer (EOC) based on a ualistic model of carcinogenesis that divides EOC into two broad categories designated Types I and II which are characterized by specific mutations, including KRAS, BRAF, ERBB2, CTNNB1, PTEN PIK3CA, ARID1A, and PPPR1A, which target specific cell signaling pathways. Type 1 tumors rarely harbor TP53. type I tumors are relatively genetically stable and typically display a variety of somatic sequence mutations that include KRAS, BRAF, PTEN, PIK3CA CTNNB1 (the gene encoding beta catenin), ARID1A and PPP2R1A but very rarely TP53 . The cancer stem cell (CSC) hypothesis postulates that the tumorigenic potential of CSCs is confined to a very small subset of tumor cells and is defined by their ability to self-renew and differentiate leading to the formation of a tumor mass. Potential protein biomarker miRNA, are promising biomarkers as they are remarkably stable to allow isolation and analysis from tissues and from blood in which they can be found as free circulating nucleic acids and in mononuclear cells. Recently, genomic anaylsis have identified biomarkers and potential therapeutic targets for ovarian cancer namely, FGF18 which plays an active role in controlling migration, invasion, and tumorigenicity of ovarian cancer cells through NF-κB activation, which increased the production of oncogenic cytokines and chemokines. This review summarizes update information on epithelial ovarian cancers and point out to the most recent ongoing research.

Keywords: epithelial ovarian cancers, somatic sequence mutations, cancer stem cell (CSC), potential protein, biomarker, genomic analysis, FGF18 biomarker

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Authors: Tareg M. Elsunaki, Suleiman A. Arafa, Mohamed A. Abd-Alla

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New interesting thermal stable polyesters containing 1-methyl-4-piperidone moiety in the main chain have been synthesized. These polyesters were synthesized by interfacial polycondensation technique of 3,5-bis(4-hydroxybenzylidene)-1-methyl-4-piperidone (I) and 3,5-bis(4-hydroxy-3-methoxy benzyli-dene)-1-methyl-4-piperidone (II) with terphthaloyl, isophthaloyl, 4,4'-diphenic, adipoyl and sebacoyl dichlorides. The yield and the values of the reduced viscosity of the produced polyesters were found to be affected by the type of an organic phase. In order to characterize these polymers, the necessary model compounds (A), (B) were prepared from (I), (II) respectively and benzoyl chloride. The structure of monomers (I), (II), model compounds and resulting polyesters were confirmed by IR, elemental analysis and 1HNMR spectroscopy. The various characteristic of the resulting polymers including solubility, thermal properties, viscosity and X-ray analysis were also studied.

Keywords: synthesis, characterization, new polyesters, chemistry

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Authors: Martha E. Aguiar-Barrera, Humberto Gutierrez-Pulido, Veronica Vargas-Alejo

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Identifying and modeling random phenomena is a fundamental cognitive process to understand and transform reality. Recognizing situations governed by chance and giving them a scientific interpretation, without being carried away by beliefs or intuitions, is a basic training for citizens. Hence the importance of generating teaching-learning processes, supported using technology, paying attention to model creation rather than only executing mathematical calculations. In order to develop the student's knowledge about basic probability distributions and decision making; in this work a model eliciting activity (MEA) is reported. The intention was applying the Model and Modeling Perspective to design an activity related to civil engineering that would be understandable for students, while involving them in its solution. Furthermore, the activity should imply a decision-making challenge based on sample data, and the use of the computer should be considered. The activity was designed considering the six design principles for MEA proposed by Lesh and collaborators. These are model construction, reality, self-evaluation, model documentation, shareable and reusable, and prototype. The application and refinement of the activity was carried out during three school cycles in the Probability and Statistics class for Civil Engineering students at the University of Guadalajara. The analysis of the way in which the students sought to solve the activity was made using audio and video recordings, as well as with the individual and team reports of the students. The information obtained was categorized according to the activity phase (individual or team) and the category of analysis (sample, linearity, probability, distributions, mechanization, and decision-making). With the results obtained through the MEA, four obstacles have been identified to understand and apply the binomial distribution: the first one was the resistance of the student to move from the linear to the probabilistic model; the second one, the difficulty of visualizing (infering) the behavior of the population through the sample data; the third one, viewing the sample as an isolated event and not as part of a random process that must be viewed in the context of a probability distribution; and the fourth one, the difficulty of decision-making with the support of probabilistic calculations. These obstacles have also been identified in literature on the teaching of probability and statistics. Recognizing these concepts as obstacles to understanding probability distributions, and that these do not change after an intervention, allows for the modification of these interventions and the MEA. In such a way, the students may identify themselves the erroneous solutions when they carrying out the MEA. The MEA also showed to be democratic since several students who had little participation and low grades in the first units, improved their participation. Regarding the use of the computer, the RStudio software was useful in several tasks, for example in such as plotting the probability distributions and to exploring different sample sizes. In conclusion, with the models created to solve the MEA, the Civil Engineering students improved their probabilistic knowledge and understanding of fundamental concepts such as sample, population, and probability distribution.

Keywords: linear model, models and modeling, probability, randomness, sample

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Authors: Sufrin Hannan, Budi Suharjo, Rita Nurmalina, Kirbrandoko

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The challenge for independent surveyor service companies now is growing with increasing uncertainty in business. Protection from the government for domestic independent surveyor industry from competitor attack, such as entering the global surveyors to Indonesia also no longer exists. Therefore, building customer loyalty becomes very important to create a long-term relationship between an independent surveyor with its customers. This study aims to develop a model that can be used to build customer loyalty by looking at various factors that determine customer loyalty, especially on independent surveyors for coal inspection in Indonesia. The development of this model uses the relationship marketing approach. Testing of the hypothesis is done by testing the variables that determine customer loyalty, either directly or indirectly, which amounted to 10 variables. The data were collected from 200 questionnaires filled by independent surveyor company decision makers from 51 exporting companies and coal trading companies in Indonesia and analyzed using Structural Equation Model (SEM). The results show that customer loyalty of independent surveyors is influenced by customer satisfaction, trust, switching-barrier, and relationship-bond. Research on customer satisfaction shows that customer satisfaction is influenced by the perceived quality and perceived value, while perceived quality is influenced by reliability, assurance, responsiveness, and empathy.

Keywords: relationship marketing, customer loyalty, customer satisfaction, switching barriers, relationship bonds

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Authors: Emma Van Schie

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The purpose of this study is to use mixed methods research to create typologies of the performance of firms in the cotton-to-clothing value chain in Zimbabwe, and to use these typologies to achieve the objective of adding to the small pool of studies on Sub-Saharan African value chains performing in the context of economic liberalisation and achieving development. The uptake of economic liberalisation measures across Sub-Saharan Africa has led to the restructuring of many value chains. While this action has resulted in some African economies positively reintegrating into global commodity chains, it has also been deeply problematic for the development impacts of the majority of others. Over and above this, these nations have been placed at a disadvantage due to the fact that there is little scholarly and policy research on approaches for managing economic liberalisation and value chain development in the unique African context. As such, the central question facing these less successful cases is how they can integrate into the world economy whilst still fostering their development. This paper draws from quantitative questionnaires and qualitative interviews with 28 stakeholders in the cotton-to-clothing value chain in Zimbabwe. This paper examines the performance of firms in the value chain, and the subsequent local socio-economic development impacts that are affected by the revival of the cotton-to-clothing value chain following its collapse in the wake of Zimbabwe’s uptake of economic liberalisation measures. Firstly, the paper finds the relatively undocumented characteristics and structures of firms in the value chain in the post-economic liberalisation era. As well as this, it finds typologies of the status of firms as either being in operation, closed down, or being placed under judicial management and the common characteristics that these typologies hold. The key findings show how a mixture of macro and local level aspects, such as value chain governance and the management structure of a business, leads to the most successful typology that is able to add value to the chain in the context of economic liberalisation, and thus unlock its socioeconomic development potential. These typologies are used in making industry and policy recommendations on achieving this balance between the macro and the local level, as well as recommendations for further academic research for more typologies and models on the case of cotton value chains in Sub-Saharan Africa. In doing so, this study adds to the small collection of academic evidence and policy recommendations for the challenges that African nations face when trying to incorporate into global commodity chains in attempts to benefit from their associated socioeconomic development opportunities.

Keywords: cotton-to-clothing value chain, economic liberalisation, restructuring value chain, typologies of firms, value chain governance, Zimbabwe

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Authors: Wenxin Mei, Jinhua Sun, Qingsong Wang

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The volume expansion of lithium-ion batteries is mainly induced by intercalation induced stress within the negative electrode, resulting in capacity degradation and even battery failure. Stress generation due to lithium intercalation into graphite particles is investigated based on an electrochemical-mechanical model in this work. The two-dimensional model presented is fully coupled, inclusive of the impacts of intercalation-induced stress, stress-induced intercalation, to evaluate the lithium concentration, stress generation, and displacement intra and inter-particle. The results show that the distribution of lithium concentration and stress exhibits an analogous pattern, which reflects the relation between lithium diffusion and stress. The results of inter-particle stress indicate that larger Von-Mises stress is displayed where the two particles are in contact with each other, and deformation at the edge of particles is also observed, predicting fracture. Additionally, the maximum inter-particle stress at the end of lithium intercalation is nearly ten times the intraparticle stress. And the maximum inter-particle displacement is increased by 24% compared to the single-particle. Finally, the effect of graphite particle arrangement on inter-particle stress is studied. It is found that inter-particle stress with tighter arrangement exhibits lower stress. This work can provide guidance for predicting the intra and inter-particle stress to take measures to avoid cracking of electrode material.

Keywords: electrochemical-mechanical model, graphite particle, lithium concentration, lithium ion battery, stress

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Authors: K. Julia Rose Mary, Victor Arokia Doss

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Electrical and chemical stimulations up-regulate phosphorylaion of CREB, a transcriptional factor that induces its target gene production for memory consolidation and Late Long-Term Potentiation (L-LTP) in CA1 region of the hippocampus. L-LTP requires complex interactions among second-messenger signaling cascade molecules such as cAMP, CAMKII, CAMKIV, MAPK, RSK, PKA, all of which converge to phosphorylate CREB which along with CBP induces the transcription of target genes involved in memory consolidation. A differential equation based model for L-LTP representing stimulus-mediated activation of downstream mediators which confirms the steep, supralinear stimulus-response effects of activation and inhibition was used. The same was extended to accommodate the inhibitory effect of the Inducible cAMP Early Repressor (ICER). ICER is the natural inducible CREB antagonist represses CRE-Mediated gene transcription involved in long-term plasticity for learning and memory. After verifying the sensitivity and robustness of the model, we had simulated it with various empirical levels of repressor concentration to analyse their effect on the gene induction. The model appears to predict the regulatory dynamics of repression on the L-LTP and agrees with the experimental values. The flux data obtained in the simulations demonstrate various aspects of equilibrium between the gene induction and repression.

Keywords: CREB, L-LTP, mathematical modeling, simulation

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Authors: Antonis Skouloudis, Konstantinos Evangelinos, Walter Leal-Filho, Panagiotis Vouros, Ioannis Nikolaou

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Organizational resilience capacity to extreme weather events (EWEs) has sparked a growth in scholarly attention over the past decade as an essential aspect in business continuity management, with supporting evidence for this claim to suggest that it retains a key role in successful responses to adverse situations, crises and shocks. Small and medium-sized enterprises (SMEs) are more vulnerable to face floods compared to their larger counterparts, so they are disproportionately affected by such extreme weather events. The limited resources at their disposal, the lack of time and skills all conduce to inadequate preparedness to challenges posed by floods. SMEs tend to plan in the short-term, reacting to circumstances as they arise and focussing on their very survival. Likewise, they share less formalised structures and codified policies while they are most usually owner-managed, resulting in a command-and-control management culture. Such characteristics result in them having limited opportunities to recover from flooding and quickly turnaround their operation from a loss making to a profit making one. Scholars frame the capacity of business entities to be resilient upon an EWE disturbance (such as flash floods) as the rate of recovery and restoration of organizational performance to pre-disturbance conditions, the amount of disturbance (i.e. threshold level) a business can absorb before losing structural and/or functional components that will alter or cease operation, as well as the extent to which the organization maintains its function (i.e. impact resistance) before performance levels are driven to zero. Nevertheless, while it seems to be accepted as an essential trait of firms effectively transcending uncertain conditions, research deconstructing the enabling conditions and/or inhibitory factors of SMEs resilience capacity to natural hazards is still sparse, fragmentary and mostly fuelled by anecdotal evidence or normative assumptions. Focusing on the individual level of analysis, i.e. the individual enterprise and its endeavours to succeed, the emergent picture from this relatively new research strand delineates the specification of variables, conceptual relationships or dynamic boundaries of resilience capacity components in an attempt to provide prescriptions for policy-making as well as business management. This study will present the development of a flood resilience capacity index (FRCI) and its application to Greek SMEs. The proposed composite indicator pertains to cognitive, behavioral/managerial and contextual factors that influence an enterprise’s ability to shape effective responses to meet flood challenges. Through the proposed indicator-based approach, an analytical framework is set forth that will help standardize such assessments with the overarching aim of reducing the vulnerability of SMEs to flooding. This will be achieved by identifying major internal and external attributes explaining resilience capacity which is particularly important given the limited resources these enterprises have and that they tend to be primary sources of vulnerabilities in supply chain networks, generating Single Points of Failure (SPOF).

Keywords: Floods, Small & Medium-Sized enterprises, organizational resilience capacity, index development

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Authors: Abdelkrim Alfalah, Lahcen Ouarbya, John Howroyd

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This paper investigates and compares the performance of four existing distances and similarity measures between partitions. The partition measures considered are Rand Index (RI), Adjusted Rand Index (ARI), Variation of Information (VI), and Normalised Variation of Information (NVI). This work investigates the ability of these partition measures to capture three predefined intuitions: the variation within randomly generated partitions, the sensitivity to small perturbations, and finally the independence from the dataset scale. It has been shown that the Adjusted Rand Index performed well overall, with regards to these three intuitions.

Keywords: clustering, comparing partitions, similarity measure, partition distance, partition metric, similarity between partitions, clustering comparison.

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Authors: Reza Rezaeipour Honarmandzad

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In this paper we propose an ANN for detection and localization of fatigue damage in aircraft structures. We used network of piezoelectric transducers for Lamb-wave measurements in order to calculate damage indices. Data gathered by the sensors was given to neural network classifier. A set of neural network electors of different architecture cooperates to achieve consensus concerning the state of each monitored path. Sensed signal variations in the ROI, detected by the networks at each path, were used to assess the state of the structure as well as to localize detected damage and to filter out ambient changes. The classifier has been extensively tested on large data sets acquired in the tests of specimens with artificially introduced notches as well as the results of numerous fatigue experiments. Effect of the classifier structure and test data used for training on the results was evaluated.

Keywords: ANN, fatigue damage, aircraft structures, piezoelectric transducers, lamb-wave measurements

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Authors: B. Paygozar, S.A. Dizaji

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Adhesive bonding is a highly valued type of fastening mechanical parts in complex structures, where joining some simple components is always needed. This method is of several merits, such as uniform stress distribution, appropriate bonding strength, and fatigue performance, and lightness, thereby outweighing other sorts of bonding methods. This study is to investigate the failure load of adhesive single-strap joints, including adherends of different sizes and materials. This kind of adhesive joint is very practical in different industries, especially when repairing the existing joints or attaching substrates of dissimilar materials. In this research, experimentally validated numerical analyses carried out in a commercial finite element package, ABAQUS, are utilized to extract the failure loads of the joints, based on the cohesive zone model. In addition, the stress analyses of the substrates are performed in order to acquire the effects of lowering the thickness of the substrates on the stress distribution inside them to avoid designs suffering from the necking or failure of the adherends. It was found out that this method of bonding is really feasible in joining dissimilar materials which can be utilized in a variety of applications. Moreover, the stress analyses indicated the minimum thickness for the adherends so as to avoid the failure of them.

Keywords: cohesive zone model, dissimilar materials, failure load, single strap joint

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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

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Authors: Mequanent Wale Mekonen, Edoardo Otranto, Angela Alibrandi

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Diabetic kidney disease is one of the main microvascular complications caused by diabetes. Several clinical and biochemical variables are reported to be associated with diabetic kidney disease in people with type 2 diabetes. However, their interrelations could distort the effect estimation of these variables for the disease's progression. The objective of the study is to determine how the biochemical and clinical variables in people with type 2 diabetes are interrelated with each other and their effects on kidney disease progression through advanced statistical methods. First, principal component analysis was used to explore how the biochemical and clinical variables intercorrelate with each other, which helped us reduce a set of correlated biochemical variables to a smaller number of uncorrelated variables. Then, ordered logit regression models (cumulative, stage, and adjacent) were employed to assess the effect of biochemical and clinical variables on the order-level response variable (progression of kidney function) by considering the proportionality assumption for more robust effect estimation. This retrospective cross-sectional study retrieved data from a type 2 diabetic cohort in a polyclinic hospital at the University of Messina, Italy. The principal component analysis yielded three uncorrelated components. These are principal component 1, with negative loading of glycosylated haemoglobin, glycemia, and creatinine; principal component 2, with negative loading of total cholesterol and low-density lipoprotein; and principal component 3, with negative loading of high-density lipoprotein and a positive load of triglycerides. The ordered logit models (cumulative, stage, and adjacent) showed that the first component (glycosylated haemoglobin, glycemia, and creatinine) had a significant effect on the progression of kidney disease. For instance, the cumulative odds model indicated that the first principal component (linear combination of glycosylated haemoglobin, glycemia, and creatinine) had a strong and significant effect on the progression of kidney disease, with an effect or odds ratio of 0.423 (P value = 0.000). However, this effect was inconsistent across levels of kidney disease because the first principal component did not meet the proportionality assumption. To address the proportionality problem and provide robust effect estimates, alternative ordered logit models, such as the partial cumulative odds model, the partial adjacent category model, and the partial continuation ratio model, were used. These models suggested that clinical variables such as age, sex, body mass index, medication (metformin), and biochemical variables such as glycosylated haemoglobin, glycemia, and creatinine have a significant effect on the progression of kidney disease.

Keywords: diabetic kidney disease, ordered logit model, principal component analysis, type 2 diabetes

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Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha

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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Keywords: TDNN, neural networks, noise, speech recognition

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Authors: Nadine Yehya, Chantal Maatouk

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Low energy buildings have been developed to achieve global climate commitments in reducing energy consumption. They comprise energy efficient buildings, zero energy buildings, positive buildings and passive house buildings. The reduced energy demands in Low Energy buildings call for advanced building energy modeling that focuses on studying active building systems such as heating, cooling and ventilation, improvement of systems performances, and development of control systems. Modeling and building simulation have expanded to cover different modeling approach i.e.: detailed physical model, dynamic empirical models, and hybrid approaches, which are adopted by various simulation tools. This paper uses DesignBuilder with EnergyPlus simulation engine in order to; First, study the impact of efficiency measures on building energy behavior by comparing Low energy residential model to a conventional one in Beirut-Lebanon. Second, choose the appropriate energy systems for the studied case characterized by an important cooling demand. Third, study dynamic modeling of Variable Refrigerant Flow (VRF) system in EnergyPlus that is chosen due to its advantages over other systems and its availability in the Lebanese market. Finally, simulation of different energy systems models with different modeling approaches is necessary to confront the different modeling approaches and to investigate the interaction between energy systems and building envelope that affects the total energy consumption of Low Energy buildings.

Keywords: physical model, variable refrigerant flow heat pump, dynamic modeling, EnergyPlus, the modeling approach

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Authors: Yash Bingi, Yiqiao Yin

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Reduction of child mortality is an ongoing struggle and a commonly used factor in determining progress in the medical field. The under-5 mortality number is around 5 million around the world, with many of the deaths being preventable. In light of this issue, Cardiotocograms (CTGs) have emerged as a leading tool to determine fetal health. By using ultrasound pulses and reading the responses, CTGs help healthcare professionals assess the overall health of the fetus to determine the risk of child mortality. However, interpreting the results of the CTGs is time-consuming and inefficient, especially in underdeveloped areas where an expert obstetrician is hard to come by. Using a support vector machine (SVM) and oversampling, this paper proposed a model that classifies fetal health with an accuracy of 99.59%. To further explain the CTG measurements, an algorithm based on Randomized Input Sampling for Explanation ((RISE) of Black-box Models was created, called Feature Alteration for explanation of Black Box Models (FAB), and compared the findings to Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME). This allows doctors and medical professionals to classify fetal health with high accuracy and determine which features were most influential in the process.

Keywords: machine learning, fetal health, gradient boosting, support vector machine, Shapley values, local interpretable model agnostic explanations

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Authors: Hanan Mikhael Dawood, Haider Salim, Jafar Al-Wash

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This paper presents Proportional-Integral (PI) controller to improve the system performance which gives better torque and flux response. In addition, it reduces the undesirable torque ripple. The conventional DTC controller approach for induction machines, based on an improved torque and stator flux estimator, is implemented using Xilinx System Generator (XSG) for MATLAB/Simulink environment through Xilinx blocksets. The design was achieved in VHDL which is based on a MATLAB/Simulink simulation model. The hardware in the loop results are obtained considering the implementation of the proposed model on the Xilinx NEXYS2 Spartan 3E1200 FG320 Kit.

Keywords: induction motor, Direct Torque Control (DTC), Xilinx FPGA, motor drive

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Authors: Nour Charara, Hussein Charara, Omar Abou Khaled, Hani Abdallah, Elena Mugellini

Abstract:

In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.

Keywords: activity modeling, clustering, PLSA, video representation

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Authors: Kazuo Nishimura, Junichi Hirata, Tadashi Yagi, Junko Urasaka

Abstract:

This paper is an investigation of the effect of science education during the high school education how science graduates of universities are appreciated in the labor market in Japan. We conducted a survey utilizing the internet and analyzed the subjects they were good at and their annual income. The results confirm that among science graduates, workers adept at physics tend to have higher incomes compared to workers good at other subjects. Generational analysis based on the curriculum guideline amendments reveals that the generational difference is small among science majors who are good at physics.

Keywords: curriculum, income, physics, science

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Authors: Maslan Lamria, Ralph E. H. Sims, Tatang H. Soerawidjaja

Abstract:

In increasing its self-sufficiency on transportation fuel, Indonesia is currently developing commercial production and use of drop-in biofuel (DBF) from vegetable oil. To maximize the level of success, it is necessary to get insights on how the implementation would develop as well as any important factors. This study assessed the dynamics of transition from existing fossil fuel system to a renewable fuel system, which involves the transition from existing biodiesel to projected DBF. A systems dynamics approach was applied and a model developed to simulate the dynamics of liquid biofuel transition. The use of palm oil feedstock was taken as a case study to assess the projected DBF implementation by 2045. The set of model indicators include liquid fuel self-sufficiency, liquid biofuel share, foreign exchange savings and green-house gas emissions reduction. The model outputs showed that supports on DBF investment and use play an important role in the transition progress. Given assumptions which include application of a maximum level of supports over time, liquid fuel self-sufficiency would be still unfulfilled in which palm biofuel contribution is 0.2. Thus, other types of feedstock such as algae and oil feedstock from marginal lands need to be developed synergically. Regarding support on DBF use, this study recommended that removal of fossil subsidy would be necessary prior to applying a carbon tax policy effectively.

Keywords: biofuel, drop-in biofuel, energy transition, liquid fuel

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Authors: Koichi Kurita

Abstract:

In this study, we propose a real-time data collection technique for the detection of human walking motion from the charge generated on the human body. This technique is based on the detection of a sub-picoampere electrostatic induction current, generated by the motion, flowing through the electrode of a wireless portable sensor attached to the subject. An FFT analysis of the wave-forms of the electrostatic induction currents generated by the walking motions showed that the currents generated under normal and restricted walking conditions were different. Moreover, we carried out a cepstrum analysis to detect any differences in the walking style. Results suggest that a slight difference in motion, either due to the individual’s gait or a splinted leg, is directly reflected in the electrostatic induction current generated by the walking motion. The proposed wireless portable sensor enables the detection of even subtle differences in walking motion.

Keywords: human walking motion, motion measurement, current measurement, electrostatic induction

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Authors: Kaushal Kishore, Vaibhav Jain, Hrishikesh Jugade, Saurabh Hadas, Manashi Adhikary, Goutam Mukhopadhyay, Sandip Bhattacharyya

Abstract:

Rotary air compressors in air conditioners are used to suck excessive volume of air from the atmosphere in a small space to provide drive to the components attached to them. Hydraulic test is one of the most important methods to decide the suitability of these components for usage. In the present application, projection welding is used to join the hot rolled steel sheets after forming for manufacturing of air compressors. These sheets belong to two different high strength low alloy (HSLA) steel grades. It was observed that one batch of compressors made of a particular grade was cracking from the weld, whereas those made of another grade were passing the hydraulic tests. Cracking was repeatedly observed from the weld location. A detailed comparative study of the compressors which failed and successfully passed pressure tests has been presented. Location of crack initiation was identified to be the interface of fusion zone/heat affected zone. Shear dimples were observed on the fracture surface confirming the ductile mode of failure. Hardness profile across the weld revealed a sharp rise in hardness in the fusion zone. This was attributed to the presence of untempered martensitic lath in the fusion zone. A sharp metallurgical notch existed at the heat affected zone/fusion zone interface due to transition in microstructure from acicular ferrite and bainite in HAZ to untempered martensite in the fusion zone. In contrast, welds which did not fail during the pressure tests showed a smooth hardness profile with no abnormal rise in hardness in the fusion zone. The bainitic microstructure was observed in the fusion zone of successful welds. This difference in microstructural constituents in the fusion zone was attributed to the presence of a small amount of boron (0.002 wt. %) in the sheets which were cracking. Trace amount of boron is known to substantially increase the hardenability of HSLA steel, and cooling rate during resolidification in the fusion zone is sufficient to form martensite. Post-weld heat treatment was recommended to transform untempered martensite to tempered martensite with lower hardness.

Keywords: compressor, cracking, martensite, weld, boron, hardenability, high strength low alloy steel

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Authors: Chuan-Ming Tung, Jin-Cheng Fu, Chia-En Feng

Abstract:

In recent years, the rapid development of urban land in Taiwan has led to the constant increase of the areas of impervious surface, which has increased the risk of waterlogging during heavy rainfall. Therefore, in recent years, promoting runoff allocation responsibilities has often been used as a means of reducing regional flooding. In this study, the single catchment area covering both urban and rural land as the study area is discussed. Based on Storm Water Management Model, urban and rural land in a single catchment area was explored to develop the runoff allocation responsibilities according to their respective control regulation on land use. The impacts of runoff increment and reduction in sub-catchment area were studied to understand the impact of highly developed urban land on the reduction of flood risk of rural land at the back end. The results showed that the rainfall with 1 hour short delay of 2 years, 5 years, 10 years, and 25 years return period. If the study area was fully developed, the peak discharge at the outlet would increase by 24.46% -22.97% without runoff allocation responsibilities. The front-end urban land would increase runoff from back-end of rural land by 76.19% -46.51%. However, if runoff allocation responsibilities were carried out in the study area, the peak discharge could be reduced by 58.38-63.08%, which could make the front-end to reduce 54.05% -23.81% of the peak flow to the back-end. In addition, the researchers found that if it was seen from the perspective of runoff allocation responsibilities of per unit area, the residential area of urban land would benefit from the relevant laws and regulations of the urban system, which would have a better effect of reducing flood than the residential land in rural land. For rural land, the development scale of residential land was generally small, which made the effect of flood reduction better than that of industrial land. Agricultural land requires a large area of land, resulting in the lowest share of the flow per unit area. From the point of the planners, this study suggests that for the rural land around the city, its responsibility should be assigned to share the runoff. And setting up rain water storage facilities in the same way as urban land, can also take stock of agricultural land resources to increase the ridge of field for flood storage, in order to improve regional disaster reduction capacity and resilience.

Keywords: runoff allocation responsibilities, land use, flood mitigation, SWMM

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