Search results for: hard classifiers

Authors: Suha K. Shihab, Zahid A. Khan, Aas Mohammad, Arshad Noor Siddiquee

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This paper presents the influence of cutting parameters (cutting speed, feed and depth of cut) on flank wear (VB) in turning of 52100 hard alloy steel using multilayer coated carbide insert under dry condition. Nine experiments were performed based on Taguchi’s L9 orthogonal array. Analysis of variance (ANOVA) was used to determine the effects of the cutting parameters on flank wear. The results of the study revealed that the cutting speed (A) and feed rate (B) are the dominant factors affecting flank wear, while the depth of cut (C) has not a significant effect. The optimal combination of the cutting parameters for flank wear is found to be A1B1C1. The mathematical model for flank wear is found to be statistically significant. The predicted and measured values of flank wear are found to be very close to each other.

Keywords: flank wear, hard turning, Taguchi approach, optimization

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Authors: Ridvan Yamanoglu

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In the current study, titanium based composites reinforced by hard nickel alloy particles were produced. Powder metallurgical hot pressing technique was used for the fabrication of composite materials. The composites containing different ratio of hard nickel particles were sintered at 900 oC for 15 and 30 minutes under 50 MPa pressure. All titanium based composites were obtained under a vacuum atmosphere of 10-4 mbar to prevent of oxidation of titanium due to its high reactivity to oxygen. The microstructural characterization of the composite samples was carried out by optical and scanning electron microscopy. The mechanical properties of the samples were determined by means of hardness and wear tests. The results showed that when the nickel particle content increased the mechanical properties of the composites enhanced. The results are discussed in detail and optimum nickel particle content were determined.

Keywords: titanium, composite, nickel, hot pressing

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Authors: Sasan Talebnezhad, Parviz Hamidia

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GPC and RMS analysis showed no distinct difference between PE 100 On, Off, and Reference grade. But FTIR spectra and multiple endothermic peaks obtained from SSA analysis, attributed to heterogeneity of ethylene sequence length, lamellar thickness and also the non-uniformity of short chain branching, showed sharp discrepancy and proposed a blend structure of high-density polyethylenes in PE 100 grade. Catalysis along with process parameters dictates poly blend PE 100 structure. This in-reactor blend is a mixture of compatible co-crystallized phases with different crystalinity, forming a physical semi hard and soft segment network responsible for improved impact properties in PE 100 pipe grade. We propose a new approach for PE100 evaluation that is more efficient than normal microstructure characterization.

Keywords: HDPE, pipe grade, in-reactor blend, hard and soft segments

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Authors: Fuad M. Alkoot

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We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.

Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation

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Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

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Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

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Authors: Raghad A. Altowairgi

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With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: S. Somerset, D. J. Hoare, P. Leighton

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Limited participation in physical activity and sport has been linked to poorer mental and physical health in children. Studies have shown that children who participate in sports benefit from improved social skills, self-confidence, communication skills and a better quality of life. Children who participate in sport are also more likely to continue their participation into their adult life. Deaf or hard of hearing children should have the same opportunities to participate in sport and receive the benefits as their hearing peers. Anecdotal evidence suggests this isn’t always the case. This is concerning given there are 45,000 children in the UK with permanent hearing loss. The aim of this study was to understand what encourages or discourages deaf or hard of hearing children to take part in sports. Ethical approval for the study was obtained from the University of Nottingham School of Medicine ethics committee. We conducted eight focus groups with deaf or hard of hearing children aged 10 to 15 years. A total of 45 children (19 male, 26 female) recruited from local schools and sports clubs took part. Information was gathered on the children’s thoughts and feelings about participation in sport. This included whether they played sports and who with, whether they did or did not like sport, and why they got involved in sport. Focus groups were audio recorded and transcribed. Transcripts were analysed using thematic analysis. Several key themes were identified as being associated with levels of sports participation. These included friendships, family and communication. Deaf or hard of hearing children with active siblings had participated in more sports. Communication was a common theme throughout regardless of the type of hearing-assistive technology a child used. Children found communication easier during sport if they were allowed to use their technology and had particular difficulty during sports such as swimming. Children expressed a desire not to have to identify themselves at a club as having a hearing loss. This affected their confidence when participating in sport. Not surprisingly, children who are deaf or hard of hearing are more likely to participate in sport if they have a good support network of parents, coaches and friends. The key barriers to participation for these children are communication, lack of visual information, lack of opportunity and a lack of awareness. By addressing these issues more deaf and hard of hearing children will take part in sport and will continue their participation.

Keywords: barrier, children, deaf, participation, hard of hearing, sport

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Authors: Flavio Cannavo

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Continuous evaluation of the status of potentially hazardous volcanos plays a key role for civil protection purposes. The importance of monitoring volcanic activity, especially for energetic paroxysms that usually come with tephra emissions, is crucial not only for exposures to the local population but also for airline traffic. Presently, real-time surveillance of most volcanoes worldwide is essentially delegated to one or more human experts in volcanology, who interpret data coming from different kind of monitoring networks. Unfavorably, the high nonlinearity of the complex and coupled volcanic dynamics leads to a large variety of different volcanic behaviors. Moreover, continuously measured parameters (e.g. seismic, deformation, infrasonic and geochemical signals) are often not able to fully explain the ongoing phenomenon, thus making the fast volcano state assessment a very puzzling task for the personnel on duty at the control rooms. With the aim of aiding the personnel on duty in volcano surveillance, here we introduce a system based on an ensemble of data-driven classifiers to infer automatically the ongoing volcano status from all the available different kind of measurements. The system consists of a heterogeneous set of independent classifiers, each one built with its own data and algorithm. Each classifier gives an output about the volcanic status. The ensemble technique allows weighting the single classifier output to combine all the classifications into a single status that maximizes the performance. We tested the model on the Mt. Etna (Italy) case study by considering a long record of multivariate data from 2011 to 2015 and cross-validated it. Results indicate that the proposed model is effective and of great power for decision-making purposes.

Keywords: Bayesian networks, expert system, mount Etna, volcano monitoring

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Authors: Sara Mahmood, Omar Ahmed, Youssef Aladham, Moustafa Abdelnaby

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The varied complications of COVID-19 present an ongoing challenge to healthcare professionals. A rare presentation of complicated sinusitis with pre-septal cellulitis and hard palatal necrosis in a COVID-19 patient, was reported. A 52-year-old male was admitted to the hospital with typical COVID manifestations where he had two successive COVID-19 positive swabs. During his admission, he developed symptoms of right orbital complications of sinusitis along with both clinical and radiological evidence of ipsilateral hard palatal necrosis. Imaging confirmed a diagnosis of right pan-sinusitis complicated with right pre-septal infection and hard palatal bony defect on the same side. Intra-operatively, the sphenopalatine artery was found to be thrombosed. This case focuses on the possible association between these manifestations and the known thromboembolic complications of COVID-19. Ongoing management of such complicated rare cases should be through a multidisciplinary team.

Keywords: COVID-19, sinusitis, sphenopalatine artery, thrombosis

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Authors: Amna Khan, Zareena Kausar, Saad Malik

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Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

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Authors: Xiaohan Bookman, Xiaoyan Zhu

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Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

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Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

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The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: color moments, visual thing recognition system, SIFT, color SIFT

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Authors: Mehmet Erdi Korkmaz, Mustafa Günay

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Nowadays, grinding is frequently replaced with hard turning for reducing set up time and higher accuracy. This paper focused on mathematical modeling of average surface roughness (Ra) in hard turning of AISI L2 grade (DIN 1.2210) cold work tool steel with ceramic tools. The steel was hardened to 60±1 HRC after the heat treatment process. Cutting speed, feed rate, depth of cut and tool nose radius was chosen as the cutting conditions. The uncoated ceramic cutting tools were used in the machining experiments. The machining experiments were performed according to Taguchi L27 orthogonal array on CNC lathe. Ra values were calculated by averaging three roughness values obtained from three different points of machined surface. The influences of cutting conditions on surface roughness were evaluated as statistical and experimental. The analysis of variance (ANOVA) with 95% confidence level was applied for statistical analysis of experimental results. Finally, mathematical models were developed using the artificial neural networks (ANN). ANOVA results show that feed rate is the dominant factor affecting surface roughness, followed by tool nose radius and cutting speed.

Keywords: ANN, hard turning, DIN 1.2210, surface roughness, Taguchi method

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Authors: Ramón Aparicio-García, Gustavo Juárez Gracia, Jesús Álvarez Cedillo

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A research line of the computer science that involve the study of the Human-Computer Interaction (HCI), which search to recognize and interpret the user intent by the storage and the subsequent analysis of the electrical signals of the brain, for using them in the control of electronic devices. On the other hand, the affective computing research applies the human emotions in the HCI process helping to reduce the user frustration. This paper shows the results obtained during the hardware and software development of a Brain Computer Interface (BCI) capable of recognizing the human emotions through the association of the brain electrical activity patterns. The hardware involves the sensing stage and analogical-digital conversion. The interface software involves algorithms for pre-processing of the signal in time and frequency analysis and the classification of patterns associated with the electrical brain activity. The methods used for the analysis and classification of the signal have been tested separately, by using a database that is accessible to the public, besides to a comparison among classifiers in order to know the best performing.

Keywords: affective computing, interface, brain, intelligent interaction

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Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

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Authors: Karima Bouakaz, Amel Youcefi, Abdessamad Abada

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We determine a compact analytic expression for the complete next-to-leading contribution to the retarded transverse photons self-energy in the context of hard-thermal-loop summed perturbation of massless quantum electrodynamics (QED) at high temperature to calculate the next-to-leading order dispersion relations for slow-moving transverse photons at high temperature scalar quantum electrodynamics (Scalar QED), using the real time formalism (RTF) in physical representation. We derive the analytic expressions of hard thermal loop (HTL) contributions to propagators and vertices to determine the expressions of the effective propagators and vertices in RTF that contribute to the complete next-to leading order contribution of retarded transverse photons self-energy.

Keywords: hard thermal loop, hot scalar QED, NLO computations, soft transverse photons

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Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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Authors: Shivani Yadav

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The paper will first elaborate on the concept of soft power as formulated by Joseph Nye, who argues that soft power is as important as hard power in international politics as it replaces coercion with non-coercive forms of co-optation and attraction. The central tenet of the paper is to extrapolate the continued relevance of soft power in international relations in the 21st century. It is argued that the relevance of soft power, in concurrence with hard power, is on the rise in the international system. This is found to be emanating out of two factors. First, the state-centric practice of international relations has expanded to allow other actors to participate in policymaking. This has led to the resources for power generation to become varied, largely move away from the control of governments, and to produce both hard and soft power attributes. Second, as the currency of coercive power seems to be devaluing in global politics, the role of intangible factors like soft power is getting more important in policymaking. The paper will then go on to elaborate on the critiques of the formulation of soft power from various perspectives, as well as the defenses to these critiques presented by soft power proponents. The paper will reflect on the continued relevance of soft power in international politics by giving the example of India, and how soft power has continued to serve its policy objectives over the years. It is observed that even as India is recognized as a rising superpower today, yet it has made a continuous effort in cultivating its soft power resources, which have proven to be its assets in furthering its foreign policy interests. In conclusion, the paper makes the point that soft power, in conjunction with hard power, will shape international politics in the coming times.

Keywords: foreign policy, India’s soft power, international politics, smart power, soft power

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Authors: Hina Verma, Karine Le Guen, Renaud Dalaunay, Iyas Ismail, Vita Ilakovac, Jean Pascal Rueff, Yunlin Jacques Zheng, Philippe Jonnard

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To the extent of our knowledge, X-ray emission spectroscopy (XES) has been applied in the soft x-ray region (photon energy ≤ 2 keV) to study the buried layers and interfaces of stacks of nanometer-thin films. Now we extend the methodology to study the buried interfaces in the hard X-ray region (i.e., ≥ five keV). The emission spectra allow us to study the interactions between elements in the buried layers from the analysis of their valence states, thereby providing sensitive information about the physical-chemical environment of the emitting element in multilayers. We exploit the chemical sensitivity of XES to study the interfaces between Fe and Si layers in the Fe/Si multilayer from the Fe Kβ₂,₅ emission spectra (7108 eV). The Fe Kβ₅ emission line results from the electronic transition from occupied 3d to 1s levels (i.e., valence to core transition) and is hence sensitive to the chemical state of emitting Fe atoms. The comparison of emission spectra recorded for Fe/Si multilayer with Fe and FeSi₂ references reveal the formation of FeSi₂ at the Fe-Si interfaces inside the multilayer stack. The interfacial thickness was calculated to be 1.4 ± 0.2 nm by taking into consideration the intensity of Fe atoms emitted from the interface and the Fe layer. The formation of FeSi₂ at the interface was further confirmed by the X-ray diffraction and X-ray photoelectron spectroscopy done on the Fe/Si multilayer. Hence, we can conclude that the XES in the hard X-ray range could be used to study multilayers and their interfaces and obtain information both qualitatively and quantitatively.

Keywords: buried interfaces, hard X-ray emission spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy

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Authors: Sukron Makmun, Topan Firmandha, Siswanto

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Ultimate Strength Assessment on ship cross section in accordance with Biro Klasifikasi Indonesia (BKI) Rules for Hull, follows step by step incremental iterative approach. In this approach, ship cross section is divided into plate-stiffener combinations and hard corners element. The average stress-strain relationship (σ-ε) for all structural elements will be defined, where the subscript k refers to the modes 0, 1, 2, 3 or 4. These results would be verified with a commercial software calculation in similar cases. The numerical calculations of buckling strength are in accordance with the commercial software (GL Rules ND). Then the comparison of failure behaviours of stiffened panels and hard corners are presented. Where failure modes 3 are likely to occur first follows the failure mode 4 and the last one is the failure mode 1.

Keywords: ultimate strength assessment, BKI rules, incremental, plate-stiffener combination and hard corner, commercial software

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Authors: Theodore Grosch, Felipe Koji Godinho Hoshino

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In wireless communications, 3GPP LTE is one of the solutions to meet the greater transmission data rate demand. One issue inherent to this technology is the PAPR (Peak-to-Average Power Ratio) of OFDM (Orthogonal Frequency Division Multiplexing) modulation. This high PAPR affects the efficiency of power amplifiers. One approach to mitigate this effect is the Crest Factor Reduction (CFR) technique. In this work, we simulate the impact of Hard Limited Clipping Crest Factor Reduction technique on BER (Bit Error Rate) in OFDM based Systems. In general, the results showed that CFR has more effects on higher digital modulation schemes, as expected. More importantly, we show the worst-case degradation due to CFR on QPSK, 16QAM, and 64QAM signals in a linear system. For example, hard clipping of 9 dB results in a 2 dB increase in signal to noise energy at a 1% BER for 64-QAM modulation.

Keywords: bit error rate, crest factor reduction, OFDM, physical layer simulation

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Authors: Cheniti Khalissa, Dekhili Mohamed

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Several fungal diseases may infect hard and soft wheat, which directly affect the yield and thus the economy of the homeland. So, a treatment fungicide is one of means of diseases control. In this context, we studied two varieties of wheat; Waha for soft wheat and Hidhab for hard wheat, at the level of the Technical Institute of crops (ITGC) in the wilaya of Setif under semi-arid conditions. This study consists of a successive application of three fungicides (Tilt, Artea, and Armistarxtra) according to three treatments (T1, T2, and T3) in addition to the witness (T0) at different stages of plant development (respectively, Montaison, earing and after flowering) whose purpose is to test and determine the effectiveness of these products used sequentially. The study showed good efficacy when we use the sum of these pesticides The comparison between these different treatments indicates that the T3 treatment reduced yield losses significantly; which is evident in the main yield components such as fertility, grain yield and weight of 1000 grains. The various components of yield and final yield are all parameters to be taken into account in such a study. In general, the fungal treatment is an effective way of improving profitability. In general, the fungal treatment is an effective way of improving profitability and positioning interventions in time is one of the requirements for an appreciable efficiency.

Keywords: hard wheat, soft wheat, diseases, fungicide treatment, fertility, 1000-grain weight, semi-arid zone

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Authors: Yanhua Ma, Lu Zhai, Xinchen Wang, Hongyu Liang

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In this paper, by understanding the development status of the human-machine interface in today's automobile cab, a subjective and objective evaluation system for evaluating the optimization of human-machine interface matching in automobile cab was established. The man-machine interface of the car cab was divided into a software interface and a hard interface. Objective evaluation method of software human factor analysis is used to evaluate the hard interface matching; The analytic hierarchy process is used to establish the evaluation index system for the software interface matching optimization, and the multi-level fuzzy comprehensive evaluation method is used to evaluate hard interface machine. This article takes Dongfeng Sokon (DFSK) C37 model automobile as an example. The evaluation method given in the paper is used to carry out relevant analysis and evaluation, and corresponding optimization suggestions are given, which have certain reference value for designers.

Keywords: analytic hierarchy process, fuzzy comprehension evaluation method, human-machine interface, matching optimization, software human factor analysis

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Authors: İsmail Kavdır, M. Burak Büyükcan, Ferhat Kurtulmuş

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Table olive is a valuable product especially in Mediterranean countries. It is usually consumed after some fermentation process. Defects happened naturally or as a result of an impact while olives are still fresh may become more distinct after processing period. Defected olives are not desired both in table olive and olive oil industries as it will affect the final product quality and reduce market prices considerably. Therefore it is critical to sort table olives before processing or even after processing according to their quality and surface defects. However, doing manual sorting has many drawbacks such as high expenses, subjectivity, tediousness and inconsistency. Quality criterions for green olives were accepted as color and free of mechanical defects, wrinkling, surface blemishes and rotting. In this study, it was aimed to classify fresh table olives using different classifiers and NIR spectroscopy readings and also to compare the classifiers. For this purpose, green (Ayvalik variety) olives were classified based on their surface feature properties such as defect-free, with bruised defect and with fly defect using FT-NIR spectroscopy and classification algorithms such as artificial neural networks, ident and cluster. Bruker multi-purpose analyzer (MPA) FT-NIR spectrometer (Bruker Optik, GmbH, Ettlingen Germany) was used for spectral measurements. The spectrometer was equipped with InGaAs detectors (TE-InGaAs internal for reflectance and RT-InGaAs external for transmittance) and a 20-watt high intensity tungsten–halogen NIR light source. Reflectance measurements were performed with a fiber optic probe (type IN 261) which covered the wavelengths between 780–2500 nm, while transmittance measurements were performed between 800 and 1725 nm. Thirty-two scans were acquired for each reflectance spectrum in about 15.32 s while 128 scans were obtained for transmittance in about 62 s. Resolution was 8 cm⁻¹ for both spectral measurement modes. Instrument control was done using OPUS software (Bruker Optik, GmbH, Ettlingen Germany). Classification applications were performed using three classifiers; Backpropagation Neural Networks, ident and cluster classification algorithms. For these classification applications, Neural Network tool box in Matlab, ident and cluster modules in OPUS software were used. Classifications were performed considering different scenarios; two quality conditions at once (good vs bruised, good vs fly defect) and three quality conditions at once (good, bruised and fly defect). Two spectrometer readings were used in classification applications; reflectance and transmittance. Classification results obtained using artificial neural networks algorithm in discriminating good olives from bruised olives, from olives with fly defect and from the olive group including both bruised and fly defected olives with success rates respectively changing between 97 and 99%, 61 and 94% and between 58.67 and 92%. On the other hand, classification results obtained for discriminating good olives from bruised ones and also for discriminating good olives from fly defected olives using the ident method ranged between 75-97.5% and 32.5-57.5%, respectfully; results obtained for the same classification applications using the cluster method ranged between 52.5-97.5% and between 22.5-57.5%.

Keywords: artificial neural networks, statistical classifiers, NIR spectroscopy, reflectance, transmittance

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Authors: Lavanya Srinivasan

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Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat, and case recorded using longwave infrared, short wave infrared, medium wave infrared, and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using YOLO, background subtraction, silhouettes extraction, and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the principal component analysis and recognised using different classifiers. The comparative results with the different classifier show that linear discriminant analysis outperforms other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, YOLO

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Authors: Suresh Reddi, Mathew Leslie, Vishnu S. Das

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Sustainable design is a prominent concept across all sectors of engineering and its importance is widely recognized within the Arabian Gulf region. Despite that sustainable or soft engineering options are not widely deployed in coastal engineering projects and a preference for utilizing ‘hard engineering’ solutions remain. The concept of soft engineering lies in “working together” with the nature to manage the coastline. This approach allows hard engineering options, such as breakwaters or sea walls, to be minimized or even eliminated altogether. Hard structures provide a firm barrier to wave energy or flooding, but in doing so they often have a significant impact on the natural processes of the coastline. This may affect the area locally or impact on neighboring zones. In addition, they often have a negative environmental impact and may create a sense of disconnect between the marine environment and local users. Soft engineering options, seek to protect the coastline by working in harmony with the natural process of sediment transport/budget. They often consider new habitat creation and creating usable spaces that will increase the sense of connection with nature. Often soft engineering options, where appropriately deployed can provide a low-maintenance, aesthetically valued, natural line of coastal protection. This paper deals with an overview of the following: The widely accepted soft engineering practices across the world; How this approach has been considered by Ramboll in some recent projects in Middle East and Asia; Challenges and barriers to use in using soft engineering options in the region; Way forward towards more widespread adoption.

Keywords: coastline, hard engineering, low maintenance, soft engineering options

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Authors: Hema Lattupalli

Abstract:

Introduction: The palate forms a partition between the oral cavity and nasal cavity. The palate is made up of two parts hard palate and soft palate. The Hard palate forms the anterior part of the palate, the soft palate forms a movable muscular fold covered by mucous membrane that is suspended from the posterior border of a hard palate. Aim and Objectives: Soft palate morphological variations have a great paucity in the literature. It’s also believed that the soft palate has no such important anatomical variations. There is a variable presentation of the soft palate morphology in the lateral cephalograms. The aim of this study is to identify the velar morphology. Materials and Methods: 100 normal subjects between the age group of 20 – 35 were taken for the study. Method: Lateral Cephalogram (radiologic study). Results: Different shapes of the soft palate were observed in the lateral cephalograms. The morphology of soft palate was classified into six types 1.Leaf like (50 cases) most common type, 2.Straight line (20 cases), 3.S shaped (4 cases) very rare, 4.Butt like (10 cases), 5. Rat tail (6 cases), 6. Hook shaped (10 cases). Conclusion: This classification helps us to understand the better diversity of the velar morphology in mid-sagittal plane. These findings help us to understand the etiology of OSAS.

Keywords: soft palate, cephalometric radiographs, morphology, cleft palate, obstructive sleep apnoea syndrome

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Authors: M. Habibi

Abstract:

The time-resolved studies of soft and hard X-ray were carried out over a wide range of argon pressures by employing an array of eight filtered photo PIN diodes and a scintillation detector, simultaneously. In 50% of the discharges, the soft X-ray is seen to be emitted in short multiple pulses corresponding to different compression, whereas it is a single pulse for hard X-rays corresponding to only the first strong compression. It should be stated that multiple compressions dominantly occur at low pressures and high pressures are mostly in the single compression regime. In 43% of the discharges, at all pressures except for optimum pressure, the first period is characterized by two or more sharp peaks.The X–ray signal intensity during the second and subsequent compressions is much smaller than the first compression.

Keywords: plasma focus device, SXR, HXR, Pin-diode, argon plasma

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Authors: Gülten Sadullahoğlu, Baki Altuncevahir

Abstract:

The scope of this study, to investigate the magnetic properties and microstructure of Nd₂Fe₁₄B₁ by alloying with Nd₃₃.₄Fe₆₂.₆Al₄, and heat treating it at different temperatures. The stoichiometric Nd₂Fe₁₄B hard magnetic alloy and Nd₃₃.₄Fe₆₂.₆Al₄ composition was produced by arc melting under argon atmosphere. The Nd₃₃.₄Fe₆₂.₆Al₄ alloy has added to the 2:14:1 hard magnetic alloy with 48% by weight, and melted again by arc melting. Then, it was heat treated at 600, 700 and 800˚C for 3h under vacuum. In AC magnetic susceptibility measurements, for the as-cast sample, the signals decreased sharply at 101 ˚C and 313 ˚C corresponding to the Curie temperatures of the two ferromagnetic phases in addition to Fe phase. For the sample annealed at 600 ˚C, two Curie points were observed at about 257˚C and at 313˚C. However, the phase corresponding to the Curie temperature of 101 ˚C was disappeared. According to the magnetization measurements, the saturation magnetization has the highest value of 99.8 emu/g for the sample annealed at 600 ˚C, and decreased to 57.66 and 28.6 emu/g for the samples annealed at 700˚ and 800 ˚C respectively. Heat treatment resulted in an evolution of the new phase that caused changes in magnetic properties of the alloys. In order to have a clear picture, the identification of these phases are being under the investigation by XRD and SEM–EDX analysis.

Keywords: NdFeB hard magnets, bulk magnetic materials, arc melting, Curie temperature, heat treatment

Procedia PDF Downloads 257

Authors: Sheena Christabel Pravin, M. Palanivelan

Abstract:

Speech disfluencies are common in spontaneous speech. The primary purpose of this study was to distinguish linguistic disfluencies from stuttering disfluencies in bilingual Tamil–English (TE) speaking children. The secondary purpose was to determine whether their disfluencies are mediated by native language dominance and/or on an early onset of developmental stuttering at childhood. A detailed study was carried out to identify the prosodic and acoustic features that uniquely represent the disfluent regions of speech. This paper focuses on statistical modeling of repetitions, prolongations, pauses and interjections in the speech corpus encompassing bilingual spontaneous utterances from school going children – English and Tamil. Two classifiers including Hidden Markov Models (HMM) and the Multilayer Perceptron (MLP), which is a class of feed-forward artificial neural network, were compared in the classification of disfluencies. The results of the classifiers document the patterns of disfluency in spontaneous speech samples of school-aged children to distinguish between Children Who Stutter (CWS) and Children with Language Impairment CLI). The ability of the models in classifying the disfluencies was measured in terms of F-measure, Recall, and Precision.

Keywords: bi-lingual, children who stutter, children with language impairment, hidden markov models, multi-layer perceptron, linguistic disfluencies, stuttering disfluencies

Procedia PDF Downloads 189