Search results for: auto fertility

Authors: Yuni Rochmawati, Luluk Il Mukarromah

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Android is a mobile operating system (OS) based on the linux kerrnel and currently developed by google. With a user interface based on direct manipulation, Android is designed primarily for touchscreen mobile deviced such as smartphone and tablet computer, with specialized user interface for television (Android TV), cars (Android Auto), and wrist watches (Android Wear). Now, almost all peoples using smartphone. Smartphone seems to be a must-have object, because smartphone has many benefits. In addition, of course smartphone have many benefits for education, like resume of lesson that form of e-book. However, this article is not about resume of lesson. This article is about practical based on android, exactly for physics. Therefore, we will explain our idea about physics’s practical based on android and for output, we wish many students will be like to studying physics and always remember about physics’s phenomenon by physics’s practical based on android.

Keywords: android, smartphone, physics, practical

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Authors: Boulis M. Ibrahim, Iordanis A. Kalaitzoglou

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A micro structural pricing model is proposed in which price components account for learning by incorporating changing expectations of the trading intensity and the risk level of incoming trades. An analysis of European carbon futures transactions finds expected trading intensity to increase the information component and decrease the liquidity component of price changes, but at different rates. Among the results, the expected persistence in trading intensity explains the majority of the auto correlations in the level and the conditional volatility of price changes, helps predict hourly patterns in the bid–ask spread and differentiates between the impact of buy versus sell and continuing versus reversing trades.

Keywords: CO2 emission allowances, market microstructure, duration, price discovery

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

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Authors: Jerome D. Donovan

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The pandemic has resulted in a dramatic re-consideration of the reliance on international student fees to support university models in Australia. A key resulting initiative for the Australian Federal Government has been shifting the way universities consider their research model, emphasising the importance of commercialising research. This study specifically examines this shift from the perspective of a university spin-off, examining how university support structures and incubation models have assisted in the translation of fundamental research into a high-growth university spin-off. A focused case study approach is adopted in this study, using an auto-ethnographic research method to document the experiences and insights drawn from being a co-founder in a university spin-off in a time where research commercialisation has emerged as a central focus in Australian universities.

Keywords: research commercialisation, spin-offs, university incubation, entrepreneurship

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Authors: Habibollah Mashhady, Behruz Lotfi, Mohammad Doosti, Moslem Fatollahi

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An exploration of the related literature reveals that all instruction methods aim at training autonomous learners. After the turn of second language pedagogy toward learner-oriented strategies, learners’ needs were more focused. Yet; the historical, social and political aspects of learning were still neglected. The present study investigates the notion of autonomous learning and explains its various facets from a pedagogical point of view. Furthermore; different elements, fields and scopes of autonomous learning will be explored. After exploring different aspects of autonomy, it is postulated that liberatory autonomy is highlighted since it not only covers social autonomy but also reveals learners’ capabilities and human potentials. It is also recommended that learners consider different elements of autonomy such as motivation, knowledge, confidence, and skills.

Keywords: critical pedagogy, social autonomy, academic learning, cultural notions

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Authors: Neera Singh, Devendra Kumar, Om Parkash

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We have synthesized nanocrystalline Fe-Ni alloy powders where Ni varies as 10, 30 and 50 mole% by a wet chemical route (sol-gel auto-combustion) followed by reduction in hydrogen atmosphere. The ratio of citrate to nitrate was maintained at 0.3 where citric acid has worked as a fuel during combustion. The reduction of combusted powders was done at 700°C/1h in hydrogen atmosphere using an atmosphere controlled quartz tube furnace. Phase and microstructure analysis has shown the formation of α-(Fe,Ni) and γ-(Fe,Ni) phases after reduction. An increase in Ni concentration resulted in more γ-(Fe,Ni) formation where complete γ-(Fe,Ni) formation was achieved at 50 mole% Ni concentration. Formation of particles below 50 nm size range was confirmed using Scherrer’s formula and Transmission Electron Microscope. The work is aimed at the effect of Ni concentration on phase, microstructure and magnetic properties of synthesized alloy powders.

Keywords: combustion, microstructure, nanocrystalline, reduction

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Authors: Weizhi Zhong, Xiaoyi Lu, Lei Xu

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In order to solve the problem of inaccurate synchronization for distributed multiple-input multiple-output (MIMO) system in multipath environment, a golay pair aided timing synchronization method is proposed in this paper. A new synchronous training sequence based on golay pair is designed. By utilizing the aperiodic auto-correlation complementary property of the new training sequence, the fine timing point is obtained at the receiver. Simulation results show that, compared with the tradition timing synchronization approaches, the proposed algorithm can provide high accuracy in synchronization, especially under multipath condition.

Keywords: distributed MIMO system, golay pair, multipath, synchronization

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Authors: Pravinchandra Patel

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Sustainable agriculture in sandy loam soil generally faces large constraints due to low water holding and nutrient retention capacity, and accelerated mineralization of soil organic matter. There is need to increase soil organic carbon in the soil for higher crop productivity and soil sustainability. Recently biochar is considered as sixth element and work as a catalyst for increasing crop yield, soil fertility, soil sustainability and mitigation of climate change. Biochar was generated at the Sansoli Farm of Anand Agricultural University, Gujarat, India by pyrolysis at temperatures (250-400°C) in absence of oxygen using slow chemical process (using two kilns) from corn stover (Zea mays, L), cluster bean stover (Cyamopsis tetragonoloba) and Prosopis julifera wood. There were 16 treatments; 4 organic sources (3 biochar; corn stover biochar (MS), cluster bean stover (CB) & Prosopis julifera wood (PJ) and one farmyard manure-FYM) with two rate of application (5 & 10 metric tons/ha), so there were eight treatments of organic sources. Eight organic sources was applied with the recommended dose of fertilizers (RDF) (80-40-0 kg/ha N-P-K) while remaining eight organic sources were kept without RDF. Application of corn stover biochar @ 10 metric tons/ha along with RDF (RDF+MS) increased dry matter (DM) yield, crude protein (CP) yield, chlorophyll content and plant height (at 30 and 60 days after sowing) than CB and PJ biochar and FYM. Nutrient uptake of P, K, Ca, Mg, S and Cu were significantly increased with the application of RDF + corn stover @ 10 metric tons/ha while uptake of N and Mn were significantly increased in RDF + corn stover @ 5 metric tons/ha. It was found that soil application of corn stover biochar @ 10 metric tons/ha along with the recommended dose of chemical fertilizers (RDF+MS ) exhibited the highest impact in obtaining significantly higher dry matter and crude protein yields and larger removal of nutrients from the soil and it also beneficial for built up nutrients in soil. It also showed significantly higher organic carbon content and cation exchange capacity in sandy loam soil. The lower dose of corn stover biochar @ 5 metric tons/ha (RDF+ MS) was also remained the second highest for increasing dry matter and crude protein yields of forage corn crop which ultimately resulted in larger removals of nutrients from the soil. This study highlights the importance of mixing of biochar along with recommended dose of fertilizers on its synergistic effect on sandy loam soil nutrient retention, organic carbon content and water holding capacity hence, the amendment value of biochar in sandy loam soil.

Keywords: biochar, corn yield, plant nutrient, fertility status

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Authors: Joël Passicousset, David Gilbert, Chloé Chervier-Legourd, Emmanuel Caron-Garant, Didier Labarre

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Living soil agriculture tries to reconciliate food production while improving soil health, soil biodiversity, soil fertility and more generally attenuating the inherent environmental drawbacks induced by modern agriculture. Using appropriate organic materials as soil amendments has a role to play in the aim of increasing the soil organic matter, improving soil fertility, sequestering carbon, and diminishing the dependence on both mineral fertilizer and pesticides. Insect farming consists in producing insects that can be used as a rich-in-protein and entomo-based food. Usually, detritivores are chosen, thus they can be fed with food wastes, which contributes to circular economy while producing low-carbon food. This process also produces frass, made of insect feces, exuvial material, and non-digested fibrous material, that have valuable fertilizer and biostimulation properties. But frass, used as a sole fertilizer on a crop may be not completely adequate for plants’ needs. This is why this project considers black soldier fly (termed BSF, one of the three main insect species grown commercially) frass as a complementary fertilizer, both in organic and in conventional contexts. Three kinds of experiments are made to understand the behaviour of fertilizer treatments based on frass incorporation. Lab-scale mineralization experiments suggest that BSF frass alone mineralizes more slowly than chicken manure alone (CM), but at a ratio of 90% CM-10% BSF frass, the mineralization rate of the mixture is higher than both frass and CM individually. For example, in the 7 days following the fertilization with same nitrogen amount introduced among treatments, around 80% of the nitrogen content supplied through 90% CM-10% BSF frass fertilization is present in the soil under mineral forms, compared to roughly 60% for commercial CM fertilization and 45% with BSF-frass. This suggests that BSF frass contains a more recalcitrant form of organic nitrogen than CM, but also that BSF frass has a highly active microbiota that can increase CM mineralization rate. Consequently, when progressive mineralization is needed, pure BSF-frass may be a consistent option from an agronomic aspect whereas, for specific crops that require spikes of readily available nitrogen sources (like cranberry), fast release 90CM-10BSF frass biofertilizer are more appropriate. Field experiments on cranberry suggests that, indeed, 90CM-10BSF frass is a potent candidate for organic cranberry production, as currently, organic growers rely solely on CM, whose mineralization kinetics are known to imperfectly match plant’s needs, which is known to be a major reason that sustains the current yield gap between conventional and organic cranberry sectors.

Keywords: soil mineralization, biofertilizer, BSF-frass, chicken manure, soil functions, nitrogen, soil microbiota

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Authors: Danladi Ali

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In this paper, we measured GSM signal strength in the Dnepropetrovsk city in order to predict path loss in study area using nonlinear autoregressive neural network prediction and we also, used neural network clustering to determine average GSM signal strength receive at the study area. The nonlinear auto-regressive neural network predicted that the GSM signal is attenuated with the mean square error (MSE) of 2.6748dB, this attenuation value is used to modify the COST 231 Hata and the Okumura-Hata models. The neural network clustering revealed that -75dB to -95dB is received more frequently. This means that the signal strength received at the study is mostly weak signal

Keywords: one-dimensional multilevel wavelets, path loss, GSM signal strength, propagation, urban environment and model

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Authors: Yahia Massinissa, Melakhessou Med Akram, Mezahdia Mehdi, Marref Salah Eddine

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Cytokines are natural proteins which act as true intercellular communication signals in immune and inflammatory responses. Reverse signaling pathways that activate cytokines help to regulate different functions at the target cell, causing its activation, its proliferation, the differentiation, its survival or death. It was shown that malfunctioning of the cytokine regulation, particularly over-expression, contributes to the onset and development of certain serious diseases such as chronic rheumatoid arthritis, Crohn's disease, psoriasis, lupus. The action mode of Kinoid® technology is based on the principle vaccine: The patient's immune system is activated so that it neutralizes itself and the factor responsible for the disease. When applied specifically to autoimmune diseases, therapeutic vaccination allows the body to neutralize cytokines (proteins) overproduced through a highly targeted stimulation of the immune system.

Keywords: cytokines, Kinoid tech, auto-immune diseases, vaccination

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Authors: Ssu-Han Chen, Der-Baau Perng

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Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded, defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: molding surface, machine vision, statistical texture, discrete Fourier transformation

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Authors: Meriem Mossaddek, El Mehdi Laadissi, El Mehdi Loualid, Chouaib Ennawaoui, Sohaib Bouzaid, Abdelowahed Hajjaji

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An electrochemical system is a subset of mechatronic systems that includes a wide variety of batteries and nickel-cadmium, lead-acid batteries, and lithium-ion. Those structures have several non-linear behaviors and uncertainties in their running range. This paper studies an effective technique for modeling Lithium-Ion (Li-Ion) batteries using a Nonlinear Auto-Regressive model with exogenous input (NARX). The Artificial Neural Network (ANN) is trained to employ the data collected from the battery testing process. The proposed model is implemented on a Li-Ion battery cell. Simulation of this model in MATLAB shows good accuracy of the proposed model.

Keywords: lithium-ion battery, neural network, energy storage, battery model, nonlinear models

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Authors: Ahmed Abbas

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Land degradation in the Lower Cheliff region leads to loss of their fertility, physical and chemical properties by secondary salinization and film forming surface or surface crust. The main factor related to runoff and soil erosion is their susceptibility to crusting caused by the impact of raindrops, which causes the reduction of the filterability of the soil. The present study aims to investigate the hydrodynamic behavior of five types of soil taken from the plain of low Cheliff under simulated rainfall by using two intensities, one moderate, and others correspond to heavy rains at low kinetic energies. Experimental results demonstrate the influence of chemical and mechanical physical properties of soils on their hydrodynamic behavior and the influence of heavy rain on the modality of the reduction in the filterability and the amount of transported sediment.

Keywords: erosion, hydrodynamic behavior, rain simulation, soil

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Authors: Ghaleb Y. Abbasi, Israa Abu Rumman

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This paper modeled sales history archived from 2012 to 2015 bulked in monthly bins for five products for a medical supply company in Jordan. The sales forecasts and extracted consistent patterns in the sales demand history from the Enterprise Resource Planning (ERP) system were used to predict future forecasting and generate sales demand forecasting using time series analysis statistical technique called Auto Regressive Integrated Moving Average (ARIMA). This was used to model and estimate realistic sales demand patterns and predict future forecasting to decide the best models for five products. Analysis revealed that the current replenishment system indicated inventory overstocking.

Keywords: ARIMA models, sales demand forecasting, time series, R code

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Authors: Ng Liang Shen, Hau Yuan Wen

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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

Procedia PDF Downloads 347

Authors: Seydou Drabo

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This paper examines how traditional contraceptives and abortion practices challenges the use of modern contraceptives in Burkina Faso. It demonstrates how fears and ‘superstitions’ interact with knowledge about modern contraceptives methods to determine use in a context where other way of controlling fertility (traditional contraceptives, abortion) are available to women in the public, private and traditional health sectors. Furthermore, these issues come at the time when Burkina Faso is among countries with a high fertility rate which (6.0 in 2010) and a very low used of contraceptives as only 16% of married women of childbearing age were using a contraceptive method in 2010. The country also has a young population since 33 % of the population is between 10-24 years old and this number is expected to increase by 2050, generating fears that a growing population of youth will put excessive pressure on available resources, including access to education, health services, and employment. Despite over two decades of dedicated policy attention, 24% of women of reproductive age (15-49) was estimated to have an unmet need for contraception in 2010. This paper draws on ethnographic fieldwork conducted since march 2016 (The research is still in progress) in Burkina Faso. Data were collected from 25 women (users and non-users of modern contraceptives and /or traditional contraceptives, post abortion care patients), 4 street drugs vendors and 3 traditional healers through formal and informal interviews, as well as direct observation. The findings show that a variety of contraceptives methods and abortion drugs or methods, both traditional and modern circulate and are available to women. Traditional contraceptives called African contraceptives by some of our participants refer to several birth control method including plants decoction, magical ring, waist necklace, a ritual done with a mixture of lay coming from termite mound and menses. Abortion is a practice that is done in secret through the use of abortion drugs or through intra uterine manoeuvres. Modern contraceptives include Oral contraceptive, implants, injectable. Stereotypes about modern contraceptives, having regular menstrual cycles and adopt of natural birth control methods, bad experience with modern contraceptives methods, the side effect of modern contraceptives, irregularity of sexual activities and the availability of emergency contraceptives are among factors that limit their use among women. In addition, a negative perception is built around modern contraceptives seen as the drug of ‘white people’. In general, the information on these drugs circulates in women’s social network (first line of information on contraceptive). Some women prefer using what they call African contraceptives or inducing an abortion over modern contraceptives because of their side effect. Furthermore, the findings show that women practices and attitudes in controlling birth varies throughout different phases of their lives. Beyond global discourses and technical solution, the issue of Family planning is all about social practices.

Keywords: abortion, Burkina Faso, contraception, culture, women

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

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Authors: P. Azimi, B. Behtoiy, A. A. Najafi, H. R. Charmchi

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According to the previous studies, one of the most famous techniques which affect the efficiency of a production line is the assembly line balancing (ALB) technique. This paper examines the balancing effect of a whole production line of a real auto glass manufacturer in three steps. In the first step, processing time of each activity in the workstations is generated according to a practical approach. In the second step, the whole production process is simulated and the bottleneck stations have been identified, and finally in the third step, several improvement scenarios are generated to optimize the system throughput, and the best one is proposed. The main contribution of the current research is the proposed framework which combines two famous approaches including Assembly Line Balancing and Optimization via Simulation technique (OvS). The results show that the proposed framework could be applied in practical environments, easily.

Keywords: assembly line balancing problem, optimization via simulation, production planning

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Authors: Ajayi Olusola Olajide, Alonge Olaide Moses

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Predicting the outcome of soccer matches poses an interesting challenge for which it is realistically impossible to successfully do so for every match. Despite this, there are lots of resources that are being expended on the correct prediction of soccer matches weekly, and all over the world. Soccer Match Result Prediction System Model (SMRPSM) is a system that is proposed whereby the results of matches between two soccer teams are auto-generated, with the added excitement of giving users a chance to test their predictive abilities. Soccer teams from different league football are loaded by the application, with each team’s corresponding manager and other information like team location, team logo and nickname. The user is also allowed to interact with the system by selecting the match to be predicted and viewing of the results of completed matches after registering/logging in.

Keywords: predicting, soccer match, outcome, soccer, matches, result prediction, system, model

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Authors: Noury Bakrim

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Translatability is one of Walter Benjamin’s most influential notions, it is somehow representing the philosophy of language and history of what we might call and what we indeed coined as ‘the other German Speaking Modernity’ which could be shaped as a parallel thought form to the Marxian-Hegelian philosophy of history, the one represented by the school of Frankfurt. On the other hand, we should consider the influence of the plural German speaking identity and the Nietzschian and Goethean heritage, this last being focused on a positive will of power: the humanised human being. Having in perspective the benjaminian notion of translatability (Übersetzbarkeit), to be defined as an internal permanent hermeneutical possibility as well as a phenomenological potential of a translation relation, we are in fact touching this very double limit of both historical and linguistic reason. By life component, we mean the changing conditions of genetic and neurolinguistic post-partum functions, to be grasped as an individuation beyond the historical determinism and teleology of an event. It is, so to speak, the retrospective/introspective canettian auto-fiction, the benjaminian crystallization of the language experience in the now-time of writing/transmission. Furthermore, it raises various questioning points when it comes to translatability, they are basically related to psycholinguistic separate poles, the fatherly ladino Spanish and the motherly Vienna German, but relating more in particular to the permanent ontological quest of a world loss/belonging. Another level of this quest would be the status of Veza Canetti-Taubner Calderón, german speaking Author, Canetti’s ‘literary wife’, writer’s love, his inverted logos, protective and yet controversial ‘official private life partner’, the permanence of the jewish experience in the exiled german language. It sheds light on a traumatic relation of an inadequate/possible language facing the reconstruction of an oral life, the unconscious split of the signifier and above all on the frustrating status of writing in Canetti’s work : Using a suffering/suffered written German to save his remembered acquisition of his tongue/mother tongue by saving the vanishing spoken multilingual experience. While Canetti’s only novel ‘Die Blendung’ designates that fictional referential dynamics focusing on the nazi worldless horizon: the figure of Kien is an onomastic signifier, the anti-Canetti figure, the misunderstood legacy of Kant, the system without thought. Our postulate would be the double translatability of his auto-fiction inventing the bios oral signifier basing on the new praxemes created by Canetti’s german as observed in the English, French translations of his memory corpus. We aim at conceptualizing life component and translatability as two major features of a german speaking modernity.

Keywords: translatability, language biography, presentification, bioeme, life Order

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Authors: S. Jakšić, B. Žmuk

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The paper investigates the key factors of export dynamics for a set of Central and Southeast European (CSEE) countries in the context of current economic and financial crisis. In order to model the export dynamics a Global Vector Auto Regressive (GVAR) model is defined. As opposed to models which model each country separately, the GVAR combines all country models in a global model which enables obtaining important information on spill-over effects in the context of globalization and rising international linkages. The results of the study indicate that for most of the CSEE countries, exports are mainly driven by domestic shocks, both in the short run and in the long run. This study is the first application of the GVAR model to studying the export dynamics in the CSEE countries and therefore the results of the study present an important empirical contribution.

Keywords: export, GFEVD, global VAR, international trade, weak exogeneity

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Authors: Lovepreet Kaur Dhugga, Dwijendra P. Singh

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Calcium copper titanate (CCTO) was synthesized via the sol-gel auto-combustion method. The precursor was calcined at 800°C and 1000°C for 6 hours providing brown-coloured powders, which were pelletized and sintered at 1000°C for 12 hrs to determine their dielectric behaviour in the frequency range (100Hz-10MHz) at room temperature. The dielectric constant(εr) and loss tangent (tanδ) has been found to be ~ 6153 and 0.5 for 800°C and ~ 5504 and 0.2 for 1000°C respectively, at frequency 1kHz. Microstructure study revealed maximum grain growth occurs in sample calcined at 800°C, responsible for its high dielectric constant. Phase identification of CaCu₃Ti₄O₁₂ has been carried out through X-ray diffraction. It can be used in various electronic applications as it shows large εᵣ and low tanδ values over a wide frequency spectrum, including energy storage devices, microwave shielding, and sensors.

Keywords: calcium copper titanate, dielectric behaviour, microstructure, X-ray diffraction

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Authors: Muhammad Farid, Jen Der Day

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The purpose of this study is to explore the construct of service innovation model for Small and medium-sized enterprises (SMEs) in automotive service industries. A case study of repair shop of the motorcycle at Makassar city illustrates measure innovation implementation, the degree of innovation, and identifies the type of innovation by the service innovation model for SMEs. In this paper, we interview 10 managers of SMEs and analyze their answers. We find that innovation implementation has been slowly; only producing new service innovation 0.62 unit average per year. Incremental innovation is the present option for SMEs, because they choose safer roads to improve service continuously. If want to create radical innovation, they still consider the aspect of cost, system, and readiness of human resources.

Keywords: service innovation, incremental innovation, SMEs, automotive service industries

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Authors: Oliver Takawira, Thembi Hope

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This study will analyse the relationship between Bitcoin price movements and the Johannesburg stock exchange (JSE). The aim is to determine whether Bitcoin price movements affect the stock market performance. As crypto currencies continue to gain prominence as a safe asset during periods of economic distress, this raises the question of whether Bitcoin’s prosperity could affect investment in the stock market. To identify the existence of a short run and long run linear relationship, the study will apply the Autoregressive Distributed Lag Model (ARDL) bounds test and a Vector Error Correction Model (VECM) after testing the data for unit roots and cointegration using the Augmented Dicker Fuller (ADF) and Phillips-Perron (PP). The Non-Linear Auto Regressive Distributed Lag (NARDL) will then be used to check if there is a non-linear relationship between bitcoin prices and stock market prices.

Keywords: bitcoin, stock market, interest rates, ARDL

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Authors: Arjun, A. D. Singh

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Concrete the basic material using in construction across the global these days. The purpose of this special concrete is to provide extra strength and stability for irregular structure where the center of gravity is disturbed. In this paper an effort has been made to use different type of material aggregates has been discussed. We named As "STAR Aggregates" which has qualities to resist Shear, tension and compression forces. We have been divided into coarse aggregates and fine aggregates according to their sizes. Star Aggregates has interlocking behavior and cutting edge technology. Star aggregates had been draft and deign in Auto CAD and then analysis in ANSYS software. by using special aggregates we deign concrete grade of M40 for mega structures and irregular structure. This special concrete with STAR aggregates use in construction for irregular structure like Bridges, Skyscrapers or in deigned buildings.

Keywords: star aggregates, high performance concrete, material aggregates, interlocking

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Authors: N. K. Gupta, R. C. Bhattacharjee

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In the aftermath of the tsunami in 2004 and terrible humanitarian disaster affecting thousands of kilometers of coastal south, the immediate priority is to begin the process of reconstruction of livelihoods including basic services. It is likely that many coastal wetlands would have been affected by the large inflow of salt-water and littoral sediments during the tsunami, with longer-term effects including changes in their hydrogeology caused by changes to coastlines and damage to sea-defenses. The reconstruction process is likely to provide opportunities to better integrate environmental protection and management with economic development in the region, including the opportunity to conserve and restore coastal habitats. Presented herein is a study pertaining to salinity problems encountered in coastal south during tsunami in 2004 and the consequent loss of fertility of agricultural land including remedial measures to revitalize economic growth in the region.

Keywords: tsunami, salinity, costal area, reconstruction

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Authors: Zainab S. Mahmood, Aisha H. Hashim, Wan Haslina Hassan, Farhat Anwar

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The wide use of the internet-based applications bring many challenges to the researchers to guarantee the continuity of the connections needed by the mobile hosts and provide reliable Internet access for them. One of proposed solutions by Internet Engineering Task Force (IETF) is to connect the local, multi-hop, and infrastructure-less Mobile Ad hoc Network (MANET) with Internet structure. This connection is done through multi-interface devices known as Internet Gateways. Many issues are related to this connection like gateway discovery, hand off, address auto-configuration and selecting the optimum gateway when multiple gateways exist. Many studies were done proposing gateway selection schemes with a single selection criterion or weighted multiple criteria. In this research, a review of some of these schemes is done showing the differences, the features, the challenges and the drawbacks of each of them.

Keywords: Internet Gateway, MANET, mobility, selection criteria

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Authors: Shan-Jen Cheng, Te-Jen Chang, Kuang-Hsiung Tan, Shou-Ling Kuo

Abstract:

Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accuracy of NNARX model are tested by one step ahead relating output voltage to input current from measured experimental of PEMFC. The results show that the obtained nonlinear NNARX model can efficiently approximate the dynamic mode of the PEMFC and model output and system measured output consistently.

Keywords: PEMFC, neural network, nonlinear modeling, NNARX

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