Search results for: LWE instances selection strategy

Authors: Huie-Wen Lin

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This study integrated various teaching factors -based on the idea of a flipped classroom- in a financial management course. The study’s aim was to establish an effective teaching implementation strategy and evaluation mechanism with respect to learning outcomes, which can serve as a reference for the future modification of teaching methods. This study implemented a teaching method in five stages and estimated the learning efficiencies of 22 students (in the teaching scenario and over two semesters). Subsequently, data envelopment analysis (DEA) was used to compare, for each student, between the learning efficiencies before and after participation in the flipped classroom -in the first and second semesters, respectively- to identify the crucial external factors influencing learning efficiency. According to the results, the average overall student learning efficiency increased from 0.901 in the first semester to 0.967 in the second semester, which demonstrate that the flipped classroom approach can improve teaching effectiveness and learning outcomes. The results also revealed a difference in learning efficiency between male and female students.

Keywords: data envelopment analysis, flipped classroom, learning outcome, teaching and learning

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Authors: Sankara Rao Gollu, Ramakant Sharma, G. Srinivas, Souvik Kundu, Dipti Gupta

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In recent years, bulk heterojunction organic solar cells (BHJ OSCs) based on polymer–fullerene attracted a large research attention due to their numerous advantages such as light weight, easy processability, eco-friendly, low-cost, and capability for large area roll-to-roll manufacturing. BHJ OSCs usually suffer from insufficient light absorption due to restriction on keeping thin ( < 150 nm) photoactive layer because of small exciton diffusion length ( ~ 10 nm) and low charge carrier mobilities. It is thus highly desirable that light absorption as well as charge transport properties are enhanced by alternative methods so as to improve the device efficiency. In this work, therefore, we have focused on the strategy of incorporating metallic nanostructures in the active layer or charge transport layer to enhance the absorption and improve the charge transport.

Keywords: organic solar cell, efficiency, bulk heterojunction, polymer-fullerene

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Authors: Nursel Koyuncu, Nihal Ata Tutkun

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Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

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Authors: Samanta Kietytė

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The object of this study is the verbal derivatives stemming from the Lithuanian prefix per-. The prefix under examination can be classified as prepositional, having descended from the preposition per, thereby sharing the same prototypical meaning – denoting movement OVER. These frequently co-occur within sentences (1). The aim of this paper is to conduct a semantic analysis of the prefix per- and to propose a possible radial network of its meanings. In essence, the aim is to identify the interrelationships existing between its meanings. 1) Jis peršoko per tvorą/ 3SG.NOM.M jump.PST.3 over fence.ACC.SG. /ʻHe jumped over the fenceʼ. The foundation of this work lies in the methodological and theoretical framework of cognitive linguistics. The prototypical meaning of prefixes consistently embodies spatial dimensions that can be described through image schemas. This entails the identification of the trajectory, the landmark, and the relation between them in the situation described by the prefixed verb. The meanings of linguistic units are not perceived as arbitrary, but rather, they are interconnected through semantic motivation. According to this perspective, a singular meaning within linguistic units is considered as prototypical, while additional meanings are descended (not necessarily directly) from it. For example, one of the per- meanings TRANSFER (2) is derived from the prototypical meaning OVER. 2) Prašau persiųsti vadovo laišką man./ Ask.PRS.1 forward.INF manager.GEN.SG email.ACC.SG 1.SG.DAT/ ʻPlease forward the manager‘s email to meʼ. Certain semantic relations are explained by the conceptual metaphor and metonymy theory. For instances, when prefixed verb has a meaning WIN (3) it is related to the prototypical meaning. In this case, the prefixed verb describes situations of winning in various ways. In the prototypical meaning, the trajector moves higher than the landmark, and winning is metaphorically perceived as being higher. 3) Sūnus peraugo tėvą./ Son.NOM.SG outgrow.PST.3 father.ACC.SG/ ʻThe son has outgrown the fatherʼ. The data utilized for this study was collected from the 2014 grammatically annotated text "Lithuanian Web (LithuanianWaC v2)", consisting of 63,645,700 words. Given that the corpus is grammatically lemmatized, the list of the 793 items was obtained using the wordlist function and specifying that verbs starting with per were searched. The list included not only prefixed verbs but also other verbs whose roots have the same letter sequences as prefixes. Also, words with misspellings, without diacritical marks, and words listed for lemmatization errors were rejected, and a total of 475 derivatives were left for further analysis. The semantic analysis revealed that there are 12 distinct meanings of the prefix per-. The spatial meanings were extracted by determining what a trajector is, what a landmark is, and what the relation between them is. The connection between non-spatial meanings and spatial ones occurs through semantic motivation established by identifying elements that correspond to the trajector and landmark. The analysis reveals that there are no strict boundaries among these meanings, instead showing a continuum that encompasses a central core and a peripheral association with their internal structure, i.e., some derivatives are more prototypical of a particular meaning than others.

Keywords: word-formation, cognitive semantics, metaphor, radial networks, prototype theory, prefix

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Authors: Indujeeva Keerthila Peiris

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The secular view of mindfulness has some connotation to the original meaning of mindfulness mentioned in the Theravada Buddhist texts (Pāli Canon), but there is a substantial difference in the meaning of the two. Secular Mindfulness Based Interventions (MBI) focus on stilling the mind, which may provide short-term benefits and help individuals to deal with physical pain, grief, and distress. However, as with many popular educational innovations, the foundational values of mindfulness strategies have been distorted and subverted in a number of instances in which ‘McMindfulness’ programmes have been implemented with a view to reducing mindfulness mediation as a self-help technique that is easily misappropriated for the exclusive pursuit of corporate objectives, employee pacification, and commercial profit. The intention of this paper is not to critique the misappropriations of mindfulness. Instead, to go back to the root source and bring insights from the Buddhist Pāli Canon and its associated teachings on mindfulness in its own terms. In the Buddha’s discourses, as preserved in the Pāli Canon, there is nothing more significant than the understanding and practice of ‘Satipatthãna’. The Satipatthāna Sutta , the ‘Discourse on the Establishment of Mindfulness,’ opens with a proclamation highlighting both the purpose of this training and its methodology. The right practice of mindfulness is the gateway to understanding the Buddha’s teaching. However, although this concept is widely discussed among the Dhamma practitioners, it is the least understood one of them all. The purpose of this paper is to understand deeper meaning of mindfulness as it was originally intended by the Teacher. The natural state of mind is that it wanders. It wanders into the past, the present, and the future. One’s ability to hold attention to a mind object (emotion, thought, feeling, sensation, sense impression) called ‘concentration’. The intentional concentration process does not lead to wisdom. However, the development of wisdom starts when the mind is calm, concentrated, and unified. The practice of insight contemplation aims at gaining a direct understanding of the real nature of phenomena. According to the Buddha’s teaching, there are three basic facts of all existence: 1) impermanence (anicca in Pāli) ; 2) fabrication (also commonly known as suffering, unsatisfactoriness, sankhara or dukka in Pāli); 3) not-self (insubstantiality or impersonality, annatta in Pāli ). The entire Buddhist doctrine is based on these three facts. The problem is our ignorance covers reality. It is not that a person sees the emptiness of them or that we try to see the emptiness of our experience by conceptually thinking that they are empty. It is an experiential outcome that happens when the cause-and- effect overrides the self-view (sakkaya dhitti), and ignorance is known as ignorance and eradicated once and for all. Therefore, the right view (samma dhitti) is the starting point of the path, not ethical conduct (sila) or samadhi (jhana). In order to develop the right view, we need to first listen to the correct Dhamma and possess Yoniso manasikara (right comprehension) to know the five aggregates as five aggregates.

Keywords: mindfulness, spirituality, buddhism, pali canon

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Authors: Ramez F. Saad, Ahmad Kobaissi, Bernard Amiaud, Julien Ruelle, Emile Benizri

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Agromining is a new technology that establishes agricultural systems on ultramafic soils in order to produce valuable metal compounds such as nickel (Ni), with the final aim of restoring a soil's agricultural functions. But ultramafic soils are characterized by low fertility levels and this can limit yields of hyperaccumulators and metal phytoextraction. The objectives of the present work were to test if the association of a hyperaccumulating plant (Alyssum murale) and a Fabaceae (Vicia sativa var. Prontivesa) could induce changes in physicochemical characteristics of a serpentine soil and in root architecture of a hyperaccumulating plant then lead to efficient agromining practices through soil quality improvement. Based on standard agricultural systems, consisting in the association of legumes and another crop such as wheat or rape, a three-month rhizobox experiment was carried out to study the effect of the co-cropping (Co) or rotation (Ro) of a hyperaccumulating plant (Alyssum murale) with a legume (Vicia sativa) and incorporating legume biomass to soil, in comparison with mineral fertilization (FMo), on the structure and physicochemical properties of an ultramafic soil and on root architecture. All parameters measured (biomass, C and N contents, and taken-up Ni) on Alyssum murale conducted in co-cropping system showed the highest values followed by the mineral fertilization and rotation (Co > FMo > Ro), except for root nickel yield for which rotation was better than the mineral fertilization (Ro > FMo). The rhizosphere soil of Alyssum murale in co-cropping had larger soil particles size and better aggregates stability than other treatments. Using geostatistics, co-cropped Alyssum murale showed a greater root surface area spatial distribution. Moreover, co-cropping and rotation-induced lower soil DTPA-extractable nickel concentrations than other treatments, but higher pH values. Alyssum murale co-cropped with a legume showed a higher biomass production, improved soil physical characteristics and enhanced nickel phytoextraction. This study showed that the introduction of a legume into Ni agromining systems could improve yields of dry biomass of the hyperaccumulating plant used and consequently, the yields of Ni. Our strategy can decrease the need to apply fertilizers and thus minimizes the risk of nitrogen leaching and underground water pollution. Co-cropping of Alyssum murale with the legume showed a clear tendency to increase nickel phytoextraction and plant biomass in comparison to rotation treatment and fertilized mono-culture. In addition, co-cropping improved soil physical characteristics and soil structure through larger and more stabilized aggregates. It is, therefore, reasonable to conclude that the use of legumes in Ni-agromining systems could be a good strategy to reduce chemical inputs and to restore soil agricultural functions. Improving the agromining system by the replacement of inorganic fertilizers could simultaneously be a safe way of rehabilitating degraded soils and a method to restore soil quality and functions leading to the recovery of ecosystem services.

Keywords: plant association, legumes, hyperaccumulating plants, ultramafic soil physicochemical properties

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Mohammad Muhebbullah Ibne Hoque, Zheng Jun, Wang Guoying

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Salinity stress is one of the most important abiotic factors contributing to crop growth and yield loss. Exploring the genetic basis is necessary to develop maize varieties with salinity tolerance. In order to discover the inherent basis for salinity tolerance traits in maize, 121 polymorphic SSR markers were used to analyze 163 F2 individuals derived from a single cross of inbred line B73 (a salt susceptible inbred line) and CZ-7 (a salt tolerant inbred line). A linkage map was constructed and the map covered 1195.2 cM of maize genome with an average distance of 9.88 cM between marker loci. Ten salt tolerance traits at seedling stage were evaluated for QTL analysis in maize seedlings. A total of 41 QTLs associated with seedling shoot and root traits were detected, with 16 and 25 QTLs under non-salinity and salinity condition, respectively. And only 4 major stable QTLs were detected in two environments. The detected QTLs were distributed on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, and chromosome 10. Phenotypic variability for the identified QTLs for all the traits was in the range from 6.27 to 21.97%. Fourteen QTLs with more than 10% contributions were observed. Our results and the markers associated with the major QTL detected in this study have the potential application for genetic improvement of salt tolerance in maize through marker-assisted selection.

Keywords: salt tolerance, seedling stage, root shoot traits, quantitative trait loci, simple sequence repeat, maize

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Authors: Hussain Ali Bekhet, Nor Hamisham Harun

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The main objective of this paper is to give a comprehensive review of non-renewable energy and renewable energy utilization in Malaysia, including hydropower, solar photovoltaic, biomass and biogas technologies. Malaysia mainly depends on non-renewable energy (natural gas, coal and crude oil) for electricity generation. Therefore, this paper provides a comprehensive review of the energy sector and discusses diversification of electricity generation as a strategy for providing sustainable energy in Malaysia. Energy policies and strategies to protect the non-renewable energy utilization also are highlighted, focusing in the different sources of energy available for high and sustained economic growth. Emphasis is also placed on a discussion of the role of renewable energy as an alternative source for the increase of electricity supply security. It is now evident that to achieve sustainable development through renewable energy, energy policies and strategies have to be well designed and supported by the government, industries (firms), and individual or community participation. The hope is to create a positive impact on sustainable development through renewable sources for current and future generations.

Keywords: Malaysia, non-renewable energy, renewable energy, sustainable energy

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: artificial immune system, breast cancer diagnosis, Euclidean function, Gaussian function

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Authors: Peter Dzakah Fanam, Hong O. Nguyen, Stephen Cahoon

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The objective of this study is to explore the buying behavior of the freight forwarders and to evaluate how their buying decision affects the ocean container carriers’ market share. This study analysed the buying decisions of the freight forwarders and validated the process of stages that the freight forwarders’ pass through before choosing an ocean container carrier. Factor analysis was applied to data collected from 105 freight forwarding companies to unveil the influential factors the freight forwarders’ consider important when selecting an ocean container carrier. This study did not only analysed the buying behaviour of the freight forwarders but also unveiled the influential factors affecting the competitiveness of the ocean container carriers in their market share maximisation. Furthermore, the study have made a methodological contribution that helps in better understanding of the critical factors influencing the selection of the ocean container carriers from the freight forwarders’ perspective. The implications of the freight forwarders’ buying behaviour is important to the ocean container carriers because it have severe effect on the market share of the ocean container carriers and the percentage of customers they control within the liner shipping sector. The findings of this study will help the ocean container carriers to formulate relevant marketing strategies in attracting the freight forwarders in purchasing the liner shipping service.

Keywords: ocean carrier, freight forwarder, buying behaviour, influential factors

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Authors: Anam Bhatti, Sumbal Arif, Mariam Mehar, Sohail Younas

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CSR has become one of the imperative implements in satisfying customers. The impartial of this research is to calculate CSR, relationship marketing, and customer satisfaction. In Pakistan, there is not enough research work on the effect of CSR and relationship marketing on relationship maintainer and customer loyalty. To find out deductive approach and survey method is used as research approach and research strategy respectively. This research design is descriptive and quantitative study. For data, collection questionnaire method with semantic differential scale and seven point scales are adopted. Data has been collected by adopting the non-probability convenience technique as sampling technique and the sample size is 400. For factor confirmatory factor analysis, structure equation modeling and medication analysis, regression analysis Amos software were used. Strong empirical evidence supports that the customer’s perception of CSR performance is highly influenced by the values.

Keywords: CSR, Relationship marketing, Relationship maintainer, Customer loyalty, Customer satisfaction

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Authors: Andrea Macruz

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This paper explores computation as a process for design by examining how computers can become more than an operative strategy in a designer's toolkit. It documents this, building upon concepts of neuroscience and Antonio Damasio's Homeostasis Theory, which is the control of bodily states through feedback intended to keep conditions favorable for life. To do this, it follows a methodology through algorithmic drawing and discusses the outcomes of three multi-sensory design installations, which culminated from a course in an academic setting. It explains both the studio process that took place to create the installations and the computational process that was developed, related to the fields of algorithmic design and tangible computing. It discusses how designers can use computational range to achieve homeostasis related to sensory data in a multi-sensory installation. The outcomes show clearly how people and computers interact with different sensory modalities and affordances. They propose using computers as meta-physical stabilizers rather than tools.

Keywords: algorithmic drawing, Antonio Damasio, emotion, homeostasis, multi-sensory installation, neuroscience

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Mohamed Amine El Hameur, Lyes Tarabet, Mahfoudh Cerdoun, Boubkr Zebiri, Giovanni Ferrara

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Due to the drastic environmental and energy regulations regarding the reduction of exhaust emissions and fuel consumption, added to the increasing demand for powerful performance, several automotive manufacturers are constantly obliged to redesign their existing products and/or develop novel powertrain techniques to respond to the aforementioned restrictions. In this aspect, an implemented approach is proposed in the present work to boost a 1.5 L, three-cylinder Diesel engine with a new turbocharger, based on 1D preliminary design codes, 3D design, and numerical assessment of a suitable radial turbine followed by an accurate selection procedure of an adequate centrifugal compressor. Furthermore, to investigate the effect of the turbine’s rotor position on the simulation convergence, stability, and calculation time; two combinations (rotor blade- volute) have been assessed. Consequently, significant results are obtained when comparing the original turbocharged engine and the new one at the engine’s full load and rated speed (@4500rpm) conditions. A maximum improvement in terms of brake-specific fuel consumption, thermal efficiency, total-to-static turbine efficiency, and total-to-total compressor efficiency equal 6.5% (corresponding to a decrease of 2.3 litre/hr in fuel consumption), 7%, 10.9%, and 19.9%, respectively.

Keywords: CFD investigation, engine boosting, turbine design, turbocharger, rotor blade positioning

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Authors: Shilpesh R. Rajpurohit, Harshit K. Dave

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Fused deposition modeling (FDM) gains popularity in recent times, due to its capability to create prototype as well as functional end use product directly from CAD file. Parts fabricated using FDM process have mechanical properties comparable with those of injection-molded parts. However, performance of the FDM part is severally affected by the poor mechanical properties of the part due to nature of layered structure of printed part. Mechanical properties of the part can be improved by proper selection of process variables. In the present study, a comparative study between unidirectional and bidirectional raster angle has been carried out at a combination of different layer height and raster width. Unidirectional raster angle varied at five different levels, and bidirectional raster angle has been varied at three different levels. Fabrication of tensile specimen and tensile testing of specimen has been conducted according to ASTM D638 standard. From the results, it can be observed that higher tensile strength has been obtained at 0° raster angle followed by 45°/45° raster angle, while lower tensile strength has been obtained at 90° raster angle. Analysis of fractured surface revealed that failure takes place along with raster deposition direction for unidirectional and zigzag failure can be observed for bidirectional raster angle.

Keywords: additive manufacturing, fused deposition modeling, unidirectional, bidirectional, raster angle, tensile strength

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Authors: Jinfeng Zhang, Chun-Sing Lee

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Pure nanodrugs (PNDs) – nanoparticles consisting entirely of drug molecules, have been considered as promising candidates for the next-generation nanodrugs. However, the traditional preparation method via reprecipitation faces critical challenges including low production rates, relatively large particle sizes and batch-to-batch variations. Here, for the first time, we successfully developed a novel, versatile and controllable strategy for preparing PNDs via an anodized aluminium oxide (AAO) template-assisted method. With this approach, we prepared PNDs of an anti-cancer drug (VM-26) with precisely controlled sizes reaching the sub-20 nm range. This template-assisted approach has much higher feasibility for mass production comparing to the conventional reprecipitation method and is beneficial for future clinical translation. The present method is further demonstrated to be easily applicable for a wide range of hydrophobic biomolecules without the need of custom molecular modifications and can be extended for preparing all-in-one nanostructures with different functional agents.

Keywords: drug delivery, pure nanodrugs, size control, template

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Authors: Ahmad Rouhani, Masood Jabbari, Sima Honarmand

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This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technics and economics. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: hybrid energy system, optimum sizing, power management, TLBO

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Authors: Hossein Alimohammadi, Mohsen Amirmojahedi, Mehrdad Rowhani

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Soil properties are used by geotechnical engineers to evaluate and analyze site conditions for designing purposes. Although basic soil classification tests are easy to perform and provide useful information to determine the properties of soils, it may take time to get the result and add some costs to the projects. Standard Penetration Test (SPT) provides an opportunity to evaluate soil parameters without performing laboratory tests. In addition to its simplicity and cheapness, the results become available immediately. This research provides a guideline on the application of the SPT test method, reliability of adapting the SPT test results in evaluating soil physical and mechanical properties such as Atterberg limits, shear strength, and compressive strength compressibility parameters. A total of 70 boreholes were investigated in this study by taking soil samples between depths of 1.2 to 15.25 meters. The project site was located in Morrow County, Ohio. A regression-based formula was proposed based on Tobit regression with a stepwise variable selection analysis conducted between SPT and other typical soil properties obtained from soil tests. The results of the research illustrated that the shear strength and physical properties of the soil affect the SPT number. The proposed correlation can help engineers to use SPT test results in their design with higher accuracy.

Keywords: standard penetration test, soil properties, soil classification, regression method

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Authors: Olaniyi Awe, Adelana R. Adetunji, Abraham Adeleke

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Mining of alluvial gold ore by artisanal miners has been going on for decades at Itagunmodi, Southwestern Nigeria. In order to optimize the traditional panning gravity separation method commonly used in the area, a mineral particle size analysis study is critical. This study analyzed alluvial gold ore samples collected at identified five different locations in the area with a view to determine the ore particle size distributions. 500g measured of as-received alluvial gold ore sample was introduced into the uppermost sieve of an electrical sieve shaker consisting of sieves arranged in the order of decreasing nominal apertures of 5600μm, 3350μm, 2800μm, 355μm, 250μm, 125μm and 90μm, and operated for 20 minutes. The amount of material retained on each sieve was measured and tabulated for analysis. A screen analysis graph using the Gaudin Schuman method was drawn for each of the screen tests on the alluvial samples. The study showed that the percentages of fine particle size -125+90 μm fraction were 45.00%, 36.00%, 39.60%, 43.00% and 36.80% for the selected samples. These primary ore characteristic results provide reference data for the alluvial gold ore processing method selection, process performance measurement and optimization.

Keywords: alluvial gold ore, sieve shaker, particle size, Gaudin Schumann

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Authors: Zahra Abdolkarimi, Naser Zouri

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Nowadays, there is unbelievable growing of Robots created a collection of complex and motivate subject in robotic and intellectual ornate, also it made a mechatronics style base of theoretical and technical way in Robocop. Additionally, robotics system recommended RoboCup factor as a provider of some standardization and testing method in case of computer discussion widely. The actual purpose of RoboCup is creating independent team of robots in 2050 based of FiFa roles to bring the victory in compare of world star team. In addition, decision making of robots depends to environment reaction, self-player and rival player with using inductive Fuzzy system valuation subsidiary to solve issue of robots in land game. The measure of selection in compare with other methods depends to amount of victories percentage in the same team that plays accidently. Consequences, shows method of our discussion is the best way for Particle Swarm Optimization and Fuzzy system compare to other decision of robotics algorithmic.

Keywords: PSO algorithm, inference fuzzy system, chaos theory, soccer robot league

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Authors: Jui-Pui Hung, Yong-Run Chen, Wei-Cheng Shih, Shen-He Tsui, Kung-Da Wu

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This paper presents the effect on the tooling conditions on the machining stabilities of a milling machine tool. The machining stability was evaluated in different feeding direction in the X-Y plane, which was referred as the orientation-dependent machining stability. According to the machining mechanics, the machining stability was determined by the frequency response function of the cutter. Thus, we first conducted the vibration tests on the spindle tool of the milling machine to assess the tool tip frequency response functions along the principal direction of the machine tool. Then, basing on the orientation dependent stability analysis model proposed in this study, we evaluated the variation of the dynamic characteristics of the spindle tool and the corresponding machining stabilities at a specific feeding direction. Current results demonstrate that the stability boundaries and limited axial cutting depth of a specific cutter were affected to vary when it was fixed in the tool holder with different overhang length. The flute of the cutter also affects the stability boundary. When a two flute cutter was used, the critical cutting depth can be increased by 47 % as compared with the four flute cutter. The results presented in study provide valuable references for the selection of the tooling conditions for achieving high milling performance.

Keywords: tooling condition, machining stability, milling machine, chatter

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Authors: Lokes Parvatha Kumaran S., Sakthi Jay Mahenthar C., Sathyaprakash P., Jayakumar V., Shobanadevi A.

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With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network.

Keywords: quantum computing, quantum machine learning, variational quantum circuit, deep reinforcement learning, quantum information encoding scheme

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Authors: Ruchi Makani, B. V. R. Reddy

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Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

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Authors: Kiumars Shahbazi, Salah Salimian, Abdolrahim Hashemi Dizaj

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Locating is one of the key elements in success and survival of industrial centers and has great impact on cost reduction of establishment and launching of various economic activities. In this study, streets with unequal length model have been used that is the classic extension of Spoke model; however with unlimited number of streets with uneven lengths. The results showed that the spoke model is a special case of streets with unequal length model. According to the results of this study, if the strategy of enterprises and firms is to select both price and location, there would be no balance in the game. Furthermore, increased length of streets leads to increased profit of enterprises and with increased number of streets, the enterprises choose locations that are far from center (the maximum differentiation), and the enterprises' output will decrease. Moreover, the enterprise production rate will incline toward zero when the number of streets goes to infinity, and complete competition outcome will be achieved.

Keywords: locating, Nash equilibrium, streets with unequal length model, streets with unequal length model

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Authors: Mohammed S. Alqahtani, Paulo J. Bartolo

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External fixation is a common technique for the treatment and stabilization of bone fractures. Different designs have been proposed by companies and research groups, but all of them present limitations such as high weight, not comfortable to use, and not customized to individual patients. This paper proposes a lightweight customized external fixator, overcoming some of these limitations. External fixators are designed using a set of techniques such as medical imaging, CAD modelling, finite element analysis, and full factorial design of experiments. Key design parameters are discussed, and the optimal set of parameters is used to design the final external fixator. Numerical simulations are used to validate design concepts. Results present an optimal external fixation design with weight reduction of 13% without compromising its stiffness and structural integrity. External fixators are also designed to be additively manufactured, allowing to develop a strategy for personalization.

Keywords: computer-aided design modelling, external fixation, finite element analysis, full factorial, personalization

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Authors: Saheed Shittu, Lolwa Alansari, Fahed Nattouf, Tawa Olukade, Naji Abdallah, Tamara Alshdafat, Sarra Amdouni

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Cesarean sections (CS), a highly regarded surgical intervention for improving fetal-maternal outcomes and serving as an integral part of emergency obstetric services, are not without complications. Although CS has many advantages, it poses significant risks to both mother and child and increases healthcare expenditures in the long run. The escalating global prevalence of CS, coupled with variations in rates among immigrant populations, has prompted an inquiry into the correlation between CS rates and the nationalities of women undergoing deliveries at Al-Wakra Hospital (AWH), Qatar's second-largest public maternity hospital. This inquiry is motivated by the notable CS rate of 36%, deemed high in comparison to the 34% recorded across other Hamad Medical Corporation (HMC) maternity divisions This is Qatar's first comprehensive investigation of Caesarean section rates and nationalities. A retrospective cross-sectional study was conducted, and data for all births delivered in 2019 were retrieved from the hospital's electronic medical records. The CS rate, the crude rate, and adjusted risks of Caesarean delivery for mothers from each nationality were determined. The common indications for CS were analysed based on nationality. The association between nationality and Caesarean rates was examined using binomial logistic regression analysis considering Qatari women as a standard reference group. The correlation between the CS rate in the country of nationality and the observed CS rate in Qatar was also examined using Pearson's correlation. This study included 4,816 births from 69 different nationalities. CS was performed in 1767 women, equating to 36.5%. The nationalities with the highest CS rates were Egyptian (49.6%), Lebanese (45.5%), Filipino and Indian (both 42.2%). Qatari women recorded a CS rate of 33.4%. The major indication for elective CS was previous multiple CS (39.9%) and one prior CS, where the patient declined vaginal birth after the cesarean (VBAC) option (26.8%). A distinct pattern was noticed: elective CS was predominantly performed on Arab women, whereas emergency CS was common among women of Asian and Sub-Saharan African nationalities. Moreover, a significant correlation was found between the CS rates in Qatar and the women's countries of origin. Also, a high CS rate was linked to instances of previous CS. As a result of these insights, strategic interventions were successfully implemented at the facility to mitigate unwarranted CS, resulting in a notable reduction in CS rate from 36.5% in 2019 to 34% in 2022. This proves the efficacy of the meticulously researched approach. The focus has now shifted to reducing primary CS rates and facilitating well-informed decisions regarding childbirth methods.

Keywords: maternal nationality, caesarean section rate variation, migrants, high-income country

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Authors: Fatin H. Mohamad, Jia H. Wong, Muhammad Bilal, Abdul A. Mohamed Yusoff, Jafri M. Abdullah, Jingli Zhang

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Kv1.4 is a Shaker-related member of voltage-gated potassium channel which can be associated with cardiac action potential but can also be found in Schaffer collateral and dentate gyrus. It has two inactivation mechanisms; the fast N-type and slow C-type. Kv1.4 produces rapid current inactivation. This A type potential of Kv1.4 makes it as a target in antiepileptic drugs (AEDs) selection. In this study, 4-hydroxybenzoic acid, which can be naturally found in bamboo shoots, were tested on its enhancement effect on potassium current of Kv1.4 channel expressed in Xenopus laevis oocytes using the two-microelectrode voltage clamp method. Current obtained were recorded and analyzed with pClamp software whereas statistical analysis were done by student t-test. The ratio of final / peak amplitude is an index of the activity of the Kv1.4 channel. The less the ratio, the greater the function of Kv1.4. The decrease of ratio of which by 1µM 4-hydroxybenzoic acid (n= 7), compared with 0.1% DMSO (vehicle), was mean= 47.62%, SE= 13.76%, P= 0.026 (statistically significant). It indicated more opening of Kv1.4 channels under 4-hydroxybenzoic acid. In conclusion, 4-hydroxybenzoic acid can enhance the function of Kv1.4 potassium channels, which is regarded as one of the mechanisms of antiepileptic treatment.

Keywords: antiepileptic, Kv1.4 potassium channel, two-microelectrode voltage clamp, Xenopus laevis oocytes, 4-hydroxybenzoic acid

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Authors: Tryastuti I. B. Manullang, Juang Sunanto

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This study aimed to find the perspectives of the Toba Batak education stakeholders towards the education of children with disabilities in Toba Samosir North Sumatra Indonesia. The education stakeholders consist of a head of the education department in Toba Samosir, head of the H foundation, two principals and three teachers from the Special Primary Schools. This study uses qualitative a descriptive approach and research data obtained through interviews. The results of this study demonstrate that the education stakeholders knowledge about disabilities needs improvement in accordance with the development of science. The cultural views towards disability and its implications, and the education services available for children with disabilities, in addition, to encountered its problem in Toba Samosir are known. The education concept considered appropriate is the special school and the CBR (Community Based Rehabilitation) strategy, also inclusive education because it represents the Toba Batak philosophy.

Keywords: community based rehabilitation, education concept, education stakeholders, inclusive education

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Authors: Eva Wagner, Lucely Vargas

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Corporate Social Responsibility (CSR) plays an important role in (large-scale) enterprises’ business strategy in developed and emerging countries. This article approaches CSR in international comparison by examining the CSR reporting of 116 leading companies in Austria, Germany, Colombia and Chile from 2006 to 2010. We have used an independently developed scoring model which analyzes reported CSR-activities using seven dimensions to efficiently assess CSR. The study reveals that there are significant differences in CSR-commitment among countries and regions: German companies, as expected, lead most of the investigated CSR dimensions revealing stronger commitment to CSR than their Austrian, Colombian and Chilean counterparts. Even if Latin American companies lag behind their European counterparts, they exhibit high CSR-performance in the social dimension: corporate giving and philanthropic activities are firmly anchored in the tradition of Latin American companies. This indicates that particular CSR-emphases reflect the political and social circumstances of each individual country.

Keywords: corporate social responsibility, corporate social performance, international comparison

Procedia PDF Downloads 305