Search results for: instance selection

Authors: Mohammad Ali Alavidoost, Hossein Bozorgian

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Criterion-referenced tests (CRTs) are designed to measure student performance against a fixed set of predetermined criteria or learning standards. The reliability of such tests cannot be based on internal reliability. Threshold loss agreement is one way to calculate the reliability of CRTs. However, the selection of master and non-master in such agreement is determined by the threshold point. The problem is if the threshold point witnesses a minute change, the selection of master and non-master may have a drastic change, leading to the change in reliability results. Therefore, in this study, the Fuzzy logic approach is employed as a remedial procedure for data analysis to obviate the threshold point problem. Forty-one Iranian students were selected; the participants were all between 20 and 30 years old. A quantitative approach was used to address the research questions. In doing so, a quasi-experimental design was utilized since the selection of the participants was not randomized. Based on the Fuzzy logic approach, the threshold point would be more stable during the analysis, resulting in rather constant reliability results and more precise assessment.

Keywords: criterion-referenced tests, threshold loss agreement, threshold point, fuzzy logic approach

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Authors: Adriano Z. Zambom, Preethi Ravikumar

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One of the biggest challenges in nonparametric regression is the curse of dimensionality. Additive models are known to overcome this problem by estimating only the individual additive effects of each covariate. However, if the model is misspecified, the accuracy of the estimator compared to the fully nonparametric one is unknown. In this work the efficiency of completely nonparametric regression estimators such as the Loess is compared to the estimators that assume additivity in several situations, including additive and non-additive regression scenarios. The comparison is done by computing the oracle mean square error of the estimators with regards to the true nonparametric regression function. Then, a backward elimination selection procedure based on the Akaike Information Criteria is proposed, which is computed from either the additive or the nonparametric model. Simulations show that if the additive model is misspecified, the percentage of time it fails to select important variables can be higher than that of the fully nonparametric approach. A dimension reduction step is included when nonparametric estimator cannot be computed due to the curse of dimensionality. Finally, the Boston housing dataset is analyzed using the proposed backward elimination procedure and the selected variables are identified.

Keywords: additive model, nonparametric regression, variable selection, Akaike Information Criteria

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Satoshi Kusaka

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The term ‘competency’ is attracting considerable scholarly attention worldwide with the advance of globalization in the 21st century and with the arrival of a knowledge-based society. In the current world environment, familiarity with varied disciplines is regarded to be vital for personal success. The idea of a competency-based educational system was mooted by the ‘Definition and Selection of Competencies (DeSeCo)’ project that was conducted by the Organization for Economic Cooperation and Development (OECD). Further, attention to this topic is not limited to developed countries; it can also be observed in developing countries. For instance, the importance of a competency-based curriculum was mentioned in the ‘2013 Harmonized Curriculum Framework for the East African Community’, which recommends key competencies that should be developed in primary schools. The introduction of such curricula and the reviews of programs are actively being executed, primarily in the East African Community but also in neighboring nations. Taking Mozambique as a case in point, the present paper examines the conception of ‘competency’ as a target of frontline education in developing countries. It also aims to discover the manner in which the syllabus, textbooks and lessons, among other things, in primary-level math education are developed and to determine the challenges faced in the process. This study employs the perspective of competency-based education design to analyze how the term ‘competency’ is defined in the primary-level math syllabus, how it is reflected in the textbooks, and how the lessons are actually developed. ‘Practical competency’ is mentioned in the syllabus, and the description of the term lays emphasis on learners' ability to interactively apply socio-cultural and technical tools, which is one of the key competencies that are advocated in OECD's ‘Definition and Selection of Competencies’ project. However, most of the content of the textbooks pertains to ‘basic academic ability’, and in actual classroom practice, teachers often impart lessons straight from the textbooks. It is clear that the aptitude of teachers and their classroom routines are greatly dependent on the cultivation of their own ‘practical competency’ as it is defined in the syllabus. In other words, there is great divergence between the ‘syllabus’, which is the intended curriculum, and the content of the ‘textbooks’. In fact, the material in the textbooks should serve as the bridge between the syllabus, which forms the guideline, and the lessons, which represent the ‘implemented curriculum’. Moreover, the results obtained from this investigation reveal that the problem can only be resolved through the cultivation of ‘practical competency’ in teachers, which is currently not sufficient.

Keywords: competency, curriculum, mathematics education, Mozambique

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Jhuang Jin-Jhong, Hsieh Wei-Fan

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Climate change causes natural disasters persistently. Therefore, nowadays environmental planning objective tends to the issues of respecting nature and coexisting with nature. As a result, the natural environment analysis, e.g., the analysis of topography, soil, hydrology, climate, vegetation, is highly emphasized. On the other hand, Feng Shui has been a criterion of site selection for residence in Eastern since the ancient times and has had farther influence on site selection for castles and even for temples and tombs. The primary criterion of site selection is judging the quality of Long: mountain range, Sha: nearby mountains, Shui: hydrology, Xue: foundation, Xiang: aspect, which are similar to the environmental variables of mountain range, topography, hydrology and aspect. For the reason, a lot researchers attempt to probe into the connection between the criterion of Feng Shui and environmental planning factors. Most researches only discussed with the composition and theory of space of Feng Shui, but there is no research which explained Feng Shui through the environmental field. Consequently, this study reviewed the theory of Feng Shui through the environmental planning viewpoint and assembled essential composition factors of Feng Shui. The results of this study point. From literature review and comparison of theoretical meanings, we find that the ideal principles for planning the Feng Shui environment can also be used for environmental planning. Therefore, this article uses 12 ideal environmental features used in Feng Shui to contrast the natural aspects of the environment and make comparisons with previous research and classifies the environmental factors into climate, topography, hydrology, vegetation, and soil.

Keywords: the composition of Feng Shui, environmental planning, site selection, main components of the Feng Shui environment

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Authors: Bisi S. Olawoyin

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This study attempts an exploration into behavioural finance in which the traditional assumptions of expected utility maximization with rational investors in efficient markets are dropped. It reviews prior research and evidence about how psychological biases affect investors behaviour and stock selection. This study examined the relationship between demographic variables and financial behaviour biases among public sector retirees who invested in the Nigerian Stock Exchange prior to their retirement. By using questionnaire survey method, a total of 214 valid convenient samples were collected in order to determine how specific demographic and psychological trait affect stock selection between dividend paying and non-dividend paying stocks. Descriptive statistics and OLS were used to analyse the results. Findings showed that most of the retirees prefer dividend paying stocks in few years preceding their retirement but still hold on to their non-dividend paying stock on retirement. A significant difference also exists between senior and junior retirees in preference for non-dividend paying stocks. These findings are consistent with the clientele theories of dividend.

Keywords: behavioural finance, clientele theories, dividend paying stocks, stock selection

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Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: Manuela Villani, Anila Xhahysa, Christopher Brooks, Marco Pagani

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The geological structure of Western Balkans is strongly affected by the collision between Adria microplate and the southwestern Euroasia margin, resulting in a considerably active seismic region. The Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project (BSHAP) (2007-2011, 2012-2015) by NATO supported the preparation of new seismic hazard maps of the Western Balkan, but when inspecting the seismic hazard models produced later by these countries on a national scale, significant differences in design PGA values are observed in the border, for instance, North Albania-Montenegro, South Albania- Greece, etc. Considering the fact that the catalogues were unified and seismic sources were defined within BSHAP framework, obviously, the differences arise from the Ground Motion Prediction Equations selection, which are generally the component with highest impact on the seismic hazard assessment. At the time of the project, a modest database was present, namely 672 three-component records, whereas nowadays, this strong motion database has increased considerably up to 20,939 records with Mw ranging in the interval 3.7-7 and epicentral distance distribution from 0.47km to 490km. Statistical analysis of the strong motion database showed the lack of recordings in the moderate-to-large magnitude and short distance ranges; therefore, there is need to re-evaluate the Ground Motion Prediction Equation in light of the recently updated database and the new generations of GMMs. In some cases, it was observed that some events were more extensively documented in one database than the other, like the 1979 Montenegro earthquake, with a considerably larger number of records in the BSHAP Analogue SM database when compared to ESM23. Therefore, the strong motion flat-file provided from the Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project was merged with the ESM23 database for the polygon studied in this project. After performing the preliminary residual analysis, the candidate GMPE-s were identified. This process was done using the GMPE performance metrics available within the SMT in the OpenQuake Platform. The Likelihood Model and Euclidean Distance Based Ranking (EDR) were used. Finally, for this study, a GMPE logic tree was selected and following the selection of candidate GMPEs, model weights were assigned using the average sample log-likelihood approach of Scherbaum.

Keywords: residual analysis, GMPE, western balkan, strong motion, openquake

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Authors: Vanaja Rao

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In the recent times, the need for the integration of Renewable Energy Sources (RES) in a Smart Grid is on the rise. As a result of this, associated energy storage systems are known to play important roles in sustaining the efficient operation of such RES like wind power and solar power. This paper investigates the importance of location selection of Energy Storage Systems (ESSs) in a Smart Grid. Three scenarios of ESS location is studied and analyzed in a Smart Grid, which are – 1. Near the generation/source, 2. In the middle of the Grid and, 3. Near the demand/consumption. This is explained with the aim of assisting any Distribution Network Operator (DNO) in deploying the ESSs in a power network, which will significantly help reduce the costs and time of planning and avoid any damages incurred as a result of installing them at an incorrect location of a Smart Grid. To do this, the outlined scenarios mentioned above are modelled and analyzed with the National Grid’s datasets of energy generation and consumption in the UK power network. As a result, the outcome of this analysis aims to provide a better overview for the location selection of the ESSs in a Smart Grid. This ensures power system stability and security along with the optimum usage of the ESSs.

Keywords: distribution networks, energy storage system, energy security, location planning, power stability, smart grid

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Authors: Ali Asghar Memon

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A cautious and astute selection of switching devices used in power electronic converters of a switched reluctance (SR) motor is required. It is a matter of choice of best switching devices with respect to their switching ability rather than fulfilling the number of switches. This paper highlights the computational determination of switching losses comprising of switch-on, switch-off and conduction losses respectively by using experimental data in simulation model of a SR machine. The finding of this research is helpful for proper selection of electronic switches and suitable converter topology for switched reluctance motor.

Keywords: converter, operating modes, switched reluctance motor, switching losses

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Authors: Minh Nguyen

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Today, QR or Quick Response Codes are prevalent, and mobile/smart devices can efficiently read and understand them. Therefore, we can see their appearance in many areas, such as storing web pages/websites, business phone numbers, redirecting to an app download, business location, social media. The popularity of the QR Code is mainly because of its many advantages, such as it can hold a good amount of information, is small, easy to scan and read by a general RGB camera, and it can still work with some damages on its surface. However, there are still some issues. For instance, some areas needed to be kept untouched for its successful decode (e.g., the “Finder Patterns,” the “Quiet Zone,” etc.), the capability of built-in auto-correction is not robust enough, and it is not flexible enough for many application such as Augment Reality (AR). We proposed a new Colour Quick Response Code that has several advantages over the original ones: (1) there is no untouchable area, (2) it allows up to 40% of the entire code area to be damaged, (3) it is more beneficial for Augmented Reality applications, and (4) it is back-compatible and readable by available QR Code scanners such as Pyzbar. From our experience, our Colour Quick Response Code is significantly more flexible on damage compared to the original QR Code. Our code is believed to be suitable in situations where standard 2D Barcodes fail to work, such as curved and shiny surfaces, for instance, medical blood test sample tubes and syringes.

Keywords: QR code, computer vision, image processing, 2D barcode

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Authors: Nisa Ertoy Inci, Cengiz Toker

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Winter or autumn-sown faba bean (Vicia faba L.) is one the most efficient ways to overcome drought since faba bean is usually grown under rainfed where drought and high-temperature stresses are the main growth constraints. The objectives of this study were assessment of (i) relationships between cold tolerance and agro-morphological traits, and (ii) the most suitable agro-morphological trait(s) under cold conditions. Three species of the genus Vicia L. includes 109 genotypes of faba bean (Vicia faba L.), three genotypes of narbon bean (V. narbonensis L.) and two genotypes of V. montbretii Fisch. & C.A. Mey. Davis and Plitmann were sown in autumn at highland of Mediterranean region of Turkey. All relatives of faba bean were more cold-tolerant than the faba bean genotypes. Three faba bean genotypes, ACV-42, ACV-84 and ACV-88, were selected as sources of cold tolerance under field conditions. Path and correlation coefficients and factor and principal component analyses indicated that biological yield should be evaluated in selection for cold tolerance under cold conditions ahead of many agro-morphological traits. The seed weight should be considered for selection in early breeding generations because they had the highest heritability.

Keywords: cold tolerance, faba bean, narbon bean, selection

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Authors: Anitha Narasimhan, Aarthy Anandan, Madhan Karky, C. N. Subalalitha

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Games can be the excellent tools for teaching a language. There are few e-learning games in Indian languages like word scrabble, cross word, quiz games etc., which were developed mainly for educational purposes. This paper proposes a Tamil word game called, “Porul”, which focuses on education as well as on players’ thinking and decision-making skills. Porul is a multiple choice based quiz game, in which the players attempt to answer questions correctly from the given multiple options that are generated using a unique algorithm called the Option Selection algorithm which explores the semantics of the question in various dimensions namely, synonym, rhyme and Universal Networking Language semantic category. This kind of semantic exploration of the question not only increases the complexity of the game but also makes it more interesting. The paper also proposes a Scoring Algorithm which allots a score based on the popularity score of the question word. The proposed game has been tested using 20,000 Tamil words.

Keywords: Porul game, Tamil word game, option selection, flash card, scoring, algorithm

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Authors: Mohammed Kamal Alhassan

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The closeness of Turkey to Greece has often been a cause of many disagreements between the people of the two countries. This is against the backdrop of the fact that they have many things in common. In the past, the two countries have had unhealthy relations, which threatened to cut diplomatic ties between them. The 1996 Imia/ Kardak incident and the Öcalan crisis, for instance, nearly resulted in war between them. There were events that also brought the two countries together, for instance, the 1999 earthquake. This was because many lives were lost during the disaster. It is important to note that these events were duly covered by the media in the two countries. First of all, the study intends to look at the role of the media in the formulation of foreign policy in Turkey-Greece relations. It examines the role of the media in the formulation of foreign policy with particular emphasis on agenda-setting and positioning theories of the media as the theoretical framework. Also, the study will discuss the media landscapes in Turkey and Greece, the ownership pattern of the media sector and the relationship between media organizations and the government in the two countries. Moreover, the core foreign policy objectives of the countries will be delved into. Finally, the study employs a qualitative method to critically analyze the role of the media in the formulation of foreign policy in Turkey-Greece relations. It uses the invitation of the Former Prime Minister of Greece, George Andreas Papandreou, to the Ambassadors Conference in Turkey as a case study. In the end, the analysis will prove that, indeed, the media in Greece was effective in the formulation of foreign policy in its relations with Turkey.

Keywords: media organizations, foreign policy, government, diplomacy

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Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

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Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: construction safety, contractor selection, decision support system, relational database

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Authors: Tao Song, Hao Cheng, Guangfeng Tian, Chuang Xu

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An autonomous emergency braking system is an advanced driving assistance system that enables vehicle collision avoidance and pedestrian collision avoidance to improve vehicle safety. At present, because the pedestrian target is small, and the mobility is large, the pedestrian AEB system is faced with more technical difficulties and higher functional requirements. In this paper, a method of pedestrian target selection based on a variable width funnel is proposed. Based on the current position and predicted position of pedestrians, the relative position of vehicle and pedestrian at the time of collision is calculated, and different braking strategies are adopted according to the hazard level of pedestrian collisions. In the CNCAP standard operating conditions, comparing the method of considering only the current position of pedestrians and the method of considering pedestrian prediction position, as well as the method based on fixed width funnel and variable width funnel, the results show that, based on variable width funnel, the choice of pedestrian target will be more accurate and the opportunity of the intervention of AEB system will be more reasonable by considering the predicted position of the pedestrian target and vehicle's lateral motion.

Keywords: automatic emergency braking system, pedestrian target selection, TTC, variable width funnel

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Authors: Caleb B. Sagwa, Tobias O. Okeno, Alexander K. Kahi

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Dairy cattle production plays an important role in the Kenyan economy. However, high incidences of mastitis is a major setback to the productivity in this industry. The current dairy cattle breeding objective in Kenya does not include mastitis resistance, mainly because the economic value of mastitis resistance has not been determined. Therefore this study aimed at estimating the economic value of mastitis resistance in dairy cattle in Kenya. Initial input parameters were obtained from literature on dairy cattle production systems in the tropics. Selection index methodology was used to derive the economic value of mastitis resistance. Somatic cell count (SCC) was used an indicator trait for mastitis resistance. The economic value was estimated relative to milk yield (MY). Economic values were assigned to SCC in a selection index such that the overall gain in the breeding goal trait was maximized. The option of estimating the economic value for SCC by equating the response in the trait of interest to its index response was considered. The economic value of mastitis resistance was US $23.64 while maximum response to selection for MY was US $66.01. The findings of this study provide vital information that is a pre-requisite for the inclusion of mastitis resistance in the current dairy cattle breeding goal in Kenya.

Keywords: somatic cell count, milk quality, payment system, breeding goal

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Authors: R. S. Vikaash, S. Vinodh, T. S. Sai Prashanth

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Six sigma is a defect reduction strategy enabling modern organizations to achieve business prosperity. The practitioners are in need to select best six sigma project among the available alternatives to achieve customer satisfaction. In this circumstance, this article presents a study in which six sigma project selection is formulated as Multi-Criteria Decision-Making(MCDM) problem and the best project has been found using AHP. Five main governing criteria and 14 sub criteria are being formulated. The decision maker’s inputs were gathered and computations were performed. The project with the high values from the set of projects is selected as the best project. Based on calculations, Project “P1”is found to be the best and further deployment actions have been undertaken in the organization.

Keywords: six Sigma, project selection, MCDM, analytic hierarchy process, business prosperity

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Authors: Jenq-Shyong Chen, Ben-Fong Yu

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CNC(computer numerical control) machining centers have been widely used for machining different metal components for various industries. For a specific CNC machine, its everyday job is assigned to cut different products with quite different attributes such as material type, workpiece weight, geometry, tooling, and cutting conditions. Theoretically, the dynamic characteristics of the CNC machine should be properly tuned match each machining job in order to get the optimal machining performance. However, most of the CNC machines are set with only a standard set of CNC parameters. In this study, we have developed an auto-tuning system which can automatically change the CNC parameters and in hence change the machine dynamic characteristics according to the selection of machining modes which are set by the mixed combination of three machine performance indexes: the HO (high surface quality) index, HP (high precision) index and HS (high speed) index. The acceleration, jerk, corner error tolerance, oscillation and dynamic bandwidth of machine’s feed axes have been changed according to the selection of the machine performance indexes. The proposed auto-tuning system of the CNC parameters has been implemented on a PC-based CNC controller and a three-axis machining center. The measured experimental result have shown the promising of our proposed auto-tuning system.

Keywords: auto-tuning, CNC parameters, machining mode, high speed, high accuracy, high surface quality

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Authors: Leila Goosen

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The research problem reported on in this paper relates to improving success in Computer Science and Information Technology subjects where students are learning applications, especially when teaching occurs in a distance education context. An investigation was launched in order to address students’ struggles with applications, and improve their assessment in such subjects. Some of the main arguments presented centre on formulating and situating significant concepts within an appropriate conceptual framework. The paper explores the experiences and perceptions of computing instructors, teaching assistants, students and higher education institutions on how they are empowered by using technologies such as myITLab. They also share how they are working with the available features to successfully teach applications to their students. The data collection methodology used is then described. The paper includes discussions on how myITLab empowers instructors, teaching assistants, students and higher education institutions. Conclusions are presented on the way in which this paper could make an original and significant contribution to the promotion and development of knowledge in fields related to successfully teaching applications for student learning, including in a distance education context. The paper thus provides a forum for practitioners to highlight and discuss insights and successes, as well as identify new technical and organisational challenges, lessons and concerns regarding practical activities related to myITLab as an implementation instance of distance education technologies.

Keywords: distance, education, myITLab, technologies

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Authors: Abeer Amayri, Akif A. Bulgak

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Due to today’s globalization as well as outsourcing practices of the companies, the Supply Chain (SC) performances have become more dependent on the efficient movement of material among places that are geographically dispersed, where there is more chance for disruptions. One such disruption is the quality and delivery uncertainties of outsourcing. These uncertainties could lead the products to be unsafe and, as is the case in a number of recent examples, companies may have to end up in recalling their products. As a result of these problems, there is a need to develop a methodology for selecting suppliers globally in view of risks associated with low quality and late delivery. Accordingly, we developed a two-stage stochastic model that captures the risks associated with uncertainty in quality and delivery as well as a solution procedure for the model. The stochastic model developed simultaneously optimizes supplier selection and purchase quantities under price discounts over a time horizon. In particular, our target is the study of global organizations with multiple sites and multiple overseas suppliers, where the pricing is offered in suppliers’ local currencies. Our proposed methodology is applied to a case study for a US automotive company having two assembly plants and four potential global suppliers to illustrate how the proposed model works in practice.

Keywords: global supply chains, quality, stochastic programming, supplier selection

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Omil Nady Mahrous Maximous

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The construction industry is currently experiencing a shift towards digitisation. This transformation is driven by adopting technologies like Building Information Modelling (BIM), drones, and augmented reality (AR). These advancements are revolutionizing the process of designing, constructing, and operating projects. BIM, for instance, is a new way of communicating and exploiting technology such as software and machinery. It enables the creation of a replica or virtual model of buildings or infrastructure projects. It facilitates simulating construction procedures, identifying issues beforehand, and optimizing designs accordingly. Drones are another tool in this revolution, as they can be utilized for site surveys, inspections, and even deliveries. Moreover, AR technology provides real-time information to workers involved in the project. Implementing these technologies in the construction industry has brought about improvements in efficiency, safety measures, and sustainable practices. BIM helps minimize rework and waste materials, while drones contribute to safety by reducing workers' exposure to areas. Additionally, AR plays a role in worker safety by delivering instructions and guidance during operations. Although the digital transformation within the construction industry is still in its early stages, it holds the potential to reshape project delivery methods entirely. By embracing these technologies, construction companies can boost their profitability while simultaneously reducing their environmental impact and ensuring safer practices.

Keywords: architectural education, construction industry, digital learning environments, immersive learning BIM, digital construction, construction technologies, digital transformation artificial intelligence, collaboration, digital architecture, digital design theory, material selection, space construction

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Authors: Reina Kawase

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Japan set the goal of 80% reduction in GHG emissions by 2050. To consider countermeasures for reducing GHG emission, the production estimation of energy intensive materials, such as steel, is essential. About 50% of steel production is exported in Japan, so it is necessary to consider steel production including export. Steel productions from 2005-2050 in Japan were estimated under various global assumptions based on combination of scenarios such as goods trade scenarios and steel making process selection scenarios. Process selection scenarios decide volume of steel production by process (basic oxygen furnace and electric arc furnace) with considering steel consumption projection, supply-demand balance of steel, and scrap surplus. The range of steel production by process was analyzed. Maximum steel production was estimated under the scenario which consumes scrap in domestic steel production at maximum level. In 2035, steel production reaches 149 million ton because of increase in electric arc furnace steel. However, it decreases towards 2050 and amounts to 120 million ton, which is almost same as a current level. Minimum steel production is under the scenario which assumes technology progress in steel making and supply-demand balance consideration in each region. Steel production decreases from base year and is 44 million ton in 2050.

Keywords: goods trade scenario, steel making process selection scenario, steel production, global warming

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Authors: A. Aguezzoul

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The Logistics Services Providers (LSPs) selection and performance is a strategic decision that affects the overall performance of any company as well as its supply chain. It is a complex process, which takes into account various conflicting quantitative and qualitative factors, as well as outsourced logistics activities. This article focuses on the evolution of the weights associated to these factors over the last years in order to better understand the change in the importance that logistics professionals place on them criteria when choosing their LSPs. For that, an analysis of 17 main studies published during 2014-2017 period was carried out and the results are compared to those of a previous literature review on this subject. Our analysis allowed us to deduce the following observations: 1) the LSPs selection is a multi-criteria process; 2) the empirical character of the majority of studies, conducted particularly in Asian countries; 3) the criteria importance has undergone significant changes following the emergence of information technologies that have favored the work in close collaboration and in partnership between the LSPs and their customers, even on a worldwide scale; 4) the cost criterion is relatively less important than in the past; and finally 5) with the development of sustainable supply chains, the factors associated with the logistic activities of return and waste processing (reverse logistics) are becoming increasingly important in this multi-criteria process of selection and evaluation of LSPs performance.

Keywords: logistics outsourcing, logistics providers, multi-criteria decision making, performance

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Authors: Mohammed A. Almomani, Dina W. Al-Qudah

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Product performance depends on the type and quality of its building material. Successful product must be made using high quality material, and using the right methods. Many foot problems took place as a result of using poor insole material. Therefore, selecting a proper insole material is crucial to eliminate these problems. In this study, the analytical hierarchy process (AHP) is used to provide a systematic procedure for choosing the best material adequate for this application among three material alternatives (polyurethane, poron, and plastzote). Several comparison criteria are used to build the AHP model including: density, stiffness, durability, energy absorption, and ease of fabrication. Poron was selected as the best choice. Inconsistency testing indicates that the model is reasonable, and the materials alternative ranking is effective.

Keywords: AHP, footwear insole, insole material, materials selection

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Authors: Markus Pajones, Theresa Steiner, Matthias Neubauer

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Selecting a logistics location is vital for logistics providers, food retailing and other trading companies since the selection poses an essential factor for economic success. Therefore various location search methods like cost-benefit analysis and others are well known and under usage. The development of a logistics location can be related to considerable negative effects for the eco system such as sealing the surface, wrecking of biodiversity or CO2 and noise emissions generated by freight and commuting traffic. The increasing importance of sustainability demands for taking an informed decision when selecting a logistics location for the future. Sustainability considers economic, ecologic and social aspects which should be equally integrated in the process of location search. Objectives of this paper are to define various methods which support the selection of sustainable logistics locations and to generate knowledge about the suitability, assets and limitations of the methods within the selection process. This paper investigates the role of economical, ecological and social aspects when searching for new logistics locations. Thereby, related work targeted towards location search is analyzed with respect to encoded sustainability aspects. In addition, this research aims to gain knowledge on how to include aspects of sustainability and take an informed decision when searching for a logistics location. As a result, a decomposition of the various location search methods in there components leads to a comparative analysis in form of a matrix. The comparison within a matrix enables a transparent overview about the mentioned assets and limitations of the methods and their suitability for selecting sustainable logistics locations. A further result is to generate knowledge on how to combine the separate methods to a new method for a more efficient selection of logistics locations in the context of sustainability. Future work will especially investigate the above mentioned combination of various location search methods. The objective is to develop an innovative instrument, which supports the search for logistics locations with a focus on a balanced sustainability (economy, ecology, social). Because of an ideal selection of logistics locations, induced traffic should be reduced and a mode shift to rail and public transport should be facilitated.

Keywords: commuting traffic, freight traffic, logistics location search, location search method

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Authors: Oluwatosin M. A. Jesuyon

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In order to propose a simpler tool that eliminates the age-long problems associated with the traditional index method for selection of multiple traits in broilers, the Barttlet factor regression equation is being proposed as an alternative selection tool. 100 day-old chicks each of Arbor Acres (AA) and Annak (AN) broiler strains were obtained from two rival hatcheries in Ibadan Nigeria. These were raised in deep litter system in a 56-day feeding trial at the University of Ibadan Teaching and Research Farm, located in South-west Tropical Nigeria. The body weight and body dimensions were measured and recorded during the trial period. Eight (8) zoometric measurements namely live weight (g), abdominal circumference, abdominal length, breast width, leg length, height, wing length and thigh circumference (all in cm) were recorded randomly from 20 birds within strain, at a fixed time on the first day of the new week respectively with a 5-kg capacity Camry scale. These records were analyzed and compared using completely randomized design (CRD) of SPSS analytical software, with the means procedure, Factor Scores (FS) in stepwise Multiple Linear Regression (MLR) procedure for initial live weight equations. Bartlett Factor Score (BFS) analysis extracted 2 factors for each strain, termed Body-length and Thigh-meatiness Factors for AA, and; Breast Size and Height Factors for AN. These derived orthogonal factors assisted in deducing and comparing trait-combinations that best describe body conformation and Meatiness in experimental broilers. BFS procedure yielded different body conformational traits for the two strains, thus indicating the different economic traits and advantages of strains. These factors could be useful as selection criteria for improving desired economic traits. The final Bartlett Factor Regression equations for prediction of body weight were highly significant with P < 0.0001, R2 of 0.92 and above, VIF of 1.00, and DW of 1.90 and 1.47 for Arbor Acres and Annak respectively. These FSR equations could be used as a simple and potent tool for selection during poultry flock improvement, it could also be used to estimate selection index of flocks in order to discriminate between strains, and evaluate consumer preference traits in broilers.

Keywords: alternative selection tool, Bartlet factor regression model, consumer preference trait, linear and body measurements, live body weight

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Authors: Maram Elkady

Abstract:

Purpose: The purpose behind this study is to determine the impact of some factors on achieving successful accounting information systems (AIS) outsourcing in Egypt, taking into account two factors: the selection of an effective accounting service provider and the quality relationships between the client firm and the accounting service provider. The researcher measured outsourcing success through the perceived benefits, including (strategic, technological, and economic benefits). Design/Methodology/Approach: A survey was carried out by means of questionnaires answered by 152 small and medium Egyptian firms outsourcing their accounting activities. The researcher targeted the personnel in the client firms who were in direct contact with the accounting outsourcer. The hypotheses were tested through multiple regression analysis using SPSS 24 and AMOS 22. Findings: Building a quality relationship with the provider is found to have more impact than the effective selection of the AIS provider on the success of the AIS outsourcing process. Originality/Value: The researcher found that some proxies of each success determinant can be more influential than others based on type of benefits perceived from AIS outsourcing (strategic, technological, and economic).

Keywords: accounting information system, AIS, outsourcing, successful outsourcing, AIS service provider selection, relationship with the accounting service provider

Procedia PDF Downloads 132