Search results for: sequential forward selection

Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: band selection, fuzzy c-means, k-means, hyperspectral image

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Authors: Jaishree Ranganathan, Poonam Rajurkar, Angelina A. Tzacheva, Zbigniew W. Ras

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In today’s world, business often depends on the customer feedback and reviews. Sentiment analysis helps identify and extract information about the sentiment or emotion of the of the topic or document. Attribute selection is a challenging problem, especially with large datasets in actionable pattern mining algorithms. Action Rule Mining is one of the methods to discover actionable patterns from data. Action Rules are rules that help describe specific actions to be made in the form of conditions that help achieve the desired outcome. The rules help to change from any undesirable or negative state to a more desirable or positive state. In this paper, we present a Lexicon based weighted scheme approach to identify emotions from customer feedback data in the area of manufacturing business. Also, we use Rough sets and explore the attribute selection method for large scale datasets. Then we apply Actionable pattern mining to extract possible emotion change recommendations. This kind of recommendations help business analyst to improve their customer service which leads to customer satisfaction and increase sales revenue.

Keywords: actionable pattern discovery, attribute selection, business data, data mining, emotion

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Authors: Rohan Erasala, Ian McCulloh

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The NFL Draft is a chance for every NFL team to select their next superstar. As a result, teams heavily invest in scouting, and millions of fans partake in the online discourse surrounding the draft. This paper investigates the potential correlations between positive sentiment in individual draft selection threads from the subreddit r/NFL and if this data can be used to make successful player recommendations. It is hypothesized that there will be limited correlations and nonviable recommendations made from these threads. The hypothesis is tested using sentiment analysis of draft thread comments and analyzing correlation and precision at k of top scores. The results indicate weak correlations between the percentage of positive comments in a draft selection thread and a player’s approximate value, but potentially viable recommendations from looking at players whose draft selection threads have the highest percentage of positive comments.

Keywords: national football league, NFL, NFL Draft, sentiment analysis, Reddit, social media, NLP

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Authors: Boussoualim Nacira, Aklouf Youcef

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Software as a Service (SaaS) is a software delivery paradigm in which the product is not installed on-premise, but it is available on Internet and Web. The customers do not pay to possess the software itself but rather to use it. This concept of pay per use is very attractive. Hence, we see increasing number of organizations adopting SaaS. However, each customer is unique, which leads to a very large variation in the requirements off the software. As several suppliers propose SaaS products, the choice of this latter becomes a major issue. When multiple criteria are involved in decision making, we talk about a problem of «Multi-Criteria Decision-Making» (MCDM). Therefore, this paper presents a method to help customers to choose a better SaaS product satisfying most of their conditions and alternatives. Also, we know that a good method of adaptive selection should be based on the correct definition of the different parameters of choice. This is why we started by extraction and analysis the various parameters involved in the process of the selection of a SaaS application.

Keywords: cloud computing, business operation, Multi-Criteria Decision-Making (MCDM), Software as a Service (SaaS)

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Authors: Chigbu Ruth Nnena

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This paper discussed the concept of meat its nutritive value in family meals. The paper further discussed the selection, storage and preparation of meat in family meal the Nigerian way. The paper made the following recommendations among others; that families in Nigeria should rear cow meat for easy access to the meant and that family should purchase meat that are fresh from chain shops in the market to avoid meat contamination among others.

Keywords: meat, selection, storage meals, concept and preparation

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Authors: Nadama Kumar, P. Parthiban, T. Niranjan

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In the present paper, we propose an incorporated approach for 3PL supplier choice that suits the distinctive strategic needs of the outsourcing organization in southern part of India. Four fundamental criteria have been used in particular Performance, IT, Service and Intangible. These are additionally subdivided into fifteen sub-criteria. The proposed strategy coordinates Structural Equation Modeling (SEM) and Non-additive Fuzzy Integral strategies. The presentation of fluffiness manages the unclearness of human judgments. The SEM approach has been used to approve the determination criteria for the proposed show though the Non-additive Fuzzy Integral approach uses the SEM display contribution to assess a supplier choice score. The case organization has a exclusive vertically integrated assembly that comprises of several companies focusing on a slight array of the value chain. To confirm manufacturing and logistics proficiency, it significantly relies on 3PL suppliers to attain supply chain superiority. However, 3PL supplier selection is an intricate decision-making procedure relating multiple selection criteria. The goal of this work is to recognize the crucial 3PL selection criteria by using the non-additive fuzzy integral approach. Unlike the outmoded multi criterion decision-making (MCDM) methods which frequently undertake independence among criteria and additive importance weights, the nonadditive fuzzy integral is an effective method to resolve the dependency among criteria, vague information, and vital fuzziness of human judgment. In this work, we validate an empirical case that engages the nonadditive fuzzy integral to assess the importance weight of selection criteria and indicate the most suitable 3PL supplier.

Keywords: 3PL, non-additive fuzzy integral approach, SEM, fuzzy

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Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris

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The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.

Keywords: cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization

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Authors: Rajeev Ravindran, Amit K. Jaiswal

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Waste from the food-processing industry is produced in large amount and contains high levels of lignocellulose. Due to continuous accumulation throughout the year in large quantities, it creates a major environmental problem worldwide. The chemical composition of these wastes (up to 75% of its composition is contributed by polysaccharide) makes it inexpensive raw material for the production of value-added products such as biofuel, bio-solvents, nanocrystalline cellulose and enzymes. In order to use lignocellulose as the raw material for the microbial fermentation, the substrate is subjected to enzymatic treatment, which leads to the release of reducing sugars such as glucose and xylose. However, the inherent properties of lignocellulose such as presence of lignin, pectin, acetyl groups and the presence of crystalline cellulose contribute to recalcitrance. This leads to poor sugar yields upon enzymatic hydrolysis of lignocellulose. A pre-treatment method is generally applied before enzymatic treatment of lignocellulose that essentially removes recalcitrant components in biomass through structural breakdown. Present study is carried out to find out the best pre-treatment method for the maximum liberation of reducing sugars from spent coffee waste (SPW). SPW was subjected to a range of physical, chemical and physico-chemical pre-treatment followed by a sequential, combinatorial pre-treatment strategy is also applied on to attain maximum sugar yield by combining two or more pre-treatments. All the pre-treated samples were analysed for total reducing sugar followed by identification and quantification of individual sugar by HPLC coupled with RI detector. Besides, generation of any inhibitory compounds such furfural, hydroxymethyl furfural (HMF) which can hinder microbial growth and enzyme activity is also monitored. Results showed that ultrasound treatment (31.06 mg/L) proved to be the best pre-treatment method based on total reducing content followed by dilute acid hydrolysis (10.03 mg/L) while galactose was found to be the major monosaccharide present in the pre-treated SPW. Finally, the results obtained from the study were used to design a sequential lignocellulose pre-treatment protocol to decrease the formation of enzyme inhibitors and increase sugar yield on enzymatic hydrolysis by employing cellulase-hemicellulase consortium. Sequential, combinatorial treatment was found better in terms of total reducing yield and low content of the inhibitory compounds formation, which could be due to the fact that this mode of pre-treatment combines several mild treatment methods rather than formulating a single one. It eliminates the need for a detoxification step and potential application in the valorisation of lignocellulosic food waste.

Keywords: lignocellulose, enzymatic hydrolysis, pre-treatment, ultrasound

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Authors: Mohamed Fawzy Elzarei, Yousef Mohammed Al-Dakheel, Ali Mohamed Alseaf

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Modern molecular techniques, like single marker analysis for linked traits to these markers, can provide us with rapid and accurate genetic results. In the last two decades of the last century, the applications of molecular techniques were reached a faraway point in cattle, sheep, and pig. In goats, especially in our region, the application of molecular techniques is still far from other species. As reported by many researchers, microsatellites marker is one of the suitable markers for lie studies. The single marker linked to traits of interest is one technique allowed us to early select animals without the necessity for mapping the entire genome. Simplicity, applicability, and low cost of this technique gave this technique a wide range of applications in many areas of genetics and molecular biology. Also, this technique provides a useful approach for evaluating genetic differentiation, particularly in populations that are poorly known genetically. The expected breeding value (EBV) and yield deviation (YD) are considered as the most parameters used for studying the linkage between quantitative characteristics and molecular markers, since these values are raw data corrected for the non-genetic factors. A total of 17 microsatellites markers (from chromosomes 6, 14, 18, 20 and 23) were used in this study to search for areas that could be responsible for genetic variability for some milk traits and search of chromosomal regions that explain part of the phenotypic variance. Results of single-marker analyses were used to identify the linkage between microsatellite markers and variation in EBVs of these traits, Milk yield, Protein percentage, Fat percentage, Litter size and weight at birth, and litter size and weight at weaning. The estimates of the parameters from forward and backward solutions using stepwise regression procedure on milk yield trait, only two markers, OARCP9 and AGLA29, showed a highly significant effect (p≤0.01) in backward and forward solutions. The forward solution for different equations conducted that R2 of these equations were highly depending on only two partials regressions coefficient (βi,) for these markers. For the milk protein trait, four marker showed significant effect BMS2361, CSSM66 (p≤0.01), BMS2626, and OARCP9 (p≤0.05). By the other way, four markers (MCM147, BM1225, INRA006, andINRA133) showed highly significant effect (p≤0.01) in both backward and forward solutions in association with milk fat trait. For both litter size at birth and at weaning traits, only one marker (BM143(p≤0.01) and RJH1 (p≤0.05), respectively) showed a significant effect in backward and forward solutions. The estimates of the parameters from forward and backward solution using stepwise regression procedure on litter weight at birth (LWB) trait only one marker (MCM147) showed highly significant effect (p≤0.01) and two marker (ILSTS011, CSSM66) showed a significant effect (p≤0.05) in backward and forward solutions.

Keywords: microsatellites marker, estimated breeding value, stepwise regression, milk traits

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Authors: Viviana Ventre, Giacomo Di Tollo, Roberta Martino

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The portfolio selection problem includes the evaluation of many criteria that are difficult to compare directly and is characterized by uncertain elements. The portfolio selection problem can be modeled as a group decision problem in which several experts are invited to present their assessment. In this context, it is important to study and analyze the process of reaching a consensus among group members. Indeed, due to the various diversities among experts, reaching consensus is not necessarily always simple and easily achievable. Moreover, the concept of consensus is accompanied by the concept of false consensus, which is particularly interesting in the dynamics of group decision-making processes. False consensus can alter the evaluation and selection phase of the alternative and is the consequence of the decision maker's inability to recognize that his preferences are conditioned by subjective structures. The present work aims to investigate the dynamics of consensus attainment in a group decision problem in which equivalent portfolios are proposed. In particular, the study aims to analyze the impact of the subjective structure of the decision-maker during the evaluation and selection phase of the alternatives. Therefore, the experimental framework is divided into three phases. In the first phase, experts are sent to evaluate the characteristics of all portfolios individually, without peer comparison, arriving independently at the selection of the preferred portfolio. The experts' evaluations are used to obtain individual Analytical Hierarchical Processes that define the weight that each expert gives to all criteria with respect to the proposed alternatives. This step provides insight into how the decision maker's decision process develops, step by step, from goal analysis to alternative selection. The second phase includes the description of the decision maker's state through Markov chains. In fact, the individual weights obtained in the first phase can be reviewed and described as transition weights from one state to another. Thus, with the construction of the individual transition matrices, the possible next state of the expert is determined from the individual weights at the end of the first phase. Finally, the experts meet, and the process of reaching consensus is analyzed by considering the single individual state obtained at the previous stage and the false consensus bias. The work contributes to the study of the impact of subjective structures, quantified through the Analytical Hierarchical Process, and how they combine with the false consensus bias in group decision-making dynamics and the consensus reaching process in problems involving the selection of equivalent portfolios.

Keywords: analytical hierarchical process, consensus building, false consensus effect, markov chains, portfolio selection problem

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

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The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors. We used mixed technique of selection that implies rules of random and proportional selection. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from the major Georgian airports. Techniques of statistical observation were prepared. A representative population of foreign visitors and a rule of selection of respondents were determined. We have a trend of growth of tourist numbers and share of tourists from post-soviet countries constantly increases. Level of satisfaction with tourist facilities and quality of service has grown, but still we have a problem of disparity between quality of service and prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher.

Keywords: tourist, expenses, methods, statistics, analysis

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Authors: Douglas MacCutcheon, Florian Pausch, Robert Ljung, Lorna Halliday, Stuart Rosen

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Contemporary classrooms are increasingly inclusive of children with mild to moderate disabilities and children from different language backgrounds (bilinguals, multilinguals), but classroom environments and standards have not yet been adapted adequately to meet these challenges brought about by this inclusivity. Additionally, classrooms are becoming noisier as a learner-centered as opposed to teacher-centered teaching paradigm is adopted, which prioritizes group work and peer-to-peer learning. Challenging listening conditions with distracting sound sources and background noise are known to have potentially negative effects on children, particularly those that are prone to struggle with speech perception in noise. Therefore, this research investigates two groups vulnerable to these environmental effects, namely children with a mild to moderate hearing loss (MMHLs) and sequential bilinguals learning in their second language. In the MMHL study, this group was assessed on speech-in-noise perception, and a number of receptive language and cognitive measures (auditory working memory, auditory attention) and correlations were evaluated. Speech reception thresholds were found to be predictive of language and cognitive ability, and the nature of correlations is discussed. In the bilinguals study, sequential bilingual children’s listening comprehension, speech-in-noise perception, listening effort and release from masking was evaluated under a number of different ecologically valid acoustic scenarios in order to pinpoint the extent of the ‘native language benefit’ for Swedish children learning in English, their second language. Scene manipulations included target-to-distractor ratios and introducing spatially separated noise. This research will contribute to the body of findings from which educational institutions can draw when designing or adapting educational environments in inclusive schools.

Keywords: sequential bilinguals, classroom acoustics, mild to moderate hearing loss, speech-in-noise, release from masking

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Authors: Stella Chioma Nwizu, Emmanuel Nwangwu

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Entrepreneurship, Vocational, and Technical education is an education that prepares one for effective adaptation to the world of work. It equally makes individuals self-reliant, self-sufficient and contributes to the development of society. It is, therefore, imperative that this type of education should be a priority in the development of any nation and should be given the utmost political support because of its importance and increasing demand on a global scale. This paper qualitatively explores three research questions on the policy status of Entrepreneurial, Vocational, and Technical Education (EVTE) in Nigeria, challenges hindering the enhancement of Entrepreneurial skills, Vocational and Technical Education in Nigeria, and strategies for the way forward. The major sources of data are secondary, interview and observation. Findings revealed the need to revise the policy of ETVE to meet the needs of the changing world of work. Challenges identified include corruption, inadequate funding, inadequate equipment, unqualified TVET Teachers/Instructors, poor documentation, policy implementation, poor conditions of service, and poor supervision of TVET programmes. Finally, the study identified policy revision, improvement in budgetary allocation, collaboration, sensitization, Public-Private Partnership, and training and retraining of instructors as the way forward toward the amelioration of the issues raised.

Keywords: entrepreneurship, entrepreneurial skills, vocational and technical education, technical and vocational education and training, VTE policy

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Authors: M. Budakoglu, M. Karaman, D. Kiran, Z. Doner, B. Zeytuncu, B. Tanç, M. Kumral

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Lake Acıgöl is one of the large saline lacustrine environment in Turkey. Eleven trace metals (Cr, Mn, Fe, Al, Co, Ni, Cu, Zn, Cd, Pb and As) in 9 surface and subsurface sediment samples from the Lake Acıgöl were analyzed with the bulk and sequential extraction analysis methods by ICP-MS to obtain the metal distribution patterns in this extreme environment. Five stepped sequential extraction technique (1- exchangeable, 2- bond to carbonates, 3- bond to iron and manganese oxides/hydroxides, 4- bond to organic matter and sulphides, and 5- residual fraction incorporated into clay and silicate mineral lattices) was used to characterize the various forms of metals in the <63μ size sediments. The metal contents (ppm) and their percentages for each extraction step were reported and compared with the results obtained from the total digestion. Results indicate that sum of the four fraction are in good agreement with the total digestion results of Ni, Cd, As, Zn, Cu and Fe with the satisfactory recoveries (94.04–109.0%) and the method used is reliable and repeatable for these elements. It was found that there were high correlations between Fe vs. Ni loads in the fraction of F2 and F4 with R2= 0,91 and 0,81, respectively. Comparison of totally 135 chemical analysis results in three sampling location and for 5 fraction between Fe-Co, Co-Ni and Fe-Ni element couples were presented elevated correlations with R2=0,98, 0,92 and 0,91, respectively.

Keywords: Lake Acigol, sequancial extraction, recent lake sediment, geochemical speciation of heavy metals

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Authors: Nasrullah khan

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Today business environment is very dynamic and most of organizations are in tough competition for their added values and sustainable hold in market. To achieve such objectives, organizations must have dynamic and creative people as optimized process. To get these people, there should strong human resource management system in organizations. There are multiple approaches have been devised in literature to hire more job relevant and more suitable people. This study proposed an ANP (Analytic Network Process) approach to hire faculty members for a university system. This study consists of two parts. In fist part, a through literature survey and universities interview are conducted in order to find the common criteria for the selection of academic staff. In second part the available candidates are prioritized on the basis of the relative values of these criteria. According to results the GRE & foreign language, GPA and research paper writing were most important factors for the selection of academic staff.

Keywords: creative people, ANP, academic staff, business environment

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Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

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Authors: Sharun Akter Khushbu

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‘SOS’ addresses text summary such as feasibility study and allows more comprehensive methods on text of language resources. Resources language has been exploited by the importance of text documental procedure. Throughout this key idea will come out a machine interpreter called an SOS that has built an argumentative as an employed model is LSTM-CNN(long short-term memory- recurrent neural network). Summarization of Bengali text formulated by the information of latent structure instead of brief input string counting as text. Text summarization is the proper utilization of optimal solutions being time reduction, and easy interpretation whenever human-generated summary and machine targeted summary remain similar and without degrading the semantic summarization quality. According to the problem affirmation key idea has advanced an algorithm with the method of encoder and decoder describing a sequential structure that is rigorously connected with actual predicted and meaningful output. Regarding the seq2seq approach aimed in the future with high semantic summarization similarity on behalf of the large data samples that are also enlisted by the method. Thus, the SOS method assigns a discriminator over Bengali text documents where encoded input sequences such as summary and decoded the targeted summary of gist will be an error-free machine.

Keywords: LSTM-CNN, NN, SOS, text summarization

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Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support the operational decision of the Emergency Medical Service (EMS) regarding the assignment of medical emergency requests to Emergency Departments (ED). In the literature, this problem is also known as “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies are mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a request. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the transport time and release the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs, considering information relating to the subsequent phases of the process, such as the case-mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to evaluate different hospital selection policies. Therefore, the next steps of the research consisted of the development of a general simulation architecture, its implementation in the AnyLogic software and its validation on a realistic dataset. The hospital selection policy that produced the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, which is based on a retrospective estimate of the TTP, and a dynamic approach, which is based on a predictive estimate of the TTP determined with a constantly updated Winters model. Findings reveal that considering the minimization of TTP as a hospital selection policy raises several benefits. It allows to significantly reduce service throughput times in the ED with a minimum increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case-mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms of TTP estimation than a retrospective approach but entails a more difficult application. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: discrete event simulation, emergency medical services, forecast model, hospital selection

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Authors: Benbellil-Tafoughalt Saida, Tababouchet Meriem

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Sexual selection is the most supported explanation for genital extravagance occurring in animals. In promiscuous species, population density, as well as climate conditions, may act on the sperm competition intensity, one of the most important mechanism of post-copulatory sexual selection. The present study is empirical testing of sexual selection's potential role on genitalia variation in the simultanuously hermaphroditic land snail Helixaperta (Pulmonata, Stylommatophora). The purpose was to detect the patterns as well as the origin of the distal genitalia variability and especially to test the potential effect of sexual selection. The study was performed on four populations, H. aperta, different in habitat humidity regimes and presenting variable densities, which were mostly low. The organs of interest were those involved in spermatophore production, reception, and manipulation. We examined whether the evolution of those organs is connected to sperm competition intensity which is traduced by both population density and microclimate humidity. We also tested the hypothesis that those organs evolve in response to shell size. The results revealed remarkable differences in both snails’ size and organs lengths between populations. In most cases, the length of genitalia correlated positively to snails’ body size. Interestingly, snails from the more humid microclimate presented the highest mean weight and shell dimensions comparing to those from the less humid microclimate. However, we failed to establish any relation between snail densities and any of the measured genitalia traits.

Keywords: fertilization pouch, helix aperta, land snails, reproduction, sperm storage, spermatheca

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Authors: Kari Huhtala, Iiro Jussila

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The supervisory board is assumed to use power in the governance of a firm, but the actual use of power has been scantly investigated. The research question of the paper is “How does the supervisory board use power in the selection of the board of directors”. The data stem from 11 large Finnish agricultural cooperatives. The research approach was qualitative including semi-structured interviews of the board of directors and supervisory board chairpersons. The results were analyzed and interpreted against theories of social power. As a result, the use of power is approached from two perspectives: (1) formal position-based authority and (2) informal power. Central elements of power were the mandate of the supervisory board, the role of the supervisory board, the supervisory board chair, the nomination committee, collaboration between the supervisory board and the board of directors, the role of regions and the role of the board of directors. The study contributes to the academic discussion on corporate governance in cooperatives and on the supervisory board in the context of the two-tier model. Additional research of the model in other countries and of other types of cooperatives would further academic understanding of supervisory boards.

Keywords: board, co-operative, supervisory board, selection, director

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Authors: Ketan Mahawer, Abeer Mutto, S. K. Gupta

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The mining wastewater contains inorganic metal salts, which makes it saline and additionally contributes to contaminating the surface and underground freshwater reserves that exist nearby mineral processing industries. Therefore, treatment of wastewater and water recovery is obligatory by any available technology before disposing it into the environment. Currently, reverse osmosis (RO) is the commercially acceptable conventional membrane process for saline wastewater treatment, but consumes an enormous amount of energy and makes the process expensive. To solve this industrial problem with minimum energy consumption, we tested the feasibility of forward osmosis-nanofiltration (FO-NF) hybrid process for the mining wastewater treatment. The FO-NF process experimental results for 0.029M concentration of saline wastewater treated by 0.42 M sodium-sulfate based draw solution shows that specific energy consumption of the FO-NF process compared with standalone NF was slightly above (between 0.5-1 kWh/m3) from conventional process. However, average freshwater recovery was 30% more from standalone NF with same feed and operating conditions. Hence, FO-NF process in place of RO/NF offers a huge possibility for treating mining industry wastewater and concentrates the metals as the by-products without consuming an excessive/large amount of energy and in addition, mitigates the fouling in long periods of treatment, which also decreases the maintenance and replacement cost of the separation process.

Keywords: forward osmosis, nanofiltration, mining, draw solution, divalent solute

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Authors: Rahmad Wisnu Wardana, Eakachai Warinsiriruk, Sutep Joy-A-Ka

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Selecting the most suitable welding process usually depends on experiences or common application in similar companies. However, this approach generally ignores many criteria that can be affecting the suitable welding process selection. Therefore, knowledge automation through knowledge-based systems will significantly improve the decision-making process. The aims of this research propose integrated data envelopment analysis (DEA) and fuzzy credibility constrained programming approach for identifying the best welding process for stainless steel storage tank in the food and beverage industry. The proposed approach uses fuzzy concept and credibility measure to deal with uncertain data from experts' judgment. Furthermore, 12 parameters are used to determine the most appropriate welding processes among six competitive welding processes.

Keywords: welding process selection, data envelopment analysis, fuzzy credibility constrained programming, storage tank

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Dechrit Maneetham

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The aim of this paper was to design a void and head controlled electric power wheelchair (EPW). A novel activate the control system for quadriplegics with voice, head and neck mobility. Head movement has been used as a control interface for people with motor impairments in a range of applications. Acquiring measurements from the module is simplified through a synchronous a motor. Axis measures the two directions namely x and y. At the same time, patients can control the motorized wheelchair using voice signals (forward, backward, turn left, turn right, and stop) given by it self. The model of a dc motor is considered as a speed control by selection of a PID parameters using genetic algorithm. An experimental set-up constructed, which consists of micro controller as controller, a DC motor driven EPW and feedback elements. This paper is tuning methods of parameter for a pulse width modulation (PWM) control system. A speed controller has been designed successfully for closed loop of the dc motor so that the motor runs very closed to the reference speed and angle. Intelligent wheelchair can be used to ensure the person’s voice and head are attending the direction of travel asserted by a conventional, direction and speed control.

Keywords: wheelchair, quadriplegia, rehabilitation , medical devices, speed control

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Authors: Nuo Xu, Kok Hun Goh, Jeyatharan Kumarasamy

Abstract:

Pile load testing is significant during foundation construction due to its traditional role of design validation and routine quality control of the piling works. In order to verify whether piles can take loadings at specified settlements, piles will have to undergo working load test where the test load should normally up to 150% of the working load of a pile. Selection or sampling of piles for the working load test is done subject to the number specified in Singapore National Annex to Eurocode 7 SS EN 1997-1:2010. This paper presents an innovative way to rationalize the number of pile load test by adopting statistical analysis approach and looking at the coefficient of variance of pile elastic modulus using a case study at Singapore Tuas depot. Results are very promising and have shown that it is possible to reduce the number of working load test without influencing the reliability and confidence on the pile quality. Moving forward, it is suggested that more load test data from other geological formations to be examined to compare with the findings from this paper.

Keywords: elastic modulus of pile under soil interaction, jurong formation, kentledge test, pile load test

Procedia PDF Downloads 355

Authors: Fatima Chaudhary, Rehan Ul Haq

Abstract:

Spatial and anthropogenic factors influencing nest-site selection in birds need to be identified for effective conservative practices. Environmental attributes such as food availability, predator density, previous reproductive success, etc., provide information regarding the site's quality. An artificial nest box experiment was carried out to evaluate the effect of various factors on nest-site selection, as it is hard to assess the natural cavities. The experiment was conducted whereby half of the boxes were filled with old nest material. Artificial nest boxes created with different materials and different sizes and colors were installed at different heights. A total of 14 out of 60 nest boxes were occupied and four of them faced predation. The birds explored a total of 32 out of 60 nests, whereas anthropogenic factors destroyed 25 out of 60 nests. Birds chose empty nest boxes at higher rates however, there was no obvious avoidance of sites having high ectoparasites load due to old nest material. It is also possible that the preference towards the artificial nest boxes may differ from year to year because of several climatic factors and the age of old nest material affecting the parasite's survival. These variables may fluctuate from one season to another. Considering these factors, nest-site selection experiments concerning the effectiveness of artificial nest boxes should be carried out over several successive seasons. This topic may stimulate further studies, which could lead to a fully understanding the birds' evolutionary ecology. Precise information on these factors influencing nest-site selection can be essential from an economic point of view as well.

Keywords: artificial nesting, nest box, old nest material, birds

Procedia PDF Downloads 53

Authors: Qianxi Lv, Junying Liang

Abstract:

Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

Procedia PDF Downloads 140

Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

Abstract:

Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

Procedia PDF Downloads 427

Authors: A. Barratt, M. H. Granat, S. Buttress, B. Roy

Abstract:

Introduction: Physiotherapy is an essential part of the treatment of patients with shoulder problems. The focus of treatment is usually centred on addressing specific physiotherapy goals, ultimately resulting in the improvement in pain and function. This study investigates if computerised physiotherapy using gamification principles are as effective as standard physiotherapy. Methods: Physiotherapy exergames were created using a combination of commercially available hardware, the Microsoft Kinect, and bespoke software. The exergames used were validated by mapping physiotherapy goals of physiotherapy which included; strength, range of movement, control, speed, and activation of the kinetic chain. A multicenter, randomised prospective controlled trial investigated the use of exergames on patients with Shoulder Impingement Syndrome who had undergone Arthroscopic Subacromial Decompression surgery. The intervention group was provided with the automated sensor-based technology, allowing them to perform exergames and track their rehabilitation progress. The control group was treated with standard physiotherapy protocols. Outcomes from different domains were used to compare the groups. An important metric was the assessment of shoulder range of movement pre- and post-operatively. The range of movement data included abduction, forward flexion and external rotation which were measured by the software, pre-operatively, 6 weeks and 12 weeks post-operatively. Results: Both groups show significant improvement from pre-operative to 12 weeks in elevation in forward flexion and abduction planes. Results for abduction showed an improvement for the interventional group (p < 0.015) as well as the test group (p < 0.003). Forward flexion improvement was interventional group (p < 0.0201) with the control group (p < 0.004). There was however no significant difference between the groups at 12 weeks for abduction (p < 0.118067) , forward flexion (p < 0.189755) or external rotation (p < 0.346967). Conclusion: Exergames may be used as an alternative to standard physiotherapy regimes; however, further analysis is required focusing on patient engagement.

Keywords: shoulder, physiotherapy, exergames, gamification

Procedia PDF Downloads 153