Search results for: generalized linear model

Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Noel Dogonyara

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This paper describes the problem of building secure computational services for encrypted information in the Cloud. Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy or confidentiality, availability and integrity of the data and user’s security. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory that is derivable from abstract algebra which can easily be integrated and leveraged in the Cloud computing interface with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based on cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, Fully Homomorphic Encryption Scheme

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Authors: Abdur Rahim, Lauro Tatsuo Kubota, Yoshitaka Gushikem

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Carbon ceramic mesoporous SiO2/50wt%C (SBET= 170 m2g-1), where C is graphite, was prepared by the sol gel method. Scanning electron microscopy images and the respective element mapping showed that, within the magnification used, no phase segregation was detectable. It presented the electric conductivities of 0.49 S cm-1. This material was used to support cobalt phthalocyanine, prepared in situ, to assure a homogeneous dispersion of the electro active complex in the pores of the matrix. The surface density of cobalt phthalocyanine, on the matrix surfaces was 0.015 mol cm-2. Pressed disk, made with SiO2/50wt%C/CoPc, was used to fabricate an electrode and tested as sensors for nitrite determination by electro chemical technique. A linear response range between 0.039 and 0.42 mmol l−1,and correlation coefficient r=0.9996 was obtained. The electrode was chemically very stable and presented very high sensitivity for this analyte, with a limit of detection, LOD = 1.087 x 10-6 mol L-1.

Keywords: SiO2/C/CoPc, sol-gel method, electrochemical sensor, nitrite oxidation, carbon ceramic material, cobalt phthalocyanine

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: Ahmed AlNouss, Salim Ahmed

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Process control refers to the techniques to control the variables in a process in order to maintain them at their desired values. Advanced process control (APC) is a broad term within the domain of control where it refers to different kinds of process control and control related tools, for example, model predictive control (MPC), statistical process control (SPC), fault detection and classification (FDC) and performance assessment. APC is often used for solving multivariable control problems and model predictive control (MPC) is one of only a few advanced control methods used successfully in industrial control applications. Advanced control is expected to bring many benefits to the plant operation; however, the extent of the benefits is plant specific and the application needs a large investment. This requires an analysis of the expected benefits before the implementation of the control. In a real plant simulation studies are carried out along with some experimentation to determine the improvement in the performance of the plant due to advanced control. In this research, such an exercise is undertaken to realize the needs of APC application. The main objectives of the paper are as follows: (1) To apply MPC to a number of simulations set up to realize the need of MPC by comparing its performance with that of proportional integral derivatives (PID) controllers. (2) To study the effect of controller parameters on control performance. (3) To develop appropriate performance index (PI) to compare the performance of different controller and develop novel idea to present tuning map of a controller. These objectives were achieved by applying PID controller and a special type of MPC which is dynamic matrix control (DMC) on the multi-tanks process simulated in loop-pro. Then the controller performance has been evaluated by changing the controller parameters. This performance was based on special indices related to the difference between set point and process variable in order to compare the both controllers. The same principle was applied for continuous stirred tank heater (CSTH) and continuous stirred tank reactor (CSTR) processes simulated in Matlab. However, in these processes some developed programs were written to evaluate the performance of the PID and MPC controllers. Finally these performance indices along with their controller parameters were plotted using special program called Sigmaplot. As a result, the improvement in the performance of the control loops was quantified using relevant indices to justify the need and importance of advanced process control. Also, it has been approved that, by using appropriate indices, predictive controller can improve the performance of the control loop significantly.

Keywords: advanced process control (APC), control loop, model predictive control (MPC), proportional integral derivatives (PID), performance indices (PI)

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Authors: Sagardeep Talukdar, Gautam Kumar Saharia, Riki Dutta, Sudipta Nandy

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In non-linear optics, the Fokas-Lenells equation (FLE) is a well-known integrable equation that describes how ultrashort pulses move across optical fiber. It admits localized wave solutions, just like any other integrable equation. We apply the Hirota bilinearization method to obtain the soliton solution of FLE. The proposed bilinearization makes use of an auxiliary function. We apply the method to FLE with a vanishing boundary condition, that is, to obtain bright soliton. We have obtained bright 1-soliton, 2-soliton solutions and propose the scheme for obtaining N-soliton solution. We have used an additional parameter which is responsible for the shift in the position of the soliton. Further analysis of the 2-soliton solution is done by asymptotic analysis. We discover that the suggested bilinearization approach, which makes use of the auxiliary function, greatly simplifies the process while still producing the desired outcome. We think that the current analysis will be helpful in understanding how FLE is used in nonlinear optics and other areas of physics.

Keywords: asymptotic analysis, fokas-lenells equation, hirota bilinearization method, soliton

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Authors: Anuruddha Jayasuriya, Thanakorn Pheeraphan

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In this paper, a review of different mathematical models which can be used as prediction tools to assess the time to crack reinforced concrete (RC) due to corrosion is investigated. This investigation leads to an experimental study to validate a selected prediction model. Most of these mathematical models depend upon the mechanical behaviors, chemical behaviors, electrochemical behaviors or geometric aspects of the RC members during a corrosion process. The experimental program is designed to verify the accuracy of a well-selected mathematical model from a rigorous literature study. Fundamentally, the experimental program exemplifies both one-dimensional chloride diffusion using RC squared slab elements of 500 mm by 500 mm and two-dimensional chloride diffusion using RC squared column elements of 225 mm by 225 mm by 500 mm. Each set consists of three water-to-cement ratios (w/c); 0.4, 0.5, 0.6 and two cover depths; 25 mm and 50 mm. 12 mm bars are used for column elements and 16 mm bars are used for slab elements. All the samples are subjected to accelerated chloride corrosion in a chloride bath of 5% (w/w) sodium chloride (NaCl) solution. Based on a pre-screening of different models, it is clear that the well-selected mathematical model had included mechanical properties, chemical and electrochemical properties, nature of corrosion whether it is accelerated or natural, and the amount of porous area that rust products can accommodate before exerting expansive pressure on the surrounding concrete. The experimental results have shown that the selected model for both one-dimensional and two-dimensional chloride diffusion had ±20% and ±10% respective accuracies compared to the experimental output. The half-cell potential readings are also used to see the corrosion probability, and experimental results have shown that the mass loss is proportional to the negative half-cell potential readings that are obtained. Additionally, a statistical analysis is carried out in order to determine the most influential factor that affects the time to corrode the reinforcement in the concrete due to chloride diffusion. The factors considered for this analysis are w/c, bar diameter, and cover depth. The analysis is accomplished by using Minitab statistical software, and it showed that cover depth is the significant effect on the time to crack the concrete from chloride induced corrosion than other factors considered. Thus, the time predictions can be illustrated through the selected mathematical model as it covers a wide range of factors affecting the corrosion process, and it can be used to predetermine the durability concern of RC structures that are vulnerable to chloride exposure. And eventually, it is further concluded that cover thickness plays a vital role in durability in terms of chloride diffusion.

Keywords: accelerated corrosion, chloride diffusion, corrosion cracks, passivation layer, reinforcement corrosion

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Authors: Beata Spilakova, Daniel J. Shaw, Radek Marecek, Milan Brazdil

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Hyperscanning affords a unique insight into the brain dynamics underlying human interaction by simultaneously scanning two or more individuals’ brain responses while they engage in dyadic exchange. This provides an opportunity to observe dynamic brain activations in all individuals participating in interaction, and possible interbrain effects among them. The present research aims to provide an experimental paradigm for hyperscanning research capable of delineating among different forms of interaction. Specifically, the goal was to distinguish between two dimensions: (1) interaction structure (concurrent vs. turn-based) and (2) goal structure (competition vs cooperation). Dual-fMRI was used to scan 22 pairs of participants - each pair matched on gender, age, education and handedness - as they played the Pattern Game. In this simple interactive task, one player attempts to recreate a pattern of tokens while the second player must either help (cooperation) or prevent the first achieving the pattern (competition). Each pair played the game iteratively, alternating their roles every round. The game was played in two consecutive sessions: first the players took sequential turns (turn-based), but in the second session they placed their tokens concurrently (concurrent). Conventional general linear model (GLM) analyses revealed activations throughout a diffuse collection of brain regions: The cooperative condition engaged medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC); in the competitive condition, significant activations were observed in frontal and prefrontal areas, insula cortices and the thalamus. Comparisons between the turn-based and concurrent conditions revealed greater precuneus engagement in the former. Interestingly, mPFC, PCC and insulae are linked repeatedly to social cognitive processes. Similarly, the thalamus is often associated with a cognitive empathy, thus its activation may reflect the need to predict the opponent’s upcoming moves. Frontal and prefrontal activation most likely represent the higher attentional and executive demands of the concurrent condition, whereby subjects must simultaneously observe their co-player and place his own tokens accordingly. The activation of precuneus in the turn-based condition may be linked to self-other distinction processes. Finally, by performing intra-pair correlations of brain responses we demonstrate condition-specific patterns of brain-to-brain coupling in mPFC and PCC. Moreover, the degree of synchronicity in these neural signals related to performance on the game. The present results, then, show that different types of interaction recruit different brain systems implicated in social cognition, and the degree of inter-player synchrony within these brain systems is related to nature of the social interaction.

Keywords: brain-to-brain coupling, hyperscanning, pattern game, social interaction

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Authors: Uyi Kizito Ehigiamusoe

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The paper examines the impact of money market on economic growth in Nigeria using data for the period 1980-2012. Econometrics techniques such as Ordinary Least Squares Method, Johanson’s Co-integration Test and Vector Error Correction Model were used to examine both the long-run and short-run relationship. Evidence from the study suggest that though a long-run relationship exists between money market and economic growth, but the present state of the Nigerian money market is significantly and negatively related to economic growth. The link between the money market and the real sector of the economy remains very weak. This implies that the market is not yet developed enough to produce the needed growth that will propel the Nigerian economy because of several challenges. It was therefore recommended that government should create the appropriate macroeconomic policies, legal framework and sustain the present reforms with a view to developing the market so as to promote productive activities, investments, and ultimately economic growth.

Keywords: economic growth, investments, money market, money market challenges, money market instruments

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Authors: N. F. Hamid, A. Kipar, J. Stewart, D. J. Antoine, B. K. Park, D. P. Williams

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Acetaminophen (APAP) is a widely used analgesic that is safe at therapeutic doses. The mouse model of APAP has been extensively used for studies on pathogenesis and intervention of drug induced liver injury based on the CytP450 mediated formation of N-acetyl-p-benzo-quinoneimine and, more recently, as model for mechanism based biomarkers. Delay of the fasted CD1 mice to rebound to the basal level of hepatic GSH compare to fed mice is reported in this study. Histologically, 15 hours fasted mice prior to APAP treatment leading to overall more intense cell loss with no evidence of apoptosis as compared to non-fasted mice, where the apoptotic cells were clearly seen on cleaved caspase-3 immunostaining. After 15 hours post APAP administration, hepatocytes underwent stage of recovery with evidence of mitotic figures in fed mice and return to completely no histological difference to control at 24 hours. On the contrary, the evidence of ongoing cells damage and inflammatory cells infiltration are still present on fasted mice until the end of the study. To further measure the regenerative capacity of the hepatocytes, the inflammatory mediators of cytokines that involved in the progression or regression of the toxicity like TNF-α and IL-6 in liver and spleen using RT-qPCR were also included. Yet, quantification of proliferating cell nuclear antigen (PCNA) has demonstrated the time for hepatic regenerative in fasted is longer than that to fed mice. Together, these data would probably confirm that fasting prior to APAP treatment does not only modulate liver injury, but could have further effects to delay subsequent regeneration of the hepatocytes.

Keywords: acetaminophen, liver, proliferating cell nuclear antigen, regeneration, apoptosis

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Authors: Ye Zhang, Chuanjun Liu

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In-service aircraft is exposed to different types of threaten, e.g. bird strike, ground vehicle impact, and run-way debris, or even lightning strike, etc. To satisfy the aircraft damage tolerance design requirements, the designer has to understand the threatening level for different types of the aircraft structures, either metallic or composite. Exposing to low-velocity impacts may produce very serious internal damages such as delaminations and matrix cracks without leaving visible mark onto the impacted surfaces for composite structures. This internal damage can cause significant reduction in the load carrying capacity of structures. The semi-probabilistic method provides a practical and proper approximation to establish the impact-threat based energy cut-off level for the damage tolerance evaluation of the aircraft components. Thus, the probabilistic distribution of impact threat and the realistic impact energy level cut-offs are the essential establishments required for the certification of aircraft composite structures. A new survey of impact threat to civil aircraft in-service has recently been carried out based on field records concerning around 500 civil aircrafts (mainly single aisles) and more than 4.8 million flight hours. In total 1,006 damages caused by low-velocity impact events had been screened out from more than 8,000 records including impact dents, scratches, corrosions, delaminations, cracks etc. The impact threat dependency on the location of the aircraft structures and structural configuration was analyzed. Although the survey was mainly focusing on the metallic structures, the resulting low-energy impact data are believed likely representative to general civil aircraft, since the service environments and the maintenance operations are independent of the materials of the structures. The probability of impact damage occurrence (Po) and impact energy exceedance (Pe) are the two key parameters for describing the statistic distribution of impact threat. With the impact damage events from the survey, Po can be estimated as 2.1x10-4 per flight hour. Concerning the calculation of Pe, a numerical model was developed using the commercial FEA software ABAQUS to backward estimate the impact energy based on the visible damage characteristics. The relationship between the visible dent depth and impact energy was established and validated by drop-weight impact experiments. Based on survey results, Pe was calculated and assumed having a log-linear relationship versus the impact energy. As the product of two aforementioned probabilities, Po and Pe, it is reasonable and conservative to assume Pa=PoxPe=10-5, which indicates that the low-velocity impact events are similarly likely as the Limit Load events. Combing Pa with two probabilities Po and Pe obtained based on the field survey, the cutoff level of realistic impact energy was estimated and valued as 34 J. In summary, a new survey was recently done on field records of civil aircraft to investigate the probabilistic distribution of impact threat. Based on the data, two probabilities, Po and Pe, were obtained. Considering a conservative assumption of Pa, the cutoff energy level for the realistic impact energy has been determined, which provides potential applicability in damage tolerance certification of future civil aircraft.

Keywords: composite structure, damage tolerance, impact threat, probabilistic

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Authors: B. Kulaga, A. Cinti, F. J. Mazzocchini

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Despite the fact that growing academic attention on dark tourism is a fairly recent phenomenon, among the various reasons for travelling death-related ones, are very ancient. Furthermore, the darker side of human nature has always been fascinated and curious regarding death, or at least, man has always tried to learn lessons from death. This study proposes to describe the phenomenon of dark tourism related to the 2016 earthquake in Central Italy, deadly for 302 people and highly destructive for the rural areas of Lazio, Marche, and Umbria Regions. The primary objective is to examine the motivation-experience relationship in a dark tourism site, using the structural equation model, applied for the first time to a dark tourism research in 2016, in a study conducted after the Beichuan earthquake. The findings of the current study are derived from the calculations conducted on primary data compiled from 350 tourists in the areas mostly affected by the 2016 earthquake, including the town of Amatrice, near the epicenter, Castelluccio, Norcia, Ussita and Visso, through conducting a Likert scale survey. Furthermore, we use the structural equation model to examine the motivation behind dark travel and how this experience can influence the motivation and emotional reaction of tourists. Expected findings are in line with the previous study mentioned above, indicating that: not all tourists visit the thanatourism sites for dark tourism purpose, tourists’ emotional reactions influence more heavily the emotional tourist experience than cognitive experiences do, and curious visitors are likely to engage cognitively by learning about the incident or related issues.

Keywords: dark tourism, emotional reaction, experience, motivation, structural equation model

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Authors: Anil Anand

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Despite enormous strides made during the past decade, particularly with the adoption and expansion of community policing, there remains much that police leaders can do to improve police-public relations. The urgency is particularly evident in cities across the United States and Europe where an increasing number of police interactions over the past few years have ignited large, sometimes even national, protests against police policy and strategy, highlighting a gap between what police leaders feel they have archived in terms of public satisfaction, support, and legitimacy and the perception of bias among many marginalized communities. The decision on which one policing strategy is chosen over another, how many resources are allocated, and how strenuously the policy is applied resides primarily with the police and the units and subunits tasked with its enforcement. The scope and opportunity for police officers in impacting social attitudes and social policy are important elements that cannot be overstated. How do police leaders, for instance, decide when to apply one strategy—say community-based policing—over another, like intelligence-led policing? How do police leaders measure performance and success? Should these measures be based on quantitative preferences over qualitative, or should the preference be based on some other criteria? And how do police leaders define, allow, and control discretionary decision-making? Mending Broken Fences Policing provides police and security services leaders with a model based on social cohesion, that incorporates intelligence-led and community policing (IP-CP), supplemented by a quality/quantity/crime (QQC) framework to provide a four-step process for the articulable application of police intervention, performance measurement, and application of discretion.

Keywords: social cohesion, quantitative performance measurement, qualitative performance measurement, sustainable leadership

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: Wann-Yun Shieh, Chin-Man Wang, Ya-Cheng Shieh

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This study aims to develop an objective scoring system to evaluate hand-eye coordination and hand dexterity for Parkinson’s disease. This system contains three boards, and each of them is implemented with the sensors to sense a user’s finger operations. The operations include the peg test, the block test, and the blind block test. A user has to use the vision, hearing, and tactile abilities to finish these operations, and the board will record the results automatically. These results can help the physicians to evaluate a user’s reaction, coordination, dexterity function. The results will be collected to a cloud database for further analysis and statistics. A researcher can use this system to obtain systematic, graphic reports for an individual or a group of users. Particularly, a deep learning model is developed to learn the features of the data from different users. This model will help the physicians to assess the Parkinson’s disease symptoms by a more intellective algorithm.

Keywords: deep learning, hand-eye coordination, reaction, hand dexterity

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Authors: G. C. Surya Bahadur, Ranjana Kothari

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The paper attempts to analyze linkages between corporate governance and firm performance in India. The study employs a panel data of 50 Nifty companies from 2008 to 2012. Using LSDV panel data model and 2SLS model the study reveals that that good corporate governance practices adopted by companies is positively related with financial performance. Board independence, number of board committees and executive compensation are found to have positive relationship while ownership by promoters and financial leverage have negative relationship with performance. There is existence of bi-directional relationship between corporate governance and financial performance. Companies with sound financial performance are more likely to conform to corporate governance norms and standards and implement sound corporate governance system. The findings indicate that companies can enhance business performance and sustainability by embracing sound corporate governance practices.

Keywords: board structure, corporate governance, executive compensation, ownership structure

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Authors: Heshalini Rajagopal, Li Sze Chow, Raveendran Paramesran

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Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modality. Subjective assessment of the image quality is regarded as the gold standard to evaluate MR images. In this study, a database of 210 MR images which contains ten reference images and 200 distorted images is presented. The reference images were distorted with four types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur and DCT compression. The 210 images were assessed by ten subjects. The subjective scores were presented in Difference Mean Opinion Score (DMOS). The DMOS values were compared with four FR-IQA metrics. We have used Pearson Linear Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) to validate the DMOS values. The high correlation values of PLCC and SROCC shows that the DMOS values are close to the objective FR-IQA metrics.

Keywords: medical resonance (MR) images, difference mean opinion score (DMOS), full reference image quality assessment (FR-IQA)

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Authors: Qiao-Yu Warren Cai

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Due to the rise of big data, building corpora and using them to analyze ChineseL2 learners’ language output has become a trend. Various empirical research has been conducted using Chinese corpora built by different academic institutes. However, most of the research analyzed the data in the Chinese corpora usingcorpus-based qualitative content analysis with descriptive statistics. Descriptive statistics can be used to make summations about the subjects or samples that research has actually measured to describe the numerical data, but the collected data cannot be generalized to the population. Comte, a Frenchpositivist, has argued since the 19th century that human beings’ knowledge, whether the discipline is humanistic and social science or natural science, should be verified in a scientific way to construct a universal theory to explain the truth and human beings behaviors. Inferential statistics, able to make judgments of the probability of a difference observed between groups being dependable or caused by chance (Free Geography Notes, 2015)and to infer from the subjects or examples what the population might think or behave, is just the right method to support Comte’s argument in the field of TCSOL. Also, inferential statistics is a core of quantitative research, but little research has been conducted by combing corpora with inferential statistics. Little research analyzes the differences in Chinese L2 learners’ language corpus output errors by using theOne-way ANOVA so that the findings of previous research are limited to inferring the population's Chinese errors according to the given samples’ Chinese corpora. To fill this knowledge gap in the professional development of Taiwanese TCSOL, the present study aims to utilize the One-way ANOVA to analyze corpus output errors of Chinese L2 learners from America, Myanmar, and Singapore. The results show that no significant difference exists in ‘shì (是) sentence’ and word order errors, but compared with Americans and Singaporeans, it is significantly easier for Myanmar to have ‘sentence blends.’ Based on the above results, the present study provides an instructional approach and contributes to further exploration of how Chinese L2 learners can have (and use) learning strategies to lower errors.

Keywords: Chinese corpus, error analysis, one-way analysis of variance, Chinese L2 learners, Americans, myanmar, Singaporeans

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Authors: Ananya Rajagopal

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The study is based on an analysis of qualitative data used to analyze the business performance of entrepreneurs in emerging markets based on core variables such as collective leadership in reference to social entrepreneurship and reverse accountability attributes of stakeholders. In-depth interviews were conducted with 25 emerging enterprises within Mexico across five industrial segments. The study has been conducted focusing on five major research questions, which helped in developing the grounded theory related to reverser accountability. The results of the study revealed that the traditional entrepreneurship model based on an individualistic leadership style is being replaced by a collective leadership model. The study focuses on the leadership styles within social enterprises aimed at enhancing managerial capabilities and competencies, stakeholder values, and entrepreneurial growth. The theoretical motivation of this study has been derived from stakeholder theory and agency theory.

Keywords: reverse accountability, social enterprises, collective leadership, grounded theory, social governance

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Authors: Debesh R. Roy

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The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

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Authors: M. Erol Genevois, D. Celik, H. Z. Ulukan

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Automated teller machines (ATMs) can be considered among one of the most important service facilities in the banking industry. The investment in ATMs and the impact on the banking industry is growing steadily in every part of the world. The banks take into consideration many factors like safety, convenience, visibility, cost in order to determine the optimum locations of ATMs. Today, ATMs are not only available in bank branches but also at retail locations. Another important factor is the cash management in ATMs. A cash demand model for every ATM is needed in order to have an efficient cash management system. This forecasting model is based on historical cash demand data which is highly related to the ATMs location. So, the location and the cash management problem should be considered together. Although the literature survey on facility location models is quite large, it is surprising that there are only few studies which handle together ATMs location and cash management problem. In order to fulfill the gap, this paper provides a general review on studies, efforts and development in ATMs location and cash management problem.

Keywords: ATM location problem, cash management problem, ATM cash replenishment problem, literature review in ATMs

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Authors: Smail Boussaadi, Hassina Aliane

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With the rapid growth of scientific literature, it is becoming increasingly challenging for researchers to keep up with the latest findings in their fields. Academic, professional networks play an essential role in connecting researchers and disseminating knowledge. To improve the user experience within these networks, we need effective article recommendation systems that provide personalized content.Current recommendation systems often rely on collaborative filtering or content-based techniques. However, these methods have limitations, such as the cold start problem and difficulty in capturing semantic relationships between articles. To overcome these challenges, we propose a new approach that combines BERTopic (Bidirectional Encoder Representations from Transformers), a state-of-the-art topic modeling technique, with community detection algorithms in a academic, professional network. Experiences confirm our performance expectations by showing good relevance and objectivity in the results.

Keywords: scientific articles, community detection, academic social network, recommender systems, neural topic model

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Authors: Selim Kermasha

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A process for the synthesis of structured lipids (SLs) by the lipase-catalyzed interesterification of selected endogenous edible oils such as flaxseed oil (FO) and medium-chain triacylglyceols such as tricaprylin (TC) in non-conventional media (NCM), including organic solvent media (OSM) and solvent-free medium (SFM), was developed. The bioconversion yield of the medium-long-medium-type SLs (MLM-SLs were monitored as the responses with use of selected commercial lipases. In order to optimize the interesterification reaction and to establish a model system, a wide range of reaction parameters, including TC to FO molar ratio, reaction temperature, enzyme concentration, reaction time, agitation speed and initial water activity, were investigated to establish the a model system. The model system was monitored with the use of multiple response surface methodology (RSM) was used to obtain significant models for the responses and to optimize the interesterification reaction, on the basis of selected levels and variable fractional factorial design (FFD) with centre points. Based on the objective of each response, the appropriate level combination of the process parameters and the solutions that met the defined criteria were also provided by means of desirability function. The synthesized novel molecules were structurally characterized, using silver-ion reversed-phase high-performance liquid chromatography (RP-HPLC) atmospheric pressure chemical ionization-mass spectrophotometry (APCI-MS) analyses. The overall experimental findings confirmed the formation of dicaprylyl-linolenyl glycerol, dicaprylyl-oleyl glycerol and dicaprylyl-linoleyl glycerol resulted from the lipase-catalyzed interesterification of FO and TC.

Keywords: enzymatic interesterification, non-conventinal media, nutraceuticals, structured lipids

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Authors: Chin-Ho Lin

Abstract:

This study explores the impact of technical barriers to trade(TBT) on the import value and weight of 54 types of waste products between ASEAN+6 countries and 200 trading partners from 1999–to 2018. By using disaggregated detailed product data and the gravity model, we obtained results demonstrating that implementation of TBT by importing countries is likely to enhance waste trade. After controlling for three combinations of fixed effects, the results remain robust. We consider the quality of waste products by dividing waste products into recyclable and nonrecyclable materials, revealing that imported recyclable waste is more likely to be imported than nonrecyclable waste. When waste trade isregulated by importing countries through TBT implementation, the exporting countries may export relatively valuable waste products, and recyclable waste is of greater economic value because it can be used as an input in other production processes. Finally, developed countries are more likely than developing countries to export waste to the ASEAN+6countries, a finding that supports the waste haven hypothesis.

Keywords: waste trade, ASEAN+6, technical barriers to trade, gravity model, waste haven hypothesis

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Authors: Mona M. Salem, Khaled S. Al-Hagla, Hany M. Ayad

Abstract:

The concept of urban metabolism has increasingly been employed in a diverse range of disciplines as a mean to analyze and theorize the city. Urban ecology has a particular focus on the implications of applying the metabolism concept to the urban realm. This approach has been developed by a few researchers, though it has rarely if ever been used in policy development for city planning. The aim of this research is to use ecologically informed urban planning interventions to increase the sustainability of urban metabolism; with special focus on land stock as a most important city resource by developing a system dynamic based DSS. This model identifies two critical management strategy variables for the Strategic Urban Plan Alexandria SUP 2032. As a result, this comprehensive and precise quantitative approach is needed to monitor, measure, evaluate and observe dynamic urban changes working as a decision support system (DSS) for policy making.

Keywords: ecology, land resource, LULCC, management, metabolism, model, scenarios, system dynamics, urban development

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Authors: V. Tabrizi, A. Vali, R. GHasemi, V. Behnamgol

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In this article, a nonlinear model of an under actuated six degrees of freedom (6 DOF) quadrotor UAV is derived on the basis of the Newton-Euler formula. The derivation comprises determining equations of the motion of the quadrotor in three dimensions and approximating the actuation forces through the modeling of aerodynamic coefficients and electric motor dynamics. The robust nonlinear control strategy includes a smooth second order non-singular terminal sliding mode control which is applied to stabilizing this model. The control method is on the basis of super twisting algorithm for removing the chattering and producing smooth control signal. Also, nonsingular terminal sliding mode idea is used for introducing a nonlinear sliding variable that guarantees the finite time convergence in sliding phase. Simulation results show that the proposed algorithm is robust against uncertainty or disturbance and guarantees a fast and precise control signal.

Keywords: quadrotor UAV, nonsingular terminal sliding mode, second order sliding mode t, electronics, control, signal processing

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Authors: Sanaz Kavianpour, Zuraini Ismail, Bharanidharan Shanmugam

Abstract:

Social Network Sites (SNSs) can be served as an invaluable platform to transfer the information across a large number of individuals. A substantial component of communicating and managing information is to identify which individual will influence others in propagating information and also whether dissemination of information in the absence of social signals about that information will be occurred or not. Classifying the final audience of social data is difficult as controlling the social contexts which transfers among individuals are not completely possible. Hence, undesirable information diffusion to an unauthorized individual on SNSs can threaten individuals’ privacy. This paper highlights the information diffusion in SNSs and moreover it emphasizes the most significant privacy issues to individuals of SNSs. The goal of this paper is to propose a privacy-preserving model that has urgent regards with individuals’ data in order to control availability of data and improve privacy by providing access to the data for an appropriate third parties without compromising the advantages of information sharing through SNSs.

Keywords: anonymization algorithm, classification algorithm, information diffusion, privacy, social network sites

Procedia PDF Downloads 309

Authors: Osarobo Omorogieva Ighodaro, Josephus Otejere

Abstract:

This paper contains the modelling and simulation of GT13E2 combined cycle gas turbine with the aid of the software EBSILON PROFESSIONAL. The design mode was modeled using guaranteed performance data from the power plant, in the off design, temperature variation of ambient air and fogging (spray water at inlet to compressor) was simulated. The fogging was simulated under two different modes; constant fuel consumption and constant turbine exhaust temperature .The model results were validated using actual operating data by applying error percentage analysis. The validation results obtained ranged from -0.0038% to 0% in design condition while the results varied from -0.9202% to 10.24% The model shows that fogging decreases compressor inlet temperature which in turn decreases the power required to drive the compressor hence improving the simple cycle efficiency and hence increasing power generated.

Keywords: inlet fogging, off design, combined cycle, modelling

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Authors: Chun-Wei Liu, Feng-Tsai Weng

Abstract:

People faced pollution threaten in modern age although the standard of exhaust gas of vehicles has been established. The goal of this study is to investigate the effect of water atomizer in a vehicle emission system. Diluted 20% ammonia water was used in spraying system. Micro particles produced by exhausted gas from engine of vehicle which were cumulated through atomized spray in a self-development collector. In experiments, a self-designed atomization model plate and a gas tank controlled by the micro-processor using Pulse Width Modulation (PWM) logic was prepared for exhaust test. The gas from gasoline-engine of vehicle was purified with the model panel collector. A soft well named ANSYS was utilized for analyzing the distribution condition of rejected gas. Micro substance and percentage of CO, HC, CO2, NOx in exhausted gas were investigated at different engine speed, and atomizer vibration frequency. Exceptional results in the vehicle engine emissions measurement were obtained. The temperature of exhausted gas can be decreased 3oC. Micro substances PM10 can be decreased and the percentage of CO can be decreased more than 55% at 2500RPM by proposed system. Value of CO, HC, CO2 and NOX was all decreased when atomizers were used with water.

Keywords: atomizer, CO, HC, NOx, PM2.5

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Authors: Iveta Řepková

Abstract:

The aim of this paper is to estimate the efficiency of the Slovak commercial banks employing the Data Envelopment Analysis (DEA) window analysis approach during the period 2003-2012. The research is based on unbalanced panel data of the Slovak commercial banks. Undesirable output was included into analysis of banking efficiency. It was found that most efficient banks were Postovabanka, UniCredit Bank and Istrobanka in CCR model and the most efficient banks were Slovenskasporitelna, Istrobanka and UniCredit Bank in BCC model. On contrary, the lowest efficient banks were found Privatbanka and CitiBank. We found that the largest banks in the Slovak banking market were lower efficient than medium-size and small banks. Results of the paper is that during the period 2003-2008 the average efficiency was increasing and then during the period 2010-2011 the average efficiency decreased as a result of financial crisis.

Keywords: data envelopment analysis, efficiency, Slovak banking sector, window analysis

Procedia PDF Downloads 346

Authors: Helen S. Ghali, Haidy S. Ghali, Salma Ibrahim, Ossama Hosny, Hatem S. Elbehairy

Abstract:

Infrastructure systems are essential assets in any community; accordingly, authorities aim to maximize its life span while minimizing the life cycle cost. This requires studying the asset conditions throughout its operation and forming a cost-efficient maintenance strategy plan. The objective of this study is to develop a highway management system that provides medium-term maintenance plans with the minimum life cycle cost subject to budget constraints. The model is applied to data collected for the highway network in India with the aim to output a 5-year maintenance plan strategy from 2019 till 2023. The main element considered is the surface coarse, either rigid or flexible pavement. The model outputs a 5-year maintenance plan for each segment given the budget constraint while maximizing the new pavement condition rating and minimizing its life cycle cost.

Keywords: infrastructure, asset management, optimization, maintenance plan

Procedia PDF Downloads 203