Search results for: indirect vector control

Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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Authors: C. Slim

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This paper presents an integrated model, which hybridized data envelopment analysis (DEA) and support vector machine (SVM) together, to class countries according to their efficiency and performance. This model takes into account aspects of multi-dimensional indicators, decision-making hierarchy and relativity of measurement. Starting from a set of indicators of performance as exhaustive as possible, a process of successive aggregations has been developed to attain an overall evaluation of a country’s competitiveness.

Keywords: Artificial Neural Networks (ANN), Support vector machine (SVM), Data Envelopment Analysis (DEA), Aggregations, indicators of performance

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Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: Mohammed Qasim, Kyoung-Dae Kim

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In this paper, we present the design of the super-ellipsoidal potential function (SEPF), that can be used for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of SEPF, we have the full control over the shape and size of the potential function. In particular, we can adjust the length, width, height, and the amount of flattening at the tips of the potential function so that the collision avoidance motion vector generated from the potential function can be adjusted accordingly. Based on the idea of the SEPF, we also propose an approach for the local autonomy of a UAV for its collision avoidance when the UAV is teleoperated by a human operator. In our proposed approach, a teleoperated UAV can not only avoid collision autonomously with other surrounding objects but also track the operator’s control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAVs collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation of quadrotor UAV teleoperation using virtual robot experimentation platform (v-rep) and Matlab programs.

Keywords: artificial potential function, autonomous collision avoidance, teleoperation, quadrotor

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Authors: Amna Khan, Zareena Kausar, Saad Malik

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Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

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Authors: Khaing Yadana Swe, Lillie Dewan

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At present, the cascade PID control is widely used to control the super-heating temperature (main steam temperature). As the main steam temperature has the characteristics of large inertia, large time-delay, and time varying, etc., conventional PID control strategy can not achieve good control performance. In order to overcome the bad performance and deficiencies of main steam temperature control system, Model Free Adaptive Control (MFAC) P cascade control system is proposed in this paper. By substituting MFAC in PID of the main control loop of the main steam temperature control, it can overcome time delays, non-linearity, disturbance and time variation.

Keywords: model-free adaptive control, cascade control, adaptive control, PID

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Authors: Federica Verna, Alessandra Pautasso, Maria Caramelli, Cristiana Maurella, Walter Mignone, Cristina Casalone

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Mosquito-Borne Diseases (MBDs) are dangerously increasing in prevalence, geographical distribution and severity, representing an emerging threat for both humans and animals. Interaction between multiple disciplines is needed for an effective early warning, surveillance and control of MBDs, according to the One Health concept. This work reports the integrated surveillance system enforced by IZSPLV in Piedmont, Liguria and Valle d’Aosta regions (Northwestern Italy) in order to control MDBs spread. Veterinary services and local human health authority are involved in an information network, to connect the surveillance of human clinical cases with entomological surveillance and veterinary monitoring in order to implement control measures in case of outbreak. A systematic entomological surveillance is carried out during the vector season using mosquitoes traps located in sites selected according to risk factors. Collected mosquitoes are counted, identified to species level by morphological standard classification keys and pooled by collection site, date and species with a maximum of 100 individuals. Pools are analyzed, after RNA extraction, by Real Time RT-PCR distinctive for West Nile Virus (WNV) Lineage 1 and Lineage 2, Real Time RT-PCR USUTU virus (USUV) and a traditional flavivirus End-point RT-PCR. Positive pools are sequenced and the related sequences employed to perform a basic local alignment search tool (BLAST) in the GenBank library. Positive samples are sent to the National Reference Centre for Animal Exotic Diseases (CESME, Teramo) for confirmation. With particular reference to WNV, after the confirmation, as provided by national legislation, control measures involving both local veterinary and human health services are activated: equine sera are randomly sampled within a 4 km radius from the positive collection sites and tested with ELISA kit and WNV NAT screening of blood donors is introduced. This surveillance network allowed to detect since 2011 USUV circulation in this area of Italy. WNV was detected in Piedmont and Liguria for the first time in 2014 in mosquitoes. During the 2015 vector season, we observed the expansion of its activity in Piedmont. The virus was detected in almost all Provinces both in mosquitoes (6 pools) and animals (19 equine sera, 4 birds). No blood bag tested resulted infected. The first neuroinvasive human case occurred too. Competent authorities should be aware of a potentially increased risk of MBDs activity during the 2016 vector season. This work shows that this surveillance network allowed to early detect the presence of MBDs in humans and animals, and provided useful information to public authorities, in order to apply control measures. Finally, an additional value of our diagnostic protocol is the ability to detect all viruses belonging to the Flaviviridae family, considering the emergence caused by other Flaviviruses in humans such as the recent Zika virus infection in South America. Italy has climatic and environmental features conducive to Zika virus transmission, the competent vector and many travellers from Brazil reported every year.

Keywords: integrated surveillance, mosquito borne disease, West Nile virus, Zika virus

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Authors: Ming Liu, Chong Wu, Bingquan Liu, Lei Chen

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Internet users have to face the massive amount of textual data every day. Organizing texts into categories can help users dig the useful information from large-scale text collection. Clustering, in fact, is one of the most promising tools for categorizing texts due to its unsupervised characteristic. Unfortunately, most of traditional clustering algorithms lose their high qualities on large-scale text collection. This situation mainly attributes to the high- dimensional vectors generated from texts. To effectively and efficiently cluster large-scale text collection, this paper proposes a vector reconstruction based clustering algorithm. Only the features that can represent the cluster are preserved in cluster’s representative vector. This algorithm alternately repeats two sub-processes until it converges. One process is partial tuning sub-process, where feature’s weight is fine-tuned by iterative process. To accelerate clustering velocity, an intersection based similarity measurement and its corresponding neuron adjustment function are proposed and implemented in this sub-process. The other process is overall tuning sub-process, where the features are reallocated among different clusters. In this sub-process, the features useless to represent the cluster are removed from cluster’s representative vector. Experimental results on the three text collections (including two small-scale and one large-scale text collections) demonstrate that our algorithm obtains high quality on both small-scale and large-scale text collections.

Keywords: vector reconstruction, large-scale text clustering, partial tuning sub-process, overall tuning sub-process

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Authors: A. Abbasi Moshaii, M. Soltan Rezaee, M. Mohammadi Moghaddam

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Control of some mechanisms is hard because of their complex dynamic equations. If part of the complexity is resulting from uncertainties, an efficient way for solving that is robust control. By this way, the control procedure could be simple and fast and finally, a simple controller can be designed. One kind of these mechanisms is 3-RRR which is a parallel mechanism and has three revolute joints. This paper aims to robust control a 3-RRR planner mechanism and it presents that this could be used for other mechanisms. So, a significant problem in mechanisms control could be solved. The relevant diagrams are drawn and they show the correctness of control process.

Keywords: 3-RRR, dynamic equations, mechanisms control, structural uncertainty

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Authors: Alia Abdul Ghaffar, Tom Richardson

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A model reference adaptive control and a fixed gain LQR control were implemented in the height controller of a quadrotor that has parametric uncertainties due to the act of picking up an object of unknown dimension and mass. It is shown that an adaptive control, unlike a fixed gain control, is capable of ensuring a stable tracking performance under such condition, although adaptive control suffers from several limitations. The combination of both adaptive and fixed gain control in the controller architecture results in an enhanced tracking performance in the presence of parametric uncertainties.

Keywords: UAV, quadrotor, robotic arm augmentation, model reference adaptive control, LQR control

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Authors: Chen-Yin Kuo, Yung-Hsin Lee

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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

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Authors: Jasna Hrncic

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Poor family relations predict depression, but also to other mental health issues. Mediating effect of self-efficacy and differentiation of self and moderating effect of decreased accessibility and/or success of other adaptive and defensive mechanisms for overcoming social disadvantages could explain depression as a specific outcome of dysfunctional family relations. The present study analyzes the mediation effect of self-efficacy and differentiation of self from poor family functioning to depressive symptoms and the moderation effect of deprivation of liberty on the listed mediation effect. Deprivation of liberty has, as a general consequence, a decreased accessibility and/or success of many adaptive and defensive mechanisms. It is hypothesized that: 1) self-efficacy and differentiation of self will mediate between family functioning and depressiveness in the total sample, and 2) deprivation of liberty will moderate the stated relations. Cross-sectional study was conducted among 323 male juveniles in Serbia divided in three groups: 98 adolescents deprived of their liberty due to antisocial behavior (incarcerated antisocial group - IAG), 121 adolescents with antisocial behavior in their natural setting (antisocial control group - CAG) and 105 adolescents in general population (general control group - CGG). The CAG was included along with GCG to control the possible influence that comorbidity of antisocial behavior and depressiveness could have on results. Instruments for family relations assessment were: for a whole family of origin the emotional exchange scale and individuation scale from GRADIR by Knezevic, and for a relationship with mother PCS-YSR and CRPBI by barber, and intimacy, rejection, sacrifice, punishment, demands, control and internal control by Opacic and Kos. Differentiation of self (DOS) is measured by emotional self scale (Opacic), self-efficacy (SE) by general incompetence scale by Bezinovic, and depression by BDI (Back), CES-D (Radloff) and D6R (Momirovic). Two-path structural equation modeling based on most commonly reported fit indices, showed that the mediation model had unfavorable fit to our data for total sample [(χ2 (1, N = 324) = 13.73); RMSEA= .20 (90% CI= [.12, .30]); CFI= .98; NFI= .97; AIC=31.73]. Path model provided an adequate fit to the data only for AIG - and not to the data from ACG and GCG. SE and DOS mediated the relationship between PFF and depressiveness. Test of the indirect effects revealed that 23.85% of PFF influences on depressiveness is mediated by these two mediators (the quotient of mediated effect = .24). Test of specific indirect effects showed that SE mediates 22.17%, while DOS mediates 1.67% of PFF influence on depressiveness. Lack of expected mediation effect could be explained by missing other potential mediators (i.e., relationship with that father, social skills, self-esteem) and lower variability of both predictor and criterion variable due to their low levels on the whole sample and on control subsamples. Results suggested that inaccessibility and/or successfulness of other adaptive and defensive mechanisms for overcoming social disadvantages has a strong impact on the mediation effect of self/efficacy and differentiation of self from poor family functioning to depressive symptoms. Further researches could include other potential mediators and a sample of clinically depressed people.

Keywords: antisocial behavior, mediating effect, moderating effect, natural setting, incarceration

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Authors: Tania Tzong, Chao-Yi Teng, Tzong-Yuan Wu

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Currently, Chikungunya virus (CHIKV) transmitted to humans by Aedes mosquitoes has distributed from Africa to Southeast Asia, South America, and South Europe. However, little is known about the antigenic targets for immunity, and there are no licensed vaccines or specific antiviral treatments for the disease caused by CHIKV. Baculovirus has been recognized as a novel vaccine vector with attractive characteristic features of an optional vaccine delivery vehicle. This approach provides the safety and efficacy of CHIKV vaccine. In this study, bi-cistronic recombinant baculoviruses vAc-CMV-CHIKV26S-Rhir-EGFP and vAc-CMV-pH-CHIKV26S-Lir-EGFP were produced. Both recombinant baculovirus can express EGFP reporter gene in insect cells to facilitate the recombinant virus isolation and purification. Examination of vAc-CMV-CHIKV26S-Rhir-EGFP and vAc-CMV-pH-CHIKV26S-Lir-EGFP showed that this recombinant baculovirus could induce syncytium formation in insect cells. Unexpectedly, the immunofluorescence assay revealed the expression of E1 and E2 of CHIKV structural proteins in insect cells infected by vAc-CMV-CHIKV26S-Rhir-EGFP. This result may imply that the CMV promoter can induce the transcription of CHIKV26S in insect cells. There are also E1 and E2 expression in mammalian cells transduced by vAc-CMV-CHIKV26S-Rhir-EGFP and vAc-CMV-pH-CHIKV26S-Lir-EGFP. The expression of E1 and E2 proteins of insect and mammalian cells was validated again by Western blot analysis. The vector construction with dual tandem promoters, which is polyhedrin and CMV promoter, has higher expression of the E1 and E2 of CHIKV structural proteins than the vector construction with CMV promoter only. Most of the E1 and E2 proteins expressed in mammalian cells were glycosylated. In the future, the expression of structural proteins of CHIKV in mammalian cells is expected can form virus-like particle, so it could be used as a vaccine for chikungunya virus.

Keywords: chikungunya virus, virus-like particle, vaccines, baculovirus expression vector system

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Authors: Ana Paula S. A. Correa, Allan K. R. Galardo, Luana A. Lima, Talita F. Sobral, Josiane N. Muller, Jessica F. S. Barroso, Nercy V. R. Furtado, Ednaldo C. Rêgo., Jose B. P. Lima

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Malaria is a public health problem in the Brazilian Legal Amazon. Among the integrated approaches for anopheline control, the Indoor Residual Spraying (IRS) remains one of the main tools in the basic strategy applied in the Amazonian States, where the National Malaria Control Program currently uses one of the insecticides from the pyrethroid class, the Etofenprox WP. Understanding the residual efficacy of insecticides on different surfaces is essential to determine the spray cycles, in order to maintain a rational use and to avoid product waste. The aim of this study was to evaluate the residual efficacy of Etofenprox - VECTRON ® 20 WP on surfaces of Unplastered Cement (UC) and Unpainted Wood (UW) on panels, in field, and in semi-field evaluation of Brazil’s Amapa State. The evaluation criteria used was the cone bioassay test, following the World Health Organization (WHO) recommended method, using plastic cones and female mosquitos of Anopheles sp. The tests were carried out in laboratory panels, semi-field evaluation in a “test house” built in the Macapa municipality, and in the field in 20 houses, being ten houses per surface type (UC and UW), in an endemic malaria area in Mazagão’s municipality. The residual efficacy was measured from March to September 2017, starting one day after the spraying, repeated monthly for a period of six months. The UW surface presented higher residual efficacy than the UC. In fact, the UW presented a residual efficacy of the insecticide throughout the period of this study with a mortality rate above 80% in the panels (= 95%), in the "test house" (= 86%) and in field houses ( = 87%). On the UC surface it was observed a mortality decreased in all the tests performed, with a mortality rate of 45, 47 and 29% on panels, semi-field and in field, respectively; however, the residual efficacy ≥ 80% only occurred in the first evaluation after the 24-hour spraying bioassay in the "test house". Thus, only the UW surface meets the specifications of the World Health Organization Pesticide Evaluation Scheme (WHOPES) regarding the duration of effective action (three to six months). To sum up, the insecticide residual efficacy presented variability on the different surfaces where it was sprayed. Although the IRS with Etofenprox WP was efficient on UW surfaces, and it can be used in spraying cycles at 4-month intervals, it is important to consider the diversity of houses in the Brazilian Legal Amazon, in order to implement alternatives for vector control, including the evaluation of new products or different formulations types for insecticides.

Keywords: Anopheles, vector control, insecticide, bioassay

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Authors: Robert Birkholc

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One of the basic issues related to the creation of characters in media, such as literature and film, is the representation of the characters' thoughts, emotions, and perceptions. This paper is devoted to the social perspective (or the focalization) expressed in film narration. The aim of the paper is to show how social point of view of the hero –conditioned by his origin and the environment from which he comes– can be created by using non-verbal, purely audiovisual means of expression. The issue will be considered on the example of the little-known polish movie The Dancing Hawk (1977) by Grzegorz Królikiewicz, based on the novel by Julian Kawalec. The thesis of the paper is that the polish director uses a narrative figure, which is somewhat analogous to literary form of free indirect discourse. In literature, free indirect discourse is formally ‘spoken’ by the external narrator, but the narration is clearly filtered through the language and thoughts of the character. According to some scholars (such as Roy Pascal), the narrator in this form of speech does not cite the character's words, but uses his way of thinking and imitates his perspective – sometimes with a deep irony. Free indirect discourse is frequently used in Julian Kawalec’s novel. Through the linguistic stylization, the author tries to convey the socially determined perspective of a peasant who migrates to the big city after the Second World War. Grzegorz Królikiewicz expresses the same social experience by pure cinematic form in the adaptation of the book. Both Kawalec and Królikiewicz show the consequences of so-called ‘social advancement’ in Poland after 1945, when the communist party took over political power. On the example of the fate of the main character, Michał Toporny, the director presents the experience of peasants who left their villages and had to adapt to new, urban space. However, the paper is not focused on the historical topic itself, but on the audiovisual form of the movie. Although Królikiewicz doesn’t use frequently POV shots, the narration of The Dancing Hawk is filtered through the sensations of the main character, who feels uprooted and alienated in the new social space. The director captures the hero's feelings through very complex audiovisual procedures – high or low points of view (representing the ‘social position’), grotesque soundtrack, expressionist scenery, and associative editing. In this way, he manages to create the world from the perspective of a socially maladjusted and internally split subject. The Dancing Hawk is a successful attempt to adapt the subjective narration of the book to the ‘language’ of the cinema. Mieke Bal’s notion of focalization helps to describe ‘free indirect discourse’ as a transmedial figure of representing of the characters’ perceptions. However, the polysemiotic medium of the film also significantly transforms this figure of representation. The paper shows both the similarities and differences between literary and cinematic ‘free indirect discourse.’

Keywords: film and literature, free indirect discourse, social experience, subjective narration

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Authors: Tiantian Gu, Dezhi Li, Mian Zhang, Ying Jiang

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Considering the characteristics of residents’ participation in the governance of old community renewal (OCR), a theoretical model of the determinant of residents’ intention to participate in the governance of OCR has been built based on the theory of planned behavior. Seven old communities in Nanjing have been chosen as cases to conduct empirical analysis. The result indicates that participation attitude, subjective norm and perceived behavioral control have significant positive effects on residents’ intention to participate in the governance of the OCR. Recognition of the community, cognition of the OCR and perceived behavioral control have indirect positive effects on residents’ intention to participate in the OCR. In addition, the education level and the length of residence have positive effects on their participation intention, while the gender, age, and monthly income have little effect on it. The research result provides suggestions for the improvement of residents’ participation in the OCR.

Keywords: old community renewal, residents’ participation in governance, intention, theory of planned behavior

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Authors: K. Yahia, A. Ghoggal, A. Titaouine, S. E. Zouzou, F. Benchabane

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This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), Inter-turn Short-Circuits Diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

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Authors: Aditi Viswanathan, Shree Ranjani, Aruna Govada

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With data sizes constantly expanding, and with classical machine learning algorithms that analyze such data requiring larger and larger amounts of computation time and storage space, the need to distribute computation and memory requirements among several computers has become apparent. Although substantial work has been done in developing distributed binary SVM algorithms and multi-class SVM algorithms individually, the field of multi-class distributed SVMs remains largely unexplored. This research seeks to develop an algorithm that implements the Support Vector Machine over a multi-class data set and is efficient in a distributed environment. For this, we recursively choose the best binary split of a set of classes using a greedy technique. Much like the divide and conquer approach. Our algorithm has shown better computation time during the testing phase than the traditional sequential SVM methods (One vs. One, One vs. Rest) and out-performs them as the size of the data set grows. This approach also classifies the data with higher accuracy than the traditional multi-class algorithms.

Keywords: distributed algorithm, MapReduce, multi-class, support vector machine

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Authors: Iqbaldeep Kaur, Amarjeet Kaur

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Software Reusability is important part of software development. So component based software development in case of software testing has gained a lot of practical importance in the field of software engineering from academic researcher and also from software development industry perspective. Finding test cases for efficient reuse of test cases is one of the important problems aimed by researcher. Clustering reduce the search space, reuse test cases by grouping similar entities according to requirements ensuring reduced time complexity as it reduce the search time for retrieval the test cases. In this research paper we proposed approach for re-usability of test cases by unsupervised approach. In unsupervised learning we proposed k-mean and Support Vector Machine. We have designed the algorithm for requirement and test case document clustering according to its tf-idf vector space and the output is set of highly cohesive pattern groups.

Keywords: software testing, reusability, clustering, k-mean, SVM

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Authors: Asim Abbasi, Muhammad Sufyan, Iqra, Hafiza Javaria Ashraf

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The share of vector-borne diseases (VBDs) in the global burden of infectious diseases is almost 17%. The advent of new drugs and latest research in medical science helped mankind to compete with these lethal diseases but still diseases transmitted by different mosquito species, including filariasis, malaria, viral encephalitis and dengue are serious threats for people living in disease endemic areas. Injudicious and repeated use of pesticides posed selection pressure on mosquitoes leading to development of resistance. Hence biological control agents are under serious consideration of scientific community to be used in vector control programmes. Fish have a history of predating immature stages of different aquatic insects including mosquitoes. The noteworthy examples in Africa and Asia includes, Aphanius discolour and a fish in the Panchax group. Moreover, common mosquito fish, Gambusia affinis predates mostly on temporary water mosquitoes like anopheline as compared to permanent water breeders like culicines. Mosquitoes belonging to genus Toxorhynchites have a worldwide distribution and are mostly associated with the predation of other mosquito larvae habituating with them in natural and artificial water containers. These species are harmless to humans as their adults do not suck human blood but feeds on floral nectar. However, their activity is mostly temperature dependent as Toxorhynchites brevipalpis consume 359 Aedes aegypti larvae at 30-32 ºC in contrast to 154 larvae at 20-26 ºC. Although many bacterial species were isolated from mosquito cadavers but those belonging to genus Bacillus are found highly pathogenic against them. The successful species of this genus include Bacillus thuringiensis and Bacillus sphaericus. The prime targets of B. thuringiensis are mostly the immatures of genus Aedes, Culex, Anopheles and Psorophora while B. sphaericus is specifically toxic against species of Culex, Psorophora and Culiseta. The entomopathogenic nematodes belonging to family, mermithidae are also pathogenic to different mosquito species. Eighty different species of mosquitoes including Anopheles, Aedes and Culex proved to be highly vulnerable to the attack of two mermithid species, Romanomermis culicivorax and R. iyengari. Cytoplasmic polyhedrosis virus was the first described pathogenic virus, isolated from the cadavers of mosquito specie, Culex tarsalis. Other viruses which are pathogenic to culicine includes, iridoviruses, cytopolyhedrosis viruses, entomopoxviruses and parvoviruses. Protozoa species belonging to division microsporidia are the common pathogenic protozoans in mosquito populations which kill their host by the chronic effects of parasitism. Moreover, due to their wide prevalence in anopheline mosquitoes and transversal and horizontal transmission from infected to healthy host, microsporidia of the genera Nosema and Amblyospora have received much attention in various mosquito control programmes. Fungal based mycopesticides are used in biological control of insect pests with 47 species reported virulent against different stages of mosquitoes. These include both aquatic fungi i.e. species of Coelomomyces, Lagenidium giganteum and Culicinomyces clavosporus, and the terrestrial fungi Metarhizium anisopliae and Beauveria bassiana. Hence, it was concluded that the integrated use of all these biological control agents can be a healthy contribution in mosquito control programmes and become a dire need of the time to avoid repeated use of pesticides.

Keywords: entomopathogenic nematodes, protozoa, Toxorhynchites, vector-borne

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Authors: Cheba Ben Amar

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Bacillus and Paenibacillus are Gram-positive aerobic endospore-forming bacteria (AEFB) and most abundant in the rhizosphere, they mediated plant growth promotion and disease protection by several complex and interrelated processes involving direct and indirect mechanisms that include nitrogen fixation, phosphate solubilization, siderophores production, phytohormones production and plant diseases control. In addition to their multiple PGPR properties, high secretory capacity, spore forming ability and spore resistance to unfavorable conditions enabling their extended commercial applications for long shelf-life. Due to these unique advantages, Bacillus species were the most an ideal candidate for developing efficient PGPR products such as biopesticides, fungicides and fertilizers. This review list all studied and reported plant growth promoting Bacillus species and strains, discuss their capacities to enhance plant growth and protection with special focusing on the most frequent species Bacillus subtilis, B. pumilus ,B. megaterium, B. amyloliquefaciens , B. licheniformis and B. sphaericus, furthermore we recapitulate the beneficial activities and mechanisms of several species and strains of the genus Paenibacillus involved in plant growth stimulation and plant disease control.

Keywords: bacillus, paenibacillus, PGPR, beneficial activities, mechanisms, growth promotion, disease control, agrobiotechnology

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Authors: Evija Silina, Maris Taube, Maksims Zolovs

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Background: Type 1 diabetes mellitus (T1D) is the most common chronic endocrine pathology in children. The management of type 1 diabetes requires a strong diet, physical activity, lifelong insulin therapy, and proper self-monitoring of blood glucose and is usually complicated and, therefore, may result in a variety of psychosocial problems for children, adolescents, and their families. Metabolic control of the disease is determined by glycated haemoglobin (HbA1c), the main criterion for diabetes compensation. A correlation was observed between anxiety and depression levels and glycaemic control in many previous studies. It is assumed that anxiety and depression symptoms negatively affect glycaemic control. Parental psychological distress was associated with higher child self-report of stress and depressive symptoms, and it had negative effects on diabetes management. Objective: The main objective of this paper is to evaluate the relationship between parental mental health conditions (depression and anxiety) and metabolic control of their adolescents with T1DM. Methods: This cross-sectional study recruited adolescents with T1D (N=251) and their parents (N=251). The respondents completed questionnaires. The 7-item Generalized Anxiety Disorder (GAD-7) scale measured anxiety level; The Patient Health Questionnaire – 9 (PHQ-9) measured depressive symptoms. Glycaemic control of patients was assessed using the last glycated haemoglobin (HbA1c) values. GLM mediation analysis was performed to determine the potential mediating effect of the parent’s mental health conditions (depression and anxiety) on the relationship between the mental health conditions (depression and anxiety) of a child on the level of glycated hemoglobin (HbA1c). To test the significance of the mediated effect (ME) for non-normally distributed data, bootstrapping procedures (10,000 bootstrapped samples) were used. Results: 502 respondents were eligible for screening to detect anxiety and depression symptoms. Mediation analysis was performed to assess the mediating role of parent GAD-7 on the linkage between a dependent variable (HbA1c) and independent variables (child GAD-7 un child PHQ-9). The results revealed that the total effect of child GAD-7 (B = 0.479, z = 4.30, p < 0.001) on HbA1c was significant but the total effect of child PHQ-9 (B = 0.166, z = 1.49, p = 0.135) was not significant. With the inclusion of the mediating variable (parent GAD-7), the impact of child GAD-7 on HbA1c was found insignificant (B = 0.113, z=0.98, p = 0.326), the impact of child PHQ-9 on HbA1c was found also insignificant (B = 0.068, z=0.74, p = 0.458). The indirect effect of child GAD-7 on HbA1c through parent GAD-7 was found significant (B = 0.366, z = 4.31, p < 0.001) and the indirect effect of child PHQ-9 on HbA1c through parent GAD-7 was found also significant (B = 0.098, z = 2.56, p = 0.010). This indicates that the relationship between a dependent variable (HbA1c) and independent variables (child GAD-7 un child PHQ-9) is fully mediated by parent GAD-7. Conclusion: The main result suggests that glycated haemoglobin in adolescents with Type 1 diabetes is related to adolescents’ mental health via parents’ anxiety. It means that parents’ anxiety plays a more significant role in the level of glycated haemoglobin in adolescents than depression and anxiety in the adolescent.

Keywords: type 1 diabetes, adolescents, parental diabetes-specific mental health conditions, glycated haemoglobin, anxiety, depression

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

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Authors: Zhiqiang Zhu, Khalegh Barati, Xuesong Shen

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Due to the energy consumption caused by the construction industry, the public is paying more and more attention to the sustainability of the buildings. With the advancement of research on recycled aggregates, it has become possible to replace natural aggregates with recycled aggregates and to achieve a reduction in energy consumption of materials during construction. The purpose of this paper is to quantitatively compare the emergy consumption of natural aggregate concrete (NAC) and recycled aggregate concrete (RAC). To do so, the emergy analysis method is adopted. Using this technique, it can effectively analyze different forms of energy and substance. The main analysis object is the direct and indirect emergy consumption of the stages in concrete production. Therefore, for indirect energy, consumption of production machinery and transportation vehicle also need to be considered. Finally, the emergy values required to produce the two concrete types are compared to analyze whether the RAC can reduce emergy consumption.

Keywords: sustainable construction, NAC, RAC, emergy, concrete

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines

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Authors: Debalkie Demissie Addisu, Ejigu Alemu Abebe, Tsegay Tensay Assefa

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This study examines the indirect effect of servant leadership on organizational citizenship behavior through perceptions of organizational politics moderated by political skill. This study reports the responses of 321 respondents from six federal public service organizations in Ethiopia. A multi-stage random sampling procedure was employed to select the sampled federal public service organizations. To test hypotheses, the study employed structural equation modeling using AMOS version-26 software. The result revealed that all direct effects have a significant effect. Specifically, servant leadership has a positive effect on organizational citizenship behavior. Likewise, servant leadership has a negative effect on perceptions of organizational politics. Also, a perception of organizational politics has a negative effect on organizational citizenship behavior. Moreover, perceptions of organizational politics competitively mediated the effect of servant leadership on organizational citizenship behavior. As well, political skill moderated the effect of perceptions of organizational politics on organizational citizenship behavior but not the indirect effect. To the best of our knowledge, no one else employs perceptions of organizational politics as a mediating effect between servant leadership and organizational citizenship behavior. Furthermore, we are not aware of anyone else employing political skill as a moderating role in the indirect effect of servant leadership on organizational citizenship behavior through perceptions of organizational politics.

Keywords: servant leadership, organizational citizenship behavior, perceptions of organizational politics, political skill, public service organization, Ethiopia

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Authors: Sevcan Ozturk

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The overall aim of this paper is to present a Kierkegaardian approach to Iqbal’s use of literature as a form of communication. Despite belonging to different historical, cultural, and religious backgrounds, the philosophical approaches of Soren Kierkegaard, ‘the father of existentialism,' and Muhammad Iqbal ‘the spiritual father of Pakistan’ present certain parallels. Both Kierkegaard and Iqbal take human existence as the starting point for their reflections, emphasise the subject of becoming genuine religious personalities, and develop a notion of the self. While doing these they both adopt parallel methods, employ literary techniques and poetical forms, and use their literary works as a form of communication. The problem is that Iqbal does not provide a clear account of his method as Kierkegaard does in his works. As a result, Iqbal’s literary approach appears to be a collection of contradictions. This is mainly because despite he writes most of his works in the poetical form, he condemns all kinds of art including poetry. Moreover, while attacking on Islamic mysticism, he, at the same time, uses classical literary forms, and a number of traditional mystical, poetic symbols. This paper will argue that the contradictions found in Iqbal’s approach are actually a significant part of Iqbal’s way of communicating his reader. It is the contention of this paper that with the help of the parallels between the literary and philosophical theories of Kierkegaard and Iqbal, the application of Kierkegaard’s method to Iqbal’s use of poetry as a communicative act will make it possible to dispel the seeming ambiguities in Iqbal’s literary approach. The application of Kierkegaard’s theory to Iqbal’s literary method will include an analysis of the main principles of Kierkegaard’s own literary technique of ‘indirect communication,' which is a crucial term of his existentialist philosophy. Second, the clash between what Iqbal’s says about art and poetry and what he does will be highlighted in the light of Kierkegaardian theory of indirect communication. It will be argued that Iqbal’s literary technique can be considered as a form of ‘indirect communication,' and that reading his technique in this way helps on dispelling the contradictions in his approach. It is hoped that this paper will cultivate a dialogue between those who work in the fields of comparative philosophy Kierkegaard studies, existentialism, contemporary Islamic thought, Iqbal studies, and literary criticism.

Keywords: comparative philosophy, existentialism, indirect communication, intercultural philosophy, literary communication, Muhammad Iqbal, Soren Kierkegaard

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

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Authors: Mohammad R. Aghakashkooli, Milutin G. Jovanovic

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The brushless doubly-fed reluctance generator (BDFRG) is an emerging, medium-speed alternative to a conventional wound rotor slip-ring doubly-fed induction generator (DFIG) in wind energy conversion systems (WECS). It can provide competitive overall performance and similar low failure rates of a typically 30% rated back-to-back power electronics converter in 2:1 speed ranges but with the following important reliability and cost advantages over DFIG: the maintenance-free operation afforded by its brushless structure, 50% synchronous speed with the same number of rotor poles (allowing the use of a more compact, and more efficient two-stage gearbox instead of a vulnerable three-stage one), and superior grid integration properties including simpler protection for the low voltage ride through compliance of the fractional converter due to the comparatively higher leakage inductances and lower fault currents. Vector controlled pulse-width-modulated converters generally feature a much lower total harmonic distortion relative to hysteresis counterparts with variable switching rates and as such have been a predominant choice for BDFRG (and DFIG) wind turbines. Eliminating a shaft position sensor, which is often required for control implementation in this case, would be desirable to address the associated reliability issues. This fact has largely motivated the recent growing research of sensorless methods and developments of various rotor position and/or speed estimation techniques for this purpose. The main limitation of all the observer-based control approaches for grid-connected wind power applications of the BDFRG reported in the open literature is the requirement for pre-commissioning procedures and prior knowledge of the machine inductances, which are usually difficult to accurately identify by off-line testing. A model reference adaptive system (MRAS) based sensor-less vector control scheme to be presented will overcome this shortcoming. The true machine parameter independence of the proposed field-oriented algorithm, offering robust, inherently decoupled real and reactive power control of the grid-connected winding, is achieved by on-line estimation of the inductance ratio, the underlying rotor angular velocity and position MRAS observer being reliant upon. Such an observer configuration will be more practical to implement and clearly preferable to the existing machine parameter dependent solutions, and especially bearing in mind that with very little modifications it can be adapted for commercial DFIGs with immediately obvious further industrial benefits and prospects of this work. The excellent encoder-less controller performance with maximum power point tracking in the base speed region will be demonstrated by realistic simulation studies using large-scale BDFRG design data and verified by experimental results on a small laboratory prototype of the WECS emulation facility.

Keywords: brushless doubly fed reluctance generator, model reference adaptive system, sensorless vector control, wind energy conversion

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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