Search results for: language learning strategy instruction

Authors: Alicja Zapolnik-Plachetka

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The paper examines the impact of the Members’ of the European Parliament (MEPs) language choice on the linguistic quality of their political discourse as delivered by the interpreters. The study, designed by the author, who is an EU interpreter herself, consisted of three phases. First, a number of speeches of Polish and Spanish MEPs were analyzed to determine whether the incidence of use of certain figures of speech depending on whether the speech had been delivered in English or their respective mother tongue. Then the use of figures of speech was also analyzed based on speeches by some British MEPs, in order to determine what was the incidence for the native users of English. Subsequently, the speeches were compared with their interpretations to find out whether the interpreters managed to convey accurately the means of oratory used by the MEPs. The final result shows that in case of institutional environments dependant on simultaneous interpretation the speakers’ choices can, in fact, influence the linguistic quality of the political communication.

Keywords: content accuracy, European Parliament, political discourse, simultaneous interpreting

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Authors: Bousnane Nour El Houda, Chennaf Ali, Yahia Mouloud, Benbia Souhila

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Male infertility or the inability of a man to procreate is a major public health problem, where it is a leading cause of marital discord in several countries such Algeria. The objective of this work is to study some biological profiles of infertile men from the city of Batna/Algeria and to identify the causes of infertility in a population of infertile males to improve its management and to establish a good therapeutic strategy through a study that lasted 10 months in the Department of Urology of the University Hospital of Banta and on a population of 140 infertile subjects. For every man, series of assessments was performed to determine the exact causes of infertility. We found 102 cases of primary infertility against 38 cases of secondary infertility; the average age of men was 39.7 years, with a predominance of the age group (46-50 years). 34.29% of subjects had genital infections against 17.14% with varicocele. 132 men presented spermiologiques abnormalities; a asthénospermie (AS) in 27.27% of the cases, astheno-terato spermiea (OATS) 11.36% while Azoospermes showed 5.07%. Genital infections are the main causes of infertility (34.29%) of the cases. The results of spermocytogramme showed a predominance of head abnormalities (41.70%), while the flagellum abnormalities presented 33.83%. The dosage of the seminal plasma carnitine showed no pathological cases, which makes it difficult to know their association with infertility. By against some disturbances Fructose and Zinc have been reported.

Keywords: male infertility, spermogramme, spermocytogramme, biological profils

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Authors: Roman Asatryan

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The decision-making processes in Corporate Social Responsibility (CSR) among firms in general and airlines in particular have to do with the benefits that accrue through those investments. The crux of the matter is not whether to invest in CSR or not, but rather, how firms can quantify the benefits derived from such investments. This paper analyzes the cost benefit adjustment strategies for firms in the airline industry in their CSR strategy adoption and implementation. The adjustment strategies identified will enable firms in the airline industry to have a basis for determining the worth of such CSR investments. This paper discusses the cost and benefit analysis model in order to understand the ways airlines can reduce costs and increase returns on CSR, or balance the cost and benefits. The analysis from this study points to the fact that economic concepts especially the CBA are useful, though they are not without challenges. The challenge arises when it is problematic to express the real impact of the externality in monetary terms. The use of rational maximization of the gains may seem to be a rather optimistic goal mainly because of environmental variability, perceptual uncertainty, and imperfect knowledge about the potential externality. This paper concludes that the CBA model gives a basic understanding of the motivations for investing in intangible assets like CSR. Consequently, it sets the tone for formulating relevant hypothesis in empirical studies in investment in CSR in particular and other intangible assets in business operations.

Keywords: cost-benefit analysis, corporate social responsibility, airline industry

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Authors: Aarthy Anandan, Anitha Narasimhan, Madhan Karky

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Word-based games are popular in helping people to improve their vocabulary skills. Games like ‘word search’ and crosswords provide a smart way of increasing vocabulary skills. Word search games are fun to play, but also educational which actually helps to learn a language. Finding the words from word search puzzle helps the player to remember words in an easier way, and it also helps to learn the spellings of words. In this paper, we present a tile distribution algorithm for a Maze-Based Treasure Hunt Game 'Pudhaiyal’ for Tamil words, which describes how words can be distributed horizontally, vertically or diagonally in a 10 x 10 grid. Along with the tile distribution algorithm, we also present an algorithm for the scoring model of the game. The proposed game has been tested with 20,000 Tamil words.

Keywords: Pudhaiyal, Tamil word game, word search, scoring, maze, algorithm

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Authors: Nizar Mansour, Chiha Gaha, Emna Gara

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The present research investigates the relationship among HRM practices, knowledge sharing behavior and a certain number of intermediary variables in the context of Tunisian knowledge-intensive firms. Results suggest that five HR practices influence either directly or indirectly the knowledge sharing behavior through enhancing the value of human capital and fostering a learning-oriented organizational climate. Results have strong theoretical implications for both the fields of knowledge management and strategic human resource management. Managerial implications are also derived.

Keywords: human capital, knowledge intensive firms, knowledge sharing, organizational climate, Tunisia

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Authors: Jacqueline M. Dias, Amina A Khowaja

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Clinical education is one of the most important components of a nursing curriculum as it develops the students’ cognitive, psychomotor and affective skills. Clinical teaching ensures the integration of knowledge into practice. As the numbers of students increase in the field of nursing coupled with the faculty shortage, clinical preceptors are the best choice to ensure student learning in the clinical settings. The clinical preceptor role has been introduced in the undergraduate nursing programme. In Pakistan, this role emerged due to a faculty shortage. Initially, two clinical preceptors were hired. This study will explore clinical preceptors views and experiences of precepting Bachelor of Science in Nursing (BScN) students in an undergraduate program. A case study design was used. As case studies explore a single unit of study such as a person or very small number of subjects; the two clinical preceptors were fundamental to the study and served as a single case. Qualitative data were obtained through an iterative process using in depth interviews and written accounts from reflective journals that were kept by the clinical preceptors. The findings revealed that the clinical preceptors were dedicated to their roles and responsibilities. Another, key finding was that clinical preceptors’ prior knowledge and clinical experience were valuable assets to perform their role effectively. The clinical preceptors found their new role innovative and challenging; it was stressful at the same time. Findings also revealed that in the clinical agencies there were unclear expectations and role ambiguity. Furthermore, clinical preceptors had difficulty integrating theory into practice in the clinical area and they had difficulty in giving feedback to the students. Although this study is localized to one university, generalizations can be drawn from the results. The key findings indicate that the role of a clinical preceptor is demanding and stressful. Clinical preceptors need preparation prior to precepting students on clinicals. Also, institutional support is fundamental for their acceptance. This paper focuses on the views and experiences of clinical preceptors undertaking a newly established role and resonates with the literature. The following recommendations are drawn to strengthen the role of the clinical preceptors: A structured program for clinical preceptors is needed along with mentorship. Clinical preceptors should be provided with formal training in teaching and learning with emphasis on clinical teaching and giving feedback to students. Additionally, for improving integration of theory into practice, clinical modules should be provided ahead of the clinical. In spite of all the challenges, ten more clinical preceptors have been hired as the faculty shortage continues to persist.

Keywords: baccalaureate nursing education, clinical education, clinical preceptors, nursing curriculum

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Authors: Adam Kok Wey Leong

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The comparison between the Western ways of war and Eastern ways of war has raised contemporary debates on the validity of these arguments. The Western way of war is popularly propounded by Victor Davis Hanson as originating from the Greek hoplite tactics, direct military maneuvers, democratic principles and social freedom and cohesion that has continued to yield military success for the Western powers for centuries. On the other hand, the Eastern way of war has been deemed as relying on indirect tactics, deception, and ruses. This often accepted notion of the divide between Western and Eastern style does not sustain in view of the available classical strategic texts from both sides from the same period that has proposed similar principles of warfare. This paper analyses the similarities between classical strategic texts on war from the Eastern perspective namely Sun Tzu’s Art of War with a similar temporal strategic text from the West which is Sextus Iuluis Frontinus’s Stratagematon, and deduces answers to this core research question - Does the hypothesis of the existence of distinctive Western and Eastern ways of warfare stands? The main thesis advanced by this research is that ways of warfare share universal principles, and it transcends cultural and spatial boundaries. Warfare is a human endeavour, and the same moral actions guide humans from different geo-cultural spheres in warfare’s objectives, which are winning over an enemy in the most economical way and serve as a mean to an end.

Keywords: ways of warfare, strategic culture, strategy, Sun Tzu, frontinus

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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Authors: Changchun Liang, Xiaodong Zhang, Xin Liu, Pengfei Sun

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Space intelligent robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the tracking and capturing technology, becomes research hot in recent years. In this paper, the authors propose a vision servo control system for target capturing. Robotic manipulator will be an intelligent robotic system with large-scale movement, functional agility, and autonomous ability, and it can be operated by astronauts in the space station or be controlled by the ground operator in the remote operation mode. To realize the autonomous movement and capture mission of SRM, a kind of autonomous programming strategy based on multi-camera vision fusion is designed and the selection principle of object visual position and orientation measurement information is defined for the better precision. Distributed control system hierarchy is designed and reliability is considering to guarantee the abilities of control system. At last, a ground experiment system is set up based on the concept of robotic control system. With that, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm, and demonstrates that the control system can fulfill the needs of function, real-time and reliability.

Keywords: control system, on-orbital service, space robot, vision servo

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Authors: Dilin Chen, Kang Luo, Jian Wu, Chun Yang, Hongliang Yi

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Electrically driven flows (EDF) systems play an important role in fuel cells, electrochemistry, bioseparation technology, fluid pumping, and microswimmers. The core scientific problem is multifield coupling, the further development of which depends on the exploration of nonlinear instabilities, force competing mechanisms, and energy budgets. In our study, two categories of electrostatic force-dominated phenomena, induced charge electrosmosis (ICEO) and ion conduction pumping are investigated while considering polymer rheological characteristics and heat gradients. With finite volume methods, the thermal modulation strategy of ICEO under the thermal buoyancy force is numerically analyzed, and the electroelastic instability turn associated with polymer addition is extended. The results reveal that the thermal buoyancy forces are sufficient to create typical thermogravitational convection in competition with electroconvective modes. Electroelastic instability tends to be promoted by weak electrical forces, and polymers effectively alter the unstable transition routes. Our letter paves the way for improved mixing and heat transmission in microdevices, as well as insights into the non-Newtonian nature of electrohydrodynamic dynamics.

Keywords: non-Newtonian fluid, electroosmotic flow, electrohydrodynamic, viscoelastic liquids, heat transfer

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Authors: Hongmeng Su, Luyu Zhao, Yanyan Qian, Hong Fan

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Aim: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors that endanger human health seriously. RNA methylation, especially N6-methyladenosine (m⁶A) and 5-methylcytosine (m⁵C), a crucial epigenetic transcriptional regulatory mechanism, plays an important role in tumorigenesis, progression and prognosis. This research aims to systematically evaluate the prognostic value of m⁶A and m⁵C modulators in HCC patients. Methods: Twenty-four modulators of m⁶A and m⁵C were candidates to analyze their expression level and their contribution to predict the prognosis of HCC. Consensus clustering analysis was applied to classify HCC patients. Cox and LASSO regression were used to construct the risk model. According to the risk score, HCC patients were divided into high-risk and low/medium-risk groups. The clinical pathology factors of HCC patients were analyzed by univariate and multivariate Cox regression analysis. Results: The HCC patients were classified into 2 clusters with significant differences in overall survival and clinical characteristics. Nine-gene risk model was constructed including METTL3, VIRMA, YTHDF1, YTHDF2, NOP2, NSUN4, NSUN5, DNMT3A and ALYREF. It was indicated that the risk score could serve as an independent prognostic factor for patients with HCC. Conclusion: This study constructed a Nine-gene risk model by modulators of m⁶A and m⁵C and investigated its effect on the clinical prognosis of HCC. This model may provide important consideration for the therapeutic strategy and prognosis evaluation analysis of patients with HCC.

Keywords: hepatocellular carcinoma, m⁶A, m⁵C, prognosis, RNA methylation

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Authors: Zan Azma Nasruddin, Irwan Mazlin, Nor Aziah Daud, Fauziah Redzuan, Fariza Hanis Abdul Razak

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This paper focuses on a machine learning that learn the correct pronunciation of Makhraj Huroofs. Usually, people need to find an expert to pronounce the Huroof accurately. In this study, the researchers have developed a system that is able to learn the selected Huroofs which are ha, tsa, zho, and dza using the Convolutional Neural Network. The researchers present the chosen type of the CNN architecture to make the system that is able to learn the data (Huroofs) as quick as possible and produces high accuracy during the prediction. The researchers have experimented the system to measure the accuracy and the cross entropy in the training process.

Keywords: convolutional neural network, Makhraj recognition, speech recognition, signal processing, tensorflow

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Authors: Elifcan Oztekin

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Compliment response strategies in cross-linguistic contexts have received a considerable amount of interest in sociolinguistic research in various language settings. In this respect, a common finding of these studies indicates that speakers of different languages employ different patterns in strategies to respond to compliments. This has triggered varying theoretical approaches to compliment responses within theories of politeness and the universality of speech acts. In the light of previous studies, the present study investigates compliment response strategies that Turkish-English bilingual university students use in English and Turkish response conditions through a cross-linguistic discourse completion task and interviews. Data were analyzed using Holmes’ (1988) taxonomy and the results indicate a similar pattern to what has been observed in Turkish compliments responses in previous research. Turkish-English comparisons also display noticeable similarities in macro-level strategies, while subtle differences in micro-level strategies were also observed.

Keywords: compliment response strategies, cross-cultural differences, bilingualism, sociolinguistics

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Authors: Samira Mahmoudkelayeh, Katayoun Taghizade, Mitra Pourvaziri, Elnaz Asadian

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Over the recent decades, depletion of resources and environmental concerns made researchers and practitioners present sustainable approaches. Since construction process consumes a great deal of both renewable and non-renewable resources, it is of great significance regarding environmental impacts. Choosing sustainable construction materials is a remarkable strategy presented in many researches and has a significant effect on building’s environmental footprint. This paper represents an assessment framework for selecting best sustainable materials for exterior enclosure in the city of Tehran based on sustainability principles (eco-friendly, cost effective and socio-cultural viable solutions). To perform a comprehensive analysis of environmental impacts, life cycle assessment, a cradle to grave approach is used. A questionnaire survey of construction experts has been conducted to determine the relative importance of criteria. Analytic Network Process (ANP) is applied as a multi-criteria decision-making method to choose sustainable material which consider interdependencies of criteria and sub-criteria. Finally, it prioritizes and aggregates relevant criteria into ultimate assessed score.

Keywords: sustainable materials, building, analytic network process, life cycle assessment

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Authors: Abdel Rahman Altakhaineh, Mohamma Alaghawat, Hiba Alhendi

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This paper reports an investigation of the comprehension of English compound nouns by sixty Arabic-speaking English Foreign Language (EFL) learners majoring in English at the University of Jordan, Amman. The investigation focused on the problems that these learners may encounter in understanding certain types of compounds and their ability to use their L1 compound noun knowledge to produce the meaning of L2 compound nouns. Participants whose English proficiency level was advanced underwent a test to identify the meaning ofan underlined compound without using a dictionary. Theresponses to the three different types of compounds were analyzed usingTwo-Way repeated measures ANOVA, and the results showed that there were different endocentric and exocentric compound responses within subordinative compounds, with a statistically significant difference between the two in favor of endocentric compounds. We argue that the endocentric, especially subordinative endocentric compounds,weremore easily understood due to its representative nature, i.e., because the head represents the meaning of the whole compound. The study concludes with pedagogical implications for teaching compound nouns.

Keywords: morphology, compounding, SLA, arabic-speaking EFL learners

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Authors: Osiris Terry, Kenneth Hopkinson, Laura Humphrey

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Systematic resampling is the most popularly used resampling method in particle filters. This paper seeks to further the understanding of systematic resampling by defining a formula made up of variables from the sampling equation and the particle weights. The formula is then verified via SPARK, a software verification language. The verified systematic resampling formula states that the minimum/maximum number of possible samples taken of a particle is equal to the floor/ceiling value of particle weight divided by the sampling interval, respectively. This allows for the creation of a randomness spectrum that each resampling method can fall within. Methods on the lower end, e.g., systematic resampling, have less randomness and, thus, are quicker to reach an estimate. Although lower randomness allows for error by having a larger bias towards the size of the weight, having this bias creates vulnerabilities to the noise in the environment, e.g., jamming. Conclusively, this is the first step in characterizing each resampling method. This will allow target-tracking engineers to pick the best resampling method for their environment instead of choosing the most popularly used one.

Keywords: SPARK, software verification, resampling, systematic resampling, particle filter, tracking

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Authors: Liping Li, Wenan Tan, Na Wang

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With the rapid development of information technology, project management has gained more and more attention recently. Based on CDIO, this paper proposes some teaching reform ideas for software project management curriculum. We first change from Teacher-centered classroom to Student-centered and adopt project-driven, scenario animation show, teaching rhythms, case study and team work practice to improve students' learning enthusiasm. Results showed these attempts have been well received and very effective; as well, students prefer to learn with this curriculum more than before the reform.

Keywords: CDIO, teaching reform, engineering education, project-driven, scenario animation simulation

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Authors: Ladan Surajo

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Nigeria as a third world country is full of people who cannot read and write, thereby constituting a stumbling block to the modern way of communication. It is a well known fact that Nigeria is a heterogeneous country with an estimated 450 or more ethnic groups communicating in divergent languages. Despite this scenario, English, Hausa, Igbo and Yoruba languages are predominantly used in the country. Apart from English language, Hausa has a wider coverage of usage among the indigenous languages in Nigeria, thereby using it in the area of social mobilization and conflict management cannot be overemphasized. Hausa Oral Singers are depicting their artistic and God endowed talents through singing to mobilize and sensitize the local communities about government programmes and the ills of other social problems of the society. It is the belief of this researcher that if used properly, the Hausa Oral Singers will assist immensely in reducing to the barest minimum some social ills of the society in Nigeria. More so that music is the food of the heart and has a resounding impact in changing the behaviour of individuals and groups.

Keywords: oral, singers, praise, social mobilization, conflict management

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Authors: Deepa Idnani

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Attendance is an important factor in school success among children. Studies show that better attendance is related to higher academic achievement for students of all backgrounds, but particularly for children with lower socio-economic status. Beginning from the early years, students who attend school regularly score higher on tests than their peers who are frequently absent. The present study in different types of School In Delhi tries to highlight the impact of student absenteeism and the challenges it poses for the students. The study relies on Lewin ‘Model of Exclusion’ and tries to focus on the analysis of children with special needs and the inclusion and exclusion of students in the school.

Keywords: student absenteeism, pedagogy, learning, right to education act, exclusion

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Authors: Ericson O. Alieto, Aprillete C. Devanadera

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The main objective of the study is to determine the dominant speech acts in five commemorative speeches of President Duterte. This study employed Speech Act Theory and Discourse analysis to determine how the speech acts features connote the pragmatic meaning of Duterte’s speeches. Identifying the speech acts is significant in elucidating the underlying message or the pragmatic meaning of the speeches. From the 713 sentences or utterances from the speeches, assertive with 208 occurrences from the corpus or 29% is the dominant speech acts. It was followed by expressive with 177 or 25% occurrences, directive accounts for 152 or 15% occurrences. While commisive accounts for 104 or 15% occurrences and declarative got the lowest percentage of occurrences with 72 or 10% only. These sentences when uttered by Duterte carry a certain power of language to move or influence people. Thus, the present study shows the fundamental message perceived by the listeners. Moreover, the frequent use of assertive and expressive not only explains the pragmatic message of the speeches but also reflects the personality of President Duterte.

Keywords: commemorative speech, discourse analysis, duterte, pragmatics

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Authors: Guezouli Larbi, Belkacem Soundes

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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

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Authors: Long Xumeng

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Place attachment focuses on the emotions and practices between people and their environment, and the influencing factors of place attachment vary depending on the nature of the place. As an important carrier of public slow-moving activities and urban culture, the feelings, cognition, and behaviors of the subjects involved in the use of mountain city trails have become the focus of research in this field. This paper will take Daijiaxiang Cliff Walkway in Yuzhong District, Chongqing City, as an example and analyze the evaluation results and correlation of each factor through questionnaire survey and field observation, using the three scales of Recreational Experience Scale, Satisfaction Scale, and Place Attachment Scale, as well as the intensity of activity, by using SPSS software. The study shows that there is a significant difference between the demographic variables of users' identity and age and the formation of place attachment; the degree of place attachment is significantly positively correlated with the emotion, industry, and service quality of recreational experience; and the recreational experience of the Mountain City Trail is significantly positively correlated with the overall satisfaction. By analyzing the influencing factors of recreational experience, satisfaction and place attachment, the corresponding conclusions and enhancement strategies were drawn to provide references for the renewal and construction of mountain city trails.

Keywords: mountain city trail, place attachment, recreational experience, satisfaction, urban renewal

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Authors: Kazuhisa Takagi

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This paper is about movies and dynamic objects for mobile phones. Dynamic objects are the software programmed by JavaScript. They consist of geometric figures and work on HTML5-compliant browsers. Mobile phones are very popular among teenagers. They like watching movies and playing games on them. So, mathematics movies and dynamic objects would enhance teaching and learning processes. In the movies, manga characters speak with artificially synchronized voices. They teach trigonometry together with dynamic mathematical objects. Many movies are created. They are Windows Media files or MP4 movies. These movies and dynamic objects are not only used in the classroom but also distributed to students. By watching movies, students can study trigonometry before or after class.

Keywords: dynamic mathematical object, javascript, google drive, transfer jet

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Authors: Ben-Caleb Egbide, Iyoha Francis, Egharevba Mathew, Oduntan Emmanuel

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The prosperity of any nation is determined not just by the availability of resources, but also by the discipline exercised in the management of those resources. This paper examines the functional association between adherence to budgetary estimates or budget discipline (BDISC) and national prosperity proxied by Real Gross Domestic Product (RGDP) and Relative Poverty Index (RPI)/Human Development Index (HDI). Adopting a longitudinal retrospective research strategy, time series data relating to both the endogenous and exogenous variables were extracted from official government publications for 36 years’ (1980-2015 in the case of RGDP and RPI), and for 26 years (1990-2015 in the case of HDI). Ordinary Least Square (OLS), as well as cointegration regressions, were employed to gauge both the short term and long term impact of BDISC on RPI/HDI and RGDP. The results indicated that BDISC is directly related with RGDP but indirectly related with RPI. The implication is that while adherence to budgetary estimate can enhance economic growth, it has the capacity to slow down the rate of poverty in the long run. The paper, therefore, recommend stricter adherence to budgets as a way out of economic under performance in Nigeria and engender the process of promoting human development and national prosperity.

Keywords: budget discipline, human development index, national prosperity, Nigeria

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Authors: Masoud Sheidaei, Melica Tabasi, Fahimeh Koohdar, Mona Sheidaei

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Juglans regia L. is an economically important species of edible nuts. Iran is known as a center of origin of genetically rich walnut germplasm and expected to be found a large diversity within Iranian walnut populations. A detailed population genetic of local populations is useful for developing an optimal strategy for in situ conservation and can assist the breeders in crop improvement programs. Different phylogenetic studies have been carried out in this genus, but none has been concerned with genetic changes associated with geographical divergence and the identification of adaptive SNPs. Therefore, we carried out the present study to identify discriminating ITS nucleotides among Juglans species and also reveal association between ITS SNPs and geographical variables. We used different computations approaches like DAPC, CCA, and RDA analyses for the above-mentioned tasks. We also performed population genetics analyses for population effective size changes associated with the species expansion. The results obtained suggest that latitudinal distribution has a more profound effect on the species genetic changes. Similarly, multiple analytical approaches utilized for the identification of both discriminating DNA nucleotides/ SNPs almost produced congruent results. The SNPs with different phylogenetic importance were also identified by using a parsimony approach.

Keywords: Persian walnut, adaptive SNPs, data analyses, genetic diversity

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Authors: F. Haddadj, F. Acheuk, S. Hamdi, S. Zenia, A. Smai, H. Saadi, B. Doumandji-Mitiche

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Locust is causing significant losses in agricultural production in the countries concerned by the invasion. Up to the present control strategy has consisted only of the spreaders chemicals; they have proven harmful to the environment and. For this, a new control method appeared it comes to the biological control based mostly by using microorganism. It is in that sense is we've made our contribution by the use of a biopesticide which is entomopathogenic fungus Metarhizium anisopliae var acridium "Green Muscle" on part of the cuticule the larval of fifth instar locust Schistocerca gregaria (Forskål, 1775). Preliminary test on the study of the pathogenicity of M. anisopliae var acridium biocontrol agent, was conducted in the laboratory on L5 S. gregaria, on which we inoculated treatment in the digestive tract and it administrant 20μl of entomopathogenic solution orally at a dose DL50 = 3.25 x107 sp./ ml (median lethal dose estimated at earlier), 5 days after treatment individuals are sacrificed. After dissection cuticles are recovered and then subjected to histological sections. The histological technique followed is that of Martoja Martoja-Pierson (1967). Microscopic observation revealed alterations in the architecture of the cuticule which leads to disorganization of cell layers.

Keywords: biopesticide, cuticle, desert locust, toxicity

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Authors: Jungho Moon, Lae-Jeong Park

Abstract:

This paper introduces a signal monitoring program developed with a view to helping electrical engineering students get familiar with sensors with digital output. Because the output of digital sensors cannot be simply monitored by a measuring instrument such as an oscilloscope, students tend to have a hard time dealing with digital sensors. The monitoring program runs on a PC and communicates with an MCU that reads the output of digital sensors via an asynchronous communication interface. Receiving the sensor data from the MCU, the monitoring program shows time and/or frequency domain plots of the data in real time. In addition, the monitoring program provides a serial terminal that enables the user to exchange text information with the MCU while the received data is plotted. The user can easily observe the output of digital sensors and configure the digital sensors in real time, which helps students who do not have enough experiences with digital sensors. Though the monitoring program was programmed in the Matlab programming language, it runs without the Matlab since it was compiled as a standalone executable.

Keywords: digital sensor, MATLAB, MCU, signal monitoring program

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Authors: Maria Korman, Carmit Gal, Ella Gabitov, Avi Karni

Abstract:

The main question addressed in this study was whether the time-of-day wherein training is afforded is a significant factor for motor skill ('how-to', procedural knowledge) acquisition and consolidation into long term memory in the healthy elderly population. Twenty-nine older adults (60-75 years) practiced an explicitly instructed 5-element key-press sequence by repeatedly generating the sequence ‘as fast and accurately as possible’. Contribution of three parameters to acquisition, 24h post-training consolidation, and 1-week retention gains in motor sequence speed was assessed: (a) time of training (morning vs. evening group) (b) sleep quality (actigraphy) and (c) chronotype. All study participants were moderately morning type, according to the Morningness-Eveningness Questionnaire score. All participants had sleep patterns typical of age, with average sleep efficiency of ~ 82%, and approximately 6 hours of sleep. Speed of motor sequence performance in both groups improved to a similar extent during training session. Nevertheless, evening group expressed small but significant overnight consolidation phase gains, while morning group showed only maintenance of performance level attained at the end of training. By 1-week retention test, both groups showed similar performance levels with no significant gains or losses with respect to 24h test. Changes in the tapping patterns at 24h and 1-week post-training were assessed based on normalized Pearson correlation coefficients using the Fisher’s z-transformation in reference to the tapping pattern attained at the end of the training. Significant differences between the groups were found: the evening group showed larger changes in tapping patterns across the consolidation and retention windows. Our results show that morning-oriented older adults effectively acquired, consolidated, and maintained a new sequence of finger movements, following both morning and evening practice sessions. However, time-of-training affected the time-course of skill evolution in terms of performance speed, as well as the re-organization of tapping patterns during the consolidation period. These results are in line with the notion that motor training preceding a sleep interval may be beneficial for the long-term memory in the elderly. Evening training should be considered an appropriate time window for motor skill learning in older adults, even in individuals with morning chronotype.

Keywords: time-of-day, elderly, motor learning, memory consolidation, chronotype

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

Abstract:

Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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