Search results for: open and distant learning programme

Authors: Rodrigo Coelho

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We believe that in the majority of the “recent production of public space", the overvaluation of the "image", of the "ephemeral" and of the "objectual", has come to determine the configuration of banal and (more or less) arbitrary "public spaces", mostly linked to a problem of “outdoor decoration”, reflecting a clear sign of uncertainty and arbitrariness about the meaning, the role and shape of public space and public art.This "inconsistency" which is essentially linked to the loss of urban, but also social, cultural and political, vocation of the disciplines that “shape” the urban space (but is also linked to the lack of urban and technical culture of techinicians and policy makers) converted a significant set of the recently built "public space" and “urban art” into diffuse and multi-referenced pieces, which generally shares the inability of confering to the urban space, civic, aesthetic, social and symbolic meanings. In this sense we consider it is essential to undertake a theoretical reflection on the values, the meaning(s) and the shape(s) that open space, and urban art may (or must) take in the current urban and cultural context, in order to redeem for public space its status of significant physical reference, able to embody a spatial and urban identity, and simultaneously enable the collective accession and appropriation of public space. Taking as reference public space interventions built in the last decade on the European context, we will seek to explore and defend the need of considering public space as a true place of exception, an exceptional support where the emphasis is placed on the quality of the experience, especially by the relations public space/urban art can established with the city, with nature and geography in a broad sense, referring us back to a close and inseparable and timeless relationship between nature and culture.

Keywords: art, city, nature, public space

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Authors: Mei Lin, Chang Liu

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Argumentative writing is the most prevalent genre in diverse writing tests. How to construct academic arguments is often regarded as a difficult task by most English as a foreign language (EFL) learners. A failure to generate enough ideas and organise them coherently and logically as well as a lack of competence in supporting their arguments with relevant evidence are frequent problems faced by EFL learners when approaching an English argumentative writing task. Overall, these problems are closely related to planning, and planning an argumentative writing at pre-writing stage plays a vital role in a good academic essay. However, how teachers can effectively guide students to generate ideas is rarely discussed in planning English argumentative writing, apart from brainstorming. Brainstorming has been a common practice used by teachers to help students generate ideas. However, some limitations of brainstorming suggest that it can help students generate many ideas, but ideas might not necessarily be coherent and logic, and could sometimes impede production. It calls for a need to explore effective instructional strategies at pre-writing stage of English argumentative writing. This paper will first examine how a Six Thinking Hats approach can be used to provide a dialogic space for EFL learners to experience and collaboratively generate ideas from multiple perspectives at pre-writing stage. Part of the findings of the impact of a twelve-week intervention (from March to July 2021) on students learning to generate ideas through engaging in group discussions of using Six Thinking Hats will then be reported. The research design is based on the sociocultural theory. The findings present evidence from a mixed-methods approach and fifty-nine participants from two first-year undergraduate natural classes in a Chinese university. Analysis of pre- and post- questionnaires suggests that participants had a positive attitude toward the Six Thinking Hats approach. It fosters their understanding of prewriting and argumentative writing, helps them to generate more ideas not only from multiple perspectives but also in a systematic way. A comparison of participants writing plans confirms an improvement in generating counterarguments and rebuttals to support their arguments. Above all, visual and transcripts data of group discussion collected from different weeks throughout the intervention enable teachers and researchers to ‘see’ the hidden process of learning to generate ideas in action.

Keywords: argumentative writing, innovative pedagogy, six thinking hats, dialogic space, prewriting, higher education

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Authors: Ghidey Ghebreyohanes, Eltahir Awad Gasim Khalil, Zemenfes Tsighe, Faiza Ali

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Background: reproductive health (RH) is a state of physical, mental and social well-being in all matters relating to the reproductive system at all stages of life. In East Africa including Eritrea, adolescents comprise more than a quarter of the population. The region holds the highest rates of sexually transmitted diseases, HIV, unwanted pregnancy and unsafe abortion with its complications. Young girls carry the highest burden of reproductive health problems due to their risk taking behavior, lack of knowledge, peer pressure, physiologic immaturity and low socioeconomic status. Design: this was a Community-based, randomized, case-controlled and pre-test-post-test intervention study. Setting: Zoba Debub was randomly selected out of the six zobas in Eritrea. The four high schools out of the 26 in Zoba Debub were randomly selected as study target schools. Over three quarter of the people live on farming. The target population was female students attending grade nine with majority of these girls live in the distant villages and walk to school. The study participants were randomly selected (n=165) from each school. Furthermore, the 1 intervention and 3 controls for the study arms were assigned randomly. Objectives: this study aimed to assess the effectiveness of peer reproductive health education in improving knowledge, attitude, and health service use of high school adolescent girls in Eritrea Methods: the protocol was reviewed and approved by the Scientific and Ethics Committees of Faculty of Nursing Sciences, University of Khartoum. Data was collected using pre-designed and pretested questionnaire emphasizing on reproductive health knowledge, attitude and practice. Sample size was calculated using proportion formula (α 0.01; power of 95%). Measures used were scores and proportions. Descriptive and inferential statistics, t-test and chi square at (α .01), 99% confidence interval were used to compare changes of pre and post-intervention scores using SPSS soft ware. Seventeen students were selected for peer educators by the school principals and other teachers based on inclusion criteria that include: good academic performance and acceptable behavior. One peer educator educated one group composed of 8-10 students for two months. One faculty member was selected to supervise peer educators. The principal investigator conducted the training of trainers and provided supervision and discussion to peer educators every two weeks until the end of intervention. Results: following informed consent, 627 students [164 in intervention and 463 in the control group] with a ratio of 1 to 3, were enrolled in the study. The mean age for the total study population was 15.4±1.0 years. The intervention group mean age was 15.3±1.0 year; while the control group had a mean age of 15.4±1.0. The mean ages for the study arms were similar (p= 0.4). The majority (96 %) of the study participants are from Tigrigna ethnic group. Reproductive knowledge scores which was calculated out of a total 61 grade points: intervention group (pretest 6.7 %, post-test 33.6 %; p= 0.0001); control group (pretest 7.3 %, posttest 7.3 %, p= 0.92). Proportion difference in attitude calculated out of 100%: intervention group (pretest 42.3 % post test 54.7% p= 0.001); controls group (pretest 45%, post test 44.8 p= 0.7). Proportion difference in Practice calculated out of 100 %: intervention group (pretest 15.4%, post test 80.4 % p= 0.0001); control group (pretest 16.8%, posttest 16.9 % p= 0.8). Mothers were quoted as major (> 90 %) source of reproductive health information. All focus group discussants and most of survey participants agreed on the urgent need of reproductive health information and services for adolescent girls. Conclusion: reproductive health knowledge and use of facilities is poor among adolescent girls in sub-urban Eretria. School-based peer reproductive health education is effective and is the best strategy to improve reproductive health knowledge and attitudes.

Keywords: reproductive health, adolescent girls, eretria, health education

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Authors: Wafa' Slaibi Alsharafat

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Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.

Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection

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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: 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: Yongsheng Guo, Shuchao Li

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This study explores Chinese foreign direct investment (FDI) in Europe and the cross-cultural cooperation between Chinese and European managers. The aim of this research is to shed light on the phenomenon of investments in developed countries from an emerging market and to gain insights into the cooperation process. A grounded theory approach is adopted, and 46 semi-structured interviews were conducted with 10 case companies in Germany and 13 case companies in the UK. Grounded theory models are developed from primary data and interview quotes are used to support the themes. The interviewees perceived differences between the two parties in cultural traits, management concepts, knowledge structure and resource endowment between the two parties. Chinese and European partners can take advantage of different resources and cooperate in innovative ways to improve corporate performance. Moreover, both parties appreciate different ethical and cultural characteristics and complement each other to develop a combined organizational culture. This study proposes an ethical and cultural diversity theory in international management arguing that a team with diversified values and behaviors may be more excited and motivated. This study suggests that “resource complement” and “cross-cultural cooperation” might be an advantage for international investment. Firms are encouraged to open their minds and cooperate with partners with different resources and cultures. The authorities may review the FDI policies to reduce social and political barriers.

Keywords: cross-culture, FDI, cooperation, innovation, China, Europe

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Authors: Ahmed Boutejdar, Bishoy I. Halim, Soumia El Hani, Larbi Bellarbi, Amal Afyf

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In this paper, a planar monopole antenna for multi band applications is proposed. The antenna structure operates at three operating frequencies at 3.7, 6.2, and 13.5 GHz which cover different communication frequency ranges. The antenna consists of a quasi-modified rectangular radiating patch with a partial ground plane and two parasitic elements (open-loop-ring resonators) to serve as coupling-bridges. A stepped cut at lower corners of the radiating patch and the partial ground plane are used, to achieve the multiband features. The proposed antenna is manufactured on the FR4 substrate and is simulated and optimized using High Frequency Simulation System (HFSS). The antenna topology possesses an area of 30.5 x 30 x 1.6 mm³. The measured results demonstrate that the candidate antenna has impedance bandwidths for 10 dB return loss and operates from 3.80 – 3.90 GHz, 4.10 – 5.20 GHz, 11.2 – 11.5 GHz and from 12.5 – 14.0 GHz, which meet the requirements of the wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX), C- (Uplink) and Ku- (Uplink) band applications. Acceptable agreement is obtained between measurement and simulation results. Experimental results show that the antenna is successfully simulated and measured, and the tri-band antenna can be achieved by adjusting the lengths of the three elements and it gives good gains across all the operation bands.

Keywords: planar monopole antenna, FR4 substrate, HFSS, WLAN, WiMAX, C and Ku

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Authors: Taju Mohammednur, Tesfaye Megersa, Karta Kaske, Tekeste Kifle

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Coffee is economically important in Ethiopia. However, the conditions under which coffee seeds are dried and processed significantly affect the seedling quality and productivity. The objective of this study was to evaluate the effect of pre-sowing treatments and drying methods on the physiological quality of coffee seeds and seedlings. The study was conducted at the Jimma Agricultural Research Center seed laboratory and nursery site. Two coffee varieties, 74110 and 75227, were used. Fully ripe red cherries were harvested, and the seeds were dried under two conditions: a shade drying room and direct open sun. Pre-sowing seed soaking treatments of 6, 8, 18, and 24 hours, including a control, were applied. A factorial design in a Complete Randomized Design was used. The highest germination percentage (91.48%), emergence rate (90.19%), and seedling vigor index (2236.30) were recorded for seeds dried in the shade drying room. In contrast, the lowest values (70.47%, 68.36%, and 1378.22, respectively) were observed for seeds dried in direct sunlight. There was a significant difference in seed germination based on soaking time, with the highest germination percentage (83.25%) recorded for seeds soaked for 6 hours, followed by 24 hours (83.13%), while the lowest (76.88%) was recorded for un-soaked seeds. The results indicated that drying seeds under shade is better for seed quality. Moreover, further investigation into seed treatment methods and preservation techniques is necessary to improve coffee seed quality.

Keywords: coffee, seed drying, germination, seed, seed longevity, seed priming

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Authors: Shakila Singh

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This research was conducted at a selected South African university campus with women students who drink alcohol. The purpose of the study was to examine their perspectives on the role of alcohol in their lives, their understandings about women’s vulnerability to alcohol-related sexual risk and their strategies against these. The study draws on feminist principles and practices to challenge gendered inequalities that legitimate and facilitate violence against women. Recognising the danger of focusing on risk management in ways that place the burden of responsibility entirely on young women to prevent their violation, this article focuses on women students’ agency in managing risk while taking up opportunities for self-discovery. Participation was voluntary, and a student-researcher administered an open-ended questionnaire to 55 participants. The findings suggest that young women position alcohol- use as a common activity at university, and that it gives them much pleasure. They recognise that it is riskier for women and articulate valuable strategies to manage the risk to their sexual safety when drinking. These include drinking within supportive networks, avoiding financial dependence, and managing their alcohol intake. This article argues that alcohol at university is an integral part of expressions of gender and sexuality and that risk-taking is a normal part of university students’ lives. Consequently, arguments about equality need to consider risk-taking as part of young people’s lives and promote ways of managing alcohol-related risks, rather than imagining that alcohol can be avoided entirely.

Keywords: alcohol-related sexual risk, drinking at university, managing risk, women students

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Authors: Arunava Chakrabarti

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A one-dimensional chain of magnetic atoms, representative of a quantum gas in an artificial quasi-periodic potential and modeled by the well-known Aubry-Andre function and its variants are studied in respect of its capability of working as a spin filter for arbitrary spins. The basic formulation is explained in terms of a perfectly periodic chain first, where it is shown that a definite correlation between the spin S of the incoming particles and the magnetic moment h of the substrate atoms can open up a gap in the energy spectrum. This is crucial for a spin filtering action. The simple one-dimensional chain is shown to be equivalent to a 2S+1 strand ladder network. This equivalence is exploited to work out the condition for the opening of gaps. The formulation is then applied for a one-dimensional chain with quasi-periodic variation in the site potentials, the magnetic moments and their orientations following an Aubry-Andre modulation and its variants. In addition, we show that a certain correlation between the system parameters can generate absolutely continuous bands in such systems populated by Bloch like extended wave functions only, signaling the possibility of a metal-insulator transition. This is a case of correlated disorder (a deterministic one), and the results provide a non-trivial variation to the famous Anderson localization problem. We have worked within a tight binding formalism and have presented explicit results for the spin half, spin one, three halves and spin five half particles incident on the magnetic chain to explain our scheme and the central results.

Keywords: Aubry-Andre model, correlated disorder, localization, spin filter

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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: D. Kabeya Nahum, L. Y. Kabeya Mukeba

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In this work, the design of surface defects some support of the anchor rod ball joint. The future adhesion contact was rocking in manufacture machining, for giving by the numerical analysis of a short simple solution of thermo-mechanical coupled problem in process engineering. The analysis of geometrical evaluation and the quasi-static and dynamic states are discussed in kinematic dimensional tolerances onto surfaces of part. Geometric modeling using the finite element method (FEM) in rough part of such phase provides an opportunity to solve the nonlinearity behavior observed by empirical data to improve the discrete functional surfaces. The open question here is to obtain spherical geometry of drain wear with the operation of rolling. The formulation with (1 ± 0.01) mm thickness near the drain wear semi-finishing tool for studying different angles, do not help the professional factor in design cutting metal related vibration, friction and interface solid-solid of part and tool during this physical complex process, with multi-parameters no-defined in Sobolev Spaces. The stochastic approach of cracking, wear and fretting due to the cutting forces face boundary layers small dimensions thickness of the workpiece and the tool in the machining position is predicted neighbor to ‘Yakam Matrix’.

Keywords: FEM, geometry, part, simulation, spherical surface engineering, tool, workpiece

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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: Ayoub Moufid, Najib Bennis, Soumia El Hani

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The objective of greenhouse climate control is to improve the culture development and to minimize the production costs. A greenhouse is an open system to external environment and the challenge is to regulate the internal climate despite the strong meteorological disturbances. The internal state of greenhouse considered in this work is defined by too relevant and coupled variables, namely inside temperature and hygrometry. These two variables are chosen to describe the internal state of greenhouses due to their importance in the development of plants and their sensitivity to external climatic conditions, sources of weather disturbances. A multivariable model is proposed and validated by considering a greenhouse as black-box system and the least square method is applied to parameters identification basing on collected experimental measures. To regulate the internal climate, we propose a Model Predictive Control (MPC) scheme. This one considers the measured meteorological disturbances and the physical and operational constraints on the control and state variables. A successful feasibility study of the proposed controller is presented, and simulation results show good performances despite the high interaction between internal and external variables and the strong external meteorological disturbances. The inside temperature and hygrometry are tracking nearly the desired trajectories. A comparison study with an On/Off control applied to the same greenhouse confirms the efficiency of the MPC approach to inside climate control.

Keywords: climate control, constraints, identification, greenhouse, model predictive control, optimization

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Authors: Aprajita Singh, Anamika Tripathi, Surya P. Dwivedi

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Moradabad is a small town in the Northern area of Uttar Pradesh, India. It is situated on the bank of river Ramganga which is also known as ‘Brass City of India’. There is eventually increase in the environmental pollution due to uncontrolled and inappropriate e-waste burning (recycling) activities which have been reported in many areas of Moradabad. In this paper, analysis of toxic heavy metals, causing pollution to the surrounding environment released from the e-waste burning and much other recycling process. All major e-waste burning sites are situated on the banks of the river which is burned in open environmental conditions. Soil samples were collected from seven (n=3) different sites including control site, after digestion of soil samples using triacid mixture, analysis of different toxic metals (Pb, Ar, Hg, Cd, Cr, Cu, Zn, Fe, and Ni) has been carried out with the help of instrument ICP-AAS. After the study, the outcome is that the soil of those areas contains a relatively high level of the toxic metals in order of Cu>Fe>Pb>Cd>Cr>Zn>Ar>Hg. The concentration of Cd, Pb, Cr, Ar and Zn (the majority of samples experimentally proved) exceeded the maximum standard level of WHO. Sequentially this study showed that uncontrolled e-waste processing operations caused serious pollution to local soil and release of toxic metals in the environment is also causing adverse effect on the health of people living in the nearby areas making them more prone to various harmful diseases.

Keywords: brass city, environment pollution, e-waste, toxic heavy metals

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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: Ezgi Şendil

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Information extracted from social media has received great attention since it has become an effective alternative for collecting people’s opinions and emotions based on specific experiences in a faster and easier way. The paper aims to put data in a meaningful way to analyze users’ posts and get a result in terms of the experiences and opinions of the users during and after natural disasters. The posts collected from Reddit are classified into nine different categories, including injured/dead people, infrastructure and utility damage, missing/found people, donation needs/offers, caution/advice, and emotional support, identified by using labelled Twitter data and four different machine learning (ML) classifiers.

Keywords: disaster, NLP, postdisaster management, sentiment analysis

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Authors: Dinesh Pathaka, Tomas Wagnera, J. M. Nunzib

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We investigated blends of MdPVV.PCBM.AIS for photovoltaic application. AgInSe2 powder was synthesized by sealing and heating the stoichiometric constituents in evacuated quartz tube ampule. Fine grinded AIS powder was dispersed in MD-MOPVV and PCBM with and without surfactant. Different concentrations of these particles were suspended in the polymer solutions and spin casted onto ITO glass. Morphological studies have been performed by atomic force microscopy and optical microscopy. The blend layers were also investigated by various techniques like XRD, UV-VIS optical spectroscopy, AFM, PL, after a series of various optimizations with polymers/concentration/deposition/ suspension/surfactants etc. XRD investigation of blend layers shows clear evidence of AIS dispersion in polymers. Diode behavior and cell parameters also revealed it. Bulk heterojunction hybrid photovoltaic device Ag/MoO3/MdPVV.PCBM.AIS/ZnO/ITO was fabricated and tested with standard solar simulator and device characterization system. The best performance and photovoltaic parameters we obtained was an open-circuit voltage of about Voc 0.54 V and a photocurrent of Isc 117 micro A and an efficiency of 0.2 percent using a white light illumination intensity of 23 mW/cm2. Our results are encouraging for further research on the fourth generation inorganic organic hybrid bulk heterojunction photovoltaics for energy. More optimization with spinning rate/thickness/solvents/deposition rates for active layers etc. need to be explored for improved photovoltaic response of these bulk heterojunction devices.

Keywords: thin films, photovoltaic, hybrid systems, heterojunction

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Authors: Dipanshu Sur, Ratnabali Chakravorty

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Background: Striae result from rapid expansion of the underlying tissue, e.g. during puberty, pregnancy or rapid weight gain. Prior data indicate that the incidence of stretch marks in Indian women is 77%.The hormonal and genetic factors are associated with their appearance. Recently that has been found skin extensibility, elasticity and rupture were strongly influenced by the water content of dermis and epidermis cells. Objective: The objectives were to assess the effects of topical treatments applied during pregnancy on the later development of stretch marks. Materials and methods: An open, prospective, randomized study was done on 120 pregnant women in whom skin elasticity and hydration as well as striae presence or apparition were measured at baseline and periodically until delivery. Patients were randomly assigned to application in wet skin cream, or in dry skin conditions. Results: The average basal hydration was 42 ±13 IU and the final was 46 ± 6 IU (P = 0.0325; 95% CI: -7.66 to -0.34), which difference was statistically significant. By measuring the moisture in the control region (forearm) a basal reading of 40 ± 9 IU and end of study of 38 ± 6; (p = 0.1547; 95% CI: -0.77 to 4.77) and this difference was considered to be not statistically significant. It was observed that at the end of the study, 55% women without ridges; mild ridges 5%; 36% moderate, and 4%, severe ridges. The proportion of women without grooves was 54% when the cream was applied studied wet skin and 45% when the cream was applied on dry skin. Conclusion: It was shown that cream under study increased hydration and elasticity of abdominal skin consequently in all subjects. This effect is more significant (54%) when the cream is applied to damp skin.

Keywords: striae gravidarum, skin moisturizer, skin hydration, skin elasticity

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Authors: Eman S. Soliman, Sana Hawamdeh, Najmus S. Mahfooz

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Purpose: The purpose of this paper was to examine various components of applied emotional intelligence as demonstrated in the leadership style of Khadijah Bint Khuwaylid in pre and post-Islamic society. Methodology: The research used a qualitative research method, specifically historical and ethnographic techniques. Data collection included both primary and secondary sources. Data from sources were analyzed to document the use of emotional intelligent leadership behaviors throughout Khadijah Bint Khuwaylid leadership experience from 596 A.D. to 621 A.D. Findings: Demonstration of four cornerstones of emotional intelligence which are self-awareness, self-management, social awareness and relationship management. Apply them on khadejah Bint Khuwaylid leadership style reveal that she possess main behavioral competences in the form of emotionally self-aware, self-.confidence, adaptability, empathy and influence. Conclusions: Khadijah Bint Khuwaylid serves as a historical model of effective leadership that included the use of emotional intelligence in her leadership behavior. The inclusion of the effective portion of the brain created a successful leadership style that can be learned by present day and future leadership. The recommendations for future leaders are to include the use of emotionally self-aware and self-confidence, adaptability, empathy and influence as components of leadership. This will then demonstrate in a leadership a basic knowledge and understanding of feelings, the keenness to be emotionally open with others, the ability to prototype beliefs and values, and the use of emotions in future communications, vision and progress.

Keywords: emotional intelligence, leadership, Khadijah Bint Khuwaylid, women

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

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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: Belyihun Muchie

Abstract:

This study investigates the low English oral communication skills of 5 second-year English major students at Debark University. It aims to identify the key factors contributing to their weaknesses and propose effective interventions to improve their spoken English proficiency. Mixed-methods research will be employed, utilizing observations, questionnaires, and semi-structured interviews to gather data from the participants. To clearly identify these factors, structured and informal observations will be employed; the former will be used to identify their fluency, pronunciation, vocabulary use, and grammar accuracy, and the later will be suited to observe the natural interactions and communication patterns of learners in the classroom setting. The questionnaires will assess their self-perceptions of their skills, perceived barriers to fluency, and preferred learning styles. Interviews will also delve deeper into their experiences and explore specific obstacles faced in oral communication. Data analysis will involve both quantitative and qualitative responses. The structured observation and questionnaire will be analyzed quantitatively, whereas the informal observation and interview transcripts will be analyzed thematically. Findings will be used to identify the major causes of low oral communication skills, such as limited vocabulary, grammatical errors, pronunciation difficulties, or lack of confidence. They are also helpful to develop targeted solutions addressing these causes, such as intensive pronunciation practice, conversation simulations, personalized feedback, or anxiety-reduction techniques. Finally, the findings will guide designing an intervention plan for implementation during the action research phase. The study's outcomes are expected to provide valuable insights into the challenges faced by English major students in developing oral communication skills, contribute to the development of evidence-based interventions for improving spoken English proficiency in similar contexts, and offer practical recommendations for English language instructors and curriculum developers to enhance student learning outcomes. By addressing the specific needs of these students and implementing tailored interventions, this research aims to bridge the gap between theoretical knowledge and practical speaking ability, equipping them with the confidence and skills to flourish in English communication settings.

Keywords: oral communication skills, mixed-methods, evidence-based interventions, spoken English proficiency

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

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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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Authors: Raed Hameed Allawi

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Wellbore instability problems are considered the majority challenge for several wells in the Ratawi shale formation. However, it results in non-productive (NPT) time and increased well-drilling expenditures. This work aims to construct an integrated mechanical earth model (MEM) to predict the wellbore failure and design optimum mud weight to improve the drilling efficiency of future wells. The MEM was based on field data, including open-hole wireline logging and measurement data. Several failure criteria were applied in this work, including Modified Lade, Mogi-Coulomb, and Mohr-Coulomb that utilized to calculate the proper mud weight and practical drilling paths and orientations. Results showed that the leading cause of wellbore instability problems was inadequate mud weight. Moreover, some improper drilling practices and heterogeneity of Ratawi formation were additional causes of the increased risk of wellbore instability. Therefore, the suitable mud weight for safe drilling in the Ratawi shale formation should be 11.5-13.5 ppg. Furthermore, the mud weight should be increased as required depending on the trajectory of the planned well. The outcome of this study is as practical tools to reduce non-productive time and well costs and design future neighboring deviated wells to get high drilling efficiency. In addition, the current results serve as a reference for similar fields in that region because of the lacking of published studies regarding wellbore instability problems of the Ratawi Formation in southern Iraqi oilfields.

Keywords: wellbore stability, hole collapse, horizontal stress, MEM, mud window

Procedia PDF Downloads 172

Authors: Simon Espigolé, Igor Shalyminov, Helen Hastie

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Deep machine learning techniques including deep neural networks (DNN) have been used to model language and dialogue for conversational agents to perform tasks, such as giving technical support and also for general chit-chat. They have been shown to be capable of generating long, diverse and coherent sentences in end-to-end dialogue systems and natural language generation. However, these systems tend to imitate the training data and will only generate the concepts and language within the scope of what they have been trained on. This work explores how deep neural networks can be used in a task that would normally require human creativity, whereby the human would read the movie description and/or watch the movie and come up with a compelling, interesting movie title. This task differs from simple summarization in that the movie title may not necessarily be derivable from the content or semantics of the movie description. Here, we train a type of DNN called a sequence-to-sequence model (seq2seq) that takes as input a short textual movie description and some information on e.g. genre of the movie. It then learns to output a movie title. The idea is that the DNN will learn certain techniques and approaches that the human movie titler may deploy that may not be immediately obvious to the human-eye. To give an example of a generated movie title, for the movie synopsis: ‘A hitman concludes his legacy with one more job, only to discover he may be the one getting hit.’; the original, true title is ‘The Driver’ and the one generated by the model is ‘The Masquerade’. A human evaluation was conducted where the DNN output was compared to the true human-generated title, as well as a number of baselines, on three 5-point Likert scales: ‘creativity’, ‘naturalness’ and ‘suitability’. Subjects were also asked which of the two systems they preferred. The scores of the DNN model were comparable to the scores of the human-generated movie title, with means m=3.11, m=3.12, respectively. There is room for improvement in these models as they were rated significantly less ‘natural’ and ‘suitable’ when compared to the human title. In addition, the human-generated title was preferred overall 58% of the time when pitted against the DNN model. These results, however, are encouraging given the comparison with a highly-considered, well-crafted human-generated movie title. Movie titles go through a rigorous process of assessment by experts and focus groups, who have watched the movie. This process is in place due to the large amount of money at stake and the importance of creating an effective title that captures the audiences’ attention. Our work shows progress towards automating this process, which in turn may lead to a better understanding of creativity itself.

Keywords: creativity, deep machine learning, natural language generation, movies

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Authors: Lalnuntluanga Hmar, Hardik Vyas

Abstract:

Hydraulic fracturing has become an essential procedure to break apart the rock and release the oil or gas which are trapped tightly in the rock by pumping fracturing fluids at high pressure down into the well. To open the fracture and to transport propping agent along the fracture, proper selection of fracturing fluids is the most crucial components in fracturing operations. Rheology properties of the fluids are usually considered the most important. Among various fracturing fluids, Borate crosslinked fluids have proved to be highly effective. Borate in the form of Boric Acid, borate ion is the most commonly use to crosslink the hydrated polymers and to produce very viscous gels that can stable at high temperature. Guar and HPG (Hydroxypropyl Guar) polymers are the most often used in these fluids. Borate gel rheology is known to be a function of polymer concentration, borate ion concentration, pH, and temperature. The crosslinking using Borate is a function of pH which means it can be formed or reversed simply by altering the pH of the fluid system. The fluid system was prepared by mixing base polymer with water at pH ranging between 8 to 11 and the optimum borate crosslinker efficiency was found to be pH of about 10. The rheology of laboratory prepared Borate crosslinked fracturing fluid was determined using Anton Paar Rheometer and Fann Viscometer. The viscosity was measured at high temperature ranging from 200ᵒF to 250ᵒF and pressures in order to partially stimulate the downhole condition. Rheological measurements reported that the crosslinking increases the viscosity, elasticity and thus fluid capability to transport propping agent.

Keywords: borate, crosslinker, Guar, Hydroxypropyl Guar (HPG), rheology

Procedia PDF Downloads 189