Search results for: building information technology

Authors: Khadijat Olabisi Abdulwahab, Mohammad Azad Malik, Paul O'Brien, Grigore Timco, Floriana Tuna

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The synthesis of spinel ferrite nanoparticles with a narrow size distribution is very crucial in their numerous applications including information storage, hyperthermia treatment, drug delivery, contrast agent in magnetic resonance imaging, catalysis, sensors, and environmental remediation. Ferrites have the general formula MFe₂O₄ (M = Fe, Co, Mn, Ni, Zn e.t.c) and possess remarkable electrical and magnetic properties which depend on the cations, method of preparation, size and their site occupancies. To the best of our knowledge, there are no reports on the use of a single source precursor to synthesise quaternary ferrite nanoparticles. Here in, we demonstrated the use of trimetallic iron pivalate cluster [CrCoFeO(O₂CᵗBu)₆(HO₂CᵗBu)₃] as a single source precursor to synthesise monodisperse cobalt chromium ferrite (FeCoCrO₄) nanoparticles by the hot injection thermolysis method. The precursor was thermolysed in oleylamine, oleic acid, with diphenyl ether as solvent at 260 °C. The effect of reaction time on the stoichiometry, phases or morphology of the nanoparticles was studied. The p-XRD patterns of the nanoparticles obtained after one hour was pure phase of cubic iron cobalt chromium ferrite (FeCoCrO₄). TEM showed that a more monodispersed spherical ferrite nanoparticles were obtained after one hour. Magnetic measurements revealed that the ferrite particles are superparamagnetic at room temperature. The nanoparticles were characterised by Powder X-ray Diffraction (p-XRD), Transmission Electron Microscopy (TEM), Energy Dispersive Spectroscopy (EDS) and Super Conducting Quantum Interference Device (SQUID).

Keywords: cobalt chromium ferrite, colloidal, hot injection thermolysis, monodisperse, reaction time, single source precursor, quaternary ferrite nanoparticles

Procedia PDF Downloads 313

Authors: Natalia Feruleva

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The goal of this paper is to develop the fraud risk assessment model basing on both relational and financial data and test the impact of the relationships between Russian non-public companies on the likelihood of financial fraud commitment. Relationships mean various linkages between companies such as parent-subsidiary relationship and person-related relationships. These linkages may provide additional opportunities for committing fraud. Person-related relationships appear when firms share a director, or the director owns another firm. The number of companies belongs to CEO and managed by CEO, the number of subsidiaries was calculated to measure the relationships. Moreover, the dummy variable describing the existence of parent company was also included in model. Control variables such as financial leverage and return on assets were also implemented because they describe the motivating factors of fraud. To check the hypotheses about the influence of the chosen parameters on the likelihood of financial fraud, information about person-related relationships between companies, existence of parent company and subsidiaries, profitability and the level of debt was collected. The resulting sample consists of 160 Russian non-public firms. The sample includes 80 fraudsters and 80 non-fraudsters operating in 2006-2017. The dependent variable is dichotomous, and it takes the value 1 if the firm is engaged in financial crime, otherwise 0. Employing probit model, it was revealed that the number of companies which belong to CEO of the firm or managed by CEO has significant impact on the likelihood of financial fraud. The results obtained indicate that the more companies are affiliated with the CEO, the higher the likelihood that the company will be involved in financial crime. The forecast accuracy of the model is about is 80%. Thus, the model basing on both relational and financial data gives high level of forecast accuracy.

Keywords: financial fraud, fraud prediction, non-public companies, regression analysis, relational data

Procedia PDF Downloads 119

Authors: Elucir Gir, Laelson Rochelle Milanês Sousa, Pedro Henrique Tertuliano Leoni, Carla Aparecida Arena Ventura, Ana Cristina de Oliveira e Silva, Renata Karina Reis

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Context and significance: Resilience is a protective agent for the physical and mental well-being of nursing professionals. Team members are constantly subjected to high levels of work stress that can negatively impact care performance and users of health services. Stress levels have been exacerbated with the COVID-19 pandemic. Objective: The aim of this study was to analyze the resilience of nursing professionals in Brazil during the COVID-19 pandemic. Method: Cross-sectional study with a quantitative approach carried out with professionals from nursing teams from all regions of Brazil. Data collection took place in the first year of the pandemic between October and December 2020. Data were obtained through an online questionnaire posted on social networks. The information collected included the sociodemographic characterization of the nursing professionals and the Brief Resilient Coping Scale was applied. Student's t-test for independent samples and analysis of variance (ANOVA) were used to compare resilience scores with sociodemographic variables. Results: 8,792 nursing professionals participated in the study, 5,767 (65.6%) were nurses, 7,437 (84.6%) were female and 2,643 (30.1%) were from the Northeast region of Brazil, 5,124 (58.8% ) had low levels of resilience. The results showed a statistically significant difference between the resilience score and the variables: professional category (p<0.001); sex (p = 0.003); age range (p<0.001); region of Brazil (p<0.001); marital status (p=0.029) and providing assistance in a field hospital (p<0.001). Conclusion: Participants in this study had, in general, low levels of resilience. There is an urgent need for actions aimed at promoting the psychological health of nursing professionals inserted in pandemic contexts. Descriptors: Psychological Resilience; Nursing professionals; COVID-19; SARSCoV-2.

Keywords: psychological resilience, nursing professionals, COVID-19, SARS-CoV-2

Procedia PDF Downloads 86

Authors: Laurin Zemmrich, Nicolai Stickler

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With the ongoing debate over how to incorporate sustainability, resilience, and value creation into business strategies, many procurement departments are put under pressure by governments, consumers, non-governmental organizations, and other stakeholders to disclose more information about their supply chains. According to practitioners and experts, procurement benefits the supply chain by increasing transparency and accountability, recruiting new suppliers, and supporting sustainable and ethical sourcing strategies. While most procurement departments establish these objectives, the bulk of activities are not carried out or are not regularly monitored. With the full potential of targeted sourcing still to be realized, procurement executives, in particular, are seeking for short-term cost-cutting impacts to appease external shareholders. We overcome this limitation by using an abductive approach to research and integrating empirical data from a Gioia methodology study design with relevant literature. Our analysis demonstrates that the procurement department has six essential levers aligned with sustainability, resilience, and value creation objectives and contributes to developing a new intra- and interorganizational purpose within the supply chain. Three enablers are identified as having a value-creating effect on supply chain interactions. Additionally, we discovered two impacts that alter the power balance between buyers and suppliers during transactions and have a cost-cutting or cost-avoiding effect. While cost-cutting, cost-avoidance, and dependency-reduction impacts are desirable, redistributing power may also have negative consequences. The article establishes a first strategy framework for evaluating the influence of the procurement department on supply chain transactions, allowing managers to understand better and apply the sourcing function inside a supply chain and embed it throughout the business.

Keywords: supply chain management, resilience, sustainability, value creation, purpose

Procedia PDF Downloads 117

Authors: Faruk Aras, Melih Inal, Tansel Cinar

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The coordination of airport staff especially in the operations and maintenance departments is important for the airport operation. As a result, this coordination will increase the efficiency in all operation. Therefore, a Collaborative Decision-Making (CDM) system targets on improving the overall productivity of all operations by optimizing the use of resources and improving the predictability of actions. Enlarged productivity can be of major benefit for all airport operations. It also increases cost-efficiency. This study explains how predictive maintenance using IoT (Internet of Things), predictive operations and the statistical data such as Mean Time To Failure (MTTF) improves airport terminal operations and utilize airport terminal equipment in collaboration with collaborative decision making system/Airport Operation Control Center (AOCC). Data generated by the predictive maintenance methods is retrieved and analyzed by maintenance managers to predict when a problem is about to occur. With that information, maintenance can be scheduled when needed. As an example, AOCC operator would have chance to assign a new gate that towards to this gate all the equipment such as travellator, elevator, escalator etc. are operational if the maintenance team is in collaboration with AOCC since maintenance team is aware of the health of the equipment because of predictive maintenance methods. Applying predictive maintenance methods based on analyzing the health of airport terminal equipment dramatically reduces the risk of downtime by on time repairs. We can classify the categories as high priority calls for urgent repair action, as medium priority requires repair at the earliest opportunity, and low priority allows maintenance to be scheduled when convenient. In all cases, identifying potential problems early resulted in better allocation airport terminal resources by AOCC.

Keywords: airport, predictive maintenance, collaborative decision-making system, Airport Operation Control Center (AOCC)

Procedia PDF Downloads 364

Authors: Ibrahim Magaji

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WhatsApp messaging platform brings about new opportunities for users to participate in unique storytelling experiences and audience engagement, particularly to Students of Mass communication who receive training to report events and issues accurately and objectively in accordance with official controls. Also, the complex nature of society today made it possible to use the WhatsApp platform that revolutionizes the means of sharing information, ideas, and experiences. This paper examined the WhatsApp messaging platform and how it influenced the academic performance of students in the Department of Mass Communication, Abdu Gusau Polytechnic, Talata Mafara. It used in-depth interview techniques and focus group discussion with students, as well as the use of published materials as well as unpublished materials to gather related and relevant data. Also, the paper used procedures involved to analyze long interview content. This procedure includes observation of a useful utterance, development of expanded observation, the examination of the interconnection of observed comments, collective scrutiny of observation for patterns and themes, and review and analysis of the themes across all interviews for development of the thesis. The result revealed that the majority of students used WhatsApp messenger for making friends and chatting. Also, the students experienced negative effects such as poor grammar and spelling, less study time, and poor academic performance because of active participation in the use of WhatsApp messaging platform. Surprisingly, there was a high addiction rate among students in the usage of WhatsApp messenger. However, other students experienced an improvement in their readings skills as a result of participation in the use of the platform. Also, students shared ideas, discussed, and shared examination questions among themselves on WhatsApp messenger.

Keywords: WhatsApp messenger, students, participation, group

Procedia PDF Downloads 130

Authors: Cécile Dufloux, Klaus Böttcher, Heike Oppermann, Jürgen Wollweber

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Hexagonal aluminum nitride (AlN) is a promising candidate for several wide band gap semiconductor compound applications such as deep UV light emitting diodes (UVC LED) and fast power transistors (HEMTs). To date, bulk AlN single crystals are still commonly grown from the physical vapor transport (PVT). Single crystalline AlN wafers obtained from this process could offer suitable substrates for a defect-free growth of ultimately active AlGaN layers, however, these wafers still lack from small sizes, limited delivery quantities and high prices so far.Although there is already an increasing interest in the commercial availability of AlN wafers, comparatively cheap Si, SiC or sapphire are still predominantly used as substrate material for the deposition of active AlGaN layers. Nevertheless, due to a lattice mismatch up to 20%, the obtained material shows high defect densities and is, therefore, less suitable for high power devices as described above. Therefore, the use of AlN with specially adapted properties for optical and sensor applications could be promising for mass market products which seem to fulfill fewer requirements. To respond to the demand of suitable AlN target material for the growth of AlGaN layers, we have designed an innovative technology based on reactive plasma spraying. The goal is to produce coarse grained AlN boules with N-terminated columnar structure and high purity. In this process, aluminum is injected into a microwave stimulated nitrogen plasma. AlN, as the product of the reaction between aluminum powder and the plasma activated N2, is deposited onto the target. We used an aluminum filament as the initial material to minimize oxygen contamination during the process. The material was guided through the nitrogen plasma so that the mass turnover was 10g/h. To avoid any impurity contamination by an erosion of the electrodes, an electrode-less discharge was used for the plasma ignition. The pressure was maintained at 600-700 mbar, so the plasma reached a temperature high enough to vaporize the aluminum which subsequently was reacting with the surrounding plasma. The obtained products consist of thick polycrystalline AlN layers with a diameter of 2-3 cm. The crystallinity was determined by X-ray crystallography. The grain structure was systematically investigated by optical and scanning electron microscopy. Furthermore, we performed a Raman spectroscopy to provide evidence of stress in the layers. This paper will discuss the effects of process parameters such as microwave power and deposition geometry (specimen holder, radiation shields, ...) on the topography, crystallinity, and stress distribution of AlN.

Keywords: aluminum nitride, polycrystal, reactive plasma spraying, semiconductor

Procedia PDF Downloads 281

Authors: Kumiko Inagaki

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In recent, years, Japanese universities have begun to face a dilemma: more than half of all high school graduates go on to attend an institution of higher learning, overwhelming Japanese universities accustomed to small student bodies. These universities have been forced to embrace qualitative changes to accommodate the increased number and diversity of students who enter their establishments, students who differ in their motivations for learning, their levels of eagerness to learn, and their perspectives on the future. One of these changes is an increase in awareness among Japanese educators of the importance of active learning, which deepens students’ understanding of course material through a range of activities, including writing, speaking, thinking, and presenting, in addition to conventional “passive learning” methods such as listening to a one-way lecture. 　The purpose of this study is to examine the effectiveness of the teaching method adapted to improve active learning. A teaching method designed to promote active learning was implemented in a social science course at one of the most popular universities in Japan. A questionnaire using a five-point response format was given to students in 2,305 courses throughout the university to evaluate the effectiveness of the method based on the following measures: ① the ratio of students who were motivated to attend the classes, ② the rate at which students learned new information, and ③ the teaching method adopted in the classes. The results of this study show that the percentage of students who attended the active learning course eagerly, and the rate of new knowledge acquired through the course, both exceeded the average for the university, the department, and the subject area of social science. In addition, there are strong correlations between teaching method and student motivation and between teaching method and knowledge acquisition rate. These results indicate that the active learning teaching method was effectively implemented and that it may improve student eagerness to attend class and motivation to learn.

Keywords: active learning, Japanese university, teaching method, university education

Procedia PDF Downloads 194

Authors: Z. B. Ibrahim, N. Ismail, K. I. Othman

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Fuzzy Differential Equations (FDEs) play an important role in modelling many real life phenomena. The FDEs are used to model the behaviour of the problems that are subjected to uncertainty, vague or imprecise information that constantly arise in mathematical models in various branches of science and engineering. These uncertainties have to be taken into account in order to obtain a more realistic model and many of these models are often difficult and sometimes impossible to obtain the analytic solutions. Thus, many authors have attempted to extend or modified the existing numerical methods developed for solving Ordinary Differential Equations (ODEs) into fuzzy version in order to suit for solving the FDEs. Therefore, in this paper, we proposed the development of a fuzzy version of three-point block method based on Block Backward Differentiation Formulas (FBBDF) for the numerical solution of first order FDEs. The three-point block FBBDF method are implemented in uniform step size produces three new approximations simultaneously at each integration step using the same back values. Newton iteration of the FBBDF is formulated and the implementation is based on the predictor and corrector formulas in the PECE mode. For greater efficiency of the block method, the coefficients of the FBBDF are stored at the start of the program. The proposed FBBDF is validated through numerical results on some standard problems found in the literature and comparisons are made with the existing fuzzy version of the Modified Simpson and Euler methods in terms of the accuracy of the approximated solutions. The numerical results show that the FBBDF method performs better in terms of accuracy when compared to the Euler method when solving the FDEs.

Keywords: block, backward differentiation formulas, first order, fuzzy differential equations

Procedia PDF Downloads 318

Authors: Franciele L. Bernard, Felipe Dalla Vecchia, Barbara B. Polesso, Jose A. Donato, Marcus Seferin, Rosane Ligabue, Jailton F. do Nascimento, Sandra Einloft

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The increasing level of carbon dioxide concentration in the atmosphere related to fossil fuels processing and utilization are contributing to global warming phenomena considerably. Carbon capture and storage (CCS) technologies appear as one of the key technologies to reduce CO2 emissions mitigating the effects of climate change. Absorption using amines solutions as solvents have been extensively studied and used in industry for decades. However, solvent degradation and equipment corrosion are two of the main problems in this process. Poly (ionic liquid) (PIL) is considered as a promising material for CCS technology, potentially more environmentally friendly and lesser energy demanding than traditional material. PILs possess a unique combination of ionic liquids (ILs) features, such as affinity for CO2, thermal and chemical stability and adjustable properties, coupled with the intrinsic properties of the polymer. This study investigated new Poly (ionic liquid) (PIL) based on polyurethanes with different ionic liquids cations and its potential for CO2 capture. The PILs were synthesized by the addition of diisocyante to a difunctional polyol, followed by an exchange reaction with the ionic Liquids 1-butyl-3-methylimidazolium chloride (BMIM Cl); tetrabutylammonium bromide (TBAB) and tetrabutylphosphonium bromide (TBPB). These materials were characterized by Fourier transform infrared spectroscopy (FTIR), Proton Nuclear Magnetic Resonance (1H-NMR), Atomic force microscopy (AFM), Tensile strength analysis, Field emission scanning electron microscopy (FESEM), Thermogravimetric analysis (TGA), Differential scanning calorimetry (DSC). The PILs CO2 sorption capacity were gravimetrically assessed in a Magnetic Suspension Balance (MSB). It was found that the ionic liquids cation influences in the compounds properties as well as in the CO2 sorption. The best result for CO2 sorption (123 mgCO2/g at 30 bar) was obtained for the PIL (PUPT-TBA). The higher CO2 sorption in PUPT-TBA is probably linked to the fact that the tetraalkylammonium cation having a higher positive density charge can have a stronger interaction with CO2, while the imidazolium charge is delocalized. The comparative CO2 sorption values of the PUPT-TBA with different ionic liquids showed that this material has greater capacity for capturing CO2 when compared to the ILs even at higher temperature. This behavior highlights the importance of this study, as the poly (urethane) based PILs are cheap and versatile materials.

Keywords: capture, CO2, ionic liquids, ionic poly(urethane)

Procedia PDF Downloads 234

Authors: H. Abas Nejad, A. R. Teymoori

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Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, etc. in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as the user stays neutral for the majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this work, we propose a light-weight neutral vs. emotion classification engine, which acts as a preprocessor to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at Key Emotion (KE) points using a textural statistical model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a textural statistical model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves ER accuracy and simultaneously reduces the computational complexity of ER system, as validated on multiple databases.

Keywords: neutral vs. emotion classification, Constrained Local Model, procrustes analysis, Local Binary Pattern Histogram, statistical model

Procedia PDF Downloads 336

Authors: Prem Bahadur Giri, Trilochana Pokhrel

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The nationalization of forest during early 1960s had become a counterproductive for the conservation of forest in Nepal. Realizing this fact, the Government of Nepal initiated a paradigm shift from government-controlled forestry system to people’s direct participation for managing forestry, conceptualizing community forest approach in the early 1980s. The community forestry approach is expected to promote sustainable forest management, restoring degraded forests for enhancing the forest condition on one hand, and on the other, improvement of livelihoods, particularly of low-income people and forest dependent communities, as well as promoting community ownership to forest. As a result, establishment of community forests started and had taken faster momentum in Nepal. Of the total land in Nepal, forest occupies 6.5 million hectares which is around 45 percent of the forest area. Of the total forest area 1.8 million hectarehas been handed-over to community management. A total of 19,361 ‘community forest users groups’ are already created to manage the community forest.Tostreamlinethe governance of community forest, the enactment of ‘Forest Act 1993’ provides a clear legal basis for managing community forest in Nepal. This article is based on an in-depth study taking a case of Tarpakha Community Forest (TCF) located in Siranchok Rural Municipality of Gorkha District in Nepal. It mainly discusses on to extent the TCF able to achieve twin objectives of this community forest for catalyzing socio-economic improvement of the targeted community and conservation of forest. The primary information was generated through in-depth interviews along with group discussion with members, management committee, and other relevant stakeholders. The findings reveal that there is significant improvement of regeneration of forest and also changes in the socio-economic status of local community. However, coordination with local municipality and forest governing entities is still weak.

Keywords: community forest, nepal, socio-economic benefit, sustainable forest management

Procedia PDF Downloads 81

Authors: Ayesha Akbar

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Pakistan is moving from a security state to a welfare state despite several security challenges both internal and external. Human security signifies a varied approach in different regions depending upon the leadership and policy priorities. The link between human development and economic growth is not automatic. It has to be created consciously by forward-looking policies and strategies by national governments. There are seven components or categories of human security these include: Economic Security, Personal Security, Health Security, Environmental Security, Food Security, Community Security and Political Security. The increasing interest of the international community to clearly understand the dimensions of human security provided the grounds to Pakistani scholars as well to ponder on the issue and delineate lines of human security. A great deal of work has been either done or in process to evaluate human security indicators in Pakistan. Notwithstanding, after having been done a great deal of work the human security in Pakistan is not satisfactory. A range of deteriorating indicators of human development that lies under the domain of human security leaves certain inquiries to be answered. What are the dimensions of human security in Pakistan? And how are they being dealt from the perspective of policy and institution in terms of its operationalization in Pakistan? Is the human security discourse reflects evidence-based policy changes. The methodology is broadly based on qualitative methods that include interviews, content analysis of policy documents. Pakistan is among the most populous countries in the world and faces high vulnerability to climate change. Literacy rate has gone down with the surge of youth bulge to accommodate in the job market. Increasing population is creating food problems as the resources have not been able to compete with the raising demands of food and other social amenities of life. Majority of the people are facing acute poverty. Health outcomes are also not satisfactory with the high infant and maternal mortality rate. Pakistan is on the verge of facing water crisis as the water resources are depleting so fast with the high demand in agriculture and energy sector. Pakistan is striving hard to deal with the declining state of human security but the dilemma is lack of resources that hinders in meeting up with the emerging demands. The government requires to bring about more change with scaling-up economic growth avenues with enhancing the capacity of human resources. A modern performance drive culture with the integration of technology is required to deliver efficient and effective service delivery. On an already fast track process of reforms; e-governance and evidence based policy mechanism is being instilled in the government process for better governance and evidence based decisions.

Keywords: governance, human development index, human security, Pakistan, policy

Procedia PDF Downloads 252

Authors: Minji Seo

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Fashion stakeholders are becoming increasingly aware of technological innovation in manufacturing. In 2020, the COVID-19 pandemic caused transformations in working patterns, such as working remotely rather thancommuting. To enable smooth remote working, 3D fashion design software is being adoptedas the latest trend in design and production. The majority of fashion designers, however, are still resistantto this change. Previous studies on 3D fashion design software solely highlighted the beneficial and detrimental factors of adopting design innovations. They lacked research on the relationship between resistance factors and the adoption of innovation. These studies also fell short of exploringthe perspectives of users of these innovations. This paper aims to investigate the key drivers and barriers of employing 3D fashion design software as wellas to explore the challenges faced by designers.It also toucheson the governmental support for digital manufacturing in Seoul, South Korea, and London, the United Kingdom. By conceptualising local support, this study aims to provide a new path for industrial clusters to optimise digital apparel manufacturing. The study uses a mixture of quantitative and qualitative approaches. Initially, it reflects a survey of 350 samples, fashion designers, on innovation resistance factors of 3D fashion design software and the effectiveness of local support. In-depth interviews with 30 participants provide a better understanding of designers’ aspects of the benefits and obstacles of employing 3D fashion design software. The key findings of this research are the main barriers to employing 3D fashion design software in fashion production. The cultural characteristics and interviews resultsare used to interpret the survey results. The findings of quantitative data examine the main resistance factors to adopting design innovations. The dominant obstacles are: the cost of software and its complexity; lack of customers’ interest in innovation; lack of qualified personnel, and lack of knowledge. The main difference between Seoul and London is the attitudes towards government support. Compared to the UK’s fashion designers, South Korean designers emphasise that government support is highly relevant to employing 3D fashion design software. The top-down and bottom-up policy implementation approach distinguishes the perception of government support. Compared to top-down policy approaches in South Korea, British fashion designers based on employing bottom-up approaches are reluctant to receive government support. The findings of this research will contribute to generating solutions for local government and the optimisation of use of 3D fashion design software in fashion industrial clusters.

Keywords: digital apparel production, industrial clusters, innovation resistance, 3D fashion design software, manufacturing, innovation, technology, digital manufacturing, innovative fashion design process

Procedia PDF Downloads 100

Authors: Aamir Hasan, Subhash Mishra

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The purpose of the study was to determine the key drivers which influence the shopping behavior of the customers in the retail store. In today‟s competitive world with increasing number of retail stores, the retailers need to be more customer oriented. Retail has changed and expanded in all lines of business, be it apparel,jewelry, footwear, groceries etc. The modern consumer is posing a challenging task for the Indian retailer. More aware, more confident and much more demanding, therefore the retailers are looking for ways to deliver better consumer value and to increase consumer purchase intention. Retailers tend to differentiate themselves by making their service easier to consumers. The study aims to study the key drivers that can influence shopping behavior in retail store. A survey (store intercept) method was employed to elicit primary information from 300 shoppers in different retail stores of Lucknow. The findings reveal the factors that play a greater role in influencing the shopping behavior of customers in retail store. As such, a survey of retail store customers‟ attitude towards reduced price, sales promotion, quality of the products, proximity to the home, customer service, store atmospherics were analyzed to identify the key drivers influencing shopping behavior in retail store. A questionnaire based on a five-item Likert scale, as well as random sampling, was employed for data collection. Data analysis was accomplished using SPSS software. The paper has found shopping experience, store image and value for money as three important variable out of which shopping experience emerged as a dominant factor which influences the consumer's shopping behavior in the retail store. Since the research has established empirical evidences in determining the key drivers which influences the shopping behavior of the customers in the retail store, it serves as a foundation for a deeper probe into the shopping behavior of the customers in the retail store research domain in the Indian context.

Keywords: retail, shopping, customers, questionnaire

Procedia PDF Downloads 421

Authors: Lucilla Crosta, Anthony Edwards

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Companies and the market place nowadays struggle to find employees with adequate skills in relation to anticipated growth of their businesses. At least half of workers will need to undertake some form of up-skilling process in the next five years in order to remain aligned with the requests of the market . In order to meet these challenges, there is a clear need to explore the potential uses of AI (artificial Intelligence) based tools in assessing transversal skills (critical thinking, communication and soft skills of different types in general) of workers and adult students while empowering them to develop those same skills in a reliable trustworthy way. Companies seek workers with key transversal skills that can make a difference between workers now and in the future. However, critical thinking seems to be the one of the most imprtant skill, bringing unexplored ideas and company growth in business contexts. What employers have been reporting since years now, is that this skill is lacking in the majority of workers and adult students, and this is particularly visible trough their writing. This paper investigates how critical thinking and communication skills are currently developed in Higher Education environments through use of AI tools at postgraduate levels. It analyses the use of a branch of AI namely Machine Learning and Big Data and of Neural Network Analysis. It also examines the potential effect the acquisition of these skills through AI tools and what kind of effects this has on employability This paper will draw information from researchers and studies both at national (Italy & UK) and international level in Higher Education. The issues associated with the development and use of one specific AI tool Edulai, will be examined in details. Finally comparisons will be also made between these tools and the more recent phenomenon of Chat GPT and forthcomings and drawbacks will be analysed.

Keywords: critical thinking, artificial intelligence, higher education, soft skills, chat GPT

Procedia PDF Downloads 107

Authors: Samar Mousa, Galini Mavromatidou, Rebecca Shirley

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Surgeons carry out numerous operations in the busy burns and plastic surgery department daily. Writing an accurate operation note with all the essential information is crucial for communication not only within the plastics team but also to the multi-disciplinary team looking after the patient, including other specialties, nurses and GPs. The Royal college of surgeons of England, in its guidelines of good surgical practice, mentioned that the surgeon should ensure that there are clear (preferably typed) operative notes for every procedure. The notes should accompany the patient into recovery and to the ward and should give sufficient detail to enable continuity of care by another doctor. The notes should include the Date and time, Elective/emergency procedure, Names of the operating surgeon and assistant, Name of the theatre anesthetist, Operative procedure carried out, Incision, Operative diagnosis, Operative findings, Any problems/complications, Any extra procedure performed and the reason why it was performed, Details of tissue removed, added or altered, Identification of any prosthesis used, including the serial numbers of prostheses and other implanted materials, Details of closure technique, Anticipated blood loss, Antibiotic prophylaxis (where applicable), DVT prophylaxis (where applicable), Detailed postoperative care instructions and Signature. Fourteen random days were chosen in December 2021 to assess the accuracy of operative notes and post-operative care. A total of 163 operative notes were examined. The average completion rates in all domains were 85.4%. An electronic operative note template was designed to cover all domains mentioned in the Royal College of surgeons' good surgical practice. It is kept in the hospital drive for all surgeons to use.

Keywords: operative notes, plastic surgery, documentation, electronic

Procedia PDF Downloads 79

Authors: Marcin Debowski, Marcin Zielinski, Magdalena Zielinska, Paulina Rusanowska

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The problem with digestate management is one of the most important factors influencing on the development and operation of biogas plant. Turbidity and bacterial contamination negatively affect the growth of algae, which can limit the use of the effluent in the production of algae biomass on a large scale. These problems can be overcome by cultivating of algae species resistant to environmental factors, such as Chlorella sp., Scenedesmus sp., or reducing load of organic compounds to prevent bacterial contamination. The effluent requires dilution and/or purification. One of the methods of effluent treatment is the use of a membrane technology such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF) and reverse osmosis (RO), depending on the membrane pore size and the cut off point. Membranes are a physical barrier to solids and particles larger than the size of the pores. MF membranes have the largest pores and are used to remove turbidity, suspensions, bacteria and some viruses. UF membranes remove also color, odor and organic compounds with high molecular weight. In treatment of wastewater or other waste streams, MF and UF can provide a sufficient degree of purification. NF membranes are used to remove natural organic matter from waters, water disinfection products and sulfates. RO membranes are applied to remove monovalent ions such as Na⁺ or K⁺. The effluent was used in UF for medium to cultivation of two microalgae: Chlorella sp. and Phaeodactylum tricornutum. Growth rates of Chlorella sp. and P. tricornutum were similar: 0.216 d⁻¹ and 0.200 d⁻¹ (Chlorella sp.); 0.128 d⁻¹ and 0.126 d⁻¹ (P. tricornutum), on synthetic medium and permeate from UF, respectively. The final biomass composition was also similar, regardless of the medium. Removal of nitrogen was 92% and 71% by Chlorella sp. and P. tricornutum, respectively. The fermentation effluents after UF and dilution were also used for cultivation of algae Scenedesmus sp. that is resistant to environmental conditions. The authors recommended the development of biorafinery based on the production of algae for the biogas production. There are examples of using a multi-stage membrane system to purify the liquid fraction from digestate. After the initial UF, RO is used to remove ammonium nitrogen and COD. To obtain a permeate with a concentration of ammonium nitrogen allowing to discharge it into the environment, it was necessary to apply three-stage RO. The composition of the permeate after two-stage RO was: COD 50–60 mg/dm³, dry solids 0 mg/dm³, ammonium nitrogen 300–320 mg/dm³, total nitrogen 320–340 mg/dm³, total phosphorus 53 mg/dm³. However compostion of permeate after three-stage RO was: COD < 5 mg/dm³, dry solids 0 mg/dm³, ammonium nitrogen 0 mg/dm³, total nitrogen 3.5 mg/dm³, total phosphorus < 0,05 mg/dm³. Last stage of RO might be replaced by ion exchange process. The negative aspect of membrane filtration systems is the fact that the permeate is about 50% of the introduced volume, the remainder is the retentate. The management of a retentate might involve recirculation to a biogas plant.

Keywords: digestate, membrane filtration, microalgae cultivation, Chlorella sp.

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Authors: Rebecca Haythorne

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Background: Agendas continuously emphasise the need to increase work based training and opportunities for individuals with learning disabilities. However research and statistics suggest that there is still significant stigma and stereotypes as to what they can contribute, or gain from being part of the working environment. Method: To tackles some of these prejudices an Occupational Therapy based intervention was developed for learning disability service users working at a social enterprise farm. The intervention aimed to increase positive public perception around individual capabilities and encourage individuals with learning disabilities to take ownership and be proud of their individual personhood and citizenship. This was achieved by using components of the Model of Human Occupation to tailor the intervention to individual values, skills and working contributions. The final project involved making creative wall art for public viewing, focusing on 'who works there and what they do'. This was accompanied by a visitor information guide, allowing individuals to tell visitors about themselves, the work they do and why it is meaningful to them. Outcomes: The intervention has helped to increased metal well-being and confidence of learning disability service users “people will know I work here now” and “I now have something to show my family about the work I do at the farm”. The intervention has also increased positive public perception and community awareness “you can really see the effort that’s gone into doing this” and “it’s a really visual experience to see people you don’t expect to see doing this type of work”. Resources left behind have further supported individuals to take ownership in creating more wall art to be sold at the farm shop. Conclusion: the intervention developed has helped to improve mental well-being of both service users and staff and improve community awareness. Due to this, the farm has decided to roll out the intervention to other areas of the social enterprise and is considering having more Occupational Therapy involvement in the future.

Keywords: citizenship, intervention, occupational therapy, personhood

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Authors: Ali Raouli, Amin Chegenizadeh, Hamid Nikraz

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The Perth metropolitan area and its surrounding regions have been expanding rapidly in recent decades and it is expected that this growth will continue in the years to come. With this rapid growth and the resulting increase in population, consideration should be given to strategic planning and modelling for the future expansion of Perth. The accurate estimation of projected traffic volumes has always been a major concern for the transport modelers and planners. Development of a reliable strategic transport model depends significantly on the inputs data into the model and the calibrated parameters of the model to reflect the existing situation. Trip distribution is the second step in four-step modelling (FSM) which is complex due to its behavioral nature. Gravity model is the most common method for trip distribution. The spatial separation between the Origin and Destination (OD) zones will be reflected in gravity model by applying deterrence functions which provide an opportunity to include people’s behavior in choosing their destinations based on distance, time and cost of their journeys. Deterrence functions play an important role for distribution of the trips within a study area and would simulate the trip distances and therefore should be calibrated for any particular strategic transport model to correctly reflect the trip behavior within the modelling area. This paper aims to review the most common deterrence functions and propose a calibrated deterrence function for work trips within the Perth Metropolitan Area based on the information obtained from the latest available Household data and Perth and Region Travel Survey (PARTS) data. As part of this study, a four-step transport model using EMME software has been developed for Perth Metropolitan Area to assist with the analysis and findings.

Keywords: deterrence function, four-step modelling, origin destination, transport model

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Authors: Harsha B. R., Anil Kumar K. S.

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Climate and soils are the two most dynamic entities among the factors affecting growth and grapes productivity. Studying of prevailing climate over the years in a region provides sufficient information related to management practices to be carried out in vineyards. Evaluating the suitability of vineyard soils under different climatic conditions serves as the yardstick to analyse the performance of grapevines. This study was formulated to study the climate and evaluate the site-suitability of soils in vineyards of southern Karnataka, which has registered its superiority in the quality production of wine. Ten soil profiles were excavated for suitability evaluation of soils, and six taluks were studied for climatic analysis. In almost all the regions studied, recharge starts at the end of the May or June months, peaking in either September or October months. Soil Starts drying from mid of December months in the taluks studied. Bangalore North (Rajanukunte) soils were highly suited for grapes cultivation with no or slight limitations. Bangalore North (GKVK Farm) was moderately suited with slight to moderate limitations of slope and available nitrogen content. Moderate suitability was observed in the rest of the profiles studied in Eastern dry zone soils with the slight to moderate limitations of either organic carbon or available nitrogen or both in the Eastern dry zone. Magadi (Southern dry zone) soils were moderately suitable with slight to moderate limitations of graveliness, available nitrogen, organic carbon, and exchangeable sodium percentage. Sustainable performance of vineyards in terms of yield can be achieved in these taluks by managing the constraints existing in soils.

Keywords: climatic analysis, dry zone, water recharge, growing period, suitability, sustainability

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Authors: Bushra Zafar, Usman Qamar

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Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

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Authors: Rima Abu Jaber Bransi, Rawya Jarjoura Burbara

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This study deals with two pioneering approaches in teaching Arabic as a mother tongue: first, computerization of literary and functional texts in the mother tongue; second, the pioneering model in teaching writing skills by computerization. The significance of the study lies in its treatment of a serious problem that is faced in the era of technology, which is the widening gap between the pupils and their mother tongue. The innovation in the study is that it introduces modern methods and tools and a pioneering instructional model that turns the process of mother tongue teaching into an effective, meaningful, interesting and motivating experience. In view of the Arabic language diglossia, standard Arabic and spoken Arabic, which constitutes a serious problem to the pupil in understanding unused words, and in order to bridge the gap between the pupils and their mother tongue, we resorted to computerized techniques; we took texts from the pre-Islamic period (Jahiliyya), starting with the Mu'allaqa of Imru' al-Qais and other selected functional texts and computerized them for teaching in an interesting way that saves time and effort, develops high thinking strategies, expands the literary good taste among the pupils, and gives the text added values that neither the book, the blackboard, the teacher nor the worksheets provide. On the other hand, we have developed a pioneering computerized model that aims to develop the pupil's ability to think, to provide his imagination with the elements of growth, invention and connection, and motivate him to be creative, and raise level of his scores and scholastic achievements. The model consists of four basic stages in teaching according to the following order: 1. The Preparatory stage, 2. The reading comprehension stage, 3. The writing stage, 4. The evaluation stage. Our lecture will introduce a detailed description of the model with illustrations and samples from the units that we built through highlighting some aspects of the uniqueness and innovation that are specific to this model and the different integrated tools and techniques that we developed. One of the most significant conclusions of this research is that teaching languages through the employment of new computerized strategies is very likely to get the Arabic speaking pupils out of the circle of passive reception into active and serious action and interaction. The study also emphasizes the argument that the computerized model of teaching can change the role of the pupil's mind from being a store of knowledge for a short time into a partner in producing knowledge and storing it in a coherent way that prevents its forgetfulness and keeping it in memory for a long period of time. Consequently, the learners also turn into partners in evaluation by expressing their views, giving their notes and observations, and application of the method of peer-teaching and learning.

Keywords: classical poetry, computerization, diglossia, writing skill

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Authors: Ayten Bakhtiyar Khasayeva

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Lower Kura depression is a part of the South Caspian Basin (SCB), located between the folded regions of the Greater and Lesser Caucasus. The region is characterized by thick sedimentary cover 22 km (SCB up to 30 km), high sedimentation rate, low geothermal gradient (average value corresponds to 2 °C / 100m). There is Quaternary, Pliocene, Miocene and Oligocene deposits take part in geological structure. Miocene and Oligocene deposits are opened by prospecting and exploratory wells in the areas of Kalamaddin and Garabagli. There are 25 mud volcanoes within the territory of the Lower Kura depression, which are the unique source of information about hydrocarbons contenting great depths. During the wells data research, solid erupted products and mud volcano fluids, and according to the geological and thermal characteristics of the region, it was determined that the main phase of the hydrocarbon generation (MK1-AK2) corresponds to a wide range of depths from 10 to 14 km, which corresponds to the Pliocene-Miocene sediments, and to the "oil and gas windows" according to the intended meaning of R0 ≈ 0,65-0,85%. Fluids of mud volcanoes comprise by the following phases - gas, water. Gas phase consists mainly of methane (99%) of heavy hydrocarbons (С2+ hydrocarbons), CO2, N2, inert components He, Ar. The content of the С2+ hydrocarbons in the gases of mud volcanoes associated with oil deposits is increased. Carbon isotopic composition of methane for the Lower Kura depression varies from -40 ‰ to -60 ‰. Water of mud volcanoes are represented by all four genetic types. However the most typical types of water are HCN type. According to the Mg-Li geothermometer formation of mud waters corresponds to the temperature range from 20 °C to 140 °C (PC2). The solid product emissions of mud volcanoes identified 90 minerals and 30 trace elements. As a result geochemical investigation, thermobaric and geological conditions, zone oil and gas generation - the prospect of the Lower Kura depression is projected to depths greater than 10 km.

Keywords: geology, geochemistry, mud volcanoes, petroleum potential

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Authors: Iman Shabanzadeh

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Over the last three decades, the main demands of the Iranian workforce have been focused on three areas: "The right to a decent wage", "The right to organize" and "The right to job security". In order to investigate and analyze this situation, the present study focuses on the component of job security. The purpose of the study is to figure out what mechanisms in Iran's Labor Law have led to the destabilization and undermining of workers' job security. The research method is descriptive-analytical. To collect information, library and document sources in the field of laws related to labor rights in Iran and, semi-structured interviews with experts have been used. In the data analysis stage, the qualitative content analysis method was also used. The trend analysis of the statistics related to the labor force situation in Iran in the last three decades shows that the employment structure has been facing an increase in the active population, but in the last decade, a large part of this population has been mainly active in the service sector, and contract-free enterprises, so a smaller share of this employment has insurance coverage and a larger share has underemployment. In this regard, the results of this study show that four contexts have been proposed as the main legal and executive mechanisms of labor instability in Iran, which are: 1) temporaryization of the labor force by providing different interpretations of labor law, 2) adjustment labor in the public sector and the emergence of manpower contracting companies, 3) the cessation of labor law protection of workers in small workshops and 4) the existence of numerous restrictions on the effective organization of workers. The theoretical conclusion of this article is that the main root of the challenges of the labor society and the destabilized workforce in Iran is the existence of structural inequalities in the field of labor security, whose traces can be seen in the legal provisions and executive regulations of this field.

Keywords: inequality, precariat, temporaryization, labor force, labor law

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Authors: Faris Tarlochan, Siva Mahesh Tangutooru

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Lateral Geniculate Nucleus (LGN) is the relay center in the visual pathway as it receives most of the input information from retinal ganglion cells (RGC) and sends to visual cortex. Low threshold calcium currents (IT) at the membrane are the unique indicator to characterize this firing functionality of the LGN neurons gained by the RGC input. According to the LGN functional requirements such as functional mapping of RGC to LGN, the morphologies of the LGN neurons were developed. During the neurological disorders like glaucoma, the mapping between RGC and LGN is disconnected and hence stimulating LGN electrically using deep brain electrodes can restore the functionalities of LGN. A computational model was developed for simulating the LGN neurons with three predominant morphologies, each representing different functional mapping of RGC to LGN. The firings of action potentials at LGN neuron due to IT were characterized by varying the stimulation parameters, morphological parameters and orientation. A wide range of stimulation parameters (stimulus amplitude, duration and frequency) represents the various strengths of the electrical stimulation with different morphological parameters (soma size, dendrites size and structure). The orientation (0-1800) of LGN neuron with respect to the stimulating electrode represents the angle at which the extracellular deep brain stimulation towards LGN neuron is performed. A reduced dendrite structure was used in the model using Bush–Sejnowski algorithm to decrease the computational time while conserving its input resistance and total surface area. The major finding is that an input potential of 0.4 V is required to produce the action potential in the LGN neuron which is placed at 100 µm distance from the electrode. From this study, it can be concluded that the neuroprostheses under design would need to consider the capability of inducing at least 0.4V to produce action potentials in LGN.

Keywords: Lateral Geniculate Nucleus, visual cortex, finite element, glaucoma, neuroprostheses

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Daniel Asiamah Ameyaw

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This research attempts to investigate how lecturer evaluation makes a difference in enhancing higher education teaching and learning processes. The research questions to guide this research work states first as, “What are the perspectives on the difference made by evaluating academic teachers in order to enhance higher education teaching and learning processes?” and second, “What are the implications of the findings for Policy and Practice?” Data for this research was collected mainly through interviewing and partly documents review. Data analysis was conducted under the framework of grounded theory. The findings showed that for individual lecturer level, lecturer evaluation provides a continuous improvement of teaching strategies, and serves as source of data for research on teaching. At the individual student level, it enhances students learning process; serving as source of information for course selection by students; and by making students feel recognised in the educational process. At the institutional level, it noted that lecturer evaluation is useful in personnel and management decision making; it assures stakeholders of quality teaching and learning by setting up standards for lecturers; and it enables institutions to identify skill requirement and needs as a basis for organising workshops. Lecturer evaluation is useful at national level in terms of guaranteeing the competencies of graduates who then provide the needed manpower requirement of the nation. Besides, it mentioned that resource allocation to higher educational institution is based largely on quality of the programmes being run by the institution. The researcher concluded, that the findings have implications for policy and practice, therefore, higher education managers are expected to ensure that policy is implemented as planned by policy-makers so that the objectives can successfully be achieved.

Keywords: academic quality, higher education, lecturer evaluation, teaching and learning processes

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Authors: Murtala Gada Abubakar, Aliyu T. Umar

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A substantial part of Nigeria is part of semi-arid areas of the world, underlain by basement complex (hard) rocks which are very poor in both transmission and storage of appreciable quantity of water. Recently, a growing attention is being paid on the need to develop water resources in these areas largely due to concerns about increasing droughts and the need to maintain water security challenges. While there is ample body of knowledge that captures the hydrological behaviours of the sedimentary part, reported research which unambiguously illustrates water distribution in the basement complex of the Sokoto basin remains sparse. Considering the growing need to meet the water requirements of those living in this region necessitated the call for accurate water balance estimations that can inform a sustainable planning and development to address water security challenges for the area. To meet this task, a one-dimensional soil water balance model was developed and utilised to assess the state of water distribution within the Sokoto basin basement complex using measured meteorological variables and information about different landscapes within the complex. The model simulated the soil water storage and rates of input and output of water in response to climate and irrigation where applicable using data from 2001 to 2010 inclusive. The results revealed areas within the Sokoto basin basement complex that are rich and deficient in groundwater resource. The high potential areas identified includes the fadama, the fractured rocks and the cultivated lands, while the low potential areas are the sealed surfaces and non-fractured rocks. This study concludes that the modelling approach is a useful tool for assessing the hydrological behaviour and for better understanding the water resource availability within a basement complex.

Keywords: basement complex, hydrological processes, Sokoto Basin, water security

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Authors: Sakulsri Srisaracam

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Social media has become an important source of information for the public and the media profession. Some social issues raised on social media are picked up by journalists to report on other platforms. This relationship between social media and mainstream media can sometimes drive public debate or stimulate social movements. The question to examine is in what situations can social media conversations raise awareness and stimulate change on public issues. This study addresses the communication patterns of social media conversations driving covert issues into mainstream media and leading to social advocacy movements. In methodological terms, the study findings are based on a content analysis of Facebook, Twitter, news websites and television media reports on three different case studies – saving Bryde’s whale, protests against a government proposal to downsize the Office of Knowledge Management and Development in Thailand, and a dengue fever campaign. These case studies were chosen because they represent issues that most members of the public do not pay much attention to but social media conversations stimulated public debate and calls to action. This study found: 1) Collective social media conversations can stimulate public debate and encourage change at three levels – awareness, public debate, and action of policy and social change. The level depends on the communication patterns of online users and media coverage. 2) Patterns of communication have to be designed to combine social media conversations, online opinion leaders, mainstream media coverage and call to both online and offline action to motivate social change. Thus, this result suggests that social media is a powerful platform for collective communication and setting the agenda on public issues for mainstream media. However, for social change to succeed, social media should be used to mobilize online movements to move offline too.

Keywords: public issues, mainstream media, social media, social movement

Procedia PDF Downloads 280