Search results for: opposition based learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31532

Search results for: opposition based learning

25322 Integrated Approach of Knowledge Economy and Society in the Perspective of Higher Education Institutions

Authors: S. K. Ashiquer Rahman

Abstract:

Innovation, sustainability, and higher education are vital issues of the knowledge economy and society. In fact, the concentration on these issues, educators and researchers convinced the learners to prepare productive citizens for the knowledge economy and society, and many initiatives have been launched worldwide. The concept of a knowledge economy requires simultaneous and balanced progress in three dimensions (Innovation, Education and Sustainability) which are totally interdependent and correlated. The paper discusses the importance of an integrated approach to the knowledge economy and society from the perspective of higher education institutions. It remarks on the advent of a knowledge-based economy and society and the need for the combination of Innovation, sustainability, and education. This paper introduces nine (9) important issues or challenges of higher education institutions that have emphasized, cross-linked each other, and combined in a new education system that can form a new generation for the completive world as well as able to manage the knowledge-based economy and societal system. Moreover, the education system must be the foundation for building the necessary knowledge-based economy and society, which must manage the innovation process through a more sustainable world. In this viewpoint, Innovation, sustainability and higher education are becoming more and more central in our economy and society, and it is directly associated with the possibility of global wealth distribution to the economy and society. The objective of this research is to demonstrate the knowledge-based economy and social paradigm in order to create the opportunity for higher education institutions' development. The paper uses the collective action methodologies to examine “the mechanisms and strategies” used by higher education institutions’ authority to accommodate an integrated pattern as per connecting behaviors of knowledge economy and society. The paper accomplishes that the combination of Innovation, sustainability and education is a very helpful approach to building a knowledge-based economy and society for practicing the higher education institution’s challenges.

Keywords: education, innovation, knowledge economy, sustainability

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25321 Information Technology and Business Alignments among Different Divisions: A Comparative Analysis of Japan and South Korea

Authors: Michiko Miyamoto

Abstract:

This paper empirically investigates whether information technology (IT) strategies, business strategies, and divisions are aligned to meet overall business goals for Korean Small and medium-sized enterprises (SMEs), based on structure based Strategic Alignment Model, and make comparison with those of Japanese SMEs. Using 2,869 valid responses of Korean Human Capital Corporate Panel survey, a result of this study suggests that Korean human resources (HR) departments have a major influence over IT strategy, which is the same as Japanese SMEs, even though their management styles are quite different. As for IT strategy, it is not related to other departments at all for Korean SMEs. The Korean management seems to possess a great power over each division, such as Sales/Service, Research and Development/Technical Experts, HR, and Production.

Keywords: IT-business alignment, structured based strategic alignment model, structural equation model, human resources department

Procedia PDF Downloads 256
25320 Performance Comparison of Thread-Based and Event-Based Web Servers

Authors: Aikaterini Kentroti, Theodore H. Kaskalis

Abstract:

Today, web servers are expected to serve thousands of client requests concurrently within stringent response time limits. In this paper, we evaluate experimentally and compare the performance as well as the resource utilization of popular web servers, which differ in their approach to handle concurrency. More specifically, Central Processing Unit (CPU)- and I/O intensive tests were conducted against the thread-based Apache and Go as well as the event-based Nginx and Node.js under increasing concurrent load. The tests involved concurrent users requesting a term of the Fibonacci sequence (the 10th, 20th, 30th) and the content of a table from the database. The results show that Go achieved the best performance in all benchmark tests. For example, Go reached two times higher throughput than Node.js and five times higher than Apache and Nginx in the 20th Fibonacci term test. In addition, Go had the smallest memory footprint and demonstrated the most efficient resource utilization, in terms of CPU usage. Instead, Node.js had by far the largest memory footprint, consuming up to 90% more memory than Nginx and Apache. Regarding the performance of Apache and Nginx, our findings indicate that Hypertext Preprocessor (PHP) becomes a bottleneck when the servers are requested to respond by performing CPU-intensive tasks under increasing concurrent load.

Keywords: apache, Go, Nginx, node.js, web server benchmarking

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25319 Data Science/Artificial Intelligence: A Possible Panacea for Refugee Crisis

Authors: Avi Shrivastava

Abstract:

In 2021, two heart-wrenching scenes, shown live on television screens across countries, painted a grim picture of refugees. One of them was of people clinging onto an airplane's wings in their desperate attempt to flee war-torn Afghanistan. They ultimately fell to their death. The other scene was the U.S. government authorities separating children from their parents or guardians to deter migrants/refugees from coming to the U.S. These events show the desperation refugees feel when they are trying to leave their homes in disaster zones. However, data paints a grave picture of the current refugee situation. It also indicates that a bleak future lies ahead for the refugees across the globe. Data and information are the two threads that intertwine to weave the shimmery fabric of modern society. Data and information are often used interchangeably, but they differ considerably. For example, information analysis reveals rationale, and logic, while data analysis, on the other hand, reveals a pattern. Moreover, patterns revealed by data can enable us to create the necessary tools to combat huge problems on our hands. Data analysis paints a clear picture so that the decision-making process becomes simple. Geopolitical and economic data can be used to predict future refugee hotspots. Accurately predicting the next refugee hotspots will allow governments and relief agencies to prepare better for future refugee crises. The refugee crisis does not have binary answers. Given the emotionally wrenching nature of the ground realities, experts often shy away from realistically stating things as they are. This hesitancy can cost lives. When decisions are based solely on data, emotions can be removed from the decision-making process. Data also presents irrefutable evidence and tells whether there is a solution or not. Moreover, it also responds to a nonbinary crisis with a binary answer. Because of all that, it becomes easier to tackle a problem. Data science and A.I. can predict future refugee crises. With the recent explosion of data due to the rise of social media platforms, data and insight into data has solved many social and political problems. Data science can also help solve many issues refugees face while staying in refugee camps or adopted countries. This paper looks into various ways data science can help solve refugee problems. A.I.-based chatbots can help refugees seek legal help to find asylum in the country they want to settle in. These chatbots can help them find a marketplace where they can find help from the people willing to help. Data science and technology can also help solve refugees' many problems, including food, shelter, employment, security, and assimilation. The refugee problem seems to be one of the most challenging for social and political reasons. Data science and machine learning can help prevent the refugee crisis and solve or alleviate some of the problems that refugees face in their journey to a better life. With the explosion of data in the last decade, data science has made it possible to solve many geopolitical and social issues.

Keywords: refugee crisis, artificial intelligence, data science, refugee camps, Afghanistan, Ukraine

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25318 A Robotic Cube to Preschool Children for Acquiring the Mathematical and Colours Concepts

Authors: Ahmed Amin Mousa, Tamer M. Ismail, M. Abd El Salam

Abstract:

This work presents a robot called Conceptual Robotic Cube, CR-Cube. The robot can be used as an educational tool for children from the age of three. It has a cube shape attached with a camera colours sensor. In addition, it contains four wheels to move smoothly. The researchers prepared a questionnaire to measure the efficiency of the robot. The design and the questionnaire was presented to 11 experts who agreed that the robot is appropriate for learning numbering and colours for preschool children.

Keywords: CR-Cube, robotic cube, conceptual robot, conceptual cube, colour concept, early childhood education

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25317 E-Hailing Taxi Industry Management Mode Innovation Based on the Credit Evaluation

Authors: Yuan-lin Liu, Ye Li, Tian Xia

Abstract:

There are some shortcomings in Chinese existing taxi management modes. This paper suggests to establish the third-party comprehensive information management platform and put forward an evaluation model based on credit. Four indicators are used to evaluate the drivers’ credit, they are passengers’ evaluation score, driving behavior evaluation, drivers’ average bad record number, and personal credit score. A weighted clustering method is used to achieve credit level evaluation for taxi drivers. The management of taxi industry is based on the credit level, while the grade of the drivers is accorded to their credit rating. Credit rating determines the cost, income levels, the market access, useful period of license and the level of wage and bonus, as well as violation fine. These methods can make the credit evaluation effective. In conclusion, more credit data will help to set up a more accurate and detailed classification standard library.

Keywords: credit, mobile internet, e-hailing taxi, management mode, weighted cluster

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25316 The Influence of Viscosifier Concentration on Rheological Properties of Invert Emulsion Mud

Authors: Suzan Ibrahim

Abstract:

Oil-based muds are the most regularly used rotary drilling methods in the oil and gas industry. However, they have a negative impact on the environment, which leads to restrictions of their application in many countries of the world. Consequently, looking for new eco-friendly alternative formulations of oil-based drilling fluids for the exploration of troublesome formations. As one of the developments of Novel formulation of environmentally friendly drilling fluids and investigation of the formulation for jatropha oil-based drilling fluid samples at different concentrations of viscosifiers such as low viscosity polyanionic cellulose (PAC- LV), high viscosity polyanionic cellulose (PAC-V) and local Egyptian bentonite. The oil-water ratio was taken as 70:30, which is beneficial in producing a low fluid loss. 15 drilling fluid samples were formulated different concentrations of bentonite, PAC- LV and PAC-V individually and their mud density, rheological properties, electrical stability and filtration loss properties were determined. The rheological performance showed at higher concentrations of viscosifier, the trend of viscosity increment of PAC performed in a similar way to bentonite. The best result of electrical stability by using the lowest concentration of viscosifier was achieved with PAC-V. The lowest fluid loss volumes were obtained by using the highest concentrations (4 g) of viscosifiers. Mud cake thickness of samples increased by using viscosifiers; however, a lower range was achieved compared to API specification. From the overall experiment, it can be concluded that as the concentrations of viscosifier increase, the viscosity trend increase in a similar way to both PAC-V and bentonite. But we must note that the PAC-V is a more environmentally friendly additive and a renewable resource, cheaper than bentonite and improves properties of eco-friendly OBMs well. It is a preferable choice for oil-based drilling fluids.

Keywords: invert emulsion mud, oil-based mud, rheological properties, viscosifier

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25315 Fuzzy Logic Based Ventilation for Controlling Harmful Gases in Livestock Houses

Authors: Nuri Caglayan, H. Kursat Celik

Abstract:

There are many factors that influence the health and productivity of the animals in livestock production fields, including temperature, humidity, carbon dioxide (CO2), ammonia (NH3), hydrogen sulfide (H2S), physical activity and particulate matter. High NH3 concentrations reduce feed consumption and cause daily weight gain. At high concentrations, H2S causes respiratory problems and CO2 displace oxygen, which can cause suffocation or asphyxiation. Good air quality in livestock facilities can have an impact on the health and well-being of animals and humans. Air quality assessment basically depends on strictly given limits without taking into account specific local conditions between harmful gases and other meteorological factors. The stated limitations may be eliminated. using controlling systems based on neural networks and fuzzy logic. This paper describes a fuzzy logic based ventilation algorithm, which can calculate different fan speeds under pre-defined boundary conditions, for removing harmful gases from the production environment. In the paper, a fuzzy logic model has been developed based on a Mamedani’s fuzzy method. The model has been built on MATLAB software. As the result, optimum fan speeds under pre-defined boundary conditions have been presented.

Keywords: air quality, fuzzy logic model, livestock housing, fan speed

Procedia PDF Downloads 357
25314 Classification of Emotions in Emergency Call Center Conversations

Authors: Magdalena Igras, Joanna Grzybowska, Mariusz Ziółko

Abstract:

The study of emotions expressed in emergency phone call is presented, covering both statistical analysis of emotions configurations and an attempt to automatically classify emotions. An emergency call is a situation usually accompanied by intense, authentic emotions. They influence (and may inhibit) the communication between caller and responder. In order to support responders in their responsible and psychically exhaustive work, we studied when and in which combinations emotions appeared in calls. A corpus of 45 hours of conversations (about 3300 calls) from emergency call center was collected. Each recording was manually tagged with labels of emotions valence (positive, negative or neutral), type (sadness, tiredness, anxiety, surprise, stress, anger, fury, calm, relief, compassion, satisfaction, amusement, joy) and arousal (weak, typical, varying, high) on the basis of perceptual judgment of two annotators. As we concluded, basic emotions tend to appear in specific configurations depending on the overall situational context and attitude of speaker. After performing statistical analysis we distinguished four main types of emotional behavior of callers: worry/helplessness (sadness, tiredness, compassion), alarm (anxiety, intense stress), mistake or neutral request for information (calm, surprise, sometimes with amusement) and pretension/insisting (anger, fury). The frequency of profiles was respectively: 51%, 21%, 18% and 8% of recordings. A model of presenting the complex emotional profiles on the two-dimensional (tension-insecurity) plane was introduced. In the stage of acoustic analysis, a set of prosodic parameters, as well as Mel-Frequency Cepstral Coefficients (MFCC) were used. Using these parameters, complex emotional states were modeled with machine learning techniques including Gaussian mixture models, decision trees and discriminant analysis. Results of classification with several methods will be presented and compared with the state of the art results obtained for classification of basic emotions. Future work will include optimization of the algorithm to perform in real time in order to track changes of emotions during a conversation.

Keywords: acoustic analysis, complex emotions, emotion recognition, machine learning

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25313 Approach Based on Fuzzy C-Means for Band Selection in Hyperspectral Images

Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

Abstract:

Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: band selection, fuzzy c-means, k-means, hyperspectral image

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25312 Assessing the Efficacy of Artificial Intelligence Integration in the FLO Health Application

Authors: Reema Alghamdi, Rasees Aleisa, Layan Sukkar

Abstract:

The primary objective of this research is to conduct an examination of the Flo menstrual cycle application. We do that by evaluating the user experience and their satisfaction with integrated AI features. The study seeks to gather data from primary resources, primarily through surveys, to gather different insights about the application, like its usability functionality in addition to the overall user satisfaction. The focus of our project will be particularly directed towards the impact and user perspectives regarding the integration of artificial intelligence features within the application, contributing to an understanding of the holistic user experience.

Keywords: period, women health, machine learning, AI features, menstrual cycle

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25311 Lyapunov-Based Tracking Control for Nonholonomic Wheeled Mobile Robot

Authors: Raouf Fareh, Maarouf Saad, Sofiane Khadraoui, Tamer Rabie

Abstract:

This paper presents a tracking control strategy based on Lyapunov approach for nonholonomic wheeled mobile robot. This control strategy consists of two levels. First, a kinematic controller is developed to adjust the right and left wheel velocities. Using this velocity control law, the stability of the tracking error is guaranteed using Lyapunov approach. This kinematic controller cannot be generated directly by the motors. To overcome this problem, the second level of the controllers, dynamic control, is designed. This dynamic control law is developed based on Lyapunov theory in order to track the desired trajectories of the mobile robot. The stability of the tracking error is proved using Lupunov and Barbalat approaches. Simulation results on a nonholonomic wheeled mobile robot are given to demonstrate the feasibility and effectiveness of the presented approach.

Keywords: mobile robot, trajectory tracking, Lyapunov, stability

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25310 Poly(N-Vinylcaprolactam) Based Degradable Microgels for Controlled Drug Delivery

Authors: G. Agrawal, R. Agrawal, A. Pich

Abstract:

The pH and temperature responsive biodegradable poly(N-vinylcaprolactam) (PVCL) based microgels functionalized with itaconic acid (IA) units are prepared via precipitation polymerization for drug delivery applications. Volume phase transition temperature (VPTT) of the obtained microgels is influenced by both IA content and pH of the surrounding medium. The developed microgels can be degraded under acidic conditions due to the presence of hydrazone based crosslinking points inside the microgel network. The microgel particles are able to effectively encapsulate doxorubicin (DOX) drug and exhibit low drug leakage under physiological conditions. At low pH, rapid DOX release is observed due to the changes in electrostatic interactions along with the degradation of particles. The results of the cytotoxicity assay further display that the DOX-loaded microgel exhibit effective antitumor activity against HeLa cells demonstrating their great potential as drug delivery carriers for cancer therapy.

Keywords: degradable, drug delivery, hydrazone linkages, microgels, responsive

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25309 Organisationmatcher: An Organisation Ranking System for Student Placement Using Preference Weights

Authors: Nor Sahida Ibrahim, Ruhaila Maskat, Aishah Ahmad

Abstract:

Almost all tertiary-level students will undergo some form of training in organisations prior to their graduation. This practice provides the necessary exposure and experience to allow students to cope with actual working environment and culture in the future. Nevertheless, a particular degree of “matching” between what is expected and what can be offered between students and organisations underpins how effective and enriching the experience is. This matching of students and organisations is challenging when preferences from both parties must be satisfied. This work developed a web-based system, namely the OrganisationMatcher, which leverage on the use of preference weights to score each organisation and rank them based on “suitability”. OrganisationMatcher has been implemented on a relational database, designed using object-oriented methods and developed using PHP programming language for browser front-end access. We outline the challenges and limitations of our system and discuss future improvements to the system, specifically in the utilisation of intelligent methods.

Keywords: student industrial placement, information system, web-based, ranking

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25308 Inappropriate Effects Which the Use of Computer and Playing Video Games Have on Young People

Authors: Maja Ruzic-Baf, Mirjana Radetic-Paic

Abstract:

The use of computers by children has many positive aspects, including the development of memory, learning methods, problem-solving skills and the feeling of one’s own competence and self-confidence. Playing on line video games can encourage hanging out with peers having similar interests as well as communication; it develops coordination, spatial relations and presentation. On the other hand, the Internet enables quick access to different information and the exchange of experiences. How kids use computers and what the negative effects of this can be depends on various factors. ICT has improved and become easy to get for everyone. In the past 12 years so many video games has been made even to that level that some of them are free to play. Young people, even some adults, had simply start to forget about the real outside world because in that other, digital world, they have found something that makes them feal more worthy as a man. This article present the use of ICT, forms of behavior and addictions to on line video games. The use of computers by children has many positive aspects, including the development of memory, learning methods, problem-solving skills and the feeling of one’s own competence and self-confidence. Playing on line video games can encourage hanging out with peers having similar interests as well as communication; it develops coordination, spatial relations and presentation. On the other hand, the Internet enables quick access to different information and the exchange of experiences. How kids use computers and what the negative effects of this can be depends on various factors. ICT has improved and become easy to get for everyone. In the past 12 years so many video games has been made even to that level that some of them are free to play. Young people, even some adults, had simply start to forget about the real outside world because in that other, digital world, they have found something that makes them feal more worthy as a man. This article present the use of ICT, forms of behavior and addictions to on line video games.

Keywords: addiction to video games, behaviour, ICT, young people

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25307 A High Efficiency Reduced Rules Neuro-Fuzzy Based Maximum Power Point Tracking Controller for Photovoltaic Array Connected to Grid

Authors: Lotfi Farah, Nadir Farah, Zaiem Kamar

Abstract:

This paper achieves a maximum power point tracking (MPPT) controller using a high-efficiency reduced rules neuro-fuzzy inference system (HE2RNF) for a 100 kW stand-alone photovoltaic (PV) system connected to the grid. The suggested HE2RNF based MPPT seeks the optimal duty cycle for the boost DC-DC converter, making the designed PV system working at the maximum power point (MPP), then transferring this power to the grid via a three levels voltage source converter (VSC). PV current variation and voltage variation are chosen as HE2RNF-based MPPT controller inputs. By using these inputs with the duty cycle as the only single output, a six rules ANFIS is generated. The high performance of the proposed HE2RNF numerically in the MATLAB/Simulink environment is shown. The 0.006% steady-state error, 0.006s of tracking time, and 0.088s of starting time prove the robustness of this six reduced rules against the widely used twenty-five ones.

Keywords: PV, MPPT, ANFIS, HE2RNF-based MPPT controller, VSC, grid connection

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25306 Comparison and Description of Enhanced Department-Based Arc Flash Safety Assessment with Substation-Based Arc Flash Safety Assessment for the Improvement of Work Place Safety

Authors: Md. Abid Khan

Abstract:

Arc Flash safety assessment is a critical component for continuous improvement of any company’s safe electrical arc flash standard (SEAFS). The standard requires periodic internal or external audits to verify compliance and assess implementation. Assessments will identify strengths and opportunities for improvement, and serve as the basis for corrective actions. An arc flash safety assessment is comprised of a review of any existing safe electrical arc flash standard documentation (e.g., such as work procedures or other supporting documents), onsite interviews, and observations (e.g., facility inspections and work task observations). Substation-based arc flash assessment is very popular as it is more specific for each substation. The enhanced department-based arc flash safety assessment will shift focus to more effective hazard control measures and emphasis will be placed on highlighting inherently unsafe equipment to support resolution actions by facility management, rather than relying on lessor effective control methods in the hierarchy of controls currently deployed at a number of facilities.

Keywords: assessment, remote racking device (RRD), key performance indicator (KPI), personal protective equipment (PPE), operation & maintenance (O&M), safety management system (SMS), safe electrical arc flash standard (SEAFS)

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25305 Attention-Based Spatio-Temporal Approach for Fire and Smoke Detection

Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

Abstract:

In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

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25304 Process Optimization of Electrospun Fish Sarcoplasmic Protein Based Nanofibers

Authors: Sena Su, Burak Ozbek, Yesim M. Sahin, Sevil Yucel, Dilek Kazan, Faik N. Oktar, Nazmi Ekren, Oguzhan Gunduz

Abstract:

In recent years, protein, lipid or polysaccharide-based polymers have been used in order to develop biodegradable materials and their chemical nature determines the physical properties of the resulting films. Among these polymers, proteins from different sources have been extensively employed because of their relative abundance, film forming ability, and nutritional qualities. In this study, the biodegradable composite nanofiber films based on fish sarcoplasmic protein (FSP) were prepared via electrospinning technique. Biodegradable polycaprolactone (PCL) was blended with the FSP to obtain hybrid FSP/PCL nanofiber mats with desirable physical properties. Mixture solutions of FSP and PCL were produced at different concentrations and their density, viscosity, electrical conductivity and surface tension were measured. Mechanical properties of electrospun nanofibers were evaluated. Morphology of composite nanofibers was observed using scanning electron microscopy (SEM). Moreover, Fourier transform infrared spectrometer (FTIR) studies were used for analysis chemical composition of composite nanofibers. This study revealed that the FSP based nanofibers have the potential to be used for different applications such as biodegradable packaging, drug delivery, and wound dressing, etc.

Keywords: edible film, electrospinning, fish sarcoplasmic protein, nanofiber

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25303 Inclusive, Just and Effective Transition: Comparing Market-Based and Redistributive Approaches to Sustainability

Authors: Karen Bell

Abstract:

While there is broad agreement among governments and civil society globally about the need to develop more sustainable societies, the best way to achieve this is still contested. In particular, there are differences regarding whether to continue to implement market-based approaches or to move to alternative redistributive-based approaches. In this paper, ‘Green Economy’ and ‘Living Well’ strategies are compared as examples of these two different strategies for achieving social, ecological and economic sustainability. The paper is based on a 3-year ESRC funded project on transitions to sustainability which examines the implementation of the ‘Green Economy’ paradigm in South Korea and the 'Living Well' paradigm in Bolivia. As well as outlining and analysing secondary data, the paper also draws on over 100 interviews with a range of local stakeholders in these countries carried out by the author between and including 2016 and 2018. The work indicates that the Living Well paradigm seems to better integrate social, ecological and economic concerns and may better deliver sustainability in the time frame necessary than the dominant Green Economy paradigm. This seems to be primarily because Living Well emphasises redistribution to reduce inequality and ensure human needs are met; living in harmony with nature, taking into account natural limits and cycles; respecting traditional values and practices where these support sustainability and human well-being; sovereignty and local control of natural resources; and participative decision-making, based on grassroots community organising. It is, therefore, argued that to achieve inclusive, just and effective transitions to sustainability we should aim to foster equality, respect planetary limits, build on local traditions, bring resources into public ownership and enhance participatory democracy. This will require a radically different approach to that offered within the market-based agenda currently dominating global sustainability debates and activities.

Keywords: environmental transition, green economy, inclusive sustainability, living well, sustainable transition

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25302 Artificial Intelligence Models for Detecting Spatiotemporal Crop Water Stress in Automating Irrigation Scheduling: A Review

Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

Abstract:

Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

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25301 Comparative Techno-Economic Assessment and LCA of Selected Integrated Sugarcane-Based Biorefineries

Authors: Edgard Gnansounoua, Pavel Vaskan, Elia Ruiz Pachón

Abstract:

This work addresses the economic and environmental performance of integrated biorefineries based on sugarcane juice and residues in the context of Brazil. We have considered four multiproduct scenarios; two from existing Brazilian sugar mills and the others from ethanol autonomous distilleries. They are integrated biorefineries producing first (1G) and second (2G) generation ethanol, sugar, molasses (for animal feed) and electricity. We show the results for the analysis and comparison of the different scenarios using a techno-economic value-based approach and LCA methodology. We have found that all the analysed scenarios show positive values of Climate change and Fossil depletion reduction as compared to the reference systems. However the scenario producing only ethanol shows less efficiency in Human toxicity, Freshwater ecotoxicity and Freshwater eutrophication impacts. The best economic configuration is provided by the scenario with the largest ethanol production. On the other hand, the best environmental performance is presented by the scenario with full integration sugar – 1G2G ethanol production. The integration of 2G based residues in a 1G ethanol production plant leads to positive environmental impacts compared to the conventional 1G industrial plant but proves to be more expensive.

Keywords: sugarcane, biorefinery, 1G/2G bioethanol integration, LCA, Brazil

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25300 Halal Authentication for Some Product Collected from Jordanian Market Using Real-Time PCR

Authors: Omar S. Sharaf

Abstract:

The mitochondrial 12s rRNA (mt-12s rDNA) gene for pig-specific was developed to detect material from pork species in different products collected from Jordanian market. The amplification PCR products of 359 bp and 531 bp were successfully amplified from the cyt b gene of pig the amplification product using mt-12S rDNA gene were successfully produced a single band with a molecular size of 456 bp. In the present work, the PCR amplification of mtDNA of cytochrome b has been shown as a suitable tool for rapid detection of pig DNA. 100 samples from different dairy, gelatin and chocolate based products and 50 samples from baby food formula were collected and tested to a presence of any pig derivatives. It was found that 10% of chocolate based products, 12% of gelatin and 56% from dairy products and 5.2% from baby food formula showed single band from mt-12S rDNA gene.

Keywords: halal food, baby infant formula, chocolate based products, PCR, Jordan

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25299 Research on Urban Carbon Reduction Strategy Based on Sponge City: Chongqing Caijia New Town as an Example

Authors: Shitong Wang

Abstract:

As an ecologically oriented urban development model, Sponge City is an important technical system that responds to the requirements of the "double carbon" policy and promotes the transformation of urban low-carbonization. Based on this, this paper constructs a sponge city carbon reduction model based on domestic and international carbon reduction studies and constructs a sponge city carbon reduction model at the theoretical level based on the sponge city carbon reduction mechanism at the four levels of a global scale, district scale, community scale, and indicator system; at the practical level, the theoretical model is located in the urban scale and neighborhood scale of Caijia New Town in Chongqing. At the urban scale, the Caijia Sponge City special planning is carried out in four aspects: sponge City spatial pattern, low-impact development facility system, low-carbon community, and control index system. At the neighborhood scale, GIS is used for ecological sensitivity evaluation and hydrological analysis, based on which the spatial pattern optimization design is carried out from the three aspects of water catchment unit division, index system construction, and sponge facility spatial planning. Through the design practice of Chongqing Caijia New City, it is helpful to verify the carbon reduction benefits of the sponge city carbon reduction model, guide Caijia New City to realize low-carbon development, and provide a reference for other cities in China to realize the "dual-carbon" transformation.

Keywords: Sponge City, low carbon city, carbon emission reduction pathway, Chongqing

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25298 A Smart Sensor Network Approach Using Affordable River Water Level Sensors

Authors: Dian Zhang, Brendan Heery, Maria O’Neill, Ciprian Briciu-Burghina, Noel E. O’Connor, Fiona Regan

Abstract:

Recent developments in sensors, wireless data communication and the cloud computing have brought the sensor web to a whole new generation. The introduction of the concept of ‘Internet of Thing (IoT)’ has brought the sensor research into a new level, which involves the developing of long lasting, low cost, environment friendly and smart sensors; new wireless data communication technologies; big data analytics algorithms and cloud based solutions that are tailored to large scale smart sensor network. The next generation of smart sensor network consists of several layers: physical layer, where all the smart sensors resident and data pre-processes occur, either on the sensor itself or field gateway; data transmission layer, where data and instructions exchanges happen; the data process layer, where meaningful information is extracted and organized from the pre-process data stream. There are many definitions of smart sensor, however, to summarize all these definitions, a smart sensor must be Intelligent and Adaptable. In future large scale sensor network, collected data are far too large for traditional applications to send, store or process. The sensor unit must be intelligent that pre-processes collected data locally on board (this process may occur on field gateway depends on the sensor network structure). In this case study, three smart sensing methods, corresponding to simple thresholding, statistical model and machine learning based MoPBAS method, are introduced and their strength and weakness are discussed as an introduction to the smart sensing concept. Data fusion, the integration of data and knowledge from multiple sources, are key components of the next generation smart sensor network. For example, in the water level monitoring system, weather forecast can be extracted from external sources and if a heavy rainfall is expected, the server can send instructions to the sensor notes to, for instance, increase the sampling rate or switch on the sleeping mode vice versa. In this paper, we describe the deployment of 11 affordable water level sensors in the Dublin catchment. The objective of this paper is to use the deployed river level sensor network at the Dodder catchment in Dublin, Ireland as a case study to give a vision of the next generation of a smart sensor network for flood monitoring to assist agencies in making decisions about deploying resources in the case of a severe flood event. Some of the deployed sensors are located alongside traditional water level sensors for validation purposes. Using the 11 deployed river level sensors in a network as a case study, a vision of the next generation of smart sensor network is proposed. Each key component of the smart sensor network is discussed, which hopefully inspires the researchers who are working in the sensor research domain.

Keywords: smart sensing, internet of things, water level sensor, flooding

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25297 The Linear Combination of Kernels in the Estimation of the Cumulative Distribution Functions

Authors: Abdel-Razzaq Mugdadi, Ruqayyah Sani

Abstract:

The Kernel Distribution Function Estimator (KDFE) method is the most popular method for nonparametric estimation of the cumulative distribution function. The kernel and the bandwidth are the most important components of this estimator. In this investigation, we replace the kernel in the KDFE with a linear combination of kernels to obtain a new estimator based on the linear combination of kernels, the mean integrated squared error (MISE), asymptotic mean integrated squared error (AMISE) and the asymptotically optimal bandwidth for the new estimator are derived. We propose a new data-based method to select the bandwidth for the new estimator. The new technique is based on the Plug-in technique in density estimation. We evaluate the new estimator and the new technique using simulations and real-life data.

Keywords: estimation, bandwidth, mean square error, cumulative distribution function

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25296 Performance Evaluation of an Ontology-Based Arabic Sentiment Analysis

Authors: Salima Behdenna, Fatiha Barigou, Ghalem Belalem

Abstract:

Due to the quick increase in the volume of Arabic opinions posted on various social media, Arabic sentiment analysis has become one of the most important areas of research. Compared to English, there is very little works on Arabic sentiment analysis, in particular aspect-based sentiment analysis (ABSA). In ABSA, aspect extraction is the most important task. In this paper, we propose a semantic aspect-based sentiment analysis approach for standard Arabic reviews to extract explicit aspect terms and identify the polarity of the extracted aspects. The proposed approach was evaluated using HAAD datasets. Experiments showed that the proposed approach achieved a good level of performance compared with baseline results. The F-measure was improved by 19% for the aspect term extraction tasks and 55% aspect term polarity task.

Keywords: sentiment analysis, opinion mining, Arabic, aspect level, opinion, polarity

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25295 Reducing Support Structures in Design for Additive Manufacturing: A Neural Networks Approach

Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

Abstract:

This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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25294 Women Executives: A Panacea to Incessant Sexual Assaults in Higher Institutions, Federal Polytechnic Nekede Imo State Nigeria as a Case Study

Authors: Ujunma Nnenna Egbuawa

Abstract:

Rape or sexual assault is a hideous crime of violence done predominantly to women and occasionally to men. In institutions of higher learning, it’s mostly experienced within or outside the campus environment due to students who are from different backgrounds socially. These students also have been imbibed with conflicting ethical standards, thus act both morally and amoral with respect to their sexual urges. The most affected among these are the female students who live outside the campus environment that is suitable for any immoral activity. These female students that are victims of rape hardly would want to be identified and this has left them as habitual prey to the unsuspecting predators. The socio-cultural setting has also been a contributory factor to the psychological and physical damage these victims face throughout their time of study as female rape victims. This is an empirical study designed to elicit information from students of Federal Polytechnic Nekede Owerri Imo State Nigeria on whether they have been sexually assaulted or raped and how they handled it thereafter. This institution was used as a case study because the provost of this tertiary institution is a woman whose name is Dr( Mrs ) C.U Njoku who has made consented efforts to ensure these rape victims rise above the social stigma associated with it. This rector has also put in some measures to bring about a decline in cases of rape within and outside the campus environment. She also granted the researcher an oral interview on how she has been able to achieve these and the challenges she hitherto faced in the process. Three research questions and a hypothesis guided the study. Samples of 119 students were used and stratification was done for sex, age and the academic level of the students. 14 item questionnaires were used and data generated from the survey were analyzed using percentages. This workshop would engage the participants by investigating some courses that may help in declining the rate of rape cases within a campus. Also, necessary measures that would be taken to help in sensitizing the tertiary institutions in areas that can aid the healing procedures of these victims. The need also for guidance and counseling unit is also a necessity for the psychological survival of these rape victims. As a result, the participants would gain an increased awareness of the influence of rape and sexual assault on campus. There ought to be a paradigm shift in institutions of higher learning in policies, administrative decisions and introduction of courses that will uplift ethical standards in order to bring about a change both locally and globally.

Keywords: institutions, psychological, sexual assault, socio-cultural

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25293 Parents' Attitudes towards a School-Based Family Program in Early Literacy in Qatari Preschool Settings

Authors: Fathi Ihmeideh

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The study aimed at investigating parents’ attitudes towards a school-based family program in developing kindergarten children’s literacy skills. The study surveyed 160 parents of preschool children, gathering information about their attitudes toward the development of children’s early literacy. Results indicated that parents hold positive attitudes towards the school-based family literacy program. The results also revealed statistically significant differences among parents due to a number of study variables. The study concludes with putting forward a number of practical and theoretical recommendations for the field of study. Acknowledgment: This paper was made possible by NPRP grant # (NPRP 8-921-5-122) from the Qatar national research fund (a member of Qatar foundation). The statements made herein are solely the responsibility of the authors.

Keywords: parents, literacy development, preschool children, family involvement

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