Search results for: automatic question generator

Authors: Labane Chrif

Abstract:

A nonlinear approach to the automatic pitch attitude control problem for aircraft transportation is presented. A nonlinear model describing the longitudinal equations of motion in strict feedback form is derived. Backstepping is utilized for the construction of a globally stabilizing controller with a number of free design parameters. The controller is evaluated using the aircraft transportation. The adaptation scheme proposed allowed us to design an explicit controller with a minimal knowledge of the aircraft aerodynamics. Finally, the simulation results will show that backstepping controller have better dynamic performance, simpler design, higher precision, easier implement, etc. At the same time, the control effect will be significantly improved. In addition, backstepping control is superior in short transition, good stability, anti-disturbance and good control.

Keywords: nonlinear control, backstepping, aircraft control, Lyapunov function, longitudinal model

Procedia PDF Downloads 578

Authors: Kuei-Chun Liu, Yu-Yu Lai, Ching-Hong Wu

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A good automated testing tool could reduce as much as possible the manual work done by testers. Traditional record-replay testing tool provides an automated testing solution by recording mouse coordinates as test scripts, but it will be easily broken if any change of resolutions. Therefore, more and more testers design multiple test scripts to automate the testing process for different devices. In order to improve the traditional record-replay approach and reduce the effort that the testers spending on writing test scripts, we propose an approach for generating the Android application test scripts based on accessibility service without connecting to a computer. This approach simulates user input actions and replays them correctly even at the different conditions such as the internet connection is unstable when the device under test, the different resolutions on Android devices. In this paper, we describe how to generate test scripts automatically and make a comparison with existing tools for Android such as Robotium, Appium, UIAutomator, and MonkeyTalk.

Keywords: accessibility service, Appium, automated testing, MonkeyTalk, Robotium, testing, UIAutomator

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Authors: Oktay Cinar

Abstract:

The aim of this study is to investigate the acquisition of Overt Pronoun Constraint (OPC) by adult Korean L2 Turkish speakers in order to find out how constraints regulating the syntax of null and overt subjects are acquired. OPC is claimed to be a universal feature of all null subject languages restricting the co-indexation between overt embedded pronoun and quantified or wh-question antecedents. However, there is no such restriction when the embedded subject is null or the antecedent is a referential subject. Considered as a principle of Universal Grammar (UG), OPC knowledge of L2 speakers has been widely tested with different language pairs. In the light of previous studies on OPC, it can be argued that L2 learners display early sensitivity to OPC constraints during their interlanguage grammar development. Concerning this, the co-indexation between overt embedded pronoun o (third person pronoun) and referential matrix subject is claimed to be controversial in Turkish, which poses problems with the universality of OPC. However, the current study argues against this claim by providing evidence from advanced Korean speakers that OPC is universal to all null subject languages and OPC knowledge can be accessed with direct access to UG. In other words, the performances of adult Korean speakers on the syntax of null and overt subjects are tested to support this claim. In order to test this, OPC task is used. 15 advanced speakers and a control group of adult native Turkish participants are instructed to determine the co-reference relationship between the subject of embedded clause, either overt pronominal o or null, and the subject of the matrix clause, either quantified pronoun and wh-question or referential antecedent. They are asked to select the interpretation of the embedded subject, either as the same person as in the matrix subject or another person who is not the same person in the matrix subject. These relations are represented with four conditions, and each condition has four questions (16 questions in total). The results claim that both control group and Korean L2 Turkish speakers display sensitivity to all constraints that OPC has, which suggests that OPC works in Turkish as well.

Keywords: adult Korean speakers, binding theory, generative second language acquisition, overt pronoun constraint

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Authors: Meshandren Naidoo

Abstract:

An artificial intelligence (AI) system named DABUS 2021 made headlines when it became the very first AI system to be listed in a patent which was then granted by the South African patent office. This grant raised much criticism. The question that this research intends to answer is (1) whether, in South African patent law, an AI can be an inventor. This research finds that despite South African law not recognizing an AI as a legal person and despite the legislation not explicitly allowing AI to be inventors, a legal interpretative exercise would allow AI inventorship.

Keywords: artificial intelligence, creativity, innovation, law

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Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

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Automatic text classification applies mostly natural language processing (NLP) and other AI-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: machine learning, text classification, NLP techniques, semantic representation

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Authors: B. Garfolo, L. Kelpsh, R. Roak, R. Kuck

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Often, student ratings of instructors play a significant role in the career path of an instructor in higher education. So then, how does a student view the effectiveness of instructor teaching? This question has been address by literally thousands of studies found in the literature. Yet, why does this question still persist? A literature review reveals that while it is true that student evaluations of instructors can be biased, there is still a considerable amount of work that needs to be done in understanding why. As student evaluations of instructors can be used in a variety of settings (formative or summative) it is critical to understand the nature of the bias. The authors believe that not only is some bias possible in student evaluations, it should be expected for the simple reason that a student evaluation is a human activity and as such, relies upon perception and interpersonal judgment. As such, student ratings are affected by the same factors that can potentially affect any rater’s judgment, such as stereotypes based on gender, culture, race, etc. Previous study findings suggest that student evaluations of teacher effectiveness differ between male and female raters. However, even though studies have shown that instructor gender does play an important role in influencing student ratings, the exact nature and extent of that role remains the subject of debate. Researchers, in their attempt to define good teaching, have looked for differences in student evaluations based on a variety of characteristics such as course type, class size, ability level of the student and grading practices in addition to instructor and student characteristics (gender, age, etc.) with inconsistent results. If a student evaluation represents more than an instructor’s teaching ability, for example, a physical characteristic such as gender, then this information must be taken into account if the evaluation is to have meaning with respect to instructor assessment. While the authors concede that it is difficult or nearly impossible to separate gender from student perception of teaching practices in person, it is, however, possible to shield an instructor’s gender identity with respect to an online teaching experience. The online teaching modality presents itself as a unique opportunity to experiment directly with gender identity. The analysis of the differences of online behavior of individuals when they perceive that they are interacting with a male or female could provide a wealth of data on how gender influences student perceptions of teaching effectiveness. Given the importance of the role student ratings play in hiring, retention, promotion, tenure, and salary deliberations in academic careers, this question warrants further attention as it is important to be aware of possible bias in student evaluations if they are to be used at all with respect to any academic considerations. For experimental purposes, the author’s constructed and online class where each instructors operate under two different gender identities. In this study, each instructor taught multiple sections of the same class using both a male identity and a female identity. The study examined student evaluations of teaching based on certain student and instructor characteristics in order to determine if and where male and female students might differ in their ratings of instructors based on instructor gender. Additionally, the authors examined if there are differences between undergraduate and graduate students' ratings with respect to the experimental criteria.

Keywords: gender bias, ethics, student evaluations, student perceptions, online instruction

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Authors: M. Barański

Abstract:

This paper presents a several diagnostic methods designed to electrical machines especially for permanent magnets (PM) machines. Those machines are commonly used in small wind and water systems and vehicles drives. Those methods are preferred by the author in periodic diagnostic of electrical machines. The special attention should be paid to diagnostic method of turn-to-turn insulation and vibrations. Both of those methods were created in Institute of Electrical Drives and Machines Komel. The vibration diagnostic method is the main thesis of author’s doctoral dissertation. This is method of determination the technical condition of PM electrical machine basing on its own signals is the subject of patent application No P.405669. Specific structural properties of machines excited by permanent magnets are used in this method - electromotive force (EMF) generated due to vibrations. There was analysed number of publications which describe vibration diagnostic methods and tests of electrical machines with permanent magnets and there was no method found to determine the technical condition of such machine basing on their own signals.

Keywords: electrical vehicle, generator, main insulation, permanent magnet, thermography, turn-to-traction drive, turn insulation, vibrations

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Authors: Adi A. Maaita, Hamza A. A. Al Sewadi

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One of the crucial parameters of digital cryptographic systems is the selection of the keys used and their distribution. The randomness of the keys has a strong impact on the system’s security strength being difficult to be predicted, guessed, reproduced or discovered by a cryptanalyst. Therefore, adequate key randomness generation is still sought for the benefit of stronger cryptosystems. This paper suggests an algorithm designed to generate and test pseudo random number sequences intended for cryptographic applications. This algorithm is based on mathematically manipulating a publically agreed upon information between sender and receiver over a public channel. This information is used as a seed for performing some mathematical functions in order to generate a sequence of pseudorandom numbers that will be used for encryption/decryption purposes. This manipulation involves permutations and substitutions that fulfills Shannon’s principle of “confusion and diffusion”. ASCII code characters wereutilized in the generation process instead of using bit strings initially, which adds more flexibility in testing different seed values. Finally, the obtained results would indicate sound difficulty of guessing keys by attackers.

Keywords: cryptosystems, information security agreement, key distribution, random numbers

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Authors: Shrabani Ghosh

Abstract:

Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Meshandren Naidoo

Abstract:

An artificial intelligence (AI) system named DABUS 2021 made headlines when it became the very first AI system to be listed in a patent which was then granted by the South African patent office. This grant raised much criticism. The question that this research intends to answer is (1) whether, in South African patent law, an AI can be an inventor. This research finds that despite South African law not recognising an AI as a legal person and despite the legislation not explicitly allowing AI to be inventors, a legal interpretative exercise would allow AI inventorship.

Keywords: artificial intelligence, intellectual property, inventorship, patents

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Authors: Ibrahim Ozkan

Abstract:

In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.

Keywords: cooperative network, adaptive modulation and coding, hybrid ARQ, correlated fading

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Authors: T. Iakovleva

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Present paper suggests a theoretical model that describes the process of the development of responsible innovations on the firm level in health and welfare sectors. There is a need to develop new firm strategies in these sectors. This paper suggests to look on the concept of responsible innovation that was originally developed on the social level and to apply this new concept to the new area of firm strategy. The rapid global diffusion of information and communication technologies has greatly improved access to knowledge. At the same time, communication is cheap, information is a commodity, and global trade increases technological diffusion. As a result, firms and users, including those outside of industrialized nations, get early exposure to the latest technologies and information. General-purpose technologies such as mobile phones and 3D printers enable individuals to solve local needs and customize products. The combined effect of these changes is having a profound impact on the innovation landscape. Meanwhile, the healthcare sector is facing unprecedented challenges, which are magnified by budgetary constraints, an aging population and the desire to provide care for all. On the other hand, patients themselves are changing. They are savvier about their diseases, they expect their relation with the healthcare professionals to be open and interactive, but above all they want to be part of the decision process. All of this is a reflection of what is already happening in other industries where customers have access to large amount of information and became educated buyers. This article addresses the question of how ICT research and innovation may contribute to developing solutions to grand societal challenges in a responsible way. A broad definition of the concept of responsibility in the context of innovation is adopted in this paper. Responsibility is thus seen as a collective, uncertain and future-oriented activity. This opens the questions of how responsibilities are perceived and distributed and how innovation and science can be governed and stewarded towards socially desirable and acceptable ends. This article addresses a central question confronting politicians, business leaders, and regional planners.

Keywords: responsible innovation, ICT, healthcare, welfare sector

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Authors: Jurijs Salijevs, Katrina Bolocko

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The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

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Authors: Zhongfei Cai, Hui He, Changsheng Li

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This paper studied in the automatic repeat request (ARQ) transmission technique in Mars detection telecommunications system. An ARQ method applied to proximity-1 space link protocol was proposed by this paper. In order to ensure the efficiency of data reliable transmission, this ARQ method combined these different ARQ maneuvers characteristics. Considering the Mars detection communication environments, this paper analyzed the characteristics of the saturation throughput rate, packet dropping probability, average delay and energy efficiency with different ARQ algorithms. Combined thus results with the theories of ARQ transmission technique, an ARQ transmission project in Mars detection telecommunications system was established. The simulation results showed that this algorithm had excellent saturation throughput rate and energy efficiency with low complexity.

Keywords: ARQ, mars, CCSDS, proximity-1, deepspace

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Authors: Faisal Zaman, Ya Ping Wong, Boon Yian Ng

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Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this, we present a novel approach using modified kernel density estimation (KDE) technique with bilateral filtering to remove noisy points and outliers. First we present a method for estimating optimal bandwidth of multivariate KDE using particle swarm optimization technique which ensures the robust performance of density estimation. Then we use mean-shift algorithm to find the local maxima of the density estimation which gives the centroid of the clusters. Then we compute the distance of a certain point from the centroid. Points belong to outliers then removed by automatic thresholding scheme which yields an accurate and economical point surface. The experimental results show that our approach comparably robust and efficient.

Keywords: point preprocessing, outlier removal, surface reconstruction, kernel density estimation

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Authors: Mario Kubek, Herwig Unger

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Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-of-the-art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking

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Authors: Manish Kumar, Krupa Shah

Abstract:

The usage of renewable energy sources is increased day by day to overcome the dependency on fossil fuels. The wind energy is considered as a prominent source of renewable energy. This paper presents an approach for utilizing wind energy obtained from moving the vehicle for cell-phone charging. The selection of wind turbine, blades, generator, etc. is done to have the most efficient system. The calculation procedure for power generated and drag force is shown to know the effectiveness of the proposal. The location of the turbine is selected such that the system remains symmetric, stable and has the maximum induced wind. The calculation of the generated power at different velocity is presented. The charging is achieved for the speed 30 km/h and the system works well till 60 km/h. The model proposed seems very useful for the people traveling long distances in the absence of mobile electricity. The model is very economical and easy to fabricate. It has very less weight and area that makes it portable and comfortable to carry along. The practical results are shown by implementing the portable wind turbine system on two-wheeler.

Keywords: cell-phone charging, on-board power generation, wind energy, vehicle

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Authors: Sharmistha Mukherjee

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Health care is the basic requirement for all. The prime question is who gets what, where and how? The unequal distribution of basic facilities do have a adverse effect on the users. The paper tries to examine health care in terms of available facilities, the health care need and how people perceive to it in a small town of Jalpaiguri in the midst of tea gardens in North Bengal. The morbidity pattern is also minutely observed with a section describing the organizational structure of health care keeping in mind the utilization.

Keywords: availability, distribution, health care, utilization

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Authors: Moein Izadi, Ali Mohammadzadeh

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Detection of damaged parts of roads after earthquake is essential for coordinating rescuers. In this study, an approach is presented for the semi-automatic detection of damaged roads in a city using pre-event vector maps and both pre- and post-earthquake QuickBird satellite images. Damage is defined in this study as the debris of damaged buildings adjacent to the roads. Some spectral and texture features are considered for SVM classification step to detect damages. Finally, the proposed method is tested on QuickBird pan-sharpened images from the Bam City earthquake and the results show that an overall accuracy of 81% and a kappa coefficient of 0.71 are achieved for the damage detection. The obtained results indicate the efficiency and accuracy of the proposed approach.

Keywords: SVM classifier, disaster management, road damage detection, quickBird images

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Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

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Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad

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As energetic and environmental issues are getting more and more attention all around the world, the penetration of distributed energy resources (DERs) mainly those harvesting renewable energies (REs) ascends with an unprecedented rate. This matter causes more uncertainties to appear in the power system context; ergo, the uncertainty analysis of the system performance is an obligation. The uncertainties of any system can be represented probabilistically or possibilistically. Since sufficient historical data about all the system variables is not available, therefore, they do not have a probability density function (PDF) and must be represented possibilistiacally. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution is appealed. The first of this two-paper series formulates a new possibilistic-probabilistic tool for the load flow uncertainty assessment. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. This possibilistic- probabilistic formulation is solved in the second companion paper in an uncertain load flow (ULF) study problem.

Keywords: probabilistic uncertainty modeling, possibilistic uncertainty modeling, uncertain load flow, wind turbine generator

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Authors: Sekou Kangoye, Alexis Todoskoff, Mihaela Barreau

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Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that aims to prove that all conditions involved in a Boolean expression can influence the result of that expression. In the context of automotive, MC/DC is highly recommended and even required for most security and safety applications testing. However, due to complex Boolean expressions that often embedded in those applications, generating a set of MC/DC compliant test cases for any of these expressions is a nontrivial task and can be time consuming for testers. In this paper we present an approach to automatically generate MC/DC test cases for any Boolean expression. We introduce novel techniques, essentially based on binary trees to quickly and optimally generate MC/DC test cases for the expressions. Thus, the approach can be used to reduce the manual testing effort of testers.

Keywords: binary trees, MC/DC, test case generation, nontrivial task

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Authors: Yu Qin

Abstract:

In order to tackle the ever-growing problem of the lack of parking space, this paper presents the design and implementation of a smart unmanned parking system that is based on RFID (radio frequency identification) technology and Wireless communication technology. This system uses RFID technology to achieve the identification function (transmitted by 2.4 G wireless module) and is equipped with an STM32L053 micro controller as the main control chip of the smart vehicle. This chip can accomplish automatic parking (in/out), charging and other functions. On this basis, it can also help users easily query the information that is stored in the database through the Internet. Experimental tests have shown that the system has the features of low power consumption and stable operation, among others. It can effectively improve the level of automation control of the parking lot management system and has enormous application prospects.

Keywords: RFID, embedded system, unmanned, parking management

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

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Authors: Chitsanzo Isaac

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Across the world, the ongoing Covid-19 pandemic has challenged urban systems and policy frameworks, highlighting societal vulnerabilities and systemic inequities among many communities. Measures of confinement and social distancing to contain the Covid-19 virus have fragmented the physical and social fabric of cities. This has caused urban dwellers to reassess how they engage with their urban surroundings and maintain social ties. Urbanists have presented strategies that would allow communities to survive and even thrive, in extraordinary times of crisis like the pandemic. Tactical Urbanism, particularly the 15-Minute City, has gained popularity. It is considered a resilient approach in the global north, however, it’s transferability to the global south has been called into question. To this end, this paper poses the question: to what extent is the 15-Minute City framework integral sustainable design, and are there processes that make it adoptable by cities in the global south? This paper explores four issues using secondary quantitative data analysis and convergence analysis in the Paris and Blantyre urban regions. First, it questions how the 15-Minute City has been defined and measured, and how it impacts urban dwellers. Second, it examines the extent to which the 15-minute city performs under the lens of frameworks such as Wilber’s integral theory and Fleming’s integral sustainable design theory. Thirdly this work examines the processes that can be transferred to developing cities which foster community resilience through the perspectives of experience, behaviors, cultures, and systems. Finally, it reviews the principal ways in which a multi-perspective reality can be the basis for resilient community design and sustainable urban development. This work will shed a light on the importance of a multi-perspective reality as a means of achieving sustainable urban design goals in developing urban areas.

Keywords: 15-minute city, developing cities, global south, community resilience, integral sustainable design, systems thinking, complexity, tactical urbanism

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Authors: Muhammad Ammar, Talha Ali, Abdul Basit, Bakhtawar Rajput, Zobia Sohail

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Music note detection is an area of study for the past few years and has its own influence in music file generation from sheet music. We proposed a method to detect music notes on sheet music using basic thresholding and blob detection. Subsequently, we created a notes dictionary using a semi-supervised learning approach. After notes detection, for each test image, the new symbols are added to the dictionary. This makes the notes detection semi-automatic. The experiments are done on images from a dataset and also on the captured images. The developed approach showed almost 100% accuracy on the dataset images, whereas varying results have been seen on captured images.

Keywords: music note, sheet music, optical music recognition, blob detection, thresholding, dictionary generation

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Authors: Salome Labeh

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Diverse Languages that exist in Nigeria, gave rise to the need to choose among these languages, which one or ones to be used as the National Language(s) in Nigeria. The Multilingual Nature of Nigeria has been examined, in relation to the provisional result of 1991 census conducted in Nigeria and the status of language policy in the country, which eventually led to the discovery of the fact that Hausa, Igbo, Yoruba languages have the highest speaker in terms of population, and are already made co-official languages in Nigeria, alongside with English language. Then, these languages should be considered as the National Languages, if eventually a language policy emerges in Nigeria.

Keywords: multilingual, languages, culture, Nigeria

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Authors: Fawad Zaidi

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This paper discusses a variety of challenges and solutions involved with creating computer games and the issues faced by the software engineers working in this field. This review further investigates the articles coverage of project scope and the problem of feature creep that appears to be inherent with game development. The paper tries to answer the following question: Is this a problem caused by a shortage, or bad software engineering practices, or is this outside the control of the software engineering component of the game production process?

Keywords: software engineering, computer games, software applications, development

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Authors: R. Ahmadi, A. Khodadadi, M. Abdollahi

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The removal of copper from a dilute synthetic wastewater (10 mg/L) was studied by ion flotation at laboratory scale. Anionic sodium dodecyl sulfate (SDS) was used as a collector and ethanol as a frother. Different parameters such as pH, collector and frother concentrations, foam height and bubble size distribution (multi bubble ion flotation) were tested to determine the optimum flotation conditions in a Denver type flotation machine. To see into the effect of bubbles size distribution in this paper, a nano-micro bubble generator was designed. The nano and microbubbles that are generated in this way were combined with normal size bubbles generated mechanically. Under the optimum conditions (concentration of SDS: 192mg/l, ethanol: 0.5%v/v, pH value: 4 and froth height=12.5 cm) the best removal obtained for the system Cu/SDS with a dry foam (water recovery: 15.5%) was 85.6%. Coalescence of nano-microbubbles with bubbles of normal size belonging to mechanical flotation cell improved the removal of Cu to a maximum floatability of 92.8% and reduced the water recovery to a 13.1%.The flotation time decreased considerably at 37.5% when the multi bubble ion flotation was used.

Keywords: froth flotation, copper, water treatment, optimization, recycling

Procedia PDF Downloads 500