Search results for: real world challenges

Authors: Vedat Senol, Gursoy Turan, Anders Helmersson, Vortechz Andersson

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In developing a mathematical model of a real structure, the simulation results of the model may not match the real structural response. This is a general problem that arises during dynamic motion of the structure, which may be modeled by means of parameter variations in the stiffness, damping, and mass matrices. These changes in parameters need to be estimated, and the mathematical model is updated to obtain higher control performances and robustness. In this study, a linear fractional transformation (LFT) is utilized for uncertainty modeling. Further, a general approach to the design of an H∞ control of a magneto-rheological damper (MRD) for vibration reduction in a building with mass, damping, and stiffness uncertainties is presented.

Keywords: uncertainty modeling, structural control, MR Damper, H∞, robust control

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Majno Ajbani

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Difficulties in teaching and learning English pronunciation in Sindh province, Pakistan Abstract Sindhi language is widely spoken in Sindh province, and it is one of the difficult languages of the world. Sindhi language has fifty-two alphabets which have caused a serious issue in learning and teaching of English pronunciation for teachers and students of Colleges and Universities. This study focuses on teachers’ and students’ need for extensive training in the pronunciation that articulates the real pronunciation of actual words. The study is set to contribute in the sociolinguistic studies of English learning communities in this region. Data from 200 English teachers and students was collected by already tested structured questionnaire. The data was analysed using SPSS 20 software. The data analysis clearly demonstrates the higher range of inappropriate pronunciations towards English learning and teaching. The anthropogenic responses indicate 87 percentages teachers and students had an improper pronunciation. This indicates the substantial negative effects on academic and sociolinguistic aspects. It is suggested an improper speaking of English, based on rapid changes in geopolitical and sociocultural surroundings.

Keywords: alphabets, pronunciation, sociolinguistic, anthropogenic, imprudent, malapropos

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Authors: Mohanad Al-Behadili, Djamila Ouelhadj

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In this paper, a specific type of vehicle routing problem under stochastic demand (SVRP) is considered. This problem is of great importance because it models for many of the real world vehicle routing applications. This paper used a robust optimisation model to solve the problem along with the novel Simulation-Particle Swarm Optimisation (Sim-PSO) approach. The proposed Sim-PSO approach is based on the hybridization of the Monte Carlo simulation technique with the PSO algorithm. A comparative study between the proposed model and the Sim-PSO approach against other solution methods in the literature has been given in this paper. This comparison including the Analysis of Variance (ANOVA) to show the ability of the model and solution method in solving the complicated SVRP. The experimental results show that the proposed model and Sim-PSO approach has a significant impact on the obtained solution by providing better quality solutions comparing with well-known algorithms in the literature.

Keywords: stochastic vehicle routing problem, robust optimisation model, Monte Carlo simulation, particle swarm optimisation

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Authors: Sunghoon Park, Hank Kim, Jinwon An, Sungzoon Cho

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Internet of Things allows one to collect data from facilities which are then used to monitor them and even predict malfunctions in advance. Conventional quality control methods focus on setting a normal range on a sensor value defined between a lower control limit and an upper control limit, and declaring as an anomaly anything falling outside it. However, interactions among sensor values are ignored, thus leading to suboptimal performance. We propose a multivariate approach which takes into account many sensor values at the same time. In particular Gaussian Mixture Model is used which is trained to maximize likelihood value using Expectation-Maximization algorithm. The number of Gaussian component distributions is determined by Bayesian Information Criterion. The negative Log likelihood value is used as an anomaly score. The actual usage scenario goes like a following. For each instance of sensor values from a facility, an anomaly score is computed. If it is larger than a threshold, an alarm will go off and a human expert intervenes and checks the system. A real world data from Building energy system was used to test the model.

Keywords: facility anomaly detection, gaussian mixture model, anomaly score, expectation maximization algorithm

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Authors: Alessandra Rossodivita, Alexei Tikhomirov, Andrey Trufanov, Nikolay Kinash, Olga Berestneva, Svetlana Nikitina, Fabio Casati, Alessandro Visconti, Tommaso Saporito

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It is well known that world and national societies are exposed to diverse threats: anthropogenic, technological, and natural. Anthropogenic ones are of greater risks and, thus, attract special interest to researchers within wide spectrum of disciplines in efforts to lower the pertinent risks. Some researchers showed by means of multilayered, complex network models how media promotes the prevention of disease spread. To go further, not only are mass-media sources included in scope the paper suggests but also personificated social bots (socbots) linked according to reflexive theory. The novel scope considers information spread over conscious and unconscious agents while counteracting both natural and man-made threats, i.e., infections and terrorist hazards. Contrary to numerous publications on misinformation disseminated by ‘bad’ bots within social networks, this study focuses on ‘good’ bots, which should be mobilized to counter the former ones. These social bots deployed mixture with real social actors that are engaged in concerted actions at spreading, receiving and analyzing information. All the contemporary complex network platforms (multiplexes, interdependent networks, combined stem networks et al.) are comprised to describe and test socbots activities within competing information sharing tools, namely mass-media hubs, social networks, messengers, and e-mail at all phases of disasters. The scope and concomitant techniques present evidence that embedding such socbots into information sharing process crucially change the network topology of actor interactions. The change might improve or impair robustness of social network environment: it depends on who and how controls the socbots. It is demonstrated that the topological approach elucidates techno-social processes within the field and outline the roadmap to a safer world.

Keywords: complex network platform, counterterrorism, information sharing topology, social bots

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Authors: Farideh Aramideh

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The aim of this essay is to study the light in Zoroastrianism, and Masnavi by Rumi. The use of light goes back to thousand years B.C. the light in the legacy of ancient Iranian wisdom has been used in Mithraism, Zurvanism, Zoroastrianism and Manichaean religion and spirituality has been emanated in the world through the light. Ontology and angelology and the sacredness of fire in Zoroastrianism have been interpreted according to the concept of light. The ruling atmosphere on mazdaism world is the world which is full of light and angels, and light is one of the basis of worldview in ancient Iranian mysticism, especially Zoroastrianism and Manichaean, continued widely in Islamic mysticism, and also it always provokes discussions among scholars and mystics especially Iranian mystics. Light and fire are used as the signs and symbols of God's existence, The Shining lights emanated from the sacred essence of God, knowledge, and mysticism, love, discovering the wisdom and a way to God. Rumi speaks eloquently about light in Masnavi, and by using the light; he could render his readers the fundamental mystic subjects such as the true existence of God, the verity of prophets and saints, intuition of God, spiritual states of union with God and abiding in God, which are the most complicated mystic terms.

Keywords: zoroastrianism, myticims, Masnavi, light

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Authors: Meenakshi Pappu

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The term, 'urban ecology' has often been misconstrued by the educational practitioners as well as the researchers as a study under a single discipline i.e., the environmental sciences. One who has done research extensively in this study would always argue that urban ecology is not a study under a single discipline, but it is a study across disciplines such as social sciences and other sciences like architecture, engineering, planning, ecology, geography, biology, economics, sociology, anthropology, psychology and health sciences. The aim of this paper is to discuss at length the scope of Urban Ecology as an interdisciplinary study. The paper highlights the nuances of urban ecology as a study across disciplines and the challenges and the implications it holds for future research by conducting a qualitative survey in the particular areas.

Keywords: educational practitioners, interdisciplinary, researchers, urban ecology

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Authors: Shwadhin Sharma, Monica Perez, Vinita Patel, Tyler Kuwatani, Siobhan Scott

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The purpose of this research is to explain and analyze why the Internet of Things (IoT) is an emerging technology trend. The aspects of this research paper include an overview of IoT, what research has already been done, the benefits, implications, and our own perspectives on the trend in order to thoroughly analyze how the trend of IoT will make an impact on society. Through the identification of what makes IoT important, it is concluded that IoT will have a tremendous impact for the whole world. Technology is never going to go away, it is going to get smarter and have the potential to change the world.

Keywords: internet of things, enablers of IoT, cost of IoT, benefits of IoT

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Authors: Liang-Ta Cheng, Ching-Yu Yang

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Based on fast discrete cosine transform (FDCT), the authors present a high capacity and high perceived quality method for electrocardiogram (ECG) signal. By using a simple adjusting policy to the 1-dimentional (1-D) DCT coefficients, a large volume of secret message can be effectively embedded in an ECG host signal and be successfully extracted at the intended receiver. Simulations confirmed that the resulting perceived quality is good, while the hiding capability of the proposed method significantly outperforms that of existing techniques. In addition, our proposed method has a certain degree of robustness. Since the computational complexity is low, it is feasible for our method being employed in real-time applications.

Keywords: data hiding, ECG steganography, fast discrete cosine transform, 1-D DCT bundle, real-time applications

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Authors: Mona Shojaei

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The Sub-Atmospheric Vapor Pipeline (SAVP) introduces a distinct approach to seawater desalination with promising applications in both land and industrial sectors. SAVP systems exploit the temperature difference between a hot source and a cold environment to facilitate efficient vapor transfer, offering substantial benefits in diverse industrial and field applications. This approach incorporates dynamic boundary conditions, where the temperatures of hot and cold sources vary over time, particularly in natural and industrial environments. Such variations critically influence convection and diffusion processes, introducing challenges that require the refinement of the convection-diffusion equation and the derivation of temperature profiles along the pipeline through advanced engineering mathematics. This study formulates vapor temperature as a function of time and length using two mathematical approaches: Eigen functions and Green’s equation. Combining detailed theoretical modeling, mathematical simulations, and extensive field and industrial tests, this research underscores the SAVP system’s scalability for real-world applications. Results reveal a high degree of accuracy, highlighting SAVP’s significant potential for energy conservation and environmental sustainability. Furthermore, the integration of SAVP technology within smart and green building systems creates new opportunities for sustainable urban water management. By capturing and repurposing vapor for non-potable uses such as irrigation, greywater recycling, and ecosystem support in green spaces, SAVP aligns with the principles of smart and green buildings. Smart buildings emphasize efficient resource management, enhanced system control, and automation for optimal energy and water use, while green buildings prioritize environmental impact reduction and resource conservation. SAVP technology bridges both paradigms, enhancing water self-sufficiency and reducing reliance on external water supplies. The sustainable and energy-efficient properties of SAVP make it a vital component in resilient infrastructure development, addressing urban water scarcity while promoting eco-friendly living. This dual alignment with smart and green building goals positions SAVP as a transformative solution in the pursuit of sustainable urban resource management.

Keywords: sub-atmospheric vapor pipeline, seawater desalination, energy efficiency, vapor transfer dynamics, mathematical modeling, sustainable water solutions, smart buildings

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Authors: Petr Mohyla, Ivo Hlavatý, Jiří Hrubý, Lucie Krejčí

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This work is focused on mechanical properties and microstructure of heat affected zone (HAZ) of steel P92. The thermal cycle simulator was used for modeling a fine grained zone of HAZ. Hardness and impact toughness were measured on simulated samples. Microstructural analysis using optical microscopy was performed on selected samples. Achieved results were compared with the values of a real welded joint. The thermal cycle simulator allows transferring the properties of very small HAZ to the sufficiently large sample where the tests of the mechanical properties can be performed. A satisfactory accordance was found when comparing the microstructure and mechanical properties of real welds and simulated samples.

Keywords: heat affected zone, impact test, thermal cycle simulator, time of tempering

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Authors: Abdelaziz Fellah, Allaoua Maamir

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We propose a domain-independent merging-cluster filter approach complemented with a set of algorithms for identifying approximate duplicate entities efficiently and accurately within a single and across multiple data sources. The near-optimal merging-cluster filter (MCF) approach is based on the Monge-Elkan well-tuned algorithm and extended with an affine variant of the Smith-Waterman similarity measure. Then we present constant, variable, and function threshold algorithms that work conceptually in a divide-merge filtering fashion for detecting near duplicates as hierarchical clusters along with their corresponding representatives. The algorithms take recursive refinement approaches in the spirit of filtering, merging, and updating, cluster representatives to detect approximate duplicates at each level of the cluster tree. Experiments show a high effectiveness and accuracy of the MCF approach in detecting approximate duplicates by outperforming the seminal Monge-Elkan’s algorithm on several real-world benchmarks and generated datasets.

Keywords: data mining, data cleaning, approximate duplicates, near-duplicates detection, data mining applications and discovery

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Authors: João Coutinho-Rodrigues, Nuno Sousa, Luís Alçada-Almeida

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Transportation infrastructure systems are fundamental in modern society and economy. However, they need modernizing, maintaining, and reinforcing interventions which require large investments. In many countries, accumulated intervention delays arise from aging and intense use, being magnified by financial constraints of the past. The decision problem of managing the renewal of large backlogs is common to several types of important transportation infrastructures (e.g., railways, roads). This problem requires considering financial aspects as well as operational constraints under a multidimensional framework. The present research introduces a linear programming multiobjective model for managing railway infrastructure asset renewal. The model aims at minimizing three objectives: (i) yearly investment peak, by evenly spreading investment throughout multiple years; (ii) total cost, which includes extra maintenance costs incurred from renewal backlogs; (iii) priority delays related to work start postponements on the higher priority railway sections. Operational constraints ensure that passenger and freight services are not excessively delayed from having railway line sections under intervention. Achieving a balanced annual investment plan, without compromising the total financial effort or excessively postponing the execution of the priority works, was the motivation for pursuing the research which is now presented. The methodology, inspired by a real case study and tested with real data, reflects aspects of the practice of an infrastructure management company and is generalizable to different types of infrastructure (e.g., railways, highways). It was conceived for treating renewal interventions in infrastructure assets, which is a railway network may be rails, ballasts, sleepers, etc.; while a section is under intervention, trains must run at reduced speed, causing delays in services. The model cannot, therefore, allow for an accumulation of works on the same line, which may cause excessively large delays. Similarly, the lines do not all have the same socio-economic importance or service intensity, making it is necessary to prioritize the sections to be renewed. The model takes these issues into account, and its output is an optimized works schedule for the renewal project translatable in Gantt charts The infrastructure management company provided all the data for the first test case study and validated the parameterization. This case consists of several sections to be renewed, over 5 years and belonging to 17 lines. A large instance was also generated, reflecting a problem of a size similar to the USA railway network (considered the largest one in the world), so it is not expected that considerably larger problems appear in real life; an average of 25 years backlog and ten years of project horizon was considered. Despite the very large increase in the number of decision variables (200 times as large), the computational time cost did not increase very significantly. It is thus expectable that just about any real-life problem can be treated in a modern computer, regardless of size. The trade-off analysis shows that if the decision maker allows some increase in max yearly investment (i.e., degradation of objective ii), solutions improve considerably in the remaining two objectives.

Keywords: transport infrastructure, asset renewal, railway maintenance, multiobjective modeling

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Authors: Delies L. Alejo

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This study explores the psychosocial influences of Spinal Cord Injury (SCI) on patients in the Philippine Orthopedic Center Hospital in the Philippines, examining their social functioning and proposing interventions for reintegration. Quantitative data were collected through surveys using a concurrent triangulation research design, while qualitative insights were obtained via interviews. Findings revealed significant psychosocial challenges among SCI patients, impacting relationships, family dynamics, work, friendships, parenting, education, and self-care. Demographic profiles indicated variations in psychosocial functioning. The study underscores the importance of tailored interventions for SCI patients based on age, marital status, gender, education, and occupation. Triangulation of data enhanced understanding, revealing four themes: ‘Resilient Navigation of Intimacy and Connection,’ ‘Family Dynamics and Care Challenges,’ ‘Occupational Hurdles and Work Engagement,’ and ‘Social and Community Integration Obstacles.’ The study proposes a holistic intervention plan, addressing emotional challenges, creating support networks, implementing vocational rehabilitation, promoting community engagement, and sustaining collaboration with healthcare professionals.

Keywords: spinal cord injury, psychosocial influences, social functioning, concurrent triangulation, intervention plan

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Authors: P. Nayak, Shakeel Shaikh

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In this paper, we analyse the apparel export performance of Southeast Asian Nations (ASEAN) in the world market. The study covers the 2003-2012 period at the sector as well as product levels (6 digit HS) and analysis is based HS 2002 nomenclature. We measure export similarity among Southeast Asian nations for the apparel sector (two digit HS-61 & 62), besides analysing the products performance in the world through Revealed Comparative Advantage (RCA) technique. Coupled with RCA, the price as a factor of competitiveness was examined from the available Unit Value Realizations (UVR). Further to this, the resource availability or outsourced from the region was considered as an extension to the analysis of competitiveness between the nations. With the help of these methodologies, we examine the degree of competition between the exports of southeast nations in the world market. Our results show that Cambodia, Indonesia, Thailand, and Vietnam are well performing states within ASEAN. The paper further delves into sustainability of the export performing countries within ASEAN.

Keywords: export competitiveness, export similarity index, revealed comparative advantage, unit value realisation

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Authors: Kamila Troper, Pedro Mestre, Maria Lurdes Menano, Joana Mendonça, Maria João Costa, Sandra Demel

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Introduction: Visual impairment is a problem that has an influence on hundreds of thousands of people all over the world. Although it is possible for a Visually Impaired person to do most jobs, the right training, technological assistance, and emotional support are essential. Ergonomics be able to solve many of the problems/issues with the relative ease of positioning, lighting and design of the workplace. A little forethought can make a tremendous difference to the ease with which a person with an impairment function. Objectives: Review the main ergonomic adaptation measures reported in the literature in order to promote better working conditions and safety measures for the visually impaired. Methodology: This was an exploratory-descriptive, qualitative literature systematic review study. The main databases used were: PubMed, BIREME, LILACS, with articles and studies published between 2000 and 2021. Results: Based on the principles of the theoretical references of ergonomic analysis of work, the main restructuring of the physical space of the workstations were: Accessibility facilities and assistive technologies; A screen reader that captures information from a computer and sends it in real-time to a speech synthesizer or Braille terminal; Installations of software with voice recognition, Monitors with enlarged screens; Magnification software; Adequate lighting, magnifying lenses in addition to recommendations regarding signage and clearance of the places where the visually impaired pass through. Conclusions: Employability rates for people with visual impairments(both those who are blind and those who have low vision)are low and continue to be a concern to the world and for researchers as a topic of international interest. Although numerous authors have identified barriers to employment and proposed strategies to remediate or circumvent those barriers, people with visual impairments continue to experience high rates of unemployment.

Keywords: ergonomic adaptations, visual impairments, ergonomic analysis of work, systematic review

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Authors: Zakari Mustapha, Clinto Aigbavboa, Wellinton Didi Thwala

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Occupational Health and Safety (OHS) issues has been a major challenge to the Ghanaian government. The purpose of the study was to examine OHS practices in Ghana. The study looked at various views from different scholars about OHS practices in order to achieve the objective of the study. Literature review was conducted on OHS in Ghana. Findings from the study shows Ministry of Roads and Transport (MRT) and Ministry of Water Resources, Works and Housing (MWRWH) are two government ministries in charge of construction and implementation of the construction sector policy. The Factories, Offices and Shops Act 1970, Act 328 and the Mining Regulations 1970 LI 665 are the two major edicts. The study presents a strong background on OHS practices in Ghana and contribute to the body of knowledge on the solution to the current trends and challenges of OHS in the construction sector.

Keywords: ILO convention, OHS challenges, OHS practices, OHS improvement

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines

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Authors: Mohamad Khairi Haji Othman, Mohd Zailani Mohd Yusoff, Rozalina Khalid

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The inculcation of noble values in teaching and learning is very important, especially to build students with good characters and values. Therefore, the purpose of this research is to identify the challenges of implementing the inculcation of noble values in teaching in primary schools. This study was conducted at four North Zone Peninsular Malaysia schools. This study was used a qualitative approach in the form of case studies. The qualitative approach aims at gaining meaning and a deep understanding of the phenomenon studied from the perspectives of the study participants and not intended to make the generalization. The sample in this study consists of eight teachers who teach in four types of schools that have been chosen purposively. The method of data collection is through semi-structured interviews used in this study. The comparative method is continuously used in this study to analyze the primary data collected. The study found that the main challenges faced by teachers were students' problems and class control so that teachers felt difficult to the inculcation of noble values in teaching. In addition, the language challenge is difficult for students to understand. Similarly, peers are also challenging because students are more easily influenced by friends rather than listening to teachers' instructions. The last challenge was the influence of technology and mass media electronic more widespread. The findings suggest that teachers need to innovate in order to assist the school in inculcating religious and moral education towards the students. The school through guidance and counseling teachers can also plan some activities that are appropriate to the student's present condition. Through this study, teachers and the school should work together to develop the values of students in line with the needs of the National Education Philosophy that wishes to produce intelligent, emotional, spiritual, intellectual and social human capital.

Keywords: challenges, implementation, inculcation, noble values

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Authors: Amir Hajian, Sepehr Damavandinejadmonfared

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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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Authors: Saw Thiha, Jay Rajasekera

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A boom in video conferencing generated millions of hours of video data daily to be analyzed. However, such enormous data pose certain scalability issues to be analyzed efficiently, let alone do it in real-time, as online conferences can involve hundreds of people and can last for hours. This paper proposes an efficient online proctoring solution that can analyze the online conferences real-time on edge devices such as Android, iOS, and desktops. Since the computation can be done upfront on the devices where online conferences take place, it can scale well without requiring intensive resources such as GPU servers and complex cloud infrastructure. According to the linear models, face orientation does indeed impact the perceived eye openness. Also, the proposed z score facial landmark standardization was proven to be functional in detecting face orientation and contributed to classifying eye blinks with single eyelid distance computation while achieving a better f1 score and accuracy than the Eye Aspect Ratio (EAR) threshold method. Last but not least, the authors implemented the solution natively in the MediaPipe framework and open-sourced it along with the reproducible experimental results on GitHub. The solution provides face orientation, eye blink, facial activity, and translation detections out of the box and is highly customizable and extensible.

Keywords: android, desktop, edge computing, blink, face orientation, facial activity and translation, MediaPipe, open source, real-time, video conference, web, iOS, Z score facial landmark standardization

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Authors: Seung-Lock Seo

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This work presents a data-mining empirical monitoring scheme for industrial processes with partially unbalanced data. Measurement data of good operations are relatively easy to gather, but in unusual special events or faults it is generally difficult to collect process information or almost impossible to analyze some noisy data of industrial processes. At this time some noise filtering techniques can be used to enhance process monitoring performance in a real-time basis. In addition, pre-processing of raw process data is helpful to eliminate unwanted variation of industrial process data. In this work, the performance of various monitoring schemes was tested and demonstrated for discrete batch process data. It showed that the monitoring performance was improved significantly in terms of monitoring success rate of given process faults.

Keywords: data mining, process data, monitoring, safety, industrial processes

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Authors: XuKe Cao

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This paper reviews the current state of research on low-resource languages in the field of speech recognition, focusing on the challenges faced by low-resource language speech recognition, including the scarcity of data resources, the lack of linguistic resources, and the diversity of dialects and accents. The article reviews recent progress in low-resource language speech recognition, including techniques such as data augmentation, end to-end models, transfer learning, and multi-task learning. Based on the challenges currently faced, the paper also provides an outlook on future research directions. Through these studies, it is expected that the performance of speech recognition for low resource languages can be improved, promoting the widespread application and adoption of related technologies.

Keywords: low-resource languages, speech recognition, data augmentation techniques, NLP

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Authors: Julia Wicker, Alexander Lang

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The shortage of skilled workers is no longer unique to Europe; Australia now faces similar challenges, particularly in the field of project management. Project managers, essential to the success of a wide range of industries, frequently operate under intense stress and, as a result, may choose to leave their positions before the completion of their projects. This trend poses significant risks to project continuity, budget stability, and the long-term success of organizations. Consequently, it is crucial to explore strategies aimed at improving the retention of project managers, with a specific focus on fostering intrinsic motivation -an essential factor for achieving sustained success and commitment within project-based roles. The aim of this paper is to investigate retention strategies from other industries to identify effective practices that could be adapted to the unique challenges faced by project managers. In particular, the paper draws inspiration from the volunteer sector, an industry also heavily reliant on intrinsic motivation to drive commitment and performance. By examining how the volunteer sector sustains retention through a focus on intrinsic motivation, this paper seeks to highlight potential parallels and offer actionable insights for improving the retention of project managers. The paper includes an overview of the current landscape of retention challenges in project management, highlighting key factors that contribute to early departures and their impacts on organizations. This is followed by an analysis of interviews conducted with both active volunteers and those who have left their roles, leading to the development of a model that categorizes different types of volunteers and explores their behaviours. The model identifies specific reasons for volunteer terminating their assignments and proposes strategies to mitigate these issues. The paper then adapts these volunteer retention strategies to address the challenges faced by project managers, concluding with actionable recommendations for fostering an intrinsically motivated and resilient project management workforce. Ultimately, this research aims to contribute to broader efforts in mitigating skilled workforce shortages by offering sustainable retention strategies.

Keywords: skilled workforce shortages, retention challenges in project management, retention strategies in the volunteering sector, retention strategies for project managers

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Authors: Wilmer Osvaldo Martinez, Manuel Dario Hernandez, Juan Manuel Julio

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We propose to assess the performance of k forecast procedures by exploring the distributions of forecast errors and error losses. We argue that non systematic forecast errors minimize when their distributions are symmetric and unimodal, and that forecast accuracy should be assessed through stochastic loss order rather than expected loss order, which is the way it is customarily performed in previous work. Moreover, since forecast performance evaluation can be understood as a one way analysis of variance, we propose to explore loss distributions under two circumstances; when a strict (but unknown) joint stochastic order exists among the losses of all forecast alternatives, and when such order happens among subsets of alternative procedures. In spite of the fact that loss stochastic order is stronger than loss moment order, our proposals are at least as powerful as competing tests, and are robust to the correlation, autocorrelation and heteroskedasticity settings they consider. In addition, since our proposals do not require samples of the same size, their scope is also wider, and provided that they test the whole loss distribution instead of just loss moments, they can also be used to study forecast distributions as well. We illustrate the usefulness of our proposals by evaluating a set of real world forecasts.

Keywords: forecast evaluation, stochastic order, multiple comparison, non parametric test

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Authors: Usman Mahmood, Khawaja M. U. Suleman

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A peer-to-peer storage system has challenges like; peer availability, data protection, churn rate. To address these challenges different redundancy, replacement and repair schemes are used. This paper presents a hybrid scheme of redundancy using replication and erasure coding. We calculate and compare the storage, access, and maintenance costs of our proposed scheme with existing redundancy schemes. For realistic behaviour of peers a trace of live peer-to-peer system is used. The effect of different replication, and repair schemes are also shown. The proposed hybrid scheme performs better than existing double coding hybrid scheme in all metrics and have an improved maintenance cost than hierarchical codes.

Keywords: erasure coding, P2P, redundancy, replication

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Authors: Khalid Achaat

Abstract:

It is difficult to speak about freedom of the press in Algeria without first talking to fifty-seven journalists killed in the country between 1993 and 1997 and the five missing journalists. No serious investigation was conducted to find the culprits. When a State is not able to guarantee law, there is no justice and violations of the law become "systematic". How to claim the freedom of press in Algeria, when death becomes "banal"? In these circumstances, can we talk of rights of the Algerian press? It is impossible to understand the problems of the press in Algeria, focusing solely legal issues. Take into account technical, financial and political. Their respective roles varies depending on whether one focuses on the collection of information, the regime of the newspaper company or publication and dissemination. Can we say that the Algerian press is "the freest in the Arab world", while the latter reflects only partially the real problems facing the country? While any newspaper company is subject, de facto, to an authorization scheme, permanently subjected to the constant threat of withdrawal of the authorization, suspension, prohibition or closure without it has the right to a remedy? Can it be free when the majority of "media owners", head of the largest daily newspapers are derived from the single party in power since independence? Some of this release does not it serves the interests of the Algerian power?

Keywords: freedom, press, power, closure, suspension

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Authors: Edna Negron-Martinez

Abstract:

Our time's global challenges and trends —like those associated with climate change, demographics displacements, growing health inequalities, and increasing burden of diseases— have complex connections to the determinants of health. Information on the burden of disease causes and prevention is fundamental for public health actions, like preparedness and responses for disasters, and recovery resources after the event. For instance, there is an increasing consensus about key findings of the effects and connections of the global burden of disease, as it generates substantial healthcare costs, consumes essential resources and prevents the attainment of optimal health and well-being. The goal of this research endeavor is to promote a comprehensive understanding of the connections between social, environmental, and economic influences on health. These connections are illustrated by pulling from clearly the core curriculum of multidisciplinary areas —as urban design, energy, housing, and economy— as well as in the health system itself. A systematic review of primary and secondary data included a variety of issues as global health, natural disasters, and critical pollution impacts on people's health and the ecosystems. Environmental health is challenged by the unsustainable consumption patterns and the resulting contaminants that abound in many cities and urban settings around the world. Poverty, inadequate housing, and poor health are usually linked. The house is a primary environmental health context for any individual and especially for more vulnerable groups; such as children, older adults and those who are sick. Nevertheless, very few countries show strong decoupling of environmental degradation from economic growth, as indicated by a recent 2017 Report of the World Bank. Worth noting, the environmental fraction of the global burden of disease in a 2016 World Health Organization (WHO) report estimated that 12.6 million global deaths, accounting for 23% (95% CI: 13-34%) of all deaths were attributable to the environment. Among the environmental contaminants include heavy metals, noise pollution, light pollution, and urban sprawl. Those key findings make a call to the significance to urgently adopt in a global scale the United Nations post-2015 Sustainable Development Goals (SDGs). The SDGs address the social, environmental, and economic factors that influence health and health inequalities, advising how these sectors, in turn, benefit from a healthy population. Consequently, more actions are necessary from an inter-sectoral and systemic paradigm to enforce an integrated sustainability policy implementation aimed at the environmental, social, and economic determinants of health.

Keywords: building capacity for workforce development, ecological and environmental health effects of pollution, public health education, sustainability

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Authors: Tumelo Jaquiline Ntsopi

Abstract:

This study explored the academic writing challenges of first-year students who use English as an Additional Language (EAL) registered in the EAW101 module at an ODeL institution. Research shows that academic writing is a challenge for EAL teaching and learning contexts across the globe in higher education institutions (HEIs). Academic writing is an important aspect of academic literacy in any institution of higher learning, more so in an ODeL institution. This has probed research that shows that academic writing is and continues to pose challenges for EAL teaching and learning contexts in higher education institutions. This study stems from the researcher’s experience in teaching academic writing to first-year students in the EAW101 module. The motivation for this study emerged from the fact that EAW101 is a writing module that has a high number of students in the Department of English Studies with an average of between 50-80 percent pass rate. These statistics elaborate on the argument that most students registered in this module struggle with academic writing, and they need intervention to assist and support them in achieving competence in the module. This study is underpinned by Community of Inquiry (CoI) framework and Transactional distance theory. This study adopted a qualitative research methodology and utilised a case study approach as a research design. Furthermore, the study gathered data from first year students and the EAW101 module’s student support initiatives. To collect data, focus group discussions, structured open-ended evaluation questions, and an observation schedule were used to gather data. The study is vital towards exploring academic writing challenges that first-year students in EAW101 encounter so that lecturers in the module may consider re-evaluating their methods of teaching to improve EAL students’ academic writing skills. This study may help lecturers towards enhancing academic writing in a ODeL context by assisting first year students through using student support interventions.

Keywords: academic writing, academic writing challenge, ODeL, EAL

Procedia PDF Downloads 105