Search results for: challenging situations

Authors: Venkata Ramana Pamu

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This paper is a case study of a 5310 ML capacity Raw Water Reservoir (RWR), situated in Indian state Rajasthan, which is a part of Rajasthan Rural Water Supply & Fluorosis Mitigation Project. This RWR embankment was constructed by locally available material on natural ground profile. Height of the embankment was varying from 2m to 10m.This is due to existing ground level was varying. Reservoir depth 9m including 1.5m free board and 1V:3H slopes were provided both upstream and downstream side. Proper soil investigation, tests were done and it was confirmed that the existing soil is sandy silt. The existing excavated earth was used as filling material for embankment construction, due to this controlling seepage from upstream to downstream be a challenging task. Slope stability and Seismic analysis of the embankment done by Conventional method for both full reservoir condition and rapid drawdown. Horizontal filter at toe level was provided along with upstream side PCC (Plain Cement Concrete) block and HDPE (High Density poly ethylene) lining as a remedy to control seepage. HDPE lining was also provided at storage area of the reservoir bed level. Mulching was done for downstream side slope protection.

Keywords: raw water reservoir, seepage, seismic analysis, slope stability

Procedia PDF Downloads 497

Authors: Ryotaro Ishikawa

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Social Anxiety Disorder (SAD) is marked by the persistent fear of social or performance situations in which embarrassment may occur. In contrast, SA in Japan and in China is understood differently. Taijin Kyofusho (TKS) is a culture-bound subtype of SAD which has been the focus of recent research. TKS refers to a unique form of SAD found in Japanese and East Asian cultures characterized by a fear of offending others, in contrast to prototypical SAD in which the source of fear is typically concerned about one’s own embarrassment, humiliation, or rejection by others. Criteria for TKS partially overlap with but are distinct from SAD; a primary factor distinguishing TKS from SAD appears to be individualistic versus interdependent or collectivistic self-construals. The aim of this study was to develop a scale to assess the typical SAD and offensive type of SAD (TKS). This study aimed to test the internal consistency and validity of the scale (Dimensional Social Anxiety Scale: DSAS) using university students sample. For this, 148 university students were enrolled (male=90, female=58, age=19.77, Standard Deviation=1.04). As a result of confirmatory factor analysis, three-factor models of DSAS were verified (χ2(74) =128.36). These three factors were named ‘general’, ‘perfomance’, and ‘offensive’. DSAS were significantly correlated with the Liebowitz Social Anxiety Scale (r = .538, p < .001). Good internal consistencies were indicated on the three subscales (α = .76 to 89). In conclusion, this study indicated DSAS has adequate internal consistency and validity for assessing of multi-type of SADs.

Keywords: social anxiety, cognitive theory, assessment, anxiety disorder

Procedia PDF Downloads 113

Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Use of speed prediction models sometimes appears as a feasible alternative to laborious field measurement particularly, in case when field data cannot fulfill designer’s requirements. However, developing speed models is a challenging task specifically in the context of developing countries like India where vehicles with diverse static and dynamic characteristics use the same right of way without any segregation. Here the traffic composition plays a significant role in determining the vehicular speed. The present research was carried out to examine the effects of traffic volume and its composition on vehicular speed under mixed traffic conditions. Classified traffic volume and speed data were collected from different geometrically identical six lane divided arterials in New Delhi. Based on these field data, speed prediction models were developed for individual vehicle category adopting Kriging approximation technique, an alternative for commonly used regression. These models are validated with the data set kept aside earlier for validation purpose. The predicted speeds showed a great deal of agreement with the observed values and also the model outperforms all other existing speed models. Finally, the proposed models were utilized to evaluate the effect of traffic volume and its composition on speed.

Keywords: speed, Kriging, arterial, traffic volume

Procedia PDF Downloads 351

Authors: A. Ras, I. Nait Zerrad, N. Benmouna, N. Boumechra

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Use of base isolators in the seismic design of structures has attracted considerable attention in recent years. The major concern in the design of these structures is to have enough lateral stability to resist wind and seismic forces. There are different systems providing such isolation, among them there are friction- pendulum base isolation systems (FPS) which are rather widely applied nowadays involving to both affordable cost and high fundamental periods. These devices are characterised by a stiff resistance against wind loads and to be flexible to the seismic tremors, which make them suitable for different situations. In this paper, a 3D numerical investigation is done considering the seismic response of a twelve-storey steel building retrofitted with a FPS. Fast nonlinear time history analysis (FNA) of Boumerdes earthquake (Algeria, May 2003) is considered for analysis and carried out using SAP2000 software. Comparisons between fixed base, bearing base isolated and braced structures are shown in a tabulated and graphical format. The results of the various alternatives studies to compare the structural response without and with this device of dissipation energy thus obtained were discussed and the conclusions showed the interesting potential of the FPS isolator. This system may to improve the dissipative capacities of the structure without increasing its rigidity in a significant way which contributes to optimize the quantity of steel necessary for its general stability.

Keywords: energy dissipation, friction-pendulum system, nonlinear analysis, steel structure

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Authors: Dina L. DiSantis

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Development and implementation of a place-based watershed science course for high school students will prove to be a valuable experience for both student and teacher. By having students study and assess the watershed dynamics of a local stream, they will better understand how human activities affect this valuable resource. It is important that students gain tangible skills that will help them to have an understanding of water quality analysis and the importance of preserving our Earth's water systems. Having students participate in real world practices is the optimal learning environment and can offer students a genuine learning experience, by cultivating a knowledge of place, while promoting education for sustainability. Additionally, developing a watershed science course for high school students will give them a hands-on approach to studying science; which is both beneficial and more satisfying to students. When students conduct their own research, collect and analyze data, they will be intimately involved in addressing water quality issues and solving critical water quality problems. By providing students with activities that take place outside the confines of the indoor classroom, you give them the opportunity to gain an appreciation of the natural world. Placed-based learning provides students with problem-solving skills in everyday situations while enhancing skills of inquiry. An overview of a place-based watershed science course and its impact on student learning will be presented.

Keywords: education for sustainability, place-based learning, watershed science, water quality

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Authors: Berna Eren Tokgoz, Mahdi Safa, Seokyon Hwang

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Power distribution systems are essential and crucial infrastructures for the development and maintenance of a sustainable society. These systems are extremely vulnerable to various types of natural and man-made disasters. The assessment of resilience focuses on preparedness and mitigation actions under pre-disaster conditions. It also concentrates on response and recovery actions under post-disaster situations. The aim of this study is to present a methodology to assess the resilience of electric power distribution poles against wind-related events. The proposed methodology can improve the accuracy and rapidity of the evaluation of the conditions and the assessment of the resilience of poles. The methodology provides a metric for the evaluation of the resilience of poles under pre-disaster and post-disaster conditions. The metric was developed using mathematical expressions for physical forces that involve various variables, such as physical dimensions of the pole, the inclination of the pole, and wind speed. A three-dimensional imaging technology (photogrammetry) was used to determine the inclination of poles. Based on expert opinion, the proposed metric was used to define zones to visualize resilience. Visual representation of resilience is helpful for decision makers to prioritize their resources before and after experiencing a wind-related disaster. Multiple electric poles in the City of Beaumont, TX were used in a case study to evaluate the proposed methodology.  

Keywords: photogrammetry, power distribution systems, resilience metric, system resilience, wind-related disasters

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Authors: S. Kadiyala, M. Berzins, D. Juba, W. Keyrouz

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This paper describes the Material Point Method (MPM) for simulating a single-track laser melting process on an IN718 solid plate. MPM, known for simulating challenging multiphysics problems, is used to model the intricate thermal, mechanical, and fluid interactions during the laser sintering process. This study analyzes the formation of single tracks, exploring the impact of varying laser parameters such as speed, power, and spot diameter on the melt pool and track formation. The focus is on MPM’s ability to accurately simulate and capture the transient thermo-mechanical and phase change phenomena, which are critical in predicting the cooling rates before and after solidification of the laser track and the final melt pool geometry. The simulation results are rigorously compared with experimental data (AMB2022 benchmarks), demonstrating the effectiveness of MPM in replicating the physical processes in laser sintering. This research highlights the potential of MPM in advancing the understanding and simulation of melt pool physics in metal additive manufacturing, paving the way for optimized process parameters and improved material performance.

Keywords: dditive manufacturing simulation, material point method, phase change, melt pool physics

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Authors: Kyung-Jin You, Kiwon Rhee, Marc H. Schieber, Nitish V. Thakor, Hyun-Chool Shin

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It remains unknown whether M1 neurons encode multi-finger movements independently or as a certain neural network of single finger movements although multi-finger movements are physically a combination of single finger movements. We present an evidence of correlation between single and multi-finger movements and also attempt a challenging task of semi-blind decoding of neural data with minimum training of the neural decoder. Data were collected from 115 task-related neurons in M1 of a trained rhesus monkey performing flexion and extension of each finger and the wrist (12 single and 6 two-finger-movements). By exploiting correlation of temporal firing pattern between movements, we found that correlation coefficient for physically related movements pairs is greater than others; neurons tuned to single finger movements increased their firing rate when multi-finger commands were instructed. According to this knowledge, neural semi-blind decoding is done by choosing the greatest and the second greatest likelihood for canonical candidates. We achieved a decoding accuracy about 60% for multiple finger movement without corresponding training data set. this results suggest that only with the neural activities on single finger movements can be exploited to control dexterous multi-fingered neuroprosthetics.

Keywords: finger movement, neural activity, blind decoding, M1

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Syarif Hidayat

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As millions of people with different backgrounds perform hajj every year in Saudi Arabia, it brings out several problems. Missing people is among many crucial problems need to be encountered. Some people might have had insufficient knowledge of using tracking system equipment. Other might become a victim of an accident, lose consciousness, or even died, prohibiting them to perform certain activity. For those reasons, people could not send proper SOS message. The major contribution of this paper is the application of the diverse alert method in pilgrims tracking system. It offers a simple yet robust solution to send SOS message by pilgrims during Hajj. Knowledge of context aware computing is assumed herein. This study presents four methods that could be utilized by pilgrims to send SOS. The first method is simple mobile application contains only a button. The second method is based on behavior analysis based off GPS location movement anomaly. The third method is by introducing pressing pattern to smartwatch physical button as a panic button. The fourth method is by identifying certain accelerometer pattern recognition as a sign of emergency situations. Presented method in this paper would be an important part of pilgrims tracking system. The discussion provided here includes easy to use design whilst maintaining tracking accuracy, privacy, and security of its users.

Keywords: context aware computing, emergency alert system, GPS, hajj pilgrim tracking, location-based services

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Authors: Han-Jeong Hwang, Jae-Hyun Jo, Fatemeh Alimardani

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An accurate diagnosis of psychiatric diseases is a challenging issue, in particular when distinct symptoms for different diseases are overlapped, such as delusions appeared in bipolar mood disorder (BMD) and schizophrenia (SCH). In the present study, we propose a useful way to discriminate BMD and SCH using electroencephalography (EEG). A total of thirty BMD and SCH patients (15 vs. 15) took part in our experiment. EEG signals were measured with nineteen electrodes attached on the scalp using the international 10-20 system, while they were exposed to a visual stimulus flickering at 16 Hz for 95 s. The flickering visual stimulus induces a certain brain signal, known as steady-state visual evoked potential (SSVEP), which is differently observed in patients with BMD and SCH, respectively, in terms of SSVEP amplitude because they process the same visual information in own unique way. For classifying BDM and SCH patients, machine learning technique was employed in which leave-one-out-cross validation was performed. The SSVEPs induced at the fundamental (16 Hz) and second harmonic (32 Hz) stimulation frequencies were extracted using fast Fourier transformation (FFT), and they were used as features. The most discriminative feature was selected using the Fisher score, and support vector machine (SVM) was used as a classifier. From the analysis, we could obtain a classification accuracy of 83.33 %, showing the feasibility of discriminating patients with BMD and SCH using EEG. We expect that our approach can be utilized for psychiatrists to more accurately diagnose the psychiatric disorders, BMD and SCH.

Keywords: bipolar mood disorder, electroencephalography, schizophrenia, machine learning

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Authors: Sophie Herr, Antoine Leybros, Yves Barre, Sergey Nikitenko, Rachel Pflieger

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The proportion of soil contaminated by a wide range of pollutants (heavy metals, PCBs, pesticides, etc.) of anthropogenic origin is constantly increasing, and it is becoming urgent to address this issue. Among remediation methods, soil washing is an effective, relatively fast, and widely used process. This study assesses its coupling with ultrasound: indeed, sonication induces the formation of cavitation bubbles in solution that enhance local mass transfer through agitation and particle erosion. The removal of target toxic elements Ni(II) and Zn(II) from vermiculite clay has been studied under 20 kHz ultrasound and silent conditions. Several acids were tested, and HCl was chosen as the solvent. The effects of solid/liquid ratio and particle size were investigated. Metal repartition in the clay has been followed by Tessier's sequential extraction procedure. The results showed that more metal elements bound to the challenging residual phase were desorbed with 20 kHz ultrasound than in silent conditions. This supports the promising application of ultrasound for heavy metal desorption in difficult conditions. Further experiments were performed at high-frequency US (362 kHz), and it was shown that fragmentation of the vermiculite particles is then limited, while positive effects of US in the decontamination are kept.

Keywords: desorption, heavy metals, ultrasound, vermiculite

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Authors: Pratyusha Das

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A paradigm shift has been noticed in the interpretation of DNA evidence for determining paternity. Sometimes DNA evidence has been accepted while sometimes it was rejected by the Indian Courts. Courts have forwarded various justifications for acceptance and rejection of such evidence through legal and scientific means. Laws have also been changed to accommodate the necessities of society. Balances between both the legal and scientific approaches are required, to make the best possible use of DNA evidence for the well-being of the society. Specifications are to be framed as to when such evidence can be used in the future by pointing out the pros and cons. Judicial trend is to be formulated to find out the present situation. The study of cases of superior courts of India using an analytical and theoretical approach is driving the questions regarding the shared identity of the legal and scientific approaches. To assimilate the differences between the two approaches, the basic differences between them have to be formulated. Revelations are required to access the favorable decisions using the DNA evidence. Reasons are to be forwarded for the unfavorable decisions and the approach preferred in such cases. The outcome of the two methods has to be assessed in relation to the parties to the dispute, the society at large, the researcher and from the judicial point of view. The dependability of the two methods is to be studied in relation to the justice delivery system. A highlight of the chronological study of cases along with the changes in the laws with the aid of presumptions will address the questions of necessity of a method according to the facts and situations. Address is required in this respect whether the legal and scientific forces converge somewhere pushing the traditional identification of paternity towards a fundamental change.

Keywords: cases, evidence, legal, scientific

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Authors: Noor Azwa Azreen Binti Abd. Aziz, Muhamad Zaim Bin Mohd Rozi

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Moving towards the 4th Industrial Revolution, artificial intelligence (AI) is now more popular than ever. This subject is gaining significance every day and is continually expanding, often merging with other fields. Instead of merely being passive observers, there are benefits to understanding modern technology by delving into its inner workings. However, in a world teeming with digital information, the impact of AI on the spread of disinformation has garnered significant attention. The dissemination of inaccurate or misleading information is referred to as misinformation, posing a serious threat to democratic society, public debate, and individual decision-making. This article delves deep into the connection between AI and the dissemination of false information, exploring its potential, risks, and ethical issues as AI technology advances. The rise of AI has ushered in a new era in the dissemination of misinformation as AI-driven technologies are increasingly responsible for curating, recommending, and amplifying information on online platforms. While AI holds the potential to enhance the detection and mitigation of misinformation through natural language processing and machine learning, it also raises concerns about the amplification and propagation of false information. AI-powered deepfake technology, for instance, can generate hyper-realistic videos and audio recordings, making it increasingly challenging to discern fact from fiction.

Keywords: artificial intelligence, digital information, disinformation, ethical issues, misinformation

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Authors: Mo-Se Lee, Cheol-Hwi Ahn, Kee-Young Kwahk, Hyunchul Ahn

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Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN (Convolutional Neural Network), which is known as effective solution for recognizing and classifying images, has been popularly applied to classification and prediction problems in various fields. In this study, we try to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. In specific, we propose to apply CNN as the binary classifier that predicts stock market direction (up or down) by using a graph as its input. That is, our proposal is to build a machine learning algorithm that mimics a person who looks at the graph and predicts whether the trend will go up or down. Our proposed model consists of four steps. In the first step, it divides the dataset into 5 days, 10 days, 15 days, and 20 days. And then, it creates graphs for each interval in step 2. In the next step, CNN classifiers are trained using the graphs generated in the previous step. In step 4, it optimizes the hyper parameters of the trained model by using the validation dataset. To validate our model, we will apply it to the prediction of KOSPI200 for 1,986 days in eight years (from 2009 to 2016). The experimental dataset will include 14 technical indicators such as CCI, Momentum, ROC and daily closing price of KOSPI200 of Korean stock market.

Keywords: convolutional neural network, deep learning, Korean stock market, stock market prediction

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Authors: A. Das, L. Hitihamillage, S. Moridpour

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Natural disasters are inevitable to the biodiversity. Disasters such as flood, tsunami and tornadoes could be brutal, harsh and devastating. In Australia, flooding is a major issue experienced by different parts of the country. In such crisis, delays in evacuation could decide the life and death of the people living in those regions. Congestion management could become a mammoth task if there are no steps taken before such situations. In the past to manage congestion in such circumstances, many strategies were utilised such as converting the road shoulders to extra lanes or changing the road geometry by adding more lanes. However, expansion of road to resolving congestion problems is not considered a viable option nowadays. The authorities avoid this option due to many reasons, such as lack of financial support and land space. They tend to focus their attention on optimising the current resources they possess and use traffic signals to overcome congestion problems. Traffic Signal Management strategy was considered a viable option, to alleviate congestion problems in the City of Geelong, Victoria. Arterial road with signalised intersections considered in this paper and the traffic data required for modelling collected from VicRoads. Traffic signalling software SIDRA used to model the roads, and the information gathered from VicRoads. In this paper, various signal parameters utilised to assess and improve the corridor performance to achieve the best possible Level of Services (LOS) for the arterial road.

Keywords: congestion, constraints, management, LOS

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Sahar Jahani, Meryem Ayse Yucel, David Boas, Seyed Kamaledin Setarehdan

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Near-infrared spectroscopy allows monitoring of oxy- and deoxy-hemoglobin concentration changes associated with hemodynamic response function (HRF). HRF is usually affected by natural physiological hemodynamic (systemic interferences) which occur in all body tissues including brain tissue. This makes HRF extraction a very challenging task. In this study, we used Kalman filter based on a general linear model (GLM) of brain activity to define the proportion of systemic interference in the brain hemodynamic. The performance of the proposed algorithm is evaluated in terms of the peak to peak error (Ep), mean square error (MSE), and Pearson’s correlation coefficient (R2) criteria between the estimated and the simulated hemodynamic responses. This technique also has the ability of real time estimation of single trial functional activations as it was applied to classify finger tapping versus resting state. The average real-time classification accuracy of 74% over 11 subjects demonstrates the feasibility of developing an effective functional near infrared spectroscopy for brain computer interface purposes (fNIRS-BCI).

Keywords: hemodynamic response function, functional near-infrared spectroscopy, adaptive filter, Kalman filter

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Authors: Anette Hay, Zama Simamane

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Capacity-building and integration of practical activities is one of the key SDGs of the 2030 Agenda for Sustainable Development. This paper will focus on SDG# 17 – “the means of implementation” - and the role of systems thinking in practice (STiP) in supporting both competence and SDG implementation capability in teacher education curricula at North-West University, South Africa. The “Environmental Management for Sustainability” module (EDTM 312), which is compulsory for all students enrolled in the education program at North-West University, will be used as a case study. There is a need for higher education to implement and practically integrate SDG goals into their curricula, and one way to achieve this is through the development of competencies. Education for Sustainable Development (ESD) has the potential to offer approaches that can be useful in the development of capacity-building activities to foster sustainability. The methodological approach adopted is based on a participatory paradigm followed by two cycles and reflection. This paper focuses on systems thinking in practice demonstrating how students apply and reflect on competencies to situations and how praxis captures the actual experiences. The results of this research indicated how to re-orientate the EDTM 312 curriculum to include an environmental justice focus. This research shares practical knowledge of systems thinking as a sustainability competency.

Keywords: education for sustainable development, environmental justice competencies, sustainable development goals, systems thinking in practice

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Authors: Reza Hosseinpourpia, Stergios Adamopoulos, Carsten Mai

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Medium density fiberboard (MDF) is a common category of wood-based panels that are widely used in the furniture industry. Fine lignocellulosic fibres are combined with a synthetic resin, mostly urea formaldehyde (UF), and joined together under heat and pressure to form panels. Like solid wood, MDF is a hygroscopic material; therefore, its moisture content depends on the surrounding relative humidity and temperature. In addition, UF is a hydrophilic resin and susceptible to hydrolysis under certain conditions of elevated temperatures and humidity, which cause dimensional instability of the panels. The latter directly affect the performance of final products such as furniture, when they are used in situations of high relative humidity. Existing water-repellent formulations, such as paraffin, present limitations related to their non-renewable nature, cost and highest allowed added amount. Therefore, the aim of the present study was to test the suitability of renewable water repellents as alternative chemicals for enhancing the dimensional stability of MDF panels. A small amount of tall oil based formulations were used as water-repellent agents in the manufacturing of laboratory scale MDF. The effects on dimensional stability, internal bond strength and formaldehyde release of MDF were tested. The results indicated a good potential of tall oil as a bio-based substance of water repellent formulations for improving the dimensional stability of MDF.

Keywords: dimensional stability, medium density fiberboard, tall oil, urea formaldehyde

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Authors: T. Esteves, S. Mesquita, A. Santos, A. Campina, C. Costa-Lobo

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The theme regarding the differentiation of high-performance athletes has always aroused curiosity and fascination, becoming a target for study, especially in the social and human sciences. It was from the 60's and 70's that the concern for the study of the excellence of athletes that showed indices of high performance in sports began to arise. From the 1990s, it became possible to specify the mental competencies and psychological characteristics associated with Olympic athletes with high levels of success. Several studies considered that well-structured pre-competitive and competitive routines and plans were predictors of sports success. Likewise, the high levels of motivation, commitment and concentration; the high levels of self-confidence and optimism; the presence of effective coping strategies to deal with distractions and unexpected situations or events; adequate regulation of activation and anxiety; the establishment and formulation of objectives; and mental visualization and practice were determinants in the manifestation of excellence in these athletes. As such, the promotion of these cognitive abilities has been emphasized in the good performance of the athletes. With the objective of implementing cognitive stimulation programs to meet the specific needs of talented athletes, together with pedagogical activities to promote educational strategies and promote interpersonal relationships, this communication systematizes a proposal for a psychopedagogical service to promote cognitive abilities in competitive athletes, SPAC, to implement in a Portuguese soccer team. This service will be based on a holistic vision in order to promote talent.

Keywords: athletes, cognitive abilities, high competition, psycho-pedagogical service

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Authors: Heba Ahmed Abdelaziz, Doaa Tawfik Mohamed Ibrahim

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Background: COVID-19 pandemic is the major health problem facing the world recently, causing variable effects on mental health and eating behavior. Aim of the study: Identifying changes in eating patterns and other health behaviors in relation to the anxiety caused by the COVID-19 pandemic lockdown in adult females in Alexandria, Egypt. Method: 344 adult females (20+ years old), were included in online self-administered questionnaire. Results: Severe anxiety symptoms was among 34.6% of the studied females especially; those aged 25-40 years, married, non-working or student females, females who had change in their work routine (half or full time from home). Homemade pastries and bakery product then beverages followed by fresh fruits and vegetables were frequently consumed by the studied females than before lockdown while fast foods were decreased during lockdown. Overweight and obesity were high among most of the participants with different grades of anxiety symptoms. Females with moderate and severe anxiety symptoms reported increase in appetite and body weight with irregular sleeping during lockdown. Conclusion: the current study concluded that stressful situations like lockdown due to COVID-19 pandemic is associated with anxiety (severe, moderate, mild then minimal, respectively) along with changes in eating habits, physical activity, sleeping pattern and smoking.

Keywords: COVID-19, lockdown, females, anxiety, eating, stress, lifestyle

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Authors: Niki K. Burns, James R. Pearson, Paul G. Stevenson, Xavier A. Conlan

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In Australian state Victoria, synthetic cannabinoids have recently been made illegal under an amendment to the drugs, poisons and controlled substances act 1981. Identification of synthetic cannabinoids in popular brands of ‘incense’ and ‘potpourri’ has been a difficult and challenging task due to the sample complexity and changes observed in the chemical composition of the cannabinoids of interest. This study has developed analytical methodology for the targeted extraction and determination of synthetic cannabinoids available pre-ban. A simple solvent extraction and solid phase extraction methodology was developed that selectively extracted the cannabinoid of interest. High performance liquid chromatography coupled with UV‐visible and chemiluminescence detection (acidic potassium permanganate and tris (2,2‐bipyridine) ruthenium(III)) were used to interrogate the synthetic cannabinoid products. Mass spectrometry and nuclear magnetic resonance spectroscopy were used for structural elucidation of the synthetic cannabinoids. The tris(2,2‐bipyridine)ruthenium(III) detection was found to offer better sensitivity than the permanganate based reagents. In twelve different brands of herbal incense, cannabinoids were extracted and identified including UR‐144, XLR 11, AM2201, 5‐F‐AKB48 and A796‐260.

Keywords: electrospray mass spectrometry, high performance liquid chromatography, solid phase extraction, synthetic cannabinoids

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Authors: Leonie Laskowitz

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A self-confident appearance is a basic prerequisite for success in the world of work 4.0. Within a few seconds, people convey a first impression that usually lasts. Artificial intelligence is making it increasingly important how our virtual selves appear and communicate (nonverbally) in digital worlds such as the metaverse. In addition to the modified creation of an avatar, the field of photogrammetry is developing fast, creating exact likenesses of ourselves in virtual environments. Given the importance of self-representation in virtual space for future collaborations, it is important to investigate the impact of phenotype in virtual worlds and how an avatar type can profitably be used situationally. We analyzed the effect of self-similar versus desirable self-presentation as an avatar on one's self-awareness, considering various theoretical constructs in the area of self-awareness and stress stimuli. The avatars were arbitrarily created on the one hand and scanned on the other hand with the help of a lidar sensor, the state-of-the-art photogrammetry method. All subjects were exposed to the established Trier Social Stress Test. The results showed that especially insecure people prefer to create rather than be scanned when confronted with a stressful work situation. (1) If they are in a casual work environment and a relaxed situation, they prefer a 3D photorealistic avatar that reflects them in detail. (2) Confident people will give their avatar their true appearance in any situation, while insecure people would only do so for honesty and authenticity. (3) Thus, the choice of avatar type has considerable impact on self-confidence in different situations.

Keywords: avatar, virtual identity, self-presentation, metaverse, virtual reality, self-awareness

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Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Muhammad Atif, Cang Yan

Abstract:

The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

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Authors: Hani Mekdash, Lina Jaber, Yehia Temsah

Abstract:

Underground space is becoming a necessity nowadays, especially in highly congested urban areas. Retaining underground excavations using shoring systems is essential in order to protect adjoining structures from potential damage or collapse. Reinforced Concrete Piles (RCP) supported by multiple rows of tie-back anchors are commonly used type of shoring systems in deep excavations. However, executing anchors can sometimes be challenging because they might illegally trespass neighboring properties or get obstructed by infrastructure and other underground facilities. A technique is proposed in this paper, and it involves the addition of eccentric high-strength steel strands to the RCP section through ducts without providing the pile with lateral supports. The strands are then vertically stressed externally on the pile cap using a hydraulic jack, creating a compressive strengthening force in the concrete section. An experimental study about the behavior of the shoring wall by pre-stressed piles is presented during the execution of an open excavation in an urban area (Beirut city) followed by numerical analysis using finite element software. Based on the experimental results, this technique is proven to be cost-effective and provides flexible and sustainable construction of shoring works.

Keywords: deep excavation, prestressing, pre-stressed piles, shoring system

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Authors: Mohsin Javed

Abstract:

School Education department is usually criticized for utilizing quite low or fewer academic days due to many reasons like extreme weather conditions, sudden holidays, summer vocations, pandemics and, terrorism etc. The purpose of the experimental study was to determine the efficacy of online cooperative learning (OCL) integrated in the rotation model of blended learning. The effects on academic achievement of students and students' attitude about OCL embedded learning were assessed. By using a posttest only control group design, sixty-two first-year students were randomly allocated to either the experimental (30) or control (32) group. The control group received face to face classes for six sessions per week, while the experimental group had three OCL and three formal sessions per week under rotation model. Students' perceptions of OCL were evaluated using a survey questionnaire. Data was analyzed by independent sample t test and one sample t test. According to findings, the intervention greatly improved the state of the dependent variables. The results demonstrate that OCL can be successfully implemented in formal education using a blended learning rotation approach. Higher secondary institutions are advised to use this model in situations like Covid 19, smog, unexpected holidays, instructor absence from class due to increased responsibilities, and summer vacations.

Keywords: blended learning, online cooperative learning, rotation model of blended learning, supplementing

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Authors: Shehroz Mukhtar, Maqsood Ahmed, Abdullah Mukhtar, Choudhry Shahid, Waqar Javaid

Abstract:

Code switching is a common phenomenon, generally observed in multilingual communities across the globe. A critical look at code switching literature reveals that mostly code switching has been studied in classroom in learning and teaching context while code switching outside classroom in settings such as café, hostel and so on have been the least explored areas. Current research investigated the reasons for code switching in the interactive practices of students and their perceptions regarding the same outside the classroom settings. This paper is the study of the common practice that prevails in the Universities of Sialkot that bilinguals mix two languages when they speak in different class room situations. In Pakistani classrooms where Multilingual are in abundance i.e. they can speak two or more than two languages at the same time, the code switching or language combination is very common. The teachers of Sialkot switch from one language to another consciously or unconsciously while teaching English in the class rooms. This phenomenon has not been explored in the Sialkot’s teaching context. In Sialkot private educational institutes does not encourage code-switching whereas the public or government institutes use it frequently. The crux of this research is to investigate and identify the importance of code switching by taking its users in consideration. Survey research method and survey questionnaire will be used to get exact data from teachers and students. We will try to highlight the functions and importance of code switching in foreign language classrooms of Sialkot and will explore why this trend is emerging in Sialkot.

Keywords: code switching, bilingual context, L1, L2

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Authors: Sultan Ayoub Meo

Abstract:

Environmental pollution is a highly challenging global concern of the 21st century and is a major cause of various communicable and non-communicable diseases. We investigate the impact of air pollution on "lung function, fractional exhaled nitric oxide, and cognitive function"in a group of one hundred young students studying in a traffic-polluted school. The students wereselected based on their age, gender, height, weight, and ethnicity. After the clinical history, one hundred students were recruited from the schoolnear and away from the polluted areas. The lung and cognitive functions were recorded. The results revealed that lung and cognitive function parameters were reduced in groups of students studying in a school located in a traffic-polluted area compared to thosestudying in a schoolsituated away from the traffic-polluted area. Environmental pollution impairs students' lung and cognitive functions studying in schools located within traffic-polluted areas. The health officials and policymakers establish strategies to minimize environmental pollution and its allied health hazards. Prof. Sultan Ayoub Meo, MD, Ph.D Professor, Department of Physiology, College of Medicine, King Saud University, Saudi Arabia Email. [email protected] / [email protected]

Keywords: environmental pOllution, lung physiology, cognitive functions, air pollution

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