Authors: Iman Hajirad

Abstract:

Water, as a vital element for human survival and natural ecosystems, has become one of the most pressing challenges in today’s world. Various crises, including diminishing water resources, climate change, and population growth, have made water resource management more critical than ever. In this context, artificial intelligence (AI), as an innovative technology, can play a pivotal role in optimizing water consumption, predicting water crises, and managing resources effectively. Leveraging big data, machine learning, the Internet of Things (IoT), and remote sensing, AI has significantly contributed to drought and flood prediction, agricultural irrigation optimization, and water quality management. This paper explores the applications of AI in water resource management, including water resource prediction and modeling, agricultural water use optimization, pollution control, and crisis management. The findings indicate that the implementation of AI technologies can enhance water resource management, reduce water waste, and preserve water quality.

Keywords: Water crisis, water resource management, water planning, artificial intelligence.

Authors: Behailu Shigute Habtemariam

Abstract:

The aim of the study was to examine the effects of training load on some selected fitness performance variables of volleyball players in the case of U-17 female volleyball project players in the Central Ethiopia region. In this study, quasi-experimental design was used. For the purpose of this study, 23 volleyball players were used as a subject from the two projects. The data collected through fitness performance assessment were analyzed and interpreted into a meaningful idea using manually as well as with computer in order to compare physical fitness variables and changes observed among participants. Those are taking part in the effects of training load on some selected physical fitness variables. The collected data were analyzed by means of the Statistical Package for Social Science version 20 (SPSS V20). The independent t-test was used to show the mean differences between the groups, and the paired t-test was used to compare the mean differences of the pre- and post-training within each group. The level of significance will be set at Alfa 0.05. The results are displayed using tables and figures. A significant difference was found in the mean differences of pre-test values (19.7 cm) and post-test values (37.5 cm) of the Durame city project on the flexibility test (MD = 17.8 cm, P = 0.00). On the other hand, there was a significant difference in the mean difference of pre-test values of (18 cm) and post-test values (26.3 cm) of the Hosana city project on the flexibility test (MD = 8.3 cm, P = 0.00). According to the results of the present studies, there were significant improvements from pre to post-test at Durame City and Hosana City projects on agility, flexibility, power, and speed fitness tests. On the other hand, a significant difference was not found before beginning the exercise between the two projects; however, a significant difference was found after 12 weeks of training.

Keywords: Overload, performance, training, volleyball.

Authors: Nattamon Srithammee, Ratchanikorn Chonchaiya

Abstract:

This study explores the impact of Augmented Reality (AR) technology on mathematics education, focusing on Area and Volume concepts at Phra Dabos School in Thailand. We developed a mobile AR application to present these mathematical concepts innovatively. Using a mixed-methods approach, we assessed the knowledge of 79 students before and after using the application. The results showed a significant improvement in students' understanding of Area and Volume, with average test scores increasing from 3.70 to 9.04 (p < 0.001, Cohen's d = 2.05). Students also reported increased engagement and satisfaction. Our findings suggest that AR technology can be a valuable tool in mathematics education, particularly for enhancing the understanding of abstract concepts like Area and Volume. This study contributes to research on educational technology in STEM education and provides insights for educators and educational technology developers.

Keywords: Augmented reality, mathematics education, area and volume, educational technology, STEM education.

Authors: Sintija Zalane

Abstract:

This paper examines the general protection and implementation of authors' moral rights in the copyright laws of Latvia, Lithuania, and Estonia, focusing on their legal frameworks in light of the Berne Convention. The analysis highlights how moral rights, such as authorship attribution, integrity of the work, and opposition to derogatory treatment, are upheld in these jurisdictions. The study compares national approaches to posthumous protection of moral rights and their interplay with economic rights. Drawing on legal texts and court decisions, the paper identifies challenges in enforcement and suggests harmonization opportunities to strengthen the moral rights framework across the Baltic region.

Keywords: Authors’ Moral Rights, Baltic States, Berne Convention, Copyright Laws, Legal Frameworks, Posthumous Protection.

Authors: Lu Ruei Tsen

Abstract:

Among Taiwanese high school students today, as academic stress increases during adolescence, it has become a major factor contributing to poor sleep, resulting in adverse impacts on mental health and academic performance. This study investigates the relationship between walking and sleep quality among Taiwanese high school students by utilizing Apple Watches for data collection. Addressing concerns over adolescents' sleep patterns due to academic stress and digital distractions, this research fills a gap in understanding the specific demographic within the Taiwanese context. Employing a quantitative approach, data were collected from 23 participants aged 15 to 18 years, focusing on their walking habits tracked by Apple Watches and sleep quality measured by the Pittsburgh Sleep Quality Index (PSQI). The findings suggest a positive correlation between walking and sleep quality, particularly among females. However, unexpected results, such as disparities in sleep quality among different age groups, highlight the complexity of factors influencing sleep patterns. While limitations exist, including potential confounding variables and sample size, this study provides valuable insights for future research. Recommendations for further research include exploring gender differences and conducting longitudinal studies across diverse demographics. Overall, this research indicates that encouraging adolescents to be more physically active, like walking, can enhance sleep quality.

Keywords: Sleep quality, Pittsburgh Sleep Quality Index, PSQI, walking, wearable device.

Authors: Abdulazeez Balogun Shittu

Abstract:

This paper examines the relationship between parochial religiosity and peaceful coexistence in Nigeria. Parochial views, characterized by exclusive interpretations and dogmatic adherence to one's faith, are identified as a significant obstacle to interreligious harmony and social cohesion. Using a mixed-methods approach, the paper investigates how parochial religiosity fosters intergroup tensions, undermines inclusive governance, and hinders constructive dialogue. The parochial religiosity significantly hinders peaceful coexistence in Nigerian society. This research contributes to the ongoing discourse on religion, conflict, and peace building, emphasizing the urgency of addressing parochial religiosity as a major obstacle to harmonious coexistence in multi-religious states in general and Nigerian society in particular.

Keywords: Parochial religiosity, peaceful coexistence, Nigerian society, interfaith relations, religious conflicts.

Authors: Rodrigo Costa, Thomas Mazzuchi, Shahram Sarkani

Abstract:

This study analyzes the evolution of Bitcoin Improvement Proposals (BIPs), the self-governing mechanism that enables updates to the Bitcoin protocol. By modeling BIP submission frequencies with a Negative Binomial distribution and detecting change points with the Pelt Rupture model, we identify three distinct intervals of proposal activity, suggesting shifts in development priorities over time. Long-term growth patterns, captured by Gompertz and Weibull models, indicate an S-shaped trend in cumulative BIP counts, pointing toward a maturation phase in Bitcoin’s protocol. Our findings suggest that Bitcoin may be entering a stable stage, with fewer fundamental changes and more incremental enhancements. This trend highlights the need for further research into BIP content and more studies into its dynamics to better understand decentralized protocol governance and maturation.

Keywords: Bitcoin improvement proposals, innovation management, change point detection, systems modeling and simulation.

Authors: Yulong Jia, Xiang Zhang, Ziyuan Wu, Shiji Hu

Abstract:

The calculation of bilinear pairing is the core of the SM9 algorithm, which relies on the underlying prime domain algorithm and the quadratic extension domain algorithm. Among the field algorithms, modular multiplication operation is the most time-consuming part. Therefore, the underlying modular multiplication algorithm is optimized to maximize the operation speed of bilinear pairings. This paper uses a modular multiplication method based on non-least positive (NLP) combined with Karatsuba and schoolbook multiplication to improve the Montgomery algorithm. At the same time, according to the characteristics of multiplication operation in quadratic extension domain, a quadratic extension domain FP2-NLP modular multiplication algorithm for bilinear pairings is proposed, which effectively reduces the operation time of modular multiplication in quadratic extension domain. The sub-expanded domain Fp2-NLP modular multiplication algorithm effectively reduces the operation time of modular multiplication under the second-expanded domain; The multiplication unit in the quadratic extension domain is implemented using SMIC55nm process, and two different implementation architectures are designed to cope with different application scenarios. Compared with the existing related literature, The output latency of this design can reach a minimum of 15 cycles. The shortest time for calculating the (AB+CD)r⁻¹ mod M form is 37.5ns, and the comprehensive area-time product (AT) is 11400, The final R-ate pairing algorithm hardware accelerator consumes 2670k equivalent logic gates and 1.8ms computing time in 55nm process.

Keywords: sm9, hardware, NLP, Montgomery.

Authors: Mustafa M. Donma

Abstract:

The associations among anthropometric measurements, body fat, and cardiometabolic parameters have attracted attention for years due to the importance and topicality of the subject. Gender is also an important factor to be considered during the evaluation of the study findings. Gender is particularly important in the field of pediatrics and during the interpretation of complete blood cell count parameters. These parameters are important because their ratios are being used as valuable and informative markers demonstrating cardiometabolic risk. The aim of this study was to introduce potential differences between male and female children in terms of the associations between these ratios and parameters closely related with obesity development. The study population was composed of 627 children, 58% were females and 42% were males. The body mass index (BMI) distribution of the groups was almost the same. The study was evaluated by the Institutional Ethics Committee and approved. Parents have given informed consent forms in behalf of their children to participate in the study. Anthropometric measurements were taken. Complete blood cell count, biochemical, and body fat percentage analysis were performed. BMI, neutrophil-to-lymphocyte (N/L) ratio, and aspartate aminotransferase-to-platelet count ratio were calculated. Statistical evaluations were performed by a statistical package program. BMI, circumferences of waist, hip, head, and neck values were higher, and body fat percentages of trunk and extremities were lower in males than females (p > 0.05). Increased eosinophil percent and alanine aminotransferase-to-aspartate aminotransferase ratio, decreased N/L ratio values in males were observed. Positive correlations between total body fat percent and N/L ratio in female children, and platelet count in male children were noteworthy. In conclusion, associations of total body fat percent with N/L and platelet count in female children and male children, respectively, point out the importance of N/L and platelet count in different genders for the future development of cardiovascular diseases.

Keywords: Body fat percentages, children, gender, neutrophil-to-lymphocyte ratio, platelet count.

Authors: Song Xinze, Cai Kejian

Abstract:

To further explore the application of waste plastics in asphalt pavement, this paper begins with the classification and characteristics of waste plastics. It then provides a state-of-the-art review of the preparation methods and processes of waste plastic modifiers, waste plastic-modified asphalt, and waste plastic-modified asphalt mixtures. The paper also analyzes the factors influencing the compatibility between waste plastics and asphalt and summarizes the performance evaluation indicators for waste plastic-modified asphalt and its mixtures. It explores the research approaches and findings of domestic and international scholars and presents examples of waste plastics applications in pavement engineering. We believe that there is a basic consensus that waste plastics can improve the high-temperature performance of asphalt. The use of cracking processes to solve the storage stability of waste plastic polymer-modified asphalt is the key to promoting its application. Additionally, we anticipate that future research will concentrate on optimizing the recycling, processing, screening, and preparation of waste plastics, along with developing composite plastic modifiers to improve their compatibility and long-term performance in asphalt pavements.

Keywords: Waste plastics, asphalt pavement, asphalt performance, asphalt modification.

Authors: Ebtesam Shadadi, Rasha Ibrahim, Essam Ghadafi

Abstract:

Phishing poses a significant threat as a cybercrime by tricking end users into revealing their confidential and sensitive information. Attackers often manipulate victims to achieve their malicious goals. The increasing prevalence of phishing has led to extensive research on this issue, including studies focusing on phishing attempts in healthcare institutions in the Kingdom of Saudi Arabia. This paper explores the importance of analyzing phishing attacks, specifically focusing on those targeting the healthcare industry. The study delves into the tactics, obstacles, and remedies associated with these attacks, all while considering the implications for Saudi Vision 2030.

Keywords: Phishing, cybersecurity, cyber threat, social engineering, Vision 2030.

Authors: Paul Toprac, Branden Heng, Harsheni Siddharthan, Allison Tseng, Sarah Abraham, Etienne Vouga

Abstract:

The goal of this project was to evaluate and document the capabilities and limitations of AI tools for empowering small teams to create high budget, high profile (AAA) 3D games typically developed by large studios. Two teams of novice game developers attempted to create two different games using AI and Unreal Engine 5.3. First, the teams evaluated 60 AI art, design, sound, and programming tools by considering their capability, ease of use, cost, and license restrictions. Then, the teams used a shortlist of 12 AI tools for game development. During this process, the following tools were found to be the most productive: ChatGPT 4.0 for both game and narrative concepting and documentation; Dall-E 3 and OpenArt for concept art; Beatoven for music drafting; ChatGPT 4.0 and Github Copilot for generating simple code and to complement human-made tutorials as an additional learning resource. While current generative AI may appear impressive at first glance, the assets they produce fall short of AAA industry standards. Generative AI tools are helpful when brainstorming ideas such as concept art and basic storylines, but they still cannot replace human input or creativity at this time. Regarding programming, AI can only effectively generate simple code and act as an additional learning resource. Thus, generative AI tools are at best tools to enhance developer productivity rather than as a system to replace developers.

Keywords: AAA Games, artificial intelligence, automation tools, game development.

Authors: Behnam Jay

Abstract:

In this study, the phenomenon called “Strengthening” in human language refers to the strategic use of multiple linguistic elements to intensify specific grammatical or semantic functions. This study explores cross-linguistic evidence demonstrating how Strengthening appears in various grammatical structures. To enhance the understanding and explanation of this phenomenon, various examples from languages such as English, French, Spanish, Japanese, and Turkish are provided. These examples illustrate how Strengthening operates in different grammatical structures, demonstrating its role in intensifying negation, politeness, and conditional meanings. Beyond these cases, Strengthening can also be observed in interrogative structures, where the combination of question words with rising intonation in various languages serves to enhance interrogative force. These instances suggest that Strengthening functions as a cross-linguistic strategy that may reflect a broader cognitive mechanism in language processing. This paper investigates these cases in detail, providing insights into why languages may adopt such strategies. The examples presented were not collected from a corpus but were instead drawn from languages the author encountered during their research, focusing on specific grammatical and morphological phenomena relevant to the concept of Strengthening. Due to the complexity of employing a comparative method across multiple languages, this approach was chosen to illustrate common patterns of Strengthening based on available data. It is acknowledged that different languages may have different Strengthening strategies in various linguistic domains. Future research should explore this phenomenon more thoroughly by including a wider range of languages and applying more rigorous comparative methods.

Keywords: Strengthening, cross-linguistic analysis, syntax, semantics, cognitive mechanism.

Authors: Zaid H. Yaseen, Jamel A. Orfi, Zeyad A. Alsuhaibani

Abstract:

Solar power has a huge potential to be employed in the fields of electricity production, water desalination, and multi generation. There are various types of solar collectors, and Parabolic Trough Collectors (PTCs) are common among these types. In PTCs, a mirror is used to direct the incident radiation on an absorber tube to utilize the heat in power generation. In this work, a PTC covered with a glass tube is presented and analyzed. Results showed that temperatures of 510 ℃ for steam can be reached for certain parameters. The work also showed the viability of using Benzene as the working fluid in the absorber tube. Also, some analysis regarding changing the absorber’s tube diameter and the efficiency of the solar collector was demonstrated in this work. The effect of changing the heat transfer correlations for the convection phenomena of the working fluid was illustrated. In fact, two heat transfer correlations: Dittus-Boelter and Gnielinski correlations were used, and the outcomes showed resemblance in the results for the maximum attainable temperature in the working fluid.

Keywords: Absorber tube, glass tube, incident radiation, parabolic trough collector.

Authors: S. Sarabandi, M. Rostampour Vajari

Abstract:

Breast cancer is the most frequent form of cancer among women and the fifth-leading cause of cancer-related deaths. A common feature of cancer cells is their ability to survive and evade apoptosis. Understanding the mechanisms of these pathways and their regulatory factors can lead to the development of effective treatment strategies. In this study, we aim to model the effect of key miRNAs, which are significant regulatory factors in breast cancer. We designed a Petri net focusing on two crucial pathways: proliferation and apoptosis, and identified the role of miRNAs in these pathways. Our analysis indicates that the upregulation of miRNAs 99a and 372 can effectively increase apoptosis and decrease proliferation. Moreover, we demonstrate that miRNA-600, previously reported as a potential candidate for treatment, may not be a suitable target due to its dual activity in proliferation. Therefore, further research is required to investigate the potential of this miRNA in cancer treatment. Our model shows that a combination of miRNA upregulation and knockdown can efficiently influence key genes such as MDM2 and PTEN, leading to the activation of apoptosis in cancer cells. Ultimately, our model successfully simulates the connection between regulatory miRNAs and key genes in breast cancer.

Keywords: Breast cancer, microRNAs, bio-modeling, petri net.

Authors: Elham Davoodi, Kylie King, Laura Jobson

Abstract:

Depression is one of the most common mental health disorders. Self-silencing theory adopts a socio-cultural lens to examine the development and maintenance of depression. Self-silencing can be a vulnerability factor in depression, and personality vulnerabilities (e.g., perfectionism) and moral emotions (e.g., guilt) are strongly related to self-silencing and depression. Yet, the relationships between all four variables among different cultural groups are not clear. We aimed to address this gap by examining whether perfectionism and depression are related indirectly through self-silencing and guilt and whether cultural group moderates these associations. Participants (N = 288) from either European Australian or Iranian Australian cultural backgrounds completed an online survey assessing self-silencing, guilt, perfectionism, and depression. First, we found an indirect relationship between perfectionism and depression through self-silencing. Second, using a serial mediation model, we found an indirect association between perfectionism and depression through self-silencing and guilt. There was no evidence that cultural groups moderated these indirect relationships. Our findings leave an important question for future longitudinal studies to answer; that is, whether the association between self-silencing and depression is oversimplified and whether moral emotions in this relationship have been overlooked.

Keywords: Perfectionism, depression, self-silencing, culture and guilt.

Authors: Anil Dhanawade, Akshay S., Harshal Lakesar

Abstract:

This paper presents a comprehensive analysis of the performance advantages offered by DSP (Digital Signal Processing) cores compared to traditional MCU (Microcontroller Unit) cores in the execution of various functions critical to real-time applications. The focus is on the integration of DSP functionalities, specifically in the context of motor control applications such as Field-Oriented Control (FOC), trigonometric calculations, back-Electromotive Force (EMF) estimation, digital filtering, and high-resolution PWM generation. Through comparative analysis, it is demonstrated that DSP cores significantly enhance processing efficiency, achieving faster execution times for complex mathematical operations essential for precise torque and speed control. The study highlights the capabilities of DSP cores, including single-cycle Multiply-Accumulate (MAC) operations and optimized hardware for trigonometric functions, which collectively reduce latency and improve real-time performance. In contrast, MCU cores, while capable of performing similar tasks, typically exhibit longer execution times due to reliance on software-based solutions and lack of dedicated hardware acceleration. The findings underscore the critical role of DSP cores in applications requiring high-speed processing and low-latency response, making them indispensable in automotive, industrial, and robotics sectors. This work serves as a reference for future developments in embedded systems, emphasizing the importance of architecture choice in achieving optimal performance in demanding computational tasks.

Keywords: Assembly code, Digital Signal Processing core, instruction set, Microcontroller Unit core.

Authors: Mojtaba Ghodsi, Morteza Mohammadzaheri, Payam Soltani

Abstract:

This study provides a detailed analysis of the LTC3588 as a low-power energy storage model, focusing on its internal circuitry and energy harvesting capabilities. The study highlights the relationship between the input and output capacitors and the behavior of the output voltage, particularly its rise time. It was found that increasing the input capacitance (Cin) from 1 µF to 220 µF reduces oscillations in the output voltage (Vout) and slows the rate of increase in the input voltage, demonstrating the impact of input capacitance on voltage dynamics. Furthermore, the study revealed that smaller output capacitors (Cout) result in fewer voltage jumps required to reach the target output voltage of 3.2 V, suggesting that a smaller Cout improves voltage regulation speed and stability. The study concludes that both input and output capacitors play a critical role in the LTC3588's performance. Optimizing these capacitors is crucial for efficient energy storage and harvesting in applications requiring minimal power consumption.

Keywords: LTC3588, energy storage, Zener Diode, LED.

Authors: Kim Michelle Siegling, Thomas Spengler, Sebastian Herzog

Abstract:

In personnel economics, the choice of a leadership style is about the question of how a supervisor should lead his or her employees in such a way that operational goals are achieved. In this paper, it is assumed that such leadership decisions are made according to the situation. Thus, the optimal or at least a permissible leadership style has to be selected from a set of several possible leadership styles. For this choice, a wide range of models has been developed in the scientific literature, from which the so-called normative decision model will be picked out and focused on. While the original model is based on univocal rules, this paper develops a fuzzy rule system.

Keywords: Fuzzy logic, leadership, leadership styles, rule-based systems.

Authors: Xiang Shijie, Zhou Dong, Tian Dan

Abstract:

This paper focuses on the application of real-time semantic segmentation technology in complex road condition recognition, aiming to address the critical issue of how to improve segmentation accuracy while ensuring real-time performance. Semantic segmentation technology has broad application prospects in fields such as autonomous vehicle navigation and remote sensing image recognition. However, current real-time semantic segmentation networks face significant technical challenges and optimization gaps in balancing speed and accuracy. To tackle this problem, this paper conducts an in-depth study and proposes a Guided Image Reconstruction Module. By resampling high-resolution images into a set of low-resolution images, this module effectively reduces computational complexity, allowing the network to more efficiently extract features within limited resources, thereby improving the performance of real-time segmentation tasks. In addition, a dual-branch network structure is designed in this paper to fully leverage the advantages of different feature layers. A Hybrid Attention Mechanism is also presented, which can dynamically capture multi-scale contextual information and effectively enhance the focus on important features, thus improving the segmentation accuracy of the network in complex road condition. Compared with traditional methods, the proposed model achieves a better balance between accuracy and real-time performance and demonstrates competitive results in road condition segmentation tasks, showcasing its superiority. Experimental results show that this method not only significantly improves segmentation accuracy while maintaining real-time performance, but also remains stable across diverse and complex road conditions, making it highly applicable in practical scenarios. By incorporating the Guided Image Reconstruction Module, dual-branch structure, and Hybrid Attention Mechanism, this paper presents an approach to real-time semantic segmentation tasks, which is expected to further advance the development of this field.

Keywords: Hybrid attention mechanism, image reconstruction, real-time, road condition recognition.

Authors: Babatunde Olatujoye, Binbin Yang

Abstract:

Microwave imaging is a portable, noninvasive, and non-ionizing imaging technique that employs low-power microwave signals to reveal objects in the microwave frequency range. This technique has immense potential for adoption in commercial and scientific applications such as security scanning, material characterization, and nondestructive testing. This work presents a monostatic microwave imaging setup using an Ultra-Wideband (UWB), low-cost, miniaturized Vivaldi antenna with a bandwidth of 1-6 GHz. The backscattered signals (S-parameters) of the Vivaldi antenna used for scanning targets were measured in the lab using a vector network analyzer (VNA). An automated two-dimensional (2D) scanner was employed for the 2D movement of the transceiver to collect the measured scattering data from different positions. The targets consist of four metallic objects, each with a distinct shape. A similar setup was also simulated in Ansys HFSS. A high-resolution Back Propagation Algorithm (BPA) was applied to both the simulated and experimental backscattered signals. The BPA utilizes the phase and amplitude information recorded over a 2D aperture of 50 cm x 50 cm with a discreet step size of 2 cm to reconstruct a focused image of the targets. The adoption of BPA was demonstrated by coherently resolving and reconstructing reflection signals from conventional time-of-flight profiles. For both the simulation and experimental data, BPA accurately reconstructed a high-resolution 2D image of the targets in terms of shape and location. An improvement of the BPA, in terms of target resolution, was achieved by applying the filtering method in the frequency domain.

Keywords: Backpropagation, microwave imaging, monostatic setup, Vivaldi antenna, ultra-wideband.

Authors: Babatunde Stephen Oladeji, Gloria Asuqouo Edet

Abstract:

The proximate, functional, pasting, and sensory properties of semolina from blends of cassava, maize, and rice were investigated. Cassava, maize, and rice were milled and sieved to pass through a 1000 µm sieve, then blended in the following ratios to produce five samples; FS1 (40:30:30), FS2 (20:50:30), FS3 (25:25:50), FS4 (34:33:33) and FS5 (60:20:20) for cassava, maize, and rice, respectively. A market sample of wheat semolina labeled as FSc served as the control. The proximate composition, functional properties, pasting profile, and sensory characteristics of the blends were determined using standard analytical methods. The protein content of the samples ranged from 5.66% to 6.15%, with sample FS2 having the highest value and being significantly different (p ≤ 0.05). The bulk density of the formulated samples ranged from 0.60 and 0.62 g/ml. The control (FSc) had a higher bulk density of 0.71 g/ml. The water absorption capacity of both the formulated and control samples ranged from 0.67% to 2.02%, with FS3 having the highest value and FSc having the lowest value (0.67%). The peak viscosity of the samples ranged from 60.83-169.42 RVU, and the final viscosity of semolina samples ranged from 131.17 to 235.42 RVU. FS5 had the highest overall acceptability score (7.46), but there was no significant difference (p ≤ 0.05) from other samples except for FS2 (6.54) and FS3 (6.29). This study establishes that high-quality and consumer-acceptable semolina that is comparable to the market sample could be produced from blends of cassava, maize, and rice.

Keywords: Semolina, gluten, celiac disease, wheat allergies.

Authors: M. H. Mohammadi Sanjani, A. Oraee, M. Fotuhi-Firuzabad, A. Amirnia, A. Taheri, M. Arabi

Abstract:

Ferroresonance effects cause overvoltage in medium voltage transformers and isolators used in electrical networks. Ferroresonance effects are nonlinear and occur between the network capacitor and the nonlinear inductance of the voltage transformer during saturation. This phenomenon is unwanted for transformers since it causes overheating, introduction of high dynamic forces in primary coils, and rise of voltage in primary coils for the voltage transformer. Furthermore, it results in electrical and thermal failure of the transformer. Expansion of distribution lines, design of the transformer in smaller sizes, and the increase of harmonics in distribution networks result in an increase of ferroresonance. There is limited literature available to improve the effects of ferroresonance; therefore, optimizing its effects for voltage transformers is of great importance. In this study, comprehensive modeling of a medium voltage transformer is performed. In addition, a model is proposed to improve the performance of voltage transformers during the occurrence of ferroresonance using damping oscillations. Also, transformer design optimization is presented in this study to show further improvements in the performance of the voltage transformer. The proposed model is experimentally tested and verified on a medium voltage transformer in the laboratory, and simulation results show a large reduction of the effects of ferroresonance.

Keywords: Optimization, voltage transformer, ferroresonance, damper.

Authors: Maria Tagarelli De Monte

Abstract:

In 2021, the passage of the law recognizing Italian Sign Language (LIS) as the language of the Italian deaf minority was the input for including this visual-gestural language in the curricula of interpreters and translators choosing the academic setting for their training. However, a gap remains concerning LIS education of teachers and communication assistants as referring figures for people who are deaf or hard of hearing in mainstream education. As well documented in the related scientific literature, deaf children often experience severe difficulties with the languages spoken in the country where they grow up, manifesting in all levels of literacy competence. In the research introduced here, the experience of deaf students (and their teachers) attending common schools is explored in areas that are characterized by strong native bilingualism, such as Friuli-Venezia Giulia (FVG), facing Italian Northeast borders. This region is peculiar as the native population may be bilingual Italian and Friulian (50% of the local population), German, and/or Slovenian. The research involved all schools of all levels in FVG to understand the relationship between the language skills expressed by teachers and those shown by deaf learners with a background in sign language. In addition to collecting specific information on the degree of preparation of teachers in deaf-related matters and LIS, the research has allowed to highlight the role, often poorly considered, covered by the communication assistants who work alongside deaf students. On several occasions, teachers and assistants were unanimous in affirming the importance of mutual collaboration and adequate consideration of the educational-rehabilitative history of the deaf child and her family. The research was based on a mixed method of structured questionnaires and semi-structured interviews with the referring teachers. As a result, a varied and complex framework emerged, showing an asymmetry in preparing personnel dedicated to the deaf learner. Considering how Italian education has long invested in creating an inclusive and accessible school system (i.e., with the "Ten Theses for Democratic Language Education"), a constructive analysis will complete the discussion in an attempt to understand how linguistic (and modal) differences can become levers of inclusion.

Keywords: Special education, deafness, LIS, teachers’ training, Friuli-Venezia Giulia, mainstream education, linguistic needs, teacher education, bilingual bimodal children, communication assistants, inclusion model.

Authors: Nene Pearl Eluchie

Abstract:

Globally, metal ion, particularly those generated from oil and gas effluents, form environmental pollution, particularly in developing regions like Nigeria, where water borne disease is fatal. This is clear evidence for metal ion contamination within the environment. Ecofriendly and cost-effective biomaterials are the best ways of reducing metal ion contamination, thus reducing the need for chemical treatment of oil and gas effluent. Despite this, research efforts to understand the mechanism of adsorption and possible biosorptive remediation interventions are limited. The study employed nano adsorption techniques such as UV-Visible spectroscopy, SEM, FTIR in a progressive manner to provide insight. The biosorption efficiency of A. indicasilver nanoparticle (AI-AgNPs) was within the range of 63-95%. The study demonstrates that AI-AgNPs can be a promising agent, cheap, efficient, and biodegradable adsorbent for lowering oil and gas contaminants. This is one of the few studies showing that A. indica is one of the many biomaterials that can be used to synthesize silver nanoparticles through the reduction of active constituents (such as Nimbidin) present in them to ensure stability and surface properties, which are critical for their performance in effluent treatment. Therefore, leveraging the knowledge from this study to raise awareness through public health initiatives and community engagement will help. The prevalence of metal ions observed in the visible region in the study indicates the need for biosorption approaches, not only in social settings but also in the immediate environment. There is, thus, an urgent need for targeted interventions in vulnerable communities.

Keywords: Azadirachta indica, biosorption, biosynthesis, effluent, Nimbidin, silver nanoparticle.

Authors: Büşra Nur Emre, Güven Kömürgöz Kırış

Abstract:

In recent years, the widespread use of electronic devices has led to a significant increase in nonlinear loads in power systems. These nonlinear loads generate harmonics, which degrade power quality and adversely affect the operation of transformers. Harmonic currents produced by nonlinear loads cause additional losses, leading to issues such as derating, overheating, and even transformer failures. Overheating, particularly the rise in hottest spot temperature during operation, is a critical consequence of harmonics. The hottest spot temperature is one of the most important factors influencing the operational lifespan of transformers. In this study, the additional load losses caused by nonlinear loads on transformers are analyzed. Following the analysis of these losses, their impact on the transformer hottest spot temperature and overall lifespan will be investigated. The study utilizes data from three-phase 6 MVA transformer with varying phase currents and harmonic content across the phases. The findings aim to provide insights into how harmonics exacerbate losses and thermal stress, ultimately affecting transformer performance.

Keywords: Harmonics, harmonic loss factor, hottest spot temperature, k-factor, transformers.

Authors: Donald Ouko

Abstract:

For decades, Africa has been home to several foreign companies doing business in various sectors. In recent years, China has consistently positioned itself as a development partner powerhouse among African nations. However, this has not been felt as equally beneficial to the local communities where the partnerships bloom in extractives trading. This paper explores the impact of Chinese involvement in mining on the local communities in three African countries, the factors that enable the sector to thrive amid the impacts, and what could be done differently for the local communities to experience a different outcome. It suggests alternative terms of engagement that aim at transparency, accountability, and anti-corruption to ensure inclusive social and economic development, and sound governance both at state and corporate levels.

Keywords: Accountability, anti-corruption, transparency, governance, social development, corporate social responsibility, disclosures, human rights.

Authors: Gianni Jacucci

Abstract:

Epistemology traditionally finds its place within human research philosophies and methodologies. Artificial Intelligence (AI) methods pose challenges, particularly given the unresolved relationship between AI and pivotal concepts in social arenas such as hermeneutics and accountability. We begin by examining the essential criteria governing scientific rigor in the human sciences. We revisit the three foundational philosophies underpinning qualitative research methods: empiricism, hermeneutics, and phenomenology. We elucidate the distinct attributes, merits, and vulnerabilities inherent in the methodologies they inspire. The integration of AI, e.g., deep learning algorithms, sparks an interest in evaluating these criteria against the diverse forms of AI architectures. For instance, Interpreted AI could be viewed as a hermeneutic approach, relying on a priori interpretations, while “straight” AI may be perceived as a descriptive phenomenological approach, processing original and uncontaminated data. And the incremental learning in chatbots like ChatGPT echoes the empiricist theory growth in grounded theory. This paper serves as groundwork for such explorations, offering preliminary reflections to lay the foundation and outline the initial landscape.

Keywords: Artificial intelligence, deep learning, epistemology, qualitative research, methodology, hermeneutics, accountability.

Authors: S. Rohmer

Abstract:

This paper proposes a progressive participatory observation that can be used as a sociological investigation within communities. The usefulness of participant observation in sociological projects is first asserted, particularly in an urban context. Competencies, know-how and interpersonal skills are then explained before to detail the progressive approach, consisting of four levels of observation. The progressive participatory observation is applied to an experimental project to set up a permaculture urban micro-farm with residents of a priority neighbourhood. Feedback on the experiment has identified several key recommendations for implementing the approach.

Keywords: Participatory observation, observation scale, priority neighbourhood, urban sociology.

Authors: ¬Yongbai Yin

Abstract:

The Friedmann–Lemaître–Robertson–Walker (FLRW) metric and the luminosity of remote radiation sources were re-derived in the Vacuum Space Decay (VSD) non-expanding universe model. The modified FLRW metric has a similar form to the classical FLRW metric, showing an elegant consistency of the VSD model with the known astronomical observation on the universe. The total radiation power of a blackbody rederived based on the fundamental physics law of the Planck’s blackbody radiation, as described by the modified Stefan–Boltzmann law, is independent of the stage of the universe, implying that the conservation law of total radiation energy in the universe is firmly upheld. The study confirms that the apparent magnitude or brightness of a remote radiation source at a given proper distance, as observed from Earth, aligns with the determination of the proper distance using the conventional methodology, such as those for the “Big Bang” model. This agreement supports the VSD non-expanding universe model in terms of that the conventional astronomical observation results can be integrated directly into the VSD model, eliminating the need on using concepts like “expanding”, “accelerate expanding”, “Dark Matter”, and “Dark Energy”. Furthermore, the temperature of a blackbody remains invariant across different stages of the universe. This finding bolsters the argument that the extraordinarily and unimaginably high-temperature radiation sources posited in the beginning of the universe in the “Big Bang” model are not required in the VSD model.

Keywords: FLRW metric, redshift, dark energy, dark matters, expanding universe, evolution of the universe, Planck’s law of blackbody radiation, the Stefan–Boltzmann law, the Stefan–Boltzmann law.

Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Mahmud Fotuhi-Firuzabad

Abstract:

The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially, Doubly Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as Static Var Compensator (SVC) and STATCOM are suitable for improving system output performance. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In this paper, optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for reactive power compensators is proposed. The design algorithm is formulated as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller improves the stability of the network and the fluctuations are at desired speed.

Keywords: Stability, reactive power compensator, doubly fed induction generator, optimal control system, genetic algorithm, Firefly algorithm.

Authors: Shyam Sunder Gupta

Abstract:

God is the infinite source of knowledge and periodically reveals tiny portions of His knowledge through chosen messengers, for good of mankind. Words revealed are perfectly designed and some content are identical and some different, as per need of mankind. These revelations are shared orally by messenger with masses and in due course of time, collected, edited and released in written form as scripture. Due to gap of time and communication issues, unintentionally, some errors and contradictions, within and between scriptures, have crept in, otherwise scriptures are in truth. There are three major religions, namely Christianity, Islam, and Hinduism, and their respective scriptures are; Bible, Quran, and Veda. Since source of all scriptures is one and the same, all scriptures are complementary and in true sense have Oneness. This oneness is proved through remarkable similarities between these scriptures by examining events such as the flood, creation of man and woman, the Last Day, and commonalities of popular names like Ram. Attributes of God described in all Scriptures are identical, namely; GOD is Eternal, Unborn, Immortal, Creator of Universe(s) and everything that exists within a Universe, Omnipotent, Omnipresent, Omniscient, Subtlest of all, Unchangeable, Unique, Always Works, Source of Eternal Bliss, etc., establishing oneness of scriptures and oneness of God.

Keywords: God, oneness, revelation, scriptures, words.

Authors: H. Al-Jabli

Abstract:

The presence of heavy metals like cadmium, arsenic, lead, and mercury in the drinking water can be a threat to public health. The measurement of these heavy metal concentrations in drinking water has, therefore, assumed a priority. The National Primary Drinking Water Regulations have set limits for the concentrations of these elements in drinking water because of their toxicity. Bromate formed during the disinfection of drinking water by Ozonation can also be a health hazard. This study concentrated on compiling all available data and information on the presence of trace metals and bromate in the drinking water in residential areas distributed over different governorates in Kuwait. New data were also generated through sampling of drinking water at some of the houses present in different residential areas of Kuwait, and they were analyzed for the contents of trace metals and bromate. The generated data are stored in Excel files and are used for preparing maps showing the distribution of these metals and bromate in the drinking water of Kuwait. SURFER software was used for this purpose. Correlation among different chemical parameters was also investigated in the study using the GRAPHER software. Results showed that the bromate and trace metals concentrations in the drinking water of residential areas in Kuwait governorates fall within the drinking water guideline values of World Health Organization (WHO), the Environment Public Authority (KEPA), and the Gulf Cooperation Council (GCC). Result also indicated that Alnahdha shows the highest values for Sr, BrO3, B and Zn, whereas the lowest values were observed at Abdullah Mubarak, Al-Khairan, Al-Qasr, and Bayan, respectively. Al-Fardous showed the maximum concentration of Cu and minimum in Electrical Conductivity (EC). The highest values of EC were observed in Saad Al-Abdullah with minimum Cu concentration. Although the drinking water quality in residential regions in Kuwait met the drinking guidelines of water by different authorities, the concentration of some of the trace elements varied in different governorates.

Keywords: Heavy metals, bromate, ozonation, GIS.

Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

Abstract:

Synthetic data generated by Generative Adversarial Networks and Autoencoders are becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic Generative Adversarial Networks (GAN) such as the Gaussian copula. We present the results from two synthetic data sets Conditional Tabular Generative Adversarial Network (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the Receiver Operating Characteristic Curve ROC and Area Under the curve AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: Synthetic data generation, Generative Adversarial Networks, GANs, Conditional Tabular GAN, CTGAN, Gaussian copula.

Authors: Mohammed H. Rasheed, Hussein Nadhem Fadhel, Mohammed M. Siddeq

Abstract:

In this paper, we presented tools for evaluating image quality that effectively align with human perception, emphasizing their usefulness in assessing the visual quality of images. These tools offer quantitative metrics to facilitate the comparison of various image compression algorithms. Specifically, we propose two metrics designed to measure the quality of decompressed images. These metrics utilize combined data (CD) derived from both the original and decompressed images to deliver accurate assessments. By comparing the results of our proposed metrics with widely used standards such as Peak Signal-to-Noise Ratio (PSNR) and Root Mean Square Error (RMSE), we demonstrate that our approach provides a closer match to human visual perception of image quality. This alignment underscores the practical application of the proposed metrics in scenarios requiring subjective evaluation accuracy.

Keywords: RMSE, Root Mean Square Error, PSNR, Peak Signal-to-Noise Ratio, image quality metrics, image compression.

Authors: Devante K. Barrett

Abstract:

The objective of this research is to evaluate the association between one's subjective tiredness as it relates to the Stroop effect and the identification of subjective tiredness among adolescents. Individuals with a high subjective tired score are more likely to have a lower reaction time in incongruent trials. It is understood that sleep is an overlooked phenomenon in psychological research, and with the utilization of adequate testing, ways to address sleep in this manner may no longer be an issue of concern in the future. Sleep researchers often obtain significant results by way of Stroop testing. The caveat is that the integrity of Stroop testing can be negatively affected by various external factors. The propensity for interference to occur is caused by the automatic process of reading. This is deemed one of the most detrimental issues in understanding the dimensions of sleep. Interference subsequently decreases response time in the identification of the ink color. Considering the fact that the Stroop task is helpful in evaluating cognitive function in clinical populations, results should be interpreted cautiously due to the multitude of variables that may affect performance. When planning studies and analyzing data related to the Stroop effect, researchers must take individual differences and environmental factors into consideration. Having a thorough understanding of the Stroop effect can aid in the development of initiatives targeted at enhancing attention span and cognitive control across a range of demographics. Age-related changes in sleep patterns and selective attention from childhood to adolescence are key points of consideration in various areas of research, which are primarily focused on age-dependent performance in vigilant attention among young populations. Thus, findings related to Stroop testing may be deemed eligible to provide meaningful implications regarding vigilant attention among such populations. With respect to future research, this can be assessed by way of neuroimaging of brain-regions associated with selective attention and circadian cycles.

Keywords: Sleep, selective attention, Stroop effect, cognitive function, sleep hygiene, vigilant attention.

Authors: Florian Kessels, Niklas Reitz, Marko Schuba

Abstract:

Operational technology (OT) controls physical processes in critical infrastructures and economically important industries. With the convergence of OT with classical information technology (IT), rising cybercrime worldwide and the increasingly difficult geopolitical situation, the risks of OT infrastructures being attacked are growing. Classical penetration testing, in which testers take on the role of an attacker, has so far found little acceptance in the OT sector - the risk that a penetration test could do more harm than good seems too great. This paper examines the resilience of various OT systems using typical penetration test tools. It is shown that such a test certainly involves risks, but is also feasible in OT if a cautious approach is taken. Therefore, OT penetration testing should be considered as a tool to improve the cyber security of critical infrastructures.

Keywords: Penetration testing, operational technology, industrial control systems, operational technology security.

Authors: Mohamed Mesbah, Bruce Janson

Abstract:

An interchange is the most important component of freeway and highway facilities. It is working as a connector between the highway’s elements. The main goal of designing interchanges is to provide an acceptable level of service and delay to make vehicles move smoothly when they are entering and exiting the interchange. There are many factors that can have a significant impact on the level of service; the main factors are traffic volumes, and type of interchange. This paper will discuss interchange with roundabouts under various values of traffic volumes to determine the level of service of the interchanges that will be studied in this paper and replace the system of interchange from roundabout to traffic signal to make a significant compression between these systems. A secondary goal is to propose improvements for scenarios where the level of service is deemed unacceptable. This will be achieved using Synchro traffic simulation software, which facilitates the simulation and optimization of interchanges to enhance operational efficiency and safety.

Keywords: Interchange, roundabout, traffic signal, Synchro, delay, level of service, traffic volumes, vehicles, simulation, optimization, adjustment.