Search results for: Saudi vision 2030

Authors: A. Almubrad, R. Clouse, A. Aljlaoud

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Organizational culture (OC) is recognized to have an influence on the propensity of organizations to innovate. It is also presumed that it may impede the innovation process from thriving within the organization. Investigating the role organizational culture plays in enabling or inhibiting innovation merits exploration to investigate organizational cultural attributes necessary to reach innovation goals. This study aims to investigate a preliminary matching heuristic of OC attributes to the type of innovation that has the potential to thrive within those attributes. A mixed methods research approach was adopted to achieve the research aims. Accordingly, participants from a national telecom company in Saudi Arabia took the Organizational Culture Assessment Instrument (OCAI). A further sample selected from the respondents’ pool holding the role of managing directors was interviewed in the qualitative phase. Our study findings reveal that the market culture type has a tendency to adopt radical innovations to disrupt the market and to preserve its market position. In contrast, we find that the adhocracy culture type tends to adopt the incremental innovation type and found this tends to be more convenient for employees due to its low levels of uncertainty. Our results are an encouraging indication that matching organizational culture attributes to the type of innovation aids in innovation management. This study carries limitations while drawing its findings from a limited sample of OC attributes that identify with the adhocracy and market culture types. An extended investigation is merited to explore other types of organizational cultures and their optimal innovation types.

Keywords: incremental innovation, radical innovation, organization culture, market culture, adhocracy culture, OACI

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Authors: Talha A. Al-Dubai, Rashad A. Bantan, Ramadan H. Abu-Zied, Brian G. Jones, Aaid G. Al-Zubieri

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Contemporary foraminiferal samples sediments were collected from the intertidal sabkha of Al-Kharrar Lagoon, Saudi Arabia, to study the vertical distribution of Foraminifera and, based on a modern training set, their potential to develop a predictor of former sea-level changes in the area. Based on hierarchical cluster analysis, the intertidal sabkha is divided into three vertical zones (A, B & C) represented by three foraminiferal assemblages, where agglutinated species occupied Zone A and calcareous species occupied the other two zones. In Zone A (high intertidal), Agglutinella compressa, Clavulina angularis and C. multicamerata are dominant species with a minor presence of Peneroplis planatus, Coscinospira hemprichii, Sorites orbiculus, Quinqueloculina lamarckiana, Q. seminula, Ammonia convexa and A. tepida. In contrast, in Zone B (middle intertidal) the most abundant species are P. planatus, C. hemprichii, S. orbiculus, Q. lamarckiana, Q. seminula and Q. laevigata, while Zone C (low intertidal) is characterised by C. hemprichii, Q. costata, S. orbiculus, P. planatus, A. convexa, A. tepida, Spiroloculina communis and S. costigera. A transfer function for sea-level reconstruction was developed using a modern dataset of 75 contemporary sediment samples and 99 species collected from several transects across the sabkha. The model provided an error of 0.12m, suggesting that intertidal foraminifers are able to predict the past sea-level changes with high precision in Al-Kharrar Lagoon, and thus the future prediction of those changes in the area.

Keywords: Lagoonal foraminifers, intertidal sabkha, vertical zonation, transfer function, sea level

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Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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Authors: Shuruq Ghazi Nahhas

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Islamic art is a decorative art that depends on repeating motifs in various shapes to cover different surfaces. Each motif has its own characteristics and style that may reflect different Islamic periods, such as Umayyad, Abbasid, Fatimid, Seljuk, Nasrid, Ottoman, and Safavid. These periods were the most powerful periods which played an important role in developing the Islamic motifs. Most of these motifs of the Islamic heritage were not used in new applications. This research focused on reviving the vegetal Islamic motifs found on Islamic heritage and redesign them in a new format to decorate various products, including scarfs, cushions, coasters, wallpaper, wall art, and boxes. The scarf is chosen as one element of these decorative products because it is used as accessories to add aesthetic value to fashion. A descriptive-analytical method is used for this research. The process started with extracting and analyzing the original motifs. Then, creating the new motifs by simplifying, deleting, or adding elements based on the original structure. Then, creating repeated patterns and applying them to decorative products. The findings of this research indicated: repeating patterns based on different structures creates unlimited patterns. Also, changing the elements of the motifs of a pattern adds new characteristics to the pattern. Also, creating frames using elements from the repeated motifs adds aesthetic and contemporary value to decorative products. Finally, using various methods of combining colors creates unlimited variations of each pattern. At the end, reviving the Islamic motifs in contemporary vision enriches decorative products with aesthetic, artistic, and historical values of different Islamic periods. This makes the decorative products valuable that adds uniqueness to their surroundings.

Keywords: Islamic motifs, contemporary patterns, scarfs, decorative products

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Authors: Raed Alsufyani, Hissam Tawfik, Victor Chang, Muthu Ramachandran

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This study investigates the factors that influence the decision by players in the healthcare sector to embrace Cloud Business Intelligence Technology with a focus on healthcare organizations in Saudi Arabia. To bring this matter into perspective, this study primarily considers the Technology-Organization-Environment (TOE) framework and the Human Organization-Technology (HOT) fit model. A survey was hypothetically designed based on literature review and was carried out online. Quantitative data obtained was processed from descriptive and one-way frequency statistics to inferential and regression analysis. Data were analysed to establish factors that influence the decision to adopt Cloud Business intelligence technology in the healthcare sector. The implication of the identified factors was measured, and all assumptions were tested. 66.70% of participants in healthcare organization backed the intention to adopt cloud business intelligence system. 99.4% of these participants considered security concerns and privacy risk have been the most significant factors in the adoption of cloud Business Intelligence (CBI) system. Through regression analysis hypothesis testing point that usefulness, service quality, relative advantage, IT infrastructure preparedness, organization structure; vendor support, perceived technical competence, government support, and top management support positively and significantly influence the adoption of (CBI) system. The paper presents quantitative phase that is a part of an on-going project. The project will be based on the consequences learned from this study.

Keywords: cloud computing, business intelligence, HOT-fit model, TOE, healthcare and innovation adoption

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Authors: Adel M. Al-Shutairi, Ahmed H. Al-Zahrani

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Tea is a popular beverage drunk by millions of people throughout the globe. Tea has considerable health advantages, in-cluding antioxidant, antibacterial, antiviral, chemopreventive, and anticarcinogenic properties. As a result of environmental pollution (atmospheric deposition) and the production process, tealeaves may also include a variety of dangerous substances, such as polycyclic aromatic hydrocarbons (PAHs). In this study, graphene oxide reinforced chitosan/poly-nitroaniline polymer was prepared to develop a sensitive and reliable solid phase extraction method (SPE) for extraction of PAH7 in tea samples, followed by high-performance liquid chromatography- fluorescence detection. The prepared adsorbent was validated in terms of linearity, the limit of detection, the limit of quantification, recovery (%), accuracy (%), and precision (%) for the determination of the PAH7 (benzo[a]pyrene, benzo[a]anthracene, benzo[b]fluoranthene, chrysene, benzo[b]fluoranthene, Dibenzo[a,h]anthracene and Benzo[g,h,i]perylene) in tea samples. The concentration was determined in two types of tea commercially available in Saudi Arabia, including black tea and green tea. The maximum mean of Σ7PAHs in black tea samples was 68.23 ± 0.02 ug kg-1 and 26.68 ± 0.01 ug kg-1 in green tea samples. The minimum mean of Σ7PAHs in black tea samples was 37.93 ± 0.01 ug kg-1 and 15.26 ± 0.01 ug kg-1 in green tea samples. The mean value of benzo[a]pyrene in black tea samples ranged from 6.85 to 12.17 ug kg-1, where two samples exceeded the standard level (10 ug kg-1) established by the European Union (UE), while in green tea ranged from 1.78 to 2.81 ug kg-1. Low levels of Σ7PAHs in green tea samples were detected in comparison with black tea samples.

Keywords: polycyclic aromatic hydrocarbons, CS, PNA and GO, black/green tea, solid phase extraction, Saudi Arabia

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Authors: Syed Farooq Adil, Merajuddinkhan, Mujeeb Khan, Hamad Z. Alkhathlan

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Phytochemicals from plant extracts belong to an important source of natural products which have demonstrated excellent cytotoxic activities. However, plants of different origins exhibit diverse chemical compositions and bioactivities. Therefore, the discovery of plants based new anticancer agents from different parts of the world is always challenging. In this study, methanolic extracts of different parts of 11 plants from Saudi Arabia have been tested in vitro for their anticancer potential on human liver cancer cell line (HepG2). Particularly, for this study, plants from Asteraceae, Resedaceae, and Polygonaceae families were chosen on the basis of locally available ethnobotanical data and their medicinal properties. Among 12 tested extract samples, three samples obtained from Artemisia monosperma stem, Ochradenus baccatus aerial parts, and Pulicaria glutinosa stem have demonstrated interesting cytotoxic activities with a cell viability of 29.3%, 28.4% and 24.2%, respectively. Whereas, four plant extracts including Calendula arvensis aerial parts, Scorzonera musilii whole plant, A. monosperma leaves show moderate anticancer properties bearing a cell viability ranging from 11.9 to 16.7%. The remaining extracts have shown poor cytotoxic activities. Subsequently, GC-MS analysis of methanolic extracts of the four most active plants extracts such as C. comosum, O. baccatus, P. glutinosa and A. monosperma detected the presence of 41 phytomolecules. Among which 3-(4-hydroxyphenyl) propionitrile (1), 8,11-octadecadiynoic acid methyl ester (2), 6,7-dimethoxycoumarin (3), and 1-(2-hydroxyphenyl) ethenone (4) were found to be the lead compounds of C. comosum, O. baccatus P. glutinosa and A. monosperma, respectively.

Keywords: medicinal plants, asteraceae, polygonaceae, hepg2

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Mohammad Al-Refai, Majed Wakid

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Introduction: Soil-transmitted diseases (STD) are caused by intestinal worms that are transmitted via various routes into the human body resulting in various clinical manifestations. The intestinal worms causing these infections are known as soil transmitted helminths (STH), including Hook worms, Ascaris lumbricoides (A. lumbricoides), Trichuris trichiura (T. trichiura), and Strongyloides sterocoralis (S. sterocoralis). Objectives: The aim of this study was to investigate the prevalence of STH among newly arrived expatriate labors in Jeddah city, Saudi Arabia, using three different techniques (direct smears, sedimentation concentration, and real-time PCR). Methods: A total of 188 stool specimens were collected and investigated at the parasitology laboratory in the Special Infectious Agents Unit at King Fahd Medical Research Center, King Abdulaziz University in Jeddah, Saudi Arabia. Microscopic examination of wet mount preparations using normal saline and Lugols Iodine was carried out, followed by the formal ether sedimentation method. In addition, real-time PCR was used as a molecular tool to detect several STH and hookworm speciation. Results: Out of 188 stool specimens analyzed, in addition to STH parasite, several other types were detected. 9 samples (4.79%) were positive for Entamoeba coli, 7 samples (3.72%) for T. trichiura, 6 samples (3.19%) for Necator americanus, 4 samples (2.13%) for S. sterocoralis, 4 samples (2.13%) for A. lumbricoides, 4 samples (2.13%) for E. histolytica, 3 samples (1.60%) for Blastocystis hominis, 2 samples (1.06%) for Ancylostoma duodenale, 2 samples (1.06%) for Giardia lamblia, 1 sample (0.53%) for Iodamoeba buetschlii, 1 sample (0.53%) for Hymenolepis nana, 1 sample (0.53%) for Endolimax nana, and 1 sample (0.53%) for Heterophyes heterophyes. Out of the 35 infected cases, 26 revealed single infection, 8 with double infections, and only one triple infection of different STH species and other intestinal parasites. Higher rates of STH infections were detected among housemaids (11 cases) followed by drivers (7 cases) when compared to other occupations. According to educational level, illiterate participants represent the majority of infected workers (12 cases). The majority of workers' positive cases were from the Philippines. In comparison between laboratory techniques, out of the 188 samples screened for STH, real-time PCR was able to detect the DNA in (19/188) samples followed by Ritchie sedimentation technique (18/188), and direct wet smear (7/188). Conclusion: STH infections are a major public health issue to healthcare systems around the world. Communities must be educated on hygiene practices and the severity of such parasites to human health. As far as drivers and housemaids come to close contact with families, including children and elderlies. This may put family members at risk of developing serious side effects related to STH, especially as the majority of workers were illiterate, lacking the basic hygiene knowledge and practices. We recommend the official authority in Jeddah and around the kingdom of Saudi Arabia to revise the standard screening tests for newly arrived workers and enforce regular follow-up inspections to minimize the chances of the spread of STH from expatriate workers to the public.

Keywords: expatriate labors, Jeddah, prevalence, soil transmitted helminths

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Authors: Hana Aljumayi, Mohammed Issa

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The aim of this study was to investigate the effect of the training program for professional athletes at the Saudi Archery Federation on the electrical activity of the muscles involved in pulling the bowstring, maximum muscle strength (MVC) and to identify the relationship between the electrical activity of these muscles and accuracy in shooting among female archers. The researcher used a descriptive approach that was suitable for the nature of the study, and a sample of nine female archers was selected using purposive sampling. An EMG device was used to measure signal amplitude, signal frequency, spectral energy signal, and MVC. The results showed statistically significant differences in signal amplitude among muscles, with F(8,1)=5.91 and a significance level of 0.02. There were also statistically significant differences between muscles in terms of signal frequency, with F(8,1)=8.23 and a significance level of 0.02. Bonferroni test results indicated statistically significant differences between measurements at a significance level of 0.05, with anterior measurements showing an average difference of 16.4 compared to other measurements. Furthermore, there was a significant negative correlation between signal amplitude in the calf muscle and accuracy in shooting (r=-0.78) at a significance level of 0.02. There was also a significant positive correlation between signal frequency in the calf muscle and accuracy in shooting (r=0.72) at a significance level of 0.04. In conclusion, it appears that the training program for archery athletes focused more on skill development than physical aspects such as muscle activity and strength development. However, it did have a statistically significant effect on signal amplitude but not on signal frequency or MVC development in muscles involved in pulling the bowstring.

Keywords: electrical activity of muscles, archery sport, shooting accuracy, muscles

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Authors: Al Muneef Maha, Al Tamimi Dana

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Introduction: Child maltreatment was proven to negatively impact children’s and adolescent’s academic performances; showing less academic achievements, problems completing homework assignments, and was marginally associated with being frequently absent from school (1). Objectives: To identify the impact of child maltreatment on school performance among adolescents in National Guard Schools. Materials and Methods: The study was conducted at National Guard schools in Riyadh. Students aged 12-19 years were invited to participate. Participants (N=674) completed the survey instrument which included demographics, exposure to different types of abuse, and overall level of academic performance. Results: Participants’ mean age was 15.6±1.6 years and males (53%). Ninety-five percent lived with both parents, 2% with single parent, and 3% with step parents. Four percent lived with alcoholic parents or guardians, and 7% have lived with a family member who has been arrested or imprisoned. Poor performance (failure in exam) were more likely among the students who lived with alcoholics vs. non-alcoholics (33% vs. 11%, p<0.01), imprisoned family member vs. non-imprisoned (26% vs. 11%, p<0.01), psychologically abused vs. not abused (21% vs. 10%, p<0.01), physically abused vs. not abused (19% vs. 9%, p<0.01). Predisposing factors to poor performance in school included living with alcoholic parents or guardians (OR=2.8, CI=1.1-6.7), psychologically abused (OR=1.7, CI=1.0-3.0), and physically abused (OR=1.7, CI=1.0-2.8). Conclusions: The results suggest that child maltreatment may adversely impact school performance. These findings highlight the importance of increasing the awareness about the impact of child maltreatment on school performance among families, schools, and the community. Recommend to the Ministry of Education to consider counseling of students with poor performance due to adverse child experiences or maltreatment.

Keywords: child abuse, child maltreatment, school performance, Saudi Arabia

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Authors: Abdullah S. Alghamdi, Khaled Alghamdi, Richard O. Jenkins, Parvez I. Haris

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Background: Physical activity is an important factor in the treatment and prevention of type 2 diabetes mellitus (T2DM). Reduction in HbA1c level, an important diabetes biomarker, was reported in patients who increased their daily physical activity. Although the ambient temperature was reported to be positively correlated to a negative impact on health and increase the incidences of diabetes, the exposure to bright sunlight was recently found to be associated with enhanced insulin sensitivity and improved beta-cell function. How Ramadan alters physical activity, and especially sunlight exposure, has not been adequately investigated. Aim: This study aimed to assess the physical activity and sun exposure of Saudis with T2DM over different periods (before, during, and after Ramadan) and related this to HbA1c levels. Methods: This study recruited 82 Saudis with T2DM, who chose to fast during Ramadan, from the Endocrine and Diabetic Centre of Al Iman General Hospital, Riyadh, Saudi Arabia. Ethical approvals for this study were obtained from De Montfort University and Saudi Ministry of Health. Physical activity and sun exposure were assessed by a self-administered questionnaire. Physical activity was estimated using the International Physical Activity Questionnaire (IPAQ), while the sun exposure was assessed by asking the patients about their hours per week of direct exposure to the sun, and daily hours spent outdoors. Blood samples were collected in each period for measuring HbA1c. Results: Low physical activity was observed in more than 60% of the patients, with no significant changes between periods. There were no significant variances between periods in the daily hours spent outdoors and the total number of weekly hours of direct exposure to the sun. The majority of patients reported only few hours of exposure to the sun (1h or less per week) and time spent outdoors (1h or less per day). The mean HbA1c significantly changed between periods (P = 0.001), with lowest level during Ramadan. There were significant differences in the mean HbA1c between the groups for the level of physical activity (P < 0.001), with significant lower mean HbA1c in the higher-level group. There were no significant variances in the mean of HbA1c between the groups for the daily hours spent outdoors. The mean HbA1c of the patients, who reported never in their total weekly hours of exposure to the sun, was significantly lower than the mean HbA1c of those who reported 1 hour or less (P = 0.001). Conclusion: Physical inactivity was prevalent among the study population with very little exposure to the sun or time spent outdoors. Higher level of physical activity was associated with lower mean HbA1c levels. Encouraging T2DM patients to achieve the recommended levels of physical activity may help them to obtain greater benefits of Ramadan fasting, such as reducing their HbA1c levels. The impact of low direct exposure to the sun and the time spent outdoors needs to be further investigated in both healthy and diabetic patients.

Keywords: diabetes, fasting, physical activity, sunlight, Ramadan

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Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

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Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: Khulud Alhussain, Anna Gavine, Stephen Macgillivray, Sushila Chowdhry

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Background: Estimates show that by the year 2030, mental illness will account for more than half of the global economic burden, second to non-communicable diseases. Often, the perinatal period is characterised by psychological ambivalence and a mixed anxiety-depressive condition. Maternal mental disorder is associated with perinatal anxiety and depression and affects breastfeeding behaviors. Studies also indicate that maternal mental health can considerably influence a baby's health in numerous aspects and impact the newborn health due to lack of adequate breastfeeding. However, studies reporting factors associated with breastfeeding behaviors are predominantly quantitative. Therefore, it is not clear what literature is available to understand the factors affecting breastfeeding and perinatal women’s perspectives and experiences. Aim: This review aimed to explore the perceptions and experiences of women with perinatal anxiety and depression, as well as how these experiences influence their breastfeeding behaviours. Methods: A systematic literature review of qualitative studies in line with the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ). Four electronic databases (CINAHL, PsycINFO, Embase, and Google Scholar) were explored for relevant studies using a search strategy. The search was restricted to studies published in the English language between 2000 and 2022. Findings from the literature were screened using a pre-defined screening criterion and the quality of eligible studies was appraised using the Walsh and Downe (2006) checklist. Findings were extracted and synthesised based on Braun and Clark. The review protocol was registered on PROSPERO (Ref: CRD42022319609). Result: A total of 4947 studies were identified from the four databases. Following duplicate removal and screening 16 studies met the inclusion criteria. The studies included 87 pregnant and 302 post-partum women from 12 countries. The participants were from a variety of economic, regional, and religious backgrounds, mainly from the age of 18 to 45 years old. Three main themes were identified: Barriers to breastfeeding, breastfeeding facilitators, emotional disturbance, and breastfeeding. Seven subthemes emerged from the data: expectation versus reality, uncertainly about maternal competencies, body image and breastfeeding, lack of sufficient breastfeeding support for family and caregivers’ support, influences positive breastfeeding practices, breastfeeding education, and causes of mental strain among breastfeeding women. Breastfeeding duration is affected in women with mental health disorders, irrespective of their desire to breastfeed. Conclusion: There is significant empirical evidence that breastfeeding behaviour and perinatal mental disturbance are linked. However, there is a lack of evidence to apply the findings to Saudi women due to lack of empirical qualitative information. To improve the psychological well-being of mothers, it is crucial to explore and recognise any concerns with their mental, physical, and emotional well-being. Therefore, robust research is needed so that breastfeeding intervention researchers and policymakers can focus on specifically what needs to be done to help mentally distressed perinatal women and their new-born.

Keywords: pregnancy, perinatal period, anxiety, depression, emotional disturbance, breastfeeding

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Authors: M. A. Zaki Ewiss, S. Afifi

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Nahda University (NUB) believes that internationalisation of higher educational is able to provide global society with an education that meets current needs and that can respond efficiently to contemporary demands and challenges, which are characterized by globalisation, interdependence, and multiculturalism. In this paper, we will discuss the the challenges of the Egyptian Higher Education system and the future vision to improve this system> In this report, the following issues will be considered: Increasing knowledge on the development of specialized programs of study at the university. Developing international cooperation programs, which focus on the development of the students and staff skills, and providing academic culture and learning opportunities. Increasing the opportunities for student mobility, and research projects for faculty members. Increased opportunities for staff, faculty and students to continue to learn foreign universities, and to benefit from scholarships in various disciplines. Taking the advantage of the educational experience and modern teaching methods; Providing the opportunities to study abroad without increasing the period of time required for graduation, and through greater integration in the curricula and programs; More cultural interaction through student exchanges.Improving and providing job opportunities for graduates through participation in the global labor market. This document sets out NUB strategy to move towards that vision. We are confident that greater explicit differentiation, greater freedom and greater collaboration are the keys to delivering the further improvement in quality we shall need to retain and strengthen our position as one of the world’s leading higher education systems.

Keywords: technology transfer higher education, knowledge transfer, internationalisation, mobility

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Authors: Xi Liu, Fan Yuan

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In the evolving landscape of physics-based machine learning (PBML), particularly within fluid dynamics and its applications in electromechanical engineering, robot vision, and robot learning, achieving precision and alignment with researchers' specific needs presents a formidable challenge. In response, this work proposes a methodology that integrates neural transformation with a modified smoothed particle hydrodynamics model for generating transformed 3D fluid simulations. This approach is useful for nanoscale science, where the unique and complex behaviors of viscoelastic medium demand accurate neurally-transformed simulations for materials understanding and manipulation. In electromechanical engineering, the method enhances the design and functionality of fluid-operated systems, particularly microfluidic devices, contributing to advancements in nanomaterial design, drug delivery systems, and more. The proposed approach also aligns with the principles of PBML, offering advantages such as multi-fluid stylization and consistent particle attribute transfer. This capability is valuable in various fields where the interaction of multiple fluid components is significant. Moreover, the application of neurally-transformed hydrodynamical models extends to manufacturing processes, such as the production of microelectromechanical systems, enhancing efficiency and cost-effectiveness. The system's ability to perform neural transfer on 3D fluid scenes using a deep learning algorithm alongside physical models further adds a layer of flexibility, allowing researchers to tailor simulations to specific needs across scientific and engineering disciplines.

Keywords: physics-based machine learning, robot vision, robot learning, hydrodynamics

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Authors: Natalya G. Filimonova, Mariya G. Ozerova, Irina N. Ermakova

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The long-term strategy of the economic development of Russia up to 2030 is based on the concept of sustainable growth. The determining factor of such development is complex changes in the economic system which may be achieved by making progressive changes in its structure. The structural changes determine the character and the direction of economic development, as well as they include all elements of this system without exception, and their regulated character ensures the most rapid aim achievement. This article has discussed the industrial structure of the agriculture in Russia. With the use of the system of indexes, the article has determined the directions, intensity, and speed of structural shifts. The influence of structural changes on agricultural production development has been found out. It is noticed that the changes in the industrial structure are synchronized with the changes in the organisation and economic structure. Efficiency assessment of structural changes allowed to trace the efficiency of structural changes and elaborate the main directions for agricultural policy improvement.

Keywords: Russian agricultural sectors, sectoral structure, organizational and economic structure, structural changes

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Authors: Al-Hindi Rashad, Alotibi Ibrahim

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The aim of this study was to examine the antibacterial activity of the peroxide components of some locally produced honeys: Toran, Zaitoon (Olive), Shaflah, Saha, Jizan, Rabea Aja, Fakhira, Sedr Aljanoob, Tenhat, Karath and Bareq against two of the drug resistant bacteria; i.e., methicillin resistant Staph. aureus (MRSA, ATCC 43330) and Acinetobacter baumannii. Measurement of the antibacterial activity of honey samples by using the agar well diffusion method was adopted as follows: by using turbidity standard McFaraland 0.5, suspensions of bacterial strains MRSA ATCC 43330 and Acinetobacter baumannii were prepared. By the spreading plate method, 100 µl of the suspension was inoculated onto Muller-Hinton agar medium. On the inoculated agar medium, five wells were made using a sterile cork borer (diameter 5 mm).100 µl of honey dilutions (10%, 30%, 50%, 70% and 100%) were used. The study indicated that the highly effective activity was in some local honey samples such as Toran honey against MRSA, and Shafalah honey against MRSA and Acinetobacter baumannii which showed bactericidal effects at concentrations 70 % to 100 % as well. The majority of local honey samples recorded bacteriostatic effects on MRSA and Acinetobacter baumannii at consternations 50 % and above. In conclusion this investigation indicated that in regard to the majority inhibitory effect on microorganisms, the existing of H2O2 in honey samples together with phenolic content greatly provide a strong antibacterial activities among different types of honey, because in some previous studies the H2O2 content of honey interacts with phenolic content and showed better inhibitory effect than in absent of H2O2.

Keywords: antibacterial activity, honey, hospital acquired, Saudi Arabia

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Authors: Ghaleb Bin Huraib, Fahad Al Harthi, Misbahul Arfin, Abdulrahman Al-Asmari

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Atopic dermatitis (AD), also known as atopic eczema, is a chronic inflammatory skin disease characterized by severe itching and recurrent relapsing eczema-like skin lesions, affecting up to 20% of children and 10% of adults in industrialized countries. AD is a complex multifactorial disease, and its exact etiology and pathogenesis have not been fully elucidated. The aim of this study was to investigate the impact of gene polymorphisms of T helper cell subtype Th1 and Th2 cytokines, interferon-gamma (IFN-γ), interleukin-6 (IL-6) and transforming growth factor (TGF)-β1on AD susceptibility in a Saudi cohort. One hundred four unrelated patients with AD and 195 healthy controls were genotyped for IFN-γ (874A/T), IL-6 (174G/C) and TGF-β1 (509C/T) polymorphisms using ARMS-PCR and PCR-RFLP technique. The frequency of genotypes AA and AT of IFN-γ (874A/T) differed significantly among patients and controls (P 0.001). The genotype AT was increased while genotype AA was decreased in AD patients as compared to controls. AD patients also had higher frequency of T containing genotypes (AT+TT) than controls (P = 0.001). The frequencies of allele T and A were statistically different in patients and controls (P = 0.04). The frequencies of genotype GG and allele G of IL-6 (174G/C) were significantly higher while genotype GC and allele C were lower in AD patients than controls. There was no significant difference in the frequencies of alleles and genotypes of TGF-β1 (509C/T) polymorphism between patient and control groups. These results showed that susceptibility to AD is influenced by presence or absence of genotypes of IFN-γ (874A/T) and IL-6 (174G/C) polymorphisms. It is concluded that T-allele and T-containing genotypes (AT+TT) of IFN-γ (874A/T) and G-allele and GG genotype ofIL-6 (174G/C) polymorphisms are susceptible to AD in Saudis.On the other hand, the TGF-β1 (509C/T) polymorphism may not be associated with AD risk in Saudi population however further studies with large sample size are required to confirm these findings.

Keywords: atopic dermatitis, interferon-γ, interleukin-6, transforming growth factor-β1, polymorphism

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Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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Authors: Amrita Mishra, Tushar Kanti Das

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Agriculture is the backbone of the economy of Odisha. Sustainability of agriculture holds the key for the development of Odisha. The Sustainable Development Goals are a framework of 17 goals and 169 targets across social, economical and environmental areas of sustainable development. Among all the seventeen goals the second goal is focusing on the promotion of Sustainable Agriculture. In this research our main aim is also to contribute an understanding of effectiveness of sustainable agriculture as a tool for rural development in the selected tribal district (i.e. Koraput and Malkangiri) of Odisha. These two districts are comes under KBK districts of Odisha which are identified as most backward districts of Odisha. The objectives of our study are to investigate the effect of sustainable agriculture on the lives of tribal farmers, to study whether the farmers are empowered by their participation in sustainable agriculture initiatives to move towards their own vision of development and to study the investment and profit ratio in sustainable agriculture. This research will help in filling the major gaps in sociological studies of sustainable agriculture. This information will helpful for farmers, development organisations, donors and policy makers in formulating the development of effective initiatives and policies to support the development of sustainable agriculture. In this study, we have taken 210 respondents and used various statistical techniques like chi-square test, one-way ANOVA and percentage analysis. This research shows that sustainable agriculture is an effective development strategy that benefits the tribal farmers to move towards their own vision of Good Fortune. The poor farmers who struggle to feed their families and maintain viable livelihoods on shrinking land for them sustainable agriculture are really benefited. The farmers are using homemade pesticides, manure and also getting the seeds from different development organisations and Government. So the investment in Sustainable Agriculture is very less. All farmers said their lives are now better than before. The creation of farmers groups for training and marketing for the produces was shown to be very important for empowerment.

Keywords: sustainable, agriculture, tribal farmers, development, empowerment

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Authors: Faraj Alhamami

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The effects of classroom input through structured input activities have been addressing two main lines of inquiry: (1) measuring the effects of structured input activities as a possible causative factor of PI and (2) comparing structured input practice versus other types of instruction or no-training controls. This line of research, the main purpose of this classroom-based research, was to establish which type of activities is the most effective in processing instruction, whether it is the explicit information component and referential activities only or the explicit information component and affective activities only or a combination of the two. The instruments were: a) grammatical judgment task, b) Picture-cued task, and c) a translation task as pre-tests, post-tests and delayed post-tests seven weeks after the intervention. While testing is ongoing, preliminary results shows that the examination of participants' pre-test performance showed that all five groups - the processing instruction including both activities (RA), Traditional group (TI), Referential group (R), Affective group (A), and Control group - performed at a comparable chance or baseline level across the three outcome measures. However, at the post-test stage, the RA, TI, R, and A groups demonstrated significant improvement compared to the Control group in all tasks. Furthermore, significant difference was observed among PI groups (RA, R, and A) at post-test and delayed post-test on some of the tasks when compared to traditional group. Therefore, the findings suggest that the use of the sole application and/or the combination of the structured input activities has succeeded in helping Saudi learners of English make initial form-meaning connections and acquire RRCs in the short and the long term.

Keywords: input processing, processing instruction, MOGUL, structure input activities

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Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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Authors: Esther Paul, Ibrahim A. M. Alzaydani, Al Hakami, Caryl Beynon

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Research Objectives and Goal: The main aim of the current study was to explore the perspectives of healthcare workers on Healthcare-associated infections (HAI) and infection control measures in a tertiary care Hospital in Abha, Saudi Arabia. As per our knowledge, this is perhaps the first qualitative study on HAI to be done in Saudi Arabia. The goal of the study was to understand the perspectives of the healthcare workers on the current protocol and guidelines for HAI and infections control measures in the hospital, the effectiveness of the current protocol for HAI and infection control measures and ways of reducing the incidence of HAI and improve infection control measures. Methods used: A qualitative research design was used to collect the data from 25 healthcare workers consisting of doctors and nurses, recruited by Snowball strategy via semi-structured interviews which were audio-recorded and transcribed verbatim immediately. An interview guide consisting of open-ended questions about the existing HAI and infection control practices in the healthcare facility, the awareness of the healthcare workers about HAI and the need for safe infection control measures were used to collect the data. The transcribed data were analyzed using the thematic analysis method. Results: Using thematic analysis four themes were identified.1.Knowledge of HAI and infection control 2. Infection control measures in practice 3. The gap in infection control measures and HAI 4. Required Implementations. The first theme covered the participants' knowledge on HAI, its definition, the types of HAI and the infection control measures.Most of the participants were aware of HAI and had some idea of the definition of HAI, its significance and the dangers posed by HAI, but few residents had no idea of the types of HAI. The second theme was focussed on the infection control measures in practice. Most of the participants were aware of the importance of infection control measures like hand hygiene, catheter care, and waste disposal. The nurses were responsible for most of the disinfection and sterilization measures and practiced it effectively. However, some doctors and residents had no inkling about these measures. The third theme emphasized that although most of the participants were aware of HAI and infection control measures and were in practice. There were some lacunae regarding their knowledge of the different types of HAI, Personal Protective Equipment practices, communication among the healthcare personnel and the hospital administrations and the means of waste disposal. The fourth and the final theme identified that most of the participants felt the need for implementations of changes regarding existing protocols, workshops/seminars, methods of waste disposal and sterilization and disinfection practices. Conclusion: The current qualitative study concluded that there is a need for better educational programs and hands-on training for all the healthcare personnel including the paramedical staff as well. The residents should have adequate knowledge of infection control practices to guide the nurses and should share the responsibility with the nurses in the practice of effective infection control measures

Keywords: healthcare-associated infections, infection control measures, perspectives, qualitative

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Alyaa Farouk AbdelFattah Ibrahim, Agnes Monica, Dolores I. Cabansag

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The prevalence of diabetes mellitus is reaching epidemic proportions in many parts of the world causing an increasing public health concern. Cases of Type 2 diabetes are rapidly increasing in the Middle East region. Deprived of lifestyle deviations, a section of the Middle East’s inhabitants will be pretentious by 2035. As all sociocultural factors have created unhealthy lifestyles, which have become part of the social norms within Saudi society, thereby increased the prevalence of sedentary lifestyle and obesity in women living in Saudi Arabia. So, this study aimed to assess the impact of diabetes mellitus on quality of life of female nursing students in King Saud bin Abdulaziz University for Health Sciences, Riyadh. In a crossectional study design, 151 nursing students at King Saud bin Abdulaziz University for health sciences in Riyadh were included in the study. Biosociodemographic questionnaire and Short-Form 36 (SF-36) Health Related Quality of life Survey Arabic version were used for data collection, and all included students were screened for random blood glucose level. Results depicted that among 151 subjects included in the study 17 (11.3%) had diagnosed medical problems, and 29.4% of those participants with medical problems were diabetics. Univariate regression model for the relation between diabetes mellitus and overall percent score of SF-36 health survey domains showed no statistically significant difference between diabetic and non-diabetic subjects 0.990(0.931-1.053). In conclusion, although the diabetes prevalence was high among the study subjects it did not affect their quality of life may be due to age of the study population.

Keywords: diabetes mellitus, diabetes prevalence, quality of life, university students' health

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Authors: Rachelle McFarlane

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The Second Decade of Action Road Safety has begun with increased focus on countries who are disproportionately affected by road fatalities. Researchers highlight the low effectiveness of road safety campaigns in Latin America and the Caribbean (LAC) still reporting approximately 130,000 deaths and six million injuries annually. The regional fatality rate 19.2 per 100,000 with heightened concern for persons 15 to 44 years. In 2021, 483 Jamaicans died in 435 crashes, with 33% of these fatalities occurring during Covid-19 curfew hours. The study objective is to conduct a systemic safety review of Jamaican road crashes and provide a framework for its use in complementing traditional methods. The methodology involves the use of the FHWA Systemic Safety Project Selection Tool for analysis. This tool reviews systemwide data in order to identify risk factors across the network associated with severe and fatal crashes, rather that only hotspots. A total of 10,379 crashes with 745 fatalities and serious injuries were reviewed. Of the focus crash types listed, 50% of ‘Pedestrian Accidents’ resulted in fatalities and serious injuries, followed by 32% ‘Bicycle’, 24% ‘Single’ and 12% of ‘Head-on’. This study seeks to understand the associated risk factors with these priority crash types across the network and recommend cost-effective countermeasures across common sites. As we press towards Vision Zero, the inclusion of the systemic safety review method, complementing traditional methods, may create a wider impact in reducing road fatalities and serious injury by targeting issues across network with similarities; focus crash types and contributing factors.

Keywords: systemic safety review, risk factors, road crashes, crash types

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Authors: Ingy Ibrahim El-Darwish, Neveen Youssef Azmy

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The endowment of a healthy environment can be implemented by endorsing sustainable fundamentals. Design of sustainable buildings through recycling of waste, can reduce health problems, provide good environments and contribute to the aesthetically pleasing entourage. Such environments can help in providing energy-saving alternatives to consolidate the principles of sustainability. The poor community awareness and the absence of laws and legislation in Egypt for waste management specifically in residential areas have led to an inability to provide an integrated system for waste management in urban and rural areas. Many problems and environmental challenges face the Egyptian urban environments. From these problems, is the lack of a cohesive vision for waste collection and recycling for energy-saving. The second problem is the lack public awareness of the short term and long term vision of waste management. Bad practices have adversely affected the efficiency of environmental management systems due to lack of urban legislations that codify collection and recycling of residential communities in Egyptian urban environments. Hence, this research tries to address residents on waste management matters to facilitate legislative process on waste collection and classification within residential units and outside them in a preparation phase for recycling in the Egyptian urban environments. In order to achieve this goal, one of the Egyptian communities has been addressed, analyzed and studied. Waste collection, classification, separation and access to recycling places in the urban city are proposed in preparation for a legislation ruling and regulating the process. Hence, sustainable principles are to be achieved.

Keywords: recycling, residential buildings, sustainability, waste

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Authors: Ivan Kuzio

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The GIZ/TTC project is the first of its kind in the Middle East, which allows the development of a teaching training programme to degree level based on modern methodologies. The graduates from this college are part of the Saudization programme and will, over the next four years be part of and eventually run the new Colleges of Excellence. The new Colleges of Excellence are being developed to create a local vocationally trained workforce and will run initially alongside the current Colleges of Technology.

Keywords: blended learning, pedagogy, training, key competencies, social skills, cognitive development

Procedia PDF Downloads 308