Papers by WARSE The World Academy of Research in Science and Engineering
International Journal of Bio-Medical Informatics and e-Health, 2024
This study investigates the utilization patterns of primary healthcare services across various de... more This study investigates the utilization patterns of primary healthcare services across various demographic groups in the Kingdom of Saudi Arabia (KSA) between 2010 and 2014. Employing a descriptive methodology, the research analyzes data from the Saudi Ministry of Health and case studies to identify trends and disparities in healthcare access and utilization. The findings reveal significant variations based on age, gender, socioeconomic status, and geographic location, highlighting the need for targeted interventions and policies to improve healthcare equity and access in KSA. Recommendations include expanding healthcare infrastructure in underserved areas, implementing community outreach programs, enhancing data collection and analysis to inform evidence-based decision-making, and developing policies that address the unique needs of different demographic groups.
International Journal of Networks and Systems, 2023
The distributed and secure nature of blockchain technology makes it an effective tool for combati... more The distributed and secure nature of blockchain technology makes it an effective tool for combating corruption, increasing transparency, and streamlining processes across fields like healthcare, government, and finance. This research demonstrates that blockchain technology can revolutionize government transparency, financial management, and corporate structures. In nations with high corruption indices, combining blockchain with forensic accounting significantly enhances the openness and accountability of anti-corruption efforts. System integration challenges, legal constraints, a shortage of skilled professionals, and scalability issues hinder blockchain adoption from reaching its potential. Overcoming these obstacles requires further research, legal frameworks, and cross-sector collaboration. To enhance decision-making in a data-driven economy and maximize blockchain's potential, a governance model that integrates big data analytics with blockchain could enable secure, transparent, and scalable adoption.
International Journal of Advances in Computer Science and Technology, 2024
There is no such thing as bulletproof authentication, and multi-factor authentication (MFA) is no... more There is no such thing as bulletproof authentication, and multi-factor authentication (MFA) is not bulletproof either. There are attacks against MFA. In this paper, we not only present a historical outline of the most significant MFA attacks but also review the available taxonomy tools. Our aim is to equip enterprises with a clear understanding of how MFA attacks may occur and how these are classified. More importantly, we provide proactive considerations on how MFA attacks may be prevented, empowering enterprises to take action.
International Journal of Information Systems and Computer Sciences, 2024
Talent development is essential to ensure organization ready to survive in the market. Although i... more Talent development is essential to ensure organization ready to survive in the market. Although it is essential, many organizations have yet taken it seriously and relies on traditional method. Recent IT technology development has changed the way the company develops its talents. It enables to simplify major bureaucracy, save unnecessary costs and talent development can be done ubiquitously. The article takes a case study of PN, an Indonesian state-owned energy company to enhance talent development program especially Training Need Assessment (TNA) methods. The PN director has mandated the current TNA method should embrace recent IT technology, to simplify TNA preparation and improve efficiency in delivery time. The article examines the use of cloud-based TNA application to promote TNA program to prepare world class talents as mandated in corporate program. Cloud technology facilitates the course designers and Subject Matter Experts (SMEs) in all training centers to collaborate and reuse the TNA materials and delivery.
International Journal of Science and Applied Information Technology , 2024
Talent development is essential task to ensure all staffs reach minimum competency levels as expe... more Talent development is essential task to ensure all staffs reach minimum competency levels as expected by the organization. The complexity of talent development increases along with the wider range of organization level. The article takes a case study of PN, an Indonesian stateowned energy company that operates in nationwide. Indonesia has thousand islands, and many remote areas surrounds with mountains; have created difficult efforts to develop talent in those remote areas. Currently, PN has more than 40 thousand staffs nationwide, and director of company has emphasized the use of latest IT technology to support talent development process. The article proposes the use of blockchain technology to support MOOC delivery to support talent development process and talent placement in new position. Blockchain technology has two advantages such as: secure access (unalterable data) and distributable to registered member. The use of blockchain to support corporate program to prepare readiness of all talents ready to cope with global and national uncertainty in energy industry. The outcome of article is expected to be used in other stateowned companies to prepare talent readiness.
International Journal of Emerging Trends in Engineering Research, 2024
The rapid evolution of wireless communication technologies, along with the increasing demand for ... more The rapid evolution of wireless communication technologies, along with the increasing demand for efficient and reliable data transfer, has driven the rethinking of traditional cellular network architectures in the context of next-generation networks. In conventional cellular systems, communication between users typically occurs through base stations. However, to improve efficiency, scalability, and spectral utilization, device-to-device (D2D) communication has been introduced, enabling direct data transmission between users without base station involvement. In this paper, we present a comprehensive review of D2D communication from architectural and challenges perspective for future generation networks. Additionally, the study focuses on relay-assisted D2D (RAD2D) communication, examining the role of machine learning (ML) and artificial intelligence (AI) in optimizing relay selection processes. In light of the existing literature, challenges for implementing RAD2D are discussed from different perspectives such as relay selection, energy efficiency, secure communication, resource allocation, and the management of dynamic network conditions.
International Journal of Advanced Trends in Computer Science and Engineering , 2024
The aim of this paper is to highlight the effect or popularity of synchronous E-learning environm... more The aim of this paper is to highlight the effect or popularity of synchronous E-learning environment in Distance education. Day by day, as information technologies improving, the mode of learning is changing from asynchronous to synchronous e-learning. System can provide the real-time interaction between the remote students and the instructor just like in the classroom lecture. Synchronous training is done in real-time with a live instructor facilitating the training. Everyone logs in at a set time and can communicate directly with the instructor and with each other. It lasts for a set amount of time-from a single session to several weeks, months or even years. This type of training usually takes place via Internet Web sites, audio-or videoconferencing, Internet telephony, or even two-way live broadcasts to students in a classroom.
International Journal of Advanced Trends in Computer Science and Engineering , 2024
The transformer architecture, first introduced in 2017 by researchers at Google, has revolutioniz... more The transformer architecture, first introduced in 2017 by researchers at Google, has revolutionized natural language processing in various tasks, including text classification. This architecture formed the basis of future models such as those used in hate speech detection in code-switched text. In this research, we conduct a comparative study of transformer-based models for hate speech detection in English-Kiswahili code-switched text. First, the models were compared as feature extractors using a traditional classifier and then as end-to-end classifiers. The three multilingual transformer-based models compared include mBERT, mDistilBERT and XLM-RoBERTa, using SVM as the traditional classifier for the extracted features. The HateSpeech_Kenya dataset, sourced from Kaggle, was utilized in this study. As a feature extractor, mBERT's hidden states trained the highest-performing SVM with an accuracy of 0.5461 and a macro f1 score of 0.40. Among the three models evaluated, XLM-RoBERTa achieved the highest accuracy of 0.6069 and a macro f1 score of 0.49 on a balanced dataset. In contrast, mBERT achieved the highest accuracy of 0.7820 and a macro f1 score of 0.53 on an imbalanced dataset. The comparative study establishes that using transformer-based models as end-to-end classifiers generally performs better than using them as feature extractors with traditional classifiers. This is because directly training the models allows them to learn more task-specific features. Furthermore, the varying performance across balanced and imbalanced datasets highlights the need for careful model selection based on the dataset characteristics and specific task requirements.
International Journal of Bio-Medical Informatics and e-Health, 2024
Radiation therapy is a complicated treatment technique that calls for meticulous coordination, st... more Radiation therapy is a complicated treatment technique that calls for meticulous coordination, strict adherence to safety procedures, and care that is concentrated on the patient. Managers in the healthcare industry play an essential role in supervising and improving these various facets of care delivery. This systematic analysis aims to evaluate the significant role that healthcare managers play in ensuring patient safety and satisfaction during radiation therapy for patients in Saudi Arabia who have lung cancer. The research analyzes the existing literature in order to identify the unique roles, problems, and tactics that healthcare managers in Saudi Arabia apply in order to improve patient safety and satisfaction during radiation therapy for patients with lung cancer. The findings of this research contribute to improving the quality of care provided to lung cancer patients undergoing radiation therapy in Saudi Arabia, which ultimately leads to better patient outcomes.
International Journal of Advances in Computer Science and Technology, 2024
The use of modern technologies, especially AI enabled features, has led to significant changes in... more The use of modern technologies, especially AI enabled features, has led to significant changes in the hospitality and tourism industry, both for travellers and service providers. Thanks to the rapid development of various AI features, the Internet of Things and other technologies, travellers can enjoy personalised and tailored booking and travel experiences. Online travel agencies (OTAs) are websites or mobile applications where users can book a variety of travel-related services such as accommodation, cruises, airline tickets, car hire and many other travel items. The focus of this study is on the impact of the introduction of AI technology in OTAs (online travel agencies) on travellers. It represents the realisation of the fourth phase of the research, which focuses on the analysis of travellers' habits and key demographic characteristics, as well as significant differences between genders and the travelling' frequency of the respondents. For this purpose, an originally developed questionnaire with specific demographic questions, OTA booking habits and 12 questions on different AI features in OTAs was used. One-way ANOVA (for frequency of travel) and a two-sample t-test (for gender) were used for this study. The results obtained showed significant differences in responses for some questions, both for gender and travel frequency, and are presented in detail in the Results and Discussion section.
International Journal of Emerging Trends in Engineering Research, 2024
The main benefit of teaching IoT in today's classroom is that students are learning crucial skill... more The main benefit of teaching IoT in today's classroom is that students are learning crucial skills they'll need in the futurewhether that's at work or at home. Schools can also benefit from the Internet of Things in several ways. This article presents some techniques of teaching on connected objects. Our work is focused on active pedagogy wich is widely integrated in order to involve students in the theoretical part and to create a prototype of an object having an application purpose. The integration of this teaching into a school of engineers illustrates its implementation.
International Journal of Advances in Computer Science and Technology, 2024
Cybersecurity within organizations: Who should be responsible for ensuring that the organization ... more Cybersecurity within organizations: Who should be responsible for ensuring that the organization is protected against cybercrime? The aim of this research is to identify who is accountable for safeguarding organizations from cybercrime. The study focused on internal cybersecurity, particularly the roles of managers and employees. The human factor refers to managers and employees. The methodology used to collect the data was the collection of literature from Google Scholar. The findings indicate that cybersecurity is a shared responsibility between managers and employees.
International Journal of Advances in Computer Science and Technology , 2024
In the realm of edge computing, a paradigm emphasizing
decentralized computational tasks, the int... more In the realm of edge computing, a paradigm emphasizing
decentralized computational tasks, the interplay between time
and space complexity holds immense significance. Time
complexity denotes the duration required for an algorithm's
execution, while space complexity concerns the memory or
storage demand throughout the process. The evaluation entails
a comparative analysis between a conventional non-quantized
model and its quantized counterpart, focusing on accuracy,
memory utilization, and runtime. The non-quantized model
exhibits commendable learning performance, achieving a 96%
accuracy rate during training but experiencing a marginal
decrease to 90% in testing. Conversely, the quantized model
sustains competitive accuracy, attaining 98% in both training
and testing phases. The architecture of the quantized model,
characterized by diminished numerical precision, emerges as a
pivotal factor in minimizing both memory footprint and
computational requirements. Graphical analyses unveil that
despite a slight increase in loss during validation, the
quantized model displays robust learning and generalization
capabilities from the training dataset. The comparative
analysis emphasizes the benefits of quantization, emphasizing
decreased memory utilization (3kb), faster runtime, and, in
specific cases, improved accuracy (96%). This thesis provides
valuable perspectives on the effectiveness of quantization in
optimizing Convolutional Neural Network (CNN) models for
deployment on edge devices with limited resources. The
evaluation metrics employed include memory usage reduction,
runtime speed, and accuracy enhancement 96%.
International Journal of Emerging Trends in Engineering Research, 2024
Secure Hash Algorithms (SHA) are widely used in the Internet of Things (IoT) systems for message ... more Secure Hash Algorithms (SHA) are widely used in the Internet of Things (IoT) systems for message authentication and integrity verification. However, the performance of different SHA algorithms can vary significantly in terms of Quality of Service (QoS) metrics such as area utilization, processing speed, energy efficiency, and security. In this paper, we present a comprehensive analysis of the QoS parameters of various SHA algorithms and discuss the trade-offs between performance and security when selecting SHA algorithms for resource-constrained IoT devices. The study focuses on the hardware implementation of SHA algorithms in Field-Programmable Gate Array (FPGA) devices, which are commonly used in IoT applications. The performances and resource utilization of different SHA algorithms are compared and analyzed. The comparative results show that SHA-2 provide a good balance between performance and security, but SHA-3 provide better security due to its resistance to attacks such as length extension and collision
International Journal of Advances in Computer Science and Technology, 2024
The future of work (FOW) is being influenced by emerging
technologies such as machine learning, a... more The future of work (FOW) is being influenced by emerging
technologies such as machine learning, artificial intelligence (AI),
and predictive analytics. With 89% of businesses adopting digital
strategies, experts predict that AI will enhance productivity and
proficiency over the next decade. However, concerns about the
impact of AI on employment and the workforce remain. The pace
of AI development contradicts stakeholder expectations, leading
to uncertainty about AI automation, competitiveness in local
markets, online disruptions, job and skill redesign, and high
pressure on the workforce.
AI has shown benefits in automating processes and improving
productivity, quality, and reliability. Descriptive analytics tools
like Office 365 Delve (O3D) can help reinforce working
relationships, improve work-life balance, and support
communication. However, there is a gap between organizations
and employees when it comes to adopting new technology tools.
A case study was conducted at Achievers Point University (APU)
to examine the use of O3D, its impacts, and user perceptions.
The results showed that non-users do not trust the implementation
of O3D, but users who use it effectively view output accuracy as
well as input. In terms of well-being and trust, 62% of respondents
trust O3D as a tool for improving work performance in time
management and capturing work activity data. The findings from
this case study can inform C-suite executives, decision-makers,
and business leaders about developing strategies to mitigate risks
during technology implementations
International Journal of Science and Applied Information Technology , 2024
With the rapid integration of Information and Communication Technology into various sectors globa... more With the rapid integration of Information and Communication Technology into various sectors globally, including education, there have been profound interconnections enhancing digital transformation. The growth of ICT in Nigeria has been rapid, necessitating a study of its impact on education in the country. This research explores the transformative impact of ICT in Nasarawa State with a specific focus on secondary schools in six local governments: Akwanga, Doma, Keffi, Lafia, Nasarawa Eggon, and Wamba. A quantitative descriptive research design was employed to gather data that was analyzed to reach a coherent conclusion. Questionnaires were provided to 680 students selected randomly from several secondary schools in the six local governments. Statistical analysis was conducted using one-way ANOVA and Tukey tests. The study investigates the ICT proficiency level of students, categorizing their proficiency levels and examining its effects on academic performance. The data analysis reveals that students in Lafia have the highest ICT proficiency 65%, followed closely by Keffi and Akwanga at 63% and 58% respectively. Conversely, Doma exhibits the lowest proficiency, with only 46%. The results indicate a general rate of ICT illiteracy among the students in these local governments due to a lack of ICT infrastructures and gadgets. Additionally, it reveals that ICT gadgets are primarily used for entertainment purposes rather than educational purposes by the students in these local governments due to the low incorporation of ICT in their education curriculum. The study concludes by emphasizing the critical role of ICT in education and the need for increased investment in ICT infrastructure and training to bridge proficiency gaps and promote a technologically adept student population across Nasarawa State and Nigeria as a whole.
International Journal of Advanced Trends in Computer Science and Engineering, 2024
This study examines the relationship between graduate attributes of 150 Bachelor of Science in In... more This study examines the relationship between graduate attributes of 150 Bachelor of Science in Information Technology (BSIT) students and Java programming. The study focuses on graduate-level skills like problem-solving abilities, communication, and problem analysis in relation to Java programming elements like classes, file handling, and methods. A 5-point Likert scale rating is incorporated into the survey questionnaire design in order to quantitatively evaluate the responses. The study makes use of the Jamovi application as a statistical spreadsheet. The outcome shows a good relationship between the characteristics of BSIT graduates, such as communication, problem-solving skills, and problem analysis, and Java programming elements like classes, file handling, and methods. Additionally, some BSIT students find it difficult to use complicated methods, indicating the necessity for instructional strategies, practical projects, assessments, and peer programming exercises.
International Journal of Advanced Trends in Computer Science and Engineering , 2024
The Internet of Things (IoT) has experienced rapid growth, resulting in a proliferation of interc... more The Internet of Things (IoT) has experienced rapid growth, resulting in a proliferation of interconnected devices in domains such as smart homes, cities, and healthcare applications. Ensuring secure communication within IoT networks is crucial for protecting privacy and data. The BB84 protocol, a quantum key distribution (QKD) protocol, shows promise in enhancing IoT communication security. This paper presents a comprehensive security analysis of the BB84 protocol in IoT networks, examining key aspects including entropy, execution time, quantum bit error rate (QBER), and cryptographic key generation efficiency. The analysis aims to evaluate the protocol's resilience against potential attacks and its suitability for securing IoT communications. We delve into the evaluation of entropy levels in the key generation process to ensure strong cryptographic properties. We also examine the correlation between execution time and QBER to determine the protocol's efficiency and ability to counter timing-based attacks. Additionally, we analyze the efficiency of the keys generated by the BB84 protocol, taking into consideration factors such as key size, generation rate, and computational overhead. These evaluations allow us to assess the protocol's suitability for resource-constrained IoT devices.
International Journal of Advanced Trends in Computer Science and Engineering, 2024
Online privacy perception among students on social media raises concerns about personal informati... more Online privacy perception among students on social media raises concerns about personal information protection, misuse, and potential misuse, including inadvertent disclosure leading to privacy breaches and identity theft. The study examined the influence of online privacy perceptions on social media usage among 150 Information and Communications Technology students through an online survey. The study revealed that students are highly aware and responsible about data privacy and security, demonstrating proactive behavior and trust in social media platforms' ability to effectively manage privacy risks.
International Journal of Advances in Computer Science and Technology, 2024
Strong cybersecurity solutions are becoming more and more important as Internet of Things (IoT) t... more Strong cybersecurity solutions are becoming more and more important as Internet of Things (IoT) technology integration in healthcare settings develops. This study offers a method for feature extraction, selection, and attack classification by fusing the discriminative capacity of feedforward neural networks (FNNs) with the adaptability of fuzzy logic systems. In delicate healthcare database of IoT wearable devices, to reduce false alarm and guaranteeing intrusion detection dependability are the main priorities. The suggested method uses a feature extraction, selection technique, training and testing based on FNN, which allows the model to adjust to the dynamic and varied character of medical data. During the assessment stage, a dataset including a range of healthcare IoT scenarios, including different kinds of attacks, is used to train and evaluate the model, the ToN_IoT dataset was used. Fuzzy logic improves the system's resilience in identifying pertinent features by managing uncertainties and imprecise input. Fuzzy logic is one of the best technique for handling uncertainty, its linguistic representation and rule reasoning helps in better identification and classification. The findings indicate a noteworthy decrease in the frequency of false alarms when juxtaposed with conventional intrusion detection systems. Results obtained from the model are 99.2, 98.8, 99.5, 99.1 & 0.008 for accuracy, precision, recall, F1-Score and False alarm respectively. Promising outcomes in protecting IoT healthcare environments are demonstrated by the suggested system, opening the door to better patient data privacy and system resilience against cyberattacks.
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Papers by WARSE The World Academy of Research in Science and Engineering
decentralized computational tasks, the interplay between time
and space complexity holds immense significance. Time
complexity denotes the duration required for an algorithm's
execution, while space complexity concerns the memory or
storage demand throughout the process. The evaluation entails
a comparative analysis between a conventional non-quantized
model and its quantized counterpart, focusing on accuracy,
memory utilization, and runtime. The non-quantized model
exhibits commendable learning performance, achieving a 96%
accuracy rate during training but experiencing a marginal
decrease to 90% in testing. Conversely, the quantized model
sustains competitive accuracy, attaining 98% in both training
and testing phases. The architecture of the quantized model,
characterized by diminished numerical precision, emerges as a
pivotal factor in minimizing both memory footprint and
computational requirements. Graphical analyses unveil that
despite a slight increase in loss during validation, the
quantized model displays robust learning and generalization
capabilities from the training dataset. The comparative
analysis emphasizes the benefits of quantization, emphasizing
decreased memory utilization (3kb), faster runtime, and, in
specific cases, improved accuracy (96%). This thesis provides
valuable perspectives on the effectiveness of quantization in
optimizing Convolutional Neural Network (CNN) models for
deployment on edge devices with limited resources. The
evaluation metrics employed include memory usage reduction,
runtime speed, and accuracy enhancement 96%.
technologies such as machine learning, artificial intelligence (AI),
and predictive analytics. With 89% of businesses adopting digital
strategies, experts predict that AI will enhance productivity and
proficiency over the next decade. However, concerns about the
impact of AI on employment and the workforce remain. The pace
of AI development contradicts stakeholder expectations, leading
to uncertainty about AI automation, competitiveness in local
markets, online disruptions, job and skill redesign, and high
pressure on the workforce.
AI has shown benefits in automating processes and improving
productivity, quality, and reliability. Descriptive analytics tools
like Office 365 Delve (O3D) can help reinforce working
relationships, improve work-life balance, and support
communication. However, there is a gap between organizations
and employees when it comes to adopting new technology tools.
A case study was conducted at Achievers Point University (APU)
to examine the use of O3D, its impacts, and user perceptions.
The results showed that non-users do not trust the implementation
of O3D, but users who use it effectively view output accuracy as
well as input. In terms of well-being and trust, 62% of respondents
trust O3D as a tool for improving work performance in time
management and capturing work activity data. The findings from
this case study can inform C-suite executives, decision-makers,
and business leaders about developing strategies to mitigate risks
during technology implementations
decentralized computational tasks, the interplay between time
and space complexity holds immense significance. Time
complexity denotes the duration required for an algorithm's
execution, while space complexity concerns the memory or
storage demand throughout the process. The evaluation entails
a comparative analysis between a conventional non-quantized
model and its quantized counterpart, focusing on accuracy,
memory utilization, and runtime. The non-quantized model
exhibits commendable learning performance, achieving a 96%
accuracy rate during training but experiencing a marginal
decrease to 90% in testing. Conversely, the quantized model
sustains competitive accuracy, attaining 98% in both training
and testing phases. The architecture of the quantized model,
characterized by diminished numerical precision, emerges as a
pivotal factor in minimizing both memory footprint and
computational requirements. Graphical analyses unveil that
despite a slight increase in loss during validation, the
quantized model displays robust learning and generalization
capabilities from the training dataset. The comparative
analysis emphasizes the benefits of quantization, emphasizing
decreased memory utilization (3kb), faster runtime, and, in
specific cases, improved accuracy (96%). This thesis provides
valuable perspectives on the effectiveness of quantization in
optimizing Convolutional Neural Network (CNN) models for
deployment on edge devices with limited resources. The
evaluation metrics employed include memory usage reduction,
runtime speed, and accuracy enhancement 96%.
technologies such as machine learning, artificial intelligence (AI),
and predictive analytics. With 89% of businesses adopting digital
strategies, experts predict that AI will enhance productivity and
proficiency over the next decade. However, concerns about the
impact of AI on employment and the workforce remain. The pace
of AI development contradicts stakeholder expectations, leading
to uncertainty about AI automation, competitiveness in local
markets, online disruptions, job and skill redesign, and high
pressure on the workforce.
AI has shown benefits in automating processes and improving
productivity, quality, and reliability. Descriptive analytics tools
like Office 365 Delve (O3D) can help reinforce working
relationships, improve work-life balance, and support
communication. However, there is a gap between organizations
and employees when it comes to adopting new technology tools.
A case study was conducted at Achievers Point University (APU)
to examine the use of O3D, its impacts, and user perceptions.
The results showed that non-users do not trust the implementation
of O3D, but users who use it effectively view output accuracy as
well as input. In terms of well-being and trust, 62% of respondents
trust O3D as a tool for improving work performance in time
management and capturing work activity data. The findings from
this case study can inform C-suite executives, decision-makers,
and business leaders about developing strategies to mitigate risks
during technology implementations
critical argument of how to develop patient safety culture in
health care settings in Riyadh, Saudi Arabia. Having
understood the pivotal role played by culture in the
improvement of patient outcomes, very systematically lays
down a literature review looking for the prevalent gaps and
inefficiencies occurring in the present practices. That is to
mean, the paper duly critically appraises different
approaches and interventions that have greatly contributed
to making a huge difference in the organizational climate,
regarding the culture of safety through a systematic and
rigorous manner. These findings, therefore, underline the
need for full-fledged deployment of safety protocols,
fostering a transparent atmosphere through which healthcare
providers should learn from their mistakes, and demand
quality enhancement programs. Presents a summary of such
findings, and their general meanings with regards to health
policy, leadership, and practice that suggest a way for
healthcare institutions in Riyadh, to draw a more resilient
and patient-centered safety culture. This research
contributes to the academic void of discourse of patient
safety by offering practical insights to the health leaders and
policy-makers in Riyadh that, when implemented, will
optimize the quality of care in health care and experience
that patients have in it.
providing information on good nutritional intake to children.
By using this application, it is hoped that the community can
monitor and optimize children's growth during the first 1000
days, with a focus on stunting prevention. This Sahabat
Terbaik Anak app (information about the importance of
good nutrition and helps in monitoring children's growth)
uses a waterfall model. The system includes an Android
mobile app, which allows users to search for articles about
children's growth and development according to the month
and efficiency while traveling. The four phases of this
system are data collection, design, implementation, and
testing. The system provides an easy-to-use interface to
provide nutrition monitoring, physical growth, and
education for parents on the importance of balanced
nutritional intake. Children's friends can provide solutions
to reduce stunting in children.
chains has increased due to the growth of e-commerce. Last-
mile delivery (LMD) is responsible for a large amount of the
environmental impact and overall logistical costs. In order to
balance economic effectiveness and environmental
sustainability in last-mile delivery operations, this article
examines optimization options. The study used a descriptive
design; collected and analyzed quantitative data. Key players
in last-mile delivery, including logistics firms, online
merchants, and delivery service providers, who were given
surveys via Google Forms to collect primary data. The topics
covered included cost structures, environmental issues,
current optimization techniques, and practices. Data on
current last-mile delivery strategies, optimization techniques,
and environmental sustainability projects were gathered
through a literature review. With a case study in Lagos,
Nigeria, the study focused on metropolitan areas.
Participants with substantial last-mile delivery and logistics
experience were chosen using a purposive sample technique.
Twenty logistics and supply chain managers, ten couriers
and delivery drivers, ten owners of e-commerce businesses,
thirty customers, five transportation and logistics service
providers, five sustainability specialists, eight city officials
and urban planners, and seven technology providers were
included in the sample. The analysis with statistical methods,
such as table and charts, was used to analyzed the
participants opinions. The paper contributes to the growing
body of literature that links supply chain efficiency with
sustainability goals.