Unsheltered: Navigating California’s Homelessness Crisis

This paper presents a comprehensive exploration of the complex phenomenon of homelessness in California,with a specific focus on the state’s three largest cities-Los Angeles,San Francisco,and San Diego.Against the backdrop of a high cost of living and a housing market strained by insufficient affordable options,the multifaceted nature of social diversity further complicates the landscape,leading to a widespread presence of homelessness that spans both major urban centers and rural regions.Through an in-depth examination of the distinct challenges confronting each city,ranging from housing shortages to intricate social dynamics,this study seeks to illuminate the underlying factors driving homelessness and identify potential avenues for intervention.Moreover,the paper delves into the unique vulnerabilities experienced by certain demographics within the homeless population,including veterans,families with children,and LGBTQ+individuals,highlighting the critical need for targeted solutions tailored to their specific needs.By synthesizing existing research and incorporating firsthand accounts,this research endeavor aims to contribute to a deeper understanding of homelessness in California and inform the development of comprehensive strategies aimed at fostering inclusive,sustainable communities statewide.

Health Behaviors and Outcomes of Mobile Health Apps and Patient Engagement in the USA

Mobile health applications, or mHealth apps, have gained popularity due to their practical functions and strengthening the connection between patients and healthcare professionals. These apps are designed for managing health and well-being on portable devices, allowing individuals to self-manage their health or healthcare practitioners to enhance patient care. Key features include personalized recommendations, data synchronization with other health devices, and connectivity with healthcare professionals. The research describes how mobile health applications support healthy behaviors, facilitate communication between patients and physicians, and empower individuals in the United States to take charge of their health. This study also examines how adults in the US use mobile health applications, or mHealth apps, on their tablets or smartphones for health-seeking purposes. The information was taken from Cycle 4 of the Health Information National Trends Survey (HINTS 4). The challenges regarding these mobile health apps have also been evaluated with possible remedies. Around 100 university students participated in a cross-sectional study by answering questions on their eating habits, physical activity, lifestyle choices related to health, and use of mobile health apps. The data was then analyzed and concluded as a result. Mobile health applications have brought about a significant shift in the way patients connect with their healthcare providers by providing them with convenient access to health services and information. By keeping track of health markers like diet, exercise, and medication compliance, patients may use these tools to help better manage their chronic conditions. Mobile health applications can improve patient outcomes and save healthcare costs by empowering patients to take charge of their health. Through the facilitation of communication between patients and healthcare professionals, mobile health apps also offer virtual consultations and remote monitoring.

Exploring the Latest Trends in AI Technologies: A Study on Current State, Application and Individual Impacts

Artificial Intelligence (AI) offers immediate insights to penetrate the overwhelming volume of everyday security warnings. The current body of research mostly examines the use of AI in the field of cyber security, but it does not adequately address the visual inspection of AI applications. The advent of AI has led to noticeable structural changes in the field of cyber security. This study facilitates the advancement of theory about artificial intelligence (AI) across several fields. It assists researchers in determining research paths and serves as a resource for corporations and governments to strategize the use of AI in areas such as cyber security, education, healthcare, and work-life balance. Numerous nations, organizations, and writers are intricately linked via cooperation and citation networks. Artificial intelligence is an academic discipline focused on the research and advancement of computer systems, robots, and other creations that possess human-like intelligence, which is defined by cognitive powers, learning capabilities, and adaptability. This research aimed to evaluate the present trajectory and influence of Artificial Intelligence (AI) on education, healthcare, cybersecurity, and work-life balance. Based on an initial examination, this research focused on evaluating the use and impact of AI in many domains, using a specific narrative and framework. The findings of this study will enable researchers to comprehend the prevailing pattern and the influence of people on the integration of AI into daily life.

Neural Network-Powered License Plate Recognition System Design

The development of scientific inquiry and research has yielded numerous benefits in the realm of intelligent traffic control systems, particularly in the realm of automatic license plate recognition for vehicles. The design of license plate recognition algorithms has undergone digitalization through the utilization of neural networks. In contemporary times, there is a growing demand for vehicle surveillance due to the need for efficient vehicle processing and traffic management. The design, development, and implementation of a license plate recognition system hold significant social, economic, and academic importance. The study aims to present contemporary methodologies and empirical findings pertaining to automated license plate recognition. The primary focus of the automatic license plate recognition algorithm was on image extraction, character segmentation, and recognition. The task of character segmentation has been identified as the most challenging function based on my observations. The license plate recognition project that we designed demonstrated the effectiveness of this method across various observed conditions. Particularly in low-light environments, such as during periods of limited illumination or inclement weather characterized by precipitation. The method has been subjected to testing using a sample size of fifty images, resulting in a 100% accuracy rate. The findings of this study demonstrate the project’s ability to effectively determine the optimal outcomes of simulations.

Ensuring Security and Privacy in the Internet of Things: Challenges and Solutions

The Internet of Things (IoT) represents a revolutionary paradigm, enabling a vast array of devices to be ubiquitously interconnected via the Internet, thereby facilitating remote control and management of these devices. This pervasive integration into daily life brings significant convenience but also raises substantial concerns regarding the security of personal data collected and stored online. As the number of connected devices grows, the urgency to address privacy and security issues becomes paramount. IoT systems are particularly susceptible to threats that could compromise consumer privacy and security, affecting their practical deployment. Recent research efforts have focused on enhancing the security of IoT devices, including the exploration of blockchain technologies to mitigate these concerns. This paper aims to elucidate the security and privacy challenges inherent in IoT systems by examining vulnerabilities at each layer of the IoT protocol stack. It identifies key security requirements and reviews existing solutions designed to protect IoT systems from a layered perspective, thereby providing a comprehensive overview of the current landscape of IoT security and highlighting the critical need for robust security measures as the adoption of IoT continues to expand.

Optimizing Resource Management for IoT Devices in Constrained Environments

Embedded computing device implementation on the Internet of Things (IoT) requires careful assessment of their intrinsic resource limitations. These constraints are not limited to memory and processing capabilities but extend to the network interfaces, particularly due to the low-power radio standards that these devices typically employ. The IPv6 protocol is shown to be a strong option for guaranteeing interoperability in the IoT, mostly because of its large address space, the range of current IP-based protocols, and its intrinsic versatility. Considering these benefits, we investigate if current IP-based network management protocols can be implemented on devices with limited resources. We investigate the resource needs in particular for implementing Network Configuration Protocol (NETCONF) and Simple Network Management Protocol (SNMP) on an 8-bit AVR-based device. Our investigation reveals the specific memory and processing demands of these protocols, providing valuable insights into their practicality and efficiency in constrained IoT environments. This study underscores the potential and challenges of leveraging IPv6-based network management protocols to enhance the functionality and interoperability of IoT devices while operating within stringent resource limitations.

Applying the Technology Acceptance Model (TAM) in Information Technology System to Evaluate the Adoption of Decision Support System

With the beginning of the information systems’ spreading, people started thinking about using them for making business decisions. Computer technology solutions, such as the Decision Support System, make the decision-making process less complex and simpler for problem-solving. In order to make a high-quality business decision, managers need to have a great deal of appropriate information. Nonetheless, this complicates the process of making appropriate decisions. In a situation like that, the possibility of using DSS is quite logical. The aim of this paper is to find out the intended use of DSS for medium and large business organizations in USA by applying the Technology Acceptance Model (TAM). Different models were developed in order to understand and predict the use of information systems, but the information systems community mostly used TAM to ensure this issue. The purpose of the research model is to determine the elements of analysis that contribute to these results. The sample for the research consisted of the target group that was supposed to have completed an online questionnaire about the manager’s use of DSS in medium and large American companies. The information obtained from the questionnaires was analyzed through the SPSS statistical software. The research has indicated that, this is primarily used due to a significant level of Perceived usefulness and For the Perceived ease of use.

Design and Implementation of Enterprise Office Automation System Based on Web Service Framework & Data Mining Techniques

The advancement of science and technology has introduced the concept of big data, which has significantly transformed the business management environment of enterprises. Currently, most administrative tasks in companies heavily rely on human resources, with skilled management staff using their expertise to oversee business operations. However, this approach is susceptible to human subjective biases. The method assists managers in formulating efficient strategies for implementing management measures and enhancing the effectiveness of production, sales, financial, and people organization structure management. This ultimately leads to a more evidence-based approach to corporate management. This technique expands the utilization of Web services from a strategy focused on integrating services to a comprehensive framework for Service-Oriented Computing (SOC). The primary focus is implementing WS-session to manage sessions in general Web services applications, defining a bidirectional entire duplex interface for communication in Web services, and developing the Web Services Initiation Protocol, presenting WIP, a thorough multimedia and voice communication framework constructed using Web services and Service-Oriented Architecture (SOA). The office automation management system, created utilizing ASP.net and SQL Server technology, encompasses the evaluation of viability, analysis of needs, and system design. Office automation refers to using equipment with computing capabilities to carry out various office tasks and utilize associated tools and applications. Office automation uses computer-based systems to collect, organize, and modify visual and auditory information to enhance business energy efficiency and time management. Office automation refers to auto-mating essential tasks employees perform, including identification, automatic appointment reminders, and automatic power management for personal computers. The employee image is obtained through the utilization of the Java media framework. Attendance data for all employees are collected and methodically examined. The database enables the retrieval of these records monthly or weekly. An office automation system offers organizations enhanced features for managing office information, significantly improving office efficiency and quality. Moreover, it improves office administration and decision-making procedures by automating and strengthening the scientific elements of office functions. The ongoing progress of organizational information technology has led to a strong focus on sharing information resources in scientific research initiatives. Conventional firms exhibit intricate company processes, inadequate managerial efficacy, and unnecessarily elevated operational expenses, resulting in diminished competitiveness. Thus, using an ERP management system is the optimal decision for organizations to restore their crucial competitive advantage. This technology enhances their operational methods, streamlines their operations, and enhances transparency in their operational approaches. The system comprises six modules: buy plan, purchase order, purchase contract, purchase document inquiry, purchase to order, and purchase return. These modules effectively meet the operational needs of enterprises.

Integrating Blockchain Innovation: A Sustainable Adoption Model for Business

Blockchain technology holds significant promise for driving innovations across diverse industries, businesses, and applications. Recognized as a crucial source of competitive advantage in a fast-evolving environment, blockchain is anticipated to contribute substantially to sustainable economic and social development. Despite these high expectations, many blockchain projects currently face high failure rates, leading to negative impacts on various aspects of economic and social sustainability, including corporate governance, risk management, financial management, human resources, culture management, and competitiveness. This paper evaluates adoption models, identifying both risk and success factors. It introduces an integrated adoption model designed to operationalize, measure, and manage blockchain-driven business innovation sustainably. An empirical study involving 20 industry sectors and 125 business leaders was conducted to assess the model’s applicability. The findings indicate that the adoption model has the potential to support the sustainable implementation of blockchain technology for business innovations across various industries and applications. Future research and industry activities should continue validating this model through further case studies.

The Impact of Leadership on the Growth of ICT Companies

Nowadays,one of the major purposes of any company is to survive in the competitive business markets.This purpose would be achievable through improving and developing growth in most cases.Prior studies suggest that leadership is a vitally important factor in achieving growth in any company.Some researchers studied leadership topics as one of the significant motivations for developing and improving the growth of a company and agreed that understanding the role of leadership and its effect on the growth of the company is influential.In all countries,Information Communication Technology(ICT)companies are recognized as significant growth drivers by leaving considerable impacts on that.According to the literature,growth is a determining factor for the productivity of any company.Based on the literature of the ICTs,weak and insufficient leadership skills are considered as the main factors that cause failure in achieving the planned growth and development of ICT.Consequently,the goal of this study is to clarify how leadership affects the development of ICT enterprises.