The phenomenon of cloud computing and related innovations such as Big Data have given rise to many fundamental changes that are evident in information and data. Managing, measuring and developing business value from the plethora of this new data has significant impact on many corporate agendas, particularly in relation to the successful implementation of business intelligence and analytics (BI&A). However, although the influence of Big Data has fundamentally changed the IT application landscape, the metrics for measuring success and in particular, the quality of information, have not evolved. The measurement of information quality and the antecedent factors that influence information has also been identified as an area that has suffered from a lack of research in recent decades. Given the rapid increase in data volume and the growth and ubiquitous use of BI&A systems in organisations, there is an urgent need for accurate metrics to identify information quality.

With the rapid development of Artificial Intelligence (AI) technology, significant breakthroughs have been made in its application in many fields. Especially, in the field of enterprise human resource management and employee performance evaluation, AI has demonstrated its powerful ability to optimise and improve performance. This study explores the application of AI in enterprise human resource management and how to use AI to evaluate employee performance. The research includes analysing and comparing existing AI-driven human resource management models, evaluating how AI can help improve employee performance and leadership styles, and designing and developing human resource management computer systems for enterprise employees. Through empirical research and case analysis, this study proposes a new AI-optimised employee performance evaluation model and explores its application and effect in practice. In general, the application of AI can improve the efficiency and accuracy of enterprise human resource management, and provide new possibilities for employee performance evaluation. At present, artificial intelligence technology has been widely used in various fields of daily life, especially in corporate human resource management, providing better support for the development of enterprises.

In India, 70% of the Indian population is dependent on agriculture, yet agriculture generates only 13% of the country's gross domestic product. Several factors contribute to high levels of stress among farmers in India, such as increased input costs, draughts, and reduced revenues. The problem lies in the absence of an integrated farm advisory system. A farmer needs help to bridge this information gap, and they need it early in the crop's lifecycle to prevent it from being destroyed by pests or diseases. This research involves developing deep learning algorithms such as <i>ResNet18</i> and <i>DenseNet121</i> to help farmers diagnose crop diseases earlier and take corrective actions. By using deep learning techniques to detect these crop diseases with images farmers can scan or click with their smartphones, we can fill in the knowledge gap. To facilitate the use of the models by farmers, they are deployed in Android-based smartphones.

Dynamic nature of the FMCG sector perpetually provides a tricky challenge for organisational leaders to nurture their employees. High demand for products, less shelf life and tough competitors always challenge the leaders to uphold their products in the market. Due to technology and e-commerce, many new competitors have joined the market, vying with the industry's veterans. Due to their unique business models that match client needs, these firms are expected to boost FMCG industry income in the future. Managers' leadership styles depend primarily on emotional intelligence. This quantitative study examines how emotional intelligence influences West Bengal FMCG senior managers' leadership styles. 500 FMCG managers were selected. PLS-SEM is used to study. Emotionally competent leaders choose transactional and transformational leadership styles depending on the occasion. Managers' transactional leadership style is strongly influenced by their sympathetic awareness, as shown by a path coefficient of 0.755. Transformational leadership style has a path coefficient of 0.693, indicating that managers' empathy affects their organisational management. Thus, sympathetic awareness and emotion regulation predict good management leadership.

The major technological developments have changed the traditional way of doing business. These developments have facilitated whistle-blowing. Access to data is easier and faster and communicating with the public can be done in seconds. Another development is the artificial intelligence (AI) which enters the business workplace in different forms challenging the traditional working relations. The combination of these concepts gives the idea of artificial whistle-blowing or robot whistle-blowing. The concept is that a machine should conceive and report relevant wrongdoing avoiding the traditional model of whistle-blowing where the employee is the person who should report. This concept, yet unexplored, presents interesting positive and negative aspects. The purpose of this contribution is to present the idea of artificial whistle-blowing and its advantages and disadvantages for the business sector. As a conclusion, this paper suggests that the concept of artificial whistle-blowing needs still to be researched and an optimal solution, for the time being, is to permit artificial whistle-blowing as a helping tool for the employees to detect wrongdoings but report them themselves.

The field of business intelligence (BI), despite rapid technology advances, continues to feature inadequate levels of adoption. The attention of researchers is shifting towards hu-man factors of BI adoption. The wide set of human factors influencing BI adoption con-tains elements of what we call BI culture – an overarching concept covering key managerial issues that come up in BI implementation. Research sources provide different sets of features pertaining to BI culture or related concepts – decision-making culture, analytical culture and others. The goal of this paper is to perform the review of research and practical sources to examine driving forces of BI – data-driven approaches, BI agility, maturity and acceptance – to point out culture-related issues that support BI adoption and to suggest an emerging set of factors influencing BI culture.

Knowledge management research applied to the development of real-time research capability, or capability to solve societal problems in hours and days instead of years and decades, is perhaps increasingly important, given persistent global problems such as the Zika virus and rapidly developing antibiotic resistance. Drawing on swarm intelligence theory, this paper presents an approach to real-time research problem-solving in the form of a framework for understanding the complexity of real-time research and the challenges associated with maximizing collaboration. The objective of this research is to make explicit certain theoretical, methodological, and practical implications deriving from new literature on emerging technologies and new forms of problem solving and to offer a model of real-time problem solving based on a synthesis of the literature. Drawing from ant colony, bee colony, and particle swarm optimization, as well as other population-based metaheuristics, swarm intelligence principles are derived in support of improved effectiveness and efficiency for multidisciplinary human swarm problem-solving. This synthesis seeks to offer useful insights into the research process, by offering a perspective of what maximized collaboration, as a system, implies for real-time problem solving.

Aim/Purpose: The purpose of this paper is to identify Critical Success Factors (CSFs) for Business Intelligence (BI) implementation projects by studying the existing BI project implementation methodologies and to compare these methodologies based on the identified CSFs. Background: The implementation of BI project has become one of the most important technological and organizational innovations in modern organizations. The BI project implementation methodology provides a framework for demonstrating knowledge, ideas and structural techniques. It is defined as a set of instructions and rules for implementing BI projects. Identifying CSFs of BI implementation project can help the project team to concentrate on solving prior issues and needed resources. Methodology: Firstly, the literature review was conducted to find the existing BI project implementation methodologies. Secondly, the content of the 13 BI project implementation methodologies was analyzed by using thematic analysis method. Thirdly, for examining the validation of the 20 identified CSFs, two questionnaires were distributed among BI experts. The gathered data of the first questionnaire was analyzed by content validity ratio (CVR) and 11 of 20 CSFs were accepted as a result. The gathered data of the second questionnaire was analyzed by fuzzy Delphi method and the results were the same as CVR. Finally, 13 raised BI project implementation methodologies were compared based on the 11 validated CSFs. Contribution: This paper contributes to the current theory and practice by identifying a complete list of CSFs for BI projects implementation; comparison of existing BI project implementation methodologies; determining the completeness degree of existing BI project implementation methodologies and introducing more complete ones; and finding the new CSF “Expert assessment of business readiness for successful implementation of BI project” that was not expressed in previous studies. Findings: The CSFs that should be considered in a BI project implementation include: “Obvious BI strategy and vision”, “Business requirements definition”, “Business readiness assessment”, “BI performance assessment”, “Establishing BI alignment with business goals”, “Management support”, “IT support for BI”, “Creating data resources and source data quality”, “Installation and integration BI programs”, “BI system testing”, and “BI system support and maintenance”. Also, all the 13 BI project implementation methodologies can be divided into four groups based on their completeness degree. Recommendations for Practitioners: The results can be used to plan BI project implementation and help improve the way of BI project implementation in the organizations. It can be used to reduce the failure rate of BI implementation projects. Furthermore, the 11 identified CSFs can give a better understanding of the BI project implementation methodologies. Recommendation for Researchers: The results of this research helped researchers and practitioners in the field of business intelligence to better understand the methodology and approaches available for the implementation and deployment of BI systems and thus use them. Some methodologies are more complete than other studied methodologies. Therefore, organizations that intend to implement BI in their organization can select these methodologies according to their goals. Thus, Findings of the study can lead to reduce the failure rate of implementation projects. Future Research: Future researchers may add other BI project implementation methodologies and repeat this research. Also, they can divide CSFs into three categories including required before BI project implementation, required during BI project implementation and required after BI project implementation. Moreover, researchers can rank the BI project implementation CSFs. As well, Critical Failure Factors (CFFs) need to be explored by studying the failed implementations of BI projects. The identified CSFs probably affect each other. So, studying the relationship between them can be a topic for future research.

Aim/Purpose: The aim of this study is to identify Critical Success Factors (CSF) of Business Intelligence (BI) and provide a framework to classify CSF into layers or perspectives using an enterprise architecture approach, then rank CSF within each perspective and evaluate the importance of each perspective at different BI maturity levels as well. Background: Although the implementation of the BI project has a significant impact on creating analytical and competitive capabilities, the lack of evaluation of CSF holistically is still a challenge. Moreover, the BI maturity level of the organization has not been considered in the BI implementation project. Identifying BI critical success factors and their importance can help the project team to move to a higher maturity level in the organization. Methodology: First, a list of distinct CSF is identified through a literature review. Second, a framework is provided for categorizing these CSF using enterprise architecture. Interviewing is the research method used to evaluate the importance of CSF and framework layers with two questionnaires among experts. The first questionnaire was done by Analytical Hierarchy Process (AHP), a quantitative method of decision-making to calculate the weight of the CSF according to the importance of CSF in each of the framework layers. The second one was conducted to evaluate framework layers at different BI maturity levels using a Likert scale. Contribution: This paper contributes to the implementation of BI projects by identifying a comprehensive list of CSF in the form of a holistic multi-layered framework and ranking the importance of CSF and layers at BI maturity levels. Findings: The most important CSF in BI implementation projects include senior management support, process identification, data quality, analytics quality, hardware quality, security standards, scope management, documentation, project team skills, and customer needs transformation, which received the highest scores in framework layers. In addition, it was observed that as the organization moves to higher levels of maturity, the average importance of strategic business and security perspectives or layers increases. But the average importance of data, applications, infrastructure, and network, the project management layers in the proposed framework is the same regardless of the level of business intelligence maturity. Recommendations for Practitioners: The results of this paper can be used by academicians and practitioners to improve BI project implementation through understanding a comprehensive list of CSF and their importance. This awareness causes us to focus on the most important CSF and have better planning to reach higher levels of maturity according to the maturity level of the organization. Future Research: For future research, the interaction of critical success factors of business intelligence and framework layers can be examined with different methods.

Aim/Purpose: The main goal of this systematic literature review was to look for studies that provide information relevant to business intelligence’s (BI) framework development and implementation in the tourism sector. This paper tries to classify the tourism sectors where BI is implemented, group various BI functionalities, and identify common problems encountered by previous research. Background: There has been an increased need for BI implementation to support decision-making in the tourism sector. Tourism stakeholders such as management of destination, accommodation, transportation, and public administration need a guideline to understand functional requirements before implementation. This paper addresses the problem by comprehensively reviewing the functionalities and issues that need to be considered based on previous business intelligence framework development and implementation in tourism sectors. Methodology: We have conducted a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Guidelines for Meta-Analysis (PRISMA) method. The search is conducted using online academic database platforms, resulting in 543 initial articles published from 2002 to 2022. Contribution: The paper could be of interest to relevant stakeholders in the tourism industry because it provides an overview of the capabilities and limitations of business intelligence for tourism. To our knowledge, this is the first study to identify and classify the BI functionalities needed for tourism sectors and implementation issues related to organizations, people, and technologies that need to be considered. Findings: BI functionalities identified in this study include basic functions such as data analysis, reports, dashboards, data visualization, performance metrics, and key performance indicator, and advanced functions such as predictive analytics, trend indicators, strategic planning tools, profitability analysis, benchmarking, budgeting, and forecasting. When implementing BI, the issues that need to be considered include organizational, people and process, and technological issues. Recommendations for Practitioners: As data is a major issue in BI implementation, tourism stakeholders, especially in developing countries, may need to build a tourism data center or centralized coordination regulated by the government. They can implement basic functions first before implementing more advanced features later. Recommendation for Researchers: We recommend further studying the BI implementation barriers by employing a perspective of an adoption framework such as the technology, organization, and environment (TOE) framework. Impact on Society: This research has a potential impact on improving the tourism industry’s performance by providing insight to stakeholders about what is needed to help them make more accurate decisions using business intelligence. Future Research: Future research may involve collaboration between practitioners and academics in developing various BI architectures specific to each tourism industry, such as destination management, hospitality, or transportation.

Aim/Purpose: The understanding of disease spread dynamics in the context of air travel is crucial for effective disease detection and epidemic intelligence. The Susceptible-Exposed-Infectious-Recovered-Hospitalized-Critical-Deaths (SEIR-HCD) model proposed in this research work is identified as a valuable tool for capturing the complex dynamics of disease transmission, healthcare demands, and mortality rates during epidemics. Background: The spread of viral diseases is a major problem for public health services all over the world. Understanding how diseases spread is important in order to take the right steps to stop them. In epidemiology, the SIS, SIR, and SEIR models have been used to mimic and study how diseases spread in groups of people. Methodology: This research focuses on the integration of air traffic network data into the SEIR-HCD model to enhance the understanding of disease spread in air travel settings. By incorporating air traffic data, the model considers the role of travel patterns and connectivity in disease dissemination, enabling the identification of high-risk routes, airports, and regions. Contribution: This research contributes to the field of epidemiology by enhancing our understanding of disease spread dynamics through the application of the SIS, SIR, and SEIR-HCD models. The findings provide insights into the factors influencing disease transmission, allowing for the development of effective strategies for disease control and prevention. Findings: The interplay between local outbreaks and global disease dissemination through air travel is empirically explored. The model can be further used for the evaluation of the effectiveness of surveillance and early detection measures at airports and transportation hubs. The proposed research contributes to proactive and evidence-based strategies for disease prevention and control, offering insights into the impact of air travel on disease transmission and supporting public health interventions in air traffic networks. Recommendations for Practitioners: Government intervention can be studied during difficult times which plays as a moderating variable that can enhance or hinder the efficacy of epidemic intelligence efforts within air traffic networks. Expert collaboration from various fields, including epidemiology, aviation, data science, and public health with an interdisciplinary approach can provide a more comprehensive understanding of the disease spread dynamics in air traffic networks. Recommendation for Researchers: Researchers can collaborate with international health organizations and authorities to share their research findings and contribute to a global understanding of disease spread in air traffic networks. Impact on Society: This research has significant implications for society. By providing a deeper understanding of disease spread dynamics, it enables policymakers, public health officials, and practitioners to make informed decisions to mitigate disease outbreaks. The recommendations derived from this research can aid in the development of effective strategies to control and prevent the spread of infectious diseases, ultimately leading to improved public health outcomes and reduced societal disruptions. Future Research: Practitioners of the research can contribute more effectively to disease outbreaks within the context of air traffic networks, ultimately helping to protect public health and global travel. By considering air traffic patterns, the SEIR-HCD model contributes to more accurate modeling and prediction of disease outbreaks, aiding in the development of proactive and evidence-based strategies to manage and mitigate the impact of infectious diseases in the context of air travel.

Creative computing is one of the rapidly growing educational trends around the world. Previous studies have shown that creative computing can empower disadvantaged children and youth. At-risk youth tend to hold a negative view of self and perceive their abilities as inferior compared to “normative” pupils. The Implicit Theories of Intelligence approach (ITI; Dweck, 1999, 2008) suggests a way of changing beliefs regarding one’s abilities. This paper reports findings from an experiment that explores the impact of a short intervention among at-risk youth and “normative” high-school students on (1) changing ITI from being perceived as fixed (entity view of intelligence) to more flexible (incremental view of intelligence) and (2) the quality of digital self-representations programmed though a creative computing app. The participants were 117 Israeli youth aged 14-17, half of whom were at-risk youth. The participants were randomly assigned to the experimental and control conditions. The experimental group watched a video of a lecture regarding brain plasticity that emphasized flexibility and the potential of human intelligence to be cultivated. The control group watched a neutral lecture about brain-functioning and creativity. Following the intervention, all of the participants watched screencasts of basic training for the Scratch programming app, designed artifacts that digitally represented themselves five years later and reported their ITI. The results showed more incremental ITI in the experimental group compared to the control group and among normative students compared to at-risk youth. In contrast to the research hypothesis, the Scratch projects of the at-risk youth, especially in the experimental condition, were rated by neutral judges as being more creative, more aesthetically designed, and more clearly conveying their message. The results suggest that creative computing combined with the ITI intervention is a way of developing creativity, especially among at-risk youth. Increasing the number of youths who hold incremental views of intelligence and developing computational thinking may contribute to their empowerment and well-being, improve learning and promote creativity.

The global Business Intelligence (BI) market grew by 10% in 2013 according to the Gartner Report. Today organizations require better use of data and analytics to support their business decisions. Internet power and business trend changes have provided a broad term for data analytics – Big Data. To be able to handle it and leverage a value of having access to Big Data, organizations have no other choice than to get proper systems implemented and working. However traditional methods are not efficient for changing business needs. The long time between project start and go-live causes a gap between initial solution blueprint and actual user requirements in the end of the project. This article presents the latest market trends in BI systems implementation by comparing Agile with traditional methods. It presents a case study provided in a large telecommunications company (20K employees) and the results of a pilot research provided in the three large companies: telecommunications, digital, and insurance. Both studies prove that Agile methods might be more effective in BI projects from an end-user perspective and give first results and added value in a much shorter time compared to a traditional approach.

Aim/Purpose: The present study aims to frame the relationship between job and personal resources (namely, organizational identification and emotional intelligence), burnout, and musculoskeletal disorders (i.e., back pain, upper limb pain, lower limb discomfort), into the theoretical framework provided by the JD-R health model. Background: Empirical research indicates a connection between burnout and the onset of musculoskeletal problems, one of the most important occupational health issues affecting all jobs and organizations. In light of the JD-R health model, we investigated the association between personal and job resources with burnout and musculoskeletal disorders. Methodology: An anonymous online questionnaire was answered by 320 workers (82.4% female, Mage = 42.18; SDage = 12.24) investigating their perceived level of burnout, the presence of musculoskeletal pain (back, neck, and shoulder), and their level of organizational identification and emotional intelligence. Descriptive analysis, correlation, and moderated mediation model were performed using SPSS. Contribution: We confirmed the role of personal and organizational resources in the salutogenic process considered by the JD-R health model. Emotional intelligence, decreasing the perceived level of burnout, limited the development of musculoskeletal disorders. Moreover, when organizational identification presented low and medium levels, the association between emotional intelligence and burnout strengthened. Findings: Our results showed a negative, indirect effect of emotional intelligence on musculoskeletal disorders via burnout. Moreover, we found a moderation of organizational organization, indicating that at low and medium levels of identification, the association between emotional intelligence and burnout is stronger. Recommendation for Researchers: In addition to work factors involved in the link between burnout and musculoskeletal disorders, it is also important to consider personal and emotional factors, which can decrease the occurrence of adverse consequences. Future Research: Future research developments could contribute to a deeper understanding of the mechanisms linking emotional intelligence, burnout, and musculoskeletal problems, as well as consider objective indicators of burnout levels or consider using ecological data collection methodologies (e.g., ecological momentary assessment), to identify patterns and associations between burnout and musculoskeletal disorders.

Aim/Purpose: This paper examines the transformative impact of Artificial Intelligence (AI) on professional skills in organizations and explores strategies to address the resulting challenges. Background: The rapid integration of AI across various sectors is automating tasks and reducing cognitive workload, leading to increased productivity but also raising concerns about job displacement. Successfully adapting to this transformation requires organizations to implement new working models and develop strategies for upskilling and reskilling their workforce. Methodology: This review analyzes recent research and practice on AI's impact on human skills in organizations. We identify key trends in how AI is reshaping professional competencies and highlight the crucial role of transversal skills in this evolving landscape. The paper also discusses effective strategies to support organizations and guide workers through upskilling and reskilling processes. Contribution: The paper contributes to the existing body of knowledge by examining recent trends in AI's impact on professional skills and workplaces. It emphasizes the importance of transversal skills and identifies strategies to support organizations and workers in meeting upskilling and reskilling challenges. Our findings suggest that investing in workforce development is crucial for ensuring that the benefits of AI are equitably distributed among all stakeholders. Findings: Our findings indicate that organizations must employ a proactive approach to navigate the AI-driven transformation of the workplace. This approach involves mapping the transversal skills needed to address current skill gaps, helping workers identify and develop skills required for effective AI adoption, and implementing processes to support workers through targeted training and development opportunities. These strategies are essential for ensuring that workers' attitudes and mental models towards AI are adaptable and prepared for the changing labor market. Recommendation for Researchers: We emphasize the need for researchers to adopt a transdisciplinary approach when studying AI's impact on the workplace. Given AI's complexity and its far-reaching implications across various fields including computer science, mathematics, engineering, and behavioral and social sciences, integrating diverse perspectives is crucial for a holistic understanding of AI's applications and consequences. Future Research: Looking ahead, further research is needed to deepen our understanding of AI's impact on human skills, particularly the role of soft skills in AI adoption within organizations. Future studies should also address the challenges posed by Industry 5.0, which is expected to bring about even more extensive integration of new technologies and automation.

Carlo Lipizzi’s Societal impacts of artificial intelligence and machine learning offers a critical and comprehensive analysis of artificial intelligence (AI) and machine learning’s effects on society. This book provides a balanced perspective, cutting through the

The study shows that artificial intelligence (AI) has become highly important in contemporary computing because of its capacity to efficiently tackle intricate jobs that were typically carried out by people. The authors provide scientific literature that analyzes and

Anthropic's large language model Claude is preparing for work in the U.S. intelligence community.

The Faculty of Geo-Information Science and Earth Observation (ITC) at the University of Twente has recently launched an investment programme to strengthen its international academic fields. For 11 pioneering-multidisciplinairy projects a PhD-position is made available, three of them already are filled in. The Department of Natural Resources (NRS) specialises in advanced spatial and temporal analysis and technique development for the environment as well as sustainable agriculture.

Job Description: 

For more information visit the official job offer.

“This year’s two Nobel Laureates in physics have used tools from physics to develop methods that are the foundation of today’s powerful machine learning,” said the Nobel committee.

The post Pioneers in artificial intelligence win the Nobel Prize in physics appeared first on Boston.com.

Failed assassination attempt on PM Netanyahu, Defense Minister Gallant reports gains in Lebanon, U.S. leaks Israeli intelligence. Res. Major Amiad Cohen on how to achieve security in N. Israel. Christian friends show support at Feast of Tabernacles.

How do we move video analytics beyond descriptive to prescriptive? From gathering potential questions to providing solutions? The answer is more than just analytics — it is data intelligence. 

The B150 step-down converter offers an additional voltage in a FlexPower system by converting a higher input voltage to a lower output.

According to the announcement, Motorola Solutions’ CommandCentral Aware unifies voice, video and data feeds from public safety, private enterprise and community-facing systems, leveraging AI to verify incident data and speed up response.

Collaborative intelligence facilitates the sharing of ALPR data between partnered organizations such as local police departments, private businesses, and community groups.

Data is valuable because it helps manufacturers make better decisions. But there’s a big difference between collecting data and being able to actually use it. If you don’t have a system in place to be able to understand what the data is telling you, then you’re going to be overwhelmed by it.

As companies seek to enhance precision, increase efficiency and reduce costs, AI-driven computer numerical control (CNC) machining is emerging as a game-changing innovation.

Abstract Social work, as a human rights–based profession, is globally recognized as a profession committed to enhancing human well-being and helping meet the basic needs of all people, with a particular focus on those who are marginalized vulnerable, oppressed, or living in poverty. Artificial intelligence (AI), a sub-discipline of computer science, focuses on developing computers […]

The post Considering a Unified Model of Artificial Intelligence Enhanced Social Work: A Systematic Review was curated by information for practice.

The post CfP: Artificial Intelligence in Health Economics and Outcomes Research was curated by information for practice.

Flashpoint has released its midyear Cyber Threat Intelligence Index, with new data and trends surrounding both persistent and emerging cyber threats observed from 1 January to 30 June, 2024. The report includes research and data tied to vulnerabilities, information-stealing malware, ransomware and insider threats.

NCC Group have just released a free CyberSecurity Threat Intelligence Report for the Retail sector as it enters its busiest spell, the "GoldenQuarter".It will help retailers manage an increasing surge in demand across their IT operations and supply chains.

Alignment of each optical element at a synchrotron beamline takes days, even weeks, for each experiment costing valuable beam time. Evolutionary algorithms (EAs), efficient heuristic search methods based on Darwinian evolution, can be utilized for multi-objective optimization problems in different application areas. In this study, the flux and spot size of a synchrotron beam are optimized for two different experimental setups including optical elements such as lenses and mirrors. Calculations were carried out with the X-ray Tracer beamline simulator using swarm intelligence (SI) algorithms and for comparison the same setups were optimized with EAs. The EAs and SI algorithms used in this study for two different experimental setups are the Genetic Algorithm (GA), Non-dominated Sorting Genetic Algorithm II (NSGA-II), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC). While one of the algorithms optimizes the lens position, the other focuses on optimizing the focal distances of Kirkpatrick–Baez mirrors. First, mono-objective evolutionary algorithms were used and the spot size or flux values checked separately. After comparison of mono-objective algorithms, the multi-objective evolutionary algorithm NSGA-II was run for both objectives – minimum spot size and maximum flux. Every algorithm configuration was run several times for Monte Carlo simulations since these processes generate random solutions and the simulator also produces solutions that are stochastic. The results show that the PSO algorithm gives the best values over all setups.

Source: Rob Goff 11/11/2024

Volatus Aerospace Inc. (TSXV:FLT; OTCQX:TAKOF:ABBA.F) secured CA$2.8 million (CA$2.8M) through a private placement after having recently completed a financing package for CA$15M, reported Ventum Capital Markets analyst Rob Goff in a Nov. 6 research note. Volatus provides aerial intelligence solutions using drones and other aircraft systems, including inspections, surveillance, design, and sales.

"We believe the two financing rounds should be positively rewarded by investors for the financial flexibility they bring to Volatus, while the commitment of the two debt partners represents a strong validation," Goff wrote.

192% Return Implied

Goff reiterated Ventum's target price on the Canadian aircraft solutions provider of CA$0.38 per share. In comparison, it was trading at the time of the report at CA$0.13 per share. From this price, the return to target is 192%.

Volatus is a Buy.

Plans for Using the Funds

Goff discussed the private placement and Volatus' intended uses of it. For the offering, a total of 19,766,000 units was sold at CA$0.14 apiece. Each unit consists of one common Volatus voting share and one common Volatus voting share purchase warrant. With each warrant, the holder may purchase one Volatus common share for CA$0.20 per warrant share during the 24 months after the close of the raise.

"We believe the equity and debt financing will allow Volatus to invest in working capital to support higher equipment sales," an advantage its smaller peers do not have, Goff wrote.

The company expects to fund about CA$9–12M in unmet equipment sales demand, so Goff forecasts it will designate CA$3–4M to this purpose, to purchase working capital. Other uses of the proceeds are for research and development, capital expenditures and inventory.

Goff reported that Volatus wants to leverage every incremental CA$1M of invested working capital into about CA$3–4M of incremental equipment sales annually, aiming for gross profit margins of about 25% and modest incremental operating costs.

Volatus plans to use proceeds from the debt raise to back pay the outstanding CA$6M senior loan it has with a major Canadian bank. The company also intends to open a new secured line of credit to support anticipated growth. Current debt related to its fleet financing is about CA$5M.

Opportunities for Growth

With more balance sheet flexibility, Goff wrote, Volatus may pursue longer-term contracts with utilities and pipelines for inspection services using unmanned and manned fleets. This would position the company to become a leader in this specific market.

Volatus can monetize its portfolio of drones and landing stations. The U.S.' initiatives and intention to reduce use of Chinese-manufactured products could help drive this expansion. The company has third-party manufacturing capabilities to significantly boost its equipment sales.

"We anticipate that Volatus will leverage its unique software, network, and equipment capabilities, stewarded by an experienced and commercially focused leadership team," Goff wrote.

Future Financial Expectations

Goff discussed forecasts for merger synergies, EBITDA, and revenue. As for initial efficiencies achieved from Volatus' merger with Drone Delivery Canada, they should be seen in Volatus' Q4/24 and Q1/25 financial results, Goff wrote. Already, the company has exceeded CA$2.6M in cost synergies and expects to surpass CA$3M in the near term. By 2026, the company estimates revenue synergies will be about CA$5M-plus and will include initial traction gained from business-to-business cargo delivery.

Looking to 2025, Ventum expects Volatus to turn EBITDA break even in Q2/25 and produce CA$5.7M in positive EBITDA in 2025 versus Volatus' estimate of CA$10M-plus, Goff reported. Ventum estimates that Volatus will generate CA$60.3M in revenue in full-year 2025, less than Volatus' guidance of CA$70M+.

"We anticipate that Volatus will leverage its unique software, network, and equipment capabilities, stewarded by an experienced and commercially focused leadership team," wrote Goff.

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1. Doresa Banning wrote this article for Streetwise Reports LLC and provides services to Streetwise Reports as an independent contractor.
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Disclosures for Ventum Capital Markets, Volatus Aerospace Inc., November 6, 2024

Analyst Certification I, Rob Goff, hereby certify that all of the views expressed in this report accurately reflect my personal views about the subject securities or issuers. I also certify that no part of my compensation was, is, or will be, directly or indirectly related to the specific recommendations or views expressed in this report. I am the research analyst primarily responsible for preparing this report.

Research Disclosures

1. Ventum Financial Corp. and its affiliates’ holdings in the subject company’s securities, in aggregate exceeds 1% of each company’s issued and outstanding securities.
2. Ventum Financial Corp. and/or its affiliates have received compensation for investment banking services for the subject company over the preceding 12- month period.
3. Ventum Financial Corp. and/or its affiliates expect to receive or intend to seek compensation for investment banking services from the subject company.
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The social and behavioral sciences (SBS) offer an essential contribution to the mission of the U.S. Intelligence Community (IC), a mission that requires an understanding of what human beings do, how, and why, says a new report by the National Academies of Sciences, Engineering, and Medicine.

Today the national science academies of the G-7 countries issued three joint statements to their respective governments, to inform discussions during the G-7 summit to be held in August in France, as well as to inform ongoing policymaking.

Much digital ink has been spilled on artificial intelligence taking over jobs, but what about AI shaking up the hiring process in the meantime?

A government official said that during the deliberations one of the leaders wondered if AI "replaced or enhanced human skills" and suggested that it should be used in an ethical manner.

Festo to introduce AI-based software for machine uptime, soft-robotic grippers, and economical electric motion at IBIE 2022.