Aim/Purpose: This study analyzes health professionals’ information security behavior (ISB) as health information system (HIS) users concerning associated information security controls and risks established in a public hospital. This work measures ISB using a complete measuring scale and explains the relevant influential factors from the perspectives of Protection Motivation Theory (PMT) and General Deterrence Theory (GDT) Background: Internal users are the primary source of security concerns in hospitals, with malware and social engineering becoming common attack vectors in the health industry. This study focuses on HIS user behavior in developing countries with limited information security policies and resources. Methodology: The research was carried out in three stages. First, a semi-structured interview was conducted with three hospital administrators in charge of HIS implementation to investigate information security controls and threats. Second, a survey of 144 HIS users to determine ISB based on hospital security risk. Third, a semi-structured interview was conducted with 11 HIS users to discuss the elements influencing behavior and current information security implementation. Contribution: This study contributes to ISB practices in hospitals. It discusses how HIS managers could build information security programs to enhance health professionals’ behavior by considering PMT and GDT elements. Findings: According to the findings of this study, the hospital has implemented particular information security management system (ISMS) controls based on international standards, but there is still room for improvement. Insiders are the most prevalent information security dangers discovered, with certain working practices requiring HIS users to disclose passwords with others. The top three most common ISBs HIS users practice include appropriately disposing of printouts, validating link sources, and using a password to unlock the device. Meanwhile, the top three least commonly seen ISBs include transferring sensitive information online, leaving a password in an unsupervised area, and revealing sensitive information via social media. Recommendations for Practitioners: Hospital managers should create work practices that align with information security requirements. HIS managers should provide incentives to improve workers’ perceptions of the benefit of robust information security measures. Recommendation for Researchers: This study suggests more research into the components that influence ISB utilizing diverse theoretical foundations such as Regulatory Focus Theory to compare preventive and promotion motivation to enhance ISB. Impact on Society: This study can potentially improve information security in the healthcare industry, which has substantial risks to human life but still lags behind other vital sector implementations. Future Research: Future research could look into the best content and format for an information security education and training program to promote the behaviors of healthcare professionals that need to be improved based on this ISB measurement and other influential factors.

Aim/Purpose: The main aim of this study was to investigate the impact of knowledge-based Human Resources Management (HRM) practices on inbound and outbound open innovation in Jordanian small and medium enterprises (SMEs). Background: SMEs in Jordan lack tangible resources. This insufficiency can be remedied by using knowledge as a resource. According to the Knowledge-Based View (KBV) theory, which posits knowledge as the most valuable resource, SMEs can achieve open innovation by implementing knowledge-based HRM practices that enhance the utilization of knowledge and yield competitiveness. Methodology: This study adopted the quantitative method employing descriptive and exploratory approaches. A total of 500 Jordanian manufacturing SMEs were selected from 2,310 manufacturing SMEs registered lists, according to the Jordan Social Security, by using random sampling. The study’s instrument was a questionnaire that was applied to these SMEs. There were 335 responses that were deemed useful for analysis after filtering out the replies with missing values; this corresponded to a response rate of 67%. The paper utilized structural equation modeling and cross-sectional design to test hypotheses in the proposed research model. Contribution: This study advocates the assumption of the role of KBV in improving innovation practices. This study contributes to the existing strategic HRM research by extending the understanding of knowledge-based HRM practices in the context of SMEs. Thus, this study contributes to the understanding of innovation management by demonstrating the role of knowledge-based HRM practices in boosting inbound and outbound OI practices, thereby enhancing innovation as an essential component of firm competitiveness. Findings: The findings revealed the positive impact of four knowledge-based HRM practices on inbound and outbound open innovation in Jordanian manufacturing SMEs. These practices were knowledge-based recruitment and selection, knowledge-based training and development, knowledge-based compensation and reward, as well as knowledge-based performance assessment. Recommendations for Practitioners: This study is expected to help the stakeholders of SMEs to re-shape the traditional HRM practices into knowledge-based practices which improve managerial skills, innovation practices, and the level of the firm’s competitiveness. Recommendation for Researchers: This study serves as a significant contribution to the research field of innovation practices by building a new association between knowledge-based HRM practices and inbound and outbound open innovation. Impact on Society: The study emphasizes the vital role of knowledge-based HRM practices in enhancing the knowledge and social skills of the human capital in SMEs in Jordan, thus improving the country’s social and economic development. Future Research: Future research could build on this study to include service SMEs. It could also employ a longitudinal study over the long run which would allow for a deeper analysis of the relationships of causality, offering a more comprehensive view of the effect of knowledge-based HRM on open innovation. Furthermore, future research could examine the sample of investigation before and after implementing the knowledge-based HRM practices to provide stronger evidence of their influence on inbound and outbound innovation.

Aim/Purpose: The UAE and other Middle Eastern countries suffer from various cybersecurity vulnerabilities that are widespread and go undetected. Still, many UAE government organizations rely on human-centric approaches to combat the growing cybersecurity threats. These approaches are ineffective due to the rapid increase in the amount of data in cyberspace, hence necessitating the employment of intelligent technologies such as AI cybersecurity systems. In this regard, this study investigates factors influencing users’ intention to adopt AI-based cybersecurity systems in the UAE. Background: Even though UAE is ranked among the top countries in embracing emerging technologies such as digital identity, robotic process automation (RPA), intelligent automation, and blockchain technologies, among others, it has experienced sluggish adoption of AI cybersecurity systems. This selectiveness in adopting technology begs the question of what factors could make the UAE embrace or accept new technologies, including AI-based cybersecurity systems. One of the probable reasons for the slow adoption and use of AI in cybersecurity systems in UAE organizations is the employee’s perception and attitudes towards such intelligent technologies. Methodology: The study utilized a quantitative approach whereby web-based questionnaires were used to collect data from 370 participants working in UAE government organizations considering or intending to adopt AI-based cybersecurity systems. The data was analyzed using the PLS-SEM approach. Contribution: The study is based on the Protection Motivation Theory (PMT) framework, widely used in information security research. However, it extends this model by including two more variables, job insecurity and resistance to change, to enhance its predictive/exploratory power. Thus, this research improves PMT and contributes to the body of knowledge on technology acceptance, especially in intelligent cybersecurity technology. Findings: This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. All the hypotheses were accepted. The relationship between the six constructs (perceived vulnerability (PV), perceived severity (PS), perceived response efficacy (PRE), perceived self-efficacy (PSE), job insecurity (JI), and resistance to change (RC)) and the intention to adopt AI cybersecurity systems in the UAE was found to be statistically significant. This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. Recommendations for Practitioners: All practitioners must be able to take steps and strategies that focus on factors that have a significant impact on increasing usage intentions. PSE and PRE were found to be positively related to the intention to adopt AI-based cybersecurity systems, suggesting the need for practitioners to focus on them. The government can enact legislation that emphasizes the simplicity and awareness of the benefits of cybersecurity systems in organizations. Recommendation for Researchers: Further research is needed to include other variables such as facilitating conditions, AI knowledge, social influence, and effort efficacy as well as other frameworks such as UTAUT, to better explain individuals’ behavioral intentions to use cybersecurity systems in the UAE. Impact on Society: This study can help all stakeholders understand what factors can increase users’ interest in investing in the applications that are embedded with security. As a result, they have an impact on economic recovery following the COVID-19 pandemic. Future Research: Future research is expected to investigate additional factors that can influence individuals’ behavioral intention to use cybersecurity systems such as facilitating conditions, AI knowledge, social influence, effort efficacy, as well other variables from UTAUT. International research across nations is also required to build a larger sample size to examine the behavior of users.

Aim/Purpose: Previous research has generally concentrated on identifying the variables that most significantly influence customer churn or has used customer segmentation to identify a subset of potential consumers, excluding its effects on forecast accuracy. Consequently, there are two primary research goals in this work. The initial goal was to examine the impact of customer segmentation on the accuracy of customer churn prediction in the banking sector using machine learning models. The second objective is to experiment, contrast, and assess which machine learning approaches are most effective in predicting customer churn. Background: This paper reviews the theoretical basis of customer churn, and customer segmentation, and suggests using supervised machine-learning techniques for customer attrition prediction. Methodology: In this study, we use different machine learning models such as k-means clustering to segment customers, k-nearest neighbors, logistic regression, decision tree, random forest, and support vector machine to apply to the dataset to predict customer churn. Contribution: The results demonstrate that the dataset performs well with the random forest model, with an accuracy of about 97%, and that, following customer segmentation, the mean accuracy of each model performed well, with logistic regression having the lowest accuracy (87.27%) and random forest having the best (97.25%). Findings: Customer segmentation does not have much impact on the precision of predictions. It is dependent on the dataset and the models we choose. Recommendations for Practitioners: The practitioners can apply the proposed solutions to build a predictive system or apply them in other fields such as education, tourism, marketing, and human resources. Recommendation for Researchers: The research paradigm is also applicable in other areas such as artificial intelligence, machine learning, and churn prediction. Impact on Society: Customer churn will cause the value flowing from customers to enterprises to decrease. If customer churn continues to occur, the enterprise will gradually lose its competitive advantage. Future Research: Build a real-time or near real-time application to provide close information to make good decisions. Furthermore, handle the imbalanced data using new techniques.

Aim/Purpose: While existing literature has extensively explored factors influencing the success of big data projects and proposed big data maturity models, no study has harnessed machine learning to predict project success and identify the critical features contributing significantly to that success. The purpose of this paper is to offer fresh insights into the realm of big data projects by leveraging machine-learning algorithms. Background: Previously, we introduced the Global Big Data Maturity Model (GBDMM), which encompassed various domains inspired by the success factors of big data projects. In this paper, we transformed these maturity domains into a survey and collected feedback from 90 big data experts across the Middle East, Gulf, Africa, and Turkey regions regarding their own projects. This approach aims to gather firsthand insights from practitioners and experts in the field. Methodology: To analyze the feedback obtained from the survey, we applied several algorithms suitable for small datasets and categorical features. Our approach included cross-validation and feature selection techniques to mitigate overfitting and enhance model performance. Notably, the best-performing algorithms in our study were the Decision Tree (achieving an F1 score of 67%) and the Cat Boost classifier (also achieving an F1 score of 67%). Contribution: This research makes a significant contribution to the field of big data projects. By utilizing machine-learning techniques, we predict the success or failure of such projects and identify the key features that significantly contribute to their success. This provides companies with a valuable model for predicting their own big data project outcomes. Findings: Our analysis revealed that the domains of strategy and data have the most influential impact on the success of big data projects. Therefore, companies should prioritize these domains when undertaking such projects. Furthermore, we now have an initial model capable of predicting project success or failure, which can be invaluable for companies. Recommendations for Practitioners: Based on our findings, we recommend that practitioners concentrate on developing robust strategies and prioritize data management to enhance the outcomes of their big data projects. Additionally, practitioners can leverage machine-learning techniques to predict the success rate of these projects. Recommendation for Researchers: For further research in this field, we suggest exploring additional algorithms and techniques and refining existing models to enhance the accuracy and reliability of predicting the success of big data projects. Researchers may also investigate further into the interplay between strategy, data, and the success of such projects. Impact on Society: By improving the success rate of big data projects, our findings enable organizations to create more efficient and impactful data-driven solutions across various sectors. This, in turn, facilitates informed decision-making, effective resource allocation, improved operational efficiency, and overall performance enhancement. Future Research: In the future, gathering additional feedback from a broader range of big data experts will be valuable and help refine the prediction algorithm. Conducting longitudinal studies to analyze the long-term success and outcomes of Big Data projects would be beneficial. Furthermore, exploring the applicability of our model across different regions and industries will provide further insights into the field.

Aim/Purpose: The objective of this study is to summarize the challenges of Agile Requirements Engineering (Agile RE) in the public sector in republican and constitutional monarchy nations. Additionally, it offers recommendations to address these challenges. Background: Failure of IT projects in the public sector results in financial losses for the state and loss of public trust, often attributed to issues in requirements engineering such as prioritization of user needs and excessive scope of requirements. IT projects can have a higher success rate with Agile RE, but there are also drawbacks. Therefore, this study holds significance by presenting a thorough framework designed to pinpoint and overcome the challenges associated with Agile RE to increase the success rate of IT projects. Methodology: This study employs a Systematic Literature Review (SLR) protocol in the field of software engineering or related domains, which consists of three main phases: planning the review, conducting the review with a snowballing approach, and reporting the review. Furthermore, the authors perform open coding to categorize challenges based on the Agile methodologies adoption factor model and axial coding to map potential solutions. Contribution: The authors assert that this research enriches the existing literature on Agile RE, specifically within the public sector context, by mapping out challenges and possible solutions that contribute to creating a foundation for future studies to conduct a more in-depth analysis of Agile adoption in the public sector. Furthermore, it compares the barriers of Agile RE in the public sector with the general context, leading to the discovery of new theories specifically for this field. Findings: Most challenges related to Agile RE in the public sector are found in the people and process aspects. Project and organizational-related are subsequent aspects. Therefore, handling people and processes proficiently is imperative within Agile RE to prevent project failure. Recommendations for Practitioners: Our findings offer a comprehensive view of Agile RE in the public sector in republican and constitutional monarchy nations. This study maps the challenges encountered by the public sector and provides potential solutions. The authors encourage practitioners to consider our findings as a foundation for adopting Agile methodology in the public sector. Furthermore, this study can assist practitioners in identifying existing barriers related to Agile RE, pinpointing elements that contribute to overcoming those challenges, and developing strategies based on the specific needs of the organizations. Recommendation for Researchers: Researchers have the potential to expand the scope of this study by conducting research in other countries, especially African countries, as this study has not yet encompassed this geographic region. Additionally, they can strengthen the evidence linking Agile RE challenges to the risk of Agile project failure by performing empirical validation in a specific country. Impact on Society: This research conducts a comprehensive exploration of Agile RE within the public sector, serving as a foundation for the successful adoption of Agile methodology by overcoming obstacles related to Agile RE. This study highlights the importance of managing people, processes, projects, and organizational elements to increase the success of Agile adoption in the public sector. Future Research: In the future, researchers should work towards resolving the limitations identified in this study. This study has not provided a clear prioritization of challenges and solutions according to their significance. Therefore, future researchers can perform a Fuzzy Analytical Hierarchical Process (F-AHP) to prioritize the proposed solutions.

DSSP stands as a foundational tool in the domain of protein secondary structure prediction, yet it encounters notable challenges in accurately annotating irregular structures, such as β-turns and γ-turns, which constitute approximately 25%-30% and 10%-15% of protein turns, respectively. This limitation arises from DSSP's reliance on hydrogen-bond analysis, resulting in annotation gaps and reduced consensus on irregular structures. Alternatively, PROMOTIF excels at identifying these irregular structure annotations using phi-psi information. Despite their complementary strengths, previous methodologies utilised DSSP and PROMOTIF separately, leading to disparate prediction methods for protein secondary structures, hampering comprehensive structure analysis crucial for drug development. In this work, we bridge this gap using an annotation fusion approach, combining DSSP structures with beta, and gamma turns. We introduce IRNN-SS, a model employing deep inception and bidirectional gated recurrent neural networks, achieving 77.4% prediction accuracy on benchmark datasets, outpacing current models.

With the continuous growth and importance of data, the need for strong data protection becomes crucial. Encryption plays a vital role in preserving the confidentiality of data, and attribute-based encryption (ABE) offers a meticulous access control system based on attributes. This study investigates the integration of Fernet encryption with initialisation vector (IV) and ABE, resulting in a hybrid encryption approach that enhances both security and flexibility. By combining the advantages of Fernet encryption and IV-based encryption, the hybrid encryption scheme establishes an effective and robust mechanism for safeguarding data. Fernet encryption, renowned for its simplicity and efficiency, provides authenticated encryption, guaranteeing both the confidentiality and integrity of the data. The incorporation of an initialisation vector (IV) introduces an element of randomness into the encryption process, thereby strengthening the overall security measures. This research paper discusses the advantages and drawbacks of the hybrid encryption of Fernet and IV with ABE.

In recent years, schools (as well as universities) have added cyber security to their computer science curricula. This topic is still new for most of the current teachers, who would normally have a standard computer science background. Therefore the teachers are trained and then teaching their students what they have just learned. In order to explore differences in both populations’ learning, we compared measures of software quality and security between high-school teachers and students. We collected 109 source files, written in Python by 18 teachers and 31 students, and engineered 32 features, based on common standards for software quality (PEP 8) and security (derived from CERT Secure Coding Standards). We use a multi-view, data-driven approach, by (a) using hierarchical clustering to bottom-up partition the population into groups based on their code-related features and (b) building a decision tree model that predicts whether a student or a teacher wrote a given code (resulting with a LOOCV kappa of 0.751). Overall, our findings suggest that the teachers’ codes have a better quality than the students’ – with a sub-group of the teachers, mostly males, demonstrate better coding than their peers and the students – and that the students’ codes are slightly better secured than the teachers’ codes (although both populations show very low security levels). The findings imply that teachers might benefit from their prior knowledge and experience, but also emphasize the lack of continuous involvement of some of the teachers with code-writing. Therefore, findings shed light on computer science teachers as lifelong learners. Findings also highlight the difference between quality and security in today’s programming paradigms. Implications for these findings are discussed.

Personalization is one of the most expected features in the current educational systems. User modeling is supposed to be the first stage of this process, which may incorporate learning style as an important part of the model. Learning style, which is a non-stable characteristic in the case of children, differentiates students in learning preferences. This paper identifies a new hybrid method to initiate and update the information of children’s learning style in an educational system. At the start-up phase, children’s learning style information is gathered through the modified Murphy-Meisgeier Type Indicator for Children (MMTIC) questionnaire, which is based on the well-known Myers-Briggs Type Indicator (MBTI). This primary information will be tuned by tracking children’s behaviors during the learning process. Analytical data mining helped us to cluster these behaviors and find their patterns. The proposed method was applied on 81 fourth grade children in elementary school. Delivering results suggest that this method provides a good precision in recognizing children learning style and may be an appropriate solution for non-stability problems in their preferences.

Aim/Purpose: Students face many challenges improving their soft skills such as critical thinking. This paper offers one possible solution to this problem. Background: This paper considers one method of enhancing critical thinking through a problem-solving game called the Coffee Shop. Problem-solving is a key component to critical thinking, and game-playing is one method of enhancing this through an interactive teaching method. Methodology: Three classes of Vietnamese high school students engaged in the Coffee Shop game. The method seeks outcome measurements through the use of analysis of multiple surveys to assess and interpret if critical thinking may have been improved. Contribution: The study may help to understand the importance of problem-solving in the context of an entrepreneurial setting and add to the variation of methods used to deliver the lesson to students in the classroom. Findings: The findings show that practicing problem-solving scenarios with a focus on critical thinking in a time limited setting results in a measured improvement of this skill. Recommendations for Practitioners: The findings suggest that educators could use games more as tools for problem-solving to contribute to their students’ learning outcomes around developing critical thinking. Recommendation for Researchers: More research could be devoted to developing problem-solving and critical thinking skills through game-play models. Impact on Society: Improved critical thinking skills in individuals could make a greater contribution to society. Future Research A comparative study between different high school grades and genders as well as between different countries or cultures.

Aim/Purpose: To explore the incidence of addiction potential within the Iranian public working population, describing how many Iranian public employees fall within the diagnostic categories of low, moderate, and high addiction potential. Also, to investigate the predicting role of occupational variables such as perceived stress, job security, and job satisfaction on addiction potential and belonging to low, moderate, and high addiction potential diagnostic categories. Background: Substance addiction among employees can lead to several negative consequences at the individual and organizational levels. Also, it is the fourth cause of death in Iran. However, few studies have been conducted on the topic among employees, and non among Iranian employees. Methodology: The study participants were 430 employees working in governmental offices of the North Khorasan province, Iran. Descriptive statistical analysis and multiple linear regression analysis were conducted to explore the incidence of addiction potential within the analyzed population and to investigate whether occupational variables such as perceived stress, job security, and job satisfaction predicted low, moderate, or high addiction potential. Contribution: This paper suggests that perceived stress might act as a risk factor for developing addiction, whereas job security and job satisfaction might be protective factors against the likelihood of addiction development. Findings: More than half of the sample showed moderate to high addiction potential. Perceived stress was positively related to addiction potential. Job security and job satisfaction were negatively related to addiction potential. Recommendation for Researchers: When addressing the topic of substance addiction, researchers should focus on the preventative side of investigating it; that is, addiction risk rather than already unfolded addiction. Also, researchers should be mindful of the cultural context in which studies are conducted. Future Research: Future research might investigate other relevant occupational predictors in relation to employee addiction potential, such as leadership style, work-life balance, and worktime schedule, or expand on the relevant causal chain by including personality traits such as neuroticism.

This article is part of the 2024 BCLT-BTLJ-CMTL Symposium.  Blake E. Reid I am grateful to the BTLJ and BCLT for the opportunity to participate in this symposium’s panel on race, Internet platforms and Section 230. It’s a fortunate and timely opportunity to discuss Spencer Overton’s and Catherine Powell’s critical ...

The post Race, Disability, and Section 230 appeared first on Berkeley Technology Law Journal.

Underpinned by stakeholder and agency theories, this study adopts a qualitative multiple-case study approach to explore and analyse various stakeholder interests and how they affect digitalisation in the health sector of a developing country (DC). The study's findings revealed that four key stakeholder interests - political, regulatory, leadership, and operational - affect digitalisation in the health sector of DCs. Further, the study found that operational and leadership interests were emergent and were triggered by some digitalisation initiatives, which included, inter alia, the use of new eHealth software and the COVID-19 vaccination exercise, which established new structures and worked better through digitalisation. Conversely, political and regulatory interests were found to be relatively enduring since they existed throughout the pre- and post-digitalisation eras. The study also unearthed principal-agent conflicts arising from technological, organisational and regulatory factors that contribute to the paradoxical outcomes of digitalisation in the health sector.

Ph.D. Dissertation Defense Modeling and Extracting Information about Cybersecurity Events from Text Taneeya Satyapanich 9:30-11:30 Monday, 18 November, 2019, ITE346? People now rely on the Internet to carry out much of their daily activities such as banking, ordering food, and socializing with their family and friends. The technology facilitates our lives, but also comes with […]

The post Defense: Taneeya Satyapanich, Modeling and Extracting Information about Cybersecurity Events from Text appeared first on UMBC ebiquity.

This paper how to apply dynamic topic models to a set of cybersecurity documents to understand how the concepts found in them are changing over time.

The post paper: Temporal Understanding of Cybersecurity Threats appeared first on UMBC ebiquity.

Avast Secure Browser strives to offer a ‘private, fast and secure’ service for Windows users. Simply put, this product has been built for privacy by security experts. It boasts an array of features to make sure that all cybersecurity bases are more t...

Hegseth, who is also a former soldier without political experience, will lead the world's most powerful military.

For advocates of universal gun rights, this debate represents a fundamental question about the nature of the Second Amendment: is it an American right or a human right?

WASHINGTON: U.S. President-elect Donald Trump said on Tuesday he has picked Fox News Channel host Pete Hegseth to be secretary of defense, tapping an outsider who has railed against diversity in the military.

“Pete is tough, smart and a true believer in America First,“ Trump said in a statement. “With Pete at the helm, America’s enemies are on notice - Our Military will be Great Again, and America will Never Back Down.”

Hegseth is an Army National Guard veteran and according to his website served in Afghanistan, Iraq, and Guantanamo Bay, Cuba.

Hegseth has said he left the Army in 2021 after being deemed an extremist by an Army that didn't want him anymore.

“The feeling was mutual -- I didn’t want this Army anymore either,“ Hegseth said in his book “The War on Warriors: Behind the Betrayal of the Men Who Keep Us Free.”

There is already anxiety in the Pentagon that Trump aims to root out military officers and career civil servants he perceives to be disloyal.

Culture war issues could be one trigger for firings. Trump was asked by Fox News in June whether he would fire generals described as “woke,“ a term for those focused on racial and social justice but which is used by conservatives to disparage progressive policies.

“At a basic level, do we really want only the woke ‘diverse’ recruits that the Biden administration is curating to be the ones with the guns and the guidons?” Hegseth wrote in “The War on Warriors,“ which was published in June.

“We want those diverse recruits -- pumped full of vaccines and even more poisonous ideologies -- to be sharing a basic training bunk with sane Americans,“ he said.

Trump's former U.S. generals and defense secretaries are among his fiercest critics, with some declaring him unfit for office. Angered, Trump has suggested that his former chairman of the Joint Chiefs of Staff, Mark Milley, could be executed for treason.

KUALA LUMPUR: Integrated palm oil milling services provider Ecoscience International Bhd (EIB), via its wholly-owned subsidiary Ecoscience Manufacturing & Engineering Sdn Bhd, has accepted a letter of award (LoA) for a RM200 million engineering, procurement, and construction (EPC) contract from renewable energy company, Wilhelmina Energy Malaysia Sdn Bhd (WEMSB).

Under the LOA, EIB will provide comprehensive EPC services for the TG2 black pellet plant in Kuantan, Pahang.

These services will include design and engineering, sourcing and quality assurance of equipment and materials, plant infrastructure construction, and testing and start-up activities to support commissioning and ensure operational standards are met.

The specific terms and conditions of the EPC works will be outlined in a binding EPC agreement, which is expected by November 30, 2024.

The LoA was built upon the collaboration agreement (CA) with WEMSB in March 2024, aimed at transforming agricultural waste into sustainable energy, thereby reducing coal consumption and carbon emissions.

EIB managing director Wong Choi Ong expressed confidence in delivering a robust waste-to-energy solution that aligns with WEMSB’s vision for sustainable energy transformation.

“This project is a strategic fit for our expansion into environmental and energy efficiency sectors, building on our core strengths in constructing palm oil mills, supporting facilities, and equipment fabrication.

“As the largest project to be undertaken in our corporate history, we see this as a valuable opportunity to broaden our customer base, enhance our project portfolio, and strengthen our market position.

“The LoA will significantly boost our order book, providing our group with healthy earnings visibility over the next two years,“ he said.

The TG2 black pellet plant will convert oil palm empty fruit bunch (EFB) waste into TG2 black pellets – a drop-in coal replacement fuel.

TG2 black pellets are an advanced type of biofuel pellet, providing benefits over traditional biomass pellets, including enhanced grindability, water resistance, and higher energy density.

As a drop-in fuel, it is renewable and can be used in existing pulverised coal power plants without requiring significant infrastructure modifications.

EIB will continue supporting WEMSB as it expands TG2 black pellet plants across the region.

“Beyond the EPC scope for the TG2 black pellet plant, the CA signed in March 2024 also outlined the possibility of WEMSB outsourcing the plant’s operation and maintenance (O&M) to EIB.

“We are currently exploring this opportunity, and both parties will decide in due course.

“This potential arrangement, if materialise, would create a new, recurring revenue stream for us, complementing our current project-based work,“ Wong added.

WEMSB is a subsidiary of the Netherlands-based renewable energy company Maatschappij Wilhelmina NV, specialising in converting agricultural waste streams into sustainable energy using TG2 black pellets.

The EPC works are expected to commence by December 2024, with an expected project completion timeline of 24 months from the commencement date.

Portable tool to securely delete data. Securely deleting files is required to block the recovering of deleted data. Secure deletion is possible with this program, because Blank And Secure overwrites t... [License: Freeware | Requires: 11|10|8|7 | Size: 158 KB ]

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When should you give your Social Security number and when should you not? Giving out your Social Security number is something you shouldn’t do unless you know it’s absolutely, positively required for what you’re doing. Companies and institutions ask for our Social Security numbers all the time. Unfortunately, they do a mediocre-to-terrible job of securing […]

The post Do Not Give Your Social Security Number at These Places appeared first on Clark Howard.

You can’t be too vigilant when it comes to computer security. It’s way too often that we hear of a new virus or another type of malware making the rounds. Email is often used to implant malware into a computer or direct the user to a malicious website. Once the computer has been compromised or […]

The post 13 Steps To Keeping Your Email Safe and Secure appeared first on Clark Howard.

Trackhouse Aprilia has announced the retention of its rider Raul Fernandez for the next two MotoGP seasons.

The post Raul Fernandez Secures Two-Year MotoGP Extension at Trackhouse Aprilia appeared first on BikeSport News.

Soaring vegetable prices undermine expectations for a dovish approach in the upcoming monetary policy meeting

The first shot to use Section 230 to force adversarial interoperability on platforms has hit a setback. Earlier this year, we wrote about an absolutely fascinating lawsuit that was an attempt to activate a mostly-ignored part of Section 230 in a really interesting way. Most people know about Section 230 for its immunity protections for […]

An undated image of Ivanka Trump. — Instagram/@ivankatrump

Ivanka Trump, the eldest daughter of former United States president Donald Trump, is often seen flaunting her flawless looks and she recently recently opened up about her fitness journey.

The 43-year-old...

In understanding and improving the CAPA system as a whole, this book reflects the importance of the investigation/root cause analysis stage as the necessary step of any effective corrective and preventive action system

The movie seems like an intense, gripping thriller with a determined female protagonist

In what has been a long period of relative low activity, FDA’s OPDP has taken the opportunity to remind us that low enforcement does not mean no enforcement when it comes to promotional speech by pharmaceutical companies. This past June … Continue reading →

Cloudflare is urging the EU Commission to exclude the company from its upcoming Piracy Watch List, despite requests from several rightsholder groups for its inclusion. The American company says it's committed to addressing piracy concerns but not at the expense of user privacy and security. Instead, the European Commission should ensure that its Piracy Watch List does not become a tool for advocating policy changes.

From: TF, for the latest news on copyright battles, piracy and more.

The Green Shirts handed 5-1 defeat in the Asian Champions Trophy

Masood says 13,000 Kashmiri boys have been abducted and kept in prison houses where they're being subjected to torture

Computerised weighing scales have been installed

Donald Trump gestures next to South Dakota Governor Kristi Noem during a town hall campaign event in Oaks, Pennsylvania, US, October 14, 2024. — Reuters

US President-elect Donald Trump has picked South Dakota Governor Kristi Noem to serve as the next secretary of the Department of...

US President-elect Donald Trump and Republican US Senator Marco Rubio 2011. — Reuters

US President-elect Donald Trump announced new members of his incoming administration on Monday, and was expected to pick Senator Marco Rubio as secretary of state.

Both Rubio and...

US President Donald Trump is interviewed by Fox and Friends co-host Pete Hegseth at the White House in Washington, US April 6, 2017. REUTERS

US President-elect Donald Trump said on Tuesday he has picked as his secretary of defence Pete Hegseth, a Fox News commentator and veteran who has...

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PTI leader Salman Akram Raja and founder Imran Khan. —Screengrab/ X/ @salmanAraja/ Instagram/ @ptiofficial/ FileOmar Ayub's resignation not yet formally accepted.Gohar says Raja’s work as secy gen is internal matter.PTI Constitution has no provision for secy gen's nomination.

Punjab police personnel arresting top PTI leaders and SIC chief outside Rawalpindi's Adiala jail on November 12, 2024. — ReporterAyub, Qaiser, Raza were detained outside Adiala Jail.Police say top politicians arrested for violating Section 144. PTI says politicians were waiting...

Karachi Police Chief Javed Alam Odho speaks during an event in Karachi, on July 24, 2024. — Facebook/@ssusindhpoliceOdho calls for stricter laws to address this alarming trend.Karachi's top cop warns security company owners of action.Legislation to tighten rules for companies in...

People ride on motorbikes amid smog on a road in Multan, Pakistan November 12, 2024. — ReutersPunjab chokes on toxic smog despite mitigation effortsMultan records AQI of 396 this morning on IQ Air's live rankings. Man killed, three injured road accident due to low...

Police personnel stop commuters at a checkpoint on a road leading towards Karachi airport, on November 13, 2024. — ReporterLEAs close off road leading from Star Gate to Jinnah Terminal.Traffic being diverted from Model Colony to Sharea Faisal: police.New measures taken due to...

Second quarter and first half 2018 results