Aim/Purpose: The primary objective of this research is to build an enhanced framework for Applied and Computational Math. This framework allows a variety of applied math concepts to be organized into a meaningful whole. Background: The framework can help students grasp new mathematical applications by comparing them to a common reference model. Methodology: In this research, we measure the most frequent words used in a sample of Math and Computer Science books. We combine these words with those obtained in an earlier study, from which we constructed our original Computational Math scale. Contribution: The enhanced framework improves the Computational Math scale by integrating selected concepts from the field of Data Science. Findings: The resulting enhanced framework better explains how abstract mathematical models and algorithms are tied to real world applications and computer implementations. Future Research: We want to empirically test our enhanced Applied and Computational Math framework in a classroom setting. Our goal is to measure how effective the use of this framework is in improving students’ understanding of newly introduced Math concepts.

Aim/Purpose. The aim of this study is to propose a teaching approach based on AI-based chatbot agents and to determine whether the use of this approach increases the students’ motivation. Background. Today, chatbots are an integral part of students’ lives where they are used in various contexts. Therefore, we are interested in incorporating these tools into our teaching process in order to profit from their benefits, assist and guide students while working with to prevent issues such as plagiarism and mainly to boost students’ motivation. Methodology. Using the proposed approach, new chatbot based learning activities were de-signed in three different courses for computer science engineering students. A mixed-method experimental study was conducted to evaluate students’ impression and satisfaction. Survey results of the students (N=58) who participated in the experiment (experimental group) were compared to the results of the students from the control group (N=60). Contribution. Trending AI conversational agents can be engaged in daily teaching activities as a learning assistant and coach to boost students motivation and skills development. Findings. Our study focuses on the impact of chatbots on student’s motivation. The study aimed to analyze the benefits and drawbacks associated with these conversational chatbots. Our findings revealed the significant role that chatbots can play in enhancing student motivation and improving teaching practices.

Aim/Purpose: This study presents a novel deep learning-based framework designed to enhance spontaneous micro-expression recognition by effectively increasing the amount and variety of data and balancing the class distribution to improve recognition accuracy. Background: Micro-expression recognition using deep learning requires large amounts of data. Micro-expression datasets are relatively small, and their class distribution is not balanced. Methodology: This study developed a framework using a deep learning-based model to recognize spontaneous micro-expressions on a person’s face. The framework also includes several technical stages, including image and data preprocessing. In data preprocessing, data augmentation is carried out to increase the amount and variety of data and class balancing to balance the distribution of sample classes in the dataset. Contribution: This study’s essential contribution lies in enhancing the accuracy of micro-expression recognition and overcoming the limited amount of data and imbalanced class distribution that typically leads to overfitting. Findings: The results indicate that the proposed framework, with its data preprocessing stages and deep learning model, significantly increases the accuracy of micro-expression recognition by overcoming dataset limitations and producing a balanced class distribution. This leads to improved micro-expression recognition accuracy using deep learning techniques. Recommendations for Practitioners: Practitioners can utilize the model produced by the proposed framework, which was developed to recognize spontaneous micro-expressions on a person’s face, by implementing it as an emotional analysis application based on facial micro-expressions. Recommendation for Researchers: Researchers involved in the development of a spontaneous micro-expression recognition framework for analyzing hidden emotions from a person’s face are playing an essential role in advancing this field and continue to search for more innovative deep learning-based solutions that continue to explore techniques to increase the amount and variety of data and find solutions to balancing the number of sample classes in various micro-expression datasets. They can further improvise to develop deep learning model architectures that are more suitable and relevant according to the needs of recognition tasks and the various characteristics of different datasets. Impact on Society: The proposed framework could significantly impact society by providing a reliable model for recognizing spontaneous micro-expressions in real-world applications, ranging from security systems and criminal investigations to healthcare and emotional analysis. Future Research: Developing a spontaneous micro-expression recognition framework based on spatial and temporal flow requires the learning model to classify optimal features. Our future work will focus more on exploring micro-expression features by developing various alternative learning models and increasing the weights of spatial and temporal features.

Aim/Purpose: Accurate detection of vacant parking spaces is crucial for autonomous parking. Deep learning, particularly Graph Neural Networks (GNNs), holds promise for addressing the challenges of diverse parking lot appearances and complex visual environments. Our GNN-based approach leverages the spatial layout of detected marking points in around-view images to learn robust feature representations that are resilient to occlusions and lighting variations. We demonstrate significant accuracy improvements on benchmark datasets compared to existing methods, showcasing the effectiveness of our GNN-based solution. Further research is needed to explore the scalability and generalizability of this approach in real-world scenarios and to consider the potential ethical implications of autonomous parking technologies. Background: GNNs offer a number of advantages over traditional parking spot detection methods. Unlike methods that treat objects as discrete entities, GNNs may leverage the inherent connections among parking markers (lines, dots) inside an image. This ability to exploit spatial connections leads to more accurate parking space detection, even in challenging scenarios with shifting illumination. Real-time applications are another area where GNNs exhibit promise, which is critical for autonomous vehicles. Their ability to intuitively understand linkages across marking sites may further simplify the process compared to traditional deep-learning approaches that need complex feature development. Furthermore, the proposed GNN model streamlines parking space recognition by potentially combining slot inference and marking point recognition in a single step. All things considered, GNNs present a viable method for obtaining stronger and more precise parking slot recognition, opening the door for autonomous car self-parking technology developments. Methodology: The proposed research introduces a novel, end-to-end trainable method for parking slot detection using bird’s-eye images and GNNs. The approach involves a two-stage process. First, a marking-point detector network is employed to identify potential parking markers, extracting features such as confidence scores and positions. After refining these detections, a marking-point encoder network extracts and embeds location and appearance information. The enhanced data is then loaded into a fully linked network, with each node representing a marker. An attentional GNN is then utilized to leverage the spatial relationships between neighbors, allowing for selective information aggregation and capturing intricate interactions. Finally, a dedicated entrance line discriminator network, trained on GNN outputs, classifies pairs of markers as potential entry lines based on learned node attributes. This multi-stage approach, evaluated on benchmark datasets, aims to achieve robust and accurate parking slot detection even in diverse and challenging environments. Contribution: The present study makes a significant contribution to the parking slot detection domain by introducing an attentional GNN-based approach that capitalizes on the spatial relationships between marking points for enhanced robustness. Additionally, the paper offers a fully trainable end-to-end model that eliminates the need for manual post-processing, thereby streamlining the process. Furthermore, the study reduces training costs by dispensing with the need for detailed annotations of marking point properties, thereby making it more accessible and cost-effective. Findings: The goal of this research is to present a unique approach to parking space recognition using GNNs and bird’s-eye photos. The study’s findings demonstrated significant improvements over earlier algorithms, with accuracy on par with the state-of-the-art DMPR-PS method. Moreover, the suggested method provides a fully trainable solution with less reliance on manually specified rules and more economical training needs. One crucial component of this approach is the GNN’s performance. By making use of the spatial correlations between marking locations, the GNN delivers greater accuracy and recall than a completely linked baseline. The GNN successfully learns discriminative features by separating paired marking points (creating parking spots) from unpaired ones, according to further analysis using cosine similarity. There are restrictions, though, especially where there are unclear markings. Successful parking slot identification in various circumstances proves the recommended method’s usefulness, with occasional failures in poor visibility conditions. Future work addresses these limitations and explores adapting the model to different image formats (e.g., side-view) and scenarios without relying on prior entry line information. An ablation study is conducted to investigate the impact of different backbone architectures on image feature extraction. The results reveal that VGG16 is optimal for balancing accuracy and real-time processing requirements. Recommendations for Practitioners: Developers of parking systems are encouraged to incorporate GNN-based techniques into their autonomous parking systems, as these methods exhibit enhanced accuracy and robustness when handling a wide range of parking scenarios. Furthermore, attention mechanisms within deep learning models can provide significant advantages for tasks that involve spatial relationships and contextual information in other vision-based applications. Recommendation for Researchers: Further research is necessary to assess the effectiveness of GNN-based methods in real-world situations. To obtain accurate results, it is important to employ large-scale datasets that include diverse lighting conditions, parking layouts, and vehicle types. Incorporating semantic information such as parking signs and lane markings into GNN models can enhance their ability to interpret and understand context. Moreover, it is crucial to address ethical concerns, including privacy, potential biases, and responsible deployment, in the development of autonomous parking technologies. Impact on Society: Optimized utilization of parking spaces can help cities manage parking resources efficiently, thereby reducing traffic congestion and fuel consumption. Automating parking processes can also enhance accessibility and provide safer and more convenient parking experiences, especially for individuals with disabilities. The development of dependable parking capabilities for autonomous vehicles can also contribute to smoother traffic flow, potentially reducing accidents and positively impacting society. Future Research: Developing and optimizing graph neural network-based models for real-time deployment in autonomous vehicles with limited resources is a critical objective. Investigating the integration of GNNs with other deep learning techniques for multi-modal parking slot detection, radar, and other sensors is essential for enhancing the understanding of the environment. Lastly, it is crucial to develop explainable AI methods to elucidate the decision-making processes of GNN models in parking slot detection, ensuring fairness, transparency, and responsible utilization of this technology.

Implementing inquiry in the outdoors introduces many challenges for teachers, some of which can be dealt with using mobile technologies. For productive use of these technologies, teachers should be provided with the opportunity to develop relevant knowledge and practices. In a professional development (PD) program in this design-based research, 24 teachers were involved in adaptation of a learning environment supporting inquiry in the outdoors that included the use of mobile technologies. They first experienced the learning environment as learners, then adapted it for their own use, and finally, enacted the adapted environment with peers. We examined the scope and character of teacher involvement in adaptation, and the consequent professional growth, by analyzing observations, questionnaires, interviews and the adapted learning-environments. Findings indicate that all teachers demonstrated change processes, including changes in knowledge and practice, but the coherence of the learning environments decreased when substantial adaptations were made. Some teachers demonstrated professional growth, as reflected by their implementation of ideas learned in the PD program in their daily practice, long after the PD program had ended. This study demonstrates how the Teachers as Designers approach can support teacher learning and illustrates productive use of scaffolds for teacher growth and professional development.

There is a growing interest in the assessment of tangible skills and competence. Specifically, there is an increase in the offerings of competency-based assessments, and some academic institutions are offering college credits for individuals who can demonstrate adequate level of competency on such assessments. An increased interest has been placed on competency-based computer simulations that can assist learners to gain tangible skills. While computer simulations and competency-based projects, in general and particularly in management, have demonstrated great value, there are still limited empirical results on their benefits to e-learners. Thus, we have developed a quasi-experimental research, using a survey instrument on pre- and post-tests, to collect the set of 12 management skills from e-learners attending courses that included both competency-based computer simulations and those that didn’t. Our data included a total of 253 participants. Results show that all 12 management skills measures demonstrated very high reliability. Our results also indicate that all 12 skills of the competency-based computer simulations had higher increase than those that didn’t. Analyses on the mean increases indicated an overall statistically significant difference for six of the 12 management skills enhancements between the experimental and control groups. Our findings demonstrate that overall computer simulations and competency-based projects do provide added value in the context of e-learning when it comes to management skills.

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.

As a result of the rapid development of Information and Communication Technology (ICT) and the growing interest in Internet-based tools for language classroom, it has become a pressing need for educators to locate, evaluate and select the most appropriate language-learning digital resources that foster more communicative and meaningful learning processes. Hence, this paper describes a mixed research project that, on the first hand, aimed at proposing a Checklist for evaluating language websites built on the principles of the Communicative Approach, and on the second hand, sought to strengthen the teachers’ Knowing-how-to-do skill as part of their digital competence. To achieve these goals, a four-phase research procedure was followed that included reviewing relevant literature and administering qualitative and quantitative research methods to participants (i.e., language teachers, an expert in the Computer-Assisted Language Learning (CALL) field and a college professor) in order to gain insights into problematic issues and, thereafter, to contribute to the creation and validation of the Checklist model and the Study Guide. The findings revealed that: (a) evaluating language websites leads to the enhancement of the teachers’ practical skills and their knowledge of the technological language; and (b) having an assessment instrument allows educators to choose the materials that best meet their communicative teaching purposes.

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.

Israel's security Cabinet has signed off on steps to improve the humanitarian situation in the Gaza Strip ahead of Wednesday's deadline imposed by the Biden administration to address the dilemma or face a weapons embargo.

Set to compile the largest biodiversity data collection for Europe to date, the EU-funded FP7 project Building the European Biodiversity Observation Network (EU BON) has now launched the beta-version of its European Biodiversity Portal.

Despite being a beta version, this release already addresses the main aim to offer a unique service for analysing and understanding biodiversity change in Europe. For instance, users can explore how relative abundance of species (within a larger group) changes over time by using big data mediated by GBIF. There is also a spatial browser for locating datasets in any part of the world, which may be usable for computing the EBVs for species populations.

Additionally, an online analytical data processing (OLAP) toolbox has been included in this release. Based on GEOSS technology, the new portal lets users harvest and simultaneously access data from several directories, including GBIF, LTER, EuMon (coming), PESI, and GEOSS sources.

Started in 2012, the five-year project EU BON has been working towards building this new European Biodiversity Portal where scattered and various information and tools are collected, highlighted and widely shared for future research.

The service will provide all interested parties with a professional database platform with a large amount of implications. For example, coordinators can receive information about related monitoring programs in different countries. Initiatives could integrate their data and compare the trends and status across different countries and regions.

"The ultimate goal of EU BON is to build a comprehensive European Biodiversity Portal that will then feed into a Global Portal currently developed by GEO BON. This initiative will provide a completely new holistic way for analyzing global trends and processes.", concludes Dr. Hannu Saarenmaa, University of Eastern Finland and Work Package leader in EU BON.

We invite everyone to test the new portal and send us their feedback and suggestions for improvements via our Feedback Form.

EU projects EuMon and EU BON call out to monitoring programs to share data and expertise for building the European Biodiversity Portal.

Combining forces, two large scale EU projects, EuMon and EU BON, are set to compile the largest data collection on biodiversity monitoring activities in Europe to date. Using existing biodiversity data and metadata collected by the two projects, the initiative is a stepping stone in completing a comprehensive European Biodiversity Portal. The projects now call out to monitoring programs across the Old Continent and beyond, to join in, provide information about their schemes and share their expertise for the cause.

For its life span between 2004 and 2008 the project EU-wide monitoring methods and systems of surveillance for species and habitats of Community interest (EuMon) created Europe's most comprehensive metadata catalogue of biodiversity monitoring activities.

Started in 2012, the five-year project Building the European Biodiversity Observation Network(EU BON) has been working towards building a new European Biodiversity Portal where this information is collected, highlighted and widely shared for future research and applied biodiversity conservation. The beta version is now all set up and available to test here.

To answer knowledge gaps since the project has ended in 2008, the original EuMon monitoring meta database is being further expanded with new information on data availability and access, as well as with new remote sensing data. Previously underrepresented, the marine realm is now also included in the EuMon collection.

"Monitoring data has received a central stage in recent years, a process largely facilitated by the instalment of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES). However, while knowledge about monitoring efforts is important, we still miss a large variety of available programs and biodiversity data", explains EuMon's Project Leader Prof. Dr. Klaus Henle, Helmholtz Centre for Environmental Research - UFZ.

"We, therefore, currently aim to increase and update the number of monitoring programs in the EuMon catalogue, as the catalogue still covers less than half of all existing programs in Europe", adds EuMon Project Coordinator, Dirk Schmeller, UFZ.

In a joint initiative EuMon and EU BON are now looking to create the opportunity for monitoring program coordinators to publish their data by using the data publishing service of the EU BON portal (data embargos also possible).

The service will provide all interested parties with a professional database platform with a large amount of implications. For example, coordinators can receive information about related monitoring programs in different countries. Initiatives could integrate their data and compare the trends and status across different countries and regions. Volunteers can find contacts about schemes in their regions they may consider to join.

Using the data publishing service of EU BON will also facilitate data sharing with the Global Biodiversity Information Facility.

"The ultimate goal of EU BON is to build a comprehensive European Biodiversity Portal that will then feed into a Global Portal currently developed by GEO BON. This initiative will provide a completely new holistic way for analyzing global trends and processes. We invite projects from across Europe to publish their datasets via the European Biodiversity Portal and become a part of this one-of-a-kind initiative", concludes Dr. Hannu Saarenmaa, University of Eastern Finland and Work Package leader in EU BON.

How to take part:

To access the EuMon database, please visit http://eumon.ckff.si/biomat. For sharing information about your monitoring program, please register here. You will then be able to provide metadata about your scheme via a simple online questionnaire. Answering the full set of questions is desirable, but not compulsory.

Oak City Remodeling in Raleigh, North Carolina, elevates the home renovation experience with comprehensive services.

Washington — The National Highway Traffic Safety Administration has issued a final rule intended to protect drivers and passengers on motorcoaches and large buses during rollovers by enhancing the structural integrity of the vehicles.

Albany, NY — Attorneys general from New York, California and Maryland have filed a lawsuit challenging the Environmental Protection Agency’s decision to indefinitely delay a requirement for employers to provide enhanced training intended to protect farmworkers, pesticide handlers and their families from exposure to pesticides.

Washington — The Environmental Protection Agency on June 14 announced its intent to publish a Federal Register notice establishing the availability of expanded pesticide safety training materials, in accordance with 2015 revisions to the federal Agricultural Worker Protection Standard.

Genetec Inc. announced that the company unified security platform has been chosen by Brazil’s Hercílio Luz International Airport in Florianópolis (Floripa), to manage its physical security infrastructure, and provide operational insights.

Convergint will integrate Alcatraz AI's Rock X facial authentication solution into its security systems, enhancing global enterprise access control with advanced AI technology.

Simpro Group’s acquisition of BigChange enhances its field service management capabilities, offering comprehensive solutions for diverse customer needs globally.

Convergint and Deloitte have announced a strategic partnership to deliver integrated cyber and physical security solutions, aimed at helping clients address evolving security challenges and enhance regulatory compliance.

The GLO-0066 FrogWear HV Enhanced Visibility Pink Surveyors Safety Vest is made of a breathable mesh material and features silver reflective material for low-light visibility, as well as contrasting black stripes.

Industry insiders convened at ISC West to discuss AVS-01, a new ANSI-accredited standard aimed at improving alarm validation and enhancing communication between the security sector and public safety agencies.

Verkada’s partner event in Denver brought together over 1,600 security professionals to showcase cutting-edge cloud-based solutions, AI-enabled products, plus insights into the evolving role of physical security technologies.

Washington – The Pipeline and Hazardous Materials Safety Administration is requesting public input on a proposal to enhance the safety and durability of rail tank cars used to transport hazardous materials.

Washington — Federal regulation of small distribution systems for propane and other liquefied petroleum gas should be revised for clarity, efficiency, enforceability and applicability to risk, a new report from the National Academies of Sciences, Engineering, and Medicine concludes.

Atlanta — Suicide prevention strategies for workers are needed to help mitigate rising workplace suicide rates, a recent report from the Centers for Disease Control and Prevention suggests.

Both features will be available to users of WeSuite’s web-based platform, QuoteAnywhere, without the need for configuration or management via WeEstimate software.

Snap One announced that its Luma x20 family of surveillance products now offer full control over integrators’ system access to view live and recorded video.

The update includes several new features for integrator partners and end users designed to help increase safety and improve the overall user experience with greater visibility into systems, flexibility, and additional third party integrations.

The Monitoring Association signed a multi-year managed services agreement with Mission Critical Partners to accelerate the rollout and development of the Automated Secure Alarm Protocol service, driving the development of ASAP’s next-generation, cloud-based solution.

Critical Response Group (CRG) and Intrado, announced the integration of CRG within Intrado’s FirstNet certified Safety Shield application.

Learn how Qovo Solutions integrated Verkada AI-powered cameras for LYNX Logistics.

In collaboration with Indiana based partner CK2 Technologies, Xtract One was able to integrate SmartGateway into decades-old buildings without compromising the visitor experience.

Cass County, a rural area encompassing 565 square miles of primarily agricultural land, has faced recent challenges in providing timely emergency medical services (EMS) due to decreased volunteers and reduced manpower.

Sarasota County Schools already completed a successful deployment in one of its high schools the past year, which received overwhelmingly positive results and response from parents and staff, according to the announcement.

The system was designed around the IQ Panel 4 and the range and reliability of PowerG to ensure wireless communication with each device across the property, including the heavily wooded areas.

Offering an efficient and effective security solution for patron ingress is essential, and with the implementation of Xtract One’s SmartGateway, these venues have enhanced security and operational efficiency while maintaining a welcoming environment.

The collaboration helps to make multimedia redaction for subject access requests and digital evidence faster and more accurate through the implementation of artificial intelligence technologies, which marks the start of an exciting business development for Pimloc.

Chimera Integrations recently completed a security upgrade at UHS Hospital in Binghamton.

Your commitment to safety can make a tangible difference in your employees’ lives and your organization’s overall success. These eight essential strategies can help you lead the way in building a safety culture beyond compliance.

To leverage its geo-diverse redundancy, COPS Monitoring will deploy two identical NetApp SANs in its New Jersey and Texas facilities.