According to the World Health Organization (WHO), the population of people over 80 years of age is projected to triple by 2050, due to advances in quality of life, as well as continued progress in medicine and technology. With this context in mind, this article focuses on conducting a comprehensive study on conventional walkers, which represent a fundamental tool to improve the mobility of elderly people. The main objective of this study is to establish the foundations for the design of walkers, with the purpose of identifying the functional and end user requirements under the WalkIES project funded by IEEE’s Industrial Electronics Society (IES). In this initial phase, we seek to define the ergonomic design of a conventional walker, evaluating its advantages and disadvantages, in addition to establishing the standards that these devices must meet. Based on the results obtained, the specific characteristics of the WalkIES walker will be determined. Additionally, international manufacturing standards for walkers are examined and detailed, taking into account the specific features necessary to ensure the effectiveness and safety of these devices for elderly people. Special attention is paid to the individual characteristics of each component that makes up the walkers, with the aim of optimizing their functionality and comfort for the user. In summary, the study of walkers and the establishment of standards are essential to address the mobility needs of the elderly population and those who require assistance to walk, guaranteeing their safety, comfort, and quality of life, as well as to define the requirements of design and manufacturing for robotic walker WalkIES.

MOTIVATION: Since 2016, the number of microbial species with available reference genomes in NCBI has more than tripled. Multiple genome alignment, the process of identifying nucleotides across multiple genomes which share a common ancestor, is used as the input to numerous downstream comparative analysis methods. Parsnp is one of the few multiple genome alignment methods able to scale to the current era of genomic data; however, there has been no major release since its initial release in 2014. RESULTS: To address this gap, we developed Parsnp v2, which significantly improves on its original release. Parsnp v2 provides users with more control over executions of the program, allowing Parsnp to be better tailored for different use-cases. We introduce a partitioning option to Parsnp, which allows the input to be broken up into multiple parallel alignment processes which are then combined into a final alignment. The partitioning option can reduce memory usage by over 4× and reduce runtime by over 2×, all while maintaining a precise core-genome alignment. The partitioning workflow is also less susceptible to complications caused by assembly artifacts and minor variation, as alignment anchors only need to be conserved within their partition and not across the entire input set. We highlight the performance on datasets involving thousands of bacterial and viral genomes. AVAILABILITY AND IMPLEMENTATION: Parsnp v2 is available at https://github.com/marbl/parsnp.

Student teaching assistants (TAs) are essential contributors to CS education and are often the first point of contact for many students. Given increasing evidence that student achievement is directly correlated to a positive classroom climate, an effective TA must possess not only strong domain and pedagogical skills, but also the skills necessary to maintain an inclusive, welcoming, and supportive classroom environment. Our view is that there is no meaningful separation between pedagogical and climate skills: rather than "compartmentalizing" climate into specific workshops or modules of a course, our semester-long required TA preparation course treats classroom climate as a lens through which traditional pedagogical skills are viewed, such as giving presentations that encourage participation, creating equitable assessments, and creating successful student groups by fostering belonging. We describe a climate-first, scalable, modular TA training curriculum with open-source and curated teaching materials, suitable for in-person or remote instruction, that serves hundreds of first-time TAs each year, and which student feedback suggests is meeting our goals.

Human factors and ergonomics (HFE) research is an important field for improving safety and minimizing risks associated with product-use errors through avoidance of intended or unintended mistakes. For industry, standardization can make the dissimilar elements into systems easier, provides a path to user acceptance, reduces product costs, and opens more markets. For HFE, standardization will increase safety and minimize the risks caused by product use errors and improve productivity. This paper presents an overview of standards in modern HFE. It explains the origins of modern HFE, the use of standards in HFE, and the past and future of HFE related standardization.

With the active development of IES in standards since the mid-2010s, the society has made considerable progress with multiple standards’ developments. This paper presents the results of engaging in standards’ development within and across borders of an IEEE society. In particular, the hands-on INTEROP Plugfests, coupled with the CoEs, provide platforms to create ideas for standards, develop standards, initiate interoperability among multiple vendors, providing competitive time-to-market advantage for involved industry partners.

The agricultural population in Japan is aging and shrinking. Therefore, it is necessary to improve the efficiency of farm work. Additionally, it takes many years to learn the skills required for farming, which discourages many young people from joining the field. As a countermeasure to this problem, smart agriculture technology is gaining increasing attention. Smart agriculture is an approach to increasing the quantity and quality of crops by leveraging advanced technologies. In smart agriculture, a large amount of data are collected from various sensors and internet of things devices. As the use of information and communication technology in agriculture spreads, the demand for data sharing between different agricultural systems increases accordingly. However, electronic data exchange interfaces for agricultural data are not standardized. Therefore, in Japan, it has been recommended to unify data formats using extensible markup language (XML). In this study, we focused on data regarding crop growth states and developed a method for representing plant structure using XML. In the proposed method, branches and fruits are extracted from plant images and their connections are expressed using the hierarchical structure of XML. Compared to conventional management of crop growth states based on images, the proposed method significantly reduces data size. Furthermore, because XML elements can be easily searched and sorted using XPath and XQuery, the XML format makes data easy to utilize for many services. For example, by counting numbers of fruits, profits and work times can be predicted. Additionally, data regarding plant structure is useful for directing farmers or robots to harvest fruits. The proposed method contributes to improving productivity and helps inexperienced farmers.

Technological advancements are allowing the development of smart sensing devices with extremely low energy requirements. An emerging trend is the powering of smart sensors with energy harvested from the operating environment. Simultaneously, the task performed by a sensing node can be performed by a microprocessor with low computational resources. Energy demand of the devices is also decreasing by the adoption of advanced operating methods and energy management strategies. For devices to interoperate efficiently together, the design and operation need to follow standardization methods.

This paper presents a real time algorithm, based on a segmentation and labelling technique, for analog transducer signals, which extracts information from the signal. The process of sampling is extremely important because it is the only one that connects the real world with the digital world. In addition, the proposed technique can be embedded into sensors, allowing applications in sensor networks and sensors data fusion architectures like Internet of Things. A simplified version of these algorithms has been proposed as a standard for transducer signal feature extraction. These algorithms are analysed and experimental results are tackled for representative signals, in different fields.

We live in an interconnected world. The IoT, Internet of Things, is a reality. There are more things connected to internet than people on the planet. The communication channels has been established and standardized, things can be easily identified. We know how to interchange data but we do not know exactly what to interchange. There is a need to reduce the traffic over the networks when the number of nodes increases. Things could be sensors or devices with sensors. Things generate signals and since that the world is inferred through these signals, there is a need to interchange knowledge at low bit rates in a standardized way. The technology explosion that invades our lives has an influence not only on what is plausible to be standardized but opens possibilities not even thought. In the sensor world, intelligence has been concentrated in the point of acquisition, inside the transducer. Considering CPU capabilities, cost, low consumption and reduction of size, the sensor signal will be processed entirely into the smart sensor, even for cheap and simple sensors. The network will be used to interchange more meaningful information or knowledge. This paper focuses on algorithms suitable for any sensor signal that start from oversampled data and end with knowledge about the sensor signal behavior in a normalized scheme. The proposed standard is an important step towards an interconnected and manageable world.