CLOCIS:Cloud-based conformance testing framework for IoT devices in the future internet

In recent years, the Internet of Things (IoT) has not only become ubiquitous in daily life but has also emerged as a pivotal technology across various sectors, including smart factories and smart cities. Consequently, there is a pressing need to ensure the consistent and uninterrupted delivery of IoT services. Conformance testing has thus become an integral aspect of IoT technologies. However, traditional methods of IoT conformance testing fall short of addressing the evolving requirements put forth by both industry and academia. Historically, IoT testing has necessitated a visit to a testing laboratory, implying that both the testing systems and testers must be co-located. Furthermore, there is a notable absence of a comprehensive method for testing an array of IoT standards, especially given their inherent heterogeneity. With a surge in the development of diverse IoT standards, crafting an appropriate testing environment poses challenges. To address these concerns, this article introduces a method for remote IoT conformance testing, underpinned by a novel conceptual architecture termed CLOCIS. This architecture encompasses an extensible approach tailored for a myriad of IoT standards. Moreover, we elucidate the methods and procedures integral to testing IoT devices. CLOCIS, predicated on this conceptual framework, is actualized, and to attest to its viability, we undertake IoT conformance testing and present the results. When leveraging CLOCIS, small and medium-sized enterprises (SMEs) and entities in the throes of IoT service development stand to benefit from a reduced time to market and cost-efficient testing procedures. Additionally, this innovation holds promise for IoT standardization communities, enabling them to champion their standards with renewed vigor

Optical Air-Gap Attacks:Analysis and IoT Threat Implications

Since 2008, the Korean government has instituted network separation technology, which physically isolates external internet networks from internal networks, aiming to thwart cyber-attacks. Consequently, the domestic financial sector was largely unaffected during global crises (2017 WannaCry ransomware outbreak and the 2021 Log4j vulnerability incident). However, there exist certain vulnerabilities owing to the presumption of their relative safety against cyber intrusions and the integration of cloud and Internet of Things (IoT) technologies in the current smart revolution. The existing network separation measures only mitigate one facet of potential cyber threats, rendering a comprehensive defense elusive. The rise of “air-gap” attacks, which exploit the isolated space between closed and external networks to illicitly transfer data and the existing research primarily substantiating the potential for data breaches from closed networks to their external counterparts are problems yet to be addressed. Thus, our study proposed a tangible optical air-gap attack methodology, harnessing readily available optical mediums within closed networks. Intricate measurement metrics that consider vital factors of the transmission environment were proposed. Moreover, acknowledging the proliferating integration of IoT devices, such as smart bulbs, to facilitate automation within closed networks, this study demonstrated the viability of optical air-gap attacks using these devices

The current state of graphical abstracts and how to create good graphical abstracts

Graphical abstracts (GAs), also known as visual abstracts, are powerful tools for communicating complex information and ideas clearly and concisely. These visual representations aim to capture the essential findings and central message of a research study, allowing the audience to understand and remember its content quickly. This review article describes the current state of GAs, including their benefits, limitations, and future directions in the development of GAs. It also presents methods and tips for producing a GA. In Korea, more than 10 medical journals have introduced GAs from 2021 to 2022. The number of citations was higher in articles with GAs than in those without GAs in the top 10 gastroenterology journals. There are five types of GAs: conceptual diagrams, flowcharts, infographics, iconographic abstracts, and photograph-like illustrations. A limitation of the GA system is the absence of a universal standard for GAs. The key steps for creating a GA are as follows: (1) start by identifying the main message; (2) choose an appropriate visual style; (3) draw an easy-to-understand graphic; (4) use colors and other design elements; and (5) request feedback. Available tools that are useful for creating GAs include Microsoft PowerPoint, Mind the Graph, Biorender, and Canva. Another effective method is collaborating with experts. Artificial intelligence will soon be able to produce GAs more efficiently from raw data or manuscripts, which will help researchers draw GAs more easily. GAs have become a crucial art for researchers to master, and their use is expected to expand in the future

An Analysis of Research Trends in Brain-based Learning in Adult Education and HRD Fields: The Content Analysis and Network Text Analysis

The purpose of this study is to address the trends of the research on brain-based learning and to present an integrative theoretical framework to provide new insights and future directions in adult education and HRD fields. Based on the neuroscientific perspective, the implications of which the ways to conceptually broaden educational research and practice were discussed

ChEDDAR: Student-ChatGPT Dialogue in EFL Writing Education

The integration of generative AI in education is expanding, yet empirical analyses of large-scale, real-world interactions between students and AI systems still remain limited. In this study, we present ChEDDAR, ChatGPT & EFL Learner's Dialogue Dataset As Revising an essay, which is collected from a semester-long longitudinal experiment involving 212 college students enrolled in English as Foreign Langauge (EFL) writing courses. The students were asked to revise their essays through dialogues with ChatGPT. ChEDDAR includes a conversation log, utterance-level essay edit history, self-rated satisfaction, and students' intent, in addition to session-level pre-and-post surveys documenting their objectives and overall experiences. We analyze students' usage patterns and perceptions regarding generative AI with respect to their intent and satisfaction. As a foundational step, we establish baseline results for two pivotal tasks in task-oriented dialogue systems within educational contexts: intent detection and satisfaction estimation. We finally suggest further research to refine the integration of generative AI into education settings, outlining potential scenarios utilizing ChEDDAR. ChEDDAR is publicly available at https://github.com/zeunie/ChEDDAR

RECIPE4U: Student-ChatGPT Interaction Dataset in EFL Writing Education

The integration of generative AI in education is expanding, yet empirical analyses of large-scale and real-world interactions between students and AI systems still remain limited. Addressing this gap, we present RECIPE4U (RECIPE for University), a dataset sourced from a semester-long experiment with 212 college students in English as Foreign Language (EFL) writing courses. During the study, students engaged in dialogues with ChatGPT to revise their essays. RECIPE4U includes comprehensive records of these interactions, including conversation logs, students' intent, students' self-rated satisfaction, and students' essay edit histories. In particular, we annotate the students' utterances in RECIPE4U with 13 intention labels based on our coding schemes. We establish baseline results for two subtasks in task-oriented dialogue systems within educational contexts: intent detection and satisfaction estimation. As a foundational step, we explore student-ChatGPT interaction patterns through RECIPE4U and analyze them by focusing on students' dialogue, essay data statistics, and students' essay edits. We further illustrate potential applications of RECIPE4U dataset for enhancing the incorporation of LLMs in educational frameworks. RECIPE4U is publicly available at https://zeunie.github.io/RECIPE4U/.Comment: arXiv admin note: text overlap with arXiv:2309.1324

Progesterone Signaling Inhibits Cervical Carcinogenesis in Mice

Human papillomavirus is the main cause of cervical cancer, yet other nonviral cofactors are also required for the disease. The uterine cervix is a hormone-responsive tissue, and female hormones have been implicated in cervical carcinogenesis. A transgenic mouse model expressing human papillomavirus oncogenes E6 and/or E7has proven useful to study a mechanism of hormone actions in the context of this common malignancy. Estrogen and estrogen receptor ? are required for the development of cervical cancer in this mouse model. Estrogen receptor ? is known to up-regulate expression of the progesterone receptor, which, on activation by its ligands, either promotes or inhibits carcinogenesis, depending on the tissue context. Here, we report that progesterone receptor inhibits cervical and vaginal epithelial cell proliferation in a ligand-dependent manner. We also report that synthetic progestin medroxyprogesterone acetate promotes regression of cancers and precancerous lesions in the female lower reproductive tracts (ie, cervix and vagina) in the human papillomavirus transgenic mouse model. Our results provide the first experimental evidence that supports the hypothesis that progesterone signaling is inhibitory for cervical carcinogenesis in vivo

センリャク ガクシュウ ニ オケル ケイエイ トップ ノ ヤクワリ ニ ツイテ ノ イチコウサツ ユウリョウ ロウジン ホーム 4 シャ ノ ジレイ ブンセキ オ トオシテ

本論文は， 医療・福祉の市場化が進展している中で， 持続的な成長と存続を図るための経営戦略を展開しながら様々な試行錯誤を積み重ねている有料老人ホームに着目し， 組織学習理論に基づいて事例研究を行ったものである． 有料老人ホームにおける戦略的行動に注目し， 環境変化に適応するためにはどのような戦略を立て， どのように実行すべきかについて， その解を究明するとともに， 戦略学習 （戦略の形成および実行プロセス） における経営トップの果たすべき役割を明らかにするよう努めている． 事例分析では， 各社が単純， 深層， 変革レベルでの様々な学習を繰り返すことによって明確な戦略的違いを形成しており， 各社の経営トップが執事， 教師， 設計者の役割を果たしながら戦略学習を促進していることが明らかになった． さらに， 本稿では， 戦略学習における経営トップの新たな役割として， 芸術家的な役割を提示し， その仮説モデルを構築している

Clinical significance of B cell-activating factor (BAFF) and a proliferation-inducing ligand (APRIL) in acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation

proliferation. We evaluated the correlation between serum concentration of BAFF or APRIL and severity of acute graft-versus-host disease (GVHD). METHODS: Fifteen patients who received allogeneic hematopoietic stem transplantation for leukemia and developed acute GVHD were enrolled. We determined serum concentrations of BAFF and APRIL at the onset of the first clinical manifestation of GVHD by enzyme-linked immunosorbent assay. RESULTS: Nine patients had grade 2 acute GVHD, and 6 had grade 3-4 acute GVHD. The BAFF serum concentration was higher in patients with grade 3-4 acute GVHD (1,093.42 in grade 2 vs. 2,171.99 pg/mL in grade 3-4), although the difference was not significant (P=0.077). However, the ratio of BAFF serum concentration to absolute lymphocyte count (ALC) (BAFF/ALC) was significantly higher in patients with grade 3-4 acute GVHD (P=0.045). The APRIL serum concentration and APRIL/ALC ratio showed similar results (P=0.077 and P=0.013, respectively). CONCLUSION: Patients with grade 3-4 acute GVHD had higher BAFF/ALC and APRIL/ALC ratios than patients with grade 2 acute GVHD. These findings suggest that B cells might play an important role in the development of acute GVHD, and that the BAFF and APRIL concentrations in serum might be significant predictive factors for estimating the severity of acute GVHD. Their clinical significance should be further evaluated in a larger patient populationope