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

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

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

General Bootstrapping Approach for RLWE-based Homomorphic Encryption

We propose a new bootstrapping approach that works for all three Brakerski-Gentry-Vaikuntanathan (BGV), Brakerski/Fan-Vercauteren (BFV), and Cheon-Kim-Kim-Song (CKKS) schemes. This approach adopts a blind rotation technique from FHEW-type schemes. For BGV and BFV, our bootstrapping does not have any restrictions on plaintext modulus unlike typical cases of the previous methods. For CKKS, our approach introduces an error comparable to a rescaling error which enables more than 70 bits of precision after bootstrapping while consuming only 1-2 levels. Due to the high precision of the proposed bootstrapping algorithm, it is the first bootstrapping resistant to the security vulnerability of CKKS found by Li and Micciancio (Eurocrypt 2021). In addition, we introduce methods to reduce the size of public keys required for blind rotations generated by a secret key holder

RECIPE: How to Integrate ChatGPT into EFL Writing Education

The integration of generative AI in the field of education is actively being explored. In particular, ChatGPT has garnered significant interest, offering an opportunity to examine its effectiveness in English as a foreign language (EFL) education. To address this need, we present a novel learning platform called RECIPE (Revising an Essay with ChatGPT on an Interactive Platform for EFL learners). Our platform features two types of prompts that facilitate conversations between ChatGPT and students: (1) a hidden prompt for ChatGPT to take an EFL teacher role and (2) an open prompt for students to initiate a dialogue with a self-written summary of what they have learned. We deployed this platform for 213 undergraduate and graduate students enrolled in EFL writing courses and seven instructors. For this study, we collect students' interaction data from RECIPE, including students' perceptions and usage of the platform, and user scenarios are examined with the data. We also conduct a focus group interview with six students and an individual interview with one EFL instructor to explore design opportunities for leveraging generative AI models in the field of EFL education