Strengthening Network Ties through Mentoring of Alienated Personnel

This study examines the social network aspects of mentoring in order to suggest ways to manage alienated public employees. It also explores the impact of mentoring that requires closer relationships between mentors and mentees to develop network ties. Networks of trust, respect, and friendship among soldiers in four barracks of the Republic of Korea Army (two experimental groups and two control groups) were measured using a social network survey. Alienated soldiers in the experimental groups were mentored by fellow soldiers with stronger ties, while no such mentoring was conducted in the control groups. After three months of mentoring, changes in network strengths were found among alienated soldiers in the experimental groups, while no significant changes were found among alienated soldiers in the control groups. This study is expected to contribute to human resource management by suggesting ways to strengthen the network ties of alienated personnel through mentoring

Extending Data Quality Management for Smart Connected Product Operations

Smart connected product (SCP) operation embodies the concept of the internet of things (IoT). To increase the probability of success of SCP operations for customers, the high quality of the IoT data across operations is imperative. IoT data go beyond sensor data, as integrate some other various type of data such as timestamps, device metadata, business data, and external data through SCP operation processes. Therefore, traditional data-centric approaches that analyze sensor data and correct their errors are not enough to preserve, in long-term basis, adequate levels of quality of IoT data. This research provides and alternative framework of data quality management as a process-centric approach to improve the quality of IoT data. The proposed framework extends the process reference model (PRM) for data quality management (DQM) defined in ISO 8000-61, and tailored to fully adapt to the special requirements of the IoT data management. These involve several adaptations: first, the scope of the SCP operations for data quality management is determined, and the processes required for SCP operations are defined following the process description format of ISO 8000-61. Second, the relationship between the processes and the structure of the processes in the technology stack of the SCP operations are described to cover the actual nature of the IoT data flows. Finally, a new IoT DQM-PRM is proposed by integrating the processes for the SCP operations with DQM-PRM. When these processes are executed in the organization, the quality of IoT data composed of data of various types can be continuously improved and the utilization rate of SCP operations is expected to increase.We would like to acknowledge the financial support provided by the Korea-Spain joint R&D program of MOTIE (Project No. N0002610), CDTI (DQIoT, Project No. INNO-20171086) and EUREKA (Project No. E!11737). Also, we would like to acknowledge the ECLIPSE (RTI2018-094283-B-C31) and GEMA (SBPLY/17/180501/000293) projects

AIM: Symmetric Primitive for Shorter Signatures with Stronger Security (Full Version)

Post-quantum signature schemes based on the MPC-in-the-Head (MPCitH) paradigm are recently attracting significant attention as their security solely depends on the one-wayness of the underlying primitive, providing diversity for the hardness assumption in post-quantum cryptography. Recent MPCitH-friendly ciphers have been designed using simple algebraic S-boxes operating on a large field in order to improve the performance of the resulting signature schemes. Due to their simple algebraic structures, their security against algebraic attacks should be comprehensively studied. In this paper, we refine algebraic cryptanalysis of power mapping based S-boxes over binary extension fields, and cryptographic primitives based on such S-boxes. In particular, for the Gröbner basis attack over $\mathbb{F}_2$, we experimentally show that the exact number of Boolean quadratic equations obtained from the underlying S-boxes is critical to correctly estimate the theoretic complexity based on the degree of regularity. Similarly, it turns out that the XL attack might be faster when all possible quadratic equations are found and used from the S-boxes. This refined cryptanalysis leads to more precise algebraic analysis of cryptographic primitives based on algebraic S-boxes. Considering the refined algebraic cryptanalysis, we propose a new one-way function, dubbed $\mathsf{AIM}$, as an MPCitH-friendly symmetric primitive with high resistance to algebraic attacks. The security of $\mathsf{AIM}$ is comprehensively analyzed with respect to algebraic, statistical, quantum, and generic attacks. $\mathsf{AIM}$ is combined with the BN++ proof system, yielding a new signature scheme, dubbed $\mathsf{AIMer}$. Our implementation shows that $\mathsf{AIMer}$ outperforms existing signature schemes based on symmetric primitives in terms of signature size and signing time

Construction Site Safety Management: A Computer Vision and Deep Learning Approach

In this study, we used image recognition technology to explore different ways to improve the safety of construction workers. Three object recognition scenarios were designed for safety at a construction site, and a corresponding object recognition model was developed for each scenario. The first object recognition model checks whether there are construction workers at the site. The second object recognition model assesses the risk of falling (falling off a structure or falling down) when working at an elevated position. The third object recognition model determines whether the workers are appropriately wearing safety helmets and vests. These three models were newly created using the image data collected from the construction sites and synthetic image data collected from the virtual environment based on transfer learning. In particular, we verified an artificial intelligence model based on a virtual environment in this study. Thus, simulating and performing tests on worker falls and fall injuries, which are difficult to re-enact by humans, are efficient algorithm verification methods. The verification and synthesis data acquisition method based on a virtual environment is one of the main contributions of this study. This paper describes the overall application development approach, including the structure and method used to collect the construction site image data, structure of the training image dataset, image dataset augmentation method, and the artificial intelligence backbone model applied for transfer learning

The interplay of semantic and syntactic processing across hemispheres

Abstract The current study investigated the hemispheric dynamics underlying semantic and syntactic priming in lexical decision tasks. Utilizing primed-lateralized paradigms, we observed a distinct pattern of semantic priming contingent on the priming hemisphere. The right hemisphere (RH) exhibited robust semantic priming irrespective of syntactic congruency between prime and target, underscoring its proclivity for semantic processing. Conversely, the left hemisphere (LH) demonstrated slower response times for semantically congruent yet syntactically incongruent word pairs, highlighting its syntactic processing specialization. Additionally, nonword data revealed a hemispheric divergence in syntactic processing, with the LH showing significant intrahemispheric syntactic priming. These findings illuminate the intrinsic hemispheric specializations for semantic and syntactic processing, offering empirical support for serial processing models. The study advances our understanding of the complex interplay between semantic and syntactic factors in hemispheric interactions

Efficient Implementations of Rainbow and UOV using AVX2

A signature scheme based on multivariate quadratic equations, Rainbow, was selected as one of digital signature finalists for NIST Post-Quantum Cryptography Standardization Round 3. In this paper, we provide efficient implementations of Rainbow and UOV using the AVX2 instruction set. These efficient implementations include several optimizations for signing to accelerate solving linear systems and the Vinegar value substitution. We propose a new block matrix inversion (BMI) method using the Lower-Diagonal-Upper decomposition of blocks matrices based on the Schur complement that accelerates solving linear systems. Compared to UOV implemented with Gaussian elimination, our implementations with the BMI result in speedups of 12.36%, 24.3%, and 34% for signing at security categories I, III, and V, respectively. Compared to Rainbow implemented with Gaussian elimination, our implementations with the BMI result in speedups of 16.13% and 20.73% at the security categories III and V, respectively. We show that precomputation for the Vinegar value substitution and solving linear systems dramatically improve their signing. UOV with precomputation is 16.9 times, 35.5 times, and 62.8 times faster than UOV without precomputation at the three security categories, respectively. Rainbow with precomputation is 2.1 times, 2.2 times, and 2.8 times faster than Rainbow without precomputation at the three security categories, respectively. We then investigate resilience against leakage or reuse of the precomputed values in UOV and Rainbow to use the precomputation securely: leakage or reuse of the precomputed values leads to their full secret key recoveries in polynomial-time

Novel Key Recovery Attack on Secure ECDSA Implementation by Exploiting Collisions between Unknown Entries

In this paper, we propose a novel key recovery attack against secure ECDSA signature generation employing regular table-based scalar multiplication. Our attack exploits novel leakage, denoted by collision information, which can be constructed by iteratively determining whether two entries loaded from the table are the same or not through side-channel collision analysis. Without knowing the actual value of the table entries, an adversary can recover the private key of ECDSA by finding the condition for which several nonces are linearly dependent by exploiting only the collision information. We show that this condition can be satisfied practically with a reasonable number of digital signatures and corresponding traces. Furthermore, we also show that all entries in the pre-computation table can be recovered using the recovered private key and a sufficient number of digital signatures based on the collision information. As case studies, we find that fixed-base comb and T_SM scalar multiplication are vulnerable to our attack. Finally, we verify that our attack is a real threat by conducting an experiment with power consumption traces acquired during T_SM scalar multiplication operations on an ARM Cortex-M based microcontroller. We also provide the details for validation process

Lateralized Displays Reveal the Perceptual Locus of the Syllable Transposition Effect in Korean

Studies of letter transposition effects in alphabetic scripts provide compelling evidence that letter position is encoded flexibly during reading, potentially during an early, perceptual stage of visual word recognition. Recent studies additionally suggest similar flexibility in the spatial encoding of syllabic information in the Korean Hangul script. With the present research, we conducted two experiments to investigate the locus of this syllabic transposition effect. In Experiment 1, lexical decisions for foveal stimulus presentations were less accurate and slower for four-syllable nonwords created by transposing two syllables in a base word as compared to control nonwords, replicating prior evidence for a transposed syllable effect in Korean word recognition. In Experiment 2, the same stimuli were presented to the right and left visual hemifields (i.e., RVF and LVF), which project both unilaterally and contralaterally to each participant’s left and right cerebral hemisphere (i.e., LH and RH) respectively, using lateralized stimulus displays. Lexical decisions revealed a syllable transposition effect in the accuracy and latency of lexical decisions for both RVF and LVF presentations. However, response times for correct responses were longer in the LVF, and therefore the RH, as compared to the RVF/LH. As the LVF/RH appears to be selectively sensitive to the visual-perceptual attributes of words, the findings suggest that this syllable transposition effect partly finds its locus within a perceptual stage of processing. We discuss these findings in relation to current models of the spatial encoding of orthographic information during visual word recognition and accounts of visual word recognition in Korean.</p

IDH2 Deficiency Aggravates Fructose-Induced NAFLD by Modulating Hepatic Fatty Acid Metabolism and Activating Inflammatory Signaling in Female Mice

Fructose is a strong risk factor for non-alcoholic fatty liver disease (NAFLD), resulting from the disruption of redox systems by excessive reactive oxygen species production in the liver cells. Of note, recent epidemiological studies indicated that women are more prone to developing metabolic syndrome in response to fructose-sweetened beverages. Hence, we examined whether disruption of the redox system through a deletion of NADPH supplying mitochondrial enzyme, NADP+-dependent isocitrate dehydrogenase (IDH2), exacerbates fructose-induced NAFLD conditions in C57BL/6 female mice. Wild-type (WT) and IDH2 knockout (KO) mice were treated with either water or 34% fructose water over six weeks. NAFLD phenotypes and key proteins and mRNAs involved in the inflammatory pathway (e.g., NF-&kappa;B p65 and IL-1&beta;) were assessed. Hepatic lipid accumulation was significantly increased in IDH2 KO mice fed fructose compared to the WT counterpart. Neutrophil infiltration was observed only in IDH2 KO mice fed fructose. Furthermore, phosphorylation of NF-&kappa;B p65 and expression of IL-1&beta; was remarkably upregulated in IDH2 KO mice fed fructose, and expression of I&kappa;B&alpha; was decreased by fructose treatment in both WT and IDH2 KO groups. For the first time, we report our novel findings that IDH2 KO female mice may be more susceptible to fructose-induced NAFLD and the associated inflammatory response, suggesting a mechanistic role of IDH2 in metabolic diseases