The Design and Implementation of Collaborative Filtering in Data Mining

Data mining is the process of discovering explicit knowledge from large amounts of data stored in database, data warehouse or other repositories. There have been many studies about models of data mining such as association rule, sequential pattern and so on. Collaborative filtering is one of data mining models. In this paper, we propose two approaches to solving the mining process of collaborative filtering. Finally, collaborative filtering mining is applied to Knowledge Management system

Effects of job rotation and role stress among nurses on job satisfaction and organizational commitment

<p>Abstract</p> <p>Background</p> <p>The motivation for this study was to investigate how role stress among nurses could affect their job satisfaction and organizational commitment, and whether the job rotation system might encourage nurses to understand, relate to and share the vision of the organization, consequently increasing their job satisfaction and stimulating them to willingly remain in their jobs and commit themselves to the organization. Despite the fact that there have been plenty of studies on job satisfaction, none was specifically addressed to integrate the relational model of job rotation, role stress, job satisfaction, and organizational commitment among nurses.</p> <p>Methods</p> <p>With top managerial hospital administration's consent, questionnaires were only distributed to those nurses who had had job rotation experience. 650 copies of the questionnaire in two large and influential hospitals in southern Taiwan were distributed, among which 532 valid copies were retrieved with a response rate of 81.8%. Finally, the SPSS 11.0 and LISREL 8.54 (Linear Structural Relationship Model) statistical software packages were used for data analysis and processing.</p> <p>Results</p> <p>According to the nurses' views, the findings are as follows: (1) job rotation among nurses could have an effect on their job satisfaction; (2) job rotation could have an effect on organizational commitment; (3) job satisfaction could have a positive effect on organizational commitment; (4) role stress among nurses could have a negative effect on their job satisfaction; and (5) role stress could have a negative effect on their organizational commitment.</p> <p>Conclusion</p> <p>As a practical and excellent strategy for manpower utilization, a hospital could promote the benefits of job rotation to both individuals and the hospital while implementing job rotation periodically and fairly. And when a medical organization attempts to enhance nurses' commitment to the organization, the findings suggest that reduction of role ambiguity in role stress has the best effect on enhancing nurses' organizational commitment. The ultimate goal is to increase nurses' job satisfaction and encourage them to stay in their career. This would avoid the vicious circle of high turnover, which is wasteful of the organization's valuable human resources.</p

MIMO Evolution toward 6G: End-User-Centric Collaborative MIMO

In 6G, the trend of transitioning from massive antenna elements to even more massive ones is continued. However, installing additional antennas in the limited space of user equipment (UE) is challenging, resulting in limited capacity scaling gain for end users, despite network side support for increasing numbers of antennas. To address this issue, we propose an end-user-centric collaborative MIMO (UE-CoMIMO) framework that groups several fixed or portable devices to provide a virtual abundance of antennas. This article outlines how advanced L1 relays and conventional relays enable device collaboration to offer diversity, rank, and localization enhancements. We demonstrate through system-level simulations how the UE-CoMIMO approaches lead to significant performance gains. Lastly, we discuss necessary research efforts to make UE-CoMIMO available for 6G and future research directions.Comment: 7 pages, 5 figures, 1 table. This work has been accepted in IEEE Communications Magazin

False Data Injection Attack on Atmospheric Electric Field in Thunderstorm Warning

Thunderstorm warning plays an important role in lightning prevention and disaster mitigation. In practical applications, thunderstorm warning system is also vulnerable to attacks, such as False Data Injection Attack (FDIA). However, there is a lack of research on False Data Injection Attack for thunderstorm warning. Therefore, this paper put forwards a FDIA method based on principal component analysis (PCA) for atmospheric electric field (AEF), which is usually used for thunderstorm warning. In the FDIA scenario, the AEF-based thunderstorm warning algorithm is also introduced with electric field differential index (EFDI). Finally, experiments are conducted based on AEF data collected by an atmospheric electric field meter (AEFM) about the real thunderstorm. The experimental results show that FDIA seriously interferes with the results of the AEF-based thunderstorm warning

Increased spinal prodynorphin gene expression in reinflammation-associated hyperalgesia after neonatal inflammatory insult

<p>Abstract</p> <p>Background</p> <p>Neuroplasticity induced by neonatal inflammation is the consequence of a combination of activity-dependent changes in neurons. We investigated neuronal sensitivity to a noxious stimulus in a rat model of neonatal hind-paw peripheral inflammation and assessed changes in pain behaviour at the physiological and molecular levels after peripheral reinflammation in adulthood.</p> <p>Results</p> <p>A decrease in paw withdrawal latency (PWL) after a heat stimulus was documented in rats that received inflammatory injections in their left hind paws on postnatal day one (P1) and a reinflammation stimulus at postnatal 6-8 weeks of age, compared with normal rats. An increase in the expression of the prodynorphin (<it>proDYN</it>) gene was noted after reinflammation in the spinal cord ipsilateral to the afferents of the neonatally treated hind paw. The involvement of the activation of extracellular signal-regulated kinases (ERK) in peripheral inflammatory pain hypersensitivity was evidenced evident by the increase in phospho-ERK (pERK) activity after reinflammation.</p> <p>Conclusions</p> <p>Our results indicate that peripheral inflammation in neonates can permanently alter the pain processing pathway during the subsequent sensory stimulation of the region. Elucidation of the mechanism underlying the developing pain circuitry will provide new insights into the understanding of the early pain behaviours and the subsequent adaptation to pain.</p

A Bilevel Optimization Model Based on Edge Computing for Microgrid

With the continuous progress of renewable energy technology and the large-scale construction of microgrids, the architecture of power systems is becoming increasingly complex and huge. In order to achieve efficient and low-delay data processing and meet the needs of smart grid users, emerging smart energy systems are often deployed at the edge of the power grid, and edge computing modules are integrated into the microgrids system, so as to realize the cost-optimal control decision of the microgrids under the condition of load balancing. Therefore, this paper presents a bilevel optimization control model, which is divided into an upper-level optimal control module and a lower-level optimal control module. The purpose of the two-layer optimization modules is to optimize the cost of the power distribution of microgrids. The function of the upper-level optimal control module is to set decision variables for the lower-level module, while the function of the lower-level module is to find the optimal solution by mathematical methods on the basis of the upper-level and then feed back the optimal solution to the upper-layer. The upper-level and lower-level modules affect system decisions together. Finally, the feasibility of the bilevel optimization model is demonstrated by experiments

An acoustic detection dataset of birds (Aves) in montane forests using a deep learning approach

Long-term monitoring is needed to understand the statuses and trends of wildlife communities in montane forests, such as those in Yushan National Park (YSNP), Taiwan. Integrating passive acoustic monitoring (PAM) with an automated sound identifier, a long-term biodiversity monitoring project containing six PAM stations, was launched in YSNP in January 2020 and is currently ongoing. SILIC, an automated wildlife sound identification model, was used to extract sounds and species information from the recordings collected. Animal vocal activity can reflect their breeding status, behaviour, population, movement and distribution, which may be affected by factors, such as habitat loss, climate change and human activity. This massive amount of wildlife vocalisation dataset can provide essential information for the National Park's headquarters on resource management and decision-making. It can also be valuable for those studying the effects of climate change on animal distribution and behaviour at a regional or global scale.To our best knowledge, this is the first open-access dataset with species occurrence data extracted from sounds in soundscape recordings by artificial intelligence. We obtained seven bird species for the first release, with more bird species and other taxa, such as mammals and frogs, to be updated annually. Raw recordings containing over 1.7 million one-minute recordings collected between the years 2020 and 2021 were analysed and SILIC identified 6,243,820 vocalisations of seven bird species in 439,275 recordings. The automatic detection had a precision of 0.95 and the recall ranged from 0.48 to 0.80. In terms of the balance between precision and recall, we prioritised increasing precision over recall in order to minimise false positive detections. In this dataset, we summarised the count of vocalisations detected per sound class per recording which resulted in 802,670 occurrence records. Unlike data from traditional human observation methods, the number of observations in the Darwin Core &quot;organismQuantity&quot; column refers to the number of vocalisations detected for a specific bird species and cannot be directly linked to the number of individuals.We expect our dataset will be able to help fill the data gaps of fine-scale avian temporal activity patterns in montane forests and contribute to studies concerning the impacts of climate change on montane forest ecosystems on regional or global scales

Apoptosis induction in BEFV-infected Vero and MDBK cells through Src-dependent JNK activation regulates caspase-3 and mitochondria pathways

Our previous report demonstrated that bovine ephemeral fever virus (BEFV)-infected cultured cells could induce caspase-dependent apoptosis. This study aims to further elucidate how BEFV activates the caspase cascade in bovine cells. BEFV replicated and induced apoptosis in Vero and Madin-Darby bovine kidney (MDBK) cells, and a kinetic study showed a higher efficiency of replication and a greater apoptosis induction ability of BEFV in Vero cells. Src and c-Jun N-terminal kinase (JNK) inhibitor, but not extracellular signal-regulated kinase (ERK) or p38 inhibitor, alleviated BEFV-mediated cytopathic effect and apoptosis. In BEFV-infected Vero and MDBK cells, BEFV directly induced Src tyrosine-418 phosphorylation and JNK phosphorylation and kinase activity, which was inhibited specifically by SU6656 and SP600125, respectively. The caspase cascade and its downstream effectors, Poly (ADP-ribose) polymerase (PARP) and DFF45, were also activated simultaneously upon BEFV infection. In addition, cytochrome c, but not Smac/DIABLO, was released gradually from mitochondria after BEFV infection. SU6656 suppressed Src, JNK, and caspase-3 and -9 activation, as well as PARP and DFF45 cleavage; SP600125 reduced JNK and caspase-3 and -9 activation, as well as PARP and DFF45 cleavage. Taken together, these results strongly support the hypothesis that a Src-dependent JNK signaling pathway plays a key role in BEFV-induced apoptosis. The molecular mechanism identified in our study may provide useful information for the treatment of BEFV