bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of COBIT5 as a Reference for Quality Service Quality Improvement
Authors: Arthananda Kevin Pratama , Wella Wella
Published: June 2022

Bank Central Asia Tbk. is the largest private bank company in Indonesia, which is now owned by one of the largest cigarette group companies in the world, namely Djarum. PT. Bank Central Asia Tbk. make various efforts to improve the quality of service quality by setting a standard and policy. One of them is the determination of ITIL V3 standardization, which covers the entire IT Service process. ITIL V3 is a series of concepts and techniques for infrastructure management, development, and information technology operations. These efforts were made to meet the ISO 20000 standardization to obtain ISO 20000 certification in 2011. However, PT Bank Central Asia Tbk wants to continue to improve the quality of IT services for the better, therefore PT Bank Central Asia Tbk. chose to use the COBIT 5 framework as a method of measuring the quality of IT service quality, especially in the field of IT Service Management (ITSM) in the DSS02 (Manage Service requests and Incidents) and DSS03 (Manage Problems) processes. The result of this research is that the Capability Level of the DSS02 and DSS03 processes is known at PT Bank Central Asia Tbk. the current condition is level 3 (Established Process), while the target level to be achieved is level 4 (Predictable Process). So that to reach the next level, PT Bank Central Asia is expected to have followed the recommendations for improvement given.
Toward National One Health Data: Reconfiguring Local Health Information Systems through Enterprise Architecture
Authors: Yovadiani Amalia , Ramadani Luthfi , Dewi Fitriyana
Published: June 2022

Indonesian government is currently on the course of nationwide digital transformation, manifested through its ‘One-Data Policy’ recently introduced by top-level government. The initiative also includes the country’s health information systems (HIS) for which various technological choices are under consideration to be implemented. However, such a sound and ambitious initiative often overlook the configurational outlook of local systems where the data is created and aggregated to the national system. This study addresses this issue by exploring the issues pertaining to local HIS and developing its enterprise architecture to reconfigure the existing arrangement of the systems. Using a case study of Palangka Raya municipal health government, this study contributes to this current important agenda by delineating the complexity that occurs at local HIS and proposing a set of enterprise architecture artifacts required toward Indonesian one health data.
COBIT 5: How Capable PT GTI Governing Innovation, Human Resource, and Knowledge Aspect?
Authors: Sudarnoto Darwin Aridarno , Wella Wella , Desanti Ririn Ikana
Published: June 2022

The performance of information technology governance by PT GTI has not been optimal and there has never been a measurement of information technology governance capability. Based on these problems, it is necessary to measure the capability of information technology governance and make an appropriate information technology management recommendation that can be used as a guide—the measurement of the COBIT 5.0 framework. The data collection method consisted of observation, questionnaires, and interviews. The data collection results will produce findings, impacts, and recommendations for PT GTI. Measuring the capability of information technology governance used includes Planning, Preparation, Implementation, and Measurement Reporting. The study focused on 3 IT processes and obtained the following capability level results: APO04 Manage Innovation got a score of 78.4% and stopped at level 3, APO07 Managed Human Resource with a score of 81.07% and stopped at level 1, and BAI08 Manage Knowledge got to score 61% and stop at level 2.
Analysis and Design of Web-Based Information System for Church Congregations Case Study: Church BNKP Pewarta
Authors: Wiratama Jansen , Desanti Ririn Ikana
Published: June 2022

During the COVID-19 pandemic, worship activities at the Church were limited. The lack of preparation and data collection on the congregations who visit to worship regularly every week increases the risk of transmission. It needs to be minimized and anticipated. One effort that can be made to reduce this risk is to collect data on the health condition of the congregation who will attend worship. The data collection process is recorded in writing on the attendance list. This requires an iterative approach to be updated and creates a build-up to the attendance record. In addition, media information about the BNKP Pewarta Church activities is not yet available. To overcome this problem, a congregational data collection information system is needed to store congregation data and provide general information about the BNKP Pewarta Church. In designing this Congregation Data Collection Information System, the design method used is the Web Development Life Cycle (WDLC). This information system website design can store Church congregation data and present general Church information.
Foreign ownership, tax preference and firm performance
Authors: Su Wunhong , Song Xiaobao , Guo Chun
Published: June 2022

Continuingly deepening reform, upgrading and transforming industries and attracting investment from foreign-funded firms become important measures to boost China's economic reform. Chinese government adopts various preferential tax policies for different industries since the beginning of the implementation of reform and opening-up. This study employs A-share listed firms from 2011 to 2017 as the sample to investigate the relation between foreign ownership, tax preference and firm performance. The results show that tax preference has positive relation with the investment of foreign-funded firms, and the investment and shareholding of foreign-funded firms have positive impact on the firm performance.
Enterprise Risk Management and Company’s Performance
Authors: Rahman Md. Jahidur , Kennedyd Sarmann I , Chen Zhenkui
Published: June 2022

The purpose of this study is to investigate the relationship between enterprise risk management (ERM) and company performance in the Chinese commercial industry. An enterprise risk management index was constructed from a strategic and operational point of view to assess the ERM level of Chinese commercial companies. ERM is also known as an integrated, comprehensive, and strategic management using the Simona-lulia (2014) approach. The study used a sample of 175 listed Chinese commercial companies from 2009 to 2018, and found that the imperfect ERM in the Chinese commercial industry as a whole had a negative effect on the performance of the companies. It also found that the size of the company, financial leverage, and intellectual capital can influence enterprise risk management. These results established a strong link between enterprise risk management and company performance in the Chinese commercial industry.
The effect of corporate social responsibility on debt finance: The moderating effect of accounting conservatism
Authors: Ali Karim Mansour , Abdel ghaffar Emad sayed
Published: June 2022

This study aims to investigate the impact of corporate social responsibility (CSR) practices on the debt finance (DF) of Egyptian firms, as well as examine the moderating role of accounting conservatism (AC) on this relationship. The sample of the study consists of 120 listed Egyptian firms from 2012 to 2019 with overall observations of 960, the data were processed using the panel corrected standards errors (PCSE) and the generalized least squares (GLS). The results reveal that CSR practices have a negative effect on the DF of listed Egyptian firms, this means that listed firms that engage in CSR practices have less ability to obtain DF than non-CSR firms. Also, the results indicate that the negative effect of CSR practices on DF is more pronounced in firms that have a high conservatism. The results of this study have some essential implications, as CSR practices are crucial for stakeholders such as regulators, investors, and credit providers. Besides, this study contributes to testing some factors that affect firms' ability to obtain DF in one of the emerging countries such as Egypt.

Keywords Corporate social responsibility, Debt finance, Accounting conservatism, Panel data, Egypt
Nutritional and anti-gastro ulcerative role of the gum Arabic (Acacia senegal L.) compared to a reference drug
Authors: Khairullah Mohammed Nameer , Yousif Jameel Qaswaa , Abdullah Ajeel Mohammed
Published: June 2022

Background: As alcohol consumption increases, ethanol impacts ulcers as a factor that causes stomach mucosal invasion, which leads to stomach ulcers. Alcohol damages the stomach through a number of processes, including increased gastric secretion, the release of pro-inflammatory cytokines, and ethanol induces a variety of pathogenic events as it is associated with the formation of stomach ulcers.Objective: The goal of this study was to see if gum Arabic as a functional food could protect albino rats against ethanol-induced stomach damage.Materials and Methods: Six groups of 30 female albino rats were formed: normal control, ulcer control, omeprazole + ethanol, and groups 4, 5, and 6, which were given GA at 7.5, 12, 25 g/ kg/ day (bw), then lab rat were given 5 mL/kg /day (bw) ethanol orally for 30 days to cause stomach mucosal damage.Results: GA suppressed gastric inflammation by lowering TNF-α and IL-6 levels while increasing IL-10 levels. GA also improved HDL, total protein, albumin, and globulin levels while lowering cholesterol, triglycerides, VLDL-C, LDL-C, and phospholipids.Conclusion: These findings demonstrate that GA plays a protective role toward gastric mucosal injury in rats induced by ethanol, which in turn reduced the inflammatory response, and significantly reduced the hemorrhagic gastric lesions and the pH of the gastric contents. Keywords: Functional food, Alcoholic, polysaccharides, soluble fiber, tumor necrosis factor alpha, oxidative stress
The Impact of Agitation in Dementia on Caregivers: A Real-World Survey
Authors: Schein Jeff , Houle Christy R. , Urganus Annette L. , Jones Eddie , Pike James , Husbands Joseph , Willey Cynthia J.
Published: June 2022

Background: Dementia patients frequently depend on caregivers. Agitation is a common behavioral dementia symptom particularly burdensome to patients and caregivers. Objective: To assess the association of agitation severity with non-professional caregiver hours, burden, health status, and productivity. Secondarily, to assess the association of agitation severity with these outcomes for patients receiving remote (not living with the patient) and proximate (living with the patient) caregiving. Methods: A retrospective analysis of physician and non-professional caregiver-reported data from a US point-in-time survey. Patients were aged ≥50 years, with early cognitive impairment or dementia. Regression analyses compared outcomes by agitation severity; covariates included age, sex, and clinical characteristics. Results: Data were included for 1,349 patients (non-agitated n = 656, agitated n = 693; no care n = 305, remote care n = 248, proximate care n = 691; unknown care n = 105). Greater agitation was significantly associated (p < 0.05) in all caregivers with increasing: Zarit Burden Interview (ZBI) Total Caregiver Burden, Personal Strain, Role Strain, and Guilt; Work Productivity and Activity Index (WPAI) presenteeism, overall work impairment, and total activity impairment. Higher ZBI Total Caregiver Burden, Personal Strain, and Role Strain were associated with greater agitation in proximate caregivers and higher ZBI Guilt associated with greater agitation in remote caregivers (p < 0.05). Higher WPAI presenteeism and total activity impairment were associated (p < 0.05) with greater agitation in proximate caregivers. Caregiving hours increased with increasing agitation for proximate caregiving (p = 0.001). Conclusion: Greater agitation severity was associated with higher caregiver burden and lower productivity, with higher indirect costs a likely outcome of agitation.
Metabolic Reprogramming of Microglia Enhances Proinflammatory Cytokine Release through EphA2/p38 MAPK Pathway in Alzheimer’s Disease
Authors: Ma Xiaowei , Zhang Yizhou , Gou Dongyun , Ma Jingle , Du Juan , Wang Chang , Li Sha , Cui Huixian
Published: June 2022

Background: The activation of microglia and neuroinflammation has been implicated in the pathogenesis of Alzheimer’s disease (AD), but the exact roles of microglia and the underlying mechanisms remain unclear. Objective: To clarify how the metabolic reprogramming of microglia induce by amyloid-β (Aβ)1-42 to affect the release of proinflammatory cytokines in AD. Methods: MTS assay was used to detect the viability of BV2 cells treated with different concentrations of Aβ1-42 for different periods of time. The expression levels of proinflammatory cytokines were determined by qRT-PCR and western blot assay in BV2 cells and hippocampus of mice. RNA sequencing was applied to evaluate the gene expression profiles in response to HK2 knockdown in BV2 cells treated with Aβ1-42. Results: Low concentrations of Aβ1-42 increased the viability of BV2 cells and promoted the release of proinflammatory cytokines, and this process is accompanied by increased glycolysis. Inhibition of glycolysis significantly downregulated the release of proinflammatory cytokines in BV2 cells and hippocampus of mice treated with Aβ1-42. The results of RNA sequencing revealed the expression of chemokine ligand 2 (Cxcl2) and ephrin receptor tyrosine kinase A2 (EphA2) were significantly downregulated when knocked down HK2 in BV2 cells. Subsequently, the expression of proinflammatory cytokines was downregulated in BV2 cell after knocking down EphA2. Conclusion: This study demonstrated that EphA2/p38 MAPK pathway is involved the release of proinflammatory cytokines in microglia induced by Aβ1-42 in AD, which is accompanied by metabolic reprogramming from oxidative phosphorylation (OXPHOS) to glycolysis.
Demonstration of Clinical Meaningfulness of the Integrated Alzheimer’s Disease Rating Scale (iADRS): Association Between Change in iADRS Scores and Patient and Caregiver Health Outcomes
Authors: Wessels Alette M. , Belger Mark , Johnston Joseph A. , Yu Youying , Rentz Dorene M. , Dowsett Sherie A. , Chandler Julie
Published: June 2022

Background: The integrated Alzheimer’s Disease Rating Scale (iADRS) is a validated cognitive/functional composite that effectively captures cognitive and functional decline over a broad spectrum of disease. The clinical meaningfulness of change on iADRS can be supported by establishing an association with changes on important health outcome measures. Objective: To evaluate the relationship between change on the iADRS and changes in health outcomes in individuals with mild cognitive impairment (MCI) due to Alzheimer’s disease (AD), or mild or moderate AD dementia using placebo data from four AD clinical trials and data from one AD observational study. Methods: Analysis of covariate (ANCOVA) models were used to estimate the relationship between 18-month change on the iADRS and changes on health outcome measures (related to cost, quality of life, and caregiver burden). The regression coefficients for the iADRS were used to compute impact of natural disease progression and disease-modifying treatment on health outcomes. Additional ANCOVAs were conducted to understand whether cognition and/or function was the underlying explanation of any association between iADRS and health outcome change. Results: Across datasets and disease stages, a worsening on the iADRS was significantly associated with increased societal costs, caregiver burden (time and distress) and worsening in measures of patient quality of life. Conclusion: Decline on the iADRS was associated with worsening in health outcome measures. These findings suggest that the iADRS can be used in clinical trials as a proxy measure of clinically meaningful outcomes of AD progression.
Impact of Climate Change on Biodiversity of Arctic Biome
Authors: Manna Shaheen , Das Dipanwita , Mukherjee Sayantika , Saha Amrita
Published: June 2022

Polar zones are identified as high species richness areas on our planet. In certain regions of the Arctic and Antarctic, air temperatures are observed to be increasing at rates over two times the global average; there are other direct human impacts on polar areas like contamination, over utilisation and advancement. Polar environments and the biodiversity they support are now reacting to this change and it is normal that much more significant effects will happen this century. Intensifying the threat to polar biodiversity is the certainty that numerous polar environments have restricted functional redundancy; in case of the disappearance of a solitary keystone species, they may possibly be exposed to descending impacts and complete biological system rebuilding. Fast environmental change influencing the polar areas will likewise have significant physical and biological outcomes for the remaining part of the planet since the ice-covered Arctic Ocean, the Antarctic landmass, and the globally notable Antarctic Circumpolar Current serves a critical job in controlling the Earth’s environment and sea frameworks. This study concentrates on the contributing variables of environmental change, the impacts of environmental change on the Arctic biome, alongside the impacts of environmental change on the species of the Arctic biome. The outcomes are evident that biodiversity is being affected extremely by environmental change through its degradation of natural surroundings and adverse consequences on species inside.
Research and application of RBF neural network based on modified Levenberg-Marquardt
Authors: Yang Yanxia , Wang Pu , Gao Xuejin , Gao Huihui , Qi Zeyang
Published: June 2022

Radial basis function neural network (RBFNN) has been widely used in industrial process modeling because of its strong approximation ability. However, many existing modeling methods aim at accuracy, but ignore the stability of mode. Therefore, this paper proposes a parameter optimization method of RBF neural network based on modified Levenberg-Marquardt (MLM-RBFNN) to ensure the stability of the network. Firstly, a typical sample mechanism with variance reduction is proposed, which can reduce the error of gradient estimation and use accurate gradient information to guide learning. Secondly, a modified LM optimization algorithm is proposed to optimize the parameters, which not only improve the convergence speed of the network, but also ensure the stability of the model. Finally, a multi-step updating rule based on a typical sample and a single sample is designed, which effectively reduces the sample bias introduced by a single sample. In order to prove the advantages of the MLM-RBFNN method proposed in this paper, experiments are carried out on three benchmark data sets and a practical wastewater treatment process application problem and compared with several existing methods. The results show that the proposed MLM-RBFNN method has good performance in both learning speed and stability.
Pricing and coordination models before and after the integration of omni-channel supply chain by mobile internet
Authors: Hu Rongrong , Yu Yiping
Published: June 2022

Under the omni-channel supply chain by mobile internet, considering both cooperation and competition, this article establishes the pricing model before and after the integration of the omni-channel supply chain by mobile internet and the coordination strategy model under the mobile internet e-commerce logistics cooperation, so as to obtain the wholesale price decision and retail price decision and compensation decisions etc. of supplier S. Furthermore, it can also obtain the corresponding price of retailer T accordingly. Based on the analysis of the above two models, numerical simulations are carried out to compare the optimal decision-making volume before and after the integration of the omni-channel supply chain by mobile internet and the overall profit level. With the help of the numerical simulation results of the above models, the effectiveness of the integration of the omni-channel supply chain by mobile internet is demonstrated which achieving win-win and multi-win in both greater breadth and depth in the supply chain.
Innovation of e-commerce marketing model under the background of big data and artificial intelligence
Authors: Wang Jin
Published: June 2022

With the advent of the era of big data and artificial intelligence, e-commerce enterprises have used a large number of advanced technologies and knowledge management methods to improve work efficiency. In the context of e-commerce, the innovation of enterprise marketing management model has become one of the important contents of the company’s business development in the e-commerce era. Focusing on the core concept of “e-commerce marketing model innovation”, this paper conducts a comprehensive and systematic research on the e-commerce marketing model innovation of enterprise e-commerce, and focuses on the two aspects of e-commerce marketing model innovation and e-commerce model performance evaluation. The purpose of this paper is to understand the importance of innovation factors in the innovation of e-commerce marketing models through questionnaires, so as to provide new ideas for the innovation path of e-commerce marketing models. This paper adopts the questionnaire survey method and data analysis method. According to the survey results, 39, 31, 33, and 35 of the respondents believe that market positioning, business strategy, marketing promotion, and operation management should be prioritized as innovative elements, among which market positioning accounts for a relatively high proportion, followed by operation management. It can be seen that most of the respondents believe that in order to innovate the marketing model of e-commerce, we must start from the aspects of market positioning, business strategy, marketing promotion, and operation management. Combined with the era background and related content of big data and artificial intelligence, this paper studies e-commerce and marketing models, so as to provide new ideas for the innovative path of e-commerce marketing models.
Evaluation of environmental carrying capacity in Xiong’an New Area based on fuzzy comprehensive evaluation method
Authors: Wang Qin , Zhang Yan
Published: June 2022

Through analysis of environmental status of Xiong’an New Area, from three dimensions of water environment, atmospheric environment and geological environment, evaluation index system of environmental carrying capacity of the New Area is preliminarily designed. By using correlation analysis and principal component analysis, 11 basic indexes, including Industrial waste water discharge per 10000 yuan GDP, Comprehensive index of air quality and Average groundwater depth etc., are selected to construct the evaluation index system of environmental carrying capacity of Xiong’an New Area. Based on the fuzzy comprehensive evaluation method, the environmental carrying capacity of the New Area from 2014 to 2018 are evaluated, which provides the basis for protection and utilization of water environment, atmospheric environment and geological environment. The results show that: environmental carrying capacity of the New Area from 2014 to 2018 is 0.2186, 0.2109, 0.2153, 0.2415 and 0.2690 respectively, showing a steady growth trend, mainly as the environmental control of water and atmosphere have been strengthened after 2017.
Risk assessment of the iced transmission line galloping based on fuzzy and cluster algorithms
Authors: Zhang Zhimeng , Liu Jie , Jia Boyan
Published: June 2022

A risk assessment method for transmission line galloping in mountainous areas is proposed based on meteorological conditions, environmental factors and line parameters to timely and effectively assess the risk level of stable and reliable power supply of iced transmission lines in galloping and ensure its normal operation. The galloping amplitude is obtained through cluster algorithm by use of three factors, i.e., icing, line and wind, on the premise of entering the key meteorological factors by fuzzy algorithm to predict the ice thickness. Then the galloping amplitude is used as the risk evaluation standard, and the risk is graded accordingly. Taking the historical galloping monitoring data and meteorological record parameters collected by a certain power grid as samples, upon analysis, it shows that the proposed method can perform more accurate assessment on the risk of transmission lines, reveal the weak links of lines through the risk assessment results, ensure that the risk points or sections can be controlled, provide the decision-making basis and enhanced decision-making support ability for power grid dispatchers and line operators and maintainers, realize the shift from passive hazard prevention to active risk avoidance, effectively improve the ability of power grid to prevent, reduce and cope with severe meteorological hazards, reduce the impact of galloping on the safe operation of power grid, and decrease unnecessary hazards and losses.
Inverse packet fuzzy sets and its characteristics
Authors: Yu Xiuqing , Shen Yanfeng , Li Qiuping
Published: June 2022

Based on inverse packet sets and fuzzy set, the concept of inverse packet fuzzy sets is proposed in this paper by means of introducing dynamic characteristics into a fuzzy set A and improving the fuzzy set A. The inverse packet fuzzy sets is composed of a pair of fuzzy sets generated by the fuzzy set A and has dynamic characteristic and fuzzy characteristic. Furthermore, on certain conditions, it can be restored to the fuzzy set A or the inverse packet sets generated by the Cantor set X=ker⁡(A). As a result, an inverse packet fuzzy sets can be expressed as a series of inverse packet sets by defining its scalar multiplication and its cut sets. Meanwhile some attribute-dependent characteristics of inverse packet fuzzy sets are obtained. The new set model will both enrich the set theory and provide a new basic tool for further practical applications.
A new approach for contact-free detection of human gait based on continuous-wave bio-radar
Authors: Yang Fang , Zhu Mingming , Xia Juanjuan , Lu Guohua
Published: June 2022

The human gait is a complex mechanism by which a variety of muscles and bones must work together in precise coordination to create characteristic human locomotion, which can be used as an identification or clinical gait characterization for detecting pathological conditions. In this paper, a contact-free detection system for human gait based on continuous-wave bio-radar is introduced. Through the spectrum analysis of the radar echo signal generated during human walking, the main frequency of the human gait signal is extracted. Correlation analyses are made with the data obtained from the acceleration sensor. The experimental results show that the bio-radar can detect the gait signal of human walking, and it is consistent with the result of acceleration and video monitoring.
Calculation and simulation of turbocharger flow field and optimization analysis of impeller structure
Authors: Yang Liang , Sheng Lina
Published: June 2022

Aiming at the problem of low efficiency of the JP80D turbocharger rotor system, an optimization analysis of the turbocharger impeller was carried out. Since the second-order critical speed of the rotor system will produce resonance hazards within the system’s operating speed range, the second-order speed needs to be optimized away from the working speed. Therefore, this paper adopts the methods of finite element analysis and Campbell diagram analysis. The three parameters of impeller’s long and short blade combination, blade thickness and blade forward inclination angle are optimized by single-variable progressive optimization method, and then the compressor is simulated by finite element. Finally, by comparing the distribution of the internal flow field characteristics of the compressor, the optimal structural parameter scheme is obtained. By optimizing the impeller to make the second-order speed far away from the working speed, the internal flow field is in an excellent working state. It greatly improves the unbalanced performance of the rotor system, and avoids the problem of low efficiency due to basic excitation and unbalance.
Uncertainty measurement for probabilistic set-valued data: Gaussian kernel method
Authors: Lian Wenwu
Published: June 2022

The uncertainty of information plays an important role in practical applications. Uncertainty measurement (UM) can help us in disclosing the substantive characteristics of information. Probabilistic set-valued data is an important class of data in machine learning. UM for probabilistic set-valued data is worth studying. This paper measures the uncertainty of a probability set-valued information system (PSVIS) by means of its information structures based on Gaussian kernel method. According to Bhattacharyya distance, the distance between objects in each subsystem of a PSVIS is first built. Then, the fuzzy Tcos-equivalence relations in a PSVIS by using Gaussian kernel method are obtained. Next, information structures in a PSVIS are defined. Moreover, dependence between information structures is investigated by using the inclusion degree. As an application for the information structures, UM in a PSVIS is investigated. Finally, to evaluate the performance of the investigated measures, effectiveness analysis is performed from dispersion analysis, correlation analysis, and analysis of variance and post-hoc test.
RETRACTED: A new robust insurance model considering the time of accident
Authors: Qu Shaojian , Jiang Shan , Feng Can
Published: June 2022

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Fog computing enabled air quality monitoring and prediction leveraging deep learning in IoT
Authors: Bharathi P. Divya , Narayanan V. Anantha , Sivakumar P. Bagavathi
Published: June 2022

With the rapid industrialization and urbanization worldwide, air quality levels are deteriorating at an unprecedented rate and posing a substantial threat to humans and the environment. This brings the concern to effectively monitor and forecast air quality levels in real-time. Conventional air quality monitoring stations are built based on centralized architectures involving high latency, communication technologies demanding high power, sensors involving high costs and decision making with moderate accuracy. To address the limitations of the existing systems, we propose a smart and distinct Air Quality Monitoring and Forecasting system embracing Fog Computing with IoT and Deep Learning (DL). The system is a three-layered architecture with the Sensing layer first, Fog Computing layer in between, and Cloud Computing layer at the end. Fog Computing is a powerful new generation paradigm that brings storage, computation, and networking at the edge of the IoT network and reduce network latency. A DL based BiLSTM (Bidirectional Long Short-Term Memory) model is deployed in the Fog Computing layer. The proposed system aims at real-time monitoring and accurate air quality forecasting to support decision making and aid timely prevention and control of pollutant emissions by alerting the stakeholders when a dangerous Air Quality Index (AQI) is expected. Experimental results show that the BiLSTM model has a better predictive performance considering the meteorological parameters than the baseline models in terms of MAE and RMSE. A proof of concept realizing the proposed system is elaborated in the paper.
RETRACTED: A novel hybrid improved hunger games search optimizer with extreme learning machine for predicting shrinkage of SLS parts
Authors: Zhang Yapeng , Guo Yanling , Xiao Yaning , Tang Wenxiu , Zhang Haoyu , Li Jian
Published: June 2022

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433.
Detection and counting of overlapped apples based on convolutional neural networks
Authors: Gao Mengyuan , Ma Shunagbao , Zhang Yapeng , Xue Yong
Published: June 2022

Automatic identification picking robot is an important research content of agricultural modernization development. In order to overcome the difficulty of picking robots for accurate visual inspection and positioning of apples in a complex orchard, a detection method based on an instance segmentation model is proposed. To reduce the number of model parameters and improve the detection speed, the backbone feature extraction network is replaced from the Resnet101 network to the lightweight GhostNet network. Spatial Pyramid Pooling (SPP) module is used to increase the receptive field to enhance the semantics of the output network. Compared with Resnet101, the parameter quantity of the model is reduced by 90.90%, the detection speed is increased from 5 frames/s to 10 frames/s, and the detection speed is increased by 100%. The detection result is that the accuracy rate is 91.67%, the recall rate is 97.82%, and the mAP value is 91.68%. To solve the repeated detection of fruits due to the movement of the camera, the Deepsort algorithms was used to solve the multi-tracking problems. Experiments show that the algorithm can effectively detect the edge position information and categories of apples in different scenes. It can be an automated apple-picking robot. The vision system provides strong technical support.
On the orders of OWA operators
Authors: Dai Songsong , Zheng Jianwei
Published: June 2022

In this paper, we propose a partial ordering ⪯ on the set of ordered weighted averaging (OWA) operators. Based on this relation ⪯, we introduce the negation, conjunction and disjunction operations, and establish a bounded De Morgan lattice equipped with an involutive negation for OWA operators. Finally, we develop a similarity measure between OWA operators based on the ordering ⪯.
The relationship of three difference operations for fuzzy numbers to three kinds of derivative
Authors: Jiang Yadan , Qiu Dong
Published: June 2022

The difference operation for fuzzy number is an essential concept for the fuzzy set theory. There are several differences proposed: generalized difference, generalized Hukuhara difference and granule difference. Based on these differences, generalized differentiability, generalized Hukuhara differentiability and granule differentiability are also proposed, respectively. In this paper, the relations among these three kinds of differences and that of related three kinds of differentiability are clarified.
A fault diagnosis method of rolling element bearing based on improved PSO and BP neural network
Authors: Song Xudong , Wang Hao , Liu Yifan , Wang Zi , Cui Yunxian
Published: June 2022

Aiming at the inherent defects of BP neural network in the field of rolling bearing fault diagnosis, based on the optimization of particle swarm optimization algorithm, this paper uses a variety of optimization strategies to optimize the particle swarm optimization algorithm, and then uses the optimized particle swarm optimization algorithm to optimize the BP neural network. Therefore, a new fault diagnosis method (Dual Strategy Particle Swarm Optimization BP neural network, DSPSOBP) is proposed. DSPSOBP fault diagnosis method is mainly divided into two steps. The first step is EMD decomposition of vibration signal, and the second step is to classify rolling bearing faults by using BP neural network optimized by Double Strategy Particle Swarm Optimization algorithm. Experiments show that DSPSOBP has stronger advantages than BP neural network basic fault diagnosis model.
Cervical cancer classification using efficient net and fuzzy extreme learning machine
Authors: Suphalakshmi A. , Ahilan A. , Jeyam A. , Subramanian Malliga
Published: June 2022

Cervical cancer is the most common and deadly malignancy affecting women worldwide. The prediction and treatment of this malignancy are necessary in order to avoid serious complications. In recent days, deep learning has enhanced the accuracy of cervical cancer prediction in its early stages. In this study, a deep learning based EN-FELM approach is proposed to detect and classify the cervical cells. Initially, the pap smear images are pre-processed to eliminate the background distortions. The EfficientNet is a reversed bottleneck MBConv used for feature extraction. Consequently, fuzzy extreme learning machine (FELM) is used to classify the healthy, benign, low squamous intraepithelial lesions (LSIL) and high squamous intraepithelial lesions (HSIL). The proposed model acquires the best classification accuracy on Herlev and SIPaKMeD datasets range of 99.6% and 98.5% respectively. As a result, the classification using FELM produces more efficient and accurate result which is significantly high compared to the traditional classifiers. The proposed EN-FELM improves the overall accuracy of 0.2%, 0.13% and 14.6% better than Autoencoder, LSTM and KNN with CNN respectively.
INCEPTUS Natural History, Run-in Study for Gene Replacement Clinical Trial in X-Linked Myotubular Myopathy
Authors: Dowling James J. ,   for the INCEPTUS investigators, Müller-Felber Wolfgang , Smith Barbara K. , Bönnemann Carsten G. , Kuntz Nancy L. , Muntoni Francesco , Servais Laurent , Alfano Lindsay N. , Beggs Alan H. , Bilder Deborah A. , Blaschek Astrid , Duong Tina , Graham Robert J. , Jain Minal , Lawlor Michael W. , Lee Jun , Coats Julie , Lilien Charlotte , Lowes Linda P. , MacBean Victoria , Neuhaus Sarah , Noursalehi Mojtaba , Pitts Teresa , Finlay Caroline , Christensen Sarah , Rafferty Gerrard , Seferian Andreea M. , Tsuchiya Etsuko , James Emma S. , Miller Weston , Sepulveda Bryan , Vila Maria Candida , Prasad Suyash , Rico Salvador , Shieh Perry B.
Published: June 2022

Background: X-linked myotubular myopathy (XLMTM) is a life-threatening congenital myopathy that, in most cases, is characterized by profound muscle weakness, respiratory failure, need for mechanical ventilation and gastrostomy feeding, and early death. Objective: We aimed to characterize the neuromuscular, respiratory, and extramuscular burden of XLMTM in a prospective, longitudinal study. Methods: Thirty-four participants < 4 years old with XLMTM and receiving ventilator support enrolled in INCEPTUS, a prospective, multicenter, non-interventional study. Disease-related adverse events, respiratory and motor function, feeding, secretions, and quality of life were assessed. Results: During median (range) follow-up of 13.0 (0.5, 32.9) months, there were 3 deaths (aspiration pneumonia; cardiopulmonary failure; hepatic hemorrhage with peliosis) and 61 serious disease-related events in 20 (59%) participants, mostly respiratory (52 events, 18 participants). Most participants (80%) required permanent invasive ventilation (>16 hours/day); 20% required non-invasive support (6–16 hours/day). Median age at tracheostomy was 3.5 months (95% CI: 2.5, 9.0). Thirty-three participants (97%) required gastrostomy. Thirty-one (91%) participants had histories of hepatic disease and/or prospectively experienced related adverse events or laboratory or imaging abnormalities. CHOP INTEND scores ranged from 19–52 (mean: 35.1). Seven participants (21%) could sit unsupported for≥30 seconds (one later lost this ability); none could pull to stand or walk with or without support. These parameters remained static over time across the INCEPTUS cohort. Conclusions: INCEPTUS confirmed high medical impact, static respiratory, motor and feeding difficulties, and early death in boys with XLMTM. Hepatobiliary disease was identified as an under-recognized comorbidity. There are currently no approved disease-modifying treatments.
Evaluating the Use of Digital Biomarkers to Test Treatment Effects on Cognition and Movement in Patients with Lewy Body Dementia
Authors: Wang Jian , Battioui Chakib , McCarthy Andrew , Dang Xiangnan , Zhang Hui , Man Albert , Zou Jasmine , Kyle Jeffrey , Munsie Leanne , Pugh Melissa , Biglan Kevin
Published: June 2022

Background: PRESENCE was a Phase 2 trial assessing mevidalen for symptomatic treatment of Lewy body dementia (LBD). Participants received daily doses (10, 30, or 75 mg) of mevidalen (LY3154207) or placebo for 12 weeks. Objective: To evaluate if frequent cognitive and motor tests using an iPad app and wrist-worn actigraphy to track activity and sleep could detect mevidalen treatment effects in LBD. Methods: Of 340 participants enrolled in PRESENCE, 238 wore actigraphy for three 2-week periods: pre-, during, and post-intervention. A subset of participants (n = 160) enrolled in a sub-study using an iPad trial app with 3 tests: digital symbol substitution (DSST), spatial working memory (SWM), and finger-tapping. Compliance was defined as daily test completion or watch-wearing ≥23 h/day. Change from baseline to week 12 (app) or week 8 (actigraphy) was used to assess treatment effects using Mixed Model Repeated Measures analysis. Pearson correlations between sensor-derived features and clinical endpoints were assessed. Results: Actigraphy and trial app compliance was > 90% and > 60%, respectively. At baseline, daytime sleep positively correlated with Epworth Sleepiness Scale score (p < 0.01). Physical activity correlated with improvement on Movement Disorder Society –Unified Parkinson Disease Rating Scale (MDS-UPDRS) part II (p < 0.001). Better scores of DSST and SWM correlated with lower Alzheimer Disease Assessment Scale –Cognitive 13-Item Scale (ADAS-Cog13) (p < 0.001). Mevidalen treatment (30 mg) improved SWM (p < 0.01), while dose-dependent decreases in daytime sleep (10 mg: p < 0.01, 30 mg: p < 0.05, 75 mg: p < 0.001), and an increase in walking minutes (75 mg dose: p < 0.001) were observed, returning to baseline post-intervention. Conclusion: Devices used in the LBD population achieved adequate compliance and digital metrics detected statistically significant treatment effects.
Quantitative Digitography Measures Motor Symptoms and Disease Progression in Parkinson’s Disease
Authors: Wilkins Kevin B. , Petrucci Matthew N. , Kehnemouyi Yasmine , Velisar Anca , Han Katie , Orthlieb Gerrit , Trager Megan H. , O’Day Johanna J. , Aditham Sudeep , Bronte-Stewart Helen
Published: June 2022

Background: Assessment of motor signs in Parkinson’s disease (PD) requires an in-person examination. However, 50% of people with PD do not have access to a neurologist. Wearable sensors can provide remote measures of some motor signs but require continuous monitoring for several days. A major unmet need is reliable metrics of all cardinal motor signs, including rigidity, from a simple short active task that can be performed remotely or in the clinic. Objective: Investigate whether thirty seconds of repetitive alternating finger tapping (RAFT) on a portable quantitative digitography (QDG) device, which measures amplitude and timing, produces reliable metrics of all cardinal motor signs in PD. Methods: Ninety-six individuals with PD and forty-two healthy controls performed a thirty-second QDG-RAFT task and clinical motor assessment. Eighteen individuals were followed longitudinally with repeated assessments for an average of three years and up to six years. Results: QDG-RAFT metrics showed differences between PD and controls and provided correlated metrics for total motor disability (MDS-UPDRS III) and for rigidity, bradykinesia, tremor, gait impairment, and freezing of gait (FOG). Additionally, QDG-RAFT tracked disease progression over several years off therapy and showed differences between akinetic-rigid and tremor-dominant phenotypes, as well as people with and without FOG. Conclusions: QDG is a reliable technology, which could be used in the clinic or remotely. This could improve access to care, allow complex remote disease management based on data received in real time, and accurate monitoring of disease progression over time in PD. QDG-RAFT also provides the comprehensive motor metrics needed for therapeutic trials.
Cross-cultural validity of the Intuitive Eating Scale-2: Psychometric evaluation in the Greek-Cypriot population
Authors: Giannakou Konstantinos , Kyprianidou Maria , Basdani Evaggelia , Hadjimbei Elena , Chrysostomou Stavri
Published: June 2022

BACKGROUND: Intuitive eating is defined by eating response to physiological hunger and satiety cues rather than situational or emotional cues and it has been linked to psychological well-being. The 23-item Intuitive Eating Scale-2 (IES-2) is commonly used to assess the concept of intuitive eating. OBJECTIVE: To develop the Greek version of the IES-2 questionnaire and to test its psychometric qualities. METHODS: Forward and backward translations into Greek and English were completed. Exploratory Factor Analysis (EFA) was applied to understand the underlying factor structure of the IES-2, whilst internal consistency was assessed by Cronbach’s alpha test. The concurrent validity was assessed by evaluating the correlation among the IES-2 and the Eating Attitudes Test-26 Item (EAT-26) questionnaire. RESULTS: A total of 379 adults (mean age = 34 years) participated. EFA gave a three-factor structure with the total variance explained being 54.4%. Cronbach’s alpha was 0.87 for the IES-2 total score, as well as 0.90, 0.84 and 0.70 for the IES-2 subscales. The revised IES-2 total score was significantly correlated with EAT-26 total score (rs = –0.46, p < 0.01) and BMI (rs = –0.46, p < 0.01). CONCLUSION: In this sample, the Greek version of the IES-2 showed good psychometric qualities and can be regarded a helpful tool for examining adult intuitive eating behaviours.
Data impressions for a smart city: Exploring new ways to present and engage citizens in environmental data
Authors: Pigott Jon , Carroll Fiona , Taylor Aidan , Hornby Jess , Thorne Simon , Gardner Eleanor
Published: June 2022

We live in a world full of data being generated in exabytes by citizens, devices, buildings and assets intricately embedded in our environments. Whilst there is potential for this data to improve many things, much of it is unused and invisible to the average citizen who in turn may have switched off through ‘data fatigue’. This paper introduces the concept of the data impression through data physicalisation as a way to engage citizens in their data. Like the art impressionists of the late 1800’s (who broke away from photo-realist painting), the authors of this paper want to break away from the rendering of detailed and complex dashboards of endless and graphs and statistics to create an engaging and meaningful impression through dynamic physical objects and systems. These ideas are explored through the detailed reporting and reflection on an 18-month data physicalisation project (Daptec) funded by the Welsh Government Smart Expertise (European Regional Development Fund). This project brought together a number of industry and academic partners around the problem of communicating environmental data relating to Flat Holm Island, a mainly uninhabited site of special scientific interest a few miles from the coast of Cardiff. The resulting physical smart technologies developed for the project were exhibited in Cardiff’s Techniquest science centre in spring 2022 with view to promoting dialogue around the island and its ecology, a more sustainable tourism and positive environmental practices for our smart cities.