Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

Agricultural investment project selection is a complex multi-criteria decision-making problem,as agricultural projects are easily influenced by various risk factors,and the evaluation information provided by decisionmakers usually involves uncertainty and inconsistency.Existing literature primarily employed direct preference elicitation methods to address such issues,necessitating a great cognitive effort on the part of decision-makers during evaluation,specifically,determining the weights of criteria.In this study,we propose an indirect preference elicitation method,known as a preference disaggregation method,to learn decision-maker preference models fromdecision examples.To enhance evaluation ease,decision-makers merely need to compare pairs of alternatives with which they are familiar,also known as reference alternatives.Probabilistic linguistic preference relations are employed to account for the presence of incomplete and uncertain information in such pairwise comparisons.To address the inconsistency among a group of decision-makers,we develop a pair of 0-1mixed integer programming models that consider both the semantics of linguistic terms and the belief degrees of decision-makers.Finally,we conduct a case study and comparative analysis.Results reveal the effectiveness of the proposed model in solving agricultural investment project selection problems with uncertain and inconsistent decision information.

User Preference Aware Hierarchical Edge-User Cooperative Caching Strategy

The emergence of various new services has posed a huge challenge to the existing network architecture.To improve the network delay and backhaul pressure,caching popular contents at the edge of network has been considered as a feasible scheme.However,how to efficiently utilize the limited caching resources to cache diverse contents has been confirmed as a tough problem in the past decade.In this paper,considering the time-varying user requests and the heterogeneous content sizes,a user preference aware hierarchical cooperative caching strategy in edge-user caching architecture is proposed.We divide the caching strategy into three phases,that is,the content placement,the content delivery and the content update.In the content placement phase,a cooperative content placement algorithm for local content popularity is designed to cache contents proactively.In the content delivery phase,a cooperative delivery algorithm is proposed to deliver the cached contents.In the content update phase,a content update algorithm is proposed according to the popularity of the contents.Finally,the proposed caching strategy is validated using the MovieLens dataset,and the results reveal that the proposed strategy improves the delay performance by at least 35.3%compared with the other three benchmark strategies.

Deep Learning Social Network Access Control Model Based on User Preferences

A deep learning access controlmodel based on user preferences is proposed to address the issue of personal privacy leakage in social networks.Firstly,socialusers andsocialdata entities are extractedfromthe social networkandused to construct homogeneous and heterogeneous graphs.Secondly,a graph neural networkmodel is designed based on user daily social behavior and daily social data to simulate the dissemination and changes of user social preferences and user personal preferences in the social network.Then,high-order neighbor nodes,hidden neighbor nodes,displayed neighbor nodes,and social data nodes are used to update user nodes to expand the depth and breadth of user preferences.Finally,a multi-layer attention network is used to classify user nodes in the homogeneous graph into two classes:allow access and deny access.The fine-grained access control problem in social networks is transformed into a node classification problem in a graph neural network.The model is validated using a dataset and compared with other methods without losing generality.The model improved accuracy by 2.18%compared to the baseline method GraphSAGE,and improved F1 score by 1.45%compared to the baseline method,verifying the effectiveness of the model.

Pregnancy Preferences in Females of Reproductive Age with Sickle Cell Disease at Laquintinie Hospital: A Cross-Sectional Analysis

Introduction: Females with sickle cell disease (SCD), despite having a delayed pubertal development, are subject to many worries relating to their abilities to conceive, their capacity to maintain a maternofetal-risk-free pregnancy till term and give birth to healthy children without sickle cell disease. Knowing that unplanned pregnancies are more likely to increase maternofetal morbidity and mortality, we sought out to explore the pregnancy preferences in female patients with sickle cell disease to promote healthy conception and childbirth in this vulnerable population. Methodology: We conducted a cross-sectional study involving female patients of child-bearing age with sickle cell disease followed at Laquintinie Hospital Douala or who were members of a local sickle cell association. Pregnancy preferences were determined using the Desire to Avoid Pregnancy (DAP) scale. Factors associated with pregnancy preferences were determined using multivariable linear regression model. Threshold for significance was set at p Results: Seventy-seven patients were included with a mean age of 24.71 ± 5.53 years. Forty patients (51.95%) had one sexual partner and thirteen women (32.5%) used contraceptive methods. Most patients (46.0%) responded “Strongly Agree” or “Agree” to the statement “it would be a good thing for me if I became pregnant in the next 3 months”. The mean DAP score was 1.63 ± 0.91 [1.28 ± 0.82 in those who had a sexual partner and 1.99 ± 0.86 in those who had no sexual partner]. Factors that were positively associated with DAP score were students (b = 0.32, 95% CI [0.21, 0.95], p = 0.003), monthly income ≥ 100,000 FCFA (b = 0.24, 95% CI [0.07, 0.81], p = 0.022), and not having a sexual partner (b = 0.26, 95% CI [0.11, 0.85], p = 0.012). Conclusion: Most female patients with SCD have a low desire to avoid pregnancy. This is especially true for patients who are not students, have a partner and have a low monthly income.

Species’ geographical range, environmental range and traits lead to specimen collection preference of dominant plant species of grasslands in Northern China

Many different factors,such as species traits,socio-economic factors,geographical and environmental factors,can lead to specimen collection preference.This study aims to determine whether grassland specimen collection in China is preferred by species traits(i.e.,plant height,flowering and fruiting period),environmental range(i.e.,the temperature and precipitation range)and geographical range(i.e.,distribution range and altitudinal range).Ordinary least squares models and phylogenetic generalized linear mixed models were used to analyze the relationships between specimen number and the explanatory variables.Random Forest models were then used to find the most parsimonious multivariate model.The results showed that interannual variation in specimen number between 1900 and 2020 was considerable.Specimen number of these species in southeast China was notably lower than that in northwest China.Environmental range and geographical range of species had significant positive correlations with specimen number.In addition,there were relatively weak but significant associations between specimen number and species trait(i.e.,plant height and flowering and fruiting period).Random Forest models indicated that distribution range was the most important variable,followed by flowering and fruiting period,and altitudinal range.These findings suggest that future floristic surveys should pay more attention to species with small geographical range,narrow environmental range,short plant height,and short flowering and fruiting period.The correction of specimen collection preference will also make the results of species distribution model,species evolution and other works based on specimen data more accurate.

Surgeon preferences in the treatment of thumb carpometacarpal osteoarthritis

BACKGROUND Primary thumb carpometacarpal(CMC)osteoarthritis is one of the most common conditions encountered by hand surgeons.Of the vast number of operations that have been proposed,none have demonstrated results significantly superior to trapeziectomy alone.AIM The purpose of our study was to determine why surgeons opt for their technique in treating CMC arthritis.METHODS A cross-sectional survey of active members of the American Society for Surgery of the Hand was conducted to evaluate the reasons behind their preferred technique in the treatment of isolated thumb CMC arthritis.Surgeons were contacted by email once and provided with a link to a de-identified survey consisting of 5 treatment questions and 5 demographic questions.RESULTS Of 950 responses were received.40.5%of surgeons preferred trapeziectomy+ligament reconstruction tendon interposition(LRTI),followed by trapeziectomy+suspensionplasty(28.2%),suture button suspension(5.9%),trapeziectomy alone(4.6%),prosthetic arthroplasty(3.2%),arthrodesis(1.1%),and other(6.6%).Proponents of trapeziectomy+LRTI cited familiarity(73.2%),exposure during fellowship(48.8%)and less proximal migration(60%)to be the main reasons affecting their decision.Surgeons who preferred trapeziectomy+suspensionplasty most reported simplicity(74.9%),fewer complications(45.3%),less proximal migration(43.8%),and avoidance of autogenous tissue harvest(42.7%).Advocates of suture button suspension cited avoidance of autogenous tissue harvest(80.4%),shorter immobilization(76.8%),and quicker recovery(73.2%)with their technique.Advocates of trapeziectomy alone cited simplicity(97.7%),fewer complications(86.4%),and avoidance of autogenous tissue harvest(59.1%).In their comments,45%of surgeons choosing trapeziectomy alone cited evidence as an additional rationale.Advocates of prosthetic arthroplasty cited improved pinch strength(83.3%)and improved range of motion(63.3%),while those preferring arthrodesis cited better pinch strength(90%)and frequently in their comments,durability.Of the surgeons who preferred a technique other than LRTI,41.8%reported they had tried LRTI in the past,citing complexity of the procedure,flexor carpi radialis harvest,and longer operative time as reasons for moving on.CONCLUSION Our study provides an update on current treatment trends and offers new insight into the reasons behind surgeons'decision making in the management of thumb carpometacarpal osteoarthritis.Despite strong Level 1 evidence supporting the use of trapeziectomy alone,our findings demonstrate that most surgeons continue to supplement trapeziectomy with other techniques such as LRTI or suspensionplasty.Several factors including familiarity,personal experience(Level 4 evidence),and comfort may be more influential than Level 1 evidence in determining the techniques in a surgeon's armamentarium.Further prospective studies are needed to determine the optimal technique for surgical management of Eaton stages II-IV CMC arthritis and how these studies will affect surgeons’choice.

Oviposition Site Preference and Its Effects on Subsequent Development of Variegated Grasshopper (Zonocerus variegatus L.) under Laboratory Conditions

Female grasshoppers can affect the fitness of their offspring through their selection of oviposition site. Knowledge of soil type on oviposition, and its effects on subsequent development can provide guidelines for habitat manipulations that reduce the harmful effects of these pests on farmers fields. The influence of soil types on the oviposition site preference of variegated grasshopper (Zonocerus variegatus L.) reared some cassava (Manihot esculenta Crantz) varieties, was investigated in a cage trial carried out at the Bio factory laboratory, School of Agriculture and Food Sciences, Njala University, Sierra Leone during 2022/2023. The treatments comprised three soil types (Sandy, Loamy and Clay), each with three replications laid out in a randomized complete block design (RCBD) in wooden cages. Data were collected on the following development parameters including, Net reproductive growth ratio (R0), Generation time (Tc), Intrinsic rate of increase (rm), Finite rate of increase (), Doubling time (Dt), and overall survivorship. Findings revealed that, Z. variegatus L. preferred sandy soil in which, on average, most eggs were deposited (338, 6.62 4.40), followed by loamy soil, 286 (5.53 3.96), and then, clayey soil, 200 (3.91 3.85);though, the differences were not significant. This study established that Z. variegatus deposited more eggs in sandy soil > loamy soil > clayey soil, respectively;and subsequent survivorship of the immature unto mature adult insect, revealed a similar order. This indicates that the sandy soil is the most preferred substrate for oviposition and subsequent development into adult insects.

Response of Distribution Range Against Climate Change and Habitat Preference of Four National Protected Diploderma Species in Tibetan Plateau

Understanding the spatial distribution and habitat preference for rare and endangered species are essential for effective conservation practice.We examined the spatial distribution and habitat preference of four Diploderma species(Diploderma drukdaypo,D.laeviventre,D.batangense,and D.vela),which are endemic to the Qinghai-Tibet Plateau and are currently under state protection.We used the ensembles of small models(ESM)approach and predicted potential distribution ranges of the species in current and two future climate scenarios(SSP126 and SSP585).The degree of overlap between the predicted distribution ranges and existing natural reserves was further analyzed.Habitat preference was examined using a paired quadrat method.Our results predicted that D.drukdaypo has a current distribution range of 600 km^(2),which would decrease to 50 km^(2)and 55 km^(2)under the SSP126 and SSP585 respectively.For D.laeviventre,the current distribution range is 817 km^(2),with minimum changes in the two future climate scenarios(774 km^(2)and 902 km^(2)).For D.batangense,the current distribution range is 875 km^(2),which would expand to 1522 km^(2)and 3340 km^(2)in the two future climate scenarios.Similarly for D.vela,the current distribution range is 1369 km^(2),which would change to 1825 km^(2)and 2043 km^(2)respectively under the two future climate scenarios.The effect of protection of current nature reserves are likely low for those species;we found no overlap(D.drukdaypo,D.laeviventre)or little overlap(D.batangense 2.04%–3.56%,D.vela 15.52%–16.87%)between the currently designated protection area and distribution range under current and future climate scenarios.For habitat preference,stones appear to be the critical habitat element for those species although different species had different stone requirements.Taken together,we provided critical information on potential distribution ranges and habitat preference for four endangered Diploderma species,and confirmed the inadequacy of current nature reserves.The establishment of new or expansion of existing nature reserves is urgent for the conservation of those species.

The role of time preferences in contract breach:Evidence from Chinese poultry farmers participating in contract farming

Farmers’contract breach behavior is cited as one of the major stumbling blocks in the sustainable expansion of contract farming in many developing countries.This paper examines farmers’contract breach decisions from the perspective of time preferences.The empirical analysis is based on a household survey and economic field experiments of poultry households participating in contract farming conducted in Jiangsu Province,China.A discounted utility model and a maximum likelihood technique are applied to estimate farmers’time preferences and the effect of time preferences on contract breach in the production and sales phases are explored with a bivariate probit model.The results show that,on average,the poultry farmers in the sample are generally present biased and impatient regarding future utility.The regression results show that farmers with a higher preference for the present and a higher discount rate are more likely to breach contracts,and time preferences play a greater role in the production phase than in the sales phase.When considering heterogeneity,specific investments and transaction costs promote contract stability only for farmers with a low degree of impatience.Moreover,compared with large-scale farmers,small-scale farmers’contract breach decisions are more significantly affected by their time preferences.These results have implications for contract stability policies and other issues that are impacted by the linking of behavioral preferences to agricultural decisions.

Risk preferences and the low-carbon agricultural technology adoption:Evidence from rice production in China

Climate change which is mainly caused by carbon emissions is a global problem affecting the economic development and well-being of human society.Low-carbon agriculture is of particular significance in slowing down global warming and reaching the goal of“carbon peak and carbon neutrality”.Therefore,taking straw incorporation as an example,this paper aims to investigate the impact of risk preferences on farmers’low-carbon agricultural technology(LCAT)adoption.Based on a two-phase micro-survey data of 1038 rice farmers in Jiangsu,Jiangxi,and Hunan provinces,this paper uses experimental economics methods to measure farmers’risk aversion and loss aversion to obtain the real risk preferences information of the farmers.We also explore the data to examine the actual LCAT adoption behavior of farmers.The results revealed that both risk aversion and loss aversion significantly inhibit farmers’LCAT adoption:more risk-averse or more loss-averse farmers are less likely to adopt LCAT.It is further found that crop insurance,farm scale and governmental regulations can alleviate the negative impact of risk aversion and loss aversion on farmers’LCAT adoption.Therefore,we propose that local governments need to promote low-carbon agricultural development by propagating the benefits of LCAT,extending crop insurance,promoting appropriate scale operations,and strengthening governmental regulations to promote farmers’LCAT adoption.

Consumers’experiences and preferences for plant-based meat food:Evidence from a choice experiment in four cities of China

This paper examined consumers’experiences in and preferences for plant-based meat(PBM)food and their respective correlates,based on data from an online survey of 579 consumers in four major cities in China in early 2021.We first described consumers’experiences in consuming and purchasing PBM food and their correlates,and then analyzed consumer preferences using hypothetical choice experiment.The experiment offered consumers various options to purchase burgers made from PBM or animal-based meat(ABM),combined with different countries of origin(COO),taste labels,and prices.Our data showed that respondents hold overall positive attitudes toward PBM food;85 and 82%of respondents reported experience in eating and purchasing PBM food,respectively.More than half of them ate PBM food because they wanted to try new food(58%),or were interested in healthy food(56%).Income,religion,and dietary restrictions were significantly correlated with consumers’experiences in PBM food consumption.Results from the Random Parameter Logit Model based on the hypothetical choice experiment data showed that 79%of respondents chose PBM burgers and were willing to pay an average of 88 CNY for a PBM burger.We also found that 99.8 and 83%of respondents are willing to buy burgers made in China and those with a taste label,with a willingness to pay(WTP)of 208 and 120 CNY,respectively.The heterogeneity test revealed that females and those with at least a bachelor’s degree,higher income,religious beliefs,and dietary restrictions are more likely to buy PBM burgers than their counterparts.

Intelligent 6G Wireless Network with Multi-Dimensional Information Perception

Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in 6G systems.Therefore,fusion is becoming a typical feature and key challenge of 6G wireless communication systems.In this paper,we focus on the critical issues and propose three application scenarios in 6G wireless systems.Specifically,we first discuss the fusion of AI and 6G networks for the enhancement of 5G-advanced technology and future wireless communication systems.Then,we introduce the wireless AI technology architecture with 6G multidimensional information perception,which includes the physical layer technology of multi-dimensional feature information perception,full spectrum fusion technology,and intelligent wireless resource management.The discussion of key technologies for intelligent 6G wireless network networks is expected to provide a guideline for future research.

Validity and Reliability of the Preference for and Tolerance of the Intensity of Exercise Questionnaire among Chinese College Students

The rising prevalence of physical inactivity is in all age groups(e.g.,in college students)a major public health issue as not meeting the recommended minimum amount of regular physical activity is linked to adverse health events.Vice versa,there is mounting evidence that achieving the recommended amount of regular physical activity is a vital element to prevent chronic diseases,but there is often an insufficient adherence to planned and structured forms of physical activity(i.e.,physical exercises).In this context,there is a large body of evidence indicating that exercise adherence is,among other factors,influenced by exercise-related affective responses.The Preference for and Tolerance of the Intensity of Exer-cise Questionnaire(PRETIE-Q)has been developed to measure these affective responses(e.g.,to specific exercise inten-sities).So far,no validated Chinese version of the PRETIE-Q has been available in the literature.To address this gap in literature,the present study developed and validated a Chinese version of the PRETIE-Q in a large sample of Chinese college students.Data from a total of 1117 college students were collected for analyses concerning factorial validity and construct validity.The re-test reliability was established using a sample of 150 randomly selected participants.In addition,the level of regular physical activity(PA),cardiorespiratoryfitness(CRF),and resilience were used to examine possible links with two domains(preference and tolerance)of the PRETIE-Q.Our results showed that a Chinese version of the PRETIE-Q has a goodfit and reliability(Cronbach’sαof 0.72 to 0.85 for preference and tolerance,respectively;ICC:r=0.72 of preference and r=0.67 of tolerance;fit indices:χ^(2)=21.612,df=19,p>0.05,TLI=0.997,CFI=0.998,RMSEA=0.016,SRMR=0.024).Secondly,positive associations of intensity-tolerance with PA,CRF,and resilience were observed.In summary,this study indicates that the Chinese version of the PRETIE-Q has sound psychometric properties and can be used in Chinese college students.The adapted version of the PRETIE-Q paves the way for further research on exer-cise-related affective responses in Chinese-speaking samples,although the generalizability of ourfindings needs to be established for other cohorts such as adolescents and older people with and without chronic diseases.

Hypoxia tolerance in fish depends on catabolic preference between lipids and carbohydrates

Hypoxia is a common environmental stress factor in aquatic organisms,which varies among fish species.However,the mechanisms underlying the ability of fish species to tolerate hypoxia are not well known.Here,we showed that hypoxia response in different fish species was affected by lipid catabolism and preference for lipid or carbohydrate energy sources.Activation of biochemical lipid catabolism through peroxisome proliferator-activated receptor alpha(Pparα)or increasing mitochondrial fat oxidation in tilapia decreased tolerance to acute hypoxia by increasing oxygen consumption and oxidative damage and reducing carbohydrate catabolism as an energy source.Conversely,lipid catabolism inhibition by suppressing entry of lipids into mitochondria in tilapia or individually knocking out three key genes of lipid catabolism in zebrafish increased tolerance to acute hypoxia by decreasing oxygen consumption and oxidative damage and promoting carbohydrate catabolism.However,anaerobic glycolysis suppression eliminated lipid catabolism inhibition-promoted hypoxia tolerance in adipose triglyceride lipase(atgl)mutant zebrafish.Using 14 fish species with different trophic levels and taxonomic status,the fish preferentially using lipids for energy were more intolerant to acute hypoxia than those preferentially using carbohydrates.Our study shows that hypoxia tolerance in fish depends on catabolic preference for lipids or carbohydrates,which can be modified by regulating lipid catabolism.

Envelope Method and More General New Global Structures of Solutions for Multi-dimensional Conservation Law

For the two-dimensional(2D)scalar conservation law,when the initial data contain two different constant states and the initial discontinuous curve is a general curve,then complex structures of wave interactions will be generated.In this paper,by proposing and investigating the plus envelope,the minus envelope,and the mixed envelope of 2D non-selfsimilar rarefaction wave surfaces,we obtain and the prove the new structures and classifications of interactions between the 2D non-selfsimilar shock wave and the rarefaction wave.For the cases of the plus envelope and the minus envelope,we get and prove the necessary and sufficient criterion to judge these two envelopes and correspondingly get more general new structures of 2D solutions.

Future Long-Term Care Setting Preferences and Related Factors among Japanese Middle-Aged and Older People Living with HIV

Since the introduction of antiretroviral therapy, the life expectancy of people living with human immunodeficiency virus (PLWH) has extended. This extension has led to an increase in the aging population in Japan and globally. Providing appropriate long-term care (LTC) for PLWH has thus become increasingly critical. Our study aimed to describe LTC setting preferences and related factors among middle-aged and older Japanese people living with HIV. A cross-sectional survey was conducted at two hospitals in Tokyo. One hundred seventy-five outpatients aged 40 years and above participated in this study. Participants completed an anonymous self-administered questionnaire to assess where they wanted to live once they could no longer care for themselves. Approximately 52.0% preferred a designated facility for older adults or LTC, while 30.3% preferred their home or living with family, a partner, or a friend (“familiar housing”). Bivariate analyses revealed that LTC setting preference was significantly associated with marital status, whether or not the participant had at least one child, and household composition. Furthermore, logistic regression analysis revealed that participants living with non-kin were less likely to prefer living in designated housing facilities for older adults or LTC (adjusted odds ratio = 0.17, 95% confidence interval: 0.05 - 0.63). The study findings suggest that family make-up and composition of cohabiters are critical indicators for LTC setting preference in this population. These findings can be the foundation for future care planning and delivery to meet the unique LTC needs and expectations of the aging population with HIV in Japan and similar global settings.

Research and Practice on the Multi-dimensional Course Goal Achievement Evaluation of Software Engineering

According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteristics of hybrid teaching in Kunming University of Science and Technology.Then a multi-dimensional evaluation system for course goal achievement of software engineering is proposed.The practice’s results show that the multi-dimensional course goal achievement evaluation is helpful to the continuous improvement of course teaching,which can effectively support the evaluation of graduation outcomes.

An Ordinal Multi-Dimensional Classification(OMDC)for Predictive Maintenance

Predictive Maintenance is a type of condition-based maintenance that assesses the equipment's states and estimates its failure probability and when maintenance should be performed.Although machine learning techniques have been frequently implemented in this area,the existing studies disregard to the nat-ural order between the target attribute values of the historical sensor data.Thus,these methods cause losing the inherent order of the data that positively affects the prediction performances.To deal with this problem,a novel approach,named Ordinal Multi-dimensional Classification(OMDC),is proposed for estimating the conditions of a hydraulic system's four components by taking into the natural order of class values.To demonstrate the prediction ability of the proposed approach,eleven different multi-dimensional classification algorithms(traditional Binary Relevance(BR),Classifier Chain(CC),Bayesian Classifier Chain(BCC),Monte Carlo Classifier Chain(MCC),Probabilistic Classifier Chain(PCC),Clas-sifier Dependency Network(CDN),Classifier Trellis(CT),Classifier Dependency Trellis(CDT),Label Powerset(LP),Pruned Sets(PS),and Random k-Labelsets(RAKEL))were implemented using the Ordinal Class Classifier(OCC)algorithm.Besides,seven different classification algorithms(Multilayer Perceptron(MLP),Support Vector Machine(SVM),k-Nearest Neighbour(kNN),Decision Tree(C4.5),Bagging,Random Forest(RF),and Adaptive Boosting(AdaBoost))were chosen as base learners for the OCC algorithm.The experimental results present that the proposed OMDC approach using binary relevance multi-dimensional classification methods predicts the conditions of a hydraulic system's multiple components with high accuracy.Also,it is clearly seen from the results that the OMDC models that utilize ensemble-based classification algorithms give more reliable prediction performances with an average Hamming score of 0.853 than the others that use traditional algorithms as base learners.

Temporal Preferences-Based Utility Control for Smart Homes

The residential sector contributes a large part of the energy to the global energy balance.To date,housing demand has mostly been uncontrollable and inelastic to grid conditions.Analyzing the performance of a home energy manage-ment system requires the creation of various profiles of real-world residential demand,as residential demand is complex and includes multiple factors such as occupancy,climate,user preferences,and appliance types.Average Peak Ratio(A2P)is one of the most important parameters when managing an efficient and cost-effective energy system.At the household level,the larger relative magni-tudes of certain energy devices make managing this ratio critical,albeit difficult.Various Demand Response(DR)and Demand Side Management(DSM)systems have been proposed to reduce this ratio to 1.The main ways to achieve this are economic incentives,user comfort modeling and control,or preference-based.In this study,we propose a unique opportunistic social time approach called the Time Utility Based Control Feature(TUBCF),which uses the concept of a utility function from economics to model and control consumer devices.We propose a DR model for residential customers to reduce Peak-to-Average Ratio(PAR)and improve customer satisfaction by eliminating Appliance Wait Time(WTA)during peak periods.For PAR reduction and WTA,we propose a system architecture and mathematical formulation.Our proposed model automatically schedules devices based on their temporal preferences and considers six households with different device types and operational characteristics.Simulation results show that using this strategy can reduce A2P by 80%and improve user comfort during peak hours.