Factors Associeted with Home Accidents in Childhood at Regional Teaching Hospital of OuéméPlateau

Introduction: Home accidents (HA) are often unknown in Benin compared to infectious pathologies. The aim of this work was to determine the prevalence and the factors associated with HA in children admitted to the CHUD-OP. Method: This was a cross-sectional study conducted from August 1st to October 31th 2021. We studied children aged 0 to 18 who presented with HA to the pediatrics and emergency reception and triage departments at CHUD-OP. We defined HA as “any event occurring inside the home or in the immediate vicinity of the home that resulted in an injury which was not done deliberately. Results: The hospital frequency of HA was 8.4% (61/725). The median age was 5 years with a male to female ratio of 1.6. Trauma was the leading cause of HA (59%) followed by poisoning (23%). Falling was the main mechanism of trauma (80.6%). The toxins causing poisoning were dominated by caustics (28.6%). The age of the children (p = 0.02), the level of education of the mothers (p , and the area they occur (kitchen with p = 0.04 and on the stairs with p = 0.03) were statistically associated with the occurrence of trauma. Conclusion: HA are common among children admitted at CHUD-OP and factors associated with HA are identified. Measures to prevent home accidents among children in the community should be considered.

Determinants of Home Deliveries by Pregnant Mothers in Lumbo Chabbobboma Zone of Gwembe District in Zambia

Background: Home deliveries is still high globally at 42% WHO 2022, due to high home deliveries, maternal death is also high at 43% globally. In sub-Sahara region home deliveries still high. Giving birth at health facilities in most of sub-Saharan African countries Zambia inclusive is still a challenge whereby more than 51% of first-time mothers give birth at home and this gives a risk of high maternal and perinatal deaths. Therefore Reducing number of home deliveries is important to improve maternal and perinatal health issues. In this study, the aim was to investigate the determinants of home deliveries by pregnant mothers in the Luumbo zone of Gwembe district, Zambia. Purpose: Access to skilled care and facilities with capacity to provide emergency and newborn care is critical to reduce maternal death. In Zambia 42% of women still deliveries from home, suggesting a persistent challenge for women to seek, reach, and receive quality maternity care. This study aimed investigate the determinants of home deliveries by pregnant mothers in Luumbo zone of Gwembe district, Zambia. Methods: The study was conducted among postnatal mothers who came for postnatal care at 6 weeks in Luumbo Chabbobboma clinic in Gwembe district southern province of Zambia. This was a descriptive cross-sectional study where a Simple random sampling technique was used to select 105 women of childbearing age who attended postnatal and had a recent delivery. Data were collected using a researcher-administered structured questionnaire to identify determinants of home deliveries in Luumbo Chabbobboma zone. Data analysis was done using SPSS computer software version 27.0. Both descriptive and inferential (chi-square test) analyses were performed and statistical significance was taken at α ≤ 0.05. Results: The results show that 46 (43.8%) respondents were in the age bracket 20 - 29 years. Of the 105 respondents included in the study, 24 (22.9%) of them delivered from home. The results show that high maternal age (p = 0.03), occupation (p = 0.024), distance to the facility (p = 0.014), means of transportation (p = 0.023), multiparity (p = 0.01), timing and number of ANC visits (p Conclusion: From this population. The major reason why women still deliver at home was long distance to the nearest facility. To reduce maternal and perinatal mortality access to health facilities by pregnant women needs to be improved. There should also be active engagement of the traditional and religious institutions in the area.

Not in Control,but Liable?Attributing Human Responsibility for Fully Automated Vehicle Accidents

Human agency has become increasingly limited in complex systems with increasingly automated decision-making capabilities.For instance,human occupants are passengers and do not have direct vehicle control in fully automated cars(i.e.,driverless cars).An interesting question is whether users are responsible for the accidents of these cars.Normative ethical and legal analyses frequently argue that individuals should not bear responsibility for harm beyond their control.Here,we consider human judgment of responsibility for accidents involving fully automated cars through three studies with seven experiments(N=2668).We compared the responsibility attributed to the occupants in three conditions:an owner in his private fully automated car,a passenger in a driverless robotaxi,and a passenger in a conventional taxi,where none of these three occupants have direct vehicle control over the involved vehicles that cause identical pedestrian injury.In contrast to normative analyses,we show that the occupants of driverless cars(private cars and robotaxis)are attributed more responsibility than conventional taxi passengers.This dilemma is robust across different contexts(e.g.,participants from China vs the Republic of Korea,participants with first-vs third-person perspectives,and occupant presence vs absence).Furthermore,we observe that this is not due to the perception that these occupants have greater control over driving but because they are more expected to foresee the potential consequences of using driverless cars.Our findings suggest that when driverless vehicles(private cars and taxis)cause harm,their users may face more social pressure,which public discourse and legal regulations should manage appropriately.

基于NodeMCU和Home Assistant的智能家居控制系统

为了提高家居生活的舒适性和便利性,开发了一套智能家居控制系统。该系统采用节点微控制单元(NodeMCU)作为基础硬件,负责收集传感器数据并操控相关执行器件。同时,该系统利用消息队列遥测传输协议(MQTT)和WiˉFi技术构建数据传输链路。此外,该系统利用开源的Home Assistant系统建立了后台服务端,以实现数据的图形化展示。用户可通过安卓移动设备实时监控家居环境状况,并对智能设备实施控制。该系统经过严格测试,表现稳定,显著提高了家居环境的智能化程度。

Informing policy makers in developing countries:Practices and limitations of geriatric home medication review in Malaysia-A qualitative inquiry

Objective:To explore existing practices and challenges in the delivery of geriatric home medication review(HMR).The study was part of a larger study aimed to offer solution to expand the range of geriatric HMR.Methods:This study employed qualitative exploratory design through semi-structured individual in-depth interviews with the public pharmacists involved in the delivery of geriatric HMR at public hospitals.The purpose of the interviews was to explore challenges faced by them in the delivery of geriatric HMR.Results:Based on the emerging themes from the qualitative data,the study reveals that geriatric HMR in Malaysia is integrated as part of multidisciplinary home care visits,encompassing a diverse patient population with various healthcare needs.However,it faces challenges such as the lack of outcome monitoring,formal training,and workforce constraints.Despite these hurdles,there is a pressing need for the expansion of this service to better serve the community,and collaboration with community pharmacists holds potential to broaden its scope.Ultimately,the findings suggest that pharmacist-led HMR is both warranted and feasible within the Malaysian healthcare context.In order to optimize medicine-use among older people living in the community,approaches for expanding geriatric HMR services in Malaysia must be developed.Conclusions:This study holds profound implications as it attempts to illuminate policy makers in developing countries,enabling them to formulate effective HMR plans.By considering the challenges highlighted within this research,policy makers can design a comprehensive HMR service that caters adeptly to the healthcare needs of the mass population.

Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology

The concept of smart houses has grown in prominence in recent years.Major challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device itself.Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features.This paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in homes.We have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT devices.Our system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing devices.We have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache server.The feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time settings.It is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation systems.Additionally,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber threats.The trial results support the proposed system and demonstrate its potential for use in everyday life.

Which Neighborhoods Have Easier Access to Online Home Delivery Services?A Spatiotemporal Accessibility Analysis in Nanjing,China

The rise in online home delivery services(OHDS)has had a significant impact on how urban services are supplied and used in recent years.Studies on the spatial accessibility of OHDS are emerging,but few is known about the temporal dimension of OHDS accessibility as well as the geographic and socioeconomic differences in the spatiotemporal accessibility of OHDS.This study measures the spatiotemporal accessibility of four types of OHDS,namely leisure,fresh and convenient,medical,and catering services.The geographic and socioeconomic disparities in the spatiotemporal accessibility of these four types of OHDS are then identified using spatial statistical methods and the Kruskal-Wallis test(K-W test).The case study in Nanjing,China,suggests that:1)spatiotemporal accessibility better reflects the temporal variation of OHDS accessibility and avoids overestimation of OHDS accessibility when only considering its spatial dimension.2)The spatiotemporal accessibility of OHDS varies geographically and socioeconomically.Neighborhoods located in the main city or neighborhoods with higher housing prices,higher population density,and higher point of interest(POI)mix have better OHDS spatiotemporal accessibility.Our study contributes to the understanding of OHDS accessibility from a spatiotemporal perspective,and the empirical insights can assist policymakers in creating intervention plans that take into account variations in OHDS spatiotemporal accessibility.

Otorhinolaryngological (ORL) and Cervicofacial Injuries Resulting from Road Accidents within the Otorhinolaryngology (ORL) Department of the Regional Hospital of Mamou

Introduction: Otorhinolaryngological (ORL) and cervicofacial traumas encompass injuries affecting the neck, face, and ORL region, resulting from external influence. The objective of this study was to conduct an epidemiological and clinical analysis of ORL and cervicofacial injuries observed in victims of road accidents treated at the Otorhinolaryngology (ORL) department of the Regional Hospital of Mamou. Materials and Methods: This prospective and descriptive study was conducted over a period of 12 months, from January 1st to December 31st, 2021, within the Otorhinolaryngology (ORL) department of the Regional Hospital of Mamou. It included patients hospitalized for ORL and/or cervicofacial traumas resulting from road accidents during the study period. Results: A total of 348 cases were included, representing 36.22% of all traumas related to road accidents (AVP) within the Regional Hospital of Mamou. The average age of the patients was 26.44 years, with a sex ratio of 3.83, favoring males. The dominant socio-professional category was students, encompassing 32.47% of cases. Road accidents were mainly associated with motorcycle use (31.32% motorcycle-to-motorcycle, 24.43% motorcycle skidding, 13.51% motorcycle-pedestrian). Facial region injuries were the most common, accounting for 69.03% of cases, followed by rhinological injuries (17.28%) and otological injuries (13.69%). Associated injuries were predominantly closed head traumas (52.55%) and lower limb fractures (20.41%). Imaging was underutilized. Regarding surgical interventions, reconstructive surgery was the most predominant, accounting for 52.51% of cases, with a management timeframe of 30 minutes to 12 hours for 99.72% of patients. Conclusion: Road traffic accidents remain a serious public health issue, primarily affecting young males. Emphasis should be placed on road safety measures to reduce the frequency of these accidents.

A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

Neuroarchitecture Analysis in the Mis Abuelitos Nursing Home in Cochachinche, Huanuco, Peru - A Secondary Publication

Neuroarchitecture is a set of characteristics grouped into principles that seek to generate a certain behavior when applied.These principles will vary according to the type of user for whom the design is intended.In this research,these neuroarchitectural principles are identified in the nursing home Mis Abuelitos in Cochachinche,Huánuco.The home was designed and built with notions of nature and the Andean while emphasizing the occupants are the elderly.With this purpose,qualitative research was carried out using two sequential criteria,the first was to identify what these principles are and the second was to recognize the principles within the area.The principles that are assertively used for the elderly occupants were selected.The study observation was performed with observation and photographic sheets and was analyzed with ATLAS.ti processing software.It was obtained that the three neuroarchitectural principles are present in the nursing home which are 67%of the recommended characteristics for the elderly.

Analysis of the Necessity of Stellate Ganglion Block after Anesthesia to Reduce the Risk of Cardiovascular Accidents in Coronary Heart Disease

Objective:To adjust the sympathetic nervous system through preoperative ultrasound-guided stellate ganglion block and to explore and analyze the situation and necessity of postanesthesia stellate ganglion block to reduce the risk of cardiovascular accidents in coronary heart disease.Methods:80 patients with cardiovascular risk factors in Songshan Hospital of Chifeng were selected,and the time span would cover from October 2022 to June 2024,with 80 cases of elective surgery and combined coronary heart disease.They will be randomly divided into blocked groups and conventional groups,40 cases each.Conventional block was performed after anesthesia in patients in the conventional group,and planetary ganglion block was performed after anesthesia in patients in the blocked group.The cardiovascular responses of patients in the two groups were observed,and the number of intraoperative cardiovascular active drugs and the occurrence of cardiovascular adverse events were recorded in patients in the two groups.Results:Analysis of the mean arterial pressure(MAP)and heart rate(HR)values of the two groups of patients at the time points before anesthesia(T0),the moment of tracheal intubation(T1),the moment of surgical skin cutting(T2),the end of the operation(T3),and the 6h postoperative period(T4)showed that the MAP and HR of the blocked group were lower than those of the conventional group at the time points of T1 to T4,and the differences in MAP and HR values of the two groups in different time points compared with the T0 time point were statistically significant(P<0.05)and the differences in cardiovascular response(P<0.05)were statistically significant(P<0.05).significance(P<0.05).The number of intraoperative cardiovascular active drugs used in the blocked group was shorter than that in the conventional group,and the incidence of cardiovascular adverse events was lower than that in the conventional group,with a statistically significant difference(P<0.05).Conclusion:By implementing preoperative ultrasound-guided stellate ganglion block in patients with cardiovascular risk factors,the frequency and degree of coronary heart disease symptoms will be reduced,thus reducing the risk of patients,which is worth promoting.

Exploring the Factors Associated with 12-Month Non-Return to Work among Motorcyclists Involved in Road Accidents

Introduction: Motorcyclists bear a disproportionate burden of morbidity and mortality from road accidents. In addition, the consequences of these accidents affect the ability of victims to return to work. This study aimed to determine the prevalence and factors associated with non-return to work among surviving motorcyclists involved in road accidents 12 months after the event. Materials and Methods: It was a cross-sectional study conducted using data from a cohort of motorcyclists involved in accidents and recruited in five hospitals in Benin from July 2019 to January 2020. The dependent variable was non-return to work 12 months after the accident (yes vs no). The independent variables were categorized into two groups: baseline and 12-month follow-up variables. Logistic regression was used to determine the factors associated with non-return to work at 12 months among the participants. Results: Among the 362 participants, 55 (15.19%, 95% CI = 11.84 - 19.29) had not returned to work 12 months after the accident. Risk factors for non-return to work identified were: smoking (aOR = 4.41, 95% CI = 1.44 - 13.56, p = 0.010), hospitalization (aOR = 2.87, 95% CI = 1.14 - 7.24, p Conclusion: The prevalence of non-return to work at 12 months was high among surviving motorcyclists involved in road accidents in Benin. Integrated support for patients based on identified risk factors should effectively improve their return to work.

Conceptual Strategy for Mitigating the Risk of Hydrogen as an Internal Hazard in Case of Severe Accidents at Nuclear Power Plant Considering Existing Risks and Uncertainties Associated with the Use of Traditional Strategies

Hydrogen challenge mitigation stands as one of the main objectives in the management of severe accidents at Nuclear Power Plants (NPPs). Key strategies for hydrogen control include atmospheric inertization and hydrogen removal with Passive Autocatalytic Recombiners (PARs) being a commonly accepted approach. However, an examination of PAR operation specificity reveals potential inefficiencies and reliability issues in certain severe accident scenarios. Moreover, during the in-vessel stage of severe accident development, in some severe accident scenarios PARs can unexpectedly become a source of hydrogen detonation. The effectiveness of hydrogen removal systems depends on various factors, including the chosen strategies, severe accident scenarios, reactor building design, and other influencing factors. Consequently, a comprehensive hydrogen mitigation strategy must effectively incorporate a combination of strategies rather than be based on one strategy, taking into consideration the probabilistic risks and uncertainties associated with the implementation of PARs or other traditional methods. In response to these considerations, within the framework of this research it has been suggested a conceptual strategy to mitigate the hydrogen challenge during the in-vessel stage of severe accident development.

Child Victims of Road Traffic Accidents: Epidemiological and Clinical Aspects in the Medical and Surgical Emergency Department of the Donka National Hospital

Introduction: Children involved in road accidents most often suffer head or limb injuries. The severity of these injuries varies according to the age of the child, the type of road user and whether or not protective devices are used. The aim of this study was to carry out a census of admissions and to identify the epidemiological and clinical profile of children involved in road traffic accidents at Donka National Hospital. Methods: This is a descriptive cross-sectional study of children involved in traffic accidents over a 3-month period from September 1 to November 30, 2021. All children admitted to the emergency department for a traffic accident were included in the study. Results: During the study period, 435/530 children (82.1%) were victims of road accidents. Boys accounted for 54.94% of cases, compared with 45.06% for girls. The age group most affected was 12-17 years old (48.97%). October had the highest accident rate (36.4%). Pedestrians are most affected (52.87%). Bicycles and mopeds were involved in 59.77% of accidents. Head injury was the most frequent pathology (33.33%). The study showed that 12.64% of victims were referred to intensive care, pediatric surgery, etc. We recorded 8 cases of death (1.84%). Conclusion: This study highlighted the characteristics, incidence and risk factors for accidents in children admitted to emergency departments. Accident prevention, particularly serious accidents in children, requires more precise knowledge of the factors and circumstances leading to their occurrence.

Characteristics of coal resources in China and statistical analysis and preventive measures for coal mine accidents

In the process of green and smart mine construction under the context of carbon neutrality,China's coal safety situation has been continuously improved in recent years.In order to recognize the development of coal production in China and prepare for future monitoring and prevention of safety incidents,this study mainly elaborated on the basic situation of coal resources and national mining accidents over the past five years(2017-2021),from four dimensions(accident level,type,region,and time),and then proposed the preventive measures based on accident statistical laws.The results show that the storage of coal resources has obvious geographic characteristics,mainly concentrated in the Midwest,with coal resources in Shanxi and Shaanxi accounting for about 49.4%.The proportion of coal consumption has dropped from 70.2%to 56%between 2011 and 2021,but still accounts for more than half of the all.Meanwhile,the accident-prone areas are positively correlated with the amount of coal production.Among different levels of coal mine accidents,general accidents had the highest number of accidents and deaths,with 692 accidents and 783 deaths,accounting for 87.6%and 54.64%respectively.The frequency of roof,gas,and transportation accidents is relatively high,and the number of single fatalities caused by gas accidents is the largest,about 4.18.In terms of geographical distribution of accidents,the safety situation in Shanxi Province is the most severe.From the time distribution of coal mine accidents,the accidents mainly occurred in July and August,and rarely occurred in February and December.Finally,the"4+4"safety management model is proposed,combining the statistical results with coal production in China.Based on the existing health and safety management systems,the manage-ments are divided into four sub-categories,and more specific measures are suggested.

Stress perceptions of nurses serving in home healthcare services during the COVID-19 pandemic:A qualitative research

Objective:To investigate the stress perceptions of nurses serving in home healthcare services during COVID-19.Methods:This study was qualitative research with a phenomenological design.Data were collected and recorded through in-depth interviews with 6 nurses working in MuşState Hospital,Home Healthcare Services Unit using a form consisting of 12 questions on an online platform between May 2021 and July 2021.The audio recordings were transcribed by the researcher and content analysis was performed by creating codes,categories,and themes.Results:The interviews yielded 10 categories and 59 sub-codes.These codes were addressed under the theme of"COVID-19 pandemic".Under this main theme,nurses expressed the problems they experienced in issues such as stress,support mechanisms,and family and social problems during COVID-19.They mentioned that they experienced high stress in this process,as well as social isolation and negative thoughts of society about them and that they could not spare time for themselves and their families.Conclusions:Nurses working in home healthcare services frequently express negativities such as high stress,isolation from society,and increased workload.Therefore,actions should be taken to raise awareness of society on these issues,increase the number of personnel,conduct more research,and share the results with the public.

Sleeping Conditions of Older Adults with Delirium Receiving Home Care

We aimed to clarify the sleep status before delirium onset among older adults receiving home care. The sleep status of 21 participants aged ≥65 years was monitored while they slept with a sensor placed under their bedding, after ruling out insomnia and dementia. The incidence of delirium was 28.6%;delirium onset occurred within an average of 2.7 (SD = 12) days after the start of home care among those whose care environment was changed due to hospital discharge or moving. Increased interrupted sleep and activity during sleep indicated that sleep fragmentation occurred before delirium onset. In conclusion, individuals aged ≥65 years and those whose care environment has changed should be screened for delirium because the time to delirium onset is short. Further, interventions to monitor the sleep status and prevent delirium onset should be implemented from the day home care begins.

Epidemioclinical Aspects of Childhood Domestic Accidents in the Emergency Department of Boffa Hospital

Introduction: Domestic accidents are defined as accidents that occur in the home or its immediate surroundings. Objective: To describe the epidemioclinical and therapeutic aspects. Patients and Methods: Prospective, descriptive study from July 1, 2019 to June 30, 2020 in the emergency department of Boffa prefectural hospital included all children aged 0 to 15 years admitted for domestic accidents. Results: Of 120 cases of accidental trauma, 56 were domestic accidents. The mean age was 7.08 years. The 0 - 5 and 11 - 15 age groups were the most represented (35.71%). The sex ratio was 1.55 in favor of boys. Domestic accidents were represented by falls (26.78%), thermal burns (21.43%), snakebite wounds (17.86%) and dog bites (10.71%), drowning (5.36%), and electrification by lightning (3.60%), one case or 1.78% of each of the following: esophageal foreign body by palm nut, firearm, wall collapse, stretching of upper limb. Paracetamol was the molecule most frequently used (89.28%). The outcome was favorable in 92.86% of cases. However, four (4) deaths were recorded. Conclusion: Domestic accidents remain a significant pathology at Boffa prefectural hospital.

Smart Home IoT Privacy and Security Preservation via Machine Learning Techniques

The development and use of Internet of Things(IoT)devices have grown significantly in recent years.Advanced IoT device characteristics are mainly to blame for the wide range of applications that may now be achieved with IoT devices.Corporations have begun to embrace the IoT concept.Identifying true and suitable devices,security faults that might be used for bad reasons,and administration of such devices are only a few of the issues that IoT,a new concept in technological progress,provides.In some ways,IoT device traffic differs from regular device traffic.Devices with particular features can be classified into categories,irrespective of their function or performance.Ever-changing and complex environments,like a smart home,demand this classification scheme.A total of 41 IoT devices were employed in this investigation.To build a multiclass classification model,IoT devices contributed 13 network traffic parameters.To further preprocess the raw data received,preprocessing techniques like Normalization and Dataset Scaling were utilized.Feature engineering techniques can extract features from the text data.A total of 117,423 feature vectors are contained in the dataset after stratification,which are used to further improve the classification model.In this study,a variety of performance indicators were employed to show the performance of the logiboosted algorithms.Logi-XGB scored 80.2%accuracy following application of the logit-boosted algorithms to the dataset for classification,whereas Logi-GBC achieved 77.8%accuracy.Meanwhile,Logi-ABC attained 80.7%accuracy.Logi-CBC,on the other hand,received the highest Accuracy score of 85.6%.The accuracy of Logi-LGBM and Logi-HGBC was the same at 81.37%each.Our suggested Logi-CBC showed the highest accuracy on the dataset when compared to existing Logit-Boosted Algorithms used in earlier studies.

Intelligent Energy Consumption For Smart Homes Using Fused Machine-Learning Technique

Energy is essential to practically all exercises and is imperative for the development of personal satisfaction.So,valuable energy has been in great demand for many years,especially for using smart homes and structures,as individuals quickly improve their way of life depending on current innovations.However,there is a shortage of energy,as the energy required is higher than that produced.Many new plans are being designed to meet the consumer’s energy requirements.In many regions,energy utilization in the housing area is 30%–40%.The growth of smart homes has raised the requirement for intelligence in applications such as asset management,energy-efficient automation,security,and healthcare monitoring to learn about residents’actions and forecast their future demands.To overcome the challenges of energy consumption optimization,in this study,we apply an energy management technique.Data fusion has recently attracted much energy efficiency in buildings,where numerous types of information are processed.The proposed research developed a data fusion model to predict energy consumption for accuracy and miss rate.The results of the proposed approach are compared with those of the previously published techniques and found that the prediction accuracy of the proposed method is 92%,which is higher than the previously published approaches.