bluuebunny/crossref_metadata_2025 huggingface dataset:
Lahure Culture and Educational Achievement in the Gorkha Communities in Pokhara Metropolitan City, Nepal
Authors: Gurung Prabin
Published: February 2024

Nepalese societies have a long history of Gurkha Army culture for centuries. There is no question about the role of this culture in enhancing the socioeconomic status of these communities from the past. However, along with its positive aspects, this trend has brought some possible adverse effects on those communities who are directly or indirectly associated with the Gurkha Army recruitment process. This study has aimed to explain the possible impact on education attainment of youth from these communities due to participation in the Army preparation and selection process. For the study explanatory research methods were used, utilizing both quantitative and qualitative data for insightful investigation of the phenomenon, where 184 aspiring youths from different army training centers operated in Pokhara Metropolitan City, Kaski were selected to gather quantitative insights from young individuals from the Gurkha community actively engaged in Army preparation training. Furthermore, qualitative data was collected through Key Informant Interviews (KIIs) conducted with esteemed principals and administrative figures from educational institutions offering class 11 and 12 courses in Pokhara, Kaski. The recruitment process for the Army, particularly among youths from the Gurkha communities, presents a significant challenge to educational pursuits, resulting in a diversion of focus away from academic endeavors. This trend has led to a substantial number of individuals prioritizing military training over education. Consequently, this phenomenon has adversely affected educational attainment, limiting future opportunities for these communities. Additionally, the Gurkha community’s historical involvement primarily in Gurkha recruitment has perpetuated their societal exclusion and marginalization. While self-realization within the Gurkha community is crucial, effective governmental policies promoting inclusive education and opportunities are equally imperative. Collaborative efforts between communities and policymakers are necessary to bridge these disparities, fostering an equitable environment and integration beyond traditional roles.
Factors Affecting Students on Enrollment in Higher Educational Institutions (HEIs)
Authors: K.C. Sudarshan , Maharjan Babita , Maharjan Reena
Published: February 2024

Community colleges are vital to the higher education system in Nepal. A Community college can act as a medium of globalization in today’s competitive world. The community college can be a great asset for local community to contribute higher education at local level.  It has greater contribution to empower the weaker sections of the society through higher education. But the choice of students towards these higher educational institutions is not satisfactory. Majority of the students staying at Kirtipur enroll in colleges specially located in Kathmandu Metropolitan City and Lalitpur Metropolitan City. So, the purpose of this study is to identify the major factors which are attracting students to enroll in private colleges outside Kirtipur.  The study was conducted among 133 students staying in Kirtipur but studying outside Kirtipur Municipality. The result of the study shows academic programs, college fees, educational facilities, quality education and promotion have positive effect on students’ enrollment, location and social factors have no effect on it.
The New Juridical Institutes for the Protection of Persons with Psychosocial Disabilities Introduced by the Romanian Law No. 140/2022
Authors: Florian Radu Gheorghe
Published: February 2024

The institute of placing under the ban was a protection measure applicable in Romania for a very long time, so that it remained ingrained in public perception as the only institute that could be applied to people with mental disabilities likely to affect their discernment. The consequence of the application of this institute emerges from its very name, namely the fact that the person targeted by the “protection” promised by the establishment of the prohibition, in fact acquired the stigma of being “forbidden” in the life of the civil circuit, more precisely, the guardian of the court-ordered banned person was in charge of absolutely all his/her fundamental rights and freedoms, excluding him/her completely from participation in social-economic and legal life.
Comportamiento reproductivo de Chroicocephalus cirrocephalus (Vieillot, 1818) (Charadriiformes: Laridae) y Coragyps atratus (Bechstein‎, 1793) (Cathartiformes: Cathartidae) en el humedal costero humedal de Villa, Lima-Perú
Authors: Amanqui-Aquino Edson , Gordillo-Rodriguez Brenda , Gómez Martinez Lisset , Iannacone Jose
Published: February 2024

El Humedal de Villa, ubicado en Lima, Perú, alberga una notable diversidad faunística, destacando la avifauna. La reproducción de las aves es un elemento crucial para la historia natural de estas especies, siendo esencial estudios para orientar estrategias de conservación y gestión tanto de las poblaciones de aves como de los ecosistemas que habitan. El objetivo de este estudio fue caracterizar y evaluar aspectos reproductivos de la Gaviota de capucha gris [Chroicocephalus cirrocephalus (Vieollot 1818)] y el Gallinazo de Cabeza Negra [Coragyps atratus (Bechstein, 1793)], como la biometría de nidos, huevos y el comportamiento reproductivo. Se realizó el seguimiento de nidos entre los meses de mayo a septiembre del 2023. Para C. cirrocephalus se encontraron 12 nidos en parches de “grama dulce” Paspalum vaginatum Sw.; mientras que, para C. atratus se registraron cuatro nidos en la base de árboles de “molle costeño” Schinus terebinthifolia G. Raddi. Para ambas especies se observó el desarrollo de los polluelos a juveniles. Asimismo, se realizó un etograma de comportamientos para ambas especies, para C. cirrocephalus se registró un total de 40 comportamientos específicos, siendo la categoría de “reproducción y cuidado parental” más importante durante incubación; mientras que, para C. atratus se registró un total de 27 conductas específicas, siendo la categoría “alerta” más importante entre individuos adultos y juveniles.
Implementación de una estrategia de marketing digital para la “tienda pantanera” del humedal pantanos de Villa - Chorrillos, Lima, Perú
Authors: Rubin-Yajahuanca Leonardo , Flores-Salinas Alexandra , Hervias-Principe Anahit , Iannacone Jose
Published: February 2024

Se evaluó la implementación de la estrategia digital de marketing para la “Tienda Pantanera” del humedal Pantanos de Villa, Lima, Perú. Se realizó una encuesta semiestructurada al público objetivo conformado por dos segmentos: personas que residen en los distritos cercanos al humedal y tienen interés sobre el turismo y el medio ambiente, y a un público general que está conformado por jóvenes con acceso a un nivel educativo superior universitario. Los resultados en relación a la estrategia digital de marketing señalan que la tienda y el catálogo en línea de los productos de la Tienda Pantanera deben ser de fácil uso. Las opciones de pago deben ser seguras y de fácil acceso. El pago en línea debe realizarse por medio de la afiliación a bancos seguros en el mercado nacional, y a los aplicativos como Yape y Plin. La propuesta de implementación de una estrategia digital de marketing para la “Tienda Pantanera” se basa en la interacción de los visitantes del humedal Pantanos de villa y los medios digitales, como las redes sociales. Esta implementación ayudará a obtener mayores oportunidades, promociones y ventajas para el público. Finalmente, deben facilitarse mecanismos para concretar mayores ventas, logrando una mayor interacción y fidelización del público con respecto a la “Tienda Pantanera”.
MEU ÁLBUM PITORESCA PELO SERTÃO
Authors:   PPGG  e PPGPatri/UFPA, CNPQ, ABC, Costa Marcondes
Published: February 2024

This article in the form of an album reports the day-to-day life of the Viagem Pitoresca Pelo Sertão through images and short text, which was carried out from the 5th to the 12th of November 2023,
IMPACT OF HIGH TEMPERATURE ON THE PROPAGATION SPEED OF ULTRASONIC WAVES IN STRONG ROCK FORMATIONS
Authors: Bilobrov Dmytro , Vapnichna Viktoriia
Published: February 2024

Purpose: The purpose of the research is to establish the relationship between the velocity of ultrasonic waves in Lesnik, Maslav granites, Bukinsky gabbro, and Kateryniv labradorite at temperatures up to 800 degrees.

Methods: In this study, samples of natural stone from the following rocks were heated: Maslav granite, Lesnik granite, Kateryniv labradorite, and Bukinsky gabbro. The samples were made in the form of cubes with a side size of 15×15 cm. One side of the sample was polished and the other sides were sawn. Measurements of ultrasonic wave propagation were made on the polished side. The samples were heated to temperatures of 200, 400, 600, and 800 degrees Celsius. Three cubes were taken for each temperature. Before heating, the velocity of ultrasonic waves in the samples of natural stone was measured using a handle with two piezoelectric sensors with a base of 120 mm. The ultrasonic wave was measured using a UK-14PM device. The velocity of ultrasonic wave propagation in the stone samples after heating was also measured. The velocity of ultrasonic wave propagation was calculated from the time it takes the ultrasonic wave to pass between the sensors.

Results: In this research, the authors consider the effect of high temperature on the velocity of ultrasonic waves in granites, gabbro, and labradorite. The article provides an overview of the main factors that affect the velocity of ultrasonic wave propagation in natural stone. The results of studies conducted to investigate the effect of high temperature on this velocity in strong rocks are considered. The relationship between the velocity of ultrasonic wave propagation in Lesnik, Maslav granites, Bukinsky gabbro, and Kateryniv labradorite at temperatures up to 800 degrees has been established. Lesnik granite has the least loss of ultrasonic wave velocity upon heating, while Maslav granite has the greatest loss. When comparing labradorite and gabbro, labradorite has the least loss of ultrasonic wave velocity upon heating.

Scientific novelty: For the first time, the dependence of the velocity of ultrasonic wave propagation in Lesnik, Maslav granites, Bukinsky gabbro, and Kateryniv labradorite at temperatures up to 800 degrees from the heating temperature has been obtained.

Practical significance: Based on the obtained values, it is possible to assess the strength of natural stone after fires using a non-destructive control method.

Keywords: high temperature, ultrasonic wave, natural stone, rock-forming minerals, color.
Feminist Approaches in Counselling Psychology: Empowering Women's Mental Health
Authors: Adebayo Abidogun Moruf
Published: February 2024

This paper explores the application of feminist approaches in counselling psychology to empower women's mental health. It highlights the importance of considering gendered experiences, power dynamics, and societal influences on women's well-being. By examining the existing literature, this article identifies the key principles and interventions of feminist counselling psychology and their impact on women's empowerment. The paper concludes with recommendations for integrating feminist perspectives into counselling practices to promote positive mental health outcomes for women.
Improving Women's Health in the 21st Century: Current Challenges, Medical Advancements and Future Prospects
Authors: Samson Enitan Seyi
Published: February 2024

The field of women's health covers various physical, emotional, and social aspects. In recent years, there has been a growing recognition of the importance of improving women's health. Women face a plethora of problems including infertility, cancer, diabetes, depression, and cardiovascular disorders amongst others. These health problems are compounded with gender disparities, lack of access to healthcare, denials of reproductive rights, aging and poverty. To surmount these challenges, comprehensive approaches, including improved access to healthcare, awareness programs, mental health support, and addressing gender bias and environmental health concerns are required. Precision medicine has the potential to transform outcomes for women with chronic and genetic diseases. Digital technologies have revolutionized healthcare access and monitoring for women, enabling remote consultations and self-monitoring of health conditions. Advancements in breast and cervical cancer screening, such as digital breast tomosynthesis (DBT) and Human Papillomavirus (HPV) testing, have improved early detection and prevention. While there is still work to be done in addressing the challenges and disparities in women's health, these medical advancements offer hope for improved outcomes and better quality of life for women. Continuous research, awareness and policy adjustments are still needed to promote woman's health on a global scale in the future.
The Role of First Trimester Ultrasound in the Detection of Vasa Previa: a Systematic Review
Authors: De Vocht Karlijn
Published: February 2024

Vasa previa is a rare disorder in which fetal blood vessels are left unprotected in the membranes and cross the internal os of the cervix. The risk of vessel tearing causing antepartum bleeding and fetal death due to exsanguination is highly increased. Prenatal detection drastically improves fetal outcome. The aim of this study is to scrutinize the recent evidence for the use of first trimester prenatal ultrasonography to improve the detection of vasa previa. We conducted a systematic literature review in the computerized databases Pubmed, Embase, CINAHL and Web of Science from inception to September 2022. Two first trimester sonographic markers are associated with vasa previa later in pregnancy: umbilical cord insertion in the lower one-third of the uterine cavity and a velamentous insertion. We conclude the evaluation of the umbilical cord insertion in the first trimester is feasible, not time-consuming and may identify the population at increased risk for vasa previa.
Forms of Breast Disorders within Females Visiting Breast Disease Clinic
Authors: Abd Elhamied Hany Mahmoud
Published: February 2024

1.1. Background: Breast disorders, either benign or malignant in nature, are clinically common. The forms of breast disorders vary within different nations. 1.2. Objectives: The goal of the current research study is to explore and observe the forms of breast disease and their correlation with various obtained variables of interest in females visiting the breast disease clinic. 1.3. Methodology: A cross-sectional research study performed at El Sahel Teaching Hospital from 1st of May 2017 till 1st of February 2017. A randomly selected cohort of 500 research subjects of all age categories have been enrolled in the research study. The cases have been cat- egorized according to their clinical diagnosis into 3 classes of breast conditions: normal, benign and malignant. The statistical significance was <0.05. 1.4. Results: breast disorders of benign nature diagnosed among (63%) of cases while breast dis- eases of malignant nature composed of (13.2%). The commonest clinical presentation have been mastalgia and breast mass (39.2%), mastalgia (37.6%), and breast mass only (23.2%). Fibro- adenoma (26.2%) has been the most common benign clinical disease with greatest incidence (76.9%) in the age research group below 20 years. Malignant breast diseases have been more frequent with increasing age. Benign breast clinical disorders and pathological lesions were correlated more with nulliparous females (p<0.001). Breast cancer observed (p <0.001) more frequent in a statistically significant fashion with in lactating females recruited in the research cohort. 1.5. Conclusion: Benign diseases and various disorder of the breast is a popular clinical di- agnosis mostly presented in younger females. Breast malignant disease despite the fact that is clinically diagnosed in lower frequency and mainly presented in older age groups, yet its sig- nificance oblige a meticulous evaluation of females of various clinical presentations particularly that of breast mass only or associated with mastalgia.
Evaluation of Cholecalciferol Interaction with Pain Signaling after Laparoscopic Ablation of Endometriotic Lesions in Women with Hypovitaminosis D
Authors: Abd Elhamied Hany Mahmoud
Published: February 2024

Aim: The study's goals were to ascertain the subjective cure rate and the safety of giving cholecalciferol to women with hypovitaminosis D after ablative operations to relieve pain associated with endometriosis. Patients and Methods: We enrolled participants in this double-blind clinical trial who had endometriosis diagnosed and treated by laparoscopy and who had at least three dysmenorrhea and/or pelvic pain scores at eight weeks following surgical therapy. They were given either a placebo or vitamin D (50 000 IU each week for 12 weeks). At 6 months following surgical therapy, the VAS test was used to assess the pain intensity between the two groups (placebo and treatment). Results: Twenty patients were in the vitamin D group and twenty were in the control group. Both groups shared common traits that were analogous. After administering vitamin D or a placebo, there were no discernible differences between the two groups in the severity of the dysmenorrhea and pelvic pain scores (p>0.05). Mean pelvic discomfort at six months following laparoscopy was 3.2 ±1.6 in the vitamin D group and 3.7 ±1.1 in the placebo group (p>0.05). Mean dysmenorrhea score in the vitamin D group was 3.4±1.2, while it was 3.1±1.8 in the placebo group. The mean pain scores in the two groups did not differ significantly from one another (p>0.05). Conclusion: Treatment with vitamin D did not significantly reduce dysmenorrhea or pelvic discomfort after ablative surgery for endometriosis.
Mekanisme Kinerja Air Purifier Dalam Upaya Pencegahan Polusi Udara
Authors: Wahyuningtyas Denisa Tri , Sudarti Sudarti , Yushardi Yushardi
Published: February 2024

Jumlah polusi udara yang dihasilkan oleh aktivitas masyarakat meningkat ketika aktivitas masyarakat tersebar sepanjang hari di dalam ruangan, seperti di rumah, tempat kerja, sekolah, kampus, dan bangunan lainnya. Kita mungkin tidak menyadari bahaya polusi udara dalam ruangan terhadap kesehatan kita namun hal ini dapat menyebabkan sejumlah masalah, terutama di ruangan dengan sirkulasi udara yang buruk.. Air purifier adalah alat yang dapat membantu mengurangi polusi udara dengan cara menyaring udara yang berada di dalam ruangan tersebut. Air purifier dipercaya memiliki peranan penting dalam menjaga kualitas udara dalam ruangan dengan mengurangi partikel-partikel udara yang kecil seperti asap dan debu. Tujuan dari penelitian ini adalah untuk mengetahui mekanisme kerja dari alat Air purifier atau alat penyaring udara, sebagai bentuk upaya untuk mengurangi polusi udara yang sering menjadi permasalahan buruknya kualitas udara di kota-kota besar. Selain itu air purifier bermanfaat untuk membuat udara yang ada di dalam ruangan menjadi bersih dan segar. Udara yang bersih akan membuat kita terhindar dari berbagai penyakit, terutama penyakit pada saluran pernafasan.
АНАЛІЗ ДЕРЖАВНОЇ ПІДТРИМКИ ПРИРОДООХОРОННИХ ЗАХОДІВ: ПРОБЛЕМИ ФІНАНСУВАННЯ БЮДЖЕТНИХ ПРОГРАМ
Authors: ЛАБЕНКО Олександр , САФОНИК Олександр
Published: February 2024

У статті вивчено проблеми фінансування бюджетних програм природоохоронних заходів в Україні. З’ясовано, що відповідно проблеми можуть виникати з різних причин, а саме: недостатність фінансування; нестабільність фінансування; низький рівень ефективності витрат; відсутність прозорості та обліку; низька залученість бізнесу та громадськості; відсутність системи стимулювання; неадекватна реакція на екологічні виклики; зміни в політичній сфері; нестабільність економічної ситуації; неефективне планування і прогнозування; корупційні ризики. Охарактеризовано капітальні інвестиції на охорону навколишнього природного середовища за напрямами. Встановлено, що для вирішення цих проблем необхідно акцентувати увагу на удосконаленні бюджетного процесу, впровадженні ефективних механізмів контролю, підвищенні прозорості та відповідальності в управлінні фінансовими ресурсами.
Konsep Pendidikan Seks Terhadap Remaja (Analisis Buku Pendidikan Seks untuk Anak dalam Islam Karya Yusuf Madani)
Authors: Handayani Indah , Umam Ahmad Khotibul , Kurnaengsih Kurnaengsih , Ali Muhammad
Published: February 2024

Pendidikan seks tentu akan sering kali dianggap sebagai upayah memberikan pengetahuan biologis, psikologis, hingga psikoseksual. Nah rentang usia remaja itu adalah 10 tahun sampai 21 tahun menurut beberapa ahli. Fase remaja adalah fase peralihan dari fase anak-anak menuju masa dewasa. Berdasarkan realitas diatas, peneliti dapat merumuskan masalah yang akan dikaji dalam penyusunan skripsi ini meliputi : pertama, bagaimana konsep pendidikan seks terhadap prespektif Islam?. Kedua, bagaimana konsep pendidikan seks terhadap remaja Meurut Yusuf Madani?.Penyusnan skripsi ini dibuat untuk mengetahui dan memahami konsep pendidikan seks terhadap prespektif Islam dan untuk mengetahui konsep pendidikan seks terhadap remaja Menurut Yusuf Madani. Adapun jenis penelitian ini ialah penelitian pustaka (Library research). Sumber data primer dalam penelitian ini diperoleh dari karya Yusuf Madani dalam bukunya Pendidikan seks terhadap remaja, dan data sekunder. Adapun kesimpulan dari penelitian ini adalah bahwa pendidikan seks itu wajib diberikan oleh keluarga (orangtua) atau guru berdasarkan kaidah-kaidah preventif seksual.
Peranan Psikologi Pendidikan untuk Pencegahan Perundungan Siswa Sekolah Dasar
Authors: Damayanti Pelangi Dea Sri , Handayani Fitri , Ramahwati Yuli , Suhernah Suhernah , Cahyani Anisa Dian , Tilova Martina Hikmah
Published: February 2024

Bullying merupakan istilah untuk tindakan kekerasan atau penindasan yang dilakukan oleh pihak yang lebih kuat baik dari segi umur, kekuatan, kekuasaan kepada pihak yang lemah. Bentuk dari perilaku bullying yaitu bullying fisik, bullying verbal dan bullying mental/psikologis yang dapat ber dampak buruk kepada korbannya, seperti lebam, luka, sakit, penakut, dan lain sebagainya dan untuk jangka panjang yaitu terganggunya kondisi psikologis dan penyesuaian sosial yang buruk. Peran psikologi pendidikanKonselor memiliki peranan penting dalam mencegah dan menanggulangi bullying di sekolah, untuk itu diperlukan pelayanan yang efisien dan komprehensif ke pada seluruh siswa dengan menggunakan berbagai keterampilan dan media yang dapat membantu kinerja psikologi pendidikan dalam menangani bullying.
Konsep danTujuan Pendidikan Islam Dalam Perspektif Tafsir Al-Qur’an Surat Al-Baqoroh
Authors: Muhazzaroh Fauziyatun
Published: February 2024

Penulisan karya tulis ini bertujuan untuk membedah atau menafsirakan surat Al-Baqoroh ayat 151 dalam kontesk untuk mengetahui isi kandugan dari ayat tersebut dan sebagai pelajaran kita dalam mempelajari ilmu tafsir dan untuk diterapkan dalam dunia nyata. Penelitian ini menggunakan dmetode kualitatif dengan jenis studi pustaka. Adapun yang menjadi latar belakang penulisan ini karena di dalam penafsiran surat Al-Baqoroh ayat 151, seorang muslim tidak cukup hanya dengan menyatakan keislamannya tanpa berusaha untuk memahami islam dan mengamalkannya. Pernyataan ini harus di buktikan dengan melakanakan konsekuensi dari islam,karna itu kita membutuhkan ilmu. menuntut ilmu itu wajib bagi setiap muslim maupun muslimah.
Microcrédito y finanzas de corto plazo en los supermercados
Authors: Melo Delgado María Paula , Escobar Quiroz Mario Javier , Delgado Bolívar Arturo
Published: February 2024

El presente artículo da a conocer la profundización sobre el caso real de los microempresarios adscritos al subsector ‘Supermercados’ de la ciudad de Pasto, teniendo como base los fundamentos teóricos de Vélez (2010), Núñez (2016), Gitman y Zutter (2012), entre otros. Mediante el uso del microcrédito como fuente de financiamiento, el desarrollo de los microempresarios se vería impulsado, ya que les permite adquirir recursos en cantidades reducidas de capital para promover proyectos productivos; así, el crecimiento económico tanto nacional como regional también percibiría cierto beneficio.
Estrategias para emprendedores sector restaurantes comuna 1 ciudad de Pasto en tiempos de COVID
Authors: Marcillo Popayán Jenny Andrea , Toro Díaz Alba Elizabeth , Solarte Solarte Claudia Magali
Published: February 2024

El sector de los restaurantes fue uno de los más afectados por la pandemia del COVID-19, obligando a varios establecimientos a encontrar nuevas estrategias para poder mantenerse en el mercado; algunos no contaron con tanta suerte y tuvieron que cerrar sus puertas, ya que no había recursos financieros para mantenerse. Con la presente investigación se quiere abordar aspectos elementales sobre cómo fue el impacto de la crisis hacia los negocios y cómo los empresarios afrontaron este hecho tan difícil, trayendo consigo varios retos a los cuales poco a poco tuvieron que irse adaptando con los nuevos cambios.

La investigación identifica que la implementación de las estrategias comerciales es de suma importancia, ya que ellas permiten atraer nuevos clientes y la fidelización de los clientes actuales; y más, en dicha época que fue una situación complicada para este sector.

A través de un estudio minucioso y detallado se pretende identificar cuáles fueron las estrategias que los empresarios decidieron implementar para la ejecución de las actividades dentro de las organizaciones, tomando como punto de partida, la recolección de información y, poder evaluar si realmente las estrategias han tenido resultado para que las empresas hayan logrado mantenerse y poder, en el largo plazo, implementar otras estrategias que contribuyan al crecimiento y les permitan estar preparadas ante cualquier evento inesperado.

Finalmente, el desarrollo e implementación de las estrategias comerciales permitirá que los emprendedores puedan sobresalir en el mercado, ayudándoles a hacer un mejor seguimiento en la gestión comercial en todo su proceso como empresarios.
Low-cost IoT-enabled indoor air quality monitoring systems: A systematic review
Authors: Peixe João , Marques Gonçalo
Published: February 2024

Indoor air quality (IAQ) is a critical challenge much less controlled in comparison with outdoor air quality. Bad IAQ is related to significant health complications such as respiratory problems, heart disease, and cancer. Many people spend most of their days inside buildings and don’t have air quality monitoring systems. Therefore, the occupants don’t know when the space has a higher quantity of pollutants than recommended, saturating the environment, and compromising people’s health. This is a problem that can be addressed by using Internet of Things (IoT) technologies to develop monitoring systems that allow a greater number of possibilities regarding the storage and processing of data and access to information by the end user, assisting the decision-making process regarding the indoor air pollution problem. Real-time data can be compared to default values, alerting the user of that situation, and suggesting an action to decrease the air pollutants concentration. There already are multiple solutions involving IoT-based technologies, many of them using low-cost sensors. Those are analyzed in this systematic review. Furthermore, the COVID-19 pandemic pointed out the importance of IAQ monitoring to evaluate the risk of contamination. The microcontrollers, IAQ parameters, sensors, data storage and visualization methods used in monitoring systems have been analyzed. The results show that most of the studies store data in Cloud systems and use Web platforms for data consulting. However, sensor calibration and efficient energy consumption are challenges that still exist.
Power AGC Allocation Method Based on Genetic Algorithm
Authors: Luo Zhibin , Shen Qihua , Li Kuanting
Published: February 2024

To realize the optimal allocation and target controllability of automatic generation control (AGC) regulation capacity, an AGC allocation method based on genetic algorithm(GA) is proposed. Firstly, the basic principle of AGC is analyzed, and the mathematical model of unit allocation to find the optimal solution under constraints is provided. Then, GA is tentatively applied to the allocation of a AGC unit, and the crossover and mutation are performed according to the capacity segment and state segment respectively. Combined with the priority method, the continuous variables in the model are processed to improve the convergence performance of AGC. The example of the actual system shows that our method can overcome the disadvantage that the integer programming method may not acquire the optimal solution, and achieve a certain economy, which also provides a new and effective strategy for the allocation of AGC units.
Human Motion Data Acquisition System of Intelligent Motion Bracelet Based on Human-Computer Interaction
Authors: Wang Mei
Published: February 2024

In order to improve the accuracy of human motion data acquisition and reduce the time-consuming of data acquisition, an intelligent motion Bracelet human motion data acquisition system based on human-computer interaction is proposed and designed. Firstly, the overall architecture of the system is designed, mainly including application layer, transmission layer and perception layer. Secondly, the system hardware is designed, mainly including the motion data acquisition module, temperature acquisition module and ZigBee wireless transmission module of human-computer interaction intelligent sports bracelet, so as to ensure the realization of the system function. Finally, in the part of system software design, wavelet transform is used to discretize the collected human motion data and divide the attributes, so as to improve the availability of the data. The experimental results show that compared with the traditional motion data acquisition system, the designed system has higher acquisition accuracy and shorter time-consuming.
Improved Human Resource Allocation Method Based on Genetic Algorithm
Authors: Wang Lianying
Published: February 2024

In order to improve the convergence of the algorithm and the utilization of human resources, a new human resources allocation optimization method based on improved hybrid genetic algorithm is proposed in this paper. Firstly, according to the relationship between post demand and human resources, the objective function of human resources allocation optimization is constructed. Secondly, the principle of traditional hybrid genetic algorithm is analyzed, and tabu search algorithm is introduced to improve the traditional hybrid genetic algorithm. Finally, the improved hybrid genetic algorithm is used to solve the objective function to complete the optimization of human resource allocation. The experimental results show that compared with the traditional optimization methods, the convergence of this method is better, and the utilization rate of human resources is significantly improved, which is always maintained at the level of more than 92%.
Power Resource Allocation in Industrial Park Based on Edge Computing
Authors: Lv Chao , Yan Hui , Long Yunxin , Shi Yaqi , Li Zhanlin , Yu Ping
Published: February 2024

At present, the industrial park has problems such as complex and unbalanced electricity consumption and low utilization rate of electricity resources. When the load is peak, the power supply of the electrical equipment is insufficient, which seriously affects the production quality of the park. In order to solve the problems of peak-to-valley difference and insufficient power resources, this paper proposes a power resource allocation method based on edge computing. This method adjusts the power scheduling by the power consumption duration of the flexible load, establishes the power resource allocation model, and solves it with the improved particle swarm algorithm (I-PSO), that is, the roulette algorithm is introduced into the particle swarm algorithm. Through simulation verification, it is concluded that the industrial park based on edge computing has higher utilization of power resources, reduces electricity consumption cost, and achieves the goals of efficiency reallocation power resources, reducing carbon emissions.
Neural Network Prediction Model for Transmission Line Icing in Freezing Rain Conditions Based on Multi-Source Data Fusion
Authors: Gu Xiaosong , Liu Jian , Yuan Yongzhe , Qu Jiayi
Published: February 2024

Icing on transmission lines can have severe impacts on the power system, making accurate prediction of icing conditions under freezing rain of great significance. This paper proposes a neural network prediction model for transmission line icing based on multi-source data fusion. Firstly, a physical model of transmission line icing considering meteorological factors is established, and icing data is simulated using historical meteorological data. Meanwhile, limited actual icing observation data is collected. Combining these two types of data as the training set, meteorological parameters such as temperature and precipitation are used as inputs, and the amount of transmission line icing is used as output to construct a multi-layer neural network for training, while incorporating physical constraint conditions. This study provides an effective learning framework for accurately predicting transmission line icing under freezing rain conditions.
An Agent-Based Retrieval System for Ideological and Political Course Resources
Authors: He Tian , An Yingxuan
Published: February 2024

Aiming at the characteristics and requirements of ideological and political curriculum resource sharing, this paper introduces Agent model and Hadoop technology to design a course resource retrieval system. This scheme follows the idea of layered architecture and the Hadoop framework is adopted to establish the entire platform. Based on the distributed environment of resource services, intelligent agent technology is introduced to implement personalized web information services. The structure of various agents in the system is explained, and the implementation methods of each functional module are described. The platform test and analysis results show that our method realizes the information management of ideological and political education and the circulation and sharing of high-quality educational resources. The Agent-based system architecture solves the problem of balancing full search and precision search in traditional information retrieval effectively and it also improves the agility of resource response and user experience.
Oral English Course Online Recommendation System Based on Support Vector Machine
Authors: Yang Yujie , Yuan Gang
Published: February 2024

Aiming at the problems of existing oral English online teaching system that the course recommendation model is not accurate enough, which leads to the low accuracy of system recommendation. This article improves the shortcomings of collaborative filtering algorithms and designs an online course recommendation system based on KNN-SVM. The course recommendation model is based on the similarity between the curriculum and student behavior recommended lesson list which is generated from the student, the history of collecting data, and the interaction of the user. Then, KNN is used to perform secondary clustering on user and topic matrices, and support vector machine cross validation is used for final classificationThe average accuracy of the oral English online education course recommendation system in this paper is 57.926%, 45.391% and 44.399%, respectively, compared with the other two kinds of course recommendation systems, indicating that the designed oral English online education course recommendation system has better effect after combining artificial intelligence technology.
A Software Code Infringement Detection Scheme Based on Integration Learning
Authors: Qin Meng
Published: February 2024

A software code plagiarism detection scheme based on ensemble learning is designed to address the issue of low accuracy in traditional abstract syntax tree based software code infringement detection methods. We adopt the AST structure of the code to integrate domain partitioning in IR with AST, and use a weighted simplified abstract syntax tree to design feature extraction and similarity calculation methods, to achieve partial detection of semantic plagiarism and calculate the similarity between text and source code. Then, the feature set of the known classification training set is placed into a random forest based ensemble classifier for training, and an association between error rate and the classification effect of the decision tree in the random forest are proposed to acquire feature node matching with the feature in the code base. The experimental results show that our scheme has higher accuracy than traditional detection methods based on abstract syntax trees. It can not only detect code similarity, but also provide the types of plagiarism, which has better comprehensive identification performance.
Research on Meteorological Prediction Method of High-Voltage Overhead Transmission Line Channel Based on Encoder-Decoder LSTM
Authors: Tan Ben , Sun Zezhong , Wang Sida , Yue Yishi , Liao Zhenyu , Yuan Yijun
Published: February 2024

Meteorological prediction has important application value in the energy industry and related fields. Accurate prediction of meteorological factors, such as sunshine intensity, ambient temperature and wind speed, is crucial to the operation of power transmission lines and the safety of equipment. However, traditional meteorological prediction methods may suffer from missing data and outliers, as well as challenges in model accuracy and generalization capabilities. This study uses the Encoder-Decoder LSTM network to predict the original wind speed, ambient temperature, and sunshine intensity of power transmission lines, by applying the Bi-LSTM neural network as the encoder of the network and the LSTM neural network as the decoder of the network. Through processing and predictive analysis of data collected from six overhead transmission lines of Hunan Power Grid, we verified that the model has strong feature extraction capabilities for long-term series, and the model has good generalization on unknown data. Not only can it accurately predict key meteorological parameters such as temperature, sunshine intensity and wind speed, but the deviation of the prediction data is small and has good validity and accuracy. It provides reliable meteorological information for the power industry and related fields, especially the application of dynamic capacity expansion technology. method of prediction.
Simulation Study on Ultrasonic Signal Propagation Characteristics of Partial Discharge in Transformers
Authors: Yang Jing , Gu Li-hong , Wang Kai , Zhu Jiong , Zhao Ying-ying , Shi Wei-feng , Lin Min , Yang Jian , Si Wen-Rong
Published: February 2024

Ultrasonic detection method is widely used to detect partial discharge (PD) in transformers because of its anti-electromagnetic interference and high sensitivity. It is of great significance to understand the sound wave propagation characteristics in transformers for ultrasonic signal detection and sensor arrangement optimization. In this paper, based on the finite element method, the ultrasonic signal propagation characteristics of PD in transformers are numerically studied, and the acoustic wave propagation characteristics in transformers are analyzed. The calculation results show the following facts: the multiple reflections of sound waves have a significant influence on the sound field distribution in transformers, and the sound pressure drops to 40Pa at 2500 μs; The absorption coefficient of the transformers has little influence on sound wave propagation, but when the absorption coefficient of the wall increases from 0.2 to 0.8, the pulse response time of receivers will be less than 1/2 of the original, and the arrival time difference in the area where the direct wave signal cannot be detected will be increased. When optimizing the sensor layout, priority should be given to the position with few obstacles, such as the area facing the winding gap.
Text Semantic Analysis Algorithm Based on LDA Model and Doc2vec
Authors: Zhang Weiwei , Zhai Guangyu , Zhong Binbin , Kong Xiaoyi
Published: February 2024

With the rapid development of the Internet, massive messy text data is distributed in all walks of life, how to quickly and effectively mine meaningful semantic information from these complex and messy texts has become an important task in the field of natural language. First, texts such as Weibo comments lack contextual semantics due to sparse data, which in turn affects the effect of text semantic mining. Second, existing topic model use semantic representations in different vector spaces, resulting in low accuracy. Therefore, this paper proposes a new text semantic analysis model: DBOW-LDA model, which integrates the LDA topic model (Latent Dirichlet Allocation) and the sentence vector model (Doc2vec), so that the output contains the given topic semantic information. Sentence vector representation of text. The accuracy of the algorithm is further improved. In the experiment, the crawled Weibo comment text is used as the data set, and the K-Means clustering algorithm is used to compare the effects of each model. The experimental results show that the clustering effect based on DBOW-LDA model is better than Word2vec, WT-LDA, LDA+Word2vec model.
Feedback Analysis of Digital Course Teaching Effectiveness Based on Neural Network
Authors: Hu Qian
Published: February 2024

In order to provide timely and comprehensive interactive feedback on digital classroom teaching, a comprehensive evaluation of teaching feedback using BP neural network is proposed. Based on the characteristics of different evaluation subjects, the evaluation index system is chosen through a combination of questionnaire survey and expert evaluation method, and the main process plan for feedback analysis is provided. Then, the preprocessed dataset is divided into a training set and a testing set in a certain proportion. The indicator data generated during the learning process is imported into the trained neural network model for calculation, and the approximate performance score is acquired. Finally, a digital teaching evaluation model is established using MATLAB, and the specific analysis results of learning effectiveness are used to provide feedback on the teaching effectiveness of the course. The experimental results show that the accuracy of the proposed model reaches 95.98%, and the convergence curve is smooth, with overall performance superior to other similar models. Therefore, this plan is a good choice that can reasonably predict and effectively control teaching quality, effectively weakening the influence of human factors in determining indicator weights.
Intelligent Diagnosis Model for Circuit Simulation Teaching Based on BP Neural Network
Authors: Li Meilian
Published: February 2024

To help students understand the theory and simulation methods of actual circuit fault diagnosis, a neural network-based diagnostic model in the simulation circuit experiment and conduct corresponding case analysis is proposed. It adopts the method of simulation and circuit board verification, and uses an independent neural network to implement primary diagnosis of the circuit based on improved BP network. Then the genetic algorithm is used to calculate the optimal weight and threshold of the BP neural network. Through circuit diagnosis examples in MATLAB, the possibility of the diagnosed circuit belonging to different fault states based on various test information is also acquired. The experimental test results show that the BP neural network optimized by GA has a high ability to process information in parallel, and it has the characteristics of fast diagnosis speed, high accuracy, and strong real-time performance when diagnosing analog circuit faults. Therefore, this method can enable students to intuitively understand and master the process of power electronic device fault diagnosis, and promote their practical understanding of circuit fault diagnosis technology.
Market Electricity Price Forecasting Model Based on ARIMA-LSTM
Authors: Li Xiaodong , Liu Gang , Zhu Shuo
Published: February 2024

To comprehensively consider the fluctuation law of electricity price in the whole power market and various factors affecting the clearing price, and to provide a more accurate electricity price prediction, a short-term electricity price forecasting model considering the nonlinear relationship between load and electricity price is established in this paper. In such scheme, the combined forecasting model of LSTM and ARIMA is adopted to analyze the power load and its autocorrelation characteristics in a period of time. Then, the regional power consumption is predicted from multiple angles, and the PJM historical electricity price data is used for example research. The simulation results show that this combined model overcomes the defects of a single method, and reflects the heteroscedasticity of electricity price, which can play a guiding role in the future bidding strategy, and meet the requirements of electricity price prediction of power system.
E-Commerce Personalized Recommendation System for Mobile Platform Based on K-Means Clustering
Authors: Wang Huili , Lu Xinyuan
Published: February 2024

To improve the accuracy and customer satisfaction of personalized shopping recommendation on mobile platform, a personalized recommendation scheme based on k-means clustering is proposed. Firstly, the key technologies involved in the research of mobile e-commerce platform recommendation system, especially collaborative filtering and its related algorithms were expounded. According to the actual needs of mobile e-commerce, a system framework based on personalized recommendation technology was established. Then, the k-mean algorithm was adopted to systematically analyze the categories and preferences of browsing users, and the user oriented collaborative filtering recommendation algorithm was also used to calculate the relationship between users and goods, which was taken as the input condition to improve the multi-dimensional information for project recommendation. Finally, the algorithm was tested through real data sets, and the results showed that it had good performance and can basically meet the requirements of personalized recommendation.
Power System Load Forecasting Method Based on Neural Network
Authors: Li Xuanyi
Published: February 2024

To improve the accuracy of power system load forecasting, this paper presents a solution based on neural network combined with the requirements and characteristics of power system load forecasting. Such method starts with the feature extraction and preprocessing of power data acquisition, and normalizes the system load data into information suitable for neural network processing. Then, BP neural network is used to describe the characteristics of power system load multi input and multi output, as well as complex and irregular. At the same time, the selection of initial weight and learning parameters of the model is also deeply analyzed. The results of MATLAB simulation show that our method can solve the problems of slow convergence speed and falling into local minimum easily in neural network, which has good prediction performance and calculation speed.