bluuebunny/crossref_metadata_2025 huggingface dataset:
Pengujian Black Box Testing Pada Aplikasi Edu Digital Berbasis Website Menggunakan Metode Equivalence Dan Boundary Value
Authors: Pratama Stevanu Dika , Lasimin Lasimin , Dadaprawira M. Noviarsyah
Published: March 2024

Aplikasi Edu digital merupakan aplikasi yang berbasis website yang digunakan untuk mengelola pendapatan yang diperoleh oleh kantin di sekolah SMPN 3 cilacap, aplikasi ini juga dapat melakukan pendaftaran kantin baru serta dapat menjadi tabungan bagi siswa / siswi SMPN 3 cilacap, dalam artian aplikasi ini berkerja sebagai koperasi bagi SMPN 3 cilacap. Untuk memastikan apakah aplikasi ini berjalan sesuai dengan kebutuhan fungsional yang digambarkan pada use case diagram maka akan dilakukan pengujian menggunakan metode Black box Equivalence partitioning dan Boundary value analysis dengan test case yang di design dengan menggunakan pendekatan use case untuk memastikan validasi output sesuai dengan input yang diberikan. Equivalence partitioning digunakan untuk mencari semua kemungkinan berdasarkan kriteria tertentu, sedangkan boundary value analysis digunakan untuk menguji tipe data dengan nilai rentang. Maka dari itu penelitian ini mengabungkan metode Equivalence dan Boundary value. Design test case menjadi pertimbangan yang penting untuk menemukan kesalahan pada pengujian aplikasi. Hasil yang ditemukan setelah dilakukan pengujian membuktikan bahwa metode ini cukup efektif dan mendapatkan nilai DRE sebesar 0,21 atau 21% yang tidak lolos uji.
Decision Suport System Penentuan Keikutsertaan Dalam Tender Pekerjaan Konstruksi Dengan Metode WASPAS
Authors: Wahyudi Eko , Fawaz Muhammad Ayyas , Iqbal Muhammad , Utama Siahaan Andysah Putera
Published: March 2024

Dalam suatu perusahaan pengadaan barang dan jasa, tidak terlepas dari yang namanya tender. Pada PT. Bumi Balakka Maju Sejahterah sendiri tender merupakan hal yang utama di dalam perusahaannya. Namun sayang proses penentuan keikutsertaan tender masih dilakukan secara manual sehingga pada saat penentuan tender yang akan diikuti tidak memiliki regulasi yang tetap, dan tidak sesuai dengan keadaan perusahaan, maka dari itu pemilihan tender sering mengalami kurangnya efisien dan efektifitasnya. Untuk membantu agar proses pemilihan tender yang lebih baik kedepannya, maka dibutuhkan sebuah Sistem Pendukung Keputusan yang merupakan sistem berbasis komputer sehingga dapat membantu mendukung sebuah keputusan yang dihasilkan melalui dukungan metode WASPAS dengan menentukan nilai terbesar, maka prioritas tender yang paling tinggi akan didapat. Berdasarkan hasil dari penelitian ini, Sistem Pendukung Keputusan berhasil dibangun guna membantu masalah untuk menentukan keikutsertaan tender pada PT.Bumi Balakka Sejahterah. Sehingga tender yang diprioritaskan untuk diajukan sesuai dengan kapabilitas yang dimiliki.
Implementasi Data Mining Untuk Memprediksi Penjualan Toko Roti Mawar Menggunakan Regresi Linier Berganda
Authors: Zaqy Muhammad Joefitra , Mentari Riya , Iqbal Muhammad
Published: March 2024

Salah satu toko atau pembuat roti tersebut adalah Mawar Bakery. Mawar Bakery berdiri pada tanggal 8 Februari 2003, berlokasi di Jalan Pinang Baris Medan nomor 261, saat ini Mawar Bakery menjadi salah satu produsen bakery terbaik di Sumatera Utara. Roti merupakan produk pangan olahan hasil proses pemanggangan adonan yang telah difermentasi dan memiliki struktur berongga yang dikembangkan dengan ragi roti. Roti biasanya dibuat dari tepung terigu, air, ragi dan garam. Seiring berjalannya waktu, khususnya di kota Medan banyak bermunculan toko dan toko roti. Dari sini terlihat bahwa masyarakat kota Medan sangat menyukai dan membutuhkan roti sebagai salah satu bahan makanannya. Keberhasilan penjualan roti ini berasal dari cara penjualannya kepada konsumen yang sering disebut dengan customer service atau ketersediaan roti, dan konsumen mengetahui apa yang sebenarnya diinginkan konsumen dari setiap elemen.Penelitian ini berjudul “Implementasi Data Mining untuk Memprediksi Penjualan Toko Roti Mawar Menggunakan Regresi Berganda”. Tujuan penelitian ini adalah mengembangkan sistem komputerisasi untuk memudahkan perolehan hasil evaluasi penjualan Mawar Bakery.Hasil dari permasalahan tersebut berupa aplikasi yang mengimplementasikan teknik data mining dengan memperkenalkan metode estimasi menggunakan algoritma regresi, yang nantinya dapat membantu Mawar Bakery untuk mengetahui estimasi penjualan dan menarik kesimpulan yang bermanfaat.  Kata Kunci : Data Mining, Regresi, Estimasi
Penerapan Data Mining dengan Algoritma C5.0 Untuk Prediksi Penyakit Stroke
Authors: Sofyan Fazrin Meila Azzahra , Riyandoro Affani Putri , Maulana Devi Fitriani , Jaman Jajam Haerul
Published: March 2024

Penyakit stroke merupakan kondisi yang mempengaruhi sistem saraf dan dapat menyebabkan dampak yang serius pada kesehatan seseorang. WHO menyatakan sebanyak 13,7 juta kasus setiap tahunnya dan 5,5 juta orang diantaranya meninggal dunia akibat penyakit ini. Tujuan dari penelitian ini adalah untuk mengembangkan model prediksi yang dapat membantu dalam identifikasi dini risiko terjadinya stroke. Metode yang digunakan dalam penelitian ini adalah Knowledge Discovery in Databases (KDD) dengan menerapkan algoritma C5.0, yang merupakan salah satu algoritma klasifikasi yang efektif dalam mengolah data dengan atribut numerik maupun kategorikal. Pada metode Knowledge Discovery in Databases (KDD) terdiri dari beberapa tahap yang perlu dilakukan untuk penelitian ini, yaitu selection, preprocessing, transformation, data mining, dan evaluation. Untuk Algoritma C5.0 sendiri merupakan sebuah algoritma klasifikasi dalam bidang data mining yang secara khusus digunakan dalam teknik decision tree.  Data yang digunakan dalam penelitian ini adalah dataset yang berisi informasi medis dan faktor risiko yang terkait dengan stroke. Hasil dari penelitian ini berupa Decision Tree (pohon keputusan) dengan nilai accuracy, recall, dan precision dengan melakukan split data 80% (data training) - 20% (data testing) hasil nilai Accuracy yang diperoleh sebesar 95%, Recall = 96%, dan Precision = 99%.
Implementasi Metode Weight Aggregated Sum Product Assesment (Waspas) Dalam Pemilihan Lokasi Cabang Baru Penjualan Bakery
Authors: Tugiono Tugiono , Hafizah Hafizah , Azizi Fadli
Published: March 2024

Maraknya penikmat roti (bakery) memberikan peluang bagi perusahaan yang bergerak dalam penjualan bakery untuk mengembangkan usaha mereka. Salah satu cara pengembangan yang dilakukan adalah dengan membuka cabang-cabang penjualan. Pemilihan lokasi sering kali dianggap sebagai hal yang sepele, padahal lokasi usaha sangat menentukan keberlangsungan dari usaha yang dilakukan. Untuk membangun lokasi usaha baru khususnya pembukaan cabang baru tidaklah mudah dikarenakan harus tepat,  strategis dan efisien agar usaha tersebut dapat diterima dengan mudah oleh konsumen. Untuk pemilihan lokasi cabang dapat mempertimbangkan beberapa aspek, diantaranya aksesibilitas (kemudahan untuk diakses), visibilitas (kemudahan untuk dilihat), lingkungan sekitar dan persaingan. Penelitian ini mengadopsi metode Weight Aggregated Sum Product Assesment (WASPAS) dalam sistem pendukung keputusan untuk mempermudah proses pemilihan lokasi cabang terbaik berdasarkan penilaian dari aspek-aspek yang telah ditentukan. Metode WASPAS merupakan metode yang dapat mengurangi kesalahan-kesalahan atau mengoptimalkan dalam penaksiran untuk penentuan nilai tertinggi dan terendah.
Sistem Pendukung Keputusan Pemilihan Bibit Kelapa Sawit Menggunakan Metode MOORA
Authors: Andika Beni , Boy Ahmad Fitri , Saniman Saniman , Sitepu Grace Kornelius
Published: March 2024

Melihat pentingnya tanaman kelapa sawit di masa ini dan masa yang akan datang, seiring dengan meningkatnya kebutuhan penduduk dunia akan minyak sawit, maka perlu dipikirkan usaha peningkatan kualitas dan kuantitas produksi  kelapa sawit secara tepat agar sasaran yang diinginkan dapat tercapai.  Pertumbuhan awal bibit ialah periode kritis yang sangat menentukan keberhasilan tanaman dalam mencapai pertumbuhan yang baik, dipembibitan pertumbuhan dan figur bibit tersebut sangat dipengaruhi oleh kecambah yang ditanam. Namun permasalahan yang sering terjadi pada PTPN IV Kebun Balimbingan adalah  asisten kepala tanaman masih melakukan pemilihan bibit kelapa sawit secara manual dan cenderung subjektif sehingga membutuhkan waktu yang cukup lama dan hasil yang didapatkan tidak akurat. Sistem Pendukung keputusan adalah salah satu bidang keilmuan  pemilihan bibit terbaik secara objektif yaitu dengan berdasarkan kriteria-kriteria tertentu dan memberikan berbagai alternatif pilihan. Salah satu metode yang dapat membantu dalam proses pemilihan bibit kelapa sawit adalah metode multi-objective optimization by ratio analysis (MOORA). Metode ini memiliki tingkat fleksibilitas yang tinggi dan kemudahan dalam memisahkan bagian subjektif dari suatu proses evaluasi ke dalam kriteria bobot keputusan dengan beberapa atribut pengambila keputusan. Hasil penelitian ini bermanfaat bagi perusahaan dan dapat dikategorikan sebagai sistem pendukung keputusan Ketika solusi atau hasil yang diperoleh dari perhitungan metode metode multi-objective optimization by ratio analysis (MOORA) dapat dijadikan suatu keputusan dalam pemilihan bibit terbaik di PTPN IV Kebun Balimbingan.
Analisis Strategi Pengelolaan Data Laporan Keuangan Bank Menggunakan Metode Konseptual Data Warehouse
Authors: Sari Dely Indah , Harahap Widiya Lestari , Ali Faishal
Published: March 2024

Teknologi Informasi adalah sebuah asset yang penting untuk Bank sehingga penggelolaan teknologi informasi bukan hanya tanggung jawab dari divisi IT atau unit kerja penyelenggara Teknologi Informasi. Data warehouse merupakan suatu hal yang penting untuk suatu perusahaan maupun perbankan, karena dengan menggunakan data warehouse, menganalisis data suatu perusahaan atau Bank akan mudah untuk dilakukan. Yang berarti data warehouse dapat membantu pihak manajemen Bank dalam pengambilan keputusan secara cepat untuk memecahkan masalah. Penelitian kali ini akan menggunakan Entity Relathionship Digram (ERD), Star-Schema, Snowflake-Schema. Penggunaan data warehouse dapat memberikan kemudahan kepada organisasi atau perusahaan dalam mengelola dan pengelompokan data guna menunjang pengambilan keputusan dan strategi bisnis serta mempermudah dalam proses bisnis.
Segmentasi Kematangan Buah Markisa Berdasarkan Kemiripan Warna Dengan Algoritma K-Means
Authors: Rifqi Aufa Siregar Farras , Sriani Sriani , Darta Ali
Published: March 2024

Tingkat matang buah markisa bisa identifikasi dari beberapa cara salah satunya yaitu melihat warna buah tersebut, bentuk buah yang semakin besar dan permukaan warna buah yang kuning menyeluruh. Menentukan tingkat kematangan markisa yang dilakukan oleh petani dan konsumen selama ini tidak efektif, yaitu dengan mengidentifikasi pada permukaan kulit buah. Menggunakan dengan cara manual tidak efisien karena akan memakan waktu yang tergolong cukup lama, selain itu manusia memiliki pandangan dan pendapat yang berbeda-beda yang akan menghasilkan hasil dari identifikasi menjadi berbagai macam. Identifikasi dengan cara tersebut memiliki kekurangan, maka dari itu dibutuhkan sebuah sistem yang mampu menentukan kematangan buah yang memiliki akurasi yang tinggi dan menghasilkan informasi yang valid. Metode algoritma k-means yang akan diimplementasikan ke dalam proses segmentasi buah markisa yaitu dengan memilah citra ke dalam suatu kelompok yang dinilai dari kemiripan atribut citra. Algoritma k-means akan memilah data yang mempunyai nilai, atribut, karakter serupa ke dalam satu grup. Data buah yang terkumpul sebanyak 8 buah markisa dan menghasilkan data citra sebanyak 48 citra buah markisa. Pengambilan gambar dari 6 sisi yaitu atas, bawah, kiri, kanan, depan dan belakang. Dari hasil klaster dengan metode algoritma k-means didapat hasil 4 buah markisa matang dan 4 buah markisa mentah.
Dijital ayak izleri aracılığıyla milli parklara gelen ziyaretçilerin zamansal ve mekânsal dağılımlarının modellenmesi: Ilgaz Dağı Milli Parkı örneği
Authors: Uslu Ahmet
Published: March 2024

Giriş ve Hedefler Milli parklar doğaya dayalı turizm ve açık hava rekreasyonu için önemli destinasyonlardan biri haline gelmiştir. Milli parkların, sürdürülebilir ve etkin yönetimi için ziyaretçilerin zamansal ve mekânsal dağılımlarının analizine ihtiyaç duyulmaktadır. Günümüzde sosyal ağlardan elde edilen dijital ayak izleri, ziyaretçilerin zamansal ve mekânsal dağılımının analizi için kullanılmaktadır. Bu çalışmada, Wikiloc’tan elde edilen dijital ayak izleri kullanılarak Ilgaz Dağı Milli Parkı’na gelen ziyaretçilerin zamansal ve mekânsal dağılımlarının modellenmesi amaçlanmıştır.
Yöntemler Wikiloc’tan elde edilen ziyaretçi verileri ile resmi ziyaretçi verileri arasındaki doğrusal ilişkiyi ölçmek için Pearson korelasyon testi kullanılmıştır.
Bulgular Pearson korelasyon analizi, Wikiloc kullanıcılarının sayısı ile resmi ziyaretçi sayıları arasında pozitif yönde çok güçlü (r=0,867) ve istatistiksel olarak ileri düzeyde anlamlı bir ilişki olduğunu (p
Aproximación a la evolución en la gestión del conocimiento en la era digital: una reflexión sobre el futuro del bibliotecario en Nicaragua
Authors: Aguirre Elías
Published: March 2024

El objetivo principal de este trabajo es dialogar con diversos autores y con la comunidad universitaria sobre el impacto que han tenido las nuevas tecnologías en la gestión del conocimiento y qué amenazas suponen estas para el ámbito académico, tomando en cuenta la reciente explosión de las inteligencias artificiales. Se sabe que la tecnología ha desplazado a cientos de trabajadores de sus puestos laborales en todo el mundo, por tal razón este ensayo se propone problematizar sobre el futuro del bibliotecario, tanto a nivel internacional como en Nicaragua. Los resultados de esta reflexión apuntan que, en el caso de nuestro país, el papel del gestor de la información se ha venido fortaleciendo conforme avanzan las nuevas Tecnologías de la Información y la Comunicación (TIC) y que desde nuestras universidades existe una política clara que apuesta por la actualización de los recursos humanos en esta materia, mediante la capacitación continua, fortaleciendo este perfil profesional a través de los programas de educación de grado y de posgrado. Una de las grandes fortalezas en la gestión del conocimiento de nuestras universidades, y en particular de la UNAN-Managua, ha sido adoptar el concepto de la biblioteca híbrida, que se mueve entre lo análogo y lo digital. Esto ha permitido la creación de todo un sistema de información de gestión institucional integrado que admite un manejo eficaz de la información a través de plataformas digitales como páginas web, repositorios institucionales, bases de datos suscritas, boletines informativos electrónicos y motores de búsqueda especializados. En este sentido, es evidente que las autoridades de nuestra institución han sabido responder con mucha certeza ante estos desafíos.
Modelos pedagógicos y tendencias didácticas en la educación superior
Authors: Calderón Ramírez Walter Jerónimo
Published: March 2024

El presente ensayo tiene como principal propósito realizar una reflexión sobre los modelos pedagógicos y las tendencias didácticas en la educación superior. El trabajo destaca que los modelos pedagógicos son una construcción teórica que tiene una base científica y técnica, la cual sirve como marco de referencia para interpretar, desarrollar y adaptar las realidades pedagógicas en respuesta a necesidades históricas específicas. Entre estos modelos pedagógicos se encuentran el conductismo, cognitivismo y constructivismo. Cada uno de ellos concibe en forma distinta el aprendizaje, así, por ejemplo, el conductismo concibe al aprendizaje como el resultado de un cambio de comportamiento constante. El cognitivismo, mientras tanto, considera que el aprendizaje es un proceso que se logra mediante una interacción entre la persona que aprende y el medio ambiente. El constructivismo enfatiza la contribución del estudiante al significado y al aprendizaje a través de la actividad individual y social. El ensayo concluye destacando que el análisis de las tendencias didácticas en educación superior debe partir de la propia identidad y situación de las instituciones de educación superior, por cuanto se hace necesario reflexionar sobre las problemáticas pedagógicas de la educación superior y el perfil del docente universitario que se requiere para facilitar el aprendizaje.
Hubungan Aktifitas Fisik, Kebiasaan Merokok dan Hipertensi terhadap Penyakit Jantung Koroner
Authors: Sriwahyuni
Published: March 2024

Introduction: The incidence of CHD at the Kalabahi Hospital has increased every year. In 2019, there were 568 CHD patients, and about 60% of the total CHD patients experienced complications of Kidney Failure, so they had to be hemodialyzed and had an impact on sudden death.
Objectives: This study aims to determine the relationship of physical activity, smoking habits, and hypertension to coronary heart disease at the Kalabahi Hospital Polyclinic, Alor, East Nusa Tenggara, 2022.
Methode: Type of analytical research with a cross-sectional approach. The sample in this study was 52 CHD patients undergoing outpatient treatment at the Kalabahi Regional Hospital Polyclinic. The sampling technique used in this research is Total Sampling. data collection techniques using questionnaires. Data analysis used the Pearson Product Moment statistical test and Multiple Correlations to determine the relationship between Physical Activity, Smoking Habits, and Hypertension in Coronary Heart Disease.
Result: Based on the results of the analysis, it was found that the relationship between physical activity and coronary heart disease had a p-value of 0.000. The relationship between smoking habits and coronary heart disease has a p-value of 0.040 and the relationship between hypertension and coronary heart disease has a p-value of 0.000.
Conclusion: There is a relationship between physical activity, smoking habits, and hypertension in coronary heart disease at the Kalabahi Hospital Polyclinic, Alor, East Nusa Tenggara, 2022.
Faktor yang Mempengaruhi Kinerja Tenaga Kesehatan terhadap Pelayanan di Rumah Sakit Daerah Kalabahi Tahun 2023
Authors: Makunimau Sovie Iriani
Published: March 2024

Background: The hospital is the main health facility for the community, so it is expected that the hospital has a good image (quality) in the eyes of its customers. This is largely determined by the quality of its human resources. Based on this educational background, SDMK is expected to be able to support quality hospital services. This is done to get health workers who are capable, skilled, qualified, and willing to achieve high work productivity and can deal with various problems and solve them intelligently, properly, and correctly. Based on the results of the interviews, it turned out that it was not by the desired expectations because of the declining health performance of workers so it had a direct impact on service.
Objectives: The purpose of this study was to determine the motivational, leadership, and imbalance factors that affect the performance of health workers towards services at the Kalabahi Hospital in 2023.
Method: The type of research used in this research is analytical quantitative research with a cross-sectional approach. The sample was obtained using total sampling obtained from the total population, namely all health workers working at the Kalabahi Regional Hospital in 2023 totaling 110 people. Data collection was carried out through face-to-face meetings with respondents by distributing questionnaires which were closed. In this analysis, the chi-square test was used to determine this effect using a significance level of 5% (0.05).
Result: The results of the chi-square test research show that the motivation value (p=0.012), the appreciation value (p=0.024), and the leadership value (p=0.134).
Conclusion: Motivational factors greatly influence the performance of health workers and also the majority of health workers whose performance is less good is greatly influenced by the reward factors they receive, thus influencing service performance. Meanwhile, leadership factors do not influence the performance of health workers at Kalabahi Hospital.
Prevalência de Sintomas Miccionais e Fatores Preditivos em Transplantados Renais em um Centro Transplantador Brasileiro
Authors: Sobrinho Diego Henrique Gomes , Tomaz Kézia Jahel Santos , Schwamback Guilherme Rodrigues , Rodrigues Renata Gonçalves Santos , Santos Alessandro Corrêa Prudente dos
Published: March 2024

Objetivos: Identificar relações entre escores de sintomas miccionais e variáveis relacionadas ao transplante. Métodos: Estudo observacional, transversal e analítico no qual o conjunto dos pacientes submetidos a transplante renal no estado de Rondônia, Brasil, foi avaliado por meio de entrevistas e análise de registros quanto a seu perfil clínico-demográfico e aos sinais e sintomas de disfunção miccional. Qui-quadrado, analysis of variance (ANOVA) e regressão linear multivariada foram utilizados para estabelecer possíveis correlações. Resultados: Abordaram-se 81,87% dos pacientes (n = 122). Os sintomas mais frequentes foram aumento da frequência (68,2%) e noctúria (97,6%). O teste ANOVA demonstrou relação entre a idade e o International Consultation on Incontinence Questionnaire (ICIQ) (Questionário Internacional de Consulta sobre Incontinência) (p = 0,014), etilismo e o Overactive Bladder Questionnaire (OAB-V8) (Question.rio de Avaliação da Bexiga Hiperativa) (p = 0,001), esquema imunossupressor e ICIQ (p = 0,04), timoglobulina e OAB (p = 0.009), uso de duplo J e ICIQ (p = 0,014), infecção por citomegalovírus e OAB (p = 0,031) e International Prostate Symptom Score (IPSS) (Escore Internacional de Sintomas Prostáticos) (p = 0,008). Das comorbidades, foi observada insuficiência cardíaca relacionada aos escores OAB (p = 0,009) e ICIQ (p = 0,003). Qui-quadrado apontou associação entre uso de álcool e grupo 1 do OAB (p = 0,005). O teste de Pearson correlacionou positivamente tempo de isquemia do enxerto com ICIQ (p = 0,04). Conclusão: A prevalência de sintomas do trato urinário inferior é maior em transplantados renais do que na população geral, e foi possível determinar fatores preditivos para sua ocorrência.
Enhancing Oxygen Evolution Reaction through In Situ Electrochemical Oxidation for the Structural Control of Co-Fe Prussian Blue Analogue
Authors: Chen Yajuan , Tang Jing , Li Weijun , Tu Jielei , Huang Chao
Published: March 2024

The development of exceptionally efficient catalysts for the oxygen evolution reaction (OER) and gaining a deep understanding of their activity is essential for advancing electrochemical conversion technologies. Prussian blue analogues (PBAs) serve as promising pre-catalysts for the OER. However, PBAs, typically prepared through the conventional co-precipitation method, exhibit a lower active site density and limited electrical transport, making them suitable precursors for the derivation of PBA derivatives. In this research, we identified a significant enhancement in the electrocatalytic performance of Co-Fe Prussian blue analogue (CoFe PBA) through electrochemical oxidation. The cubic CoFe PBA was synthesized by one-step co-precipitation method using adjusting the amount of sodium citrate and potassium ferricyanide. After the electrochemical treatment, CoFe PBA demonstrates remarkable attributes, including a low overpotential of 331mV at a current density of 10mA·cm-2, a small Tafel slope of 50.4mV·dec-1, and excellent long-term stability during electrolysis in a 1M KOH alkaline medium for over 37h. Moreover, the electrochemical oxidation of CoFe PBA was comprehensive, employing techniques such as Transmission electron microscope, Powder X-ray diffraction, and X-ray photoelectron spectroscopy. These analyses confirmed the presence of real active substances, including CoOOH and a part of FeOOH species, further supporting the observed improvements in electrocatalytic activity.
The impact of fibres reinforcement on the thermal characteristics of lime-stabilised compressed earth blocks
Authors: Abdelkader Fidjah , Naimi Oussama , Mohamed Rabehi , Cheikh Kezarane , Ahmed Zitouni Tidjani , Sakhi Tayeb , Roqiya Dahmani , Mahieddine Chettah
Published: March 2024

In civil engineering, the use of fibers in construction has spread recently, because of their many benefits in terms of increasing the cohesion of buildings and their thermal insulation. In addition to having several good physical and mechanical properties. Thermal insulation has become an important thing in the field of construction. Because it is linked to increasing the lifespan of buildings and predicting their thermal behavior. It includes increasing energy efficiency and reducing its costs. Fibers are used to increase thermal insulation, because it creates voids inside the structures that are within its content, and thus impedes the transfer of heat, regardless of the type of transfer by convection, radiation, or conductivity. This study aims to determine the amount of thermal insulation in compressed earth bricks with dimensions of 20 × 10 × 10 cm3, to which palm fibers and glass are added in different proportions: 0%, 0.1%, 0.2%, 0.3%, 0.4% and 0.5%.In earthen bricks composed of soil, sand and lime. The study includes the physical, mechanical and thermal properties of these bricks. We focus on thermal insulation in the best samples in terms of hardness. Laboratory samples were taken according to standard experiments in university laboratories. Preliminary results showed a decrease in bulk density between 6% and 8.34%, an increase in mechanical stresses between 42.85% and 45.45%, and an increase in thermal insulation between 26% and 29%. These results give us an overview of the impact of using fibers in construction in terms of increasing weight bearing and predicting the amount of thermal insulation.
Práticas educativas em educação profissional e tecnológica (EPT)
Authors: Santos Silvana Maria Aparecida Viana , Caetano Aline Braga , Sobrinho Benedito Braz , Rocha Danylo Soeiro da , Soeiro Juliana Tavares Pereira , Jordão Lorena Santana Furtado , Silva Paulo Edson Cutrim , Silva Sandra Regina Moisés da , Modesto Valéria Teixeira
Published: March 2024

Este estudo abordou o problema da necessidade de inovação nas práticas educativas na Educação Profissional e Tecnológica (EPT) diante das rápidas mudanças no mercado de trabalho. O objetivo geral foi avaliar como metodologias ativas, tecnologias educacionais e formação docente contribuem para a qualidade da EPT. A metodologia empregada foi a revisão de literatura, focando em trabalhos que discutem a aplicação de práticas educativas inovadoras na EPT. Os resultados apontaram para a eficácia das metodologias ativas em promover uma aprendizagem mais engajada e significativa, a importância das tecnologias educacionais em tornar o ensino mais acessível e interativo, e a necessidade de programas de desenvolvimento profissional contínuo para educadores. A análise comparativa destacou a complementaridade entre essas práticas na melhoria da qualidade educacional. As considerações finais enfatizaram a importância de adaptar e inovar continuamente o ensino na EPT, visando melhor preparação dos estudantes para o mercado de trabalho.
Organização e memórias de espaços pedagógicos na educação profissional e tecnológica (EPT)
Authors: Santos Silvana Maria Aparecida Viana , Silva Ana Luzia dos Santos da , Carvalho Anderson César Ramos da Luz , Melo Júnior Hermócrates Gomes , Silva Liliane Inácia da , Machado Renato , Bianchini Tatiani Bonfim , Oliveira Thiago Souza de
Published: March 2024

Este estudo investigou a organização e memórias de espaços pedagógicos na Educação Profissional e Tecnológica (EPT), abordando o desafio de adaptar esses ambientes às demandas educacionais contemporâneas e às necessidades de inclusão e inovação. O objetivo geral foi analisar como a configuração desses espaços influencia o processo de ensino-aprendizagem e contribui para a construção da identidade institucional. A metodologia adotada baseou-se em uma revisão de literatura, explorando estudos anteriores sobre o tema, políticas públicas relevantes e exemplos de práticas pedagógicas inovadoras. Os resultados indicaram que os espaços pedagógicos na EPT desempenham um papel fundamental na promoção de uma aprendizagem integrada e significativa, enfrentando, contudo, desafios relacionados à atualização tecnológica e à manutenção de uma infraestrutura que suporte metodologias ativas de aprendizagem. As considerações finais destacaram a necessidade de investimentos contínuos e de uma gestão eficaz para que os espaços pedagógicos evoluam de forma a atender às exigências de uma educação profissional qualificada e alinhada com as demandas do mercado de trabalho e da sociedade.
An investigation of machine learning-based video compression techniques
Authors: Zhu Ye
Published: March 2024

As video technology continues to seamlessly weave itself into the fabric of daily life, there is a growing need for enhanced storage and efficient video transmission. This surge in demand has led to heightened expectations and standards for video compression technology. Machine learning as an up-and-coming technology can play its advantages in the field of video compression. This article reviews the current state of research on combining video compression techniques with machine learning. The article provides an overview of various research avenues for enhancement, spanning from conventional video compression algorithms to the fusion of traditional compression frameworks with machine learning methodologies, and even the development of novel end-to-end compression algorithms. In additional, the article explores the possible various application scenarios of machine learning-based video compression algorithms based on the characteristics of such non-standard and arithmetic demanding algorithms. At the end, the article speculates on the future of video compression algorithms based on the content of the various studies reviewed in the article.
A comparative analysis of blockchain attack classifications
Authors: Wang Zichao
Published: March 2024

As blockchain technology has evolved, it has introduced an array of functionalities and mechanisms. However, this advancement has also attracted a growing number of threats specifically targeting blockchains, heightening concerns regarding blockchain security. Although several researchers have attempted to categorize blockchain attacks in their respective studies, there remains a significant disparity among these taxonomies. This paper delves into three distinct classification methodologies, comparing their respective strengths and weaknesses. Additionally, it offers insights into the essential attributes that a comprehensive and effective taxonomy should possess. By breaking down each classification method, the paper provides a clearer understanding of how various researchers approach the challenge of categorizing blockchain threats. This includes looking at the criteria each method uses, such as the level of technical sophistication required for each attack, the potential damage inflicted, or the underlying motivations of the attackers. Furthermore, the paper emphasizes the importance of a universally accepted taxonomy, as this would not only facilitate more effective communication among researchers but also help in devising better defense mechanisms. In conclusion, by analyzing and comparing these classification methodologies, the study hopes to pave the way for a more unified and comprehensive approach to understanding blockchain security threats in the future.
Generating high-quality images from brain EEG signals
Authors: Yang Daxiang
Published: March 2024

This study presents DreamDiffusion, an innovative approach to produce high-quality images straight from electroencephalogram (EEG) brain signals, eliminating the need for thought-to-text translation. By harnessing pre-trained text-to-image models, DreamDiffusion integrates temporal masked signal modeling to adeptly pre-train the EEG encoder, ensuring accurate and dependable EEG data representation. Moreover, by integrating the CLIP image encoder, this method fine-tunes the alignment of EEG, text, and image embeddings, even with a scant amount of EEG-image pairs. Effectively navigating the complexities inherent in EEG-based image creation, such as data noise, limited content, and personal variances, DreamDiffusion showcases promising outcomes. Both quantitative and qualitative assessments validate its efficacy, marking a considerable advancement in the realm of efficient, affordable "thought-to-image" conversions, with promising implications in both neuroscience and computer vision.
Narrative-guided synthesis: Revolutionizing text-to-image translation based on Generative Adversarial Networks
Authors: Sun Shanmin
Published: March 2024

Synthesizing images from textual descriptions remains an intricate yet essential task in the field of artificial intelligence. However, this process often encounters challenges related to intricacy and time consumption. This study introduces a pioneering approach known as narrative-guided synthesis, harnessing the power of Generative Adversarial Networks (GANs) in conjunction with platforms such as Midjournary. This innovative technique transforms abstract narratives into stunning visual creations, streamlining the image generation process by providing real-time feedback and guidance. This research showcases an optimized framework that integrates diverse modules into a unified system, effectively reducing computational complexity and boosting overall efficiency. Central to this framework is an attention-guided mechanism that emphasizes semantic nuances within the text, ensuring greater fidelity in the generated images. This is complemented by spatially adaptive normalization techniques that maintain contextual relevance within the visual outputs. Preliminary results indicate that this approach not only competes with existing models but potentially surpasses them in producing visually and contextually accurate images, heralding a new era of digital innovation where technology and creativity converge seamlessly. Furthermore, this study underscores the transformative potential of AI in revolutionizing content production, interactive design, and user interfaces, promising a future where textual narratives can be visualized with unprecedented accuracy and creativity.
The analysis of social E-commerce with artificial intelligence
Authors: Kang Kaiwen , Wang Xuezhou , Yang Wenwen
Published: March 2024

Nowadays, with the widespread popularization and development of the internet, the e-commerce industry has begun to rise, among which social e-commerce, as a new community, has become popular on the Internet. At the same time, the field of artificial intelligence is slowly infiltrating into every field of today's society. The diversified data contained in the social e-commerce platform has great potential value, but artificial intelligence, as an important technology of information analysis, is rarely applied in this direction. This paper fundamentally discusses the role of artificial intelligence in e-commerce. Taking Xiaohongshu as an example, the SWOT framework is used to analyze the advantages and drawbacks, potential benefits and risks caused by the application of artificial intelligence in an e-commerce platform with rich user data. The limitation and extensibility of artificial intelligence in e-commerce platforms, finally put forward the application prospect of artificial intelligence in the e-commerce direction. This study recommends that the social e-commerce community establish a robust data privacy protection system, increase investment in technology research and development, and fully leverage the potential of AI technology.
Comparative analysis of clustering algorithm and improved algorithm application in shipping congestion
Authors: Liyang Wang
Published: March 2024

In recent years, due to the lack of reasonable planning of ship operation routes, shipping congestion accidents have been increasing, seriously restricting port development and channel operation, posing a great threat to ship navigation safety and greatly restricting the development prospects of the shipping industry. This paper aims to compare and analyze the application of the clustering algorithm and its improved algorithm in solving port and waterway congestion problems. By analyzing the literature on the use of clustering algorithms to solve shipping congestion problems, and comparing the advantages and disadvantages of multiple clustering algorithms in solving problems, this paper concludes that Partition-based Methods are more suitable for identifying port congestion and the improved Fuzzy DBSCAN algorithm for identifying channel congestion. The research in this paper will help to select clustering algorithms when solving shipping congestion problems in the future.
Drone detection with radio frequency signals and deep learning models
Authors: Dai Xuanze
Published: March 2024

The widespread use of drones raises security, environmental, privacy, and ethical issues; therefore, effective detection by drones is important. There are several methods for detecting drones, such as wireless signal detection, photoelectric detection, radar detection, and sound detection. However, these detection methods are not accurate enough to identify drones for use. To solve this question, more robust drone detection method are needed. In addition, for different types of drones and application scenarios, different technical means need to be used for detection and identification. Based on 2-class ,4-class and 10-class problems on an open ratio frequency (RF) signal dataset, we compared the drone detection and classification performances of different machine learning with deep learning models and multi-task models which is proposed by combining different RF methods with Convolutional neural networks (CNNs). Our experimental results show that the XGBoost model achieved the latest results on this groundbreaking dataset, with 99.96% accuracy for 2-class problem, 92.31% accuracy for 4-class problem, and 74.81% accuracy for 10-class problem, which exhibits the best performance for drone detection and classification.
Neural Style Transfer with automatic style weight searching
Authors: Zhou Xiang
Published: March 2024

Neural Style Transfer (NST) has garnered significant attention in the field of computer vision. Previous research in this area has made important breakthroughs, creating various style transfer models and innovative architectural designs, and has achieved success in commercial applications. This paper presents a novel design for automatic style weight determination based on constraining the initial total loss within a healthy range and finding the optimal solution through grid search. This design aims to harness the potential of existing NST models by automating the optimization of neural style transfer hyperparameters. The paper first discusses the impact of content weights and loss weights on the generated images and validates the influence of weight ratios on image quality through experimental adjustments of weight proportions. It also confirms that the initial loss essentially defines the optimization space of the optimizer. The paper explores the significance of the initial loss and proposes a method to improve image generation quality by constraining the initial loss range.
Revolutionizing machine learning: Harnessing hardware accelerators for enhanced AI efficiency
Authors: Zou Cong
Published: March 2024

In recent decades, the field of Artificial Intelligence (AI) has undergone a remarkable evolution, with machine learning emerging as a pivotal subdomain. This transformation has led to increasingly complex algorithms and soaring data volumes, necessitating robust computational resources. Conventional central processing units (CPUs) are struggling to meet the demanding requirements of modern AI applications. In response to this computational challenge, a new generation of hardware accelerators has been developed to enhance the processing and learning capabilities of machine learning systems. Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), and Application Specific Integrated Circuits (ASICs) are among the specialized accelerators that have emerged. These hardware accelerators have proven instrumental in significantly improving the efficiency of machine learning tasks. This paper provides a comprehensive exploration of these hardware accelerators, offering insights into their design, functionality, and applications. Moreover, it examines their role in empowering machine learning processes and discusses their potential impact on the future of AI. By addressing current trends and anticipated challenges, this paper contributes to a deeper understanding of the dynamic landscape of hardware acceleration in the context of machine learning research and development.
The application of Internet of Things technology in intelligent fire protection
Authors: Guo Peihan
Published: March 2024

The uncertainty of fire and the difficulty of accurate prevention greatly increase the difficulty of fire prevention and control. Therefore, it is necessary to actively introduce modern science and technology, adopt fire Internet of Things (IoT) technology, realize remote dynamic monitoring, and accurately obtain fire prevention and control data information. This paper carries out an in-depth analysis on fire prevention and control, focusing on the application of fire IoT in the field of fire prevention and control. In addition, it specifically introduces the key technologies of intelligent fire protection, Radio Frequency ID, and the construction of fire safety models. At the same time, it describes the problems faced by the IoT in intelligent fire protection, that is, the quality of transmitted information is not strong, the speed of message transmission needs to be improved, and the application platform that is more conducive to the transmission of information needs to be built. By overcoming these issues, the future intelligent fire control system will be more intelligent and bring more convenience to people.
Prediction of patient breast cancer probability
Authors: Qiu Wenyang
Published: March 2024

Breast cancer has a significant global impact; in 2015, it caused 570,000 deaths and 1.5 million yearly diagnoses. A challenge is that it has a poor prognosis for cure and is metastatic. The 21st century's health-conscious atmosphere emphasizes the need to lower the death toll from cancer, which will account for approximately one in six fatalities in 2020. According to malignancy, an estimated 7.8 million women are projected to be diagnosed with breast cancer throughout the upcoming five-year period. For the identification and prevention of cancer, proactive measures are required. Python algorithms, particularly linear regression, are extraordinarily useful for analyzing complex datasets. Using linear regression in Python to analyze data yields illuminating models that reveal morbidity trends. With the insights gained from these models, healthcare providers can provide patients with more individualized care. This proactive approach and implementing Python's linear regression algorithms enhance the understanding of cancer risk and allow for effective preventative measures. Greater public awareness of health issues has resulted in an emphasis on preventative measures against breast cancer and other cancers. With the help of Python's data-driven algorithms, society may acquire a more accurate understanding of cancer risks and make decisions that will enhance patient welfare.
Research on emergency transport planning for E-commerce logistics network based on simulated annealing algorithm
Authors: Wang Haiquan , Cao Jianhua
Published: March 2024

In response to the issue of insufficient demand for logistics facilities during holidays or the temporary or permanent closure of logistics facilities due to sudden events such as epidemics, natural disasters, etc., this paper proposes a planning model and solution algorithm based on multi-objective dynamic decision-making to optimize the emergency transport plan and structure of the e-commerce logistics network. Firstly, an LSTM model is utilized to predict the transportation demand for a certain period in the future. Decision variables are introduced to indicate whether to open or close new routes after closing a logistics facility. The objective functions are set to minimize the number of routes with changes in cargo volume, minimize the load imbalance of each route, and minimize the cumulative total of parcels that cannot circulate normally. Considering factors such as normal circulation of parcels, circulation capacity, transportation capacity after opening or closing facilities, and time constraints, a multi-objective planning model is constructed. Finally, the simulated annealing algorithm is employed for solution, obtaining a circulation plan that meets the requirements. Simulation experiment results demonstrate that the model can rapidly and accurately respond to the paralysis of the e-commerce logistics network caused by sudden events, showcasing high efficiency and practical application value.
Analisis Peran dan Kesenjangan Eksistensi Bursa Kerja Khusus (BKK) dalam Menjebatani Lulusan SMK Memasuki Dunia Industri
Authors: Ma'rufiati Tri , Habsya Chundakus , Estriyanto Yuyun , Siswandari Siswandari
Published: March 2024

Studi pendahuluan menunjukkan adanya ketidaksesuaian antara ketrampilan yang dimiliki lulusan sekolah kejuruan dengan pekerjaan yang ditawarkan. Hal ini menunjukkan kurang optimalnya peran Bursa Kerja Khusus (BKK) di sekolah sebagai penghubung dengan dunia industri. Penelitian ini bertujuan untuk mengetahuib peran dari BKK dalam menjembatani lulusan SMK dengan dunia industri dan menganalisa kesenjangan dari pelaksanaanya. Analisis data yang digunakan adalah analisis deskriptif, dengan pendekatan kualitatif. Hasil dari penelitian ini menunjukkan bahwa peran BKK berupa mengorganisir database lulusan SMK, penelusuran minat dan bakat siswa, keberlanjutan siswa, dan memfasilitasi lulusan yang ingin bekerja dengan dunia industri melalui perekrutan tenaga kerja. Kinerjanya saat ini dinilai sudah cukup baik, hal ini ditunjukkan indeks kinerja yang baik. BKK mampu menginformasikan adanya lowongan kerja pada alumni, menjalin kerja sama dengan dunia kerja dan menjalin kerja sama dengan ikatan alumni. Namun demikian, masih terdapat kesenjangan yang menyebabkan kinerjanya dalam lebih optimal. Lebih lanjut, peran BKK yang perlu ditingkatkan adalah menjalin kerjasama dengan industri.
Workers in the Cambodian informal economy
Authors: Bordon Giulio ,   ILO DWT for East and South-East Asia and the Pacific and Country Office for Thailand, Cambodia and Lao People's Democratic Republic,
Published: March 2024

Informality is pervasive in Cambodia: 88.3 per cent of workers are engaged in informal employment. This brief offers insights into labour informality indicators based on the 2019 LFS.
Manajemen Strategi Pembiayaan Dalam Organisasi Sekolah
Authors: Romandoni Ilham Yahya , Sulistyorini Sulistyorini , Chotimah Chusnul
Published: March 2024

Research on Financing Strategy Management in School Organizations is motivated by the need for a strategy in managing school financing based on operational needs that have been designed. This research uses research methodslibrary research. With a descriptive qualitative approach. The data analysis technique was carried out using descriptive analysis. The data sources for this research come from scientific articles and books. The results of this research show that the strategy for managing school organization finances starts from planning, bookkeeping, spending, supervision and financial accountability, where the financial sources come from the APBN, APBD, parents and other sources. In managing financing, it must be based on the school's operational needs which include financing all activities, financing books, financing exams, financing consumables and school maintenance.