bluuebunny/crossref_metadata_2025 huggingface dataset:
Labour of Love: Alienation, Race, and Family in Julia Cho’s Aubergine
Authors: Hyeon Youngbin
Published: January 2025

Julia Cho’s Aubergine (2016) illustrates a conflicted relationship between a Korean father and a Korean American son that both identifies and challenges familiar sets of binary paradigms around race, gender, and labour. While Asian labour has frequently been marginalized and devalued throughout history through the reproduction of racial stereotypes, Aubergine deconstructs such imagery by depicting an Asian American chef who restores the labour of cooking to its original meaning by making food for his dying father. This restored labour of cooking restores filial love as well: Cho turns the father-son conflict caused by labour into a father-son reconciliation enabled by the value of work. After analysing how domestic labour in general and culinary labour in particular have been racialized, gendered, and undervalued for Asian Americans, I examine how Cho simultaneously recuperates working lives and Asian American father-son relationships. Through this process, I illuminate the importance of labour in thinking about family conflicts in Asian American drama more broadly.
The Freedom Mythology of Father Comes Home from the Wars
Authors: Turley Elliott
Published: January 2025

This article analyses how Suzan-Lori Parks’s trilogy Father Comes Home from the Wars (Parts 1, 2, & 3) remakes American Civil War mythology and interrogates the enduring myth of American freedom. Parks, I argue, combines Greek mythology with Black American history to create a new, Parksian mode of myth-making. First, I highlight Parks’s exploration of the paradoxes underneath the Lost Cause myth (in the Barthesian sense of the word) that Black men willingly fought for the Confederacy. Next, I probe the trilogy’s treatment of American freedom more broadly, assessing freedom’s historical and philosophical complicity with property and bondage. Finally, I examine how Parks envisions in Father a version of a freedom grounded not in property but performativity—a freedom that has propelled struggles for Black equality from pre–Civil War slavery to the present day.
Comprehensive Analysis of a Bridged-T Pre-Equalizer Circuit for High-Speed Visible Light Communications
Authors: Ab Aziz Siti Hajar , Mohd Nor Norhanis Aida , Zabidi Suriza Ahmad
Published: January 2025

This paper presents a comprehensive analysis of a bridged-T equalizer circuit (BTEC) designed for a high-speed visible light communications (VLC) system. The circuit is proposed to overcome the bandwidth limitation of light-emitting diodes (LEDs) in the VLC system. The advanced design system (ADS) and MATLAB were integrated to analyze the behavior of the BTEC in terms of transfer functions and scattering parameters S11, S12, S21, and S22. The results indicate a good correlation between the two tools, with the center frequency being 786 MHz. The 3-dB lower and upper cut-off frequencies are 501 MHz and 1.23 GHz, respectively. The impedance point is at magnitude 1 and 0 phase degrees on the Smith chart. This precise point ensures optimal matching to 50 ? of source and load impedance. This simulation proves that the bridged-T pre-equalizer circuit is a symmetric and reciprocal network since S11 = S22 and S12 = S21. This work combines the computational capabilities of MATLAB with the circuit simulation capabilities of ADS, which satisfied the pre-equalizer circuit experimental stage.
ABSTRAK: Kertas kerja ini membentangkan analisis komprehensif bagi litar penyama T terjepit (BTEC) yang direka untuk sistem komunikasi cahaya nampak (VLC) berkelajuan tinggi. Litar ini dicadangkan untuk mengatasi had lebar jalur diod pemancar cahaya (LED) dalam sistem VLC. Sistem reka bentuk lanjutan (ADS) dan MATLAB telah disepadukan untuk menganalisis kelakuan BTEC dari segi fungsi pemindahan dan parameter serakan S11, S12, S21, dan S22. Keputusan menunjukkan korelasi yang baik antara kedua-dua alat, dengan frekuensi tengah ialah 786 MHz. Frekuensi potong bawah dan atas 3-dB ialah 501 MHz dan 1.23 GHz, masing-masing. Titik impedans adalah pada magnitud 1 dan 0 darjah fasa pada carta Smith. Titik tepat ini memastikan padanan optimum kepada 50 ? sumber dan galangan beban. Dalam simulasi ini, terbukti bahawa litar pra-penyamaan bridged-T adalah rangkaian simetri dan timbal balik sejak S11 = S22 dan S12 = S21. Kerja ini menggabungkan keupayaan pengiraan MATLAB dengan keupayaan simulasi litar ADS, yang memenuhi peringkat percubaan litar pra-penyamaan.
Optimizing FPGA Resource Allocation for SHA-3 Using DSP48 and Pipelining Techniques
Authors: Putra Agfianto Eko , Natan Oskar , Istiyanto Jazi Eko
Published: January 2025

Deploying SHA-3 on FPGA devices requires significant resource allocation; however, the resulting throughput still needs improvement. This study employs the DSP48 module on the Xilinx FPGA to address this issue and implements an eight-stage pipeline methodology to minimize latency. The implementation design comprises a datapath and controller module, utilizing a Xilinx Artix-7-100T series FPGA as the hardware. This method makes use of FPGA resources like Look-Up Tables (LUT), Look-Up Table Random Access Memory (LUTRAM), Flip-Flops (FF), Block RAM (BRAM), Digital Signal Processing (DSP), Input/Output (IO), and Buffer (BUFG). The system's highest frequency is 107.979 MHz, achieving different throughputs for cryptographic hash functions. Specifically, it performs a throughput of 5.183 Gbps for SHA3-224, 4.895 Gbps for SHA3-256, 3.743 Gbps for SHA3-384, and 2.591 Gbps for SHA3-512.
ABSTRAK: Menggunakan SHA-3 pada peranti FPGA memerlukan peruntukan sumber yang ketara, walaupun daya pengeluaran yang terhasil adalah terhad. Untuk menangani isu ini, kajian ini menggunakan modul DSP48 yang disertakan pada Xilinx FPGA dan melaksanakan metodologi saluran paip lapan peringkat untuk meminimumkan kependaman. Reka bentuk pelaksanaan terdiri daripada laluan data dan modul pengawal, menggunakan siri FPGA  Xilinx Artix-7-100T sebagai perkakasan. Kaedah ini menggunakan sumber FPGA seperti Look-Up Tables (LUT), Look-Up Table Random Access Memory (LUTRAM), Flip-Flops (FF), Block RAM (BRAM), Digital Signal Processing (DSP), Input/Output (IO), dan Penampan (BUFG). Kekerapan tertinggi sistem ialah 107.979 MHz, dan ia mencapai daya pemprosesan yang berbeza untuk fungsi cincang kriptografi yang berbeza. Secara khususnya, ia mencapai daya pemprosesan 5.183 Gbps untuk SHA3-224, 4.895 Gbps untuk SHA3-256, 3.743 Gbps untuk SHA3-384 dan 2.591 Gbps untuk SHA3-512.
Global-Local Self-Attention-Based Long Short-Term Memory with Optimization Algorithm for Speaker Identification
Authors: Ghate Pravin Marotrao , Jadhav Bhagvat D. , Kulkarni Shriram Sadashiv , Chopade Pravin Balaso , Kota Prabhakar N.
Published: January 2025

Speaker identification (SI) involves recognizing a speaker from a group of unknown speakers, while speaker verification (SV) determines if a given voice sample belongs to a particular person. The main drawbacks of SI are session variability, noise in the background, and insufficient information. To mitigate the limitations mentioned above, this research proposes Global Local Self-Attention (GLSA) based Long Short-Term Memory (LSTM) with Exponential Neighborhood – Grey Wolf Optimization (EN-GWO) method for effective speaker identification using TIMIT and VoxCeleb 1 datasets. The GLSA is incorporated in LSTM, which focuses on the required data, and the hyperparameters are tuned using the EN-GWO, which enhances speaker identification performance. The GLSA-LSTM with EN-GWO method acquires an accuracy of 99.36% on the TIMIT dataset, and an accuracy of 93.45% on the VoxCeleb 1 datasets, while compared to SincNet and Generative Adversarial Network (SincGAN) and Hybrid Neural Network – Support Vector Machine (NN-SVM).
ABSTRAK: Pengenalpastian pembicara (Speaker Identification, SI) melibatkan pengenalan pembicara daripada kumpulan pembicara yang tidak dikenali, manakala pengesahan pembicara (Speaker Verification, SV) menentukan sama ada sampel suara tertentu milik seseorang individu. Kekurangan utama dalam SI ialah variasi sesi, bunyi latar belakang, dan maklumat yang tidak mencukupi. Untuk mengatasi kekangan tersebut, kajian ini mencadangkan kaedah Global Local Self-Attention (GLSA) berasaskan Long Short-Term Memory (LSTM) dengan Pengoptimuman Grey Wolf Jiranan Eksponen (EN-GWO) bagi pengenalpastian pembicara yang berkesan menggunakan set data TIMIT dan VoxCeleb 1. GLSA digabungkan dalam LSTM yang memberi tumpuan pada data yang diperlukan, manakala parameter hiper ditala menggunakan EN-GWO untuk meningkatkan prestasi pengenalpastian pembicara. Kaedah GLSA-LSTM dengan EN-GWO mencapai ketepatan 99.36% pada dataset TIMIT dan ketepatan 93.45% pada dataset VoxCeleb 1, berbanding dengan SincNet dan Generative Adversarial Network (SincGAN) serta Hybrid Neural Network – Support Vector Machine (NN-SVM).
Improving Model Performance for Predicting Exfiltration Attacks Through Resampling Strategies
Authors: Hakim Arif Rahman , Ramli Kalamullah , Salman Muhammad , Agustina Esti Rahmawati
Published: January 2025

Addressing class imbalance is critical in cybersecurity applications, particularly in scenarios like exfiltration detection, where skewed datasets lead to biased predictions and poor generalization for minority classes. This study investigates five Synthetic Minority Oversampling Technique (SMOTE) variants, including BorderlineSMOTE, KMeansSMOTE, SMOTEENC, SMOTEENN, and SMOTETomek, to mitigate severe imbalance in our customized tactic-labeled dataset with dominant majority class influence and weak class separability class imbalance. We use seven imbalance metrics to assess each SMOTE variant’s impact on class distribution stability and separability. Furthermore, we evaluate model performance across five classifiers: Logistic Regression, Naïve Bayes, Support Vector Machine, Random Forest, and XGBoost. Findings reveal that SMOTEENN consistently enhances performance metrics (accuracy, precision, recall, F1-score, and geometric mean) on an average of 99% across most classifiers, establishing itself as the most adaptable variant for handling imbalance. This study provides a comprehensive framework for selecting resampling strategies to enhance classification efficacy in cybersecurity tasks with imbalanced data.
ENSINO DE FÍSICA E INTERDISCIPLINARIDADE
Authors: Pereira Costa William Henrique , Andrade Silva Gabriel , Fernandes Silva Luciano
Published: January 2025

: Em um mundo globalizado, no qual as fronteiras disciplinares estão cada vez mais tênues, a interdisciplinaridade tem um importante papel no contexto educacional, principalmente em áreas do conhecimento como a Física. No contexto da educação básica, a organização das práticas pedagógicas deve se pautar pelos eixos da interdisciplinaridade e da contextualização. A partir dessas orientações, elaborou-se e aplicou-se uma sequência didática fundamentada nos preceitos da interdisciplinaridade e da contextualização. A sequência didática foi construída em torno do tema “Física das Pandemias”. Esse foi o cenário para a construção de uma investigação orientada pelo objetivo: identificar e analisar conhecimentos mobilizados pelos alunos ao discutirem aspectos relacionados às pandemias durante as aulas de Física. Procurou-se identificar e analisar que relações são estabelecidas por estudantes entre a Física e outras ciências para a discussão de aspectos relacionados ao tema Pandemias. A sequência didática foi composta por oito aulas, aplicadas junto a alunos que frequentavam um curso pré-vestibular assistencial. Dentre os resultados mais significativos, destaca-se que a organização de práticas pedagógicas interdisciplinares traz uma série de desafios aos professores, sobretudo ao possibilitar a superação da rígida linearidade e fragmentação do ensino.
EXPLORING INTERACTIVE STRATEGIES FOR TEACHING PATHOLOGY IN NURSING GRADUATION IN SOUTHEAST BRAZIL
Authors: Germano da Silva Andressa , Ferreira Santino Samara , Garnevi Fávero Aline , Xavier Souza Rosana , Luiz Brandão André , Araki Ribeiro Daniel , Yujra Veronica Quispe , De Moraes Malinverni Andréa Cristina
Published: January 2025

A pandemia de COVID-19 trouxe desafios para a educação, ressaltando a necessidade de soluções inovadoras no ensino da saúde. Desde 2002, o MEC recomendou metodologias ativas nas Diretrizes Nacionais Curriculares (DNCs). Este estudo avalia o ensino de Patologia em cursos de Enfermagem em IES públicas no Sudeste do Brasil. Também analisa as opiniões dos alunos sobre a tutoria de pós-graduandos na UNIFESP. Foram coletados dados de 21 cursos de Enfermagem e formulários da UNIFESP entre 2019 e 2023, durante a implementação do programa de aperfeiçoamento didático (PAD). A análise foi estatística. Os resultados indicam a necessidade de ajustes curriculares, devido à falta de padronização na carga horária de Patologia, com variações na estrutura e metodologia. Em relação à metodologia ativa, 90% dos alunos da UNIFESP a consideraram muito boa.
PANORAMA SOBRE TECNOLOGIAS EDUCACIONAIS E A DESIGUALDADE ENTRE OS PAÍSES: UM ESTUDO BIBLIOMÉTRICO
Authors: Palácios Emilly Kelen , Gonçalves dos Santos Eloiza , Alves Marinho Daniele
Published: January 2025

Pesquisadores do mundo inteiro têm se dedicado para entender os impactos que envolvem as tecnologias dentro do contexto educacional. Este estudo bibliométrico analisa a produção mundial sobre tecnologias educacionais no ensino fundamental, com o objetivo de investigar se reflete as desigualdades de acesso destacadas pela UNESCO. A metodologia incluiu buscas em bases de dados indexadas e análise estatística dos resultados usando o software R. Os Estados Unidos e a China lideram tanto em produção quanto em citações, evidenciando sua influência na área. Embora os resultados sugiram uma correlação entre acesso à tecnologia e produção acadêmica, há limitações, como a falta de pesquisas aplicadas em contextos específicos. Conclui-se que a desigualdade de acesso pode impactar as produções sobre tecnologias educacionais, mas o estudo não esgota o tema, destacando a complexidade da relação entre tecnologia e educação. Essas descobertas podem auxiliar a atualização de políticas educacionais e direcionar futuras pesquisas na área.
IMPLEMENTASI MODEL DEVOPS (DEVELOPMENT DAN OPERATION) PADA APLIKASI PENGELOLAAN ANGGARAN PENGADAAN BARANG DAN INVENTARIS BARANG DAN MONITORING PADA CV USAHA BERSAMA
Authors: Sirajuddin Haji , Rusdi Muhammad , Hijriana Nadiya , Alfah Rina
Published: January 2025

Untuk mendukung kemajuan teknologi, penggunaan  berbagai teknologi digital dapat diaplikasikan dalam pengelolaan anggaran dana barang dan pendataan barang inventaris agar mempermudah pekerjaan pada suatu usaha/kantor . Hal ini dapat mempermudah bendahara barang, pimpinan dan pegawai dalam memonitoring data dan meminimalisir waktu pendataan barang dan anggarannya serta dapat melaporkan rekapan data yang dapat dicetak. Kami mengimplementasikan model devops (Development dan Operation) untuk CV Usaha bersama sebagai objek penelitian. Model devops (Development dan Operation) yang digunakan dalam pembuatan aplikasi ini  bersifat sistematis dan berurutan dalam membangun sistem. Hasil dari sistem ini berupa aplikasi yang berguna bagi bendahara barang, pimpinan dan pegawai yang ada pada CV Usaha bersama dalam pengelolaan anggaran dana barang dan pendataan barang inventaris dengan lebih baik lagi, di mana nantinya aplikasi ini dapat membantu kinerja pegawai untuk kedepannya, dengan adanya aplikasi ini dapat menampilkan semua data berkaitan dengan pengelolaan anggaran dana barang dan inventaris barang.
PENERAPAN ALGORITMA K-MEANS UNTUK MENGELOMPOKKAN KUNJUNGAN WISATAWAN PADA DUA PULUH TEMPAT WISATA DI JAKARTA
Authors: Wasesha Dian Ambar , Syafrianto Syafrianto
Published: January 2025

Dengan meningkatnya jumlah kunjungan wisatawan setelah pembatasan perjalanan, analisis mendalam menjadi penting untuk memahami preferensi wisatawan dan mengelola volume kunjungan yang terus bertambah. Penelitian ini bertujuan untuk menganalisis pola kunjungan wisatawan nusantara pada dua puluh lokasi daya tarik wisata di Provinsi DKI Jakarta. Algoritma K-Means digunakan untuk mengelompokkan lokasi wisata berdasarkan data kunjungan, menghasilkan tiga cluster utama. Cluster 1 terdiri dari 17 lokasi yang berfokus pada wisata sejarah dan budaya, seperti Taman Mini Indonesia Indah dan Museum Nasional. Cluster 2 mencakup dua lokasi yang lebih difokuskan untuk rekreasi dan edukasi umum, yaitu Taman Marga Satwa Ragunan dan Monumen Nasional. Sementara itu, Cluster 3, yang berisi satu lokasi, yaitu Taman Impian Jaya Ancol, menarik wisatawan dengan beragam atraksi hiburan modern. Hasil penelitian ini memberikan wawasan bagi pengembangan pariwisata Jakarta yang berkelanjutan, memungkinkan pemerintah dan pengelola wisata untuk merancang strategi pemasaran sesuai karakteristik masing-masing cluster, serta merencanakan infrastruktur yang sesuai.
ANALISIS CAPABILITY TATA KELOLA TEKNOLOGI INFORMASI MENGGUNAKAN KERANGKA KERJA COBIT 2019 (STUDI KASUS: DISKOUMPERINDAG KABUPATEN SERANG, BANTEN)
Authors: Krisnanik Erly , Muliawati Anita , Rahayu Tri , Puspita Dewi Catur Nugrahaeni , Hesti Indriana Intan
Published: January 2025

Penelitian ini menganalisis capability tata kelola teknologi informasi pada instansi pemerintah lokal menggunakan kerangka kerja COBIT 2019. Tata kelola TI yang efektif penting untuk mendukung tujuan organisasi dan memberikan nilai kepada para pemangku kepentingan. Namun, banyak instansi pemerintah yang belum mencapai tingkat kapabilitas tata kelola TI yang optimal, khususnya dalam mendukung pelayanan publik. Untuk mengatasi kesenjangan pengetahuan ini, penelitian ini menggunakan pendekatan kuantitatif dengan kerangka kerja COBIT 2019 yang meliputi domain-domain penting seperti EDM01, EDM02, APO02, APO03, APO12, APO13, BAI06, DSS04, DSS06 dan MEA02. Data dikumpulkan melalui survei, wawancara terstruktur, dan analisis dokumen untuk mengukur tingkat kapabilitas pada Diskoumperindag Kabupaten Serang. Hasil penelitian menunjukkan tingkat kapabilitas yang bervariasi di setiap domain, dengan rekomendasi peningkatan pada aspek keamanan, transparansi, dan akuntabilitas. Implikasi dari hasil ini menunjukkan bahwa peningkatan tata kelola TI dapat memperkuat efektivitas layanan publik dan memastikan bahwa TI mendukung tujuan organisasi secara optimal. Penelitian ini juga memberikan wawasan bagi pemangku kepentingan dalam merumuskan kebijakan dan strategi pengembangan tata kelola TI yang lebih terukur dan sesuai kebutuhan pemerintah daerah
INTEGRASI MODEL NEURAL NETWORK DENGAN SVM DAN KNN UNTUK DETEKSI DINI PENYAKITA JANTUNG PADA PENDERITA HYPERTENSI
Authors: Arfian Andi , Siregar Juarni , Wijayanti Diah
Published: January 2025

Penyakit jantung, yang bisa berakibat fatal jika tidak ditangani dengan tepat, menjadi salah satu penyebab kematian utama di dunia. Berdasarkan data dari Organisasi Kesehatan Dunia (WHO), sekitar 17,5 juta orang meninggal setiap tahun akibat penyakit jantung, dan angka ini diperkirakan akan meningkat menjadi 75 juta pada tahun 2030. Namun, para tenaga medis dalam bidang kardiologi memiliki keterbatasan dalam memprediksi serangan jantung, dengan akurasi hanya mencapai 67%. Oleh karena itu, diperlukan sistem yang dapat membantu dokter dalam memberikan prediksi penyakit jantung yang lebih akurat. Penelitian ini bertujuan untuk mengembangkan model neural network yang dapat memprediksi potensi penyakit jantung pada penderita hipertensi, dengan menggunakan model SVM dan KNN. Model ini didesain berdasarkan parameter medis seperti tekanan darah, detak jantung, kadar kolesterol, usia, dan indikator kesehatan lainnya. Metode supervised learning digunakan dalam pelatihan model, yang melibatkan data historis dari pasien hipertensi. Hasil pengujian menunjukkan bahwa model SVM memiliki precision (0.819) yang lebih tinggi dibandingkan dengan KNN (0.63). Selain itu, berdasarkan Matthews Correlation Coefficient (MCC), SVM menunjukkan hasil lebih baik (0.63) dibandingkan KNN (0.26).  Dengan hasil ini, dapat disimpulkan bahwa model SVM lebih efektif dalam memprediksi penyakit jantung dan dapat menjadi pilihan utama dalam membantu tenaga medis dalam pengambilan keputusan klinis. Model ini diharapkan dapat berfungsi sebagai alat bantu dalam melakukan intervensi dini untuk mencegah kondisi yang lebih serius. Penelitian ini berkontribusi pada pengembangan solusi berbasis kecerdasan buatan dalam sektor kesehatan, khususnya dalam pencegahan penyakit jantung pada penderita hipertensi.
SISTEM INFORMASI PENGELOLAAN BANK SAMPAH BERBASIS WEB DALAM MENINGKATKAN KEMUDAHAN TRANSAKSI (STUDI KASUS: BANK SAMPAH KARYA MANDIRI)
Authors: Annisha Angelin Fitri , Kusuma Pradana Teguh Hari , Afriansyah Riki , Fujiyanti Linda
Published: January 2025

Masalah pengelolaan sampah di Indonesia terus meningkat, sementara bank sampah menawarkan solusi berbasis komunitas dengan manfaat ekonomi. Penelitian ini bertujuan membuat dan mengambangkan sistem informasi berbasis web untuk Bank Sampah Karya Mandiri untuk meningkatkan efisiensi dan transparansi pengelolaan pada Bank Sampah Karya Mandiri. Menggunakan metode prototype, sistem ini dirancang iteratif dengan fitur pencatatan otomatis, akses berbasis peran, dan portal nasabah untuk memantau transaksi. Hasil menunjukkan sistem ini mampu meningkatkan efisiensi, mengurangi kesalahan, dan menyediakan akses transparan, mendukung pengelolaan sampah yang lebih baik dan berkelanjutan.
DESAIN SISTEM INFORMASI PENJUALAN RUMAH MENGGUNAKAN METODE OBJECT ORIENTED ANALYSIS AND DESIGN (OOAD)
Authors: Dewi Suzana , Solaiman Marcia Sheva , Atmojo Suryo , Widhiyanta Nurwahyudi
Published: January 2025

Perkembangan   informasi   teknologi sangat sedemikian hebatnya dan cepat, salah   satu  bidang yang berkembang cepat adalah  ilmu terkait dengan komputer.   Masa kini,   komputer memiliki peranan   penting dalam mempermudah proses penyelesaian suatu pekerjaan yang telah ditentukan, sehingga ini menyebabkan  kebutuhan  untuk  sistem  informasi  yang tepat, informatif, dan lengkap bertujuan untuk   mendorong   manusia   dapat   melakukan  kegiatannya, sehingga dapat dijalankan dengan cepat serta akurat. Adapun tujuan penulisan adalah agar digunakan untuk  merancang  sistem dan menganalisa kegiatan penjualan perumahan perusahaan properti terkait,   sehingga dapat  mendukung berbagai pihak  yang terkait proses  pengumpulan data, khususnya dalam  kegiatan penjualan  perumahan.Untuk melakukan penelitian seperti dijelaskan di atas, ada hal yang akan dilakukan, sehingga hasil penelitian dapat ada hasil dan ada manfaat info bagi pembaca, hal yang akan dilakukan dan dijadikan dasar adalah suatu analisa untuk mengetahui dan melihat penyusunan yang terjadi. Hal ini akan dilakukan lewat tanya jawab dengan audiens yang terkait.     Metode perancangan dilakukan menggunakan metode analisa perancangan atau penyusunan dan pengembangan perangkat atau peralatan lunak yang disebut sebagai metode Desain Analisa yang Berfokus pada Obyek (dan disingkat dengan OOAD). Hasil  yang dicapai  adalah sebuah application (aplikasi), yang berfungsi sebagai pendukung sangat bagus dalam kegiatan pemasaran Perusahaan Properti terkait.  Kesimpulan  yang didapat adalah  sistem  penjualan dapat mempermudah    proses dan memenuhi   kebutuhan   informasi   diperlukan.
FONDASI MODERASI BERAGAMA DALAM DINAMIKA ERA DIGITAL DI INDONESIA
Authors: Puteri Rahmi Yuningsih
Published: January 2025

Dalam era digital yang terus berkembang, moderasi beragama menjadi sangat penting untuk mempertahankan keharmonisan sosial di Indonesia, negara dengan populasi muslim terbesar di dunia. Penelitian ini bertujuan untuk mengeksplorasi dan memahami bagaimana fondasi moderasi beragama dibangun dan dipertahankan dalam konteks dinamika digital. Metode yang digunakan adalah kualitatif deskriptif, yang memungkinkan peneliti untuk menggali pengalaman dan perspektif berbagai pihak, termasuk pemuka agama, generasi muda, dan praktisi digital. Melalui wawancara mendalam dan observasi partisipatif, data dikumpulkan untuk menganalisis tantangan dan peluang yang dihadapi dalam menyebarluaskan nilai-nilai moderasi beragama. Hasil penelitian menunjukkan bahwa media sosial berperan penting dalam membentuk pandangan masyarakat tentang moderasi beragama. Di satu sisi, platform digital memberikan akses yang lebih luas terhadap informasi agama, memfasilitasi dialog lintas agama, dan mendorong pemahaman yang lebih inklusif. Namun, di sisi lain, tantangan muncul dari penyebaran konten intoleran dan radikal yang dapat memicu perpecahan. Para responden sepakat bahwa meskipun digitalisasi menawarkan peluang, perlu adanya pengawasan yang lebih ketat terhadap konten yang beredar untuk menjaga nilai-nilai moderasi beragama tetap terjaga. Penelitian ini menegaskan pentingnya kolaborasi lintas sektor antara pemerintah, organisasi masyarakat, dan komunitas digital untuk menciptakan ekosistem yang mendukung moderasi beragama. Upaya bersama dalam bentuk program edukasi, kampanye kesadaran, dan pelatihan literasi digital diharapkan dapat memperkuat fondasi moderasi beragama di Indonesia. Dengan demikian, penelitian ini tidak hanya memberikan kontribusi akademis, tetapi juga menawarkan wawasan praktis bagi para pemangku kepentingan dalam mempromosikan nilai-nilai moderasi beragama di tengah tantangan yang dihadapi di era digital.Keywords:  Moderasi Beragama; Era Digital; Kolaborasi Lintas Sektor; Literasi Digital
SISTEM CERDAS PENGENDALI PADA KAMAR HOTEL MENGGUNAKAN SIDIK JARI BERBASIS INTERNET OF THINGS
Authors: Sulistyo Eko , Tristha Adysha , Oktariana Nabila , Irwan Irwan
Published: January 2025

Kamar hotel adalah ruangan yang sangat pribadi bagi setiap tamu yang penyewanya. Keamanan kamar hotel menjadi sangat penting. Saat ini, sistem pengunci pintu kamar hotel telah menggunakan teknologi RFID. Namun, penggunaannya masih kurang optimal karena setiap kamar hanya dapat diakses dengan satu kartu. Oleh karena itu, diperlukan penerapan teknologi kunci pintu otomatis berbasis sidik jari pada kamar hotel adalah meningkatkan keamanan dan kenyamanan tamu, teknologi ini menghemat energi dengan otomatis mengaktifkan lampu dan AC saat pintu terbuka, sambil tetap menyediakan kontrol manual, sehingga memberikan pengalaman lebih efisien dan aman dibandingkan sistem kunci RFID. Tahapan metodelogi meliputi studi literatur, perancangan perangkat keras dan lunak, perakitan sistem menggunakan ESP32, dan pengujian integrasi hardware dan software untuk memastikan performa sistem. Proses ini mencakup desain rangkaian elektrikal dan pembuatan website berbasis CodeIgniter. Pengujian ini menganalisis kinerja sensor sidik jari dengan membandingkan kondisi sidik jari terdaftar dan tidak terdaftar. Setiap kamar menggunakan satu sensor fingerprint dengan satu sidik jari terdaftar. Data pembacaan sidik jari, respons LCD, serta reaksi selenoid, kipas, dan lampu diamati, termasuk waktu deteksi. Sistem berhasil memberikan solusi keamanan praktis dan efisien untuk kamar hotel, menggantikan kartu akses, meningkatkan kenyamanan pengguna, dan menghemat energi secara signifikan.
Liderazgo educativo y clima escolar: un estudio de caso en una escuela pública en Chile
Authors: Carrasco-Aguilar Claudia , Verdejo Tabisa , Ortiz-Mallegas Sebastián , Valdenegro-Egozcue Boris , Figueroa Varela Marlen
Published: January 2025

In recent years, the field of educational leadership has garnered increasing attention with a growing emphasis on its relationship with school climate and coexistence. This study examined the facilitators of educational leadership in fostering a positive school climate, drawing on the experiences and perceptions of teachers at a primary school in Chile. Employing a qualitative single case study approach, the research  was conducted in an educationally vulnerable context, characterized by  an Institutional Educational Project (IEP) and Internal Regulations (IR) centered on affectivity and achieving  high learning outcomes. Data collection methods included observations, document reviews, and interviews with key stakeholders: for second-cycle primary school teachers, the school principal, and the coexistence coordinator.  A reflexive thematic analysis revealed five emergent categories: (i) the introduction of new leadership practices, (ii) the cultivation of an affective organizational climate, (iii) the implementation of situated pedagogical leadership, (iv) the adoption of shared responsibility in coexistence management, and (v) unresolved tensions as persistent challenges. These findings highlight the interplay of leadership styles, and identify key facilitators in addressing the research question.
Optimizing Single-Inverter Electric Differential System for Electric Vehicle Propulsion Applications
Authors: Moumni Rachad , Laroussi Kouider , Benlaloui Idriss , Mahmoud Mohamed Metwally , Elnaggar Mohamed F.
Published: January 2025

The increasing demand for electric vehicles (EVs) is driven by the urgent need for environmentally friendly transportation. This paper addresses the challenge of optimizing EV drivetrain efficiency by proposing a novel single-inverter electronic differential system for distributed EV drivetrains. The research focuses on reducing system cost and complexity while maintaining high performance. The methodology involves a detailed simulation using MATLAB/Simulink to validate the theoretical soundness of the proposed connection method. The results demonstrate that the proposed system achieves a minimum accuracy rate of 97.5%, marking a significant improvement over traditional dual-inverter systems. This approach not only enhances drivetrain efficiency but also contributes to more compact and cost-effective vehicle designs. Additionally, the findings underscore the potential for further refinement and exploration, suggesting that continued advancements in ED systems could lead to even greater performance gains in the future. This research lays the groundwork for future innovations in EV technology, particularly in the areas of cost reduction and system efficiency.
Accurate Robot Navigation Using Visual Invariant Features and Dynamic Neural Fields
Authors: Raoui Younès , Elmennaoui Nouzha
Published: January 2025

Robot navigation systems are based on Simultaneous Localization and Mapping (SLAM) and obstacle avoidance. We construct maps for the robot using computer vision methods requiring high repeatability for consistent feature tracking. Also, the obstacle avoidance method needs an efficient tool for fusing data from multiple sensors. This research enhances SLAM accuracy and obstacle avoidance using advanced visual processing and dy namic neural fields (DNF). We propose two key methods: (1) an enhanced multiscale Harris detector using steerable filters for robust feature extrac tion, achieving around 90% repeatability; and (2) a dynamic neural field algorithm that predicts the optimal heading angle by integrating visual de scriptors and LIDAR data. The first method’s experimental results show that the new feature detector achieves high accuracy, outperforming exist ing methods. Its invariance to the orientation of the image makes it insen sitive to the rotations of the robot. We applied it to the monocular SLAM and remarked that the positions of the robot were computed precisely. In the second method, the results showed that the dynamic neural fields algo rithm ensures efficient obstacle avoidance by fusing the gist of the image and LIDAR data, resulting in more accurate and consistent navigation than laser-only methods. In conclusion, the study presents significant advance ments in robot navigation through robust feature detection for SLAM and effective obstacle avoidance using dynamic neural fields. These advance ments significantly enhance precision and reliability in robot navigation, paving the way for future innovations in autonomous robotic applications.
Comparative Analysis of Path Planning Algorithms for Multi-UAV Systems in Dynamic and Cluttered Environments: A Focus on Efficiency, Smoothness, and Collision Avoidance
Authors: Sukwadi Ronald , Airlangga Gregorius , Basuki Widodo Widjaja , Kristian Yoel , Rahmananta Radyan , Sugianto Lai Ferry , Nugroho Oskar Ika Adi
Published: January 2025

This study evaluates the performance of various path planning algorithms for multi-UAV systems in dynamic and cluttered environments, focusing on critical metrics such as path length, path smoothness, collision avoidance, and computational efficiency. We examined several algorithms, including A*, Genetic Algorithm, Modified A*, and Particle Swarm Optimization (PSO), using comprehensive simulations that reflect realistic operational conditions. Key evaluation metrics were quantified using standardized methods, ensuring the reproducibility and clarity of the findings. The A* Path Planner demonstrated efficiency by producing the shortest and smoothest paths, albeit with minor collision avoidance limitations. The Genetic Algorithm emerged as the most robust, balancing path length, smoothness, and collision avoidance, with zero violations and high feasibility. Modified A* also performed well but exhibited slightly less smooth paths. In contrast, algorithms like Cuckoo Search and Artificial Immune System faced significant performance challenges, especially in adapting to dynamic environments. Our findings highlight the superior performance of the Genetic Algorithm and Modified A* under these specific conditions. We also discuss the potential for hybrid approaches that combine the strengths of these algorithms for even better performance. This study's insights are critical for practitioners looking to optimize multi-UAV systems in challenging scenarios.
Application of Artificial Neural Networks in Predicting Internal Combustion Engine Performance and Emission Characteristics: A Review of Key Methodologies and Findings
Authors: Mohasab Hamada , Abouelsoud Mostafa , Shmroukh Ahmed N. , Ghazaly Nouby
Published: January 2025

The global need for fuel-efficient coupled with minimizing the environmental impacts of ICEs. This review paper highlights how different ANN methodologies such as backpropagation, recurrent neural networks (RNNs), and long short-term memory (LSTM) networks have been applied to optimize engine calibration, improve fuel efficiency, and minimize emissions across a wide range of fuel blends, including hydrogen-gasoline and ethanol-gasoline mixtures. The research focuses on the application of ANN models to predict performance indicators such as brake thermal efficiency, brake-specific fuel consumption, and emissions, reducing reliance on costly and time-consuming experimental tests. The methodology involved a systematic review of peer-reviewed studies published between 2010 and 2024. Studies were selected based on criteria such as relevance to ICE performance and emission control, use of ANN methodologies, and the availability of experimental or simulation data for validation. involves the use of advanced ANN architectures, including backpropagation, RNNs, and LSTM networks, to establish nonlinear relationships between input parameters such as engine speed, load, and fuel type, and output performance indicators. Findings show that comparison between real model and developed program enhanced from ANN model make a difference prediction capability for engine performance enhanced by at least 10 to 15 % of the traditional modeling. techniques, provide better calibration method of ICEs for better fuel consumption. efficiency and reduced emissions. This present study seeks to establish itself in matters that have not been explored in other papers or researches as follows. integration of Hybrid ANN models, which are better than conventional methods in two major trends, one of which is the improvement of the predictive accuracy and the other is the achievement of increased computational efficiency. It is found that the ANN methodologies presents a strong armory in improving the performance of ICE coupled with lowering of emissions with the possibilities of additions for further enhancements of the technology through the incorporation of other machines use of learning techniques in the future studies.
Sensorless Speed Estimation Basing on MRAS Model for a PMSM Machine Application
Authors: Elnaggar Mohamed F. , Aymen Flah , Mourad Dina
Published: January 2025

Wind energy systems utilizing synchronous machines can encounter challenges with speed detection at high rotational speeds due to increasing motor temperatures affecting parameters like stator resistance. This paper addresses these challenges by proposing a novel high-speed estimator algorithm based on the Model Reference Adaptive System (MRAS) approach. The primary contribution of this research is the development of an MRAS-based speed estimator that leverages a reactive power model to maintain robustness against variations in stator resistance, even at elevated speeds. To optimize the estimator’s performance, we employed a particle optimization algorithm for tuning, which overcomes issues related to regulator parameter identification. We implemented the proposed algorithm in Matlab and validated it on a real machine prototype capable of high-speed operation. After a comparison wth 5 different methods, the results indicate that the estimator performs effectively up to 42,000 RPM (600 Hz), demonstrating a maximum speed estimation error of 50 Hz. Stability analyses across various speed regions and practical lab tests confirm the robustness and accuracy of the proposed control scheme. The findings highlight the estimator’s improved performance in high-speed scenarios, showcasing its potential for enhancing speed detection in wind energy systems.
Design and Quality Evaluation of the Position and Attitude Control System for 6-DOF UAV Quadcopter Using Heuristic PID Tuning Methods
Authors: Mien Trinh Luong , Tu Tran Ngoc
Published: January 2025

Nowadays, UAV quadcopters are widely used in many fields, specially in transporting the lightweight goods parcels. This article aims to design and evaluation of the quality of the 6-DOF UAV quadcopter control system using heuristic PID tuning methods to ensure stable control of flight position and attitude. Firstly, the article presents the dynamic mathematical model of the 6-DOF UAV quadcopter, including 3 Euler angle variables and 3 flight position and altitude variables. From there, the article proposes the 6-DOF UAV control syste structure with two single control loops for flight attitude, yaw angle and two dual control loops for roll-pitch angles, flight position. And then, the article presents the application of the heuristic PID tuning methods to each control loop of a 6-DOF UAV quadcopter to calculate the PID controller parameters to ensure stable control the desired flight position and altitude. The simulation results and evaluating the 6-DOF UAV quadcopter control system quality in Matlab, using the proposed heuristic PID controllers, show that the PID controllers according to the Tyreus-Luyben method gives the best quality, with a steady-state error of less than 1%. The main contribution of this article is the comparative analysis of three heuristic PID tuning methods - Ziegler-Nichols, Tyreus-Luyben, PID tuner - for controlling the position and attitude of a 6-DOF UAV quadcopter.  These findings demonstrate that the proposed PID controllers can be effectively implemented in practical UAV applications, enhancing the stability and performance of quadcopters in various fields.
Enhanced RSA Optimized TID Controller for Frequency Stabilization in a Two-Area Power System
Authors: Ekinci Serdar , Eker Erdal , Izci Davut , Smerat Aseel , Abualigah Laith
Published: January 2025

This study presents an enhanced reptile search algorithm (ImRSA) optimized tilt-integral-derivative (TID) controller for load frequency control (LFC) in a two-area power system consisting of photovoltaic (PV) and thermal power units. The ImRSA integrates Lévy flight and logarithmic spiral search mechanisms to improve the balance between exploration and exploitation, resulting in more efficient optimization performance. The proposed controller is tested against the original reptile search algorithm (RSA) and other state-of-the-art optimization methods, such as modified grey wolf optimization with cuckoo search, black widow optimization, and gorilla troops optimization. Simulation results show that the ImRSA-optimized TID controller outperforms these approaches in terms of undershoot, overshoot, settling time, and the integral of time-weighted absolute error metric. Additionally, the ImRSA demonstrates robustness in managing frequency deviations caused by solar radiation fluctuations in PV systems. The results highlight the superior efficiency and reliability of the proposed method, especially for renewable energy integration in modern power systems.
Morphogenetic effects of long-term selection of American mink (Neogale vison Schreber, 1777) strains on characters of defensive behavior: Intra- and interspecific aspects
Authors: Vasil’ev A. G. , Chibiryak M. V. , Nekrasova M. A. , Stepanova M. A. , Trapezov O. V.
Published: January 2025

Since the time of Charles Darwin, the study of the mechanisms of domestication of animals as a model of rapid evolutionary transformations has been of general biological importance. Methods of Geometric morphometrics (GM) make it possible to assess the morphogenetic changes that occur during domestication. Using the experimental strains of American mink Neogale vison, selected for aggressive and tame behavior, significant differences in the centroid size (CS) and shape of the mandible were established between them. Cage non-selected and wild Canadian minks were used as controls. Selection has led to an increase in the CS of mandibles in aggressive and their decrease in tame ones. The greatest differences in the shape of mandibles were manifested between the aggressive and tame strains. The destabilization of mandible development, indirectly estimated by the volume of within-group morphospace (Vm) along the first canonical axes, turned out to be most pronounced in males and females of the tame mink strain, which is directly consistent with the theory of destabilizing selection by D. K. Belyaev. After 16–17 generations of mink selection for aggressive and tame behavior, morphogenetic effects were found, expressed in the divergence of the shape of their mandible, accompanied by destabilization of development, and reflecting the high rate of experimental domestication. The differentiation of the aggressive and tame minks by the shape of the mandibles exceeds the level of sexual differences and is comparable to the degree of morphological divergence between caged and wild Canadian individuals. It is accompanied by morphological hiatus and is formally close to the subspecific rank of intraspecific morphological differences compared with the morphological divergence of the American mink from another species – the Siberian weasel Mustela sibirica. The morphogenetic effects of American mink selection by behavior demonstrate the high adaptive and evolutionary potentials of this invasive species.
Biomarkers of stress in common coastal amphipods and bivalves under salinity gradient and pollution influence (the White Sea)
Authors: Berezina N. A.
Published: January 2025

Studies of the biochemical parameters of aquatic organisms are important for understanding the mechanisms of their adaptive reactions in response to the influence of environmental factors. They are also used in a comprehensive assessment of the quality of the aquatic environment under the influence of anthropogenic pollution. The purpose of the work is a comparative study of the biochemical parameters of marine invertebrates, showing neurotoxic effects, the process of antioxidant protection, and the functioning of the biotransformation system. These indicators are considered “biomarkers of stress” in aquatic organisms. Widespread White Sea species were chosen as model species: Gammarus oceanicus (Amphipoda: Malacostraca), Mytilus edulis (Mytilida: Bivalvia), and Mya arenaria (Myoida: Bivalvia). At the end of August 2015–2016, these invertebrates were collected from several locations of the littoral zone of the Kandalaksha Bay of the White Sea: the wild littoral in the absence of visible anthropogenic influence, and with different levels of local pollution (far from an urban settlement (Maly Pitkul Bay), on a wild beach near the confluence of the Niva River, near the port of Kandalaksha at the boat pier, and at the Kartesh biological station). In addition, a comparison was made between molluscs (M. edulis) living in the intertidal and subtidal zones (as part of mussel rope aquaculture). The highest levels of enzyme activity (catalase, glutathione-S-transferase) and increased levels of lipid peroxidation, indicating the state of oxidative stress in the amphipods and molluscs, were determined for animals living at the mouth of the Niva River and local pollution with oil products in the port of Kandalaksha. For each indicator, interspecies differences in response to impacts of one nature or another were found. Principal component analysis revealed two factors that explained 81.08% of the variability of the variables. The main influencing factors were the river reducing the salinity of the water and introducing pollutants into the sea, increasing the levels of metals (copper, zinc, and lead) in the water. The second important impact factor was local pollution of habitats with oil products (motor boats), and it was this second factor that was associated with changes in a large number of biochemical parameters of molluscs and amphipods, indicating the state of stress in organisms. The results of this study confirm the usefulness of using biochemical indicators of marine invertebrates to assess their condition under the influence of environmental stress factors, including pollution, and the high indicator significance of the applied biomarkers.