bluuebunny/crossref_metadata_2025 huggingface dataset:
RANCANG BANGUN SISTEM INFORMASI INVENTARIS FASILITAS PONDOK PESANTREN NURUL ULUM DENGAN MENGUNAKAN METODE XP (EXTREME PROGRAMMING)
Authors: Ridwan Nawawi Muhamad , Lestanti Sri , Fanny Dimas
Published: February 2023

Inventarisasi yang baik, sistematis, dan terstruktur atas barang yang terdapat di suatu tempat kerja atau forum adalah hal yang wajib dilakukan, sebab menggunakan adanya inventarisasi barang yang sistematis akan mengakibatkan proses kerja menjadi lebih efektif serta efisien. Sistem inventarisasi barang pada Pondok Pesantren Nurul Ulum ini perlu diadakan. Penelitian ini bertujuan untuk membentuk aplikasi berbasis website guna memudahkan pada perencanaan, pengadaan, penyaluran, serta pendataan atas barang-barang yang ada pada Pondok Pesantren Nurul Ulum. Pengembangan sistem informasi berbasis website ini dilakukan menggunakan Bahasa pemrograman PHP dan database MySQL. Metode pengembangan sistem yang digunakan pada pembuatan sistem informasi ini merupakan Extreme Programing. Pengujian perangkat lunak mengunakan 3 pengujian yaitu white box, black box, dan kuesioner dengan menghasilkan pengujian white box berjalan 100% tanpa ada masalah eror, pengujian black box bejalan 100% tanpa ada valid tanpa terdapat fungsi yang tidak berhasil, kuesioner yang menghasilkan 72% sangat setuju, 28% putusan bulat. Penelitian ini diperlukan bisa membantu pihak Pondok Pesantren dalam melakukan inventarisasi barang milik tempat kerja sebagai akibatnya menjadi lebih terstruktur dan sistematis buat mencapai efisiensi serta efektifitas kinerja admin Pondok Pesantren.
PENERAPAN DATA MINING METODE K-MEANS CLUSTERING UNTUK ANALISA PENJUALAN PADA TOKO YANA SPORT
Authors: Nugraha Agung , Nurdiawan Odi , Dwilestari Gifthera
Published: February 2023

Saat ini proses penjualan dan pemasaran yang di lakukan oleh Yana Sport masih sudah menggunakan aplikasi E-commerce, maka dari itu dengan pemanfaata teknologi informasi berupa E-commerce dapat memberikan peningkatan penjualan produk bagi Yanaspot. Akan tetapi persaingan dalam dunia bisnis pasti ada karena yang menjual barang masih ada toko lain yang membuka usaha yang sama. Kondisi tersebut menyebabkan pemilik toko ini dituntut untuk menemukan strategi yang dapat meningkatkan penjualan dan pemasaran toko olahraga. Data penelitian ini bersumber dari data transaksi penjualan toko yang sport yang beralamat di Jl. Fatahillah No.225, Watubelah, Kec. Weru, Kabupaten Cirebon, Jawa Barat 45154 Model algoritma k-means bahwa operator yang digunakan yaitu retrive dipergunakan untuk memanggil data set pada penelitian ini. Kemudian clustring kmeans untuk memodelkan data set yang telah ada, serta clusterdistance performance digunakan untuk menguji hasil pengelompokan, penelitian ini menetapkan 2 kelompok yaitu laris terjual dan tidak laris terjual. Hasil Data Performance menejelaskan bahwa Cluster 0 dengan nilai 110 dikategorikan sebagai Tidak Laris Terjual sedangkan 21389 dikategorikan sebagai laris terjual. Hasil rekomendasai penelitian ini mendapatkan informasi atau pola dari penerapan algoritma k-means dengan data penjualan terdapat sebanyak 99 item barang yang laris terjual dan terdapat 23 item barang yang tidak terjual sehingga pemilik dapat melakukan strategi penjualan dan pembelian ulang berdasarkan barang yang laris terjual.
SISTEM INFORMASI EKSTRAKURIKULER UNTUK MENINGKATKAN PELAYANAN KEGIATAN DI SMAN 1 SUMBERJAYA
Authors: Khaeru Abdullah , Astuti Rini , Suarna Nana
Published: February 2023

Belum adanya sistem informasi ekstrakurikuler yang terkomputerisasi di SMAN 1 Sumberjaya, dimana sistem yang lama kurang efektif dalam proses pencarian data,  juga tidak dapat mebuat laporan kegiatan secara otomatis. Maka peneliti bertujuan untuk membuat sebuah sistem informasi yang lebih efektif dan efisien dalam pengolahan data untuk meningkatkan pelayanan kegiatan di SMAN 1 Sumberjaya. Metode yang dipakai dalam penelitian yaitu metode kuantitatif, yakni meneliti hubungan antar variabel dengan menguji beberapa teori. Model pengembangan yang digunakan dalam penelitian ini adalah model prototype. Model prototype dipilih karena model ini merupakan model yang paling efektif karena user, bisa menyesuaikan program seperti apa yang hendak dibuat sesuai dengan apa yang mereka inginkan. Sistem Informasi Ekstrakurikuler mempermudah dalam proses akses data, dan pengolahan data di SMAN 1 Sumberjaya. Hasil penelitian menunjukkan bahwa penerapan “Sistem Informasi Ekstrakurikuler” dapat meningkatkan pelayanan kegiatan lebih dari 50%. Hal ini dibuktikan dengan hasil uji hipotesis dimana t hitung sebesar 2,450 dan t tabel 1.699. Maka t hitung lebih besar dari t tabel. Maka disimpulkan penelitian tentang Sistem Informasi Ekstrakurikuler berjalan sebagaimana seharusnya.
PENERAPAN ALGORITMA K-MEANS CLUSTERING DALAM PENGELOMPOKAN ARSIP SKCK
Authors: Ananda Wahyu , Hartami Santi Indyah , Kirom Sabitul
Published: February 2023

Kepolisian pelayanan umum yang dilakukan oleh Polres maupun Polsek merupakan sebuah bentuk pelayanan publik yang teah dilaksanakan oleh kepolisian dalam memenuhi kebutuhan masyarakat sesuai dengan tuntunan dan harapan masyarakat maupun sesuai dengan perundang-undangan yang berlaku. Adapun tugas pokok POLRI salah satunya ialah pelayanan pembuatan Surat Keterangan Catatan Kepolisian (SKCK), karena itu hampir setiap hari masyarakat umum dari berbagai latar belakang datang ke Polsek untuk membuat SKCK. Untuk mengelompokan kalangan masyarakat atau pemohon yang membuat SKCK di Polsek Lodoyo Barat menggunakan metode clustering dengan algoritma K-Means yang diharapkan dapat membantu untuk mengetahui kalangan apa yang mendominasi pembuatan SKCK. Penelitian ini menggunakan 416 data dengan jumlah cluster 3 cluster. Hasil dari perhitungan untuk masing-masing cluster antara perhitungan manual dan hasil yang menggunakan software tanagra menghasilkan nilai yang berbeda karena penentuan titik pusat atau inisiasi cluster dimulai dengan angka yang berbeda
SISTEM PENDUKUNG KEPUTUSAN SELEKSI CALON PEGAWAI BARU RUMAH PINTAR CENDIKA AZHARI BERBASIS WEB JUDUL
Authors: Damas Tri Yudha Febri , Paranita Kartika R Kurnia , Chulkamdi M. Taufik
Published: February 2023

Tujuan di bangun penelitian ini seleksi calon pegawai baru yang dapat memberikan informasi dan rekomendasi pilihan calon karyawan sesuai kriteria yang di tentukan, menggunakan metode waterfall yang terdiri dari 5 tahapan requirement and analysis, design, coding/implementation, testing dan maintenance. memanfaatkan metode profile matching, Data yang digunakan untuk membangun sistem pendukung keputusan didapat dari hasil wawancara dari pemilik maupun admin yayasan rumah pintar cendika azhari. Sistem di rancang mengunakan framework laravel. Hasil dari penelitian ini adalah sebuah sistem seleksi calon pegawai yang hasil akirnya perangkingan. Sistem ini telah dilakuan pengujian agar mendapatkan kesimpulan yang diinginkan dengan cara menetukan hasil presentasi pengujian.  Pengujian aplikasi ini mengunakan black box, beta testing dan pengujian validasi ahli IT. Hasil akir pengujian black box mendapat nilai total rata-rata 87,5 yang berarti aplikasi  sangat layak digunakan. Sedangkan untuk pengujian beta testing mendapat nilai total rata-rata 85,61 yang berarti aplikasi dapat mempermudah proses pengambilan keputusan. dan hasil dari pengujian ahli IT mendapat nilai total rata-rata aplikasi yang di bangun layak dan sudah bisa digunakan
REKOMENDASI PENEMPATAN PRAKTIK KERJA LAPANGAN MENGGUNAKAN METODE PROFILE MATCHING DI SMK PGRI WLINGI
Authors: Nurul Fitrah  , Yuana Haris , Taofik Chulkamdi Mukh
Published: February 2023

Dalam memberikan rekomendasi tempat PKL merupakan kegiatan yang memerlukan kejelian dalam menentukan penilaian calon peserta PKL dengan mempertimbangkan berbagai aspek dengan menggunakan metode yang sesuai. Perlu adanya pengujian untuk mengetahui bagaimana tingkat akurasi dan performa dari penerapan metode yang digunakan. Penelitian ini menggunakan metode profile matching terhadap rekomendasi penempatan jenis PKL di SMK PGRI Wlingi dengan menggunakan sampel data 220 siswa kelas X pada program keahlian Teknik Komputer dan Informatika. Hasil penelitian ini berupa perangkingan jenis PKL pada tiap siswa dengan kriteria nilai yang telah ditentukan yang selanjutnya dihitung menggunakan metode profile matching. Nilai tertinggi dari jenis PKL tersebut akan menjadi rekomendasi jenis tempat PKL bagi siswa tersebut. Dari hasil rekomendasi akan diuji menggunakan confusion matrix yang didapatkan hasil hasil akurasi sebesar 90%. Nilai akurasi yang didapatkan mendekati nilai 100% sehingga metode profile matching ini dapat digunakan untuk memberikan rekomendasi tempat PKL di SMK PGRI Wlingi
PENERAPAN ALGORITMA BOYER-MOORE TERHADAP APLIKASI KAMUS TEMINOLOGI BIOMEDIS BERBASIS ANDROID
Authors: Bagus Wicaksono Ilham , Hartami Santi Indyah , Febrinita Filda
Published: February 2023

Terdapat banyak bahasa yang ada di seluruh dunia. Dengan banyaknya bahasa maka dibuatlah kamus sebagai penerjemah antar bahasa termasuk juga kamus terminologi biomedis. Seiring berkembangnya teknologi dan karena kamus ini cukup tebal dan berat untuk dibawa ke mana-mana, di buatlah kamus terminologi biomedis untuk mempermudah penggunaan kamus. Kamus terminologi biomedis ini di buat menggunakan android studio dengan bahasa pemrograman dart dan framework flutter. Algoritma yang digunakan dalam penelitian ini adalah boyer moore yang merupakan algoritma yang banyak digunakan untuk pencocokan string. Algoritma boyer moore ini pertama kali di publis oleh Robert S boyer dan J Strother Moore pada tahun 1977. Algoritma ini banyak di gunakan karena dianggap paling efisien di bandingkan dengan algoritma string matching lainnya. Algoritma ini mencocokkan kata dari kanan ke kiri yang di nilai bisa mendapatkan lebih banyak informasi. Dalam penelitian ini dilakukan pembuatan kamus dengan data yang berawalan dengan abjad A saja yang memiliki jumlah 1089 data. Data yang sudah ada nantinya akan di cocokkan dengan input yang akan dicari dan jika di dalam data terdapat kata sama seperti dengan input yang dicari, maka akan dimunculkan data tersebut ketika user melakukan pencarian. Dari pengujian yang sudah dilakukan, data dapat muncul dengan waktu yang berbeda pada setiap perangkat seperti perhitungan perbandingan eksponensial emulator mendapatkan nilai 6,756586 sedangkan smartphone mendapat nilai 6,355025. Semakin kecil nilainya menandakan bahwa semakin efisien aplikasinya
SISTEM FORECASTING PENJUALAN BERAS DENGAN MENERAPKAN METODE TREND MOMENT
Authors: Indah Kusuma Wardhani Nurlaili , Hartami S Indyah , Dwi Puspitasari Wahyu
Published: February 2023

Penjualan beras yang berubah-ubah membuat Toko Sejahtera Mart sering mengalami kekurangan atau penumpukan jumlah barang yang akan dijual. Sehingga, perlu adanya sistem atau metode untuk mengatasi hal tersebut yaitu forecasting atau peramalan. Forecasting dapat dipakai untuk memprediksi jumlah kebutuhan barang yang akan datang berdasarkan pengalaman penjualan barang di masa lampau. Forecasting atau peramalan memiliki banyak metode, salah satunya yaitu Metode Trend Moment. Metode trend moment adalah sebuah metode analisis yang bisa digunakan untuk keperluan prediksi stok barang pada perusahaan, sehingga perusahaan bisa meminimalkan biaya suplai barang yang akan dijual serta barang yang akan disuplai tidak berlebihan jumlahnya. Perhitungan metode Trend Moment yang diterapkan pada peramalan berdasarkan penjualan beras 2 tahun sebelumnya. Merek beras yang digunakan dalam penelitian yaitu merek Koi, merek Lahap Lele, merek Lahap Biasa, merek Bang Toyib, dan merek Stroberri. Untuk pengujian dilakukan dengan 5 jenis beras berbeda yang menghasilkan nilai MAPE terendah. Berdasarkan hasil pengujian merek beras koi memiliki nilai MAPE sebesar 22,62%.
PENERAPAN ALGORITMA C4.5 UNTUK PREDIKSI MINAT PENJURUSAN SISWA DI SMKN 1 KADEMANGAN
Authors: Yulia Devinda , Pandu Kusuma Abdi , Fanny Hebrasianto Permadi Dimas
Published: February 2023

Uji Intelligence Quotient (IQ) ini pula berperan dalam memprediksi, menguatkan, serta meyakinkan para siswa, salah satunya untuk memilih jurusan. Dilakukannya penelitian ini, dikarenakan anak usia remaja terkadang salah mengambil jurusan jenjang berikutnya karena berdasarkan ikut-ikutan teman, sedangkan dampak penting dalam pendidikan itu sendiri yaitu jika siswa memilih jurusan yang salah, hasil yang akan diperoleh tidak akan maksimal, dan membuat sulit untuk mendapatkan kesempatan kerja. Oleh karena itu, riset ini bertujuan untuk mengenal perkembangan anak dalam pemilihan jurusan sesuai minat. Oleh karena itu peminatan jurusan harus disiapkan dari sekarang dengan arahan supaya siswa tidak salah jurusan dan memudahkan siswa untuk memilih jurusan sesuai bidang pengetahuan yang akan mereka praktikkan. Penelitian ini menggunakan perhitungan Algoritma C.45. Hasil yang diperoleh yaitu klasifikasi jurusan dengan nilai akurasi menggunakan Confusion Matrix yang menghasilkan nilai akurasi 92% pada jurusan TKRO dan TKJ, 83% pada jurusan BDP dan ATUG, dan 50% pada jurusan APAT dan ATPH.
PENERAPAN ALGORITMA C4.5 UNTUK MENENTUKAN KUALITAS TELUR AYAM HIBRIDA
Authors: Fikri Yunus Moh. , Hartami Santi Indyah , Kirom Sabitul
Published: February 2023

Penelitian ini menerapkan algoritma C4. 5 untuk menentukan kualitas telur ayam hibridra di CV Senik desa suruhwadang. Penelitian ini bertujuan untuk menentukan kualitas telur ayam hibridra menggunakan algoritma C4. 5. Dengan dilakukannya data mining melibatkan 90 data wawancara tersebut memiliki 2 kategori pilihan yaitu: bagus dan tidak bagus. Terdapat 5 atribut yang mempengaruhi penentuan kualitas telur ayam yaitu: Kebersihan Kulit, Kondisi Kulit Telur, Warna Kulit, Bentuk Telur, Ukuran/Berat. Dengan adanya penelitian ini dapat memudahkan pihak CV. Senik dalam menentukan kualitas telur ayam dengan kendala yang dapat diminimalisir. Berdasarkan hasil penelitian menggunakan algoritma C4. 5 jumlah hasil yang bagus sebanyak 56 dan yang tidak bagus sebanyak 34.  Hasil pengunjian menggunakan aplikasi rapid miner tingkat akurasi dalam menentukan kualitas telur rata-rata sebesar 80%. Dapat disimpulkan bahwa algoritma C4. 5 cocok digunakan untuk menentukan kualitas telur ayam hibridra di CV Senik.
ANALISIS PERBANDINGAN METODE SAW DENGAN WP DALAM MENDUKUNG KEPUTUSAN CALON KARYAWAN HYFRESH BLITAR
Authors: Ivan Maulana Herlambang , Pandu Kusuma Abdi , Febrinita Filda
Published: February 2023

Pada penelitian ini memiliki tujuan untuk membandingkan dua metode sistem pendukung keputusan yaitu metode Simple Additive Weighting (SAW) dan Weighted product (WP) pada rekrutmen calon pegawai Hyfresh Blitar Square, dan mengetahui hasil perbandingan pada penerapan sistem rekrutmen pegawai Hyfresh Blitar Square menggunakan metode sistem pendukung keputusan Simple Additive Weighting (SAW) & Weigted Product (WP). Metode penelitian yang digunakan yaitu metode kualitatif, dengan teknik pengumpulan data meliputi observasi, wawancra, Dan juga tahapan penelitian meliputi studi lapangan, identifikasi dan perumusan, pengumpulan data, penerapan metode, dan analisis perbandingan metode. Hasil penelitian dapat disimpulkan bahwa penggunaan metode Simple Additive Weighting (SAW) serta metode Weighted product (WP) pada masalah pemilihan calon karyawan, dengan pengujian yang menggunakan confusion matrix. Pada hasil uji confusion matrix menunjukkan tingkat akurasi dalam perhitunganya menggunakan metode Simple Additive Weighting (SAW) sebesar 96,5% dan Weighted product (WP) 81%, jadi metode yang efektif atau baik di gunakan untuk rekrutmen calon karyawan Hyfresh Blitar Square adalah metode Simple Additive Weighting. (SAW).
Penatausahaan Keuangan Non Tunai pada Bendahara RSUD dr. Rasidin Padang
Authors: Reflinda Reflinda
Published: February 2023

Penatausahaan keuangan non tunai merupakan langkah awal dalam mewujudkan good governance. Dengan adanya penatausahaan non tunai maka seluruh transaksi pembayaran dapat dilakukan dengan mudah dan efisien. Selain itu penatausahaan keuangan non tunai juga dapat menghasilkan laporan keuangan yang akurat dan aktual sehingga dapat dengan mudah dilakukan pengendalian dan evaluasi terhadap kinerja keuangan.

Penelitian ini bertujuan untuk mengetahui dan mendeskripsikan Penatausahaan Keuangan Non Tunai pada Bendahara RSUD dr. Rasidin Padang, mengetahui kendala-kendala yang dihadapi serta upaya-upaya yang dapat dilakukan dalam mengatasi kendala-kendala tersebut. Menurut Chabib dan Heru (2010:10) pengelolaan keuangan mencakup 5 hal yakni : akuntabilitas, pengukuran kinerja keuangan, kejujuran, transparansi dan pengendalian.

Teknik pemilihan informan adalah purposive sampling. Selanjutnya peneliti menggunakan teknik pengumpulan data dengan melakukan observasi, wawancara dan dokumentasi. Metode penelitian adalah kualitatif deskriptif dengan informan berjumlah 21 orang yang terdiri atas Staf dan Rekanan (pihak ke-3) di RSUD dr. Rasidin Padang. Sumber data diambil dari data primer yang diperoleh langsung dari informan dan data sekunder berupa dokumen-dokumen pendukung.

Hasil penelitian menunjukkan bahwa Penatausahaan Keuangan Non Tunai pada Bendahara RSUD dr. Rasidin Padang secara umum sudah berjalan dengan baik. Namun masih ada terdapat kendala yakni kurang lancarnya akses internet. Oleh karena itu perlu dilakukan peningkatan kapasitas jaringan internet dan peningkatan kualitas perangkat komputer.
Die großen Philosophen und ihre Probleme
Authors: Liessmann Konrad Paul
Published: February 2023

Philosophie ist vom Leben und von der Zeit des Philosophierenden nicht zu trennen. Was in den Lehrbüchern als philosophisches Problem auftaucht, war in der Tat nur allzu oft das Problem eines Philosophen.
Ziel dieses Buches ist es, mit einem biographischen, mitunter auch anekdotischen Ansatz, den Zugang zu den zentralen Konzepten und Fragestellungen der Philosophie zu eröffnen.
Porträtiert werden: Sokrates, Platon, Augustinus, Spinoza, Kant, Hegel, Marx, Kierkegaard, Nietzsche, Wittgenstein, Popper, Heidegger, Adorno, Anders und
Arendt.
The Design of Cavity Resonators and Microwave Filters Applying Shape Deformation Techniques
Authors: Baranowski Michal , Balewski Łukasz , Lamecki Adam , Mrozowski Michal , Galdeano Jaione
Published: February 2023

This paper introduces shape deformation as a new approach to the computer-aided design (CAD) of high frequency components. We show that geometry deformation opens up new design possibilities and offers additional degrees of freedom in the 3D modeling of microwave structures. Such design flexibility is highly desirable if the full potential of Additive Manufacturing (AM) is to be exploited in the fabrication of RF & microwave devices. The use of deformation techniques in the design of high-frequency components allows the attainment of improved electrical parameters, such as high-quality factors for cavity resonators and wide higher-order mode separation. In this work, shape deformation with radial basis functions (RBFs) is integrated with an electromagnetic field simulator based on the 3D finite-element method (FEM), allowing the semiautomated optimization of microwave components, such as cavity resonators and filters. The proposed strategy is used for the design of high Q-factor cavity resonators, cavity bandpass filters with improved spurious mode separation and of a compact twisted waveguide filter. Three designs of waveguide cavity filters with complex geometry are experimentally verified using 3D-printed prototypes fabricated with the selective laser melting (SLM) technology.
Benefits of Pod dimensioning with best-effort resources in bare metal cloud native deployments
Authors: Tonini Federico , Natalino Carlos , Temesgene Dagnachew , Ghebretensaé Zere , Wosinska Lena , Monti Paolo
Published: February 2023

Existing container orchestration platforms provide frameworks capable of automatically scaling resources to evolving traffic conditions based on resource usage. Service providers rely on these automatic scaling capabilities to improve the traffic adaptability of their cloud native applications while reducing costs. However, this may lead to service degradation related to the delayed response to the traffic changes. Traditionally, Pod dimensioning has been performed considering guaranteed (or request) resources. Recently, container orchestration platforms included the possibility to allow Pods to use idle resources that can be withheld for a short period of time in a best-effort fashion (known as limit resources). This paper analyzes the potential of limit resources as a way to mitigate degradation while reducing the amount of request resources. Results for a sample case show that a strategy relying on limit resources achieves the same level of degradation as a conventional strategy that uses only request resources, while reducing requested CPU by 25%.
Communication Network Reliability under geographically correlated failures using Probabilistic Seismic Hazard Analysis
Authors: Barrera Javiera , Jiménez-Álvarez Dora , Cancela Héctor
Published: February 2023

The research community’s attention has been attracted to the reliability of networks exposed to large-scale disasters and this has become a critical concern in network studies during the last decade. Earthquakes are high on the list of those showing the most significant impacts on communication networks, and simultaneously, they are the least predictable events.  This study uses the Probabilistic Seismic Hazard Analysis method to estimate the network element state after an earthquake. The approach considers a seismic source model and ground prediction equations to assess the intensity measure for each element according to its location. In the simulation, nodes fail according to the building's fragility curves. Similarly, links fail according to a failure rate depending on the intensity measure and the cable's characteristics. We use the source-terminal, and the diameter constrained reliability metrics. The approach goes beyond the graph representation of the network and incorporates the terrain characteristics and the component's robustness into the network performance analysis at an affordable computational cost.  We study the method on a network in a seismic region with almost 9000 km of optical fiber. We observed that for source-terminal that are less than 500 km apart the improvements are marginals while for those that are more than 1000 km apart, reliability improves near a 30\% in the enhanced designs. We also showed that these results depend heavily on the robustness/fragility of the infrastructure, showing that performance measures based only the network topology are not enough to evaluate new designs.
Latent Similarity Identifies Important Functional Connections for Phenotype Prediction
Authors: Orlichenko Anton
Published: February 2023

We present a new machine learning algorithm, Latent Similarity, and use it to predict subject (endo)phenotypes from fMRI data. fMRI can be used to predict dysfunctional mental states. In addition, endophenotypes are known to be predictive of disease status, and are of interest in developmental studies. However, fMRI studies often suffer from small cohort size and high feature dimensionality, making reproducible prediction challenging. The innovation of our algorithm is to combine a kernel similarity function with metric learning to increase the robustness of prediction. Our algorithm becomes robust by utilizing the N squared connections between the N subjects in the cohort, rather than the features of the N subjects themselves. We identify important functional connections in the default mode and uncategorized functional networks for predicting age, sex, and intelligence. We also find that only a few connections contain most of the information required for any predictive task. We believe that our algorithm can be beneficial in small sample size, high noise, high dimensionality settings.
Fast-Convergence Digital Signal Processing for Coherent PON using Digital SCM
Authors: Wang Haide , Zhou Ji , Xing Zhenping , Feng Qiguang , Zhang Kuo , Zheng Keshuang , Chen Xi , Gui Tao , Li Liangchuan , Zeng Jianrui , Yang Jinyang , Liu Weiping , Yu Changyuan , Li Zhaohui
Published: February 2023

It is foreseeable that the 100 Gb/s/λ and beyond passive optical network (PON) will be required in future optical access networks to meet the explosive growth of data traffic. The coherent optical systems could be a promising solution for the future beyond 100G PON. Coherent PON using digital subcarrier multiplexing (DSCM) can provide flexible bandwidth allocation to a large number of access subscribers by dividing subcarriers of the DSCM signal into time slots for time-and-frequency division multiple access. When the optical network unit is allocated a new subcarrier, digital signal processing (DSP) should converge fast in the allocated time slot to ensure a low handoff latency for real-time bandwidth allocation. However, the traditional coherent DSP is hard to realize fast convergence due to blind and complex algorithms. In this paper, we design a specific training sequence (TS) structure and propose data-aided DSP to achieve fast convergence for coherent PON. The feasibility of the proposed scheme is experimentally verified in an  8 Gbaud/SC×8 SCs 400 Gb/s-net-rate coherent PON using DSCM with 16 quadrature amplitude modulation. The experimental results show that fast convergence is jointly realized by the proposed TS structure and data-aided DSP using a 416-symbol TS with a 52 ns duration. The receiver sensitivity at the 20% soft-decision forward error correction limit is approximately −27 dBm and an optical power budget of about 35.5 dB is achieved with a booster amplifier.
Human-as-a-Robot Performance in Augmented Reality Teleultrasound
Authors: Black David , Moradi Hamid , Salcudean Septimiu
Published: February 2023

 Purpose: In “human teleoperation” [1], augmented reality (AR) and haptics are used to tightly couple an expert leader to a human follower. To determine the feasibility of human teleoperation, we quantify the abil- ity of humans to track a position and/or force trajectory via AR cues. The human response time, precision, frequency response, and step response were characterized, and several rendering methods were compared. 

Methods: Volunteers (n=11) performed a series of tasks as the fol- lower in our human teleoperation system. The tasks involved tracking pre-recorded series of motions and forces, each time with a different rendering method. The order of tasks and rendering methods was ran- domized to avoid learning effects and bias. The volunteers then performed a series of frequency response tests and filled out a questionnaire. 

Results: Rendering the full ultrasound probe as a position target with an error bar displaying force led to the best position and force tracking. Following force and pose simultaneously was more difficult but did not lead to significant performance degradation versus following one at a time. On average, subjects tracked positions, orientations, and forces with rms tracking errors of 6.2 ± 1.9 mm, 5.9 ± 1.9˚, 1.0 ± 0.3 N, steady-state errors of 2.8 ± 2.1 mm, 0.26 ± 0.2 N, and lags of 345.5 ± 87.6 ms respectively. Performance decreased with input frequency, until the person could no longer follow, depending on the input amplitude. 

Conclusion: This paper characterizes human tracking ability in aug- mented reality human teleoperation, which shows the system’s feasi- bility and good performance, and is important for designing future human computer interfaces using augmented and virtual reality. 
Analysis of Flight Disruption Data to Determine Problem Areas Utilizing Database Applications
Authors: Issoufou Fadjimata , Jennings Sean , Sanders Jordan , Martin Tyler
Published: February 2023

Flight delays represent a significant issue to airline profits and passenger satisfaction. Many factors can lead to a flight being delayed and/or canceled. The study evaluates flight delays, cancellations, and incident data with the goal of visualizing which airports, airlines, and cities, to visualize or states are experiencing the highest number of flight disruptions relative to others. Databases are commonly used for data analysis to allow pattern recognition and large data distribution and organization. The study will mainly serve the purpose of flight data retrieval, the compilation of data and database design, and finally output data visualizations.
On the Vital Aspects and Characteristics of Cryptocurrency – A Survey
Authors: Shah A F M Shahen , Karabulut Muhammet Ali , AKHTER A F M SUAIB , Mustari Nazifa , PATHAN AL-SAKIB KHAN , Rabie Khaled , SHONGWE THOKOZANI
Published: February 2023

 Cryptocurrencies acquire user confidence by making the whole creation and transaction history transparent to the public. In exchange, the transaction history accurately captures the complete range of user activities related to cryptocurrencies. In this paper, the use of data mining methods in Bitcoin transactions is analyzed and summarized. Cryptocurrencies, similar to the well-known Bitcoin, were targeted to ensure transaction security and privacy and overcome the drawbacks of traditional banking systems as well as other centralized systems. We also conduct a thorough analysis of the literature on the challenges and applications of electronic currencies. We outline the evolution of digital currency from electronic cash to cryptocurrencies and put the spotlight on the methods used to increase user privacy. We also highlight security threats in the existing cryptocurrency systems that jeopardize the privacy of Bitcoin users. Finally, we identify several research gaps and trends that need to be looked at further.  
A Low-cost and Accurate Microwave Sensor System for Permittivity Characterization
Authors: Pourafzal Alireza , Roi-Taravella Thomas , Cheffena Michael , yayilgan sule yildirim
Published: February 2023

A novel low-cost microwave sensor system is proposed for accurate sensing of the real relative permittivity of materials under test (MUT). The proposed solution eliminates the need for using advanced measurement devices such as the vector network analyzer (VNA) for sensor characterization. The proposed sensor system is built on a software-defined radio platform. A suitable two-stage frequency estimation approach was developed for estimating the frequency shift of the resonator sensor associated with the real relative permittivity of the MUT. First, the neighborhood of the resonance frequency is obtained utilizing a low-resolution coarse search, followed by a fine search method to accurately estimate the resonance frequency. For the fine search, we modified the AM frequency estimation algorithm and the Golden Section search algorithm to suite the proposed sensor system. The performance of the proposed sensor system is validated through simulations and experiments. To demonstrate the feasibility of the concept, experiments were conducted by implementing the solution on a Universal Software Radio Peripheral transceiver using a resonator sensor for detecting the binary mixture of water and methanol. The results show that the proposed sensor system achieves measurement accuracy comparable to advanced equipment such as the VNA. Thus, the proposed sensor system could be a low-cost alternative for sensor characterization purposes with accuracy comparable to standard equipment.
Structure of the space of GL4 (Z2)-coinvariants Z2 ⊗ GL4 (Z2) P H∗ (Z42,Z2) in some generic degrees and its application
Authors: Võ Phúc Đặng
Published: February 2023

 Let $A$ denote the Steenrod algebra at the prime 2 and let $k = \mathbb Z_2.$ A very difficult problem in algebraic topology is to determine a minimal set of $A$-generators for the polynomial ring $P_q = k[x_1, \ldots, x_q] = H^{*}(k^{q}, k)$ on $q$ generators $x_1, \ldots, x_q$ with $|x_1|= |x_2| = \cdots = |x_q| =  1.$ Equivalently, one can write down explicitly a basis for the cohit space $\pmb{Q}^{q} := k\otimes_{A} P_q$ in each non-negative degree $n.$ This subject, which has now a long history, is the content of the classical "hit problem" proposed in [Abstracts Papers Presented Am. Math. Soc.  \textbf{833} (1987), 55-89]. Furthermore, it is closely related to the $q$-th transfer homomorphism $Tr_q^{A}$ constructed by William Singer in [Math. Z. \textbf{202} (1989), 493-523]. This $Tr_q^{A}$ passes from the space of $G(q)$-coinvariant $k\otimes _{G(q)} P_A((P_q)_n^{*})$ of $\pmb{Q}^{q}$ to the $k$-cohomology group of the Steenrod algebra, ${\rm Ext}_{A}^{q, q+n}(k, k),$ where $G(q)$ denotes the general linear group of degree $q$ over the field $k,$ whereas $P_A((P_q)_n^{*})$ is the primitive part of $(P_q)^{*}_n$ under the action of $A.$ Particularly, Singer conjectured that $Tr_q^{A}$ is a monomorphism, but this remains unanswered for all $q\geq 4.$ The present paper is devoted to investigating this conjecture for rank 4 in some certain internal degrees. Specifically, by the usage of the techniques of the hit problem in four variables, we explicitly determine the structure of $k\otimes _{G(4)} P_A((P_4)_{n}^{*})$ in some generic degrees $n.$ Then, applying these results and a representation of $Tr_4^{A}$ via the lambda algebra, we show that Singer's conjecture is true for rank $q = 4$ in respective degrees $n.$ This has contributed to the final proof of Singer's conjecture in the rank 4 case.
Practices for Managing Machine Learning Products: a Multivocal Literature Review
Authors: alves isaque , Leite Leonardo , Meirelles Paulo Roberto Miranda , Kon Fabio , Rocha Carla
Published: February 2023

Machine Learning (ML) has grown in popularity in the software industry due to its ability to solve complex problems. Developing ML Systems involves more uncertainty and risk because it requires identifying a business opportunity and managing the source code, data, and trained model. Our research aims to identify the existing practices used in the industry for building ML applications. The goal is to comprehend the orga- nizational complexity of adopting ML Systems. We conducted a Multivocal Literature Review (MLR) and used Grounded Theory (GT) to build a taxonomy with the practices applied to the ML System lifecycle from the industry and academic perspectives. We selected 41 posts from grey literature and 37 papers from scientific repositories. Following a systematic GT protocol, we mapped 91 practices, grouped in 6 core categories related to designing, developing, testing, and deploying ML Systems. The results can help organizations identify the gaps in their current ML processes and practices, and provide a roadmap for improving and optimizing their ML systems. The comprehensive taxonomy of practices developed in this research serves as a valuable tool for managers, practitioners, and researchers in the ML field, providing a clear and organized understanding of the complexity of managing ML systems.
Design and development of a mecanum-built portable perturbation-based balance training device
Authors: MATHUNNY JAISON JACOB , Srinivasan Hari Krishnan , Devaraj Ashokkumar , Karthik Varshini
Published: February 2023

A novel portable perturbation-based balance training device using a mecanum wheel to perturb in eight directions.
Computation and Information Theory of Chess Games
Authors: Hwang Chunkai , Gilbert John Reuben , Huang Tsung-Ren , Tsai Chen-An , Oyang Yen-Jen
Published: February 2023

We provide two methodologies in the area of computation theory to solve optimal strategies for games such as Watermelon chess and Go. From experimental results, we find relevance to graph theory, group representation, and mathematical consciousness. We prove that the decision strategy of movement for Watermelon chess and Chinese checker games belongs to a matrix that is a noncommutative ring or an abelian group over set Y={-1,0,1}. Additionally, the movement for any chess game with two players belongs to a noncommutative ring or an abelian group from Occam’s razor principle. We derive the closed form of the transition matrix for any chess game with two players and discover that the element of the transition matrix belongs to a rational number. We propose a different methodology based on abstract algebra to analyze the complexity of chess games in their entirety, instead of being limited solely to endgame results. It is probable that similar decision processes of people may also belong to a noncommutative ring or an abelian group.
Adapting to progressive paralysis: A tongue-brain hybrid robot interface for individuals with amyotrophic lateral sclerosis
Authors: Leck Kæseler Rasmus , Farina Dario , Bentsen Bo , Obál Izabella , Vinge Lotte , Dremstrup Kim , Jochumsen Mads , Andreasen Struijk Lotte N. S.
Published: February 2023

Individuals suffering from progressive neuromuscular diseases gradually lose all muscle control and therefore are forced to repeatedly adapt to new control interface technologies to maintain some level of independence. Accordingly, the ideal interface technology should adapt to the progression of paralysis. We propose an adaptive tongue-brain hybrid interface framework for the three-dimensional control of a robotic arm. The interface was tested with able-bodied individuals and individuals with amyotrophic lateral sclerosis. The experiments demonstrated the importance of flexible frameworks for cooperation between control modalities as this allows a critical optimization of the control performance relative to the disease stage. The hybrid framework allowed a 4-34% stepwise decrease in performance rather than a 200% decrease when moving directly from a tongue to a brain control interface. This hybrid framework is the first step towards a new concept of assistive robotic control with a higher focus on adapting to the functionality of disabled individuals.
Inversion-Free Sparse Bayesian Learning for Temporally Correlated Signal Recovery
Authors: Song Yuhui
Published: February 2023

Compressed sensing recovers the sparse signal from far fewer samples than required by the well-known Nyquist–Shannon sampling theorem to speed up the measure- ment procedure. The sparse signal recovery performance can be significantly improved by exploiting the temporal correlation in the multiple measurement vector model within the framework of sparse Bayesian learning. However, it is inevitable to involve the matrix inversion for existing methods, making the application of these schemes to large datasets impractical. To overcome this bottleneck, in this letter, we propose an inversion-free sparse Bayesian learning algorithm for temporally correlated sparse signal recovery, which is free of any matrix inversion operation and only requires simple addition and multiplication operations. Specifically, utilizing a property for the convex quadratic func- tion, we obtain a lower bound for the likelihood distribution that enables the computationally efficient model inference based on the expectation-maximization algorithm. Simulation results show its superior performance over other state-of-the-art methods in terms of the recovery performance and the running time.
PMU Network Routing for Resilient Observability of Power Grids
Authors: Islam Md Zahidul , Vokkarane Vinod M , Lin Yuzhang
Published: February 2023

Smart grid technologies have been transforming the power grid operation paradigms by integrating smart sensing devices, advanced communication networks, and powerful computing resources. In addition, data-driven applications have significantly increased in recent years, accelerating the use of smart sensors, such as phasor measurement units (PMU), in power grid monitoring. It necessitates a well-functioning communication network (CN) for PMU measurement data transfer to the control center even in the event of failures. This paper proposes a PMU network routing algorithm to ensure data transfer for control center's resilient observability to the power grid. The interdependent roles of PMUs in power grid observability is first identified based on the power grid topology. Then, a failure-tolerant routing algorithm is proposed to find data transfer paths in the CN that meets the power grid monitoring needs. The resultant routing paths ensure resilience against single link failure, where the resilience is defined in terms of grid observability. Besides, a cost metric is defined to minimize end-to-end delay in the network to facilitate real-time data transfer. Simulation results verify the superiority of the proposed routing algorithm compared with conventional fault-tolerant routing algorithms that are agnostic to the domain knowledge of power grid observability.
Automatic detection of microcalcifications in whole slide image - comparison of deep learning and standard computer vision approaches
Authors: Clavel Marceau , Sockeel Stéphane , Sockeel Marie , Miquel Catherine , Adam Julien , Lanteri Elisabeth , Pozin Nicolas
Published: February 2023

Early detection of breast cancer through mammography is crucial for successful treatment. Microcalcifications are small deposits of calcium in breast ducts, they can be an indication of breast cancer and are first detected by mammography. However, their presence must be confirmed by an histopathologist through slides examination. As a help to practitioners, we present an automatic microcalcification detection pipeline in Whole Slide Images (WSI). This pipeline is a patch-based approach, in which patches from epithelial regions are analyzed by a classifier to determine if they contain microcalcifications. We have developed two classifiers for this pipeline, one based on image processing techniques and the other on deep learning. In addition to standard classification metrics, we compare the performance of these two classifiers using custom metrics specifically designed to capture the value brought by the pipeline to pathologists. Both approaches provide promising results. The deep learning classifier has better metrics, but requires more labeled data to be implemented. 
Quantized Magnetic Domain Wall Synapse for Efficient Deep Neural Networks
Authors: Dhull Seema , Misba Walid , Nisar Arshid , Atulasimha Jayasimha , Kaushik Brajesh Kumar
Published: February 2023

 Quantization of synaptic weights using emerging non-volatile memory devices has emerged as a promising solution to implement computationally efficient neural networks on resource constrained hardware. However, the practical implementation of such synaptic weights is hampered by the imperfect memory characteristics, specifically the availability of limited number of quantized states and the presence of large intrinsic device variation and stochasticity involved in writing the synaptic state. This article presents on-chip training and inference of a neural network using quantized magnetic domain wall (DW) based synaptic array and CMOS peripheral circuits.  The quantization of the synaptic device offers a balanced neural network performance in terms of accuracy, power, and area. A rigorous model of the magnetic DW device considering stochasticity and process variations has been utilized for the synapse. To achieve stable quantized weights, DW pinning has been achieved by means of physical constrictions. Finally, VGG8 architecture for CIFAR-10 image classification has been simulated by using the extracted synaptic device characteristics. The performance in terms of accuracy, energy, latency, and area consumption has been evaluated while considering the process variations and non-idealities in the DW device as well as the peripheral circuits. The proposed quantized neural network architecture achieves efficient on-chip learning with 92.4% and 90.4 % training and inference accuracy, respectively. In comparison to pure CMOS based design, it demonstrates an overall improvement in area, energy, and latency by 13.8×, 9.6×, and 3.5×, respectively. 
Autonomous Driving Decision Algorithm for Complex Multi-vehicle Interactions: an Efficient Approach Based on Global Sorting and Local Gaming
Authors: Li Daofei , Zhang Jiajie , Liu guanming
Published: February 2023

For autonomous driving, it is important to develop safe and efficient decision algorithms to handle multi-vehicle interactions. Game theory is suitable to manage the interactive driving decision modelling, however, common approaches of multi-player game formulation is computationally complex for dynamic and intense interactions.  The main contributions of this work are two-fold: 1) a global sorting-local gaming framework, namely GLOSO-LOGA, is proposed to solve the intersection interaction problem for autonomous driving, which can comprehensively consider the advantages of multi-vehicle collaboration and single-vehicle intelligence approaches; 2) an interaction disturbance function is used to quantify the impact of indirect interactions on ego vehicle. To validate the algorithm performances, corner case simulations and human-in-the-loop simulator experiments are carried out, in which a four-armed intersection scenario with various urgent and challenging interaction conditions is used. Results show that compared to the traditional approach that decomposes a multi-vehicle game into multiple two-vehicle games, the proposed algorithm can improve both safety and traffic efficiency in intensively interactive driving scenarios even in complex and urgent cases. It may be potentially applied in handling autonomous vehicle's dynamic interactions with multiple road users.
Autonomous Interactive Driving Decision Based on Global Sorting and Local Gaming
Authors: Li Daofei , Zhang Jiajie , Liu guanming
Published: February 2023

For autonomous driving, it is important to develop safe and efficient decision algorithms to handle multi-vehicle interactions. Game theory is suitable to manage the interactive driving decision modelling, however, common approaches of multi-player game formulation is computationally complex for dynamic and intense interactions. To overcome this challenge, a global sorting-local gaming framework, namely GLOSO-LOGA, is proposed to solve the intersection interaction problem for autonomous driving, which can comprehensively consider the advantages of multi-vehicle collaboration and single-vehicle intelligence approaches. Further, an interaction disturbance function is used to quantify the impact of indirect interactions on ego vehicle. Then simulations with single and multiple conflict areas settings in a four-armed intersection are carried out. Simulations and human-in-the-loop simulator experiments show that the proposed algorithm can improve the interaction safety in intensively interactive driving scenarios even in complex and urgent interaction cases. The proposed framework may be potentially applied in handling autonomous vehicle's dynamic interactions with multiple road users.
A Wearable Wireless Magnetic Eye-Tracker, in-vitro and in-vivo tests
Authors: Bevilacqua Giuseppe , Biancalana Valerio , Carucci Mario , Cecchi Roberto , Chessa Piero , Donniacuo Aniello , Mandalà Marco , Stiaccini Leonardo , viberti francesca
Published: February 2023

A wireless, wearable magnetic eye tracker is described and characterized. The proposed instrumentation enables simultaneous evaluation of eye and head angular displacements. Such a system can be used to determine the absolute gaze direction as well as to analyze spontaneous eye re-orientation in response to stimuli consisting in head rotations. The latter feature has implications to analyze the vestibulo-ocular reflex and constitutes an interesting opportunity to develop medical (oto-neurological) diagnostics. Details of data analysis are reported together with some results obtained in-vivo or with simple mechanical simulators that enable measurements under controlled  conditions. 
A Wearable Wireless Magnetic Eye-Tracker
Authors: Bevilacqua Giuseppe , Biancalana Valerio , Carucci Mario , Cecchi Roberto , Chessa Piero , Donniacuo Aniello , Mandalà Marco , Stiaccini Leonardo , viberti francesca
Published: February 2023

A wireless, wearable magnetic eye tracker is described and characterized. The proposed instrumentation enables simultaneous evaluation of eye and head angular displacements. Such a system can be used to determine the absolute gaze direction as well as to analyze spontaneous eye re-orientation in response to stimuli consisting in head rotations. The latter feature has implications to analyze the vestibulo-ocular reflex and constitutes an interesting opportunity to develop medical (oto-neurological) diagnostics. Details of data analysis are reported together with some results obtained in-vivo or with simple mechanical simulators that enable measurements under controlled  conditions. 