bluuebunny/crossref_metadata_2025_split huggingface dataset:
Heterogeneous Growth Cycles
Authors: Hernández-Veleros Zeus Salvador 
Published: November 2021

This paper focuses on the Dirichlet and the Dirichlet-multinomial distributions to analyze one definition of the cycle based on three economic performance regimens: augmentation, stagnation and diminution. We use data from 142 economies grouped in seven clusters during the second half of the last century, a period which has witnessed various structural changes. Furthermore, this paper advances to investigate what the probabilities are of reaching significant positive growth rates ⎯the frequency of the augmentation regimen⎯ which prevailed during the decade from 1950 to 1960, using Bayesian statistics.
Ranking multicriterio de viviendas: una adaptación del modelo de precio único
Authors: Cervelló Roberto , García Fernando , Guijarro Francisco 
Published: November 2021

Este trabajo presenta la aplicación del modelo multicriterio de precio único para elaborar un ranking total de viviendas. Realizando una adaptación de este modelo, se caracteriza el conjunto de viviendas en equilibrio desde la perspectiva del oferente y la perspectiva del demandante, y a partir del mismo se calcula un índice de eficiencia de las viviendas con el que construir el ranking. Se demuestra cómo, en una situación de equilibrio, ambas perspectivas conducen necesariamente a jerarquizaciones inversas. Frente a otras propuestas de ranking total, la utilizada en este trabajo (i) asume una actitud moderada por parte del decisor formulada mediante una base axiomática robusta, (ii) proporciona el peso de los criterios independientemente de la vivienda evaluada y de la actitud optimista o pesimista del decisor, y (iii) requiere un coste computacional mínimo. El modelo se ilustra sobre una muestra de viviendas situadas en la ciudad de Valencia.
Penerapan Algoritme Nearest Centroid Neighbor Classifier Based on K Local Means Using Harmonic Mean Distance (LMKHNCN) Untuk Klasifikasi Hasil Kinerja Pegawai Negeri Sipil
Authors: Hidayatullah Adam Syarif , Bachtiar Fitra Abdurrachman , Cholissodin Imam 
Published: November 2021

Keberhasilan sebuah perusahaan terjadi karena dapat mengelola sumber daya manusianya dengan baik begitu juga sebaliknya. Salah satu instansi yang mengelola sumber daya manusia menggunakan Manajemen Talenta adalah Badan Kepegawaian Daerah (BKD) kota Malang, dengan mengevaluasi pegawainya setiap tahunnya setelah pekerjaan selesai dilakukan. Hal ini menyebabkan hasil pekerjaan yang telah dilakukan tidak optimal, sehingga perlu identifikasi dini pegawai yang memiliki kinerja dibawah rata – rata sehingga dapat dievaluasi dan meminimalisir hasil pekerjaan yang tidak optimal dengan menggunakan teknik klasifikasi. Penelitian ini menggunakan teknik klasifikasi Nearest Centroid Neighbor Classifier Based on K Local Means Using Harmonic Mean Distance (LMKHNCN). Metode ini merupakan metode modifikasi dari metode K-Nearest Neighbor (KNN) dan dibuktikan memiliki performa lebih baik dibandingkan dengan metode aslinya KNN. Dilakukan pengujian F1-Score dan akurasi menggunakan K-Fold Cross Validation untuk mengetahui persebaran akurasi dan juga pengujian mengenai pengaruh normalisasi karena tidak ada informasi normalisasi pada penelitian sebelumnya. Metode pada kasus ini menghasilkan performa klasifikasi yang baik, dibuktikan bahwa hasil akurasi dan F1-Score oleh metode ini berturut – turut ialah mencapai 98,8% dan 98,1%. AbstractThe success of company occurs because is manage human resources well and vice versa. One of institute that mange human resource using Talent Management is Malang city Badan Kepegawaian Daerah (BKD), which evaluates its employee annually after the work is completed. This can cause not optimal work result, so it necessary to early identification of employees who have performance below average performance so that can be evaluated and minimize not optimal result. This study is use classification technique Nearest Centroid Neighbor Classifier Based on K Local Means Using Harmonic Mean Distance (LMKHNCN). This method is modified base algorithm of K-Nearest Neighbor (KNN). F1-Score and Accuracy using K-Fold Cross Validation to measure performance of this method and normalization testing due to no any information about that in previous study. This method is proven to have better performance compared to it original algorithm KNN. The method in this study has produced good classification performance. The result of classification accuracy and F1-Score by this method reach 98,8% dan 98,1%.
Segmentasi Citra Wajah dengan Implementasi Adaptif Threshold- Integral Image
Authors: Habibah Maryam Ummul , Kurniawan Muchamad 
Published: November 2021

Segmentasi wajah merupakan bagian penting dalam pengolahan citra digital untuk mengetahui objek wajah dalam citra sebelum dilakukan pendeteksian ekspresi wajah. Adaptif Threshold – Integral Image adalah salah satu teknik segmentasi berbasis pixel-based, yaitu local thresholding. Penelitian ini bertujuan untuk memisahkan objek wajah manusia dan background -nya. Citra wajah yang akan digunakan nanti citra di dalam ruangan (indoor) dan di luar ruangan (outdoor) dengan resolusi gambar 300x400 piksel. Pada penelitian ini juga mencari nilai parameter S (kernel) dan T (threshold) yang terbaik dengan melakukan 16 kali percobaan. Dan didapatkan hasil terbaik, yaitu citra di dalam ruangan (indoor) nilai S=1/2 dan T=50, serta citra di luar ruangan (outdoor) nilai S=1/30 dan T=30. Segmentasi citra wajah dengan menggunakan metode Adaptif Threshold – Integral Image robust (kuat) terhadap intensitas cahaya tinggi dan rendah dengan mengatur nilai parameter S (kernel) dan T (Threshold) maka metode ini mampu memisahkan objek wajah dan background -nya. Dari hasil uji coba threshold menggunakan metode Adaptif Threshold – Integral Image terhadap citra di dalam ruangan (indoor) dan di luar ruangan (outdoor) menghasilkan thresholding yang baik dengan mempertimbangkan nilai parameter S (kernel) dan T (threshold) memberikan hasil dengan tingkat akurasi yang tinggi, yaitu citra di dalam ruangan (indoor) sebesar 96.72%, dan citra di luar ruangan (outdoor) sebesar 93.59%. AbstractFace segmentation is an important in digital image processing to find out the object's face in the image before detecting facial expressions. Adaptive Threshold - Integral Image is a pixel-based segmentation technique, which is local thresholding. This study is intended to split the object of a human face and its background. Face images that will be used later in indoor and outdoor with an image resolution of 300x400 pixels. This study also searched for the best S (kernel) and T (threshold) parameter values by performing 16 experiments. And the best results are obtained, name the image in the room (indoor) the value of S = 1/2 and T = 50, and the image outside the room (outdoor) the value of S = 1/30 and T = 30. Face image segmentation using the Adaptive Threshold - Integral Image robust method of high and low light intensity by setting the S (kernel) and T (Threshold) parameter values, this method is able to split the face object and its background. From the results of the threshold trial using the Adaptive Threshold - Integral Image method for indoor and outdoor images produces a good thresholding by considering the values of the S (kernel) and T (threshold) parameters to give results with a high degree of accuracy, that is indoor images of 96.72%, and outdoor images of 93.59%.
Pemeringkatan Pencarian pada Buku Pedoman Akademik Filkom UB Menuju Merdeka Belajar dan Free E-Book Pembelajaran Sebagai Prototype Local Smart Micro Search Engine Menggunakan Algoritma Pagerank dan TF-IDF
Authors: Cholissodin Imam , Saâ€™rony Akhmad , Salsabila Rona , Firmansyah Ilham , Mahardika Guedho Augnifico , Pardede Andreas , Alaydrus Zaien Bin Umar 
Published: November 2021

Buku Pedoman Akademik FILKOM Universitas Brawijaya merupakan suatu kebutuhan informasi akademik yang cukup penting, dan juga buku penunjang pembelajaran seperti Free e-Book bagi para mahasiswa. Untuk memperoleh informasi yang relevan terhadap query yang diberikan seringkali belum sesuai dengan kebutuhan pencarian pengguna. Pengguna harus menguasai secara keseluruhan untuk mengetahui dokumen mana yang paling sesuai, dan proses ini akan memakan waktu yang banyak. Sistem ini mampu memberikan rekomendasi dokumen sesuai dengan hasil perhitungan pemeringkatan teks. Proses pemeringkatan teks dapat diselesaikan dengan algoritma PageRank, di mana dokumen yang memiliki bobot pemeringkatan terkecil, memiliki kata terbanyak pada dokumen tersebut. Algoritma ini telah dibuktikan mampu memeberikan feedback dokumen yang relevan melalui dua tahap pengujian. Evaluasi yang dilakukan terhadap dua buah pengujian menghasilkan rata-rata nilai recall tertinggi yaitu 80.6% pada data ke-1, dan data ke-2 didapatkan korelasi terbaik antara precision, recall dan f-measure sebesar 0,98, 0,99, 0,99. AbstractThe Brawijaya University FILKOM Academic Handbook is an important academic information need, as well as learning support books such as Free e-Books for students. To obtain information that is relevant to the query given is often not in accordance with the wishes of the user. Users must master the whole to find out which documents are most suitable, which is where the process will take a lot of time. This system is able to provide document recommendations in accordance with the results of the text ranking calculation. The process of ranking the text can be solved by the PageRank algorithm, where documents that have the smallest ranking weight, have the most words in the document. This algorithm has been proven to be able to provide feedback on relevant documents through two stages of testing. he evaluation conducted on the two tests resulted in the highest average recall value of 80.6% on the 1st dataset, and 2nd dataset the best correlation was obtained between precision, recall and f-measure of 0.98, 0.99, 0.99.
Klasifikasi Mutu Telur Burung Puyuh Berdasarkan Warna dan Tekstur Menggunakan Metode K-Nearest Neighbor (KNN) dan Fusi Informasi
Authors: Sumari Arwin Datumaya Wahyudi , Mawarni Putri Indah , Syulistyo Arie Rachmad 
Published: November 2021

Kualitas produk merupakan faktor utama untuk menjamin keberlangsungan satu usaha peternakan. Perusahaan telur puyuh yang memiliki ribuan burung Puyuh seperti CV. NS Quail Farm mampu memproduksi ribuan telur dalam sehari karena seekor burung Puyuh mampu menghasilkan 250-300 butir telur per tahun. Penyeleksian ribuan telur-telur tersebut dilakukan secara tradisional oleh para pekerja peternakan sehingga kualitas telur-telur hasil seleksi bergantung pada perspektif masing-masing pekerja. Guna memperoleh telur hasil seleksi dengan kualitas yang sama, maka dibangun sebuah sistem pencitraan digital untuk pemilihan telur burung Puyuh berdasarkan fitur warna dan tekstur kulit telur menggunakan metode klasifikasi K-Nearest Neighbor (KNN) yang dikombinasikan dengan fusi informasi. 300 data citra telur burung Puyuh diolah menggunakan normalisasi Red, Green, Blue (RGB) dan Otsu thresholding guna memperoleh fitur warna dan fitur tekstur yang kemudian difusikan menjadi fitur terfusi tunggal sebagai masukan pengklasifikasi KNN. Dari hasil-hasil penelitian, disimpulkan bahwa sistem berhasil mengklasifikasikan mutu telur Baik, Sedang, dan Buruk dengan akurasi rata-rata sebesar 77,78%. Disamping itu, klasifikasi dengan fusi informasi mampu mengungguli klasifikasi tanpa fusi informasi sebesar 11,11% pada nilai yang sama yakni 7 dan fusi informasi juga mampu mempercepat proses klasifikasi sebesar 0,22 detik dibandingkan terhadap klasifikasi tanpa fusi informasi.AbstractThe quality of product us a primary factor to ensure the sustainability of a farm business. A company which has thousands of quail such as CV. NS Quail is capable of producing thousand quail eggs in a day because a quail is able to produce 250-300 eggs per year. The selection of the eggs is carried out traditionally by the farm workers so that the quality of the selected eggs are depended on the perspective of each worker. In order to obtain the same quality of the selected eggs, a digital imaging system for quail egg selection based on color feature and texture feature using K-Nearest Neighbor (KNN) combined with information fusion is developed. 300 image data of quail egg was processed using Red, Green, Blue (RGB) and Otsu thresholding to obtain color feature and texture feature which then were fused to become single fused feature as the input to KNN classifier. From the research results, it is concluded that the system was managed to classify egg quality as good, medium, and bad with an accuracy of 77,78%. In addition, the classification with information fusion was able to outperform the classification without information fusion by 11.11% at the same value of 7 and information fusion is also able to accelerate classification process by 0.22 seconds compared to that of without information fusion.
Sistem Bantu untuk Pengrajin dalam Menentukan Kayu Terbaik Terbaik untuk Bahan Gitar dengan Menggunakan Matode Moora
Authors: Tundo Tundo , Nugroho Wisnu Dwi 
Published: November 2021

Penelitian ini bertujuan untuk membantu pengrajin kayu di Dongkelan, Krapyak, Yogyakarta dalam menentukan kayu terbaik untuk dijadikan sebagai bahan gitar, karena sering terjadi keluhan dari para pembeli bahwa bahan yang dijadikan bahan gitar cepat lapuk dan kusam dari segi warnah. Berdasarkan permasalahan tersebut, dicari suatu solusi dengan menggunakan metode Decision Support System Multi Objective Optimization on the basic of Ratio Analysis (MOORA) serta dibantu oleh pakar dalam menentukan kriteria yang tepat berkaitan penentuan kayu terbaik yang digunakan dalam pembuatan bahan gitar, setelah berdiskusi panjang ditemukan hasil kriteria yang tepat berdasarkan permasalahan, berupa kriteria kekuatan kayu, serat kayu, tekstur, dan berat kayu. Semua kriteria tersebut, kemudian diproses dengan menggunakan metode MOORA, dengan data yang digunakan sebanyak 29 jenis data kayu, yang diperoleh dari pengrajin yang ada di wilayah tersebut. Setelah diproses, diperoleh hasil 3 kayu terbaik yang layak untuk digunakan sebagai bahan pembuatan gitar secara berurutan dalah kayu Bubinga dengan nilai 18,36785, kayu Bocote dengan nilai 17,33385, dan kayu Eboni dengan nilai 17,33385 dari beberapa pilihan alternatif kayu yang ada. Membuktikan hasil dari metode MOORA, maka dilakukan responden secara langsung dengan memberikan hasil metode kepada pakar pembuat gitar. Dari 15 pakar pembuat gitar, 13 mengatakan setuju dengan peringkat 3 terbesar, dan 2 mengatakan kurang setuju. Sehingga ditemukan tingkat akurasi berdasarkan penilaian pakar sebesar 86,67 %. AbstractThis study aims to assist wood craftsmen in Dongkelan, Krapyak, Yogyakarta in determining the best wood to be used as guitar material, because there are frequent complaints from buyers that the material used for guitar is rotten quickly and is dull in terms of color. Based on these problems, a solution was sought using the Multi Objective Optimization on the basic of Ratio Analysis (MOORA) Decision Support System method and assisted by experts in determining the right criteria related to determining the best wood used in making guitar materials, after a long discussion found the results. the right criteria based on the problem, in the form of wood strength criteria, wood grain, texture, and wood weight. All of these criteria are then processed using the MOORA method, with the data used as much as 29 types of wood data, which are obtained from craftsmen in the area. After processing, the 3 best woods that are suitable for use as a guitar-making material are Bubinga wood with a value of 18.36785, Bocote wood with a value of 17.333385, and Eboni wood with a value of 17.333385 from several alternative wood choices. . Proving the results of the MOORA method, the respondents directly gave the results of the method to guitar-making experts. Of the 15 expert guitar makers, 13 said they agreed with the third largest ranking, and 2 said they disagreed. So that it found the level of accuracy based on expert judgment of 86.67%.
Shale adhesion force measurements via atomic force microscopy
Authors: Mitiurev Nikolai , Verrall Michael , Shilobreeva Svetlana , Keshavarz Alireza , Iglauer Stefan 
Published: November 2021

Wettability of sedimentary rock surface is an essential parameter that defines oil recovery and production rates of a reservoir. The discovery of wettability alteration in reservoirs, as well as complications that occur in analysis of heterogeneous sample, such as shale, for instance, have prompted scientists to look for the methods of wettability assessment at nanoscale. At the same time, bulk techniques, which are commonly applied, such as USBM (United States Bureau of Mines) or Amott tests, are not sensitive enough in cases with mixed wettability of rocks as they provide average wettability values of a core plug. Atomic Force Microscopy (AFM) has been identified as one of the methods that allow for measurement of adhesion forces between cantilever and sample surface in an exact location at nanoscale. These adhesion forces can be used to estimate wettability locally. Current research, however, shows that the correlation is not trivial. Moreover, adhesion force measurement via AFM has not been used extensively in studies with geological samples yet. In this study, the adhesion force values of the cantilever tip interaction with quartz inclusion on the shale sample surface, have been measured using the AFM technique. The adhesion force measured in this particular case was equal to the capillary force of water meniscus, formed between the sample surface and the cantilever tip. Experiments were conducted with a SiconG cantilever with (tip radius of 5 nm). The adhesion forces between quartz grain and cantilever tip were equal to 56.5 ± 5 nN. Assuming the surface of interaction to be half spherical, the adhesion force per area was 0.36 ± 0.03 nN/nm2. These measurements and results acquired at nano-scale will thus create a path towards much higher accuracy-wettability measurements and consequently better reservoir-scale predictions and improved underground operations.
Incidence of fungal keratitis in Libya: An epidemiological study
Authors: Atia Ahmed , Ashour Abdulsalam , Alfaigh Hanan 
Published: November 2021

Objectives:
The aim of this study was to assess the occurrence of eye fungal infection among patients attending the eye hospital in Tripoli city, Libya.

Materials and Methods:
Seventy-one patients with ocular fungal infections were subjected to clinical and microbiological investigations. They were selected from patients attending the Tripoli Eye Hospital. The specimens of the external ocular infections were collected using sterile swab and inoculated to different culture media. Data were presented as count and percentages.

Results:
The current findings showed that Aspergillus was the most common causative agent, being responsible for 91.54% of the all cases, followed by Candida albicans (8.46%).

Conclusion:
Occurrence of fungal keratitis gradually increased in the years after 2009, especially after 2013. Knowledge of the pathological course and clinical features of fungal keratitis will undoubtedly bead in early diagnosis and treatment, with reduction in ocular morbidity.
Psychosocial Issues Among Primary Caregivers of Patients with Advanced Head and Neck Cancer - A Mixed-method Study
Authors: Ramasamy Thendral , Veeraiah Surendran , Balakrishnan Kalpana 
Published: November 2021

Objectives:
This study aims to explore the psychosocial issues faced by the primary caregivers of advanced head and neck cancer patients with the primary objective to understand their experiences within social context.

Materials and Methods:
Burden and QOL of caregivers (n = 15) were quantified using Zarit Burden Interview schedule and caregiver quality of life index-cancer (CQOLC), respectively. Primary caregivers (n = 10) were interviewed using semi-structured interview schedule. Thematic analysis was employed to analyse the qualitative data. Descriptive statistics was used for quantitative data.

Results:
Four major themes emerged: (1) Impacts of caregiving, (2) coping with caregiving, (3) caregiver’s appraisal of caregiving and (4) caregiver’s perception of illness. Majority (73.3%) of the caregivers had QOL below 100. The mean CQOLC score was 73.07 (SD 24.17) and most (46.7%) of the caregivers reported mild-to-moderate burden, while 27% had little to no burden. The mean ZBI score was 32.4 (SD 18.20).

Conclusion:
Caregiving impacts the physical, emotional, financial and social aspects of caregiver’s life. Caregivers adopt active coping strategies to overcome the impacts of caregiving. Family acts as a major source of strength to manage the emotional constraints faced by Indian caregivers. Cultural beliefs and values of caregivers influence their appraisal of caregiving situation. Majority of the caregivers experienced mild-to-moderate burden while most of the caregivers scored low on QOL.
Компьютерное моделирование ультразвуковой агломерации субмикронных частиц с учетом вихревого движения несущей среды
Authors: Хмелев В.Н. , Голых Р.Н. , Нестеров В.А. , Боченков А.С. , Шалунов А.В. 
Published: November 2021

В статье представлены результаты численного эксперимента, показывающие, что акустические потоки, формирующиеся в резонансном газовом промежутке, обеспечивают повышение эффективности агломерации субмикронных частиц не менее 4 раз. Разработана численная модель процесса ультразвуковой агломерации, впервые учитывающая вихревое движение взвешенных частиц в акустических потоках.
A model of the influence of vortex acoustic flows on the efficiency of agglomeration is proposed. As a result of the numerical analysis of the model, the fundamental possibility of a significant (more than 4 times) increase in the efficiency of ultrasonic agglomeration of submicron particles due to the formation of vortex acoustic flows in resonant gaps has been revealed.