bluuebunny/crossref_metadata_2025 huggingface dataset:
Alih Teknologi Budidaya Ikan Lele pada Lahan Gambut di Desa Seponjen, Muaro Jambi
Authors: Fitriadi Ren , Palupi Mustika , Fakhri Saitul
Published: March 2022

Hutan rawa gambut di Provinsi Jambi telah banyak yang berubah menjadi semak belukar, ladang, tegalan dan areal terbuka yang tidak produktif. Sehingga lokasi tersebut perlu dimanfaatkan sebagai lahan budidaya ikan. Tujuan pengabdian ini adalah terciptanya percontohan usaha budidaya terpadu dan terintegrasi di lahan gambut dengan mengadopsi teknologi budidaya ikan sehingga memberikan penghasilan tambahan kepada masyarakat dan berdampak secara ekologi bagi restorasi gambut. Metode pengabdian yang dilakukan adalah pendekatan Participatory Rural Appraisal (PRA),  penyuluhan / diskusi dan percontohan/demplot yang melibatkan 20 orang masyarakat. Hasil budidaya ikan lele yang dilakukan selama 3,5 bulan dengan hasil produksi panen sebanyak 200 kg dengan SR 80%. Pakan yang dikonsumsi selama pemeliharaan sebanyak 210 kg.
Pemanfaatan Kultur Biakan Murni Bakteri Asam Laktat Genus (L. Plantarum) Pada Fermentasi Rebung di Sentra Pengolahan Rebung di Girikusumo Mranggen Demak
Authors: Rohadi Rohadi , Cahyanti Antonia Nani , Gunantar Devy Angga
Published: March 2022

Dusun Girikusumo, Banyumeneng Kecamatan Mranggen, Demak, Jawa Tengah merupakan salah satu sentra pengolahan rebung (bamboo shoots) menjadi produk fermentasi. Hasil fermentasi rebung dimanfaatkan sebagai sayuran isi Lumpia. Semua produsen rebung fermentasi masih menggunakan metode fermentasi alami dan menggunakan tawas (alum), pada tahap perebusan dan fermentasi. Disamping itu produsen rebung fermentasi tidak memanfaatkan limbah cair (broth) dari fermentasi rebung, sebagai ragi (starter) untuk proses fermentasi berikutnya. Pengabdian masyarakat ini bertujuan untuk meningkatkan pengetahuan dan keterampilan pengolah rebung, tentang proses produksi asinan rebung yang efisien, baik, dan aman serta meningkatkan pengetahuan dan keterampilan penyiapan starter dari biakan murni bakteri asam laktat (BAL) jenis L. plantarum. Metode yang digunakan adalah pendidikan masyarakat dan pelatihan.  Luaran (outcome) yang diperoleh dari pengabdian ini adalah  berupa peningkatan pengetahuan dan kapasitas pengolah rebung di Dusun Girikusumo, Mranggen Demak dalam memproduksi asinan rebung yang efisien, benar dan aman. Peserta yang berjumlah 16 orang yang terdiri dari pemasok dan pengolah rebung sudah memahami bahwasanya tawas tidak boleh dipakai dalam pengolahan rebung. Peserta paham bahwa limbah cair dari fermentasi alami rebung penuh (kaya) BAL dapat dimanfaatkan sebagai ragi untuk fermentasi rebung yang baru. Namun semua peserta tidak faham cara menyiapkan ragi starter dari kultur murni L. plantarum. Hasil pengabdian ini sangat penting agar produsen asinan rebung menghasilkan rebung yang aman pada tingkat residu cemaran logam aluminium.
Pelatihan Pembuatan MP ASI Dalam Mewujudkan Pemenuhan Gizi Balita di Kampung Penumping, Gowongan, Jetis
Authors: Sofiana Liena , Darmawati Linda Putri , Aditya Deliar Yudhantara , Setyorini Diyah , Amari Fortuna Indira
Published: March 2022

Penyakit yang diakibatkan oleh gizi pada balita masih menjadi permasalahan kesehatan di Indonesia, baik gizi kurang atau gizi lebih. Faktor yang mempengaruhi terjadinya adalah pendidikan, pendapatan, pengetahuan, keterampilan dalam mengelola makanan pendamping ASI. Untuk meningkatkan pengetahuan ibu dalam mengelola MPASI dan pengelolaannya dapat melalui pelatihan mengolah MPASI. Pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pengetahuan dan keterampilan ibu dalam mengolah MPASI sesuai dengan standar gizi untuk balita. Kegiatan intervensi yang dilakukan dengan menggunakan metode penyuluhan dan pelatihan dengan tujuan untuk meningkatkan pengetahuan masyarakat mengenai gizi balita dan praktik mengolah makanan pendamping ASI. Kegiatan ini dilakukan pada tanggal 5 November, 1 Desember dan 11-12 Desember tahun 2019 di Balai Dusun Balai RW 01, 02, dan 03 dengan jumlah peserta adalah ibu-ibu. Penyuluhan ini berjalan dengan lancar, semua peserta aktif dalam diskusi dan tanya jawab baik saat pemberian materi ataupun praktik. Hasil menyatakan bahwa pelatihan ini dapat meningkatkan pengetahuan dan keterampilan peserta.
Pembentukan dan Pelatihan Kader Posbindu PTM Berbasis Masjid di Kecamatan Turen Kabupaten Malang
Authors: Griana Tias Pramesti , Rachma Lailia Nur , Gaffar Herry Darsim
Published: March 2022

Pos Pembinaan Terpadu (Posbindu) Penyakit Tidak Menular (PTM) merupakan bentuk peran serta masyarakat dalam upaya deteksi dini, pemantauan dan pengendalian faktor risiko PTM yang dilaksanakan secara terpadu, rutin, dan periodik serta mandiri dan berkesinambungan. Dewan Masjid Indonsia (DMI) berkeinginan agar semua masjid di kecamatan Turen memiliki Posbindu PTM untuk memelihara kesehatan masyarakat di sekitarnya. Tujuan pengabdian masyarakat ini untuk menginisiasi pembentukan kader Posbindu PTM berbasis masjid di kecamatan Turen dan meningkatkan kualitas kemampuan kader. Digunakan metode Asset Based Community Development, dengan langkah awal dilakukan survey dan Focus Group Discussion dengan pengurus DMI dan takmir masjid. Dilakukan pengamatan pelaksanaan Posbindu PTM, survei tingkat pengetahuan dengan kuesioner dan pelatihan bagi kader dan calon kader. Hasil penilaian kuesioner tingkat pengetahuan didapatkan 73,13% kader Posbindu PTM dapat menjawab 60% soal yang diberikan dengan benar. Pelatihan yang diberikan membantu menambah kemampuan kader dan calon kader Posbindu PTM berbasis masjid di kecamatan Turen Kabupaten Malang.
Gestión de las páginas web de los centros de Educación Secundaria: voces de coordinadores TIC
Authors: Álvarez Álvarez Carmen , Moreno-Díaz Felipe
Published: March 2022

Introducción: El incremento en el uso de Internet y el desarrollo de las páginas web ha ofrecido la oportunidad a los centros educativos para implementar una nueva forma de comunicación e interacción con los usuarios.

Método: Se presenta un estudio cualitativo en el que se indaga, mediante un cuestionario abierto, cómo gestionan las páginas web 24 coordinadores TIC que trabajan en centros cántabros de Educación Secundaria (concertados y públicos y situados en zonas urbanas, semi-urbanas y rurales).

Resultados: Los resultados muestran las principales tendencias que se siguen en la actualidad a la hora de actualizar la página web, quiénes colaboran en dicha tarea, la responsabilidad del coordinador TIC y los retos a los que se enfrentan los centros en gestión web.

Conclusiones: Las páginas web constituyen un elemento fundamental de interacción y comunicación en la realidad actual de los centros, por lo que es imprescindible identificar los elementos objeto de mejora para facilitar la tarea a los encargados de éstas.
Legitimacy and Societal Consent under Putin’s Leadership: State Capacity and National Identity
Authors: Loftus Suzanne
Published: March 2022

The system of informal governance, despite its weak performance in many international comparative governance indicators, turned Russia around in the early 2000s, and keeps the country functioning despite evidence of endemic corruption or economic stagnation. Despite increasing authoritarianism, the regime has the consent of the governed and is considered legitimate inside Russia. Despite what many scholars have argued on the long-term prospects of the survival of the regime, the Russian political system has demonstrated resilience and will continue to do so for the foreseeable future. Legitimacy of the regime is based both on state capacity and state national identity. The former is an entity of the latter along with a strong and unique international standing. The post-Soviet national identity that took shape while Putin has been in power has allowed for positive “national self-esteem” to flourish throughout the country. The mentality of the general population has allowed the space necessary for this narrative to evolve and for the post-Soviet identity to take shape, exhibited by the symbiotic relationship between elite action and popular support.
IMPROVING THE METHODS FOR CALCULATING ELASTIC CHARACTERISTICS OF FIBRE COMPOSITES
Authors: Kisel' Yuriy , Ulyanov Alexey , Kamynin Viktor
Published: March 2022

Applying solid-state modelling methods for calculating the elastic properties and stress-strain state of fibre-reinforced composite materials is shown. A model of a composite material including a base and fibres is developed. The elastic properties and equivalent stresses in a fibrous composite material with different fibre content are determined.
MODEL OF MANAGING PROCESSES OF ENGINEERING CHANGES IN PRODUCTS AT AN INDUSTRIAL ENTERPRISE
Authors: Tatuyko Pavel
Published: March 2022

The aim of the work is to determine promising converters for supplying consumer devices with the required voltage level. As part of the task implementation, a mathematical description of the resonant converter with a series LC resonant circuit is made. The equivalent replacement circuit of the converter is given, as a result of its analysis analytical expressions are determined that describe the main dependences of this converter on the load and switching frequency of the keys. In the process of analyzing the resonant converter operation with a series LC resonant circuit, mathematical modelling methods are used. The result of the work is the obtained analytical expressions that allow determining the oscillatory circuit parameters for the resonant converter operation with a series LC resonant circuit in the mode with the highest efficiency. The presented graphs demonstrate the key parameter dependence of the oscillatory circuit on the load magnitude and on the switching frequency of semiconductor keys, and, accordingly, on the oscillatory circuit frequency. Applying a resonant converter with a series LC resonant circuit is possible in those areas where a static load is used that changes little over time. Applying this converter is not optimal for a dynamic load, because to maintain the output voltage at the required level, it will be necessary to complicate the control system and introduce pulse-width modulation in addition to pulse-frequency one and to control the converter by means of skipping control pulses in the case when an operating mode is close to the idle one.
Psychobiological personality traits of children and adolescents with disorders of arousal
Authors: Castelnovo Anna , Turner Katherine , Perogamvros Lampros , Cloninger Robert , Bertolotti Alessia , Galbiati Andrea , Proserpio Paola , Terzaghi Michele , Strambi Luigi Ferini , Manni Raffaele , Nobili Lino , Manconi Mauro , Canevini Maria Paola , Zambrelli Elena
Published: March 2022

Disorders of arousal (DOA) are Non-Rem Sleep (NREM) parasomnias that emerge from incomplete arousal out of deep sleep and lead to a broad variety of emotional and motor behaviours. Increasing evidence supports the hypothesis that specific psychopathological traits contribute to the multifactorial origin of these phenomena. The aim of the current multicenter study was to compare the personality profile of children and adolescents with and without DOA using the Junior Temperament and Character Inventory (JTCI).We enrolled 36 patients with a diagnosis of DOA (mean age of 11 ± 3 years, 64% males), and 36 healthy age and gender matched control subjects (mean age of 11.2 ± 3.6, years, 67% males). Their parents completed the Paris Arousal Disorder Severity Scale (PADSS), the Sleep Disturbance Scale for Children (SDSC) and the JTCI.Patients with DOA reached significantly higher levels compared to their control group in total PADSS (p <.0001) and in total SDSC (p < 0.0001). They also displayed higher scores in novelty seeking (p = 0.005), harm avoidance (p = 0.01), self-transcendence (p = 0.006) JTCI subscales, and lower scores on the self- directedness subscale (p = 0.004). Our pediatric sample with DOA exhibited specific psychobiological personality traits compared to age and gender matched subjects without DOA. These results shed light on new possible etiopathogenetic mechanisms, as TCI traits have been linked to specific genetic variants and brain circuits, like the reward system. Prospective studies are required to assess the effect of targeted psychological/psychiatric treatment on DOA symptomatology.
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF
Authors: Parekh Jayneel , Parekh Sanjeel , Mozharovskyi Pavlo , ́e-Buc Florence d’Alch , Richard Ga ̈el
Published: March 2022

This paper tackles post-hoc interpretability for audio processing networks. Our goal is to interpret decisions of a network in terms of high-level audio objects that are also listenable for the end-user. To this end, we propose a novel interpreter design that incorporates non-negative matrix factorization (NMF). In particular, a carefully regularized interpreter module is trained to take hidden layer representations of the targeted network as input and produce time activations of pre-learnt NMF components as intermediate outputs. Our methodology allows us to generate intuitive audio-based interpretations that explicitly enhance parts of the input signal most relevant for a network’s decision. We demonstrate our method’s applicability on popular benchmarks, including a real-world multi-label classification task.
Statistical modelling in L3/Ln acquisition
Authors: Garcia Guilherme D.
Published: March 2022

This chapter introduces Bayesian data analysis and shows how such an approach can better deal with the intricacies of L n acquisition data. The data analyzed is simulated based on Rothman (2010) to demonstrate how we can use Bayesian models to estimate variables of interest in R. The chapter discusses (a) how to tackle smaller sample sizes and (b) how to incorporate theoretical principles and assumptions into our statistical analysis. As will be shown, in addition to its general advantages, Bayesian data analysis provides an eﬀective toolset to address both (a) and (b). It also oﬀers a much more nuanced and comprehensive approach to meet the methodological needs in the ﬁeld. All ﬁles and code used are available at OSF.
Favouring Responsible Publishing: Creating a Database of Researchers and Surveying Their Knowledge, Attitudes and Opinions towards Open Access Publishing and a New Field-Specific Journal
Authors: Ng Jeremy Y. , Quach Halton , Steen Jeremy , Zheng Ming , Dhawan Tushar , Dychiao Julian Vincent T. , Hashmani Aisha , Jameel Bismah , Jegathesan Kirrthana , Kogan Leah , Li Xiao Wen , Reyes Natasha , Shah Jill , Ashbury Fredrick D. , Cooley Kieran , Haddad Pierre S.
Published: March 2022

Introduction: There may be value to understanding the interests and needs of a journal’s audience, particularly regarding open access publishing (OAP) and behaviours associated with predatory publishing while establishing a new field-specific journal. As a new journal facing potential challenges in the publishing space, the Journal of Natural Health Product Research (JNHPR) undertook a stakeholder and community feedback initiative on publishing research in the field of natural health products (NHPs). This is the first study, to our knowledge, where academic representatives of the journal used this method to examine the knowledge, attitudes, and opinions of its potential audience. Methods: A database of international researchers in the NHP field was built using publicly available online data. Most NHP researchers (n= 1892) were identified by a keyword-based, systematic search, with additional researchers discovered through snowball sampling. A survey was then developed and distributed to all identified researchers to collect their knowledge, attitudes, and opinions about OAP in general and the JNHPR. Results: One hundred sixty-seven NHP researchers completed the survey where most were familiar with OAP and preferred the OAP model over a subscription-based journal. Additionally, responses indicated that OAP is a polarizing subject with both positive and negative perceptions. Positives included wider circulation and the potential for shorter publication times, while negatives included the potential for less rigorous peer-review standards and generally higher costs. Regardless of perceptions on OAP, impact factor, reputation, scope, and indexing were the most valued factors in choosing a journal for submission.Discussion: According to the survey results, as a new field-specific journal, the JNHPR would benefit the NHP research community greatly, connecting NHP researchers globally. The journal succeeds in two areas: its broad scope, which attracts NHP researchers from a variety of disciplines, and its rapid publishing time. Indexing and further reduced publication fees for developing nations were mentioned as areas in need of improvement. Conclusions: This approach may be useful to researchers who wish to launch their own journal in the future to gain a better understanding of their potential audience’s knowledge, attitudes, and opinions, allowing them to better engage and provide for their audience.
Resume tentang konsep dasar ekonomi
Authors: Khumairah Latifa
Published: March 2022

Ekonomi berasal dari kata ekonomi dari bahasa Yunani.
Writing Literature Reviews in Church-Based Research
Authors: Dunaetz David Robert
Published: March 2022

Because of the knowledge explosion taking place, literature reviews in church-based research are needed more than ever. Summaries and syntheses of previous research make this knowledge available to practitioners and help researchers focus on what remains unknown. In contrast to empirical studies, literature reviews rely on previously published studies to make conclusions and advance theory. These studies may include both church-based research and more general research that is not particularly Christian. In contrast to meta-analyses which focus on synthesizing statistical information, literature reviews focus on conceptual synthesis and theory advancement. To write a literature review, authors must first choose a research problem to address. An initial review of past literature will help them focus on a narrower research question, most likely in an iterative process, to choose a specific topic. The authors must also consider the purpose of their review in light of past research and theoretical contributions that they can make to the chosen topic.
A practical framework for multi-domain speech recognition and an instance sampling method to neural language modeling
Authors: Zhang Yike , Feng Xiaobing , Liu Yi , Cao Songjun , Ma Long
Published: March 2022

Automatic speech recognition (ASR) systems used on smartphones or vehicles are usually required to process speechqueries from very different domains. In such situations, avanilla ASR system usually fails to perform well on every do-main. This paper proposes a multi-domain ASR frameworkfor Tencent Map, a navigation app used on smart phones andin-vehicle infotainment systems. The proposed frameworkconsists of three core parts: a basic ASR module to generaten-best lists of a speech query, a text classification moduleto determine which domain the speech query belongs to,and a reranking module to rescore n-best lists using domain-specific language models. In addition, an instance samplingbased method to training neural network language models(NNLMs) is proposed to address the data imbalance problemin multi-domain ASR. In experiments, the proposed frame-work was evaluated on navigation domain and music domain,since navigating and playing music are two main features ofTencent Map. Compared to a general ASR system, the pro-posed framework achieves a relative 13% ∼ 22% charactererror rate reduction on several test sets collected from TencentMap and our in-car voice assistant.
S3T: Self-Supervised Pre-training with Swin Transformer for Music Classification
Authors: Zhao Hang , Zhang Chen , Zhu Bilei , Ma Zejun , Zhang Kejun
Published: March 2022

In this paper, we propose S3T, a self-supervised pre-training method with Swin Transformer for music classification, aiming to learn meaningful music representations from massive easily accessible unlabeled music data. S3T introduces a momentum-based paradigm, MoCo, with Swin Transformer as its feature extractor to music time-frequency domain. For better music representations learning, S3T contributes a music data augmentation pipeline and two specially designed pre-processors. To our knowledge, S3T is the first method combining the Swin Transformer with a self-supervised learning method for music classification. We evaluate S3T on music genre classification and music tagging tasks with linear classifiers trained on learned representations. Experimental results show that S3T outperforms the previous self-supervised method (CLMR) by 12.5 percents top-1 accuracy and 4.8 percents PR-AUC on two tasks respectively, and also surpasses the task-specific state-of-the-art supervised methods. Besides, S3T shows advances in label efficiency using only 10\% labeled data exceeding CLMR on both tasks with 100\% labeled data.
CONTRASTIVE-MIXUP LEARNING FOR IMPROVED SPEAKER VERIFICATION
Authors: Zhang Xin , Jin Minho , Chendg Roger , Li Ruirui , Han Eunjung , Stolcke Andreas
Published: March 2022

This paper proposes a novel formulation of prototypical loss with mixup for speaker verification. Mixup is a simple yet efficient data augmentation technique that fabricates a weighted combination of random data point and label pairs for deep neural network training.Mixup has attracted increasing attention due to its ability to improve robustness and generalization of deep neural networks. Although mixup has shown success in diverse domains, most applications have centered around closed-set classification tasks. In this work, we propose contrastive-mixup, a novel augmentation strategy that learns distinguishing representations based on a distance metric. During training, mixup operations generate convex interpolations of both inputs and virtual labels. Moreover, we have reformulated the prototypical loss function such that mixup is enabled on metric learning objectives. To demonstrate its generalization given limited training data, we conduct experiments by varying the number of available utterances from each speaker in the VoxCeleb database. Experimental results show that applying contrastive-mixup outperforms the existing baseline, reducing error rate by 16\% relatively, especially when the number of training utterances per speaker is limited.
Extended Graph Temporal Classification for Multi-Speaker End-to-End ASR
Authors: Chang Xuankai , Moritz Niko , Hori Takaaki , Watanabe Shinji , Le Roux Jonathan
Published: March 2022

Graph-based temporal classification (GTC), a generalized form of the connectionist temporal classification loss, was recently proposed to improve automatic speech recognition (ASR) systems using graph-based supervision.For example, GTC was first used to encode an N-best list of pseudo-label sequences into a graph for semi-supervised learning.In this paper, we propose an extension of GTC to model the posteriors of both labels and label transitionsby a neural network, which can be applied to a wider range of tasks.As an example application, we use the extended GTC (GTC-e) for the multi-speaker speech recognition task. The transcriptions and speaker information of multi-speaker speech are represented by a graph, where the speaker information is associated with the transitions and ASR outputs with the nodes. Using GTC-e, multi-speaker ASR modelling becomes very similar to single-speaker ASR modeling, in that tokens by multiple speakers are recognized as a single merged sequence in chronological order.For evaluation, we perform experiments on a simulated multi-speaker speech dataset derived from LibriSpeech, obtaining promising results with performance close to classical benchmarks for the task.
Acoustic Event Detection with Classifier Chains
Authors: Komatsu Tatsuya , Watanabe Shinji , Miyazaki Koichi , Hayashi Tomoki
Published: March 2022

This paper proposes acoustic event detection (AED) with classifier chains, a new classifier based on the probabilistic chain rule. The proposed AED with classifier chains consists of a gated recurrent unit and performs iterative \red{binary detection} of each event one by one. In each iteration, the event's activity is estimated and used to condition the next \red{output} based on the probabilistic chain rule to form classifier chains. Therefore, the proposed method can handle the interdependence among events upon classification, \red{while} the conventional AED methods with multiple binary classifiers with a linear layer and sigmoid function have placed an assumption of conditional independence.In the experiments with a real-recording dataset, the proposed method demonstrates its superior AED performance to a relative 14.80\% improvement compared to a convolutional recurrent neural network baseline system with the multiple binary classifiers.
A Squeeze-and-Excitation and Transformer based Cross-task System for Environmental Sound Recognition
Authors: Bai Jisheng , Chen Jianfeng , Mou~Wang  , Ayub Muhammad Saad
Published: March 2022

Environmental sound recognition (ESR) is an emerging research topic in audio pattern recognition.Many tasks are presented to resort to computational systems for ESR in real-life applications.However, current systems are usually designed for individual tasks, and are not robust and applicable to other tasks.Cross-task systems, which promote unified knowledge modeling across various tasks, have not been thoroughly investigated.In this paper, we propose a cross-task system for three different tasks of ESR: acoustic scene classification, urban sound tagging, and anomalous sound detection.An architecture named SE-Trans is presented that uses attention mechanism-based Squeeze-and-Excitation and Transformer encoder modules to learn channel-wise relationship and temporal dependencies of the acoustic features.FMix is employed as the data augmentation method that improves the performance of ESR.Evaluations for the three tasks are conducted on the recent databases of DCASE challenges. The experimental results show that the proposed cross-task system achieves state-of-the-art performance on all tasks. Further analysis demonstrates that the proposed cross-task system can effectively utilize acoustic knowledge across different ESR tasks.
Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing
Authors: Qi Jun , Yang Chao-Han Huck , Chen Pin-Yu
Published: March 2022

This work focuses on designing low complexity hybrid tensor networks by considering trade-offs between the model complexity and practical performance. Firstly, we exploit a low-rank tensor-train deep neural network (TT-DNN) to build an end-to-end deep learning pipeline, namely LR-TT-DNN. Secondly, a hybrid model combining LR-TT-DNN with a convolutional neural network (CNN), which is denoted as CNN+(LR-TT-DNN), is set up to boost the performance. Instead of randomly assigning large TT-ranks for TT-DNN, we leverage Riemannian gradient descent to determine a TT-DNN associated with small TT-ranks. Furthermore, CNN+(LR-TT-DNN) consists of convolutional layers at the bottom for feature extraction and several TT layers at the top to solve regression and classification problems. We separately assess the LR-TT-DNN and CNN+(LR-TT-DNN) models on speech enhancement and spoken command recognition tasks. Our empirical evidence demonstrates that the LR-TT-DNN and CNN+(LR-TT-DNN) models with fewer model parameters can outperform the TT-DNN and CNN+(TT-DNN) counterparts.
Materi perkuliahan Konsep dasar ekonomi
Authors: Ali Nurfadilla Nur
Published: March 2022

Tulisan ini bertujuan untuk membantu teman-teman dalam mencari materi terkait ekonomi yang telah disampaikan oleh dosen kami di kampus, dan juga sebagai bukti pemenuhan tugas individu yang telah diberikan. selain itu, dengan adanya resume materi ini bisa membantu para mahasiswa untuk bisa berpikir lebih dalam mengembangkan materi agar bisa lebih lengkap dan mudah dimengerti.
Pengantar Makro Ekonomi Islam
Authors: Mirnawati
Published: March 2022

Ekonomi makro atau makroekonomi adalah bagian dari ilmu ekonomi yang mempelajari masalah ekonomi secara keseluruhan (agregatif). Ekonomi makro mempelajari konsisi ekonomi suatu masyarakat/negara seperti pengangguran, kesempatan kerja, pengeluaran negara, pendapatan nasional, tingkat suku bunga, kurs/nilai tukar, dan sebagainya.
Towards Speaker Age Estimation with Label Distribution Learning
Authors: Si Shijing , Wang Jianzong , Peng Junqing , Xiao Jing
Published: March 2022

Existing methods for speaker age estimation usually treat it as a multi-class classification or a regression problem. However, precise age identification remains a challenge due to label ambiguity, \emph{i.e.}, utterances from adjacent age of the same person are often indistinguishable. To address this, we utilize the ambiguous information among the age labels, convert each age label into a discrete label distribution and leverage the label distribution learning (LDL) method to fit the data. For each audio data sample, our method produces a age distribution of its speaker, and on top of the distribution we also perform two other tasks: age prediction and age uncertainty minimization. Therefore, our method naturally combines the age classification and regression approaches, which enhances the robustness of our method. We conduct experiments on the public NIST SRE08-10 dataset and a real-world dataset, which exhibit that our method outperforms baseline methods by a relatively large margin, yielding a 10\% reduction in terms of mean absolute error (MAE) on a real-world dataset.
Instance-Level Loss based Multiple-Instance Learning for Acoustic Scene Classification
Authors: CHOI WON-GOOK , CHANG JOON-HYUK , YANG JAE-MO , MOON HAN-GIL
Published: March 2022

In acoustic scene classification (ASC) task, an acoustic scene consists of diverse attributes and is inferred by identifying combinations of some distinct attributes among them.This study aims to extract and cluster these attributes effectively using a multiple-instance learning (MIL) framework for ASC.MIL, known as one of the weakly supervised learning methods, is a way to extract instances from input data and infer a scene corresponding to the input data with those unlabeled instances.We develop the MIL framework more suitable for ASC systems, adopting instance-level labels and instance-level loss, which are effective in extracting and clustering instances.As a result, the witness rate increases significantly compared to the framework without instance-level loss and labels.Also in several MIL-based ASC systems, the classification accuracy improves by about 5 to 11\% than without instance-level loss.In addition, we designed a fully separated convolutional module which is a low-complexity neural network consisting of pointwise, frequency-sided depthwise, and temporal-sided depthwise convolutional filters.Considering both complexity and performance, our proposed system is more practical compared to previous systems on the DCASE 2019 challenge task 1-A leader board.We surpassed the third-place model by achieving a performance of 82.3\% with only the model complexity of 417K, which is at least 40 times fewer than other systems.
Pengembangan Media Pembelajaran Pop Up Book Pada Materi Bangun Ruang Kelas V SDN Bugih 1 Pamekasan
Authors: Pradini Nuril Laila
Published: March 2022

Matematika adalah sebuah pelajaran yang tidak jauh dari rumus dan berhitung. Dalam kehidupan sehari-hari tentunya kita tidak akan terlepas dari matematika . Banyak orang yang beranggapan bahwa matematika merupakan pelajaran yang sulit untuk dipahami karena banyaknya rumus yang digunakan. “Matematika adalah ilmu deduktif, aksiomatik, formal, hierarkis, abstrak, bahasa symbol yang padat inti dan semacamnya”. Dari dua defenisi mengenai matematika yang telah disebutkan, maka dapat disimpulkan bahwa matematika merupakan sebuah ilmu yang abstrak dan sangat penting untuk dipelajari karena sangat berguna di dalam kehidupan. Media pembelajaran yang baik dapat mampu meningkatkan rasa ingin tau siswa terhadap materi pembelajaran sehingga siswa dapat lebih aktif di dalam kelas saat pembelajaran. Pentingnya penggunaan media pembelajaran dalam mentransfer ilmu sangatdiperlukan.
A BENCHMARK OF STATE-OF-THE-ART SOUND EVENT DETECTION SYSTEMS EVALUATED ON SYNTHETIC SOUNDSCAPES
Authors: Ronchini Francesca , Serizel Romain
Published: March 2022

This paper proposes a benchmark of submissions to Detection and Classification Acoustic Scene and Events 2021 Challenge (DCASE) Task 4 representing a sampling of the state-of-the-art in Sound Event Detection task. The submissions are evaluated according to the two polyphonic sound detection score scenarios proposed for the DCASE 2021 Challenge Task 4, which allow to make an analysis on whether submissions are designed to perform fine-grained temporal segmentation, coarse-grained temporal segmentation, or have been designed to be polyvalent on the scenarios proposed.We study the solutions proposed by participants to analyze their robustness to varying level target to non-target signal-to-noise ratio and to temporal localization of target sound events. A last experiment is proposed in order to study the impact of non-target events on systems outputs. Results show that systems adapted to provide coarse segmentation outputs are more robust to different target to non-target signal-to-noise ratio and, with the help of specific data augmentation methods, they are more robust to time localization of the original event. Results of the last experiment display that systems tend to spuriously predict short events when non-target events are present. This is particularly true for systems that are tailored to have a fine segmentation.
Epsilon-Logarithm Theorem
Authors: Nam Kyumin
Published: March 2022

In this paper, we provide Epsilon-Logarithm Theorem.
Pengantar Makro ekonomi
Authors: Azifah Nurul
Published: March 2022

Makro ekonomi yaitu ilmu yang memperlajari mekanisme bekerjanya perekonomian secara keseluruhan. Yang dimaksud variabel keseluruhan adalah variabel tingkat pendapatan nasional, konsumsi rumah tangga, investasi nasional, tingkat tabungan, balanja pemerintah, tingkat harga umum, jumlah uang beredar, kesempatan kerja neraca pembayaran.
Suicidal Ideation
Authors: Mai Nhat Chi
Published: March 2022

Suicidal ideation (or suicidal thoughts) means having thoughts, ideas, or ruminations about the possibility of ending one's own life. It is not a diagnosis, but is a symptom of some mental disorders and can also occur in response to adverse events without the presence of a mental disorder.
RESUME PERTEMUAN DUA EKONOMI MIKRO
Authors: Nurqalbi Amanda
Published: March 2022

RESUME PERTEMUAN KEDUA EKONOMI MIKRO
Robust and Complex Approach of Pathological Speech Signal Analysis
Authors: Mekyska Jiri , Eva~Janousova  , Pedro~Gomez-Vilda  , Zdenek~Smekal  , Irena~Rektorova  , Eliasova Ilona , Kostalova Milena , Mrackova Martina , Alonso-Hernandez Jesus B. , Faundez-Zanuy Marcos , Lopez-de-Ipina Karmele
Published: March 2022

This article presents a~study of the approaches in the state-of-the-art in the field of pathological speech signal analysis with a~special focus on parametrization techniques. It provides a~description of 92 speech features where some of them are already widely used in this field of science and some of them have not been tried yet (they come from different areas of speech signal processing like speech recognition or coding). As an original contribution, this work introduces 36 completely new pathological voice measures based on modulation spectra, inferior colliculus coefficients, bicepstrum, sample and approximate entropy and empirical mode decomposition. The significance of these features was tested on 3 (English, Spanish and Czech) pathological voice databases with respect to classification accuracy, sensitivity and specificity. To our best knowledge the introduced approach based on complex feature extraction and robust testing outperformed all works that have been published already in this field. The results (accuracy, sensitivity and specificity equal to $100.0\pm0.0\,\%$) are discussable in the case of Massachusetts Eye and Ear Infirmary (MEEI) database because of its limitation related to a~length of sustained vowels, however in the case of Pr{\'i}ncipe de Asturias (PdA) Hospital in Alcal{\'a} de Henares of Madrid database we made improvements in classification accuracy ($82.1\pm3.3\,\%$) and specificity ($83.8\pm5.1\,\%$) when considering a~single-classifier approach. Hopefully, large improvements may be achieved in the case of Czech Parkinsonian Speech Database (PARCZ), which are discussed in this work as well. All the features introduced in this work were identified by Mann-Whitney~U test as significant ($p < 0.05$) when processing at least one of the mentioned databases. The largest discriminative power from these proposed features has a~cepstral peak prominence extracted from the first intrinsic mode function ($p = 6.9443\cdot10^{-32}$) which means, that among all newly designed features those that quantify especially hoarseness or breathiness are good candidates for pathological speech identification. The article also mentions some ideas for the future work in the field of pathological speech signal analysis that can be valuable especially under the clinical point of view.
The n-th Mean
Authors: Nam Kyumin
Published: March 2022

We define the n-th mean of a_1, a_2, ..., a_k as M_n(a_1, a_2, ..., a_k) = I_{n+1}({H_n}_{i=1}^{k} (a_i), k) where a_1, a_2, ..., a_k ∈ R, {H_i}_{k=1}^{n} = H_i(a_1, H_i(a_2, ..., H_i(a_{n-1}, a_n)...)).
The development of creative search strategies
Authors: Hart Yuval , Kosoy Eliza , Liquin Emily , Leonard Julia , Mackey Allyson , gopnik alison
Published: March 2022

How does creativity develop? Creativity is a multi-faceted behavior and thus it is difficult to find measures for creativity that are both precise and comparable across development. Here, we examine the development of creativity using a “creative foraging” task. The task measures different facets of creativity which we compare between 4- to 8-year-old children and adults. We find that compared to adults, children spend a higher percentage of their search exploring, and their exploitation phases are less efficient. Moreover, children orient their search to a different and smaller region of the search space, but within that space they produce more unique creative products. Lastly, as children grow up, their creative products become more adult-like and their uniqueness decreases. Together, these results suggest that creative search changes across development, in the search strategy employed, in how the space of possibilities is navigated, and in what ideas are ultimately chosen.
Trusting to abide: The role of institutional and interpersonal trust for the support of COVID-19 prevention behaviors and policies and the mediating role of national identification
Authors: Gkinopoulos Theofilos , Elbaek Christian T. , Mitkidis Panagiotis
Published: March 2022

Trust in the era of the pandemic has been a key determining factor of compliance with health protective behaviors and policies. However, little has been evidenced on underlying mechanisms of this relationship, such as national identification. Lack of trust may give rise to xenophobic attitudes, making national identities salient and leading to perceptions of foreigners as a threat against domestic public health states and economies but, on the other hand, trust may ensure shared social identifications as a nation as highly important. To gain a better understanding of how different levels of trust – interpersonal, institutional and trust towards science – has affected health containment behaviors and support of public health policies, as well as what the mediating role of national identification is, we analyzed a national representative sample from the United Kingdom (Total N = 895). We found that the different measures of trust, as well as national identification, positively predicted abidance to health containment behaviors as well as support of public health policies. Facets of trust were also mediated by national identification to predict health containment behaviors and support for public health policies. We discuss the results in light of the societal significance of restoration and assurance of people’s multilevel trust amidst the still evolving hygienic crisis that threatens nations worldwide.
Social Psychology, Alternative Scenario Theory, and the case of Judas Iscariot
Authors: Wernik Uri
Published: March 2022

The Gospels' depiction of Judas Iscariot, as the evil betrayer of Jesus, was generalized over the centuries to Jews as a whole and became the foundation for antisemitism, eventually leading up to the Holocaust. The arguments and pleas to avoid blaming all the past and present Jews, as well as having some empathy for Judas' fate, are reviewed. These attempts are based on an uncritical acceptance of the Gospels' narrative, in which the power struggles between the disciples are ignored and Judas' presumed motivation to betray is not questioned. Notwithstanding the gospel of Judas, the article goes further and suggests an alternative scenario: Judas was Jesus' closest friend, a supporter of his social agenda and unlike Simon Peter, his rival, not a proponent of Jesus' exaltation as the Messiah. Judas Iscariot became the victim of false blaming and scapegoating.
Likely decline in the number of farms globally by the middle of the century
Authors: Mehrabi Zia
Published: March 2022

Farm number and size are deemed important for a variety of social and environmental outcomes,including yields, input use efficiencies, biodiversity, crop diversity, climate change, and concentrationof power in food systems. Using a model incorporating theoretical drivers of the creationand consolidation of farms within countries, I historically reconstruct the number of farms onEarth over 1969-2013 and predict their future evolution. I show that under current developmenttrajectories the number of farms globally will likely decline from the current 616M (95% CIs495M-779M) in 2020 to 272M (95% CIs 200M-377M) by the end of the 21st century, with averagefarm size doubling. In some regions, Europe and Northern America, we will see a continueddecline from recent history, whereas in other regions, including Asia, Middle East & NorthAfrica, Oceania, and Latin America and the Caribbean, we will see a turning-point from farmcreation to widespread consolidation. The turning point also occurs for Sub-Saharan Africa, butmuch later in the century. This world in which significantly fewer large farms replace numeroussmaller ones carries major rewards and risks for the human species and the food systems whichsupport it.
Situational Appraisals Shape Preferences for Escalation and Conciliation in Foreign Policy Crises
Authors: Milliff Aidan
Published: March 2022

What determines whether the public supports aggressive, conciliatory, or business-as-usual strategies in response to military and foreign policy crises? What explains why similar and reasonable people diverge in their preferred policies for dealing with perceived military threats posed by the rise of China? Using a large survey experiment with over 3,000 respondents in the United States, I show that situational appraisals—respondents’ perceptions of how controllable and predictable a threat environment is—have significant and substantial effects on the type of military action that respondents prefer when confronted with a plausible but dangerous escalation of a U.S.-China maritime crisis in the South China Sea. Control and predictability appraisals regulate preferences for approach vs. avoid strategies and drastic vs. moderate strategies, respectively. Respondents with appraisals of low control and low predictability, for instance, are more likely to favor withdrawing U.S. forces from disputed territory, while respondents with high control and low predictability appraisals favor potentially-escalatory steps to enlarge U.S. Freedom of Navigation operations. Findings from the survey experiment have implications for literature on public opinion about foreign policy, as well as both academic implications and practical lessons crisis decision-making.
Reconstructing the Lost Years of Jesus
Authors: Wernik Uri
Published: March 2022

The inquiries about the lost years of Jesus have invited wild suppositions and speculations. This enigma was treated in the scholarly literature as a non-issue or an issue that for lack of facts, cannot be resolved. Two existing common will be reviewed in brief, and a new answer, based on an examination of Jesus’ parables, using the methodology of structural corroboration will be offered. In this approach, different considerations and findings reinforce each other: Nietzsche’s idea of philosophy as autobiography, studies on charismatic religious leaders, psychological theories of transition into adulthood and search for meaning, understanding Jesus as a prophet, and seeing him in the context of his family. It is suggested that some parables and sayings usually examined from different perspectives, can be understood as personal anecdotes, gleaned from his life experience during the undocumented years. Based on this portrayal, it becomes clear how Jesus found his mission in life, and some open questions in the Gospels’ narrative can be answered.
Mapping Research on Cardio-Metabolic Diseases
Authors: Rafols Ismael , Yegros-Yegros Afredo , van de Klippe Wouter , Willemse Tim
Published: March 2022

This report aims to map and provide information on current cardiometabolic research to inform and help funding agencies reflect on their research and innovation priorities. The emphasis lies in showing the distribution of current research across fields and approaches against perceived societal needs.
Pediatric Acute Mastoiditis: Recent Evolutions in Clinical Presentation and Microbiology
Authors: Bruyne N De , Bruyne N De , I Dhooge , E De Leenheer , V Van Driessche , L Coorevits , H Van Hoecke
Published: March 2022

Acute mastoiditis is a well-known complication of acute otitis media in children. Last year we noticed some changes: more virulent pathogens, a more fulminant course of the disease and an increased need for surgical treatment in children with acute mastoiditis admitted to our hospital. Recently, other authors have raised the same concerns. Based on the last 12 consecutive cases of pediatric acute mastoiditis admitted to our hospital and a review of recent literature, we discuss a possible change in presentation, complication rate and microbiology in order to raise vigilance to a possibly changing pathology.
Forecasting of Covid-19 deaths in South Africa using the autoregressive integrated moving average time series model
Authors: Kinyili Musyoka , Wanyonyi Maurice
Published: March 2022

Covid-19 epidemic continues to escalate globally posing life threats to humans. Time series modeling plays a key role for the prediction of data-driven scenarios. A case for Covid-19 pandemic future numbers occurrence is one of the open forecasting scenario for application of the time series modeling. We applied the Autoregressive Integrated Moving Average (ARIMA) model to forecast the possible numbers of Covid-19 deaths in the Republic of South Africa using the previously reported data for a period of 17 months (May 2020 to September 2021). We adapted the Box-Jenkins’ methodology to step-by-step achieve the entire forecasting process. We identified the MA(1) (ARIMA(0,0,1)) as the best model based on the Akaike Information Criterion and the Bayesian Information Criterion. The forecasting done at 95% confidence interval for a period of 7 months (October 1, 2021 to April 31, 2022) indicated that the Covid-19 associated deaths in South Africa would slightly increase during the month of October 2021 but remain constant throughout the entire prediction period.