bluuebunny/crossref_metadata_2025_split huggingface dataset:
LINEAR GROWTH AND FINAL HEIGHT IN PEOPLE WITH TYPE 1 DIABETES MELLITUS: A STUDY FROM KARACHI-PAKISTAN
Authors: Ali Wajid , Riaz Musarrat , Askari Saima , Basit Abdul 
Published: August 2022

OBJECTIVE: To determine the linear growth in children/adolescents with type 1 diabetes mellitus (T1DM) at a tertiary care hospital. METHODS: This observational study was conducted in Baqai Institute of Diabetology and Endocrinology, Baqai Medical University, Karachi, Pakistan from January-2001 to July-2021. All children/adolescents diagnosed with T1DM of either gender, between 8-18 years age visiting the outpatient department were included after informed consent. Predesigned questionnaire was developed for data records. Height of study participants and parents was checked in centimeters (cm) by stadiometer and mid-parental height was calculated. Weight was checked in kilograms (kg) on calibrated digital weight machine. Centers for Disease Control and Prevention growth chart was plotted and growth velocity was checked every six months to check linear growth. Final height was compared with targeted height of respective participants. RESULTS: Total of 66 people participated (24 male, 42 female), with mean age at diagnosis was 11.17±4.77 years and duration of diabetes at first visit was 1.97±3.3 years. Mean age at menarche was noted 13.56±1.41 years. The overall height standard deviation score (SDS) at first visit was -0.62±2.58 and at last visit was -1.34±0.94, whereas the overall weight SDS at first visit and at last visit was -0.62±2.58 and 1.34±0.94 respectively. Furthermore, overall mid-parental height was 160.95±10.28 cm and 50% males and 85.7% females achieved genetic target height (p-value=0.002). CONCLUSION: Majority of males did not achieve genetic target height, however females achieved genetic target height along with late age of menarche as compared to general population.
FREQUENCY OF CARDIOMETABOLIC RISK FACTORS AMONG YOUNG PEOPLE WITH TYPE 2 DIABETES MELLITUS AT A TERTIARY CARE UNIT OF KARACHI, PAKISTAN
Authors: Abbas Kanwal , Riaz Musarrat , Askari Saima , Basit Abdul 
Published: August 2022

OBJECTIVE: To observe frequency of cardiometabolic risk factors (CMRF) among young people with type 2 diabetes mellitus (T2DM). METHODS: This retrospective study was conducted at Baqai Institute of Diabetology and Endocrinology, Baqai Medical University, Karachi-Pakistan. Data of all patients of T2DM aged 18-45 years, from 1st January-2000 to 31st December-2019 of first patient visit was retrieved and analyzed from computerized hospital management system record. Age, gender, duration of diabetes, smoking habit, family history of diabetes, glycemic status, fasting lipid profile, blood pressure and body-mass-index was noted to assess CMRF in T2DM. RESULTS: Out of 5336, 54.5% (2907) were male and 1643 (30.8%) people were newly diagnosed. Mean age of patients at diagnosis of diabetes was 31.94±5.52 years, mean age at first out-patient department (OPD) visit was 35.52±4.58 years and mean diabetes duration was 3.52±3.58 years. At time of first OPD visit 3878 (77.1%) were obese, 585 (11%) were smokers and 1663 (31.4%) were hypertensive. Furthermore, 4161 (78%) had positive family history for diabetes, 1274 (47.2%) had HbA1c >10%, 1069 (39.6%) had 7-10% and 357 (13.2 %) had <7% respectively. Additionally, 1864 (85.8%) of people with diabetes had low HDL-C, 1387 (63.4%) had high triglycerides, 1552 (60%) had high LDL-C and 717 (32.4%) had high total cholesterol at the time of presentation. CONCLUSION: Increased frequency of CMRF is noted in T2DM young people. Obesity, smoking, hypertension, dyslipidemia, poor glycemic control, and positive family history of diabetes all contribute to disease's burden and early cardiovascular morbidity and mortality.
Deep Reinforcement Learning in Human Activity Recognition: A Survey
Authors: Nikpour Bahareh , Sinodinos Dimitrios , Armanfard Narges 
Published: August 2022

<p> Human activity recognition is a popular research field in computer vision that has already been widely studied. However, it is still an active research field since it plays an important role in many current and emerging real-world intelligent systems, like visual surveillance and human-computer interaction. Deep Reinforcement Learning (DRL) has recently been employed to address the activity recognition problem with various purposes, such as finding attention in video data or obtaining the best network structure. DRL-based human activity recognition has only been around for a short time, and it is a challenging, novel field of study. Therefore, to facilitate further research in this field, we have constructed a comprehensive survey on activity recognition methods that incorporate deep reinforcement learning. Towards the end of this survey, we summarize key challenges and open problems in this area that can be addressed by researchers in the future. </p>
UAV-Assisted-Smart Farming for Agricultural Monitoring in a Large Scale WSN area
Authors: Leranso Mesfin , Leng Supeng , Salau Ayodeji Olalekan , Fakirah Maged 
Published: August 2022

<p>With the aid of multiple autonomous unmanned aerial vehicles (UAVs), data collection from the large-scale Wireless Sensor Network (WSN) is a highly efficient, but challenging solution. In this paper, to minimize the total energy consumption of both UAVs, and the effective use of sink nodes' power, we optimize both the number of sink nodes and the trajectories of multiple UAVs in WSN. To do this, the UAV can start from the docking station and come back to the same dock station after the completion of the mission. To increase the lifetime WSN, we specifically use the Genetic Algorithm to choose the number of sink nodes. Then, we utilize a Deep Q-network-based method providing a Markov decision pr to establish all trajectory paths. We can show that our method can expedite the process of identifying the best answers by simulating its performance and contrasting it with other traditional heuristic benchmark techniques. </p>
Monolithic-3D Inference Engine with IGZO Based Ferroelectric Thin Film Transistor Synapses
Authors: De Sourav , Lederer Maximilian , Raffel Yannick , Lehninger David , Thunder Sunanda , Jank Michael P.M. , Ali Tarek , Kaempfe Thomas 
Published: August 2022

<p> Instigated by the plethora of data generated by edge devices and IoT devices, machine learning has become the de facto choice of everyone for solving many tasks. Applications such as intelligent healthcare monitoring systems, smart watches, or automatic cars require real-time processing of the data or image, which is done by machine learning algorithms with higher efficiency than humans. There are two possible methods for artificial intelligence?1. non-von-Neumann hardware-based implementation of neural networks 2. traditional computer science based approach for neural networks or traditional von-Neumann architecture?based implementation of neural networks The standard von-Neumann performance of neural networks, where the memory and computation parts are segregated, suffers from severe latency with increasing number of edge devices. However, the multitude of edge devices used in our daily life imposes strict restrictions on latency, device area, and power consumption for hardware. Therefore, we need to take the route beyond the CMOS-based mixed-signal implementation of neural networks, where the memory bandwidth is not limited by the quintessential von-Neumann archi?tecture. The primary motivation of present-day research on the non-von-Neumann computing architecture is to build dedicated hardware modules for implementing low-power, fast-computing units without affecting the recent trend of scaling. This chapter focuses on amorphous indium-gallium-zinc-oxide (α-IGZO) based and their system-level applications. Back-end-of-line (BEoL) compatible indium IGZO based multibit one-time programmable (OTP) ferroelectric thin film transistors (FeTFT) with lifelong retention capability were fabricated. The maximum temperature of the entire fabrication process was limited to 350oC. The gate-stack engineering by varying the thickness ratio of ferroelectric hafnium zirconium oxide (HZO) and IGZO layer fomented excellent data-retention capability and one time programming property. Further, we have evaluated the performance of IGZO-based FeTFT as synaptic devices for an inference engine. The system-level simulation revealed inference accuracy loss of only 1.5% after ten years without re-training for Modified National Institute of Standards and Technology (MNIST) hand-written digits in a multi-layer perceptron (MLP) neural network with a baseline of 97%. The proposed inference engine also showed superior energy efficiency and cell area of 95.33 TOPS/W (binary) and 8F2 , respectively. </p>
FDRL Approach for Association and Resource Allocation in Multi-UAV Air-To-Ground IoMT Network
Authors: Erbad aiman , Nahom Hayla , Albaseer Abdullatif , Abdallah Mohamed , Guizani Mohsen 
Published: August 2022

<p>In 6G networks, unmanned aerial vehicles (UAVs) can serve as aerial flying base stations (AFBS) with aerial mobile edge computing (AMEC) server capabilities. AFBS is an increasingly popular solution for delivering time-sensitive applications, extending network coverage, and assisting ground base stations in the healthcare systems for remote areas with limited infrastructure. Furthermore, the UAVs are deployed in the healthcare system to support the Internet of medical things (IoMT) devices in data collection, medical equipment distribution, and providing smart services. However, ensuring the privacy and security of patients' data with the limited UAV resources is a major challenge. In this paper, we present a federated deep reinforcement learning framework for resource allocation in UAV-enabled healthcare systems, where IoMT devices send their trained model parameters without transmitting sensitive raw data to the AMEC server. In the proposed framework, the IoMT device is associated with AFBS based on the quality of the data and its demand in order to maximize learning efficiency and accuracy. This work aims to minimize the computation costs of the IoMT devices while considering UAV resources and the fairness of UAV coverage. Simulation results prove that our proposed algorithm outperforms other baseline algorithms in learning accuracy and computational cost.</p>
Nurses on the Edge: An On-device Human Activity Recognition Framework that Optimizes the Sensor Placement
Authors: Konak Orhan 
Published: August 2022

<p>On-body Sensor-based Human Activity Recognition provides an excellent opportunity to monitor a person’s movement unobtrusively. This is commonly used to provide recommendations about physical activity and similar, while our main motivation was to streamline the time-consuming process of documenting nursing activities. In this paper we lay out the methodology for building activity recognition models, and present a mobile application that provides comprehensive support for it: from data acquisition and annotation, to on-device training and execution of activity recognition in real time. Furthermore, we developed a novel approach to determine the optimal sensor placement to achieve higher classification accuracy through real-time video data conversion into pose estimations. We demonstrate our systems’ various features in a feasibility study. For this purpose, we conducted a study with inertial sensors on nursing activities with ten subjects on 13 activities. We demonstrate that our vision-based approach for the optimal sensor placement achieved a high correspondence with a trained model. Furthermore, we achieved a higher accuracy for a multimodal and on-device trained model approach compared to a single-modality and offline variant. This evaluation showed that the system served essential support in a realistic environment. </p>
Effect of Dyadic Haptic Collaboration on Ankle Motor Learning and Task Performance
Authors: Kim Sangjoon J. , Wen Yue , Ludvig Daniel , Küçüktabak Emek Barış , Short Matthew R. , Lynch Kevin , Hargrove Levi , Perreault Eric J. , Pons José 
Published: August 2022

<p>Optimizing skill acquisition during novel motor tasks and (re)learning lost motor functions have been the interest of many researchers over the past few decades. One approach shown to accelerate motor learning is haptically coupling two individuals through robotic interfaces. Studies have shown that an individual’s solo performance of upper-limb tracking tasks may improve after haptically coupled training with a partner. In this study, our goal was to investigate whether these findings can be translated to lower-limb motor tasks, more specifically, during an ankle position tracking task. Using one-degree-of-freedom ankle movements, pairs of participants (i.e., dyads) tracked target trajectories while intermittently coupled through a virtual spring rendered between two ankle rehabilitation robots. We compared changes in task performance across trials while training with and without haptic coupling. We found that dyadic haptic coupling did not lead to faster individual learning of the tracking task. Dyadic task performance (i.e., tracking performance while haptically coupled) improved during haptic coupling, likely due to averaging of errors of the dyadic pair during tracking. These results suggest that haptic coupling between unimpaired individuals may not be an effective method of training ankle movements during a simple one-degree-of-freedom task.</p>
EDUCAÇÃO BASEADA NO DESENVOLVIMENTO DE COMPETÊNCIAS: DESAFIOS NO PROCESSO DE AVALIAÇÃO
Authors: Gerstenberger Rodolfo Ângelo Correia , Ramos de Andrade Maria de Fátima , Loutfi Silvana de Carvalho Arantes 
Published: August 2022

Neste artigo, apresenta-se um levantamento bibliográfico de dissertações e teses que tratam do processo de avaliação baseado no desenvolvimento de competências, no contexto do Ensino Técnico. Para tal, recorreu-se à Biblioteca Digital Brasileira de Teses e Dissertações (BDTD-IBICT), utilizando os seguintes descritores: avaliação, competências e Ensino técnico. O levantamento considerou as produções realizadas de 2010 até 2020, nas áreas de Ciências Humanas e Educação. Foram encontrados oito trabalhos relacionados ao objeto em estudo, e mais um trabalho de 2007, identificado antes do filtro dos 10 anos e que mantinha considerável relação com o tema aqui abordado. Após o estudo das pesquisas selecionadas, concluiu-se que dificuldades diversas ainda são encontradas pelos docentes em um processo avaliativo de formação por competências, o que denota a necessidade de maior aprofundamento nos estudos e processos que levem à formação contínua do docente
PERMANÊNCIA E ÊXITO DOS ESTUDANTES NO CURSO DE LICENCIATURA EM QUÍMICA VERSUS REPROVAÇÕES EM DISCIPLINAS INICIAIS
Authors: Feu Karla , Simmer Ana `Paula , P. Dardengo Raquel , D. L. Ferreira Bárbara 
Published: August 2022

O trabalho analisou as taxas de reprovação dos discentes em duas disciplinas introdutórias do curso de Licenciatura em Química, a Química Geral I e Fundamentos de Matemática Elementar, do Instituto Federal do Espírito Santo (IFES) - Campus Vila Velha. Trata-se de uma pesquisa quantitativa exploratória cujos dados foram obtidos do sistema acadêmico utilizado na instituição (Q-AcadêmicoⓇ) e dos questionários aplicados aos estudantes com matrículas ativas no curso, aprovados e reprovados nas disciplinas em foco nos semestres letivos de 2016 a 2019. Ao todo, 30 e 29 estudantes aprovados e 10 e 8 reprovados nas disciplinas de Química Geral I e Fundamentos de Matemática Elementar respectivamente responderam ao questionário construído na ferramenta Google Forms enviado por e-mail, no período de 09 de setembro a 09 de novembro de 2020. Os dados foram organizados e gráficos foram feitos com a utilização do software Excel. As disciplinas de Química Geral I e Fundamentos da Matemática Elementar apresentam altos índices de reprovação e os resultados comprovaram a nossa hipótese que a principal dificuldade é a falta dos conceitos fundamentais de Química e Matemática da educação básica. Em face dessa questão, algumas estratégias educacionais para o êxito nas disciplinas em estudo e a permanência no curso são apresentadas no presente artigo.
PENGEMBANGAN MEDIA INTERAKTIF BERBASIS ARTICULATE STORYLINE PADA PEMBELAJARAN IPA MATERI SISTEM TATA SURYA UNTUK MENINGKATKAN LITERASI SAINS
Authors: Supeno Supeno , Fitriani Dewi Kurnia , Wahyuni Diah , Rahayuningsih Rahayuningsih 
Published: August 2022

Penelitian ini bertujuan mengembangkan media pembelajaran interaktif berbasis Articulate Storyline pada materi sistem tata surya serta mengetahui validitas, kepraktisan dan efektivitas untuk meningkatkan literasi sains. Penelitian ini merupakan penelitian dan pengembangan (R&D) dengan mengadaptasi pengembangan 4-D. Tahapan dalam 4-D, antara lain: 1) Define, 2) Design, 3) Develop, 4) Disseminate namun pada penelitian ini hanya sampai pada tahap develop. Tahap define ini dilakukan untuk mengetahui kebutuhan yang diperlukan sehingga tahap ini dikenal dengan analisis kebutuhan. Tahap design dilakukan setelah mengetahui permasalahan yang berdasarkan analisis define kemudian peneliti mendesain peralatan yang digunakan seperti melakukan penyusunan tes mengacu pada analisis siswa yang kemudian disesuaikan dengan tingkat kemampuan kognitif siswa dan tujuan. Tahap develop terdiri dari dua tahap yaitu tahap validasi media dan tahap uji coba media interaktif yang dikembangkan. Validitas media memperoleh persentase sebesar 86% kriteria sangat valid. Kepraktisan dilakukan dengan menggunakan lembar keterlaksanaan dan memperoleh 100% kriteria sangat praktis. Efektivitas dilakukan dengan memberikan tes essay yang mengacu pada indikator literasi sains diujikan menggunakan N-Gain. Efektivitas media interaktif menggunakan N-Gain sebesar 0,57 dengan kriteria sedang.Kata Kunci: Articulate storyline, sistem tata surya; literasi sains
Peluang dan Tantangan : Bisnis di era disrupsi industri
Authors: Aprilia Annisa , Subiyantoro Subiyantoro 
Published: August 2022

Penelitian ini bertujuan untuk mendiskripsikan berbagai tantangan dan peluang bisnis yang akan dihadapi di era disrupsi industri. Penelitian ini mengguanakan pendekatan kualitatif dengan metode studi literatur, yakni mengumpulkan berbagai informasi menjawab rumusan masalah penelitian melaui berbagai sumber seperti buku-buku dan jurnal. Adapun yang menjadi rumusan masalah dalam penelitian ini yaitu: 1) Apa saja tantangan dan peluang bisnis di era disrupsi industri?; 2) Bagaimana strategi menghadapi tantangan dan peluang bisnis di era disrupsi industr?. Adapun hasil temuan penelitian adalah Era disrupsi industri mengubah cara hidup manusia yang fundamental, dari manual menjadi otomatisasi digitalisasi. Hal tersebut dapat memudahkan pekerjaan manusia menjadi lebih praktis, efektif dan efesien karena perkembangan teknologi. Namun kehadiran era disrupsi di waktu yang bersamaan juga dapat menjadi ancaman bagi pelaku industri. Pekerjaan yang dulu biasa dilakukan oleh manusia, kini diambil alih oleh mesin dan robot. Maka untuk mengadapi tantangan dan peluang tersebut diperlukannya sebuah strategi, yakni Trend Watching; Research, Risk Management, Inovation, Switching, Partnership, Change Managemen.
IMPLEMENTASI BLENDED LEARNING TERINTEGRASI STEM UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR KRITIS MAHASISWA
Authors: Maryam Isnaeni 
Published: August 2022

Latar belakang penelitian ini adalah mahasiswa banyak yang mengalami kesulitan pada saat pembelajaran online, hal tersebut menyebabkan tingkat berpikir kritis mahasiswa rendah. Penelitian ini bertujuan untuk meningkatkan kemampuan berpikir kritis mahasiswa melalui pembelajaran blended learning yang diintegrasikan dengan pendekatan STEM. Penelitian ini merupakan penelitian tindakan kelas. Subyek penelitian ini adalah kelas 4A Program Studi Pendidikan Matematika Universitas Muhammadiyah Purworejo Tahun ajaran 2021/2022. Obyek penelitian ini adalah keseluruhan pembelajaran menggunakan blended learning yang diintegrasikan dengan STEM. Kesimpulan dari penelitian ini adalah pembelajaran Blended Learning yang diintegrasikan dengan pendekatan STEM dapat meningkatkan kemampuan berpikir kritis mahasiswa kelas 4A pada mata kuliah Statistika Matematika. Mahasiswa mampu merumuskan pokok-pokok permasalahan, mengungkap fakta yang dibutuhkan dalam menyelesaikan suatu masalah, memilih argumen argument logis, relevan, dan akurat, mendeteksi bias berdasarkan sudut pandang yang berbeda, serta menentukan akibat dari suatu pernyataan yang diambil sebagai suatu keputusan.Kata Kunci: Blended Learning; STEM; berpikir kritis
Membangun Karakter Anak Usia Dini melalui Buku Cerita Bergambar
Authors: Azis Kholil , Sunardi Sunardi , Subhan Yan Ardian 
Published: August 2022

Pendidikan karakter pada anak usia dini adalah sesuatu yang mutlak harus diajarkan kepada setiap anak agar nantinya mereka memiliki karakter yang tangguh dan bisa bersaing ditengah-tengah arus globalisasi dan digitalisasi dewasa ini. Pendidikan karakter sesungguhnya telah diajarkan kepada anak usia dini mulai dari tingkat PAUD atau TK hingga tingkat perguruan tinggi. Terdapat indikasi bahwa kesadaran masyarakat akan pentingnya pembelajaran pembentukan karakter anak juga masih minim, diakibatkan banyak kalangan masyarakat juga masih banyak yang belum mendapatkan akses pembelajaran yang cukup memadai di sana sini masih banyak kendala dan hambatan dalam pembelajaran. Tujuan kegiatan pengabdian ini adalah memberikan pengajaran dan pembimbing pembentukan karakter dengan menggunakan dengan metode buku storytelling cerita fabel bergambar berbahasa Inggris di PAUD-TK Arimbi Tangerang Selatan. Lewat narasi dan penceritaan, siswa-siswi PAUD mengenal beragam kosa kata yang merujuk pada karakter atau sifat-sifat yang baik mengenai kejujuran, kesopanan, rajin belajar, menghormati Guru dan lain sebagainya.
IDENTIFIKASI HAMBATAN PENYELESAIAN STUDI BAGI MAHASISWA PGSD PENJAS
Authors: Hermawan Hedi Ardiyanto 
Published: August 2022

Mahsiswa PGSD Penjas FIK UNY dalam menyelesaikan studi selama ini rata-rata 4 tahun 6 bulan. Penelitian ini dilakukan untuk tujuan mengetahui hambatan mahasiswa PGSD Penjas FIK UNY dalam menyelesaikan studi tepat waktu (4 tahun atau kurang dari 4 tahun). Jenis penelitian ini adalah campuran (deskriptif kuantitatif dan kulitatif). Populasi dalam penelitian ini mahasiswa PGSD Penjas FIK UNY sebanyak 120 orang. Sampel yang digunakan pada penelitian ini berjumlah 91 orang. Teknik penarikan sampel yang dilakukan dengan cara random sampling. Instrumen yang digunakan dalam pelitian ini adalah angket tertutup dan terbuka. Teknik analisis datanya mengunakan statistik deskriptif dan secara kualitatif. Hasil penelitian secara deskriptif kuantitatif diperoleh sebagai berikut, yaitu: hambatan sangat kurang 55 mahasiswa (60,44%), hambatan kurang 32 mahasiswa (35,16%), dan hambatan sedang 4 mahasiswa (4,40%). Hasil penelitian secara kulitatif ada 4 kesimpulan terkait hambatan untuk menyelesaikan kuliah tepat waktu, yaitu 1) mahasiswa takut praktik renang sehingga tidak lulus renang, 2) pada masa pendemi Covid-19 ini banyak mahasiswa mengalami masalah dalam mencari referensi buku untuk menulis proposal penelitian, 3) beberapa materi kuliah teori terkait penyusunan tugas akhir seperti statistik dan metodologi penelitian yang disampaikan secara daring kurang dikuasi dan dipahami oleh mahasiswa, dan 4) kurang lengkapnya fasilitas yang ada di kampus Wates menyebabkan kurang efektifnya proses perkuliahan sehingga ilmu yang didapat kurang maksimal. Sebagai contoh tidak adanya lapangan basket dan alat olahraga yang tidak lengkap sehingga banyak bagian yang terlewatkan.