Miracle-dz/UniFAR-FTUs huggingface dataset:
PENGUKURAN KUALITAS LAYANAN PADA JASA PENGIRIMAN BARANG BERDASARKAN PERSEPSI PELANGGAN DENGAN METODE SERVPERF DAN IMPORTANCE PERFORMANCE ANALYSIS

Penilaian kualitas pelayanan berbeda dengan penilaian terhadap suatu produk, terutama karena sifatnya yang tidak nyata (intangible) dan produksi serta konsumsi berjalan secara simultan. Pada era pandemi Covid 19 tidak dapat dipungkiri bahwa jasa pengiriman barang sangat dibutuhkan dalam proses transaksi barang karena sering kali kita melakukan pembelian barang melalui e commerce. Dalam pengiriman barang yang tidak tepat waktu dapat menyebabkan terlambatnya penyampaian barang. Hal inilah yang menyebabkan konsumen kurang puas dalam pelayanan jasa pengiriman barang. Kualitas layanan jasa yang diberikan akan mempengaruhi tingkat kepuasan konsumen, semakin baik kualitas jasa maka konsumen akan semakin puas. Penelitian ini bertujuan untuk mengukur kualitas layanan dengan berdasarkan persepsi dari pengguna layanan dengan menggunakan metode SERVPERF dan IPA. Metode Importance Performance Analysis (IPA) menggunakan bobot persepsi dan bobot kepentingan serta presentase tingkat kesesuaian dalammenentukan prioritas utama dalam upaya meningkatkan kepuasan pelayanan yang diberikan. Dari hasil penelitian didapatkan bahwa dimensi timelineness sudah memuaskan pelanggan tetapi pihak penyedia layanan harus tetap memperhatikan atribut layanan yang masuk dalam prioritas perbaikan pada kuadran IPA.
The Effect of Socio-Economic Status on Food Quality in West of Iran

BackgroundSocio-economic status affects many health-related outcomes and one of the most important factors is the pattern and quality of nutrition. Thus, this study is carried out to investigate the effect of socio-economic status on the quality of nutrition based on healthy Eating Index (HEI). MethodsThis is a population-based study using the baseline data from Ravansar Non-Communicable Disease cohort study. HEI calculated from Food Frequency Questionnaire. The quality of nutrition was assessed based on HEI-2015 which evaluates 13 food groups.ResultsThe mean of age of the participants was 48.02 (SD = ±8.27) years. The median and mean of HEI in the studied population were 53 and 53.69 (SD = ±7.34), respectively. Women, the educated, city dwellers, people of higher socioeconomic classes, and non-smokers had greater odds of having higher quality of nutrition. The worst score among all components of HEI were for the refined grains and then the whole grain, and the highest score was obtained for the tatal protein foods. ConclusionsDue to low nutritional quality and its adverse effects, especially in people with low socioeconomic status and villagers, the quality of nutrition, especially in the poor, should be promoted with proper interventions so as to reduce disparity in the society.
Techniques to Reduce The Computational Cost of Finite Element Models of the Lower Limb Muscles

Modeling the lower limb muscles using the Finite Element (FE) method is required for various applications including injury mechanisms or when stress/strain distribution in the muscle is of interest. When the muscles are represented with 3D FE models, the interaction between the muscles can be taken into account that has an effect on their force production. However, the computational cost of such a method is considerably high. Besides, in many cases, a major part of this computational cost is committed to gain unnecessary information. For instance, when having two FE muscles in contact, both muscles need to get finely meshed to conserve their surface details even if having the stress/strain distribution inside one of the two muscles is not required. As a result, the current study aims to explore a model reduction technique based on mesh embedding to decrease the computational cost of such models. A combination of Computerized Tomography and Magnetic Resonance Imaging (MRI) data obtained from a volunteer subject was used to generate a musculoskeletal model of the quadriceps muscle group. The modeling process was performed in ArtiSynth which is an opensource 3D modeling platform supporting combined simulation of multibody and finite element models. This platform allows the attachment of a passive embedded mesh to a FE body so that it deforms in accordance with the motion of the FE body. Considering that the external forces applied to the passive mesh can be propagated back to the FE body attached to it, contact can be defined between the embedded mesh and any other structure. A full and a reduced model are generated and are used to simulate a passive deep knee flexion to test the reliability of the method. The kinematic outcomes are compared against data points obtained from MRI at different flexion angles. The results show that the proposed methodology can be considered as a substitute to fully FE models without a substantial sacrifice on the outcomes despite having lower computational cost.
Cognitive Instrumental Processes of Flipped Learners: Effects of Relevance for Learning, Quality of Learning Outcomes, and Result Demonstrability

This study investigated the influence of students’ cognitive instrumental processes (i.e., relevance for learning, the quality of learning outcomes, and result demonstrability) on students’ perceived usefulness and intention to use flipped learning. An extension of the technology acceptance model (TAM2) was employed in this study. A total of 277 undergraduate students enrolled in flipped classes at a Korean university completed an online survey for this study. The results of the cognitive instrumental processes revealed that the quality of learning outcomes influenced students’ perceived usefulness and intention to use flipped learning. This finding emphasizes that it is necessary to deliver high-quality classes using a flipped learning approach to satisfy students’ expectations of improving learning outcomes. The relevance for learning also affected students’ perceived usefulness of flipped learning classes and indirectly influenced their future intention to use flipped learning. The results emphasize that students should be given opportunities to recognize the relevance of flipped learning based on their expected learning achievement. Finally, result demonstrability did not influence perceived usefulness nor intention to use flipped learning. The research findings of this study have practical implications and recommendations for flipped class instructors to persuade students to enroll in flipped learning courses from the perspective of cognitive instrumental processes.
Embracing Stochasticity to Enable Neuromorphic Computing at the Edge

Editor’s notes: This article discusses emerging nano-devices—resistive RAMs and spintronics—and their use in future neuromorphic systems. The authors discuss construction of stochastic neurons and synapses and their use for (supervised and unsupervised) learning and inference. —John Hayes, University of Michigan
Microbiological screening of tobacco raw materials for rolling of cigarettes

In the modern market of tobacco products worldwide, there is a trend towards increased consumption and trade in cut tobacco for manual rolling of cigarettes (RYO tobacco), including and from unregulated producers. This hides additional risks for the health of the consumers due to the possibility to use low-quality and uncontrolled raw materials, including and with increased presence of pathogenic and conditionally pathogenic microorganisms. The aim of the study was to determine the total amount of heterotrophic bacteria (microbial count), the amount of microscopic fungi and the most common species in the raw material for tobacco RYO, distributed on the Bulgarian market. The microbiological analyzes were performed by classical methods accepted in sanitary microbiology. In all samples, spores of the genus Bacillus showed mass development, and according to the macro-morphological characteristics of the colonies, the predominant species can be attributed to B. cereus. The detected amounts of microscopic fungi in the tested tobacco mixtures were significant at strong presence of species of the genus Aspergillus, over 85.48%. Macroscopically, species were defined as A. flavus (41.94%), A. niger (27.42%) and A. fumigatum (16.13%). The relative share of species of the genus Penicillium was 9.68% and of species of the genus Mucor -4.84%. The studied tobacco raw material for manual rolling of cigarettes had significant contamination by microorganisms that had the rank of pathogens. Quantitative microbial assessment suggests a potential health risk for consumers.
Analysis of Popularity Sentiment in Opinion Presidential Election 2019 on Twitter

Presidential Election (Pilpres) 2019 which has been passed on 17 April 2019 which is being widely discussed in cyberspace, electronics and social media, one of them is on Twitter. Before the voting, there were many opinions and opinions about the 2019 presidential candidates who had their respective advantages, one that could be relied on in terms of popularity. Social media is one place for an effective and efficient campaign but raises many good, positive and negative opinions. In this study, it is expected to be able to see opinions in the community that contain positive and negative sentiments.
Municipal Response to Fiscal and Governance Reforms: Effects of Stricter Debt Limits across Jurisdictions

ABSTRACT The effectiveness of fiscal rules in limiting governmental indebtedness and expenditures has mixed results. This inconclusiveness may suggest debt-limit effects on fiscal outcomes may be moderated by other factors. Although literature has addressed the moderating effects government size has on fiscal outcomes, scarce research has done so with the type of jurisdictions making up a unit of government. Consequently, this study tests whether the type (e.g., urban and rural vs. urban) of administrative jurisdictions moderates the effect of debt limits on municipal debt and spending. Results confirm that municipalities with different types of jurisdictions increase both level of indebtedness and investment expenditure, despite a stricter debt limit being in place.
GCN2CDD: A Commercial District Discovery Framework via Embedding Space Clustering on Graph Convolution Networks

Modern enterprises attach much attention to the selection of commercial locations. With the rapid development of urban data and machine learning, we can discover the patterns of human mobility with these data and technology to guide commercial district discovery. In this article, we propose an unsupervised commercial district discovery framework via embedding space clustering on graph convolution networks to solve the problem of commercial district discovery. Specifically, the proposed framework aggregates human mobility features according to geographic similarity by graph convolution networks. Based on the graph convolution network embedding space, we apply hierarchical clustering to mine the latent functional regions hidden in different human patterns. Then, with the kernel density estimation, we can obtain the semantic labels for the clustering results to discover commercial districts. Finally, we analyze the multisource data of the Xiaoshan District and Chengdu City, and experiments verify the effectiveness of our framework.
Identifying build orientation of 3D‐printed materials using convolutional neural networks

The advent of additive manufacturing (AM) processes brought with it intense research into various materials and manufacturing processes. At the same time, the need for validation of material properties, as well as study and forecasting of aging, has arisen. Modern imaging techniques, like X‐ray computed tomography (XCT), are a convenient vehicle for such studies; however, the large datasets they produce require novel analysis techniques to efficiently extract critical information. In this paper, we present our work on developing a 3D extension of the ResNet architecture to distinguish between two build orientations of tensile bars produced by AM. Using only information from XCT, our method achieves a 99.3% correct classification at a misidentification of 1%.
Locally Played: Real-World Games for Stronger Places and Communities [Book Review]

Locally Played: Real-World Games for Stronger Places and Communities by Benjamin Stokes is a necessary title for all games scholars, one that illuminates the complications of integrating social games into various localities in order to drive community outreach and engagement. One vital addition it makes to gaming scholarship in the 21st century is the application of design principles and systems to existing urban infrastructures, linking various neighborhoods through the power of play. Networks can be strengthened through play, and Stokes points out how understanding the network in the first place can be used to create the game. The relationship between play and space is illustrated here.
Entropy Field Decomposition Based Outage Detection for Ultra-Dense Networks

—Ambitious quality of experience expectations from 5G mobile cellular networks have spurred the research towards ultra-dense heterogeneous networks (UDHNs). However, due to coverage limitations of millimeter wave cells and lack of coverage data in UDHNs, discovering coverage lapses in such 5G networks may become a major challenge. Recently, numerous studies have explored machine learning-based techniques to detect coverage holes and cell outages in legacy networks. Majority of these techniques are susceptible to noise in the coverage data and only characterize outages in the spatial domain. Thus, the temporal impact of an outage, i.e., the duration of its presence remains unidentiﬁed. In this paper, for the ﬁrst time, we present an outage detection solution that characterizes outages in both space and time while also being robust to noise in the coverage data. We do so by employing entropy ﬁeld decomposition (EFD) which is a combination of information ﬁeld theory and entropy spectrum pathways theory. We demonstrate that compared to other techniques such as independent component analysis and k-means clustering, EFD returns accurate detection results for outage detection even in the presence of heavy shadowing in received signal strength data which makes it ideal for practical implementation in emerging mobile cellular networks.
Learning Analytics in the Monitoring of Learning Processes

During the last few years, learning analytics (LA) has gained the interest of researchers in the field of education. Generally, LA is related with the development of methods that use educational data sets to support the learning process. Therefore, there is a need understanding how learners, educators, and institutions can best support this process. Thus, a framework is presented that tries to extend the collaborative three-dimensional virtual environments for educational by integrating a LA tool. The aim is to help the teacher to monitor and evaluate the students' learning process in these types of environments. It is the intention include a (1) comprehensive analysis of the currently available LA tools for educational, (2) design of a user-centered framework based the requirements gathered from the analysis, and (3) thorough evaluation of framework to allow identify possible behavior patterns of students within the environment, related to your preferences for materials and expertise.
Application of Exposure Plus Response Prevention for Obsessive Compulsive Disorder Related to Pediatric Acute-Onset Neuropsychiatric Syndrome

ABSTRACT Pediatric obsessive-compulsive disorder (OCD) often produces significant and chronic impairment for patients and their families. A subset of youths with OCD experience rapid-onset, severe OCD symptoms with multiple co-occurring neuropsychiatric problems, motor/sensory impairments, and dietary restrictions temporally linked to infectious disease, termed pediatric acute-onset neuropsychiatric syndrome (PANS). Although medical treatment for youths in this clinical subgroup has gained attention in recent years, literature detailing the evidence-based psychological treatment of such cases remains sparse. We describe the application of exposure plus response prevention (ERP), a cognitive-behavioral approach with extensive research support for pediatric and adult OCD, for a pediatric patient who presented for treatment with a multidisciplinary team of infectious disease, psychiatry, and psychology. This case report details the flexible application of ERP, as guided by a social-ecological framework wherein the patient, family, and broader community were all integral to treatment. This case study emphasizes the importance of future research on PANS-suspected pediatric OCD cases, as well as the utility of flexible application of ERP, guided by an ecological framework.
Mass and Charge Transport in Hydrated Polymeric Membranes

Mass and charge transport through hydrated polymer membranes has significant importance for many areas of engineering and industry. Multi-scale modeling and simulation techniques were used to study transport in relation to two specific membrane applications: (1) food packaging and (2) additives for polymer electrolytes. Chitosan/chitin films were studied due to their use as a sustainable, biodegradable food packaging film. The effects of hydration on the solvation, diffusivity, solubility, and permeability of oxygen molecules in these films were studied via molecular dynamics and confined random walk simulations. With increasing hydration, the membrane was observed to have a more homogeneous water distribution with the polymer chains being fully solvated. Insight from this work will help guide molecular modeling of chitosan/chitin membranes and experimental synthesis of these membranes, specifically highlighting efforts to chemically tailor chitosan membranes to favor discrete as opposed to continuous aqueous domains to help reduce oxygen permeability. Additives for proton exchange membranes (PEMs) were studied to aid in the developing next-generation membrane materials for fuel cell applications. We calculate and present predictions of our analytical model that describes the fundamental relationship between the nanoscale structure of PEMs and their proton conductivity using a set of structural descriptors, accounting for nanopore size, functionalization and connectivity in order to predict proton conductivities in PEMs. The model reproduces experimentally determined conductivities in two current PEM materials. To extend the model based on structural descriptors of PEMs, we studied polyethylene glycol (PEG), a polymer used in electrochemistry applications due to it hydrophilicity and pH-dependent behavior in aqueous environments. We conducted ab initio molecular dynamics simulations of an excess proton in bulk water and aqueous triethylene glycol (TEG) solution and reactive molecular dynamics simulations of an excess proton in bulk water, aqueous TEG solution, and aqueous PEG solution. We determined differences in protonic defect structures, kinetics, thermodynamics, and hydrogen-bond networks associated with structural diffusion between systems. Driving forces for polymeric membrane design goals include economics, efficiency, energy consumption and sustainable production. Insight from this work hopes to aid in determining key design parameters and reduce time-to-discovery for developing next-generation polymeric membranes.
Analisis Komparasi Penerapan Virtual Local Area Network Pada Software Defined Network

Industri telekomunikasi dengan skalabilitas yang tinggi tentunya sangat membutuhkan prototipe teknologi jaringan untuk dapat bekerja secara terpusat di berbagai kondisi ekosistem jaringan. Melalui teknologi Virtual Network yaitu VLAN yang dapat mendedikasikan perangkat jaringan tersendiri yang secara fisik terletak pada satu struktur jaringan yang logis. Tujuan dari peneilitan ini adalah untuk menganalisis implementasi VLAN pada lingkungan Software Defined Networking (SDN). Beberapa tipe controller dievaluasi menggunakan metrik jaringan seperti throughput, jitter, latency dan packet delivery ratio yang memanfaatkan Openflow sebagai protokol komunikasi yang menghubungkan bidang kontrol dan bidang data. Peneliti memfokuskan untuk mengevaluasi kemampuan controller SDN Opendaylight, floodlight, ONOS, POX dan Ryu pada Openflow stream forwarding yang dapat memasang dan menghapus header VLAN. Hasil pengujian skenario yang diusulkan menunjukkan bahwa semua jenis controller dapat berjalan dengan baik dengan memberikan instruksi ke lapisan forwarding yang dilewati paket data saat dikirimkan. Melalui pengujian konektivitas dan parameter metrik jaringan, karakteristik controller yang diharapkan dan direkomendasikan adalah controller yang berjalan pada bahasa pemrograman Java. Performa dan modularitas yang tinggi sebagai keunggulannya, fitur yang memadai, meskipun lebih sulit untuk dipahami dibandingkan dengan yang berjalan pada berbasis python. Controller jaringan SDN seperti ONOS mendapatkan hasil yang signifikan dalam proses pengiriman data aktual dengan nilai rata-rata nilai throughput 13.570 kbps. Sedangkan Opendaylight menunjukkan persentase delivery ratio yang stabil untuk semua skenario pengiriman data
Strukturänderungen von Cellulose durch Alkalibehandlung : physikalische und chemische Beurteilungsmethoden

Eight technical chemical pulps inclusive of linters were treated with caustic soda lye of increasing concentration (up to 50%). The assessment of the resulting structural alterations was by means of IR spectroscopy, X-ray diffraction and by determination of water and lye retention values, also by measuring the level-off DP values. The results showed a.o. that the grid change, cellulose I to cellulose II, can be satisfactorily characterized with the IR index 1370/670, giving the relation of the peak surfaces at 1370 and 670 cm -1 .
The Effect of Video Imagery Training on Soccer Skills Performance of High School Players

This study evaluated the effect of PETTLEP video imagery onreactive motor skill test (Total RMST time, sprint time, reactive agility time, passing time, and passing accuracy) among 32 Malaysian high school soccer players (mean age of 15.31±1.83) who were randomly assigned into an experimental group (N:16) and a control group (N:16). A pre-test-post-test design was used to evaluate the effect of the intervention on the high schoolplayers' soccer skill performance. The experimental group received 10-minute PETTLEP video imagery trainingbefore their regular soccer training for eight weeks in addition to their regular soccer training, while thecontrol group only attended their regular soccer training. The data analysis revealed a significant effect of video imagery training on players' performance in the experimental group. The results showed that total RMST time, reactive agility time, passing time, and passing accuracy were statistically different within the experimental group F(15, 154.993)= 14.440, p = < . 001, Wilks' Λ = . 050 and between groups F(5, 56.00)=379.774, p = < . 001, Wilks' Λ = . 050 after receiving the training, except for the sprint time which was not significant. The findings of this study provide evidence that eight weeks ofPETTLEPvideo imagery training interventioncan significantly improve soccer players' total RMST time, reactive agility time, passing time, and passing accuracy. These findings could be integrated into training programs by coaches and players in order to improve the performance of different soccer skills among high school players.