Reversible moisture damage in asphalt mixture

A moisture damage has been one of the major concerns for HMA pavement by loss of adhesion between asphalt binder and aggregate surface or loss of the cohesion within asphalt binder due to action of water. Water is the one of major contributor towards the damage of asphalt pavement. The aim of this research is to evaluate the effects of moisture damage toward the performance of asphalt mixture under different conditions (dry, wet and dry back). The specimens were conditioned in accordance to ASTM D4867 to achieve desire saturation level up to 80% and then immersed in water for different soaking period to simulate flooding scenario. Indirect Tensile strength and Resilient modulus tests were performed on moisture conditioned specimens at regular interval (1, 3 and 5 days). After 5 days testing specimens were stored at room temperature for another 5 days to dry and were tested again to determine the recoverability of moisture damage. The results from this study indicated that tensile strength and modulus gradually decreased with the increasing of conditioning period, and upon drying at certain period specimens recovered 82% and 76% of initial ITS and Resilient modulus respectively. The results suggested that moisture damage in asphalt mixture tested is reversible

PEMBELAJARAN BERBASIS PRAKTIK: PEMBUATAN SABUN CUCI TANGAN SEBAGAI BENTUK KEMANDIRIAN DAN BERPIKIR KRITIS PESERTA DIDIK SD NEGERI 2 SEMANGKAK

Pembelajaran merupakan kegiatan yang terjadi dikarenakan adanya interaksi antara guru atau pengajar dengan peserta didik pada suatu lingkungan belajar. Banyak guru atau pendidik yang berlomba-lomba memberikan bermacam-macam jenis strategi pembelajaran yang kreatif yang menunjang suatu sistem kegiatan belajar dan mengajar di kelas. Dari banyaknya strategi pembelajaran yang ada, pembelajaran berbasis Praktik atau eksperimen diyakini dapat membuat level pemahaman peserta didik lebih optimal. Tujuan dari pengabdian ini adalah melakukan sebuah terobosan baru dalam melaksanakan pembelajaran yang ada di SD Negeri 2 Semangkak, Kabupaten Klaten, Jawa Tengah. Hal baru yang dibawa oleh penulis dan tim merupakan penggunaan sistem pembelajaran berbasis praktik atau eksperimen dapat membuka jalan untuk menjadi pribadi yang mandiri dan memiliki gaya berpikir yang kritis melalui kegiatan praktik membuat sabun cuci tangan

Effectiveness of Tympanic Thermometry for diagnosing Acute Otitis Media

Background: Acute Otitis Media (AOM) is a common upper respiratory tract infection (URTI) in children and usually presents with fever and otalgia. AOM is characterized by congested tympanic membrane and possible increase in temperature, which might be picked up by infrared tympanic thermometry. The objective of this study was to compare the temperature difference of tympanic membrane of affected ear with the unaffected ear and axilla in unilateral acute otitis media, and compare it with the control group.Material and Methods: This case control study comprised of 200 cases of both genders, aged up to 5 years. They were divided into two groups; Group A included 100 clinically diagnosed cases of acute otitis media (AOM), who reported in the ENT Outpatient Department (OPD) and Group B included 100 controls who presented in General Filter Clinic with no ear complaints. Cases with chronic ear disease, ear discharge, and use of local drugs including ear drops, impacted ear wax, tragal tenderness and congenital malformations of the ear were excluded by taking a detailed history. Clinical examination including otoscopy by an expert was done before subjecting patients to axillary and tympanic thermometry measurements and data recording. Data was collected and tabulated using Microsoft Excel Worksheet and analyzed by SPSS 16. Qualitative data like gender were presented as percentage and ratio, while means and standard deviation were calculated for the quantitative data. Difference between the means of experimental and control groups were analyzed by independent sample t-test and P value of less than or equal to 0.05 was taken as significant.Results: This study included 100 cases of unilateral AOM and 100 normal controls without AOM. In patients with AOM, the mean temperature difference between the affected ear and axilla was 1.41ºF as compared to 0.075ºF in controls (p=0.026). While the mean temperature difference between the affected ear and other ear was 0.65ºF as compared to 0.19ºF in controls (p=0.069).Conclusion: In acute otitis media, the temperature of affected ear is significantly higher than axilla but was not significantly higher than the other ear. The finding may help establish thermometry as a diagnostic tool in clinics manned by doctors not competent to do otoscopy

PENGARUH INOVASI PRODUK DAN KUALITAS PRODUK TERHADAP KEPUTUSAN PEMBELIAN SEPATU FUTSAL MEREK SPECS DI KOTA TEGAL

ABSTRAK M. Arfat Maulana. “PengaruhInovasi Produk dan Kualitas Produk Terhadap Keputusan Pembelian Sepatu Futsal Merek Specs di Kota Tegal”.Skripsi.Tegal.FakultasEkonomiUniversitasPancasaktiTegalTahun 2019. Penelitian ini bertujuan untuk mengetahui : 1) pengaruh inovasi produk terhadap keputusan pembelian sepatu futsak merek Specs di Kota Tegal. 2) pengaruh kualitas produk terhadap keputusan pembelian sepatu futsal merek Specs di Kota Tegal. Metodepengumpulan data yaitukesioner.Sedangkanmetodeanalisis data danujihipotesismenggunakananalisiskorelasi rank spearman, ujisignifikansikoefisienkorelasi rank spearnan, analisiskorelasiberganda, ujisignifikansikoefisienkorelasiberganda, danujikoefisiendeterminasi. Hasil penelitian menunjukan bahwa : 1) inovasi produk berpengaruh signifikan terhadap keputusan pembelian. Hal ini dibuktikan dengan diperolehnya rsxy sebesar 0,763 dan nilai Zhitung > Ztabel yaitu 7,584 > 1,96. 2) kualitas produk berpengaruh positif dan signifikan terhadap keputusan pembelian. Hal ini dibuktikan dengan diperolehnya nilai rsxy sebesar 0,752 dan Zhitung > Ztabel yaitu 7,747 > 1,96. 3) terdapat pengaruh yang signifikan inovasi produk dan kualitas produk secara bersama-sama terhadap keputusan pembelian. Hal tersebut dibuktikan dengan diperolehnya hasil korelasi berganda (R) sebesar 0,782, dengan nilai Fhitung sebesar 76,346 > Ftabel 3,94. Dan hasil koefisien determinasi (R2) sebesar 61,15% sedangkan 38,85% dipengaruhi oleh faktor lain. Kata Kunci : Inovasi Produk , Kualitas Produk, dan Keputusan Pembelian ------------------------------------------------------ ABSTRACT M. Arfat Maulana. "The Effect of Product Innovation and Product Quality on Purchasing Decisions of Specs Brand Futsal Shoes in Tegal City". Thesis. Tegal. Faculty of Economics, University of Pancasakti Tegal in 2019. This study aims to determine: 1) the effect of product innovation on purchasing decisions for Specs brand futsak shoes in Tegal City. 2) the effect of product quality on the decision to buy Specs brand futsal shoes in Tegal City. The data collection method is questionnaire. While the method of data analysis and hypothesis testing using Spearman rank correlation analysis, the significance test of Spearnan rank correlation coefficients, multiple correlation analysis, the significance test of multiple correlation coefficients, and the coefficient of determination test. The results showed that: 1) product innovation had a significant effect on purchasing decisions. This is evidenced by obtaining an rsxy of 0.763 and a value of Zhitung> Ztable which is 7.584> 1.96. 2) product quality has a positive and significant effect on purchasing decisions. This is evidenced by obtaining a rsxy value of 0.752 and Zhitung> Ztable which is 7.747> 1.96. 3) there is a significant influence of product innovation and product quality together on purchasing decisions. This is evidenced by obtaining the results of multiple correlation (R) of 0.782, with a Fcount value of 76.334> Ftable 3.94. And the results of the coefficient of determination (R2) of 61.15% while 38.85% is influenced by other factors. Keywords: Product Innovation, Product Quality, and Purchasing Decision

Internet of Things (IoT) Assisted Context Aware Fertilizer Recommendation

An accurate amount of fertilizer according to the real-time context is the basis of precision agriculture in terms of sustainability and profitability. Many fertilizers recommendation systems are proposed without considering the real-time context in terms of soil fertility level, crop type, and soil type. The major obstacle in developing the real-time context-aware fertilizer recommendation system is related to the complexity associated with the real-time mapping of soil fertility. Furthermore, the existing methods of determining the real-time soil fertility levels for the recommendation of fertilizer are costly, time-consuming, and laborious. Therefore, to tackle this issue, we propose a machine learning-based fertilizer recommendation methodology according to the real-time soil fertility context captured through the Internet of Things (IoT) assisted soil fertility mapping to improve the accuracy of the fertilizer recommendation system. For real-time soil fertility mapping, an IoT architecture is also proposed to support context-aware fertilizer recommendations. The proposed solution is practically implemented in real crop fields to assess the accuracies of IoT-assisted fertility mapping. The accuracy of IoT-assisted fertility mapping is assessed by comparing the proposed solution with the standard soil chemical analysis method in terms of observing Nitrogen (N), Phosphorous (P), and Potassium (K). The results reveal that the observations by both methods are in line with a mean difference of 0.34, 0.36, and −0.13 for N, P, and K observations, respectively. The context-aware fertilizer recommendation is implemented with the Logistic Regression (LR), Support Vector Machine (SVM), Gaussian Naïve Bayes (GNB), and K-Nearest Neighbor (KNN) machine learning models to assess the performance of these machine learning models. The evaluation of the proposed solution reveals that the GNB model is more accurate as compared to the machine learning models evaluated, with accuracies of 96% and 94% from training and testing datasets, respectively.©2022 Authors. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/fi=vertaisarvioitu|en=peerReviewed

Tension Pneumothorax During Apnea Testing for the Determination of Brain Death

The apnea test (AT) is considered as the ‘condition sinequa non’ by most of the intesivists for determiningbrain death (BD) as it provides an importantinformation for a definitive loss of brainstem function.It is the most difficult clinical test in BD protocols andis also potentially harmful and lengthy. The possiblecomplications of this test include severe decrease inblood pressure, pneumothorax, excessive CO2 retention,hypoxia, acidosis, and cardiac arrhythmia or asystole.It is important to abort the test in the setting of any ofthe above mentioned complication, which willcompromise BD diagnosis. It is important to ensurethat certain prerequisites are satisfied before the AT iscarried out. These include body temperature 32°C ormore, normal PO2 or preoxygenation to obtain anarterial PO2 ≥ 200 mmHg, arterial PCO2 orPaCO2 normal or above 40 mmH, blood pH normal orin the low basic range, pretest systolic blood pressureof at least 90 mmHg, Euvolemia or a positive fluidbalance during the previous 6 hours, no drug that canparalyze the respiratory muscles. If continuous orintermittent oxygen supply is preceded by decreasingnitrogen levels of blood gases, high PaO2 levels can bemaintained for very long periods of time.Preoxygenation removes alveolar nitrogen stores andhelps oxygen transport. There are several techniquesfor ascertaining that there is sufficient oxygenationduring AT .1-

Dual-3DM3-AD : Mixed Transformer based Semantic Segmentation and Triplet Pre-processing for Early Multi-Class Alzheimer’s Diagnosis

Alzheimer’s Disease (AD) is a widespread, chronic, irreversible, and degenerative condition, and its early detection during the prodromal stage is of utmost importance. Typically, AD studies rely on single data modalities, such as MRI or PET, for making predictions. Nevertheless, combining metabolic and structural data can offer a comprehensive perspective on AD staging analysis. To address this goal, this paper introduces an innovative multi-modal fusion-based approach named as Dual-3DM3-AD. This model is proposed for an accurate and early Alzheimer’s diagnosis by considering both MRI and PET image scans. Initially, we pre-process both images in terms of noise reduction, skull stripping and 3D image conversion using Quaternion Non-local Means Denoising Algorithm (QNLM), Morphology function and Block Divider Model (BDM), respectively, which enhances the image quality. Furthermore, we have adapted Mixed-transformer with Furthered U-Net for performing semantic segmentation and minimizing complexity. Dual-3DM3-AD model is consisted of multi-scale feature extraction module for extracting appropriate features from both segmented images. The extracted features are then aggregated using Densely Connected Feature Aggregator Module (DCFAM) to utilize both features. Finally, a multi-head attention mechanism is adapted for feature dimensionality reduction, and then the softmax layer is applied for multi-class Alzheimer’s diagnosis. The proposed Dual-3DM3-AD model is compared with several baseline approaches with the help of several performance metrics. The final results unveil that the proposed work achieves 98% of accuracy, 97.8% of sensitivity, 97.5% of specificity, 98.2% of f-measure, and better ROC curves, which outperforms other existing models in multi-class Alzheimer’s diagnosis.© 2024 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/fi=vertaisarvioitu|en=peerReviewed

Joint delay and energy aware dragonfly optimization-based uplink resource allocation scheme for LTE-A networks in a cross-layer environment

The exponential growth in data traffic from smart devices has led to a need for highly capable wireless networks with faster data transmission rates and improved spectral efficiency. Allocating resources efficiently in a 5G communication system with a huge number of machine type communication (MTC) devices is essential to ensure optimal performance and meet the diverse requirements of different applications. The LTE-A network offers high-speed mobile data services and caters to MTC devices and has relatively low data service requirements compared to human-to-human (H2H) communications. LTE-A networks require advanced scheduling schemes to manage the limited spectrum and ensure efficient transmissions. This necessitates effective resource allocation schemes to minimize interference between cells in future networks. To address this issue, a joint delay and energy aware Levy flight Brownian movement-based dragonfly optimization (DELFBDO)-based uplink resource allocation scheme for LTE-A Networks is proposed in this work to optimize energy efficiency, maximize the throughput and reduce the latency. The DELFDO algorithm efficiently organizes packets in both time and frequency domains for H2H and MTC devices, resulting in improved quality of service while minimizing energy consumption. The Simulation results demonstrate that the proposed method increases the energy efficiency by producing the appropriate channel and power assignment for UEs and MTC devices.© 2024 The Authors. The Journal of Engineering published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

Cyberattack patterns in blockchain-based communication networks for distributed renewable energy systems : A study on big datasets

Blockchain-based reliable, resilient, and secure communication for Distributed Energy Resources (DERs) is essential in Smart Grid (SG). The Solana blockchain, due to its high stability, scalability, and throughput, along with low latency, is envisioned to enhance the reliability, resilience, and security of DERs in SGs. This paper presents big datasets focusing on SQL Injection, Spoofing, and Man-in-the-Middle (MitM) cyberattacks, which have been collected from Solana blockchain-based Industrial Wireless Sensor Networks (IWSNs) for events monitoring and control in DERs. The datasets provided include both raw (unprocessed) and refined (processed) data, which highlight distinct trends in cyberattacks in DERs. These distinctive patterns demonstrate problems like superfluous mass data generation, transmitting invalid packets, sending deceptive data packets, heavily using network bandwidth, rerouting, causing memory overflow, overheads, and creating high latency. These issues result in ineffective real-time events monitoring and control of DERs in SGs. The thorough nature of these datasets is expected to play a crucial role in identifying and mitigating a wide range of cyberattacks across different smart grid applications.© 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)fi=vertaisarvioitu|en=peerReviewed