1,742 research outputs found
Hydraulic simulations to evaluate and predict design and operation of the Chashma Right Bank Canal
No full textIrrigation systems / Irrigation canals / Flow control / Velocity / Canal regulation techniques / Hydraulics / Simulation models / Design / Operations / Crop-based irrigation / Distributary canals / Water delivery / Policy / Protective irrigation / Water allocation / Water requirements / Sedimentation / Water distribution / Equity / Water conveyance / Pakistan / Chashma Right Bank Canal
Discrepancy detection between actual user reviews and numeric ratings of Google App store using deep learning
No full textNowadays online reviews play a significant role in influencing the decision of consumers. Consumers show their experience and information about product quality in their reviews. Product Reviews from Amazon to Restaurant Reviews from Yelp are facing problems with fake reviews and fake numeric ratings. Online reviews typically consist of qualitative (text format) and quantitative (rating) formats. In the case of Google Play store fake numeric ratings can play a big role in the success of apps. People tend to believe that a high-star rating may be significantly attached with a good review. However, user star level rating information does not usually match with text format of review. Despite many efforts to resolve this issue, Apple App Store and Google Play Store are still facing this problem. This study proposes a novel Google App numeric reviews & ratings contradiction prediction framework using Deep Learning approaches. The framework consists of two phases. In the first phase, the polarity of reviews are predicted using sentiment analysis tool to build ground truth. In the second phase, star ratings are predicted from text format of reviews after training deep learning models on ground truth obtained in the first phase. Experimental results demonstrate that based on actual user reviews the proposed framework significantly predicts unbiased star rating of app.No Full Tex
Stress Optimization for a MEMS Multilayer Fixed-Fixed Beam
No full textMicro-Electro Mechanical System (MEMS) based multi-layer fixed-fixed beams are used as suspensions to support the suspended membranes in tunable Fabry-Pérot Filters and tunable Vertical Cavity Surface Emitting Lasers. The electrical and optical performance of these devices depends highly on the parallelism of the suspensions holding the membrane in place. However, the residual stress in the suspension layer(s), upon relaxation, results in bending of the suspensions, which in turn results in displacement of the membrane. Therefore, the stress induced bending in the free-standing suspensions holding the membrane in place, must be minimized. A novel stress optimized multi-layer suspension system consisting of a fixed-fixed beam is designed in this work, whereby a tensile stressed material is sandwiched between two compressively stressed material films; such that the suspension layer system has an overall tensile film force, while an additional stress less layer is used to balance the clock-wise and counter clock-wise moments. The displacement of the central portion of the fixed-fixed beam is reduced from several micrometers to a mere 1.63 nm using this technique
Improving the Prediction of Heart Failure Patients’ Survival Using SMOTE and Effective Data Mining Techniques
No full textCardiovascular disease is a substantial cause of mortality and morbidity in the world. In clinical data analytics, it is a great challenge to predict heart disease survivor. Data mining transforms huge amounts of raw data generated by the health industry into useful information that can help in making informed decisions. Various studies proved that significant features play a key role in improving performance of machine learning models. This study analyzes the heart failure survivors from the dataset of 299 patients admitted in hospital. The aim is to find significant features and effective data mining techniques that can boost the accuracy of cardiovascular patient’s survivor prediction. To predict patient’s survival, this study employs nine classification models: Decision Tree (DT), Adaptive boosting classifier (AdaBoost), Logistic Regression (LR), Stochastic Gradient classifier (SGD), Random Forest (RF), Gradient Boosting classifier (GBM), Extra Tree Classifier (ETC), Gaussian Naive Bayes classifier (G-NB) and Support Vector Machine (SVM). The imbalance class problem is handled by Synthetic Minority Oversampling Technique (SMOTE). Furthermore, machine learning models are trained on the highest ranked features selected by RF. The results are compared with those provided by machine learning algorithms using full set of features. Experimental results demonstrate that ETC outperforms other models and achieves 0.9262 accuracy value with SMOTE in prediction of heart patient’s survival.Full Tex
Optical-Interference Mitigation in Visible Light Communication for Intelligent Transport Systems Applications
No full textIntelligent Transport Systems (ITS) are anticipated to be one of the key technologies for the next decade and their deployment can benefit from the recent developments in the domain of Visible Light Communication (VLC). Light Emitting Diode (LED)-based low-cost VLC is considered in this work to provide a practical approach towards the implementation of an ITS by addressing the major issues of channel noise, free-space optical multipath reflections and interference from light sources. An analytical model is presented for the proposed Multiple-Input–Single-Output (MISO)-based VLC, and simulations are performed to analyze the performance of the system for various transmission distances. Results show that the proposed optimal receiver for 4 × 1 MISO can provide considerable improvement in the bit error rate for the forward error correction (FEC) threshold of 3.8 × 10−3 in the presence of optical interference, and is suitable to support an ITS with an inter-vehicle transmission approach. The comparison of achieved performance with existing solutions for VLC-based ITS depicts that the proposed framework provides much higher data rates, three times longer transmission distance and improved receiver sensitivity
Optimization of stress induced bending in mems based suspensions
No full textThe suspended membrane is currently becoming the trend in Micro-Electro-Mechanical Systems (MEMS) devices. For example, in tunable Fabry-Pérot (FP) Filter, the suspended membrane can be used as a top moveable mirror. The parallelism of the suspension holding the membrane is crucially important, as output characteristics of the filter highly depend on it. However, the adverse effect of residual stress of the material causes bending in the suspension which limits the performance of the FP filter. Therefore for high performance of FP filter, the stress-induced bending must be minimized. This paper reports a novel stress optimized multilayer Suspension(s) design by using Finite Element Method (FEM).In which the bending of the suspension is reduced to 76 nm form several μm, for typically used suspended membrane dimensions
A Real-Time Hybrid Approach to Combat In-Browser Cryptojacking Malware
No full textCryptojacking is a type of computer piracy in which a hacker uses a victim’s computer resources, without their knowledge or consent, to mine for cryptocurrency. This is made possible by new memory-based cryptomining techniques and the growth of new web technologies such as WebAssembly, allowing mining to occur within a browser. Most of the research in the field of cryptojacking has focused on detection methods rather than prevention methods. Some of the detection methods proposed in the literature include using static and dynamic features of in-browser cryptojacking malware, along with machine learning algorithms such as Support Vector Machine (SVM), Random Forest (RF), and others. However, these methods can be effective in detecting known cryptojacking malware, but they may not be able to detect new or unknown variants. The existing prevention methods are shown to be effective only against web-assembly (WASM)-based cryptojacking malware and cannot handle mining service-providing scripts that use non-WASM modules. This paper proposes a novel hybrid approach for detecting and preventing web-based cryptojacking. The proposed approach performs the real-time detection and prevention of in-browser cryptojacking malware, using the blacklisting technique and statistical code analysis to identify unique features of non-WASM cryptojacking malware. The experimental results show positive performances in the ease of use and efficiency, with the detection accuracy improved from 97% to 99.6%. Moreover, the time required to prevent already known malware in real time can be decreased by 99.8%
Synthesis of CZTS kesterite by pH adjustment in order to improve the performance of CZTS thin film for photovoltaic applications
No full text[EN] Quaternary CZTS (Cu2ZnSnS4) kesterite thin layers were successfully made by electrochemical deposition method. CZTS thin layers were deposited on Indium Tin Oxide (ITO) from an aqueous solution. In this work, the effects of pH adjustment under ambient conditions of CZTS thin films were studied. The as grown samples were investigated by numerous existing characterization systems. The X-ray diffraction (XRD) proves the polycrystalline description of the layer. The average crystallite size is varying from 10 nm to 24 nm of the films is dependent on the pH of the solution. All the thin films are in the CZTS kesterite phase attributed to A(1) mode at 334 cm(-1) verified by Raman spectroscopy. The SEM and AFM study show that the pH variation of the so-lution improved the surface morphology and topography of the CZTS thin films which increase several nm in grain size. Moreover, the optical analysis indicates a suitable band gap in the range of 1.5-1.8 eV depending upon the sulfurization temperature. It is found that the pH variation affects both the stability and the performance of the high-quality CZTS absorber layer applications. The CZTS layer with 4.80 pH was annealed at 450 degrees C and 500 degrees C, and at these temperatures the band gap was varied. At the end the band gap variations effect on the performance of CZTS based solar cell is being analyzed by using a simulation tool SCAPS-1D.Author Sha fi Ullah acknowledged the post -doctoral contract supported by the, RRHH, postdoctoral contract (PAID-10-20), and Ministerio de Economia y Competitividad (Grant Number PID2019-107137RB-C21) , Universitat Politècnica de València (UPV) Spain. Author Amal Bouich acknowledged the Post -doctoral contract supported by the, RRHH, Postdoctoral contract the Margarita Salas fi nanced with union European Next Generation EU. This research has been funded by Grant PID2019-107137RB-C21 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe". The author Muhammad Aamir Sha fi acknowledge the Higher Education Commission of Pakistan, International Research Support Initiative Program (IRSIP) , for grant No: 1-8/HEC/HRD/2020/10744 PIN: IRSIP 45 Engg 17.Aamir Shafi, M.; Khan, L.; Ullah, S.; Bouich, A.; Ullah, H.; Mari, B. (2022). Synthesis of CZTS kesterite by pH adjustment in order to improve the performance of CZTS thin film for photovoltaic applications. Superlattices and Microstructures. 164:1-10. https://doi.org/10.1016/j.spmi.2022.107185S11016
Synthesis, structural characterization and catalytic application of citrate-stabilized monometallic and bimetallic palladium@copper nanoparticles in microbial anti-activities
No full textInayat Ullah,1 Khakemin Khan,2 Muhammad Sohail,3 Kifayat Ullah,4 Anwar Ullah,4 Shabnum Shaheen5 1Lanzhou Center for Tuberculosis Research and Institute of Pathogen Biology, School of Basic Medical Sciences, Lanzhou University, Lanzhou, People’s Republic of China; 2Department of Chemistry, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan; 3School of Chemical Engineering and the Environment, Beijing Institute of Technology, Beijing 100081, People’s Republic of China; 4Department of Biosciences, COMSATS Institute of Information Technology, Park Road, Chack Sahzad, Islamabad, Pakistan; 5Department of Botany, Lahore College for Women University, Lahore, Punjab-Pakistan Abstract: In this research work, copper (Cu), palladium (Pd) and their bimetallic palladium@copper (Pd@Cu) nanoparticles were synthesized using trisodium citrate as a stabilizing agent using the known chemical reduction method. The synthesized Cu, Pd and Pd@Cu nanoparticles were characterized by the ultraviolet–visible spectroscopy, scanning electron microscopy and X-ray diffraction spectroscopy, respectively. The different volumes of trisodium citrate were used for the stability of synthesized monometallic Cu, Pd and bimetallic Pd@Cu nanoparticles. The synthesized Cu, Pd and their bimetallic Pd@Cu nanoparticles were used as catalysts for the reduction of 4-nitrophenol in the presence of NaBH4. The bimetallic Pd@Cu nanoparticles had efficient catalytic activities with a high rate constant (1.812 min-1) as compared to monometallic Cu (0.3322 min-1) and Pd (0.2689 min-1) nanoparticles, respectively. The correlation coefficient (R2) was found to be 0.99 for these three nanoparticles. Meanwhile, the effect of Cu, Pd and bimetallic Pd@Cu nanoparticles was checked on the physiology of specific different micro-organism strains. The bimetallic Pd@Cu nanoparticles reported the maximum resistance at maximum level the growth of bacterial strain and had observed a smooth antibacterial graph than the monometallic analogs. Keywords: stabilizing agent, bimetallic nanoparticles, catalytic activities, antimicrobial effect
Incidence of Nephropathy After Spontaneous Bacterial Peritonitis in Decompensated Liver Cirrhosis at Muhammad Teaching Hospital, Peshawar: A Single Institution Descriptive Cross-Sectional Study
No full textObjective: To determine the incidence of nephropathy after spontaneous bacterial peritonitis in patients with
decompensated liver cirrhosis.
Study Design: Descriptive cross-sectional study.
Place and Duration of Study: This study was conducted at the Department of Medicine, Muhammad Teaching
Hospital (MTH), Peshawar, Pakistan from November 1st, 2024, to April 30th 2025.
Methods: A total of one hundred and ten (110) patients were part of the current study. This sample size was
obtained by using the WHO sample size calculator, for which a reference study was considered having a
frequency of renal impairment in about 83.3% of patients who had developed decompensated liver cirrhosis
followed by spontaneous bacterial peritonitis. Consecutive, non-probability sampling technique was used. The
confidence interval was equal to 95% while error margin was equal to 6% to calculate the size.
Results: Participants of the study were adults, and the minimum age was 18, whereas the oldest was 60 years,
with a mean of 46.436 ± 6.81 years. As chronic liver disease patients were selected, they had a prolonged
history of decompensated cirrhosis of the liver (mean duration was 8.845 ± 2.38 months). Gender classification
of 110 participants was done, in which males were 91 (82.7%) and females were 19 (17.3%). Nephropathy
(Renal impairment) was observed in 33 (30%) of patients after spontaneous bacterial peritonitis in
decompensated liver cirrhosis.
Conclusion: In this study, the results showed that overall, there was 30% renal impairment in the observed
cases. They were more prominent in Child's Pugh C cirrhosis liver compared to Class A or B cirrhosis liver
because of the development of ascites.
How to cite this: Alam S, Ayaz M, Kausar SAZ, Ullah R, Imran A, Khan MS. Incidence of Nephropathy After Spontaneous Bacterial Peritonitis in Decompensated Liver Cirrhosis at Muhammad Teaching Hospital, Peshawar: A Single Institution Descriptive Cross-Sectional Study. Life and Science. 2025; 6(3): 356-361. doi: http://doi.org/10.37185/LnS.1.1.94
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