Improving collaborative filtering using lexicon-based sentiment analysis

Since data is available increasingly on the Internet, efforts are needed to develop and improve recommender systems to produce a list of possible favorite items. In this paper, we expand our work to enhance the accuracy of Arabic collaborative filtering by applying sentiment analysis to user reviews, we also addressed major problems of the current work by applying effective techniques to handle the scalability and sparsity problems. The proposed approach consists of two phases: the sentiment analysis and the recommendation phase. The sentiment analysis phase estimates sentiment scores using a special lexicon for the Arabic dataset. The item-based and singular value decomposition-based collaborative filtering are used in the second phase. Overall, our proposed approach improves the experiments’ results by reducing average of mean absolute and root mean squared errors using a large Arabic dataset consisting of 63,000 book reviews

Clay minerals damage quantification in sandstone rocks using core flooding and NMR

Sandstone oil reservoirs consist of different clay minerals such as kaolinite, illite, and chlorite. These clay minerals highly affect the formation damage during enhanced oil recovery (EOR) and well stimulation operations in these reservoirs. No attention was paid to investigate the effect of these clay minerals on the formation damage during different reservoir processes. In addition, no solution was introduced to mitigate the effect of clay minerals on the formation damage in sandstone reservoirs. In this study, the effect of clay mineral contents and type on the formation damage was studied in detail by injecting water and HCl as damaging fluids. Bandera grey, Berea, and Bandera brown sandstone rocks with various clay mineral contents were studied. XRD was used to characterize the sandstone rocks to determine the clay type and content in each rock. Two core plugs from each rock were selected for HCl and water injection. Core flooding experiments were performed to measure the initial and final permeability. In the core flooding experiments, fluids were injected into the cores at 25 °C and at a backpressure of 1000 psi. SEM was carried out before and after flooding for the tested rocks to locate the change in the clay distribution inside the rocks. The NMR analysis of core samples was done before and after flooding with the damaging fluid to quantify the formation damage and to find the possible damaging mechanism. NMR was used to locate the damage inside the rock due to the migration of clay minerals. Based on the core flooding, SEM, and NMR analysis, the maximum damage by the fresh water took place in Berea sandstone core due to fine migration and clay swelling. The illite clay mineral and chlorite can cause the formation damage on HCl injection. Illite can break down and migrates in the cores during the acid injection. In sandstone acidizing, chlorite clay mineral caused iron hydroxide precipitation inside the cores during treatment with mud acid. NMR showed that clay minerals plugged the pore throats of the rocks and reduced the rock permeability during the injection of fresh water

Context-aware recommender system for multi-user smart home

Smart home is one of the most important applications of the internet of things (IoT). Smart home makes life simpler, easier to control, saves energy based on user’s behavior and interaction with the home appliances. Many existing approaches have designed a smart home system using data mining algorithms. However, these approaches do not consider multiusers that exist in the same location and time (which needs a complex control). They also use centralized mining algorithm, then the system’s efficiency is reduced when datasets increase. Therefore, in this paper, we firstly build a context-aware recommender system that considers multi-user’s preferences and solves their conflicts by using unsupervised algorithms to deliver useful recommendation services. Secondly, we improve smart home’s responsive using parallel computing. The results reveal that the proposed method is better than existing approaches

Search for the production of dark fermion candidates in association with heavy neutral gauge boson decaying to dimuon in proton-proton collisions at s=8\sqrt{s} = 8 TeV using the CMS open data

This analysis shows a search for dark fermion particles produced in association with a heavy neutral gauge boson (Z$^{\prime}$). The studied events topology are dimuon and a large missing transverse momentum. %We considered the muonic decay of Z$^{\prime}$. The analyzed data were the Open Data collected by the CMS detector in proton-proton collisions at the LHC in 2012 and correspond to an integrated luminosity of 11.6 fb$^{-1}$ at $\sqrt{s} =$ 8 TeV. One benchmark scenario the light vector was used for interpreting the data, based on a simplified model so called the mono-Z$^{\prime}$ model. No evidence of dark fermion candidates was found, 95$\%$ confidence level limits have been set on both Z$^{\prime}$ and dark fermion masses.Comment: 10 pages. arXiv admin note: substantial text overlap with arXiv:2103.04326, arXiv:2109.1127

Ultrawide phononic band gap for combined in-plane and out-of-plane waves

We consider two-dimensional phononic crystals formed from silicon and voids, and present optimized unit cell designs for (1) out-of-plane, (2) in-plane and (3) combined out-of-plane and in-plane elastic wave propagation. To feasibly search through an excessively large design space (10e40 possible realizations) we develop a specialized genetic algorithm and utilize it in conjunction with the reduced Bloch mode expansion method for fast band structure calculations. Focusing on high symmetry plain-strain square lattices, we report unit cell designs exhibiting record values of normalized band-gap size for all three categories. For the combined polarizations case, we reveal a design with a normalized band-gap size exceeding 60%.Comment: 4 pages, 1 figure, submitted for journal publicatio

Contactless Heart Rate Detection Using MM-Wave Radar Systems Advancements

In recent years, there has been a significant surge in the development of non-contact methods for detecting heart and breathing rates. Various Millimeter-wave (MM-wave) radar systems, operating at different frequency bands like 10 GHz, 24 GHz, 77 GHz, and 122 GHz, have been effectively deployed for this purpose. This paper explores the vital application of contactless systems in the medical field, particularly during disasters and epidemics. These systems are crucial for detecting the heart and breathing rates of individuals trapped under debris, in military operations, long-term vital sign monitoring in hospitals, and aiding the elderly in public spaces. Consequently, our focus is on heart and breathing rate detection using radar systems. This paper highlights the significance of capturing the electrical representation of the heart signal. This approach is known for its trustworthiness and accuracy in identifying various medical conditions. Furthermore, a traditional method based on Fourier transform is presented for heart and respiration rate estimation. This method leverages the direct proportionality between heart and breathing rates and the frequencies of raw radar signals. To estimate the breathing rate, it identifies the maximum peak within the frequency range of 0.15 to 0.4 Hz in the frequency domain and multiplies the corresponding frequency by 60 to obtain the rate per minute. For heart rate estimation, it detects the maximum peak within the frequency range of 0.8 to 2 Hz and calculates the rate per minute accordingly

Contactless Heart Rate Detection Using MM-Wave Radar Systems Advancements

In recent years, there has been a significant surge in the development of non-contact methods for detecting heart and breathing rates. Various Millimeter-wave (MM-wave) radar systems, operating at different frequency bands like 10 GHz, 24 GHz, 77 GHz, and 122 GHz, have been effectively deployed for this purpose. This paper explores the vital application of contactless systems in the medical field, particularly during disasters and epidemics. These systems are crucial for detecting the heart and breathing rates of individuals trapped under debris, in military operations, long-term vital sign monitoring in hospitals, and aiding the elderly in public spaces. Consequently, our focus is on heart and breathing rate detection using radar systems. This paper highlights the significance of capturing the electrical representation of the heart signal. This approach is known for its trustworthiness and accuracy in identifying various medical conditions. Furthermore, a traditional method based on Fourier transform is presented for heart and respiration rate estimation. This method leverages the direct proportionality between heart and breathing rates and the frequencies of raw radar signals. To estimate the breathing rate, it identifies the maximum peak within the frequency range of 0.15 to 0.4 Hz in the frequency domain and multiplies the corresponding frequency by 60 to obtain the rate per minute. For heart rate estimation, it detects the maximum peak within the frequency range of 0.8 to 2 Hz and calculates the rate per minute accordingly

The Effect of Collimator Diameters on Buildup Factor by using Gamma – Gamma Coincidence System

In this work buildup factor of aluminum and copper samples was studied for different thickness using a  gamma _  gamma coincidence technique and by use two collimator 10 and 7 mm, buildup factor  was calculated for thickness ranged between ( 0 - 9.6 ) cm of aluminum and ( 0 - 4.0 ) cm of copper  using  Na - 22  source with activity of   ( 1 micro Curie ) with single energy ( 0.511 MeV ) and by using ( 3 "× 3" ) sodium iodide detector  NaI (TI). The results showed that buildup factor was more accuracy when we used small diameter because this will decrease the scattering ray which make our calculations more acute for buildup factor which is very important in shielding process for gamma ray. Keywords: Buildup factor, Gamma ray, Shield, Coincidence