bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantum tops at the LHC: from entanglement to Bell inequalities
Authors: Severi Claudio , Boschi Cristian Degli Esposti , Maltoni Fabio , Sioli Maximiliano 
Published: April 2022

AbstractWe present the prospects of detecting quantum entanglement and the violation of Bell inequalities in $$t\bar{t}$$

t

t

¯

events at the LHC. We introduce a unique set of observables suitable for both measurements, and then perform the corresponding analyses using simulated events in the dilepton final state, reconstructing up to the unfolded level. We find that entanglement can be established at better than $$5 \sigma $$

5
σ

both at threshold as well as at high $$p_T$$

p
T

already in the LHC Run 2 dataset. On the other hand, only very high-$$p_T$$

p
T

events are sensitive to a violation of Bell inequalities, making it significantly harder to observe experimentally. By employing a sensitive and robust observable, two different unfolding methods and independent statistical approaches, we conclude that, at variance with previous estimates, testing Bell inequalities will be challenging even in the high luminosity LHC run.
Analog resistive-switching property of Ni/TiOx/W structure
Authors: Liu Chih-Yi , Liu Shih-Kun , Huang Chung-Chia , Lin Chao-Cheng , Lai Chun-Hung 
Published: April 2022

A radio-frequency magnetron sputter was used to deposit a 60 nm TiO[Formula: see text] film on a W-coated Si substrate at room temperature. Subsequently, a 100 nm Ni film was deposited using a thermal evaporator to form a Ni/TiO[Formula: see text]/W structure. Numerous oxygen vacancies and defects were present in the TiO[Formula: see text] film. The current–voltage characteristics indicate that Schottky emission dominated the conduction mechanism of the Ni/TiO[Formula: see text]/W structure. Because of Schottky barrier modulation, analog resistive switching of the Ni/TiO[Formula: see text]/W structure can be performed using consecutive voltage sweepings or voltage pulses. Various pulse waveforms were used to demonstrate synaptic potentiation and depression.
A microcontroller based microfluidic biochip for calcium percentage detection in blood
Authors: Al-Sawwaff Zaid H. , Rashid Zahraa M. , Al-Okby Mohammed Faeik Ruzaij , Kandemirli Fatma 
Published: April 2022

Apheresis is an essential step in clinical diagnostic. Searching for a safe and fast way was necessary to avoid wasting time and obtain the desired results efficiently. <span lang="EN-US">This research includes two stages: First, a microfluidic biochip with the properties of fast processing response, automation capability, and low-cost was designed having a tiny mesh-type channel that filters pure plasma from the blood components and a straight channel to deliver the pure plasma to a tank. Second, an automated system was designed to detect blood calcium levels using a microcontroller and a colors-detection sensor TCS3200-DB. The device is designed to take a 0.15 to 2.15 mg/dL, 10-160 µm blood sample, which is considered small compared to the samples taken for the blood apheresis process used in laboratories where a substantial quantity of pure plasma is obtained naturally. Pure plasma is mixed with calcium detectors R1 and R2 to get a violet-colored solution with a wavelength between 390 nm to 440 nm. The results of the proposed device were compared with the traditional methods used spectroscopy method using concentrations of 10 different blood samples, and the results proved that there is a slight error between the two processes.</span>
Development of mini smart multipurpose vehicle for organic rice harvesting
Authors: Daoden Kanchana , Sringam Sureeporn , Nicrotha Supanat , Sornnen Thanawat 
Published: April 2022

This <span lang="EN-US">research aimed to develop the mini smart multipurpose vehicle (MSMPv) innovative from the conventional agriculture tractor for three objectives. The novel automatic gear modified technique for the MSMPv is proposed, then an idea to enhance peripheral capability through a hitch system. The final purpose is to support the farmer's ability to follow organic agriculture regulations on the issue of contaminated tools and machinery, especially in the rules related to contamination of equipment or machines that cannot share with conventional agricultural production. The organic rice crop plot of Nong Bua Lamphu Province in Thailand has been set to the case study. Here, farmers faced problems; lack of labour, production under an organic system that does not permit chemicals, and limited harvesting. According to the existing technology, this research has developed a typical farm tractor used in the country by inventing a manual transmission engine to an automatic transmission and accessories such as remote control, GPS, camera, and sensors. Thus, the development of this organic rice harvesting prototype should be an approach that provides both the opportunity to raise the self-reliance concept and enhance the knowledge of the development of innovative tools for farmers simultaneously.</span>
A novel optimization-based power quality enhancement using dynamic voltage restorer and distribution static compensator
Authors: Chiranjivi Madduluri , Swarnasri Katragadda 
Published: April 2022

The power assurance <span lang="EN-US">for distinct purchaser in the nation must be guaranteed through electric power distribution (EPD) system, subsequently EPD must be reliable, and well facilitating with power quality (PQ) in distribution framework. It will be much significant to keep up with PQ in power distribution (PD) framework for service continuity. The PQ issue basically emerge in distribution framework are voltage swell, sag, harmonics, and disparities in power. In this manuscript, the PQ development in photovoltaic (PV) PD framework for IEEE 33 and 57 bus frameworks is deliberated as the aim. The improvement is satisfied with FACTS pay gadgets of dynamic voltage restorer (DVR) and distributed static compensator (DSTATCOM). The butterfly optimizer (BO) and gray wolf optimizer (GWO) framework is deliberated for suggested work that implies a switching gadget and it compares the yield signal of DSTATCOM and DVR. In this proposed system DVR is compensated with an advanced GWO and DSTATCOM with BO for optimal location of FACTS devices in IEEE 33 and 57 bus systems are discussed like in the conventional paper as 13th bus for IEEE 33 system &amp; 30th bus for IEEE 57 system.</span>
Performance comparison between fixed tilt angle and solar tracking systems at Basra governorate: A case study
Authors: R. Alnaab Ismaeil , M. Taha Harwan , A. Abdulwahab Zainab , Salah Al-Radhi Mohammed 
Published: April 2022

Theoretical <span lang="EN-US">calculations and online system simulations using PVWatts and global solar atlas simulators, were conducted in this study to find the difference in solar power production between fixed solar power systems and tracking systems at Basra Governorate. The research included the analysis of geographical location and weather conditions and their effect on output power. The reliant power resource types and power generation of the southern region of Iraq as well as load demands were demonstrated and discussed in this research. Furthermore, the sun path, solar angles and solar radiations were considered in this study, in addition to the mathematical calculations of optimum tilt angles. The methodology used in this study was based upon theoretical and online measures of real-time weather factors, solar angles, solar radiations and model properties of the examined system. The results and factors of different systems including: peak sun hours per day, dc to ac derate factors, tilt angles, solar radiations and power production were compared to multiple similar research elements that were accomplished around the same region and some other countries. The study concluded that solar tracking system absorbs more radiations and produces an annual production of 15–30% higher than fixed tilt angle system.</span>
Advanced control of a permanent magnet synchronous generator for a wind turbine
Authors: Belkacem Abdelkader , Boudjema Zinelaabidine , Bachir Ghalem , Taleb Rachid 
Published: April 2022

This article <span lang="EN-US">presents an improved vector control scheme based on super twisting continuous sliding mode for a permanent magnet synchronous generator integrated in a dual roror wind turbine system. To augment the energy effectiveness of wind systems, several research has recently been realized by different researchers and in various technologies fields. The field of machine control occupied a large part of this research as the objective was always to find the most optimal control solution. Two main objectives are targeted in this work. The first goal is to develop the vector control performance of the permanent magnet synchronous generator by using second order continuous sliding mode controller, which is known for their robustness and ability to reduce chattering phenomenon. The second objective of this work is to use a dual rotor wind turbine in order to increase the energy efficiency of the wind power system used. The obtained simulation results showed the efficacy of the techniques used.</span>
Adaptive backstepping control of linear induction motors using artificial neural network for load estimation
Authors: Mahmoudi Omar , Boucheta Abdelkrim 
Published: April 2022

Linear induction motors (LIMs) make performing a direct linear motion possible without any mechanical rotary to linear motion transforming parts. <span lang="EN-US">Obtaining a precise mathematical model of such type of motors presents a difficulty due to time varying parameters and external load disturbance. This paper proposes an adaptive backstepping controller structure based on lyapunov stability for controlling a LIM position. Which can guarantee the annulment of position tracking error, despite of parameter uncertainties. Parameter update laws are extracted to estimate mover mass, friction coefficient and load force disturbance, which are assumed to be constant parameters; as a result, compensating their undesirable effect on control design. Then, load disturbance estimate is replaced with an artificial neural network (ANN) to reduce the estimation error. The numerical validation has shown better performance compared to the conventional backstepping controller, and proved the robustness of the proposed adaptive controller design against parameter changes.</span>
Performance analysis of different intonation models in Kannada speech synthesis
Authors: Chakrasali Sadashiva Veerappa , Indira Krishnappa , Narasimhaiah Sunitha Yariyur , Chandraiah Shadaksharaiah 
Published: April 2022

Text <span lang="EN-US">to speech (TTS) is a system that generates artificial speech from text input. The prosodic models used improve the quality of the synthesized speech especially naturalness and intelligibility. The prosody involves intonation, intonation refers to the variations in the pitch frequency (F0) with respect to time in an utterance. This work mainly concentrates on building feedback neural network model to predict F0 contour in the utterances using Fujisaki intonation model parameters as the input features to the network since the Fujisaki intonation model is data driven and not a rule based one. In this work we have built 4-layer feedback neural network in the festival framework. Finally, the synthetically generated Kannada speech using the neural network model, is compared for its performance with the classification and regression tree (CART) model and Tilt model. Database of simple declarative Kannada sentences created by Carnegie Mellon University have been deployed in this work. From the study it is very clear that F0 contours can be accurately predicted using CART and neural network models, whereas naturalness and intelligibility is high in CART model rather than neural network model.</span>
Simulating the Covid-19 epidemic event and its prevention measures using python programming
Authors: Hamid Mustofa Abi , Aditama Dimas , Permata Endi , Kholifah Nur , Nurtanto Muhammad , Abdul Majid Nuur Wachid 
Published: April 2022

A simulation is needed to observe and indicate how much preventive measures influence the pandemic flow, controlling and stopping it. This study <span>succeeded in making a stochastic susceptible infected recovered deceased (SIRD) simulation using Python programming language to determine the effectiveness of prevention methods such as masks policy, social distancing, vaccination, quarantine, and lockdown. Every preventive measure is modeled based on an equivalent actual event and every essential aspect that affects the course of the pandemic. A person is represented as a circle moving freely in two-dimensional space, and disease spreads through person-to-person contact. This simulator then tested using parameters to simulate COVID-19 and found significant results between communities that implement preventive measures and those that do not. We found that within 106 days, 284 people were infected, but when five preventive methods are applied for a total of 33 days, only 31 people were infected. Adequate to simulate epidemic events and their prevention measures, this simulator can also be used as a learning tool with factors in epidemic events such as population density, mobility, infection rate, disease mortality, and every effect of each preventive measure. Users can change and influence the simulation course using interactive and straightforward software tools.</span>
Power loss minimization with simultaneous location and sizing of distribution generation units using artificial algae algorithm
Authors: Chauhan Vineeta S. , Chakravorty Jaydeep 
Published: April 2022

Power loss is one <span lang="EN-US">of the important pointers used to measure the performance of distributions networks. Many optimization algorithms have been proposed to solve various optimal power flow problems in Electrical Engineering. In this paper, a novel technique, artificial algae algorithm is developed to robustly detect the optimal location and size of distributed generation (DG) units for minimization of total power losses without violating the equality and inequality constraints. The main objective of optimal power flow (OPF) is to maximize or minimize the objective function using various constraint so that steady-state operation point is achieved. The concept of optimal power flow in power system helps to minimize real power loss. In the proposed approach, various control variables like generator bus, voltage magnitudes, and transformer tap settings are considered. The proposed algorithm is simulated in MATLAB and effectiveness is carried on IEEE 33 bus radial distribution system and satisfactory results are achieved when compared with other optimization techniques. A notable improvement in reduction of active power losses with 3 DG operating at different power factors are 65.5%, 42.4%, and 77.8% respectively, were achieved in comparison to the system without DGs and as compared with other research papers.</span>
Investigation of pattern division multiple access technique in wireless communication networks
Authors: Yonis Aws Zuheer , Mohammed Khalid Khalil 
Published: April 2022

Recently, <span>pattern division multiple access (PDMA) is a non-orthogonal multiple access system that is now being developed in next-generation telecoms to address the requirement for mass connectivity. The core premise of non-orthogonal multiple access is to simultaneously serve multiple users with varying power levels across the same spectrum resources such as time, frequency, code, as well as space with minimal inter-user interference. A simulation analysis of significant technology enhancements focusing on PDMA aims to describe the benefits of the two plans now being examined by the third-generation partnership project for 5G technologies, namely filtered orthogonal frequency division multiplexing (F-OFDM) and windowed orthogonal frequency division multiplexing (W-OFDM), and to compare them to alternative modulation processes such as 16, 32, and 128 modulations. The research results explained the PDMA is less bit error rate used in multiple access technologies compare with W-OFDM and F-OFDM.</span>
Design a monitoring system for COVID-19 patients
Authors: Hendi Hayder Ibrahim , Mshali Haider Hassan 
Published: April 2022

This paper <span lang="EN-US">considers to developing application software that can assist COVID-19 patients in-home quarantine to know their situations and call the emergence center when the patient needs it. It includes a smart band as well as an application on the smartphone, the smart band can determine blood oxygen levels, the temperature of the patient, environmental temperature and humidity, also daily activities that affect the decision to go to the hospital or stay at home. The core of the proposed project is using ontology and semantics web to process the data that coming from sensors (physiology and environment), and the information of patients stored in the database on the mobile application. The response depends on the dataset of affect sensors parameters and type of activity the patient at the time. There are three types of response to proposed program is (normal, alert, and emergency).</span>
Improving the sub-image classification of invasive ductal carcinoma in histology images
Authors: Kawattikul Khanabhorn , Sermsai Kodchanipa , Chomphuwiset Phatthanaphong 
Published: April 2022

Whole <span>slide image (WSI) processing is a common technique used in the analysis process performed by pathologists. Identifying precise and accurate regions of cancerous in the tissue is an important process in the disease diagnosis modality. This work proposes an automated technique for identifying invasive ductal carcinoma (IDC) in histology images using. An image is divided into small non-overlapped patches (or image windows). Then, the task is to classify the image patches into different classes, i.e., i) IDC and ii) non-IDC. We employ a two-stage classification-based to classify the patches, as to identify IDC regions in the tissue. In the first stage (patch-level classification), image patch classification is carried out using a conventional handcrafted feature and deep-learning technique are explored. The second stage (post-processing) undergoes a refinement process, which considers the spatial relationships between the neighboring patches. This stage aims to amend some of miss-classified patches. Markov random field (MRF) is implemented in this stage to examine the relationships of the patches and their neighborhoods. The experiments are conducted on public dataset. The experimental results show the post-processing can improve the performance of the classification in the first stage using the handcrafted-based technique and deep learning.</span>
Prediction of of heart diseases utilising support vector machine and artificial neural network
Authors: Faieq Alaa Khaleel , Mijwil Maad M. 
Published: April 2022

The heart, <span lang="EN-US">like a pump, is an organ about the size of a fist, mainly composed of muscle and connective tissue that functions to distribute blood to tissues. The heart is located under the rib cage, above the diaphragm between the lungs, slightly closer to the left. Sometimes a small, unexpected problem with the veins or the valves that supply the heart affects a person's life and can lead to death. Early diagnosis is essential to predict diseases that affect the human heart and lead people to live another period of life. In this context, the authors introduce two methods for early diagnosis of heart disease, the support vector machine and artificial neural network. The medical data is taken from the University of California Irvine (UCI) Machine Learning Repository database, and it contains reports of 170 people. The investigation results confirm that the optimal execution is the support vector machine technique. It gives high-accuracy prediction results. As for the performance of the forward propagation artificial neural networks (ANN) technique is acceptable.</span>
Automatic deception detection system based on hybrid feature extraction techniques
Authors: Abd Shaimaa Hameed , Hashim Ivan A. , Jalal Ali Sadeq Abdulhadi 
Published: April 2022

Human face <span lang="EN-US">is considered as a rich source of non-verbal features. These features have proven their efficiency, so they are used by the deception detection system (DDS) to distinguish liar from innocent subjects. The suggested DDS utilized three kinds of features, these are facial expressions, head movements and eye gaze. Facial expressions are simply encoded and represented in the form of action units (AUs) based on facial action coding system (FACS). Head movements are represented based on both transitions and rotation. For eye gaze features, the eye gaze directional angle in both x-axis and y-axis are extracted. The collected database used to prove validity and robustness of the suggested system contains videos for 102 subjects from both genders with age range 18-55 years. The detection accuracy of the suggested DDS based on applying the logistic regression classifier is equal to 88.0631%. The proposed system has proven its robustness and the achievement of the highest detection accuracy when compared with previously designed systems.</span>
Light weight serverless computing at fog nodes for internet of things systems
Authors: Elkholy Mohamed , Marzok Marwa A. 
Published: April 2022

Internet of <span lang="EN-US">things (IoT) systems collect large size of data from huge numbers of sensors. A wide rage of IoT systems relies on cloud resources to process and analyze the collected data. However, passing large amount of data to the cloud affects the overall performance and cannot support real-time requirements. Serverless computing is a promising technique that allows developer to write an application code, in any programming language, and specify an event to start its execution. Thus, IoT system can get a good benefit of serverless environment. The proposed work introduces a framework to allow Serverless computing to take place on the Fog nodes near the data collectors. The proposed framework is implemented as an extension to a Kubernetes cluster that manages a set of Docker containers at the fog layer. A prototype of the proposed solution was implemented using Node.Js for coding and YAML files to transfer data. The proposed framework was evaluated against traditional cloud Serverless execution. The experimental results proved the significant enhancement of the framework by dcreasing the respond time especially for data intensive IoT applications.</span>
The development of smart flowerpot based on internet of things and mobile and web application technology
Authors: Janpla Satien , Jewpanich Chaiwat , Tachpetpaiboon Nisanart , Prongsanthia Waraporn , Jewpanich Butsirin 
Published: April 2022

Cultivation <span lang="EN-US">of ornamental plants in the office is popular among office workers and the general public because it can create a good environment in the area, but the plant growers must pay attention to watering the plants, because it may cause the plant to die</span><em><span lang="TH">. </span></em><span lang="EN-US">With the advancement of internet of things </span><span lang="TH">(</span><span lang="EN-US">IoT</span><span lang="TH">)</span><span lang="EN-US"> technology, used to control devices wirelessly, this research developed the smart flowerpot system that works through mobile and web applications, using a microcontroller to control the system and connect to users via mobile and web application that can monitor the system, and control the operation both directly and automatically</span><em><span lang="TH">. </span></em><span lang="EN-US">When soil moisture is reduced to a predetermined value, the system will order the plants to be watered automatically, and when the water level is almost completely reduced, the ultrasonic sensor will send a notification to the mobile application to let the user know, after testing the system, it was found that the smart plant pot can work efficiently and can automatically water the plants</span><em><span lang="TH">.</span></em>