bluuebunny/crossref_metadata_2025 huggingface dataset:
Entorhinal Tau Predicts Hippocampal Activation and Memory Deficits in Alzheimer’s Disease
Authors: Richter Nils , Bischof Gérard N. , Dronse Julian , Nellessen Nils , Neumaier Bernd , Langen Karl-Josef , Drzezga Alexander , Fink Gereon R. , van Eimeren Thilo , Kukolja Juraj , Onur Oezguer A.
Published: November 2020

Background: To date, it remains unclear how amyloid plaques and neurofibrillary tangles are related to neural activation and, consequently, cognition in Alzheimer’s disease (AD). Recent findings indicate that tau accumulation may drive hippocampal hyperactivity in cognitively normal aging, but it remains to be elucidated how tau accumulation is related to neural activation in AD. Objective: To determine whether the association between tau accumulation and hippocampal hyperactivation persists in mild cognitive impairment (MCI) and mild dementia or if the two measures dissociate with disease progression, we investigated the relationship between local tau deposits and memory-related neural activation in MCI and mild dementia due to AD. Methods: Fifteen patients with MCI or mild dementia due to AD underwent a neuropsychological assessment and performed an item memory task during functional magnetic resonance imaging. Cerebral tau accumulation was assessed using positron emission tomography and [18F]-AV-1451. Results: Entorhinal, but not global tau accumulation, was highly correlated with hippocampal activation due to visual item memory encoding and predicted memory loss over time. Neural activation in the posterior cingulate cortex and the fusiform gyrus was not significantly correlated with tau accumulation. Conclusion: These findings extend previous observations in cognitively normal aging, demonstrating that entorhinal tau continues to be closely associated with hippocampal hyperactivity and memory performance in MCI and mild dementia due to AD. Furthermore, data suggest that this association is strongest in medial temporal lobe structures. In summary, our data provide novel insights into the relationship of tau accumulation to neural activation and memory in AD.
Effect of AMB winding configurations on static and dynamic performances and power consumptions of the AMB-rotor system
Authors: Liu Qing , Wang Li , Zhang Shiping , Li Yuanyuan , Lei Gang
Published: November 2020

Active magnetic bearings (AMBs) bring extraordinary benefits such as free of contact, elimination of lubrication, active control of rotor position, and a built-in monitoring system. In the design of AMBs, the bearing structure is of significance since it has an important impact on bearing performances. However, the effect of winding configurations of AMBs is still obscure. In this paper, the system-level implications of two radial AMB winding configurations termed the Ortho and the Cross types are investigated, including the bearing characteristics, power consumptions and rotor dynamic behaviors. The simulation results demonstrate that the Cross type contributes to larger load capacity in the direction of gravity. In condition of a heavier gravity load (−200 N), the Cross-type winding configuration saves power consumption with a percentage of 17.2% at steady state (20,000 rpm) and 12.7% considering unbalance mass during the run-up process. However, the rotor vibrations of the Cross type in case of external loads and unbalance mass are larger than the Ortho type. The proposed results of this paper provide some useful information for the AMB winding configuration design.
FEM-based transformer design optimization technique with evolutionary algorithms and geometric programming
Authors: Orosz Tamás , Karban Pavel , Pánek David , Doležel Ivo
Published: November 2020

Cost optimization of power transformers is a complex engineering task. The design engineers have to solve this multidisciplinary, non-linear optimization problem in a very short-time. Due to the importance of the topic, numerous optimization methods have been developed in the industry to solve this problem. These methods generally use different, simplified two-winding transformer models, where the windings are generally modeled by their copper filling factors. These models cannot consider the eddy current losses and the temperature gradients of the windings properly, because the calculation of these quantities needs knowledge of the conductor dimensions. This paper proposes a novel method, which uses a general geometric programming search based sub-problem to determine the optimal conductor dimensions for the optimal winding shape. The proposed method considers the temperature gradients of the windings and uses FEM to determine the eddy losses of the windings. The whole optimization process is made by an evolutionary algorithm (NSGA-II)-based search. The paper presents this novel transformer optimization methodology and then illustrates it with a practical example.
For intelligent debugging management of offshore oil engineering with big data
Authors: Liu Chen , Sergeevna Chernova Oksana
Published: November 2020

With the development of science and technology, in the field of oilfield commissioning, the requirements for process management are more and more standardized and scientific, and the requirements for decentralized equipment status detection and maintenance are also higher and higher. It is the hope of any manager to eliminate hidden dangers and prevent them in a timely manner. This paper introduces an intelligent debugging model based on big data. Based on the big data mechanism, the model is divided into different functions according to different functions and requirements. It can ensure the authenticity of debugging data, coordinate all big data work through the big data communication mechanism, and conduct scientific management of debugging data. The model is divided into three levels: data acquisition layer, data transmission layer and control management layer. The offshore oil intelligent debugging platform software based on big data technology is built. A new intelligent debugging method for offshore oil based on big data is presented to study the warning information, fault location and equipment health status of intelligent debugging. Development for Marine oil intelligent debugging applications, for business people to provide intelligent Marine oil intelligent debugging method, provide data support for management decision-making, implementation of the lean management data in the field of intelligent debugging, improving the capacity of intelligent debugging data analysis and mining, effective use of the existing intelligent debugging automation system and other related data in the system, solved the “huge amounts of data, information, the lack of a” awkward situation, improve intelligence debugging application function, meet the demand of intelligent debugging of each department, improve the efficiency of debugging and running reliability and intelligent management.
Improved whale optimization algorithm based on random hopping update and random control parameter
Authors: Guo Yanju , Shen Huan , Chen Lei , Liu Yu , Kang Zhilong
Published: November 2020

Whale Optimization Algorithm (WOA) is a relatively novel algorithm in the field of meta-heuristic algorithms. WOA can reveal an efficient performance compared with other well-established optimization algorithms, but there is still a problem of premature convergence and easy to fall into local optimal in complex multimodal functions, so this paper presents an improved WOA, and proposes the random hopping update strategy and random control parameter strategy to improve the exploration and exploitation ability of WOA. In this paper, 24 well-known benchmark functions are used to test the algorithm, including 10 unimodal functions and 14 multimodal functions. The experimental results show that the convergence accuracy of the proposed algorithm is better than that of the original algorithm on 21 functions, and better than that of the other 5 algorithms on 23 functions.
Multi-scale personnel deep feature detection algorithm based on Extended-YOLOv3
Authors: Liu Shuai , Xu Ying , Guo Lingming , Shao Meng , Yue Guodong , An Dong
Published: November 2020

Tens of thousands of work-related injuries and deaths are reported in the construction industry each year, and a high percentage of them are due to construction workers not wearing safety equipment. In order to address this safety issue, it is particularly necessary to automatically identify people and detect the safety characteristics of personnel at the same time in the prefabricated building. Therefore, this paper proposes a depth feature detection algorithm based on the Extended-YOLOv3 model. On the basis of the YOLOv3 network, a security feature recognition network and a feature transmission network are added to achieve the purpose of detecting security features while identifying personnel. Firstly, a security feature recognition network is added side by side on the basis of the YOLOv3 network to analyze the wearing characteristics of construction workers. Secondly, the S-SPP module is added to the object detection and feature recognition network to broaden the features of the deep network and help the network extract more useful features from the high-resolution input image. Finally, a special feature transmission network is designed to transfer features between the construction worker detection network and the security feature recognition network, so that the two networks can obtain feature information from the other network respectively. Compared with YOLOv3 algorithm, Extended-YOLOv3 in this paper adds security feature recognition and feature transmission functions, and adds S-SPP module to the object detection and feature recognition network. The experimental results show that the Extended-YOLOv3 algorithm is 1.3% better than the YOLOV3 algorithm in AP index.
A new model for coreference resolution based on knowledge representation and multi-criteria ranking
Authors: Hourali Samira , Zahedi Morteza , Fateh Mansour
Published: November 2020

Coreference resolution is critical for improving the performance of all text-based systems including information extraction, document summarization, machine translation, and question-answering. Most of coreference resolution solutions rely on using knowledge resources like lexical knowledge, syntactic knowledge, world knowledge and semantic knowledge. This paper presents a new knowledge-based coreference resolution model using neural network architecture. It uses XLNet embeddings as input and does not rely on any syntactic or dependency parsers. For more efficient span representation and mention detection, we used entity-level information. Mentions were extracted from the text with an unhand engineered mention detector, and the features were extracted from a deep neural network. We also propose a nonlinear multi-criteria ranking model to rank the candidate antecedents. This model simultaneously determines the total score of alternatives and the weight of the features in order to speed up the process of ranking alternatives. Compared to the state-of-the-art models, the simulation results showed significant improvements on the English CoNLL-2012 shared task (+6.4 F1). Moreover, we achieved 96.1% F1 score on the n2c2 medical dataset.
Capsule network with K-Means routingfor plant disease recognition
Authors: Mensah Patrick Kwabena , Weyori Benjamin Asubam , Ayidzoe Mighty Abra
Published: November 2020

Capsule Networks (CapsNets) excel on simple image recognition problems. However, they fail to perform on complex images with high similarity and background objects. This paper proposes Local Binary Pattern (LBP) k-means routing and evaluates its performance on three publicly available plant disease datasets containing images with high similarity and background objects. The proposed routing algorithm adopts the squared Euclidean distance, sigmoid function, and a ‘simple-squash’ in place of dot product, SoftMax normalizer, and the squashing function found respectively in the dynamic routing algorithm. Extensive experiments conducted on the three datasets showed that the proposed model achieves consistent improvement in test accuracy across the three datasets as well as allowing an increase in the number of routing iterations with no performance degradation. The proposed model outperformed a baseline CapsNet by 8.37% on the tomato dataset with an overall test accuracy of 98.80%, comparable to state-of-the-art models on the same datasets.
Segmentation of overlapping chromosome images using U-Net with improved dilated convolutions
Authors: Sun Xiaofei , Li Jianming , Ma Jialiang , Xu Huiqing , Chen Bin , Zhang Yuefei , Feng Tao
Published: November 2020

Chromosome visualization has been used in human chromosome analysis and is a crucial step in clinical diagnosis and drug development. An important step in chromosome visualization is the extraction of chromosomes from chromosome images obtained by light microscopy. Chromosomes often overlap in a complex and variable manner, resulting in significant challenges in chromosome segmentation. The process of chromosome visualization requires manual intervention and is tedious. A method based on a neural network is proposed for the automatic segmentation of overlapping chromosome images to speed up the workflow of visualizing chromosomes. Three improved dilated convolutions are used in the chromosome image segmentation models based on U-Net. The proposed models successfully segment overlapping chromosomes in two publicly available overlapping chromosome data sets. Our models have better performance than existing overlapping chromosome segmentation methods based on U-Net. In summary, it is demonstrated that the improved dilated convolutions can be used for the automatic segmentation of overlapping chromosome images. The proposed improved dilated convolutions have a stable performance improvement, can be easily extended to the segmentation of multiple overlapping chromosomes, and are suitable as general neural network operations to replace standard convolutions in any network.
Identification of Pre-Dominant Coping Types in Patients with Parkinson’s Disease: An Abductive Content Analysis of Video-Based Narratives
Authors: Thomsen Trine Hørmann , Jørgensen Lene Bastrup , Kjær Troels Wesenberg , Winge Kristian , Haahr Anita
Published: November 2020

Background: People with Parkinson’s disease suffer from a range of various symptoms. Altered movement patterns frequently represent the prevailing symptom experience and influence the everyday life of the affected persons. Objective: This qualitative study explores how persons with Parkinson‘s disease experience everyday life with a complex symptom profile and how they manage the consequential challenges in their daily life, as well as the motivation and consequences of these coping behaviours. Methods: Thirty-four patients with Parkinson’s disease were interviewed as an integrated part of the method Video-based Narrative. The interviews were analysed by means of qualitative content analysis according to Graneheim & Lundman. Results: The analysis identified six predominant coping types with different behavioural traits: The convincing behaviour, The economizing behaviour, The encapsulating behaviour, The evasive behaviour, The adaptable behaviour, and The dynamic behaviour. The strategies embedded in each of the six types are diverse, but all participants seek to maintain their integrity in different ways leading to the main motivation “To stay the same person”. Conclusion: Healthcare professionals should be aware of the patients‘ various coping behaviour in order to offer a person-centred approach. Psychoeducational interventions to promote coping skills may be essential in incorporating disease-related changes in the conduct of everyday life with Parkinson’s disease to maintain integrity.
Continuous Subcutaneous Levodopa Delivery for Parkinson’s Disease: A Randomized Study
Authors: Olanow C. Warren ,   for the 006 study group, Espay Alberto J. , Stocchi Fabrizio , Ellenbogen Aaron L. , Leinonen Mika , Adar Liat , Case Ryan J. , Orenbach Shir Fuchs , Yardeni Tami , Oren Sheila , Poewe Werner
Published: November 2020

Background: ND0612 is a continuous, subcutaneous levodopa/carbidopa delivery system in development for patients with Parkinson’s disease (PD) experiencing motor fluctuations Objective: Evaluate the efficacy and safety of two ND0612 dosing regimens in patients with PD. Methods: This was a 28-day open-label study (NCT02577523) in PD patients with ≥2.5 hours/day of OFF time despite optimized treatment. Patients were randomized to treatment with either a 24-hour infusion (levodopa/carbidopa dose of 720/90 mg) or a 14-hour ‘waking-day’ infusion (levodopa/carbidopa dose of 538/68 mg plus a morning oral dose of 150/15 mg). Supplemental oral doses of levodopa were permitted for patients in both groups if required. In-clinic assessments of OFF time (primary endpoint) and ON time with or without dyskinesia were determined by a blinded rater over 8 hours (normalized to 16 hours). Results: A total of 38 patients were randomized and 33 (87%) completed the study. Compared to baseline, OFF time for the overall population was reduced by a least squares (LS) mean[95% CI] of 2.0[– 3.3, – 0.7] hours (p = 0.003). ON time with no/mild dyskinesia (no troublesome dyskinesia) was increased from baseline by a LS mean of 3.3[2.0, 4.6] hours (p < 0.0001), and ON time with moderate/severe dyskinesia was reduced by a LS mean of 1.2[– 1.8, – 0.5] hours (p≤0.001). Reduction in OFF time was larger in the 24-hour group (– 2.8[– 4.6, – 0.9] hours; p = 0.004) than in the 14-hour group (– 1.3[– 3.1, 0.5] hours; p = 0.16). Complete resolution of OFF time was observed in 42% (n = 8) of patients in the 24-hour group. Infusion site reactions were the most common adverse event. Conclusion: This study demonstrates the feasibility and safety of continuous subcutaneous delivery of levodopa as a treatment for PD and provides preliminary evidence of efficacy.
A replication and migration strategy on the hierarchical architecture in the fog computing environment
Authors: Berkennou Ahmed , Belalem Ghalem , Limam Said
Published: November 2020

Connecting objects have increasingly become popular in recent years, leading to the connection of more than 50 billion objects by the end of 2020. This large number of objects will generate a huge amount of data that is currently being processed and stored in the cloud. Fog Computing presents a promising solution to the problems of high latency and huge network traffic encountered in the cloud. As Fog’s infrastructures are dense, heterogeneous and geo-distributed, managing the data in order to satisfy users demand in such context is very complicated. In this work, we propose a data management strategy called ‘RMS-HaFC’ in which we consider the characteristics of Fog Computing environment. To do so, we proposed a hierarchical multi-layer model, on which we designed a migration and replication strategy based on data popularity. These strategies duplicate files dynamically and store them in different locations to improve the response time of users requests and minimize the system energy consumption without loading network usage. The strategy was evaluated using the iFogSim simulator and the experimental results obtained are very promising.
The health effects of quarantine during the COVID-19 pandemic
Authors: Feiz Arefi Maryam , Babaei-Pouya Amin , Poursadeqiyan Mohsen
Published: November 2020

BACKGROUND: Quarantine is considered as an effective solution in the early stages of an epidemic. In the case of the coronavirus epidemic, quarantine was also recommended and implemented as a significant guideline to prevent the disease. However, despite the benefits of quarantine, there are also complications and problems. OBJECTIVE: The present study aimed to investigate the health effects of quarantine during the COVID-19 pandemic. METHODS: This study was conducted as a literature review through searching the databases Google Scholar, PubMed, and Science Direct for papers published before July 2020. The research was conducted based on the keywords “Coronavirus,” “COVID-19,” and “quarantine.” The references of the papers were also reviewed to find the ones not found in the databases. The guidelines published by reputable organizations such as the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) were used in this study. RESULTS: Although quarantine is applied as an important and primary solution in the outbreak of epidemics, in cases of pandemics, it may not be free of negative effects on individuals and public health. However, because of the need to reopen and restart social and economic activities, some changes should be made in lifestyles and work activities. Using cyberspace and telework can be helpful. As the findings showed, COVID-19 bubbles can be used to restore social communications. CONCLUSION: Using masks, avoiding unnecessary gatherings, complying with personal and social hygiene, and respecting social distancing can be valuable solutions that, if implemented properly, can decrease the rate of the disease significantly. It is also emphasized that quarantine is still necessary and important as the best solution for sick people and individuals who are suspected carriers of the disease.
Activity-based working: Qualitative analysis of working conditions and health-related outcomes
Authors: Fincke Isabelle , Hieb Amy , Harth Volker , Mache Stefanie
Published: November 2020

BACKGROUND: The changing of work, driven by digitization, leads to the demand of large, open spaces in which the employees can work alone or in teams, can hold meetings or even find corners to relax. OBJECTIVE: This study empirically analyzed job demands and resources that can be found in innovative office concepts, like so called “activity-based working concepts”. METHODS: 16 semi-structured face-to-face interviews were performed with employees working in activity-based offices. Content of the interviews included questions on their working conditions and health-related outcomes. RESULTS: The results show that work autonomy, the flexibility to decide where and when to work, and an improved communication and collaboration between different departments had a perceived positive effect on well-being, performance and motivation. Job demands, like missing territoriality on individual and team level, limited privacy and distractions in form of noise and interruptions describe consequences in form of perceived strain. CONCLUSION: The study results contribute to the expansion of knowledge in the subject area of flexible work arrangements in open work spaces. They can serve to design future working environments and thus increase the well-being and job performance of employees. It needs additional research to investigate the effects of office designs on the health of employees in the long term.
Effects of vehicular whole-body vibration on focus measured by a mobile app for brain training: A pilot study on the influence of gender and Attention Deficit Hyperactivity Disorder
Authors: Duarte Maria Lúcia Machado , Costal Glauber Zerbini , Martinelli Sthéfani Ferreira , Neves Jorge Alexandre Barbosa
Published: November 2020

BACKGROUND: Students, as well as other professional drivers, must have focus to adequately perform their tasks. However, they are subjected to whole-body vibration (WBV) in their journey to school or work. OBJECTIVE: To investigate the influence of in-loco WBV exposure on focus, both instantaneously, as well as residually. Analysis is performed for both genders, as well as for the presence of Attention Deficit Hyperactivity Disorder (ADHD). METHODS: Using a tablet computer, 20 volunteers played a focus game available on an app for brain training while exposed or not exposed to WBV. The exposure was that of a car travelling on a stone paved route. The performance measure was the score provided at the end of each game. Subjective comfort and difficulty evaluations were also investigated. RESULTS: The results suggest that WBV had a negative effect on the focus performance. However, it proved positive three minutes after the exposure (residual effect). The mean scores of females were higher than for males for most of the tests, apart from the one under WBV although at the expense of getting more discomfort. The difficulty level was not different within the gender groups. CONCLUSION: It could be concluded that the group with ADHD had a small but positive influence on the results for most of the tests, indicating that they are less affected by the presence of WBV. Since many students and workers have ADHD, this may be considered an important finding. It was shown that objective results should not be the only measures to use, as the subjective evaluation may explain the results better.
Work analysis tool for higher education: Development and validation of the german student measure WA-S Screening
Authors: Strecker Cornelia , Höge Thomas , Brenner Mirjam , Huber Alexandra , Hausler Melanie , Höfer Stefan
Published: November 2020

BACKGROUND: Work demands, resources and stressors affecting health, well-being and motivation also exist in the work of university students. There is a shortage of measures for analyzing work characteristics in this setting. OBJECTIVE: This article addresses that shortage of measures and describes the development and the validation of the short Work Analysis Measure for Students (WA-S Screening). METHODS: In study 1 (N = 422 students in Austria) the final version of the measure was developed based on analyzing the factor structure and psychometric properties of items and scales. Study 2 (N = 333 German-speaking students in Germany, Austria and Switzerland) was conducted for a cross validation and analyzing the criterion validity. RESULTS: An eight-scale structure of the WA-S Screening was supported in study 1 and 2. The scales have shown to be significantly associated with burnout and work engagement in study 2. CONCLUSIONS: The examinations indicate that the WA-S Screening is a short, reliable and valid instrument to identify critical, health-promoting work characteristics in the context of studying at university.
The association of smoking status with SARS-CoV-2 infection, hospitalisation and mortality from COVID-19: A living rapid evidence review with Bayesian meta-analyses (version 9)
Authors: Simons David , Shahab Lion , Brown Jamie , Perski Olga
Published: November 2020

AIMS: To estimate the association of smoking status with rates of i) infection, ii) hospitalisation, iii) disease severity, and iv) mortality from SARS-CoV-2/COVID-19 disease. 

DESIGN: Living rapid review of observational and experimental studies with random-effects hierarchical Bayesian meta-analyses. Published articles and pre-prints were identified via MEDLINE and medRxiv.

SETTING: Community or hospital. No restrictions on location.

PARTICIPANTS: Adults who received a SARS-CoV-2 test or a COVID-19 diagnosis.

MEASUREMENTS: Outcomes were SARS-CoV-2 infection, hospitalisation, disease severity and mortality stratified by smoking status. Study quality was assessed (i.e. ‘good’, ‘fair’ and ‘poor’).

FINDINGS: Version 9 (searches up to 27 October 2020) included 279 studies with 42 ‘good’ and ‘fair’ quality studies included in unadjusted meta-analyses. Seventy-nine studies (28%) reported current, former and never smoking status with the remainder using broader categories. Recorded smoking prevalence among people with COVID-19 was generally lower than national prevalence. Current compared with never smokers were at reduced risk of SARS-CoV-2 infection (RR = 0.69, 95% Credible Interval (CrI) = 0.57-0.83, τ = 0.38). Data for former smokers were inconclusive (RR = 1.02, 95% CrI = 0.93-1.12, τ = 0.18) but favoured there being no important association (5% probability of RR ≥1.1). Former compared with never smokers were at somewhat increased risk of hospitalisation (RR = 1.17, CrI = 1.04-1.36, τ = 0.17), greater disease severity (RR = 1.52, CrI = 1.12-2.06, τ = 0.29) and mortality (RR = 1.39, 95% CrI = 1.16-1.69, τ = 0.23). Data for current smokers on hospitalisation, disease severity and mortality were inconclusive (RR = 1.06, CrI = 0.89-1.27, τ = 0.23; RR = 1.26, CrI = 0.86-1.94, τ = 0.34; RR = 1.05, 95% CrI = 0.71-1.49, τ = 0.45, respectively) but favoured there being no important associations with hospitalisation and mortality (32% and 39% probability of RR ≥1.1, respectively) and a small but important association with disease severity (80% probability of RR ≥1.1). 

CONCLUSIONS: Compared with never smokers, current smokers appear to be at reduced risk of SARS-CoV-2 infection while former smokers appear to be at increased risk of hospitalisation, greater disease severity and mortality from COVID-19. However, it is uncertain whether these associations are causal.

v7 of this living review article has been published in _Addiction _and is available here https://doi-org.libproxy.ucl.ac.uk/10.1111/add.15276
Automatic Shopping Trolley Using IoT
Authors: A Lohabade Shivani , J Pathan Tanzila , S Hasija Shawni , S Patil Sachin
Published: November 2020

Nowadays activities such as shopping at big malls is really increasing in various cities. We can see huge crowd at the shopping malls on public holidays ,weekends and specially during the festivals which can cause rush at the billing counters. After purchasing the products the customers need to wait in long queues at the billing counter for payments. At billing counter the cashier needs to scan each product using barcode scanner for calculating the amount of product to generate a bill which is very time consuming. In this project, we are going to implement the RFID card scanner on the trolley itself and an automatic billing system in the shopping malls using the WI-FI to transfer the data into the database . The structure of the trolley consists of a door which will block the products to be entered without scanning for security purpose. The trolley has the inbuilt product code reader. The use of product code reader is to read the RFID cards/tags attached to all products to define the name ,weight ,quantity and price of the products. Depending on the signal from the reader, the controller display the name and price of the each product on the LCD display. The wireless billing system is uses the Wi-Fi for data transfering to the cashier . A load cell has been attached so that even if the RFID is not read, the weight of the product is also been measured. If the weight of the products appears to be more than displayed on the LCD screen product code reader then an error message in billing system so that bill can be generated only for the scanned products.
Effective Methodology for Co-Referential Aspect Based Sentiment Analysis of Tourist Reviews
Authors: A. Waghmare Kamlesh , K. Bhala Sheetal
Published: November 2020

Tourist reviews are the source of data that is going to be used for the travelers around the world to find the hotels for their stay according to their comfort. In this the hotels are ranked over the parameters or aspects considered keeping travelers in mind. This computation of data sets is done with the help of the machine learning algorithms and the neural network. The knowledge processing done over the reviews generates the sentiment score for each hotel with respect to the aspects defined. Here, the explicit , implicit and co-referential aspects are identified by suppressing the noise. This paper proposes the method that can be best used for the detection of the sentiments with the high accuracy.
A Novel Based 3d Facial Expression Detection Using Recurrent Neural Network
Authors: K S Jaswanth , David D. Stalin
Published: November 2020

People periodically have diverse facial expressions and disposition changes in this way. Human facial expression acknowledgment plays a really energetic part in social relations. The acknowledgment of feelings has been an dynamic breakdown point from early age. The real-time location of facial expressions like appall, upbeat, pitiful, irate, anxious, astonish. The proposed framework can recognize 6 diverse facial expression. A facial expression acknowledgment framework needs to perform location and change to 3D image, then the facial highlight extraction, and facial expression classification is worn. Out proposed strategy we should be utilizing Recurrent Neural Network (RNN). This RNN show is prepared on JAFEE and Yale database dataset. This framework has capacity to screen individuals’ feelings, to segregate between feelings and name them fittingly.
Automated Timetable Generation
Authors: Tanksali Prajakta , Dhond Ila , Pednekar Shivani , Singbal Varshanda , Sivaraman Shruti
Published: November 2020

A STUDY ON AUTOMATIC TIMETABLE GENERATOR Akshayputtaswamy, H M Arshad Ali Khan, Chandan S.V, Parkavi.A Department of Computer Science and Engineering, M S Ramaiah Institute of Technology,Bangalore ://www.researchgate.net/publication/326265336_A_STUDY_ON_AUTOMATIC_TIMETABLE_GENERATOR

International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at:www.ijarcsse.com Automatic Time Table Generator 1 Saritha M, 2 Pranav Kiran Vaze, 3 Pradeep, 4Mahesh N R 1Assistant Professor, 2, 3, 4 UG Scholar 1, 2, 3, 4 Department of CSE, SDMIT Ujire, Karnataka, India https://www.researchgate.net/publication/326265336_A_STUDY_ON_AUTOMATIC_TIMETABLE_GENERATOR

International Journal of Scientific & Engineering Research Volume 9, Issue 4, April-2018 31 ISSN 2229-5518 IJSER © 2018 http://www.ijser.org Automated college timetable generator Adithya R Pai, Ashwitha S, Raksha Shetty, Prof.Geethalaxmi https://www.ijser.org/researchpaper/Automated-college-timetable-generator.pdf

Automatic Timetable Generation System 1Deeksha C S, 2A Kavya Reddy, 3Nagambika A, 4Akash Castelino, 5K Panimozhi 1,2,3,4UG Student, 5Assistant Professor 1Dept. of Computer Science and Engineering, 1BMSCE, Bangalore, India. http://www.jetir.org/papers/JETIR1504029.pdf
The analysis of the parenting implications on the emotional closeness of parent-child improvement
Authors: Ardi Zadrian , Aulia Galang Zaki
Published: November 2020

The development of science and knowledge and the structure of society has had various impacts on the order of social life. No exception influences the smallest organization, namely the family. The model and parenting patterns of the previous generation (the baby boomers’ generation) are significantly different from the next generation. Of course, this also causes differences in the results and impacts obtained. However, the issues related to parenting tend to remain the same. One parenting that is often used is authoritarian parenting, in which parent’s tom much impose his will on the child as desired. This makes children become depressed so that the proximity of the child with parents rift or loose. The purpose of this study is to analyze the implications of parenting conditions and its various characteristics in building closeness between parents and children.
Analisis Keterlambatan Rekapitulasi Penghitungan Suara di KPU Kabupaten Deli Serdang dan KPU Kabupaten Nias Selatan Pada Pemilu Tahun 2019
Authors: Dana Permana  , Fernanda Putra Adela
Published: November 2020

Permasalahan keakuratan dan ketepatan waktu dalam penghitungan suara menjadi hal yang penting dalam setiap diskursus Kepemiluan. Pengalaman keterlambatan penghitungan suara di beberapa daerah termasuk di Sumatera Utara pada Pemilu 2019 menjadi pelajaran penting. Tulisan ini menganalisis keterlambatan proses rekapitulasi di 2 daerah di Sumatera Utara yakni Kabupaten Nias Selatan dan Kabupaten Deli Serdang. Metode penelitian yang digunakan adalah penelitian kualitatif dengan analisis deskriptif hasil temuan dari penelitian ini yakni Keterlambatan rekapitulasi di 2 daerah tersebut memiliki kesamaan dan juga perbedaan. Kesamaannya adalah bahwa Proses keterlambatan di beberapa Kecamatan di masinbg-masing daerah dikarenakan permasalahan teknis penghitungan suara ditingkat KPPS. Hal ini disebabkan kurang ketelitian pada saat pengisian formulir rekapitulasi penghitungan suara. Perbedaannya di Kabupaten Nias Selatan disebabkan permasalahan integritas penyelenggara sedang di Kabupaten Deli Serdang disebabkan oleh Kapasitas penyelenggara.
Farmacoterapia aplicada à COVID-19
Authors: Gonçalves Emanuella Dutra , Justiniano Ana Luisa Marossi , Freitas Camila de Carvalho e , Abrame Éttore Eduardo Simensato , Reinaldi João Remesso Ferreira , Matos Laura Ribeiro de
Published: November 2020

A epidemia da Doença do Coronavírus (COVID-19) causada pelo vírus SARS-CoV-2 teve início em dezembro de 2019 em Hubei, China, e rapidamente alcançou proporções mundiais, levando a Organização Mundial da Saúde (OMS) a declarar surto pandêmico em março de 2020. Por tratar-se de uma doença potencialmente grave e muito recente, ainda não foram estabelecidos tratamentos baseados em evidências científicas sólidas. Diante disso, o presente artigo consiste em uma revisão narrativa sobre as principais drogas propostas para o tratamento da doença e seus respectivos mecanismos de ação, bem como alguns dos ensaios clínicos já realizados. Para isso, foi feito um levantamento de publicações no banco de dados das bibliotecas eletrônicas Google Scholar, PubMed e BVS, entre maio e agosto de 2020. De modo geral, Cloroquina/Hidroxicloroquina, Azitromicina, Nitazoxanida, Remdesivir, heparinas e dexametasona apresentam resultados satisfatórios no combate a várias infecções virais e sugerem ações semelhantes no SARS-CoV-2, in vitro, porém os resultados dos ensaios clínicos ainda são controversos. Até o momento, a heparina de baixo peso molecular, o Remdevisir e a dexametasona foram aprovados para utilização em situações específicas, a fim de amenizar complicações clínicas. No entanto, mais estudos deverão ser realizados a fim de determinar uma farmacoterapia assertiva.
Application of Mitscherlich-Bray equation to formulate fertilizer recommendations for sweetpotato in Leyte, Philippines
Authors: Asio Luz , de la Cruz Nenita
Published: November 2020

Until now, no studies have been conducted in the Philippines on the use of the Mitscherlich-Bray equation to formulate NPK fertilizer recommendation for sweetpotato. This study used the Mitscherlich-Bray equation to formulate NPK requirements for sweetpotato. Independent experimental set-ups of N (7 application levels), P (6 levels), and K (9 levels) arranged in RCBD with three replications were simultaneously conducted. Theoretical maximum yield, NPK constants c, and c, NPK fertilizer recommendations for sweetpotato at different soil fertility levels, and optimum fertilizer rates were calculated. Fertilizer recommendations for a common range of soil test values were developed but needed further field verification trials. Theoretical maximum yields determined by the Mitscherlich-Bray equation were 19.05, 12.66, and 14.88t ha-1 for NPK, respectively. The study showed that inherent soil fertility is vital in the development of fertilizer recommendation for sweetpotato not only to increase root yield but likewise to increase overall productivity. It showed that 30, 50, and 60 percent of the maximum possible yield was attributed to the inherent soil N, P, and K, respectively. N, P2O5, and K2O recommendations for sweetpotato were computed based on a common range of soil test values ranging from 50 to 300, 5to 40, and 200 to 700kg ha1 NPK, respectively.
Planktonic algae as bioindicators of water quality in Pagbanganan River, Baybay City, Leyte
Authors: Seriño Eunice Kenee , Belonias Beatriz
Published: November 2020

Biological monitoring is a valuable method used in conservation studies to protect and preserve the biological integrity of natural ecosystems. This study was conducted to assess the water quality of the Pagbanganan River using planktonic algae as bioindicators of organic pollution. Horizontal tows were made in three selected stations (upstream, midstream & downstream) using a Wisconsin plankton net with 80pm mesh size. Collected samples were preserved with Lugol’s solution and 70% ethyl alcohol. Identified phytoplankton genera were analyzed using Palmer’s Pollution Index. Out of the 20 pollution indicator genera identified by Palmer (1969), 10 were present in Pagbanganan River, namely; Ankistrodesmus, Closterium, Cyclotella, Gomphonema, Melosira, Navicula, Nitzschia, Oscillatoria, Stigeoclonium and Synedra. Four of these were among the most abundant algae in the river. Mean Palmer’s Pollution Index Scores indicate that there is “less” organic pollution existing in the river. Results imply that the river is still relatively safe for general household use, but effective conservation measures should be done to preserve the integrity of the river ecosystem.
Is there a market power in the Philippine Rice Industry?
Authors: Bellezas Maria Hazel , Yorobe Jose , Paduayon lsabelita , Gordoncillo Prudenciano , Alcantara Antonio
Published: November 2020

Rice, as a staple food for the Filipinos, is widely studied from production to consumption. However, observations of the National Food Authority domestic procurement and price stabilization policy, as well as results of the marketing and market-related studies, still reveal some gaps which call forth for an in-depth investigation and analysis. One ofthese is the possible presence ofmarket power, a market inefficiency in rice. Hence, this study aimed to ascertain the presence of market power in the Philippine rice industry. Secondary data published by the Philippine Statistics Authority from 1990 to 2015 were utilized. A structural econometric model using a time series approach was used in estimating the presence of market power. Results revealed the presence of market power in non-major rice-producing regions for well-milled and regular-milled rice in major rice-producing areas. The more the demand curve becomes inelastic the more the market power becomes apparent. The price elasticity of demand in the non-major rice-producing regions is -0.63 for both well-milled and regular-milled rice and -0.83 and -0.59, respectively, in the major rice producing areas. To minimize, if not solve market power, a substitute staple for rice may be introduced, programs/policies that will encourage more palay traders may be implemented, and farmers may be trained to operate like industry clusters.
BİLİŞİM SİSTEMİNE GİRME SUÇUNUN YARGI KARARLARI BAĞLAMINDA İNCELENMESİ
Authors: İHTİYAROĞLU Uğur
Published: November 2020

Bilişim alanında 1990’lı yıllardan itibaren yaşanan gelişmeler bilgiye ve veriye ulaşma hızını hayal edilemeyecek derecede arttırmıştır. Bilişim teknolojileri insan hayatını kolaylaştırmakla birlikte toplumlar ve bireyler üzerinde tehlike oluşturabilecek bir silah haline de dönüşmüştür. Bilgisayar, cep telefonu ve internetin her alanda kullanımının yaygınlaşması, bu teknolojiler üzerinden suç işlenmesini kolaylaştırmaktadır. Bilişim suçlarının sürekli yaygınlaşması nedeniyle dijital sistemlerin ve verilerin korunması gerekliliği ortaya çıkmıştır. Bu nedenle bilişim sistemleri kullanımı yoluyla işlenen suçlar için ayrı düzenlemeler bulunması günümüz hukuk sistemleri açısından zorunludur. Bu çalışmanın amacı 5237 sayılı Türk Ceza Kanunu’nun (TCK) 243. maddesinde yer alan “Bilişim Sistemine Girme” suçunu yargı kararları ışığında incelemektedir. Türkiye’de bilişim sistemine girme suçunun yasal boyutu, ihlal koşulları, mukayeseli hukuk örnekleri, Bölge Adliye Mahkemeleri ve Yargıtay uygulamaları çalışmada analiz edilmiştir.
Financial consulting: trends and features of development in Ukraine
Authors: Pavlykivska O. , Plekan U.
Published: November 2020

The essence of consulting is investigated in this paper. Historical aspects of development and current trends in the consulting services market in Ukraine are considered. Approaches to consulting classification are given. Ukrainian consulting is at the stage of development, the prospects for further rooting in this industry depend on the process of stabilization of market relations in Ukraine in general. The consulting market is growing quantitatively and professionally. Significant growth in demand in the field of tax consulting and tax risk management is predicted. In this paper the authors reveal the signs of consulting activities in Ukraine. According to the authors point of view, the most balanced structure of consulting services is that offered by the European Directory of management consultants which combines all types of services into 8 groups: general management, administration, financial management, personnel management, marketing, organization of production, information technologies and special services, particularly, training consulting, consulting on power management, telecommunications, small business consulting, engineering consulting, etc. The segmentation of the consulting services market in Ukraine by functional purpose is reflected. The following key clients of consulting services in Ukraine are identified: metallurgical, chemical, food industry, telecommunication, civil engineering, financial sectors, trade. Since financial consulting is becoming more and more popular in Ukraine, features of this type of consulting are given in this paper. The role of financial consulting in the consulting system is highlighted. Peculiarities of financial consulting application are defined. Restraining factors of financial consulting application are given, the main ones are as follows: imperfection of regulatory and legal support; low level of trust in consulting companies; disinterest or resistance of the customer organization employees; unclear and opaque pricing for financial consulting services to customers; difficulties with reliable assessment of the effectiveness and efficiency of provided consulting services; lack of social perception of consulting as a profession and business by potential consumers; low solvency of customers. According to the authors point of view, financial consulting services support the sustainable development of business structures. Further development of the market of consulting services should meet current demands of domestic business structures and should meet international standards.