bluuebunny/crossref_metadata_2025 huggingface dataset:
Smells Like Animal Spirits: The Effect of Corporate Sentiment on Investment
Authors:   Reserve Bank of Australia, La Cava Gianni
Published: November 2021

Economists have long been interested in the effect of business sentiment on economic activity. Using text analysis, I construct a new company-level indicator of sentiment based on the net balance of positive and negative words in Australian company disclosures. I find that company-level investment is very sensitive to changes in this corporate sentiment indicator, even controlling for fundamentals, such as Tobin's Q and expected profits, as well as controlling for measures of company-level uncertainty. I explore the mechanisms that link investment to sentiment. The conditional relationship could be because sentiment proxies for private information held by managers about the future prospects of the company or because of animal spirits among managers relative to investors. I find that the effect of sentiment on investment is relatively persistent, which is consistent with the private information story, albeit less persistent than other news shocks, such as Tobin's Q. But the effect of sentiment on investment is not any stronger at 'opaque' companies in which managers are likely to be better informed than investors, which argues against the private information story. Corporate investment has been weak in Australia since the global financial crisis (GFC) and demand-side factors, such as lower sales growth, explain more than half of this persistent weakness. Low sentiment and heightened uncertainty weighed on investment during the GFC but have been less important factors since then.
Impact of Conflict Induced Displacement on Primary and Secondary Schooling in Pakistan
Authors: Ullah Anayat , Abbas Syed Hasnain Ali , Shah Faryal , Orakzai Muneer Khan
Published: November 2021

Abstract

The impact of armed conflict on primary and secondary schooling is very hazardous and apparent. Since, 2001 the conflict has made millions of people displaced in the form of Internally Displaced Persons (IDPs) mainly from Tribal Areas on western border with Afghanistan to the settled areas within Pakistan. This research addressed the impact of internal conflict on primary and secondary level school children during displacement at Jalozia camp, Khyber Pukhtoonkhwa. For that reason, the household survey was conducted at Jalozai IDPs camp. The survey results indicate that conflict induced displacement has negatively impacted the level of schooling both at primary and secondary level. However, the impact is more hazardous for secondary schooling. Due to some socio-economic and cultural constraints, mostly female students were dropout of schools at secondary kevel. In addition, conflict affected the socio-economic status of the marginalized displaced people which either way affected the schooling of displaced children.  

 

Key words:    Conflict; Displacement; Schooling; Socio-Economic Status; Pakistan
A Solution to Tough Logging Conditions (Lwf): Intro to Tough Logging Conditions, Logging While Fishing, Operation Procedure and Conditions
Authors: Williams G. Bob , Bora Purabi , Sahu Omprakash
Published: November 2021

This review work summarised new generation logging techniques such Tough Logging Conditions (TLC) & Logging While Fishing (LWF) and their advancement in drilling operations. The production of Oil & gas from the stage of exploration to production should need a lot of data for economic and safe operations. The conditions of the sub-surface cannot be simply predicted unless with some measured parameters under the LOGGING term. Logging is defined as a continuous record of Petro’s physical parameters of rock against time and depth. Instead of conventional logging techniques of wireline such as SP, Gamma-ray, Neutron, Calliper log, etc, logging while drilling, logging while fishing set them aside of their extended applications. Logging while Fishing is a new generation technology that allows unfailing operations of logging tool by a special installation even in cut and thread operation also aids economic and time enhancement. Tough logging conditions are a technique applied either when the hole has highly deviated or when you need to control the position of a tool. This project includes the study and interpretation of above discussed new generation logs. These tools offer all types of logging carried out on wireline except the SP logging. Logging while drilling provides real-time measurements of physical parameters while drilling operation itself which avoids an additional running of tools causing trips and sticking of drill pipe. The data is stored in the bottom assembled logging tool.
Indications and types of hysterectomy in the National Referral Hospital of Bhutan, 2020
Authors: Dorji Namkha , Zangmo Kencho , Tshering Sangay , Mongar Renuka , Sonam Sonam
Published: November 2021

Introduction: Hysterectomy, the removal of uterus, is a major gynecological surgery performed in Bhutan. It is performed for both benign and malignant gynecological conditions. This study was conducted to assess the socio-demographic profiles, types of hysterectomies and their indications, and duration of surgery and duration of peri-operative hospital stay among women who had hysterectomy at the national referral hospital of Bhutan. 

Method: This was a retrospective study conducted at the Jigme Dorji Wangchuck National Referral Hospital, Thimphu. Data of women, who had hysterectomy from 1st January to 31st December, 2020 was extracted into a structured questionnaire by investigators from the patients record maintained at the record section, JDWNRH. Ethical approval was sought from the Research Ethics Board of Health. Data were entered into EpiData 3.1 and was analyzed using descriptive commands of STATA 13.1

Result: Hysterectomy comprised of 9.8% of gynecological surgery in 2020. The commonest route of approach was total abdominal hysterectomy which comprised of 81.7% of hysterectomies. It was found out that 92.9% of hysterectomies were performed under general anesthesia and 97.4% of the surgeries were done as elective or planned cases. The mean (+SD) duration of surgery from skin incision to closure was shortest for vaginal hysterectomy (68.8 + 17.6 minutes) and longest for total laparoscopic hysterectomy (210 + 35.2 minutes). The duration of peri-operative hospital stay was shortest for vaginal hysterectomy.

Conclusion: Total abdominal hysterectomy was the common approach despite vaginal hysterectomy being performed under regional anesthesia with shorter duration of surgery and shorter hospital stays.
Incidental diagnosis of Herlyn-Werner-Wunderlich Syndrome in a nulliparous woman: a case report in Bhutan
Authors: Sonam Dhrupthob , Pradhan Geeta , Tshomo Ugyen
Published: November 2021

Herlyn-Werner-Wunderlich syndrome (HWWS) is a rare congenital syndrome with features of uterus didelphys, ipsilateral absent kidney and obstructed hemivagina. Ultrasound findings of absent kidney or abnormalities in the kidney should alert the clinicians about the syndrome. Complications like endometriosis, infertility and pelvic inflammation occurs with late diagnosis.A 42-yearold nulliparious married woman who presented with right sided abdominal pain to the National Referral Hospital was diagnosed to have HWWS. The diagnosis was supported by ultrasound, CT and MRI findings. Patient was treated for endometriosis and had symptomatic improvement. The diagnosis of the syndrome is challenging as it is rare but clinicians should suspect the syndrome in women who present with infertility. Ultrasound scan is the basic investigation to screen the syndrome which is available in most hospitals.
Supply Chain Management: A Game Changer in the Oil and Gas industry in Nigeria: A Review of Literature
Authors: Akintokunbo Oluwarotimi Odunayo , Arimie Biebele Emmanuel
Published: November 2021

Nigeria has abundant deposit and supply of accessible crude oil and gas resources and it remains the mainstay of her economy. The oil and gas industry in Nigeria is a part of the global oil and gas market which depends on effective and efficient supply-chain management system for the seamless procurement of goods and services (domestic and international), logistics, operations and production management, warehousing, storage of goods from organisations supplier’s suppliers to the customer’s customers with the help of adequate use of modern information and communication technology. The purpose of this study was to examine supply chain management: a game changer in the oil and gas industry in Nigeria. The paper is largely a literature review, hence a desk research methodology was adopted. The paper revealed that the industry offers a classic model for changing the competition game in the sector through a lean, innovative and environmentally sustainable integrated supply chain management system, as today’s competition is no longer between organizations, but among supply chains that compete to reduce their cost of acquisition, production, logistics and warehousing along the chain while delivering customers products and services of quality at the right time, quantity and quality, at the right place and total cost, and creating value throughout the chain.
Konsep Rumah Sehat Sederhana terhadap Kenyamanan Ruang (Studi Kasus: Rumah Tipe 18/24, 22/36 & 36/72 di DKI Jakarta)
Authors: Dwiyan Delyuzir Randy
Published: November 2021

Penelitian ini bertujuan untuk memberikan solusi desain pada penelitian sebelumnya berjudul analisa rumah sederhana sehat terhadap kenyamanan ruang, dimana studi kasus yang diteliti 3 tipe rumah tangga di DKI Jakarta (18/24, 22/36 & 36/72), berdasarkan hasil penelitian ditemukan masalah pada tipe 18/23 & 22/36 terdapat pada area dapur yang belum memiliki sarana pembuangan asap sesuai standard Kepmenkes, 1999. Sehingga alternatif desain yang diberikan berupa penambahan exhaust fan dan perencanaan ulang tata letak dapur. Masalah yang timbul pada bangunan tipe 36/72 terletak pada posisi penataan perabot yang kurang baik, sehingga sirkulasi menuju kamar tidur dan kamar mandi menjadi sempit. Untuk mengatasi masalah tersebut usulan solusi yang ditawarkan berupa penggunaan perabot dengan konsep compat furniture sehingga penataan perabot menjadi lebih irit tempat dan lebih fleksibel.
Manajemen Pengelolaan Kawasan Bersejarah di Desa Soditan, Lasem, Rembang
Authors: Kurniawati Wakhidah , Susanti Retno , . Nurini , Kurniati Rina , Sutomo Sugiono , Islami M. Rizki
Published: November 2021

Desa Soditan merupakan salah satu desa warisan sejarah yang terletak di pusat Kecamatan Lasem, Kabupaten Rembang, Jawa Tengah. Desa Soditan terletak di sepanjang Sungai Babagan Lasem dan Jalur Pantura yang dahulu disebut sebagai jalan raya pos De Groote Post Weg yang dibangun oleh Daendels. Di desa ini terdapat kawasan heritage Pecinan dengan Klenteng Cu An Kiong-nya, rumah candu Lawang Ombo, budaya khas Kopi Nglelet dan Batik Lasem. Saat ini kawasan bersejarah ini mengalami masalah degradasi fungsi, rusaknya bangunan khas Cina, dan semakin hilangnya sense of place kawasan. Untuk itulah, penelitian ini bertujuan untuk merumuskan konsep manajemen pengelolaan kawasan berdasar karakteristik khas kawasan. Adapun tahapan yang dilakukan dalam penelitian ini adalah mengeksplorasi potensi masalah Desa Soditan terkait pengembangan kawasan bersejarah, dan merumuskan konsep manajemen pengelolaan kawasan yang sesuai. Konsep manajemen pengelolaan yang yang ditawarkan adalah kemitraan antara pemerintah, swasta, dan masyarakat. Dari konsep manajemen pengelolaan yang disusun diharapkan dapat mendukung pelestarian cagar budaya di Desa Soditan di sektor pariwisata, memperkuat sense of place kawasan bersejarah, serta mampu mendukung perekonomian daerah dan masyarakat lokal.
Optimisation of pelvic imaging radiography protocols in plain radiology: a scoping review
Authors: Matjašič Alenka , Mekiš Nejc
Published: November 2021

Introduction: The purpose of this work is to explore which studies have been performed in the field of radiation dose reduction in pelvic x-ray imaging and to determine optimization techniques for dose reduction.Materials and methods: A scoping review was performed by using databases Science Direct, PubMed, EBSCO Host and Springer Link. The keywords used were "radiography", "dose reduction", "pelvis" and "pelvic". Exclusion criteria were the keywords "CT" and "MRI".Results: 15 scientific articles that analyse the current dose impacts in selected institutions or regions were reviewed as a starting point to optimise protocols, to establish diagnostic reference levels, or to suggest different measures for dose reduction. Studies suggest the use of digital image receptor, adaptation of exposure parameters; they also point out the use of air gap instead of radiographic grid and investigate the usefulness of the gonad protection. A difference was noticed in developing countries that focus more on the establishment of DRLs and following the guidelines provided by other countries rather than developing new dose optimisation techniques.Conclusion: A pelvic x-ray must be performed with a low radiation dose impact that still doesn't compromise the diagnostic value of the image, which can be achieved by following the ALARA principle and with certain adjustments, suggested by the considered studies, especially with exposure parameters. The establishment of national and local diagnostic reference levels is also required.
Frequency of various forms of spondylodiscitis on spinal column segments
Authors: Kajmaković Aldin , Kožo Kajmaković Azra , Čorović Kuburović Jasmina
Published: November 2021

Introduction: The term spinal infections or spinal column infections usually include processes localized in various parts of spinal column, parts of vertebrae as well as in intervertebral disc. There are three main types of spondylodiscitis. Bacterial spondylodiscitis (vertebral osteomyelitis) is inflammatory process usually involving two (neighboring) vertebrae and intervertebral disc causing the space for the disc between the vertebrae to be narrowed down. The aim of this paper is to present the frequency of various forms of spondylodiscitis on spinal column segments following laboratory, microbiological and radiological diagnostic procedures.Patients and methods: Descriptive research method was used in the work, as it was deemed appropriate for this type of research analysis. Diagnostic procedures used include: laboratory tests, microbiological analysis, MRI scans of cervical spine, MRI scans of thoracic spine, MRI scans of L/S spinal column.Results: Out of 307 patients included in the research, in 109 occurrences spondylodiscitis was verified on various parts of spinal column. Brucellosis spondylodiscitis represents the most frequent form (in 86% of patients), and the majority of occurrences was localized at lumbosacral part of spinal column. During the research, quite unusually, there was also one occurrence of spondylodiscitis with paravertebral abscess on cervical part of spinal column. It is also a type of brucellosis spondylodiscitis. The use of magnetic resonance imaging appears to be gold standard in diagnostics of spondylodiscitis, especially following the application of contrast agent and the use of T1 FS (fat saturation) sequences along with standard tomograms in times T1 and T2. The majority, up to 262 (85.3%) of Elisa tests were related to brucellosis. In 245 out of 307 cases, the result was positive, that is in direct relation to the fact that various forms of brucellosis are present in the areas being examined.Conclusion: Research results indicated that spondylodiscitis was diagnosed in all segments of spinal column. The most frequent occurrences are on L/S part of spinal column and the most frequent form of brucellosis is spondylodiscitis.
De toelichting over impairment testing onder NL GAAP
Authors: Brouwer Arjan , de Graaff Gijs , van Oosterbosch Renick
Published: November 2021

In dit artikel doen we verslag van de informatieverschaffing over impairment testing onder NL GAAP. Het onderzoek is uitgevoerd onder grote ondernemingen met een relatief hoog bedrag aan immateriële vaste activa. De verwachting was dat de COVID-19-crisis en de resultaatontwikkeling bij een groot deel van de onderzochte ondernemingen aan te merken is als een aanwijzing dat activa aan een bijzondere waardevermindering onderhevig kunnen zijn. Echter, we treffen in veel gevallen geen of beperkte informatie aan over de uitgevoerde triggering events-analyse en de uitgevoerde impairment tests. Het lijkt er dan ook op dat niet veel ondernemingen de toelichting in de jaarrekening 2020 hebben aangepast naar aanleiding van de in 2020 ontstane situatie.

De ondernemingen die de meest omvangrijke impairments hebben verantwoord in 2020 hebben wel een meer uitgebreide toelichting opgenomen over de uitgevoerde impairment tests, inclusief de gehanteerde veronderstellingen. Op basis van het onderzoek concluderen wij dat ondernemingen meer aandacht kunnen besteden aan de belangrijke schattingen die in een specifiek jaar relevant zijn voor het begrip van de in de jaarrekening opgenomen bedragen.
Effecten coronapandemie op de jaarverslaggeving 2020 van beursfondsen in Nederland
Authors: van Beest Ferdy , Van der Kuij-Groenberg Katja , van der Tas Leo , Vergoossen Ruud
Published: November 2021

In dit artikel wordt verslag gedaan van een onderzoek naar de effecten van de coronapandemie op de jaarverslaggeving 2020 van in totaal 85 ondernemingen waarvan aandelen zijn genoteerd aan Euronext Amsterdam, in het bijzonder naar de effecten op de verantwoording van overheidsbijdragen en bijzondere waardeverminderingen en de verklaring van de controlerend accountant. Ondernemingen in precaire sectoren bleken meer overheidssteun te hebben ontvangen en slechtere resultaten te hebben dan ondernemingen in niet-precaire sectoren. Wij vonden geen significant verband tussen de coronapandemie en de verantwoording van impairmentverliezen. Daarnaast geeft het artikel inzicht in het gebruik van key audit matters gelieerd aan COVID-19 en blijkt dat er een positief verband is tussen de mate waarin de onderneming COVID-19 noemt in het jaarverslag en de aandacht die de accountant daaraan besteedt in de accountantsverklaring.
Een bijzonder jaar, bijzondere verslaggeving?
Authors: Brouwer Arjan
Published: November 2021

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Finding Clusters of Similar-minded People on Twitter Regarding the Covid-19 Pandemic
Authors: Kappus Philipp , Groß Paul
Published: November 2021

Two clustering methods to determine users with similar opinions on the Covid-19 pandemic and the related public debate in Germany will be presented in this paper. We believe, they can helpgaining an overview over similar-minded groups and could support the prevention of fake-news distribution. The first method uses a new approach to create a network based on retweetrelationships between users and the most retweeted users, the so-called influencers. The second method extracts hashtags from users posts to create a “user feature vector” which is then clustered, using a consensus matrix based on previous work, to identify groups using the same language. With both approaches it was possible to identify clusters that seem to fit groups of different public opinions in Germany. However, we also found that clusters from one approach cannot be associated with clusters from the other due to filtering steps in the two methods.
Classification Methods for Motor Vibration in Predictive Maintenance
Authors: Kammerer Christoph , Gaust Michael , Starke Pascal , Radtke Roman , Jesser Alexander
Published: November 2021

Reducing costs is an important part in todays business. Therefore manufacturers try to reduce unnecessary work processes and storage costs. Machine maintenance is a big, complex, regular process. In addition, the spare parts required for this must be kept in stock until a machine fails. In order to avoid a production breakdown in the event of an unexpected failure, more and more manufacturers rely on predictive maintenance for their machines. This enables more precise planning of necessary maintenance and repair work, as well as a precise ordering of the spare parts required for this. A large amount of past as well as current information is required to create such a predictive forecast about machines. With the classification of motors based on vibration, this paper deals with the implementation of predictive maintenance for thermal systems. There is an overview of suitable sensors and data processing methods, as well as various classification algorithms. In the end, the best sensor-algorithm combinations are shown.
LFO2: An Enhanced Version of Learning-From-OPT Caching Algorithm
Authors: Kwok Yipkei , L. Sullivan David
Published: November 2021

Recent machine learning-based caching algorithm have shown promise. Among them, Learning-FromOPT (LFO) is the state-of-the-art supervised learning caching algorithm. LFO has a parameter named Window Size, which defines how often the algorithm generates a new machine-learning model. While using a small window size allows the algorithm to be more adaptive to changes in request behaviors, experimenting with LFO revealed that the performance of LFO suffers dramatically with small window sizes. This paper proposes LFO2, an improved LFO algorithm, which achieves high object hit ratios (OHR) with small window sizes. This results show a 9% OHR increase with LFO2. As the next step, the machine-learning parameters will be investigated for tuning opportunities to further enhance performance.
GPF: A Green Power Forwarding Technique for Energy-Efficient Network Operations
Authors: Gandotra Rahil , Perigo Levi
Published: November 2021

The energy consumption of network infrastructures is increasing; therefore, research efforts designed to diminish this growing carbon footprint are necessary. Building on prior work, which determined a difference in the energy consumption of network hardware based on their forwarding configurations and developed a real-time network energy monitoring tool, this research proposes a novel technique to incorporate individual device energy efficiency into network routing decisions. A new routing metric and algorithm are presented to select the lowest-power, least-congested paths between destinations, known as Green Power Forwarding (GPF). In addition, a network dial is developed to enhance GPF by allowing network administrators to tune the network to optimally operate between energy savings and network performance. To ensure the scope of this research for industry adoption, implementation details for different generations of networking infrastructure (past, present, and future) are also discussed. The experiment results indicate that significant energy and, in turn, cost savings can be achieved by employing the proposed GPF technique without a reduction in network performance. The future directions for this research include developing dynamically-tuning network dial modes and extending the principles to inter-domain routing.
Security in Agile Development, use Case in Typeform
Authors: Julià Pau , Salvador David , Peña Marc
Published: November 2021

Software development methodologies have evolved during the last years to reduce the time to market to the minimum possible. Agile is one of the most common and used methodologies for rapid application development. As the agile manifesto defines in its 12 principles, one of its main goals is to satisfy the customer needs through early and continuous delivery of valuable software. Significantly, that none of the principles refers to security. In this paper, we will explain how Typeform integrates security activities into the whole development process, reducing at the same time the phases on the S-SDLC to reduce friction and improve delivery while maintaining the security level.
BurnoutWords - Detecting Burnout for a Clinical Setting
Authors: Nath Sukanya , Kurpicz-Briki Mascha
Published: November 2021

Burnout, a syndrome conceptualized as resulting from major workplace stress that has not been successfully managed, is a major problem of today's society, in particular in crisis times such as a global pandemic situation. Burnout detection is hard, because the symptoms often overlap with other diseases and syndromes. Typical clinical approaches are using inventories to assess burnout for their patients, even though free-text approaches are considered promising. In research of natural language processing (NLP) applied to mental health, often data from social media is used and not real patient data, which leads to some limitations for the application in clinical use cases. In this paper, we fill the gap and provide a dataset using extracts from interviews with burnout patients containing 216 records. We train a support vector machine (SVM) classifier to detect burnout in text snippets with an accuracy of around 80%, which is clearly higher than the random baseline of our setup. This provides the foundation for a next generation of clinical methods based on NLP.
Reducing Cyber Incident Response to Protect CNI from Cyber Attacks using an N-SIEM Integration with an ICTI-CNI
Authors: Tafa Igli , Shahollari Kevin
Published: November 2021

The rapid evolution of technology has increased the role of cybersecurity and put it at the center of nationalcritical infrastructure. This role supports and guarantees the vital services of (CNI) while provides the proper functionalities for running operations between the public and private sectors. This evolution has hadthe same impact on cyberattack tools, methods, techniques used to gain unauthorized access to these computer systems that contain confidential and high-value information in the digital data sales market or asit called "darkweb". As a result, it has become necessary to monitor all events of the National Critical Infrastructure (CNI) computer systems. This proposed system uses a centralized National SIEM (N-SIEM) specializing in the correlation of security events caused by cyber attacks, collected by CNIs systems while integrating with anInternational Cyber Threat Intelligence system (ICTI-CNI). In addition, this conceptual model collects security breach events of CNIs systems, analyzes only cyber attacks, and correlates these security events in real-time with an intelligent automated platform while reducing the response time of security analysts.
Smartphone Model Fingerprinting using WiFi Radiation Patterns
Authors: Burton Thomas , Rasmussen Kasper
Published: November 2021

This paper aims to demonstrate the feasibility of our proposed method for fingerprinting different classes of wireless devices. Our method relies on the observation that different device types, or indeed different models of the same type, have different wireless radiation patterns. We show in detail how a small set of stationary receivers can measure the radiation pattern of a transmitting device in a completely passive manner. As the observed device moves, our method can gather enough data to characterize the shape of the radiation pattern, which can be used to determine the type of the transmitting device from a database of patterns. We demonstrate that the patterns produced by different models of smartphones are easily different enough to be identified. Our measurements are repeatably measurable using RSS with commercial-off-theshelf hardware. We then use simulations to show the success of our method as a classifier.
Development of Administration Professional Competences in Brazilian Public Universities: A Multicase Study in Florianópolis
Authors: de Souza Vilela Ednaldo , Dias Filipe José , B. L. Dalmau Marcos
Published: November 2021

The article aims to investigate how the development of competences applied to the professional formation of the egress administrator of public municipal higher education institutions in the Florianópolis region occurs under perspective of teachers and coordinators of the bachelor's degree in administration course. For this, a qualitative and documentary research was carried out, using a structured questionnaire applied to 20 people as a data collection instrument, including 2 course coordinators and 18 professors from the studied institutions who teach the subjects whose contents are related to professional formation from the administrator. The results show that the new national curriculum guidelines encourage the development of competences. In this context, despite the effort to comply with such devices, there is some misalignment between the teaching plans and the pedagogical project of the course. Difficulties in implementing formation based on competence and lack of institutional stimuli are also perceived.
An Improved Framework for C-V2X Systems with Data Integration and Identity-based Authentication
Authors: Huang Rui
Published: November 2021

Current trends of autonomous driving apply the hybrid use of on-vehicle and roadside smart devices to perform collaborative data sensing and computing, so as to achieve a comprehensive and stable decision making. The integrated system is usually named as C-V2X. However, several challenges have significantly hindered the development and adoption of such systems. For example, the difficulty of accessing multiple data protocols of multiple devices at the bottom layer, and the centralized deployment of computing arithmetic power. Therefore, this work proposes a novel framework for the design of C-V2X systems. First, a highly aggregated architecture is designed with fully integration with multiple traffic data resources. Then a multilevel information fusion model is designed based on multi-sensors in vehicle-road coordination. The model can fit different detection environments, detection mechanisms, and time frames. Finally, a lightweight and efficient identity-based authentication method is given. The method can realize bidirectional authentication between end devices and edge gateways.
An Intelligent System to Improve Athlete Depression and Eating Disorder using Artificial Intelligence and Big Data Analysis
Authors: Chen Xuannuo , Sun Yu
Published: November 2021

The inspiration for the creation of this app stemmed from the deeply rooted history of eating disorders in sports, particularly in sports that emphasize appearance and muscularity which often includes gymnastics, figure skating, dance, and diving [1]. All three sports require rapid rotation in the air which automatically results in the necessity of a more stringent weight requirement. Eating disorders can also be aggravated by sports who focus on individual performances rather than team-oriented like basketball or soccer [5]. According to research, up to thirteen percent of all athletes have, or are currently suffering from a form of eating disorder such as anorexia [2] and bulimia [3]. In the National Collegiate Athletic Association, it is estimated that up to sixteen percent of male athletes and forty-five percent of female athletes have been diagnosed with an eating disorder.
Predicting Alzheimer's Disease Progression by Combining Multiple Measures
Authors: Zawawi Nour , Gamal Saber Heba , Hashem Mohamed , F.Gharib Tarek
Published: November 2021

Alzheimer's disease (AD) is a degenerative brain ailment that affects millions worldwide. It is the most common form of dementia. Patients with an early diagnosis of Alzheimer's disease have a strong chance of preventing additional brain damage by halting nerve cell death. At the same time, it begins to progress several years before any symptoms appear. The variety of data is the biggest problem encountered during diagnosis. Neurological examination, brain imaging, and often asked questions from his connected closed relatives are the three forms of data that a neurologist or geriatrics employs to diagnose patients. One of the biggest questions which need answering is the choice of a convenient feature. The main objective of this paper is to help neurologists or geriatricians diagnose patient conditions. It proposes a new hybrid model for features extracted from medical data. It discusses AD's early diagnosis and progression for all features considered in the diagnosis and their complex interactions. It proves to have the best accuracy when compared with the state-ofthe-art algorithm. Also, it proves to be more accurate against some recent research ideas. It got 95% in all cases, considering this work focused more on increasing the number of instances in comparison.
Interactive Dashboard Design for Manager, Data Analyst and Data Scientist Perspective
Authors: Olubunmi Awodiji Temitope
Published: November 2021

With large amounts of unstructured data being produced every day, organizations are trying to extract as much relevant information as possible. This massive quantity of data is collected from a variety of sources, and data analysts and data scientists use it to create a dashboard that provides a complete picture of the organization's performance. Dashboards are business intelligence (BI) reporting tools that collect and show key metrics and key performance indicators (KPIs) on a single screen, enabling users to monitor and analyse business performance at a glance. An objective assessment of the company's overall performance, as well as of each department, is provided. If each department has access to the dashboard, it may serve as a springboard for future discussion and good decision-making. The goal of this article is to explain in detail the implementation of Dashboard and how it works, which will serve as a blueprint for building an effective dashboard with respect to best practices for dashboard design.
Unsupervised Named Entity Recognition for Hi-Tech Domain
Authors: Govindan Abinaya , Ranjan Gyan , Verma Amit
Published: November 2021

This paper presents named entity recognition as a multi-answer QA task combined with contextual natural-language-inference based noise reduction. This method allows us to use pre-trained models that have been trained for certain downstream tasks to generate unsupervised data, reducing the need for manual annotation to create named entity tags with tokens. For each entity, we provide a unique context, such as entity types, definitions, questions and a few empirical rules along with the target text to train a named entity model for the domain of our interest. This formulation (a) allows the system to jointly learn NER-specific features from the datasets provided, and (b) can extract multiple NER-specific features, thereby boosting the performance of existing NER models (c) provides business-contextualized definitions to reduce ambiguity among similar entities. We conducted numerous tests to determine the quality of the created data, and we find that this method of data generation allows us to obtain clean, noise-free data with minimal effort and time. This approach has been demonstrated to be successful in extracting named entities, which are then used in subsequent components.
Common Ground, Frames and Slots for Comprehension in Dialogue Systems
Authors: Blache Philippe , Houlès Matthis
Published: November 2021

This paper presents a dialogue system for training doctors to break bad news. The originality of this work lies in its knowledge representation. All information known before the dialogue (the universe of discourse, the context, the scenario of the dialogue) as well as the knowledge transferred from the doctor to the patient during the conversation is represented in a shared knowledge structure called common ground, that constitute the core of the system. The Natural Language Understanding and the Natural Language Generation modules of the system take advantage on this structure and we present in this paper different original techniques making it possible to implement them efficiently.
Thermal entropy based hesitant fuzzy linguistic term set analysis in energy efficient opportunistic clustering
Authors: Anees Junaid , Zhang Hao-Chun
Published: November 2021

Limited energy resources and sensor nodes’ adaptability with the surrounding environment play a significant role in the sustainable Wireless Sensor Networks. This paper proposes a novel, dynamic, self-organizing opportunistic clustering using Hesitant Fuzzy Linguistic Term Analysis- based Multi-Criteria Decision Modeling methodology in order to overcome the CH decision making problems and network lifetime bottlenecks. The asynchronous sleep/awake cycle strategy could be exploited to make an opportunistic connection between sensor nodes using opportunistic connection random graph. Every node in the network observe the node gain degree, energy welfare, relative thermal entropy, link connectivity, expected optimal hop, link quality factor etc. to form the criteria for Hesitant Fuzzy Linguistic Term Set. It makes the node to evaluate its current state and make the decision about the required action (‘CH’, ‘CM’ or ‘relay’). The simulation results reveal that our proposed scheme leads to an improvement in network lifetime, packet delivery ratio and overall energy consumption against existing benchmarks.
Comparative Study of Justification Methods in Recommender Systems: Example of Information Access Assistance Service (IAAS)
Authors: Yacouba Kyelem , Kiswendsida Kisito Kabore , Tounwendyam Frédéric Ouedraogo , Florence Sèdes
Published: November 2021

Justification of recommendations increases trust between users and the system but also generates more relevant recommendations than recommendation systems that do not incorporate it. That is why, we conducted a justification study of the recommendation for IAAS. Our comparative study shows that IAAS, which currently does not offer the opportunity to justify recommendations, needs to be improved. From the analysis of justification methods studied in this work, it appears that none of these methods can be used effectively in IAAS. That is why, we proposed a new IAAS architecture that deals separately with item classification and the extraction of the justification has added the item during recommendation generation. The item selection method remains unchanged as we plan to implement a new strategy to filter user’s reviews should now be extended to four elements: the documentary unit, the group of users, the justification and the weight. Opinion A=(UD,G,J,a). Where UD represents the documentary unit, G the user group, J is the justification and a is the weight of the recommendation.
Pengaruh Media Sosial Facebook Terhadap Perilaku Cyberbullying Pada SMK Patriot 1 Bekasi
Authors: Apriliani Desi , Aulianita Rizki
Published: November 2021

Dengan adanya media sosial khususnya facebook tidak dapat dipungkiri bahwa perilaku cyberbullying dapat dilakukan bahkan dialami oleh para pengguna terutama pengguna pada kalangan remaja. Tujuan dari penelitian ini adalah untuk mengetahui adakah pengaruh media sosial facebook terhadap perilaku cyberbullying pada siswa SMK Patriot 1 Bekasi. Penelitian ini menggunakan metode kuantitatif data diambil dari kuesioner yang dibagikan kepada siswa. Peneliti menggunakan 3 variabel bebas yaitu kesenangan, komunikasi dan informasi. Sedangkan variabel terikatnya adalah cyberbullying. Untuk menentukan sebarapa besar pengaruh dari ketiga variabel tersebut peneliti menggunakan analisis regresi linier berganda. Hasil penelitian menunjukkan bahwa nilai Y = 5,838 + 0X1 + -0,137X2 + 1,085X3 sedangkan nilai koefisien determinasi (Rsquare) sebasar 0,103 atau 10,3%. Angka tersebut menunjukkan bahwa pengaruh media sosial facebook cukup dan sisanya 89,7% dipengaruhi oleh variabel lain diluar dari penelitian ini.
Praktek Requirement Engineering: Persiapan Implementasi Teknologi QR Code Pada Kegiatan Bimbingan Tugas Akhir
Authors: Somantri Asep
Published: November 2021

Abstrak: Maraknya penggunaan Smartphone sebagai sebuah teknologi yang saat ini dapat digunakan untuk melakukan verifikasi dan validasi pada proses pengesahan data transaksi, hal ini juga telah mendorong perkembangan teknologi agar dapat mendukung proses tersebut. Saat ini, teknologi QR Code telah dimanfaatkan untuk memudahkan penggunanya dalam melakukan proses pengesahan data transaksi (contoh: transaksi jual-beli, kehadiran suatu acara, registrasi pada suatu komunitas, dll.). Penelitian ini bertujuan untuk menunjukkan peluang bahwa teknologi QR Code dapat digunakan untuk verifikasi dan validasi pada proses pencatatan berita acara bimbingan Tugas Akhir (TA) yang terjadi antara Peserta TA dengan Pembimbing TA. Penelitian dilakukan dengan metode Requirement Engineering (RE) untuk memperoleh gambaran tentang kondisi sistem saat ini serta menganalisis data, proses, dan infrastruktur yang diperlukan. Penelitian ini menghasilkan hal-hal yang diperlukan untuk melakukan implementasi teknologi QR Code berupa spesifikasi sistem target yang dapat digunakan untuk menyiapkan organisasi dalam mengimplementasikan teknologi QR Code pada proses pencatatan kehadiran bimbingan TA.

 

Kata kunci: requirement engineering, tugas akhir, teknologi QR code, verifikasi, validasi.

 

Abstract: The rise of the use of smartphones as a technology that can currently be used to verify and validate the transaction data has encouraged the development of technology to support that process. At present, QR Code technology has been utilized to facilitate its users in the process of validating transaction data (for example: buying and selling transactions, the presence of an event, registration in a community, etc.). This study aims to show the opportunity that QR Code technology can be used for verification and validation in the process of recording the progress of final thesis activity that occurs between students and advisors. The study was conducted using the Requirement Engineering method to obtain an overview of the current state of the system and analyze the data, processes and infrastructure required. This research produced the system requirements to implement QR Code technology in the form of a system target specification that can be used to prepare organizations to implement QR Code technology in the process of recording the progress of final thesis activity.

 

Keywords: final thesis, QR code technology, requirement engineering, verification, validation.
DEVELOPMENT OF A HAND-PUSH WEEDER FOR CUTTING WEEDS
Authors: Adetola Olufemi Adeyemi
Published: November 2021

An hand-push weeder was designed, fabricated and evaluated for household use and peasant farmers in order to mechanize cutting process and minimize the higher aggressive nature of weeds contrasted with harvests poising major danger to crop production, the invasion on soils is very high particularly during the raining seasons when soil moisture is high and plant development conditions are ideal. The major components of the weeder are the weeding drum and frame made of mild steel, adjustable handle made of galvanized steel, transmission system made up of belt and pulley mechanism, two wheels both at the front and rear. The highest weeding efficiency of 93.496% and field capacity of 0.055 ha/hr were obtained based on some parameters that influence mechanized weeding (soil condition, age of weed, number of weed, and optimum speed of the weeding machine been 1800rpm). The production cost of the weeder is $185 and it is powered by a 3 hp gasoline engine.
DRYING KINETICS OF FISH (Clarias gariepinus) SMOKED WITH BIOGAS
Authors: Oyerinde O. S. , Olumurewa John A. V. , Fajobi D.
Published: November 2021

This is aimed at studying the aeration kinetics of catfish (Clarias gariepinus) smoked directly with biogas. Five live fresh fishes (Clarias gariepinus) were obtained from Fishery and Aquaculture Technology Department in FUTA, Ondo State, Nigeria at the age of 4 months with average weight of 900g each. The fishes were killed, de-gutted, thoroughly washed with water, cut into pieces of 3cm length. The chunks were laid in a single layer on a mesh directly exposed to biogas flame obtained from bio-decomposition of poultry waste and the weight was being monitored at 15 minutes interval until constant weight was observed. The study showed that the time taken for drying of Clarias gariepinus to reach the humidity point of around 12.43% (db.) was two and a half hours. The drying data was subjected to 10 thin-layer drying models. The compared the performances of the models using the determination of coefficient (R2), reduced chi­square (x2) and root mean square error (RMSE) between the calculated and predicted moisture ratios. The results showed that Henderson and Pabis modified model (highest R2 and lowest x2 and RMSE of 0.998, 0.00021 and 0.01386 respectively) was found to satisfactorily describe the biogas drying curves of Clarias gariepinus.
FORMATION DAMAGE MECHANISMS AND NUMERICAL SIMULATION OF PERMEABILITY IMPAIRMENT IN HORIZONTAL WELLS
Authors: Adeosun Tunde , Adabanija Moruffdeen , Akinpelu Folake
Published: November 2021

Puzzling circumstance associated with formation damage near wellbore occur frequently, resulting in permeability impairments and increased pressure losses. Potential damage phenomenon usually starts from drilling to completion via production and such mechanisms have been fully considered. Most of the existing tasks to mitigate the near oil wellbore damages involve use of empirical models, conducting experiments, frequent shut down of wells for proper well tests and pressure maintenance are highly expensive and time consuming. Permeability impairments have been simulated by modifying Darcyâ€™s equation to optimize reservoir pressure for improved near wellbore in horizontal wells. The model, transient linear partial differential equation (TLPDE) for impaired permeability is developed and numerically resolved using finite difference method. The model was implemented by writing codes in MATLAB language and the solution obtained was validated using synthetic/ field data. The results obtained for TLPDE model indicated pressure depletion over time. This was also shown for every values of coefficient of anisotropy until 400 days when the anisotropy became insignificant approaching isotropy condition, suggesting permeability impairment. Numerical simulation proved to be effective in simulating near oil wellbore damages. This paper describes the detailed mechanisms of formation damage and provided a numerical approach to model impaired permeability in horizontal wells. This approach allowed us to study the impact of various damage mechanisms related to drilling, completion conditions and significant improvement of near oil wellbore for well performance.
Romosozumab (Evenity)
Authors: Reimbursement Team
Published: November 2021

CADTH recommends that Evenity should be reimbursed by public drug plans for the treatment of osteoporosis in postmenopausal women if certain conditions are met.

Evenity should only be covered to treat postmenopausal women with a history of osteoporosis-related fracture and who are likely to have such a fracture in the future and who have never received previous medications for osteoporosis.

Evenity should only be reimbursed if the cost is reduced and if it is not prescribed concurrently with other osteoporosis medications, except for calcium and/or vitamin D.
A Spectroscopic and Nondestructive Analysis Methods for Investigation of Inorganic Pigments in A Cultural Heritage in North of Iran
Authors: Charati Faramarz Rostami , Rahmani Gholamreza , Bahadori Roya , Madani Farah Sadat
Published: November 2021

Many of the historical objects that form our cultural heritage are made of wood. Wooden artefacts, wood painted panels and historic furniture represent a significant part of our cultural heritage. Their preservation over time is a challenging task, and insect infestation still represents a primary cause of loss of cultural heritage artifacts. For this reason in this research, wood pigments that are important in the conservation of historical wooden objects are described. The characterization of very stable pigments from a cultural heritage building named by SAGHATALAR which is located in Mazandaran province, a suburb around of Fridonkenar city in the north of Iran near Caspian Sea (Cochakbishehmahaleh village) was investigated. The result were showed no organic materials was find in the four colors (Blue, Red, Yellow and Green) as samples of this building were detected and taken samples from them for characterization and analysis. The spectroscopic techniques that have been used are Fourier transform infrared spectroscopy (FT-IR), X‐ray fluorescence spectroscopy (XRF), X‐ray emission spectroscopy (XRD), Uv-vis spectroscopy, fluorescence spectroscopy, Raman spectroscopy and Mossbauer spectroscopy.