bluuebunny/crossref_metadata_2025 huggingface dataset:
Sözlükler Öğrencilere Ne Kadar Yardımcı Oluyor?
Authors: YILDIZ Mustafa , CEYHAN Sümeyra , UZUN Elif Büşra
Published: July 2023

Bu çalışmanın amacı, ilkokul Türkçe derslerinde öğrencilerin temel başvuru kaynaklarından olan sözlüklerin öğrencilere ne kadar rehberlik yapabildiğini anlamaya çalışmaktır. Araştırma nitel araştırma desenlerinden durum çalışması deseninde yapılandırılmıştır. Çalışmada incelenen durumu ortaya çıkarabilmek için araştırma süreci önce doküman incelemesi ardından görüşmeler şeklinde aşamalandırılmıştır. Doküman inceleme sürecinde veri kaynağı olarak farklı yayınevleri tarafından ilkokul düzeyi için hazırlanmış dört adet sözlük ve ilkokul ikinci, üçüncü ve dördüncü sınıf Türkçe ders kitapları kullanılmıştır. Ders kitapları incelenerek üç sınıf düzeyi için metinler seçilmiş ve bu metinlerden öğrencilerin anlamını bilmediği kelimeler belirlenmiştir. Ardından seçilen kelimelerin açıklamalarına belirlenen sözlüklerden alınarak kelime listeleri oluşturulmuş ve sınıf öğretmenlerinden bu açıklamaların öğrenci düzeyi için ne kadar uygun olduğuna dair görüşleri alınmıştır. Bu süreçte 21 sınıf öğretmeni ve 18 ilkokul öğrencisi ile görüşmeler yapılarak veri toplanmış, elde edilen veriler betimsel analiz yöntemi ile analiz edilmiştir. Görüşmeler sonucunda öğretmenlerin sözlüklerin sınıf seviyesine uygun olmaması ve anlamı bilinmeyen bir kelimenin açıklamasında yine öğrencilerin anlamını bilemedikleri bir kelimeyle karşılaşabilmeleri sebebiyle sözlüklerde yer alan açıklamaları öğrencilerin düzeyine uygun bulmadığı görülmüştür. Öğrencilerin sözlüklere ilişkin görüşleri incelendiğinde ise sözlük çalışmalarını eğlenceli buldukları, resimli ve büyük yazılı sözlüklerle çalışmayı istedikleri belirlenmiştir.
Verbo-Visual Pun in Memetic Warfare Against Russia’s Aggression in Ukraine
Authors: Bielova Maryna
Published: July 2023

With humor, which has long been known as a coping mechanism in extreme crises, punning memes, armed with words and images, have become weapons of ‘mass disruption’ influencing the hearts and minds of a target audience. This invites the examination of how memes detailing Russian-Ukrainian war employ verbo-visual puns as a strategic tool of information warfare to counter president Putin’s military aggression and misleading political messaging. This article1 proposes an interdisciplinary template for the analysis of puns drawing on multimodal social semiotics, cognitive linguistics, critical discourse analysis and crisis communication analysis. The data sampled for this research comprises 87 memes about Russian-Ukrainian war that employ verbo-visual puns with 6 cases described in this paper. The article proposes a taxonomy, in which verbo-visual puns can be classified in accordance with mechanisms that are used to classify wordplay (homonymy, polysemy, and paronymy). Evidence is thus provided to show that this typology is applicable to the taxonomy of multimodal signs as well. The results of this research reveal cognitive and semiotic triggers of puns as well as their potential to serve as a tool generating public reaction to Russia’s military aggression in Ukraine and reaching the intended goals of crisis communication.
ПРАВА ЛЮДИНИ І ДЕМОКРАТІЯ: ЗАГРОЗИ ГЛОБАЛЬНОГО ХАР АКТЕРУ
Authors: Юрченко О.А.  , Філіпчук К.В.
Published: July 2023

Стаття присвячена аналізу стану обмеження прав людини в демократичному суспільстві в контексті глобалізаційних змін сучасності та їх впливу на суспільно-правову реальність. Сучасна парадигма державної політики демократичних держав ґрунтується на ідеї, що права людини є юридично обов’язковими для держав-учасниць через міжнародні договори та національне законодавство. Державні установи та особи, які діють від імені держави, зобов'язані поважати, захищати та виконувати права людини не залежно від соціально-політичних обставин. Констатовано, що донедавна демократія як форма публічно-владних відносин поширилася в більшості країн світу, проте пандемічна загроза трансформувала право. Глобалізація впливає на всі сфери життя суспільства, міграційні процеси, пандемічна загроза, а тепер і військові конфлікти спричинили суттєве обмеження всієї системи прав людини. Доведено, що саме зміна правових чинників задля забезпечення громадського здоров’я продемонструвала безпрецедентну проблему – суттєве обмеження прав людини у всіх державах, у всіх сферах та на всіх рівнях. Демократія знову стала під суттєвою загрозою. Правова політика урядів різних країн щодо подолання пандемії була подібна до умов військового стану, характеризується вжиттям заходів, які серйозно обмежують користування особистими свободами, до такого рівня, який був безпрецедентним у демократичних країнах у мирний час. Також і політичні права на державному рівні були «відкладеними». Доведено, що, проте, не тільки соціально-комунікативна чи трудова сфера передбачала обмеження прав людини. Демократичні цінності, вироблені людством роками, на сучасному етапі розвитку міжнародно-правової системи, підлягають трансформації та обмеженню. Пандемічна загроза стала викликом для реалізації політичних прав громадян та досвід багатьох держав доводить суттєву прогалину в правовому регулюванні і виваженій політиці. Загроза громадському здоров’ю використовується як чинник забезпечення владних інтересів правлячої еліти, провокує неможливість належної реалізації прав та свобод громадян, створює інформаційну закритість органів публічної влади. Тому вагомим є належне регулювання кризових явищ та вироблення загальних стандартів заради можливості протидії майбутнім загрозам глобального характеру.
ДО ПИТАННЯ СТВОРЕННЯ РЕЄСТРУ МЕДІАТОРІВ В УКРАЇНІ: ТЕОРЕТИКО-ПРАВОВИЙ АСПЕКТ
Authors: Доляновська І.М.
Published: July 2023

Із прийняттям наприкінці 2022 року Закону України «Про медіацію» розпочався новий етап імплементації даного інституту в суспільне та правове життя країни. До прийняття закону, левова роль у популяризації та застосуванні даного методу альтернативного вирішення спорів належала численним громадським організаціям, які відігравали роль амбасадорів медіації як засобу протилежному судовому розгляду конфлікту (спору). Наразі чинний Закон України «Про медіацію» встановлює стандарти підготовки та навчання медіаторів, принципи медіаційної процедури та інші ключові моменти медіації. Однак крапку у врегулюванні даного питання ставити зарано, адже практична реалізація законодавчого акту вимагає подолання нових нагальних викликів, одним із яких є дискусія щодо доцільності створення єдиного державного Реєстру медіаторів. Безперечно, запровадження інституту медіації і забезпечення якості медіаційних послуг та допомоги населенню в будь-якій країні потребує належної професійної підготовки медіаторів та дотримання ними правил проведення медіації. Тому питання регулювання професії медіатора є надзвичайно важливими. Як відомо, основним принципом правового регулювання медіації є забезпечення необхідних стандартів медіації при мінімальному втручанні держави в ці відносини, надання сторонам спору найбільш повної свободи реалізації своїх прав як під час згоди на медіацію у якості альтернативи суду, так і під час вибору особи медіатора. Сама процедура медіації побудована на вільному самовизначенні і волевиявленні сторін спору, на добровільній і усвідомленій відповідальності за свої слова і вчинки і, зрештою, за результат спору. Надмірне регулювання процедур медіації може обмежити ці можливості і звести нанівець основні її переваги. Разом з тим, коли діяльність медіаторів підтримується державою з метою впорядкування правового регулювання, надання цій діяльності більш легітимного характеру та її поширення в усіх можливих сферах застосування, держава таким чином забезпечує мінімально необхідні гарантії законності цієї діяльності. Саме ініціативі створення Реєстру медіаторів як свідчення належного державного регулювання даної сфери і присвячена дана наукова стаття.
Metonimia en el uso de determinantes definidos e indefinidos en español. Aproximación descriptiva y aplicación didáctica para el aula de ELE
Authors:   Universidad de Granada, Castañeda Castro Alejandro
Published: July 2023

En este trabajo indagamos qué procesos metonímicos actúan en el funcionamiento de determinantes definidos e indefinidos del español y cómo la conceptualización de los sistemas de determinación nominal puede verse beneficiada si se incorpora a las descripciones pedagógicas la toma de conciencia de los vínculos metonímicos entre los diferentes valores de las formas y construcciones estudiadas. Abordaremos la distinción entre valores de generalización (Un médico debe ser empático), valores inespecíficos (Necesitamos un médico) y valores específicos (Pediré cita a un médico que me recomendaron) de artículos y otros determinantes cuantificadores, así como la interpretación cuantificativa de determinantes definidos, como en No sabes los amigos que tiene Laura, en el sentido de ‘No sabes cuántos amigos tiene Laura’. El uso de notaciones icónicas propias de la Gramática Cognitiva, así como de conceptos tales como la distinción perfil/base, entre otros, permitirá integrar la metonimia en el marco de la noción de estructuración conceptual (construal), propia del modelo de la Gramática Cognitiva. En cuanto a la aplicación didáctica, valoraremos las ventajas de la aproximación cognitiva en combinación con distintos tipos de ejercicios y estrategias de conceptualización en las tareas de presentación y práctica de diferentes determinantes.
La adquisición adulta y temprana de eventos de colocación en español
Authors:   Universidad de Zaragoza – IPH, Ibarretxe-Antuñano Iraide
Published: July 2023

Este artículo investiga la codificación y la categorización de los eventos de colocación por parte de hablantes adultos y preescolares de español L1 y aprendientes daneses de español L2. Los eventos de colocación son situaciones en las que algún tipo de agente hace que un objeto se mueva a una ubicación específica. Investigaciones anteriores han mostrado que, a pesar de ser situaciones cotidianas y ubicuas que se codifican en cualquier lengua del mundo, los hablantes de estas lenguas difieren en la categorización de estos eventos. Es decir, se fijan y escogen aspectos semánticos diferentes a la hora de describir este tipo de situaciones (Kopecka y Narasimhan, 2012). En el español, los eventos de colocación se organizan a partir de la Intencionalidad (caerse, dejar), la Dinámica de Fuerzas (tirar) y la configuración topológica del lugar de destino o Base (meter). Este artículo muestra que este tipo de patrones conceptuales son constantes y prototípicos en los hablantes adultos de español L1, aparecen de forma sólida en la adquisición temprana de estos eventos, pero están ausentes en los aprendientes de español L2. Los datos, elicitados a partir de la herramienta «PUT task» (Bowerman y otros 2004), provienen de 54 informantes: 40 hablantes nativos de español (variedad de Aragón): 10 adultos (edades 18-44) y 30 niños (10 por cada curso de Educación Infantil; edades 3;6 - 5;14) y 14 hablantes nativos de danés con español como segunda lengua.
Sobre la interrelación entre lengua y sociedad: la industrialización como motor del cambio semántico en el dominio del olfato
Authors:   Universidad Complutense de Madrid, Pettersson-Traba Daniela
Published: July 2023

En esta contribución se formula una hipótesis para dar cuenta del cambio semántico experimentado por adjetivos que designan el concepto pleasant smelling en inglés americano, los cuales se han vuelto cada vez más frecuentes para designar aromas artificiales en detrimento de aromas naturales. Los desarrollos sociales y tecnológicos que tuvieron lugar en la sociedad estadounidense durante la Primera y Segunda Revolución Industrial bien podrían constituir una de las causas subyacentes detrás de dicho cambio semántico. Para comprobar esta hipótesis, se utilizan métodos frecuentes en la investigación sobre la interrelación entre lengua y sociedad. En concreto, primero se recurre a un enfoque basado en diccionarios, cuyos resultados se complementan posteriormente con análisis semánticos distribucionales para así examinar como se conceptualiza una serie de categorías semánticas que podrían reflejar los desarrollos extralingüísticos mencionados anteriormente. Los resultados apoyan la hipótesis de que el cambio semántico experimentado por los adjetivos del dominio del olfato con toda probabilidad se ha visto influenciado por los desarrollos sociales que tuvieron lugar en los Estados Unidos en el período examinado. Este cambio hacia un mayor grado de artificialidad, por lo tanto, no parece ser una coincidencia, sino el resultado de alguna causa subyacente.
Intervention Analysis for Modeling and Forecasting Exchange Rates Rupiah Against Yen
Authors: Anjuita Anjuita , Rahayu Widyanti , Siregar Dania
Published: July 2023

The Rupiah exchange rate against the Yen is one of the most important exchange rates in Indonesia since the agreement between the two countries to conduct investment and trade transactions using local currency. Exchange rate movements tended to strengthen during 2019. In 2020 there was a COVID-19 intervention and there was a significant weakening. An intervention is an event that causes a sharp increase or decrease in time series data. Intervention analysis is an analysis used on the data affected by the intervention by measuring the magnitude of the change in value and the duration of the intervention. Intervention analysis research on data on the rupiah exchange rate against the yen is still very rarely done. This study aims to apply intervention analysis in modeling and forecasting the Rupiah against the Yen exchange rate by considering the impact of the COVID-19 intervention. Research shows that the COVID-19 intervention on the Rupiah exchange rate against the Yen has had a long impact with the best intervention model being ARIMA (4,2,0) with an order of intervention (0,1,0). The level of forecasting accuracy using the model is very good with a MAPE value of 2.69%.
Attack Level Of Coffee Fruit Borer Pest (Hypothenemus hampei) And Branch Borer Pest (Xylosandrus compactus) In Central Dempo District Pagaralam City
Authors: Arsi Arsi , SHK Suparman , Gunawan Bambang , Umayah Abu , Pujiastuti Yulia , Hamidson Harman , Irsan Chandra , Suwandi  , Nurhasnah
Published: July 2023

Pagaralam is a city in South Sumatra Province with five districts: North Dempo, Central Dempo, South Dempo, North Pagaralam and South Pagaralam. The main commodity is coffee. Coffee cultivation has a major problem, namely the attack of fruit and branch borer pests because it can reduce the quality and productivity of coffee. This study was to determine the level of attack by fruit borer and branch borer in the Dempo Tengah sub-district. Coffee farmers in Pagaralam use monoculture and polyculture cultivation systems. This field practice method is observation, observation in this study, and interviews with coffee farmers. The results showed that the attack of young coffee berry borer pests can cause the fruit to wither and fall off, while ripe fruit has holes in its seeds. Branch borer attacks cause branches to wither and dry. The highest percentage of fruit and branch borer attacks on coffee plants was found in young mixed-aged coffee plantations. In conclusion, fruit borer and coffee branch borer are more susceptible to attacking coffee at a young age, because young coffee plants have soft plant organs. Lush shade creates high humidity and low temperatures, which can make it easier for pests to breed.
IMPLEMENTASI METODE SIMPLEKS UNTUK MEMPEROLEH LABA MAKSIMUM PADA TOKO KUE CANTIKA
Authors: Rastryana Ulta , Rusmayanti Santi , Lestari Tri , Damhudi Dedi
Published: July 2023

Saat ini banyak sekali berkembangnya bisnis UKM yang di sertai persaingan yang cukup ketat antar bisnis yang sejenis dan banyak faktor yang mempengaruhi untung atau tidaknya bisnis tersebut dapat berjalan dengan baik, Dengan kondisi banyaknya UKM yang banyak berdiri di Indonesia, maka itu peneliti ingin meneliti perkembangan dari suatu usaha toko kue cantika yang baru berdiri kurang lebih lima tahun. Toko kue cantika merupakan usaha dagang yang bergerak di bidang makanan ringan yaitu berupa penjualan donat kentang dan donat aneka rasa, toko kue ini berlokasi di jalan kebon jati No. 1 sukabumi jawa barat. penelitian ini bertujuan untuk mengetahui seberapa besar laba maksimun yang diperoleh oleh toko kue cantika dalam satu hari produksi Untuk menjaga kelangsungan, berkembangnya usaha dagang dari toko kue cantika maka diperlukan langkah-langkah untuk dapat mengalokasi bahan baku serta meningkatkan keuntungan. Diperlukan metode dalam menentukan kombinasi yang tepat dari produk yang dibuat serta kombinasi dari produk yang dihasilkan. Metode simpleks ialah metode yang digunakan dalam penelian ini yaitu berupa aplikasi POM-QM for windows V5. Aplikasi ini bisa untuk memperkirakan laba maksimum yang diperoleh dari setiap produksi yang dilakukan oleh pemilik toko kue cantika dalam jangka waktu satu hari, sehingga memiliki perkiraan perhitungan yang akurat. Hasil perhitungan laba maksimum dalam satu hari sebesar Rp 2.472.000
Recognizing the Potential to Reduce GHG Emissions Through Air Transportation Electrification
Authors:   California State University, Fresno, Roa Julio , Oldham Joseph ,   Mineta Transportation Institute, Lima Marina ,   California State University, Fresno
Published: July 2023

California is aggressively moving forward with efforts to deploy zero-emission transportation technology to fight climate change, especially the Greenhouse Gas (GHG) emissions from the high-impact transportation sector. However, to date, the investments California has made with Cap-and-Trade funding have focused on ground transportation and some marine sources and not the aircraft at the over 140 airports in the state. Through a California-focused comprehensive GHG emissions analysis, this research project seeks to determine how RAM using electric/hybrid electric aircraft can provide new high-speed transportation for high-priority passenger and cargo movement within Fresno County and connections to coastal urban centers. Using VISION, a model developed by the Argonne National Laboratory Transportation Systems Assessment Group, the research team identified and compared the emission per mile and emission per passenger mile between different modes of transportation using traditional petroleum fuel and other sustainable alternatives at an individual level and within the context of the transportation sector, by comparing different modes of transportation. With this estimation on hand, it becomes more viable for the state of California and other states, as well as the federal government, to establish guidelines and goals for transportation policies and investments.
Strategic information planning and performance of SMEs: A structural equation modelling approach
Authors: Al-Shukri Kadri S.
Published: July 2023

BACKGROUND: The business environment is getting unstable due to which execution of decision support systems has become significant to maintain competitive advantage. Small and medium enterprises in particular confront issues, such as insufficiency of devising strategic planning, strategic decision-making, and information exchange, as well as difficulty increasing performance. Because functional strategic management and decision-making are required, strategic information systems planning is employed to accumulate information and assist decision-makers in developing and implementing the best strategy for gaining superior performance. Executives in information systems focus on technical difficulties while ignoring decisions to support strategic plans. OBJECTIVE: The purpose of this article is to investigate how strategic information systems planning contributes to increased performance in SMEs. METHODS: Data was gathered through questionnaires distributed to information system executives in SMEs, primarily in Jordan. The data was collected with the help of questionnaires adopted from prior studies. For Analysis after applying the diagnostic tests, structural equation modelling has been applied to test the framework developed based on the literature. RESULTS: A structural equation modeling (SEM) was conducted, the individual loadings of the SEM items are investigated, reliability and discriminant validity is tested, and path coefficients of hypothesized relationships of the developed model are tested. CONCLUSIONS: The findings suggested that managers should prioritize implementing strategic information systems planning so that they can gain superior performance with better agility in the future. This research not only enhances the current understanding of the significance of strategic information systems planning but also assists supervisors to improve the procedure.
Inhibition of Pro-Inflammatory Microglia with Minocycline Improves Cognitive and Sleep-Wake Dysfunction Under Respiratory Stress in a Sporadic Model for Alzheimer’s Disease
Authors: Vicente Mariane C. , Paneghini Julia L. , Stabile Angelita M. , Amorim Mateus , Anibal Silva Conceição E. , Patrone Luis Gustavo A. , Cunha Thiago M. , Bícego Kênia C. , Almeida Maria C. , Carrettiero Daniel C. , Gargaglioni Luciane H.
Published: July 2023

Background:

Neuroinflammation in Alzheimer’s disease (AD) can occur due to excessive activation of microglia in response to the accumulation of amyloid-β peptide (Aβ). Previously, we demonstrated an increased expression of this peptide in the locus coeruleus (LC) in a sporadic model for AD (streptozotocin, STZ; 2 mg/kg, ICV). We hypothesized that the STZ-AD model exhibits neuroinflammation, and treatment with an inhibitor of microglia (minocycline) can reverse the cognitive, respiratory, sleep, and molecular disorders of this model.

Objective:

To evaluate the effect of minocycline treatment in STZ model disorders.

Methods:

We treated control and STZ-treated rats for five days with minocycline (30 mg/kg, IP) and evaluated cognitive performance, chemoreflex response to hypercapnia and hypoxia, and total sleep time. Additionally, quantification of Aβ, microglia analyses, and relative expression of cytokines in the LC were performed.

Results:

Minocycline treatment improved learning and memory, which was concomitant with a decrease in microglial cell density and re-establishment of morphological changes induced by STZ in the LC region. Minocycline did not reverse the STZ-induced increase in CO2 sensitivity during wakefulness. However, it restored the daytime sleep-wake cycle in STZ-treated animals to the same levels as those observed in control animals. In the LC, levels of A and expression of Il10, Il1b, and Mcp1 mRNA remained unaffected by minocycline, but we found a strong trend of minocycline effect on Tnf- α.

Conclusion:

Our findings suggest that minocycline effectively reduces microglial recruitment and the inflammatory morphological profile in the LC, while it recovers cognitive performance and restores the sleep-wake pattern impaired by STZ.
Hippocampal Reduction of α-Synuclein via RNA Interference Improves Neuropathology in Alzheimer’s Disease Mice
Authors: Leitão André D.G. , Spencer Brian , Sarsoza Floyd , Ngolab Jennifer , Amalraj Jessica , Masliah Eliezer , Wu Chengbiao , Rissman Robert A.
Published: July 2023

Background:

Alzheimer’s disease (AD) cases are often characterized by the pathological accumulation of α-synuclein (α-syn) in addition to amyloid-β (Aβ) and tau hallmarks. The role of α-syn has been extensively studied in synucleinopathy disorders, but less so in AD. Recent studies have shown that α-syn may also play a role in AD and its downregulation may be protective against the toxic effects of Aβ accumulation.

Objective:

We hypothesized that selectively knocking down α-syn via RNA interference improves the neuropathological and biochemical findings in AD mice.

Methods:

Here we used amyloid precursor protein transgenic (APP-Tg) mice to model AD and explore pathologic and behavioral phenotypes with knockdown of α-syn using RNA interference. We selectively reduced α-syn levels by stereotaxic bilateral injection of either LV-shRNA α-syn or LV-shRNA-luc (control) into the hippocampus of AD mice.

Results:

We found that downregulation of α-syn results in significant reduction in the number of Aβ plaques. In addition, mice treated with LV-shRNA α-syn had amelioration of abnormal microglial activation (Iba1) and astrocytosis (GFAP) phenotypes in AD mice.

Conclusion:

Our data suggests a novel link between Aβ and α-syn pathology as well as a new therapeutic angle for targeting AD.
Classification of ischemic and hemorrhagic stroke using Enhanced-CNN deep learning technique
Authors: Shakunthala M. , HelenPrabha K.
Published: July 2023

Stroke is a type of cerebrovascular disorder that has a significant impact on people’s lives and well-being. Quantitative investigation of MRI imaging of the brain plays a critical role in analyzing and identifying therapy for stroke. A block primarily provokes stroke in the brain’s blood supply. Deep learning algorithms can be used to identify strokes in patients in a short period. Proposed deep learning methods are used to classify strokes using magnetic resonance imaging (MRI) images. Early detection enhances treatment opportunities and saves lives, which is the primary motivation of the proposed work. Deep learning methods have emerged as significant research trends in recent years, particularly for classifying different types of stroke such as ischemic and hemorrhagic stroke. A dataset of 13,850 MRI images of stroke patients was collected from various reliable sources, including Madras scans and labs, Radiopaedia, Kaggle datasets, and online databases. Among these images, 7,810 were identified as cases of ischemic stroke, while 6,040 represented hemorrhagic strokes. For training purposes, a total of 9,700 images were used, with 4,150 images employed for testing. A comparative analysis of ANN, SVM, NB, ELM, KNN and Enhanced CNN technique is carried out, and 98.4% of classification accuracy is obtained by using Enhanced CNN. Statistical analysis of parameters such as accuracy, precision, F1-score, and recall was conducted, demonstrating that the Enhanced CNN method outperformed SVM, NB,ELM, KNN and ANN classifiers. The Enhanced CNN method achieved an accuracy of 0.984, precision of 0.949, recall of 0.972, and an F1-score of 0.960 on the training dataset, which is significantly higher than the other classifiers. Furthermore, the Enhanced CNN algorithm’s ability to automatically learn features and efficiently process large datasets enhances its potential as a powerful tool for accurately classifying stroke lesions.
A quality evaluation method for intelligent traffic management system based on business data flow
Authors: Cheng Chen , Li Bixin , Chen Dong
Published: July 2023

Intelligent Traffic Management System (ITMS) is a complex and intelligent cyber-physical system (CPS) with multi-subsystem interaction, which plays a significant role in traffic safety. However, the quality evaluation requirements of ITMS, particularly its running quality, cannot be satisfied by the current quality evaluation metrics. Moreover, the present ITMS evaluation techniques are arbitrary. The effectiveness of road traffic is impacted because ITMS quality cannot be adequately assured. To fill this gap, this paper proposes a quality evaluation (QE) methodology based on the ITMS business data flow. First, the ITMS QE dimension extraction process was introduced to describe the ITMS architecture and activities; then the new evaluation indexes including intelligence, complexity and interactivity were proposed and an ITMS QE model was established; further through the measurement of metrics elements, the quality score of the indicators were calculated; finally a prototype tool was developed to verify the efficacy and practicability of the method. The results showed that the proposed method has the advantages of accurate problem tracking and decrease decision-making uncertainty. This is applicable to the ITMS QE in various operational scenarios.
Detection of lung cancer using novel attention gate residual U-Net model and KNN classifier from computer tomography images
Authors: Princy Magdaline P. , Ganesh Babu T.R.
Published: July 2023

Computed tomography (CT) scan pictures are routinely employed in the automatic identification and classification of lung cancer. The texture distribution of lung nodules can vary widely over the CT scan space and requires accurate detection. The evaluation of discriminative information in this volume can tremendously aid the classification process. A convolutional neural network, the Attention Gate Residual U-Net model, and KNN classifiers are utilized to detect lung cancer. The dataset of 1097 computed tomography (CT) images utilized in this study was obtained from the Iraq-Oncology Teaching Hospital/National Centre for Cancer Diseases (IQ-OTH/NCCD) to segment and classify lung tumors from CT images using the novel Attention Gate Residual U-Net model, i.e., AGResU-Net and CNN architecture. The initial step is applying CNN to detect normal, benign, and malignant patients in CT images. Second, use AGResU-Net to partition lung tumour areas. In the third section of the project, a KNN classifier is used to determine if an instance is malignant or benign. In the initial phase, CNN was proposed to classify three distinct regions. Three optimization strategies are used in this work: Adam, RMSP, and SGDM. The classifier’s accuracy is 97%, 85%, and 82%, respectively. When compared to the RMSP optimizer, the Adams optimizer predicts probability rates more accurately. In the second phase, AGResU-Net is used for schematic segmentation of the tumor region. In the third phase, a KNN classifier is used to classify benign and malignant tumor from the segmented tumor regions. A new segmentation of the lung tumor model is proposed. In this developed algorithm, the labelled classified data set and the segmented tumor output result provide the same accuracy. The study results demonstrate high tumour classification accuracy and high probability of detection in benign and malignant cases.
Better diet quality is associated with healthier aging among urban elderly
Authors: Surya Reggie , Surya Ervan , Nurkolis Fahrul , Santos Reinaldo Socorro , Suryani Yunita
Published: July 2023

BACKGROUND:

Diet quality is suggested to be an important element in a healthy aging experience among elderly population.

OBJECTIVE:

We investigated the association of diet quality and parameters related to healthy aging in elderly living in urban areas.

METHODS:

A cross-sectional study was carried out on 1,355 older adults aged 60 years or older living in big cities in Indonesia from April 2016 until June 2017. Diet quality was assessed using the healthy eating index (HEI-2015) while healthy aging was determined using the healthy aging index (HAI) consisting of 5 physiological indicators: systolic blood pressure, forced vital capacity, random blood glucose, serum cystatin C, and digit symbol substitution test. The correlation among study variables was analyzed using Spearman’s correlation test and linear regression test.

RESULTS:

The HEI-2015 and HAI scores obtained in this study were (48.8±3.5) and (5.2±0.3) respectively, thus demonstrating a slightly poor diet quality and health status. The HEI-2015 score was strongly associated with the HAI (ρ=–0.85, p<0.05; β=–0.08, 95% CI: –0.13–(–0.02), p<0.05). Four components of the HEI-2015 were found to be strongly associated with the HAI score: whole fruits, total vegetables, sodium, and added sugars. The physiological parameters of the HAI correlating strongly with the HEI-2015 score were systolic blood pressure and random blood glucose.

CONCLUSIONS:

Our study is the first to establish the strong correlation between the HEI-2015 and HAI. Our findings suggest that improving diet quality would help urban elderly support their healthy aging experience.
Multi-objective secure aware workflow scheduling algorithm in cloud computing based on hybrid optimization algorithm
Authors: Narendrababu Reddy G. , Phani Kumar S.
Published: July 2023

Cloud computing provides the on-demand service of the user with the use of distributed physical machines, in which security has become a challenging factor while performing various tasks. Several methods were developed for the cloud computing workflow scheduling based on optimal resource allocation; still, the security consideration and efficient allocation of the workflow are challenging. Hence, this research introduces a hybrid optimization algorithm based on multi-objective workflow scheduling in the cloud computing environment. The Regressive Whale Water Tasmanian Devil Optimization (RWWTDO) is proposed for the optimal workflow scheduling based on the multi-objective fitness function with nine various factors, like Predicted energy, Quality of service (QoS), Resource utilization, Actual task running time, Bandwidth utilization, Memory capacity, Make span equivalent of the total cost, Task priority, and Trust. Besides, secure data transmission is employed using the triple data encryption standard (3DES) to acquire enhanced security for workflow scheduling. The method’s performance is evaluated using the resource utilization, predicted energy, task scheduling cost, and task scheduling time and acquired the values of 1.00000, 0.16587, 0.00041, and 0.00314, respectively.
Deep learning classifiers for computer-aided diagnosis of multiple lungs disease
Authors: ur Rehman Aziz , Naseer Asma , Karim Saira , Tamoor Maria , Naz Samina
Published: July 2023

Background: Computer aided diagnosis has gained momentum in the recent past. The advances in deep learning and availability of huge volumes of data along with increased computational capabilities has reshaped the diagnosis and prognosis procedures. Objective: These methods are proven to be relatively less expensive and safer alternatives of the otherwise traditional approaches. This study is focused on efficient diagnosis of three very common diseases: lung cancer, pneumonia and Covid-19 using X-ray images. Methods: Three different deep learning models are designed and developed to perform 4-way classification. Inception V3, Convolutional Neural Networks (CNN) and Long Short Term Memory models (LSTM) are used as building blocks. The performance of these models is evaluated using three publicly available datasets, the first dataset contains images for Lung cancer, second contains images for Covid-19 and third dataset contains images for Pneumonia and normal subjects. Combining three datasets creates a class imbalance problem which is resolved using pre-processing and data augmentation techniques. After data augmentation 1386 subjects are randomly chosen for each class. Results: It is observed that CNN when combined with LSTM (CNN-LSTM) produces significantly improved results (accuracy of 94.5 %) which is better than CNN and InceptionV3-LSTM. 3,5, and 10 fold cross validation is performed to verify all results calculated using three different classifiers Conclusions: This research concludes that a single computer-aided diagnosis system can be developed for diagnosing multiple diseases.
Use of Tofu Waste as Food for Silver Worms (Tubifex sp)
Authors: Khotimah Khusnul , Helmizuryani Helmizuryani , Sari Meika Puspita , Dwi Harmilia Elva , Suyatno Suyatno , Rosmiah Rosmiah
Published: July 2023

Silkworms (Tubifex sp) are a natural feed with high nutritional content and are needed by fish, especially in the fry phase to support fish growth. Therefore, knowledge of natural food cultivation is needed to support the success of fish farming. Silkworm cultivation requires media with high organic content. Tofu pulp waste is one of the media that can be utilized for silkworm cultivation.  The purpose of this activity is to increase community skills in silkworm cultivation by utilizing tofu pulp waste as a cultivation medium to provide natural feed for cultured fish carried out by the Bumdes fish farming group of Serdang Menang village, SP. Padang OKI. Padang OKI.  The method is carried out by conducting counseling and mentoring in making silkworm cultivation sites and how to cultivate silkworms. Community Service activities regarding the production of silkworm cultivation with a system of utilizing organic waste have been well understood by the community.  It is hoped that the community in Serdang Menang Village, SP. Padang Kab.OKI can apply it in fish farming activities.
Export and application of SARIMA model for forecasting the value of Vietnam export during Covid-19
Authors:   University of Economics and Law, Ho Chi Minh City, Vietnam, Nguyễn Ngọc Diep Thị ,   Vietnam National University, Ho Chi Minh City, Vietnam
Published: July 2023

This article examines the export value before and during the ongoing Covid-19 pandemic in Vietnam, and applies the SARIMA model to forecast the export value of Vietnam in the period from 01/2000 to 05/2021, collected from VietstockFinance and processed using Eviews 10 software. Research results show that the Covid-19 pandemic does not seem to affect Vietnam's export value compared to the same period last year. Through this result, it also shows that the Government of Vietnam has taken good export strategy to deal with the pandemic and bring high export value. The results of applying SARIMA model show that the model has a predictive value that approximates the actual export value with high accuracy in the period from January 2000 to May 2021. From testing the forecast accuracy of the SARIMA model, the study also makes forecasts about Vietnam's export value from 06/2021 to the end of 2021. Based on the research results, the authors also make a number of recommendations for current export policy makers to focus on diversifying export markets, actively seeking new markets, effectively exploiting export markets and exploiting export markets, opportunities from FTAs, successfully harmonizing the "dual goal" of both preventing and controlling the Covid-19 epidemic and promoting economic development in Vietnam.
Trust, organizational commitment and tacit knowledge sharing between employees in IT industry firms in Ho Chi Minh City
Authors:   Vietnam Aviation Academy, Doan Bao Son
Published: July 2023

In organizations, knowledge is divided into two types: explicit and tacit knowledge. Tacit knowledge can play an important role towards company’s sustainable development and competitiveness capabilities. The crucial of tacit knowledge has been verified in relation to decision-making, time management, quality and performance in organizations. Tacit knowledge is an intangible asset and its value increases as more people share it. However, tacit knowledge sharing is not a very easy task because of its complex nature. This study aims to analyze the psychological mechanism affecting the tacit knowledge sharing (TKS) behaviour of IT employees based on psychological contract model and organizational commitment literature. Surveys were designed by structured questionnaires to collect data using convenience sampling and yielded 408 responses from IT employees working at IT industry enterprises in Ho Chi Minh City. The research hypotheses were developed and validated using structural equation modeling (SEM) approach. The results show that TKS is directly influenced partly by trust (TRU) among coworkers and three organizational commitment components such as affective, normative, and continuance commitment (AOC, COC and NOC) mediate the relationship between TRU and TKS. Based on these results, author offers some suggestions to managers in firms concerning relevant policies that enable their knowledgeable employees to share tacit knowledge.
Factors affecting the willingness to accept digital transformation by small and medium enterprises in Ho Chi Minh City
Authors:   Sai Gon University, Vietnam, Nguyen Hang Phan Thu , Ho Toan Anh ,   VNPT HCM
Published: July 2023

Digital transformation is becoming a strategy at businesses and organizations in the 4th Industrial Revolution. The 2020 report by Cisco & IDC on digital maturity of small and medium-sized businesses in 14 countries in the Asia-Pacific region shows that: 31% of businesses are in the early stages of digital transformation, down 8% compared to 2019; 53% are in the observation period - a 3% increase compared to 2019; 13% are in the challenging stage, and 3% of the businesses have entered the mature stage, an increase of 4% and 1% respectively from 2019. Digital transformation is an irreversible trend; if a business do not keep up with it, they will inevitably fail, especially small and medium enterprises in Vietnam.The study analyzes the factors affecting the willingness to accept of Digital Transformation by small and medium enterprises (SMEs) in Ho Chi Minh City. For research, the author collects data from a direct survey of 290 SMEs in Ho Chi Minh City. The research results show that there are 8 independent factors affecting the adoption of Digital Transformation by enterprises: (1) Perceived relative advantage, (2) Perceived compatibility, (3) Perceived complexity, (4) Knowledge of digital transformation, (5) Management awareness of digital transformation, (6) External change agents, (7) Pressure from partners and opponents. From there, the author proposes implications to raise awareness of SME business owners equip, update knowledge, change awareness, see the benefits and advantages of businesses accepting to participate in digital transformation, suitable in line with social development, in line with the trend of the 4.0 technology era.
The impact of household size and income on food spending in Vietnam
Authors:   Ho Chi Minh City University of Technology and Education, Lê THỊ TUYẾT THANH , HUỲNH THỦY TIÊN ,   University of Economics and Law, VNU-HCM
Published: July 2023

The study analyzes the impact of income and household size on per capita food expenditure in Vietnam, thereby testing the food paradox. The data for the study was extracted from the dataset of the results of the Vietnam Living Standards Survey 2018 (VHLSS 2018). After the data was connected, filtered, and cleaned, 34,448 observations were qualified. To overcome endogenous difficulties in the model, the estimation of linear Engel equations using instrumental variable regression was conducted. The findings of the study reveal that as household size increases, average food expenditure reduces, supporting the food paradox that exists in the Vietnamese food market. The positive relationship between income per capita and average expenditure on food is also confirmed in the OLS model. Research shows that households with the head being married, educated, employed (especially self-employed) have a higher average expenditure on food than those in other household groups. The average food cost per household rises in households with a high number of children and the elderly. The findings of this study will assist food companies in forecasting market demand, allowing them to develop effective business strategies and production plans. It also aids policymakers in forecasting food demand so that proper national food security policies can be implemented.
Effects of exports on the growth of small and medium enterprises – empirical evidence from Vietnam
Authors:   Foreign Trade University, Ho Chi Minh City, Vietnam, Lê Ngân Thị Thanh
Published: July 2023

The paper aims to examine the impact of exports on the growth of Vietnamese manufacturing small and medium-sized enterprises (SMEs) by exploring the information of 36,486 enterprises across 24 manufacturing sectors from the Vietnam Annual Enterprise Survey (VAES) in the period 2014-2019. To deal with the problem of variable variance, autocorrelation, and endogeneity of the model, the paper uses the Pooled Ordinary Least Squares (POLS) regression method with a strong standard error method and system Generalized Method of Moments (GMM). Export participation by SMEs is positively associated with business growth in terms of sales and employee, according to the findings. Moreover, the positive impact of exporting on firm growth is greater among permanent exporters than among new exporters. The relationship between exporting and employment growth is negative among firms that exit international activities. The study's findings indicate the need of adopting policies that promote SMEs in transition economies like Vietnam to engage in exporting activities. Furthermore, the findings show that financial assistance and suitable ownership would enable SMEs to take advantage of export opportunities to increase sales and employees.
Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Authors: Sayyad Shabnam , Sayyad Farook
Published: July 2023

In this study, artificial neural networks (ANNs) are being used to diagnose hair loss in patients. An autoimmune condition known as Alopecia Areata (AA) results in hair loss in the affected area. The most recent figures from throughout the world show that AA affects 1 in 1000 persons and has a 2% incidence rate. Based on the look of photographs with healthy hair in the dataset, machine learning techniques were employed to classify the conditions. Before making predictions, each of these ANNs algorithms creates a prediction model using pictures of healthy hair. The aim of this study is to evaluate the accuracy of neural networks for alopecia detection in human subjects. The study presents a classification framework for distinguishing between healthy hairs (HHs) and Alopecia Areata (AA). The framework incorporates Contrast Limited Adaptive Histogram Equalization (CLAHE) enhancement and segmentation techniques to enhance the quality of the images. Additionally, Data Augmentation (DA) is employed to generate additional data and improve the precision of the proposed framework. To extract features from the images, two powerful techniques are utilized. The Visual Geometry Group (VGG), which consists of very deep convolutional networks designed for large-scale image recognition, is employed. VGG networks have proven to be effective in learning complex features directly from data, eliminating the need for manual feature extraction. Additionally, a Convolutional Neural Network (CNN), a deep learning network architecture specifically designed for image processing tasks, is employed. To create a machine learning model for classification, the Support Vector Machine (SVM) approach is utilized. SVM is a widely used algorithm in supervised learning, capable of solving both classification and regression problems. Its versatility and effectiveness make it a suitable choice for the classification task in this study. By combining the CLAHE enhancement, segmentation, data augmentation, feature extraction using VGG and CNN, and classification using SVM, the proposed framework aims to accurately classify HHs and AA cases.
Desa Wisata Tegaren: Sadewa, Jadesta, Adwi dan Persepsi Sosial Publik Terhadap Kemajuan Desa Wisata
Authors: Nuryananda Praja Firdaus , Mijiarto Joko , Alawi A. Muammar , Wahyuni Wahyuni
Published: July 2023

It has been four years since the process of developing a tourism village in Tegaren has been going on since 2019. Appreciation to the hard work of all parties involved in raising a tourism village in Tegaren, this village, which is located in the northern part of Trenggalek, has made several achievements. In addition to being one of the Seratus Desa Wisata villages that were fostered directly by Trenggalek Regency, Tegaren has succeeded in becoming the top 500 Anugerah Desa Wisata Indonesia 2022 and won third place at the local Soetran Award. The research team later found that with this series of achievements, the progress of developing tourism villages in Tegaren ultimately created positive social perceptions from stakeholders in Tegaren and the wider village community. By using interview instruments, questionnaires, and literature studies, the research team assessed that this perception was formed due to three things, including 1) the increasing attention that Tegaren received from the Trenggalek Regency government and the agencies under it, 2) the more trusted Tegaren to be the organizer of the official activities by the Trenggalek Regency government, and 3) the existence of village original income (pendapatan asli desa/PAD) from the tourism sector which this time became the first time Tegaren received PAD from the tourism sector. The three results of confirmation of the positive perception are verification of the success of the community-based tourism concept in developing rural tourism.