bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and development of portable smart traffic signaling system with cloud-artificial intelligence enablement
Authors: Kamasetty Badarinath , Renduchintala Mahesh , Shetty Lochan Lingaraja , Chandarshekar Suresh , Shettar Rajashree
Published: April 2022

With increasing traffic, apart from the major traffic junctions, there are few smaller junctions which witness heavy traffic only during a certain period of the day. For such cases, deploying of conventional traffic lights are not a viable option. A cost-effective internet of things (IoT) enabled portable smart traffic signaling system is designed using ESP32 dual core microcontroller, to assist traffic personnel working at small traffic junctions. It uses a foldable mechanical structure which can be carried easily. The system is designed to work with and without internet connectivity depending on its functionality and place of deployment. The system can be pre-programmed with default time value to work without human intervention. Using an android application, the user can manually control the traffic signal by analysing the traffic density. System gathers the traffic density information based on the operations performed by the traffic personnel and stores it in the cloud. In Smart mode, system computes the mean value and also runs K-means clustering algorithm on the dataset to generate optimized time values. Comparison of the data generated using manual and automatic modes infer the credibility of the system in generating optimized time values and reducing human effort.
Protection coordination of directional over current relay with distributed generation
Authors: Tripathi Jayant Mani , Gupta Santosh Kumar , Ranjan Mrinal , Kumar Vikash , Yadav Shivam , Chandel Aseem , Singh Smriti
Published: April 2022

The present study is focussed on a comparative analysis of different meta-heuristic optimization approaches for directional overcurrent relay (DOCRs) coordination which has been discussed and presented in the literature. Further, to have a comparative analysis of the performance of the optimization methods discussed they have been tested on power system network of different sizes. To overcome such issues, this work proposed a simplex linear programming technique-based overcurrent relay method using general algebraic modelling system (GAMS). The execution of this work is done on the MATLAB 2018 a platform. Based on the obtained result the best meta-heuristic optimization method for mitigating the problem of relay coordination has been identified. Nevertheless, the operating time of the relay is high, so the fault is not corrected at a time. The developed model has been tested on test system of different sizes namely IEEE 9 bus and IEEE 14 bus system. The obtained values through series of simulation are compared with different methods for proving the proposed protection coordination scheme is more effective and efficient than others in terms of operating time and coordination time.
Sentiment classification of delta robot trajectory control using word embedding and convolutional neural network
Authors: Iklima Zendi , Kadarina Trie Maya , Hajar Muhammad Hafidz Ibnu
Published: April 2022

Sentiment classification (SC) is an important research field in natural language processing (NLP) that classifying, extracting and recognizing subjective information from unstructured text, including opinions, evaluations, emotions, and attitudes. Human-robot interaction (HRI) also involves natural language processing, knowledge representation, and reasoning by utilizing deep learning, cognitive science, and robotics. However, sentiment classification for HRI is rarely implemented, especially to navigate a robot using the Indonesian Language which semantically dynamics when written in text. This paper proposes a sentiment classification of Bahasa Indonesia that supports the delta robot to move in particular trajectory directions. Navigation commands of the delta robot were vectorized using a word embedding method containing two-dimensional matrices to propose the classifier pattern such as convolutional neural network (CNN). The result compared the particular architecture of CNN, GloVe-CNN, and Word2Vec-CNN. As a classifier method, CNN models trained, validated, and tested with higher accuracy are 98.97% and executed in less than a minute. The classifier produces four navigation labels: right means 'kanan', left means 'kiri', top means 'atas', bottom means 'bawah', and multiplier factor. The classifier result is utilized to transform any navigation commands into direction along with end-effector coordinates.
Datasets design of gate diffusion input based pipeline architecture for numerically controlled oscillator
Authors: Gujjula Ramana Reddy , Perumal Chitra , Kodali Prakash , Rajanna Bodapati Venkata
Published: April 2022

Gate diffusion input (GDI) is a technique, which enables reducing power consumption, area and delay in the digital circuits significantly, at the same time maintains low complexity of the logical design. This paper focuses on the analysis and interpretation of the design and implementation of GDI-based pipeline architecture for numerically controlled oscillator (NCO) using look up table (LUT). Based on the input signal and the alternate signal, this phase separation will separate the phase difference signal. The NCO generates a frequency and phase harmonized output signal with an antecedence fixed frequency clock. The 32-bit counter then compares the current count to the value stored in the compare register. Here the Coherent control comes into picture. It controls the carrier synchronizer by employing data from the 32-bit counter and the obtained data will be saved. It is updated and advanced using the third peer group of frequency synthesis technology. The test outcomes are accompanied with the theoretical concept and reproduced the results. The main objective of GDI-based pipeline architecture for NCO using LUT is to reduce the usage of metal oxide semiconductor field effect transistors (MOSFET’s). NCO is an indispensable component in many digital communication systems linked to modems, software-defined radios, and digital radio, digital down/upconverters for cellular and personal communications service base stations.
Impacts of relay and direct links at destinations in full-duplex non-orthogonal multiple access system
Authors: Do Dinh-Thuan , Nguyen Tu-Trinh Thi
Published: April 2022

In this study, one of effective methods of multiple access, namely non-orthogonal multiple access (NOMA), is investigated. Such NOMA scheme can be worked with signal processing at downlink side. As such, the base station sends mixed signals of two signals to destinations. A near user could be a relay to forward the signal to the distant user by leveraging benefits of full-duplex mode which allows relay to transmit and receive signals in the same time. For simple analysis, the two-user approach and fixed power allocation factors are implemented. We also derive formulas of the outage probability of two users (near-user and far-user) to indicate fairness and emphasize the role of the near user as a relay. This considered NOMA system adopts transmission with Nakagami-m fading channel. As a further metric, throughput is considered under the impacts of key system parameters. The transmit signal-to-noise ratio (SNR) at the base station make influences the performance of two users significantly as observation indicated in our simulation results. These results are confirmed by matching Monte-Carlo with the theoretical simulations.
Spam detection by using machine learning based binary classifier
Authors: Abdul Kadir Mohd Fadzil , Abidin Ahmad Faisal Amri , Mohamed Mohamad Afendee , Hamid Nazirah Abdul
Published: April 2022

Because of its ease of use and speed compared to other communication applications, email is the most commonly used communication application worldwide. However, a major drawback is its inability to detect whether mail content is either spam or ham. There is currently an increasing number of cases of stealing personal information or phishing activities via email. This project will discuss how machine learning can help in spam detection. Machine learning is an artificial intelligence application that provides the ability to automatically learn and improve data without being explicitly programmed. A binary classifier will be used to classify the text into two different categories: spam and ham. This research shows the machine learning algorithm in the Azure-based platform predicts the score more accurately compared to the machine learning algorithm in visual studio, hybrid analysis and JoeSandbox cloud.
Identifying significant elements of the digital transformation of organizatios in Kuwait
Authors: Alshehab Abdullah , Alfozan Thalaya , Gaderrab Hesham F. , Alahmad Mohammad Abdulateef , Alkandari Abdulrahman
Published: April 2022

The adoption and implementation of digital transformation (DT) plans and initiatives have become compulsory for organizations worldwide during this flourishing era of advanced technology. However, it is estimated that 70% of all DT initiatives do not achieve their goals, with billions of dollars going to waste. This study identified the main elements of digital transformation initiatives from the literature by scholars around the world and then applied these elements to organizations in Kuwait. 33 organizations (private and public) in Kuwait participated in a survey to investigate the level of readiness of organizations attempting to execute digital transformation plans and initiatives. Some insights were found: having a well-defined strategic vision in organizations, digital leadership, technical talent, and having digital expertise are significant elements in implementing digital transformation plans.
Rapid bacterial colony classification using deep learning
Authors: Akbar Son Ali , Ghazali Kawarul Hawari , Hasan Habsah , Mohamed Zeehaida , Aji Wahyu Sapto , Yudhana Anton
Published: April 2022

Bacterial colonies infection is one of the causes of bloodstream disease, and it can be a fatality. Therefore, medical diagnoses require fast identification and classification of organisms. Artificial Intelligence with deep learning (DL) can now be developed as a rapid bacterial classification. The research aims to combine deep learning and support vector machines (SVM). The ResNet-101 model of the DL algorithm extracted the image’s features using transfer learning then classified by the SVM classifier. According to the experimental results, this model had 99.61% accuracy, 99.58% recall, 99.58% precision, and 99.97% specificity. The technique presented might enhance clinical decision-making.
Multilayer perceptron artificial neural networks-based model for credit card fraud detection
Authors: Kasasbeh Bassam , Aldabaybah Balqees , Ahmad Hadeel
Published: April 2022

Nowadays, credit card fraud has emerged as a major problem. People are becoming increasingly using credit cards to pay for their transactions, it has become more popular and essential in our lives. Fraudsters are developing new strategies and techniques over time, and it is not easy for humans to manually check out all transactions. The cost of fraudulent transactions is significant and without prevention mechanisms it is rising. Finding the best methodology to detect fraudulent transactions is a crucial asset to the industry to reduce the fraud financial loss. Artificial neural networks (ANN) technique is considered as one of the effective techniques that has proved its efficiency in detecting credit card fraud transactions with high precision and minimum cost. In this paper, we propose a multilayer perceptron (MLP) ANN-based model solution to improve the accuracy of the detection process. The performance of the methodology is measured based on the precision, sensitivity, specificity, accuracy, F-measure, area under curve (AUC) and root mean square error (RMSE). Moreover, we illustrate the performance results of these measures with a descriptive analysis. Experimental results have shown that the proposed ANN-based model is efficient and does improve the accuracy of the detection of fraudulent transactions.
Convolutional neural network for the detection of coronavirus based on X-ray images
Authors: Ahmed Essam Hammodi , Alsemawi Majid Razaq Mohamed , Hasan Mutar Mohammed , Hanoosh Hatem Oday , Abbas Ali Hashem
Published: April 2022

Nowadays, the coronavirus disease (COVID-19) is considered an ongoing pandemic that spread quickly in most countries around the world. The COVID-19 causes severe acute respiratory syndrome. Moreover, the technique of chest computed tomography (CT) is a method used in the detection of COVID-19. However, the CT method consumes more time and higher-cost as compared with chest X-ray images. Therefore, this paper presents convolutional neural network (CNN) algorithm in the detection of COVID-19 by using X-ray images. In this method, we have used a balanced image database for the normal (healthy) and COVID-19 subjects. The total number of image database is 188 samples (94 healthy samples and 94 COVID-19 samples). Furthermore, there are several evaluation measurements are used to evaluate the proposed model such as accuracy, precision, specificity, sensitivity, F-measure, G-mean, and others. According to the experimental results, the proposed model obtains 98.68% accuracy, 100% precision, and 100% specificity. Besides, the proposed model achieves 97.37%, 98.67%, and 98.68% for sensitivity, F-measure, and G-mean, respectively. The performance of the proposed model by using CNN algorithm shows promising results in the detection of COVID-19. Also, it has outperformed all its comparatives in terms of detection accuracy.
A cluster validity for optimal configuration of Kohonen maps in e-learning recommendation
Authors: Mawane Jamal , Naji Abdelwahab , Ramdani Mohamed
Published: April 2022

the first block of our unsupervised deep collaborative recommendation (UDCF) system and proposes a platform whose goal is to try to find the adequate parameters of the Kohonen maps, to create homogeneous clusters in profile data and results, the homogeneity is verified thanks to the very low variance rate of the results obtained by the cluster population and a second criterion which is the high prediction rate of collaborative recommendation. Although the revision concerns only the clustering block, and the use of a symmetrical autoencoder without searching for its optimization, the result obtained (82.33%) for the optimal configurations with high homogeneity of the Kohonen map is equivalent to the optimized result of the UDCF and even better than the classical recommendation methods
Novel approach for semantic similarity cross ontology
Authors: Benaissa Kaddar Leila , Ben-Naoum Farah
Published: April 2022

Measuring semantic similarity between terms is a crucial step in information retrieval and integration since it necessitates semantic content matching. Even though several models have been proposed to measure semantic similarity, these models are not able to effectively quantify the weight of relevant items that affect the semantic similarity judgment process. In this study, we present a new method for measuring semantic similarity between cross-ontologies, that consists of hybridizing node-based approaches such as WuP and Reda with the weight of similarity computed using WordNet. The proposed approach has been experimented to show its efficiency with two ontologies, configuration management tool (CMT) and ConfOf, from the conference domaine in the web ontology language (OWL) ontologies benchmark OAEI 2015 and evaluated using two metrics: density and cohesion.
Two phase secure data collection technique for wireless sensor networks
Authors: Thahniyath Gousia , Mishra Priti , Moorthy Sundar Raj
Published: April 2022

Wireless sensor networks (WSNs) are the sensors that are dispersed in a different location that can sense the accumulated data in real-time and send it to the central location for the process of data aggregation. During the transfer of the information using the data nodes from the WSNs to the central location, there may be chances that the data node could be compromised by sensor failure or by an attack from a malicious user. To overcome this problem, we propose a two-phase secure data collection (TPSDC) technique for wireless sensor networks which provides confidentiality and integrity for the data nodes that are being sent to the central location and also during the data aggregation in the central location. Various existing methods have been proposed to secure the data when sent from the WSNs to the internet of things (IoT) devices but they lack to provide both confidentiality and integrity at the same time. Hence our model provides both integrity and confidentiality by providing security to the data nodes. Experimental results show that our model TPSDC performs better in terms of misclassification rate, detection rate, throughput, network lifetime analysis of the node, and communication overhead of the node when compared with the existing methods.
Turbo polar code based on soft-cancelation algorithm
Authors: Alebady Wallaa Yaseen , Hamad Ahmed Abdulkadhim
Published: April 2022

Since the first polar code of Arikan, the research field of polar codes has been continuously active. Improving the performance of finite-code-length polar codes is the central point of this field. In this paper, the parallel concatenated systematic turbo polar code (PCSTPC) model has been proposed to improve the polar codes performance in a finite-length regime. On the encoder side, two systematic polar encoders are used as constituent encoders. While on the decoder side, two single iteration soft-cancelation (SCAN) decoders are used as soft-in-soft-out (SISO) algorithms inside the iterative decoding algorithm of the parallel concatenated systematic turbo polar code (PCSTPC). As compared to the optimized turbo polar code with SCAN and BP decoders, the proposed model has about 0.2 dB and 0.48 dB gains at BER=10(-4), respectively, in addition to 0.1 dB, 0.31 dB, and 0.72 dB gains over the TPC-SSCL32, TPC-SSCL16, and TPC-SSCL8 models, respectively. Moreover, the proposed model offers less complexity in comparison with other models, therefore requiring less memory and time resources.
Predicting customers churning in banking industry: A machine learning approach
Authors: Muneer Amgad , Faizan Ali Rao , Alghamdi Amal , Mohd Taib Shakirah , Almaghthawi Ahmed , Ghaleb Ebrahim Abdulwasea Abdullah
Published: April 2022

In this era, machines can understand human activities and their meanings. We can utilize this ability of machines in various fields or applications. One specific field of interest is a prediction of churning customers in any industry. Prediction of churning customers is the state of art approach which predicts which customer is near to leave the services of the specific bank. We can use this approach in any big organization that is very conscious about their customers. However, this study aims to develop a model that offers a meaningful churn prediction for the banking industry. For this purpose, we develop a customer churn prediction approach with the three intelligent models Random Forest (RF), AdaBoost, and Support Vector Machine (SVM). This approach achieves the best result when the Synthetic Minority Oversampling Technique (SMOTE) is applied to overcome the unbalanced dataset and the combination of undersampling and oversampling. The method on SMOTED data has produced excellent results with a 91.90 F1 score and overall accuracy of 88.7% using RF. Furthermore, the experimental results show that RF yielded good results for the full feature-selected datasets.
Short term forecasting of electrical consumption using a neural network: joint approximate diagonal eigenvalue
Authors: Hussain Mashitah Mohd , Zakaria Zuhaina , Dahlan Nofri Yenita , Ilham Nur Iqtiyani , Hussin Zhafran , Rahman Noor Hasliza Abdul , Md Yasin Md Azwan
Published: April 2022

This article aims to estimate the load profiling of electricity that provides information on the electrical load demand. In achieving this research implemented the neural network algorithm of joint approximate diagonalisation of eigen-matrices (JADE) to describe the load profile pattern for each point. Nowadays, utility providers claim that natural sources are used to generate power by rising consumer demands for energy. However, occasionally utility workers need to know the demand at certain location, corresponding to maintenance issues or for any shutdown area involved.
 A distribution pattern based on the data can be predicted based on the incoming data profile without having detailed information of certain load bus, the concept of derivatives was relevant to forecast the types of distribution data. The model was constructed with load profile information based on three different locations, and the concept of derivative was recognized, including the type of incoming data. Historical data were captured from a selected location in Malaysia that was proposed to train the JADE algorithm from three different empirical distributions of consumers, recording every 15 minutes per day. The results were analyzed based on the error measurement and compared with the real specific load distribution feeder information of needed profiles.
Agent-based model simulation for ground penetration radar based on Netlogo platform
Authors: Bezzout Hamid , El Faylali Hanan
Published: April 2022

Ground penetrating radar is used to detect magnetic materials underground by transmitting an electromagnetic wave into the material and receive the reflected pulse. In this paper, we develop a new agent-based model to simulate and evaluate the behavior of the ground penetrating radar based on Maxwell’s equations. This model contains several agents that represent the electric field, the magnetic field, the transmitted wave, the simulated medium, and the object to be detected. The implementation of this model is performed in Netlogo plaform because of its simplicity of coding and robustness of simulation. In order to validate our model, we have simulated the effect of the medium characterized by a dielectric constant and a conductance on the transmitted wave to evaluate the behavior of ground penetrating radar. The results obtained are compared with the literrature. Findings demonstrate that the transmitted pulse in the form of Gaussian pulse is reflected when it interacts with the object to detect. Thus, the ground penetrating radar can be efficiently simulated on Netlogo platform.
Elastic net feature selected multivariate discriminant mapreduce classification
Authors: Nakkiran Arunadevi , Thulasiraman Vidyaa
Published: April 2022

Analyzing the big stream data and other valuable information is a significant task. Several conventional methods are designed to analyze the big stream data. But the scheduling accuracy and time complexity is a significant issue. To resolve, an elastic-net kernelized multivariate discriminant map reduce classification (EKMDMC) is introduced with the novelty of elastic-net regularization-based feature selection and kernelized multivariate fisher Discriminant MapReduce classifier. Initially, the EKMDMC technique executes the feature selection to improve the prediction accuracy using the Elastic-Net regularization method. Elastic-Net regularization method selects relevant features such as central processing unit (CPU) time, memory and bandwidth, energy based on regression function. After selecting relevant features, kernelized multivariate fisher discriminant mapr classifier is used to schedule the tasks to optimize the processing unit. Kernel function is used to find higher similarity of stream data tasks and mean of available classes. Experimental evaluation of proposed EKMDMC technique provides better performance in terms of resource aware predictive scheduling efficiency, false positive rate, scheduling time and memory consumption.
GROWTH OF BLACK SOLDIER FLY LARVAE ( Hermetia illucens ) FED WITH PAK CHOI ( Brassica chinensis ) AND CARP ( Cyprinus carpio ) RESIDUES
Authors: Permana Agus Dana , Putra Ramadhani Eka , Nurulfah Auliya , Rosmiati Mia , Kinasih Ida
Published: April 2022

One main drawback of the local animal industry is the inavailability of affordable and sustainable protein supply for the livestock. Insect larvae, such as the Black Soldier Fly (Hermetia illucens) larvae (BSFL), have been considered as a protein source which can be produced at a large scale using low cost organic wastes as feeding material. This study was designed to determine the response of BSFL to various waste combinations of vegetable and animal remains, Pak Choi (Brassica chinensis) residues (S) and carp (Cyprinus caprio) fish offal (I)). A total of 540 BSFL were fed with 100 mg/larvae/day combination of vegetable wastes: animal waste 70%: 30% (S > I), 50%: 50% (S = I), and 30%: 70% (S < I). Among the feed combinations, the S < I group showed the best results as it produced the significantly highest weight of BSFL at 122.8 mg/larvae and approximate digestibility of 62.01%, with the least pupae mortality rate at 4.29%.Keywords: bioconversion, biomass, Brassica chinensis, Cyprinus carpio, Hermetia illucen
“Ah Lai’s Crossing” – Malaysia’s first artificial road canopy bridge to facilitate safer arboreal wildlife crossings
Authors: Yap Jo Leen , Rosely Nik Fadzly Nik , Mahadzir Mazrul , Benedict Mark Louis , Muniandy Vikneswaran , Ruppert Nadine
Published: April 2022

Roads negatively affect wildlife populations globally, causing habitat fragmentation that can facilitate mortality by access to forest for poaching and wildlife collisions with vehicles. Primate habitats are vulnerable to fragmentation exposing them to anthropogenic threats. Endangered dusky langurs (Trachypithecus obscurus) in Malaysia are often found in urban areas and have been frequent victims of vehicle collisions. To mitigate the hazardous impact of a busy asphalt road on wild dusky langurs in Teluk Bahang, Penang, we built the first artificial road canopy bridge in Malaysia in February 2019 to assist arboreal wildlife to move between habitat fragments more safely. Four days after the bridge construction, the first long-tailed macaque (Macaca fascicularis) was recorded via a camera trap crossing the bridge, and plantain squirrels (Callosciurus notatus) and dusky langurs first crossed one and eight months later, respectively. The bridge was upgraded from a single-firehose rope to a double-rope in August 2020 to assess the effectiveness of the two designs. In total, 2128 animal crossings comprising three mammal species were recorded between March 2019 and May 2021. Plantain squirrels crossed the bridge most frequently with 2075 crossings, long-tailed macaques crossed 32 times, and dusky langurs 21 times. There was a significant difference in bridge use according to species between the two designs (Chi-Square, p < 0.001). Since the construction of the bridge, the rate of previously frequently reported primate roadkills near the bridge location has dropped to zero. This successful pilot project has spurred the efforts to implement more canopy bridges country-wide to support primate conservation efforts and better protect arboreal wildlife from the negative impacts of linear infrastructure.
The Falun Gong in the New World
Authors: Ownby David
Published: April 2022

Despite the polarised debate which has raged in the media over whether the Chinese spiritual movement Falun Gong should be seen as an ‘evil cult’ or as an innocent ‘cultivation system’, there is little doubt that most objective Western scholars would categorise Falun Gong as a new religious movement (many of which have also been accused rightly or wrongly of being ‘cults’ or ‘sects’). Indeed, the controversy surrounding Falun Gong has attracted considerable media and scholarly attention, so that the Falun Gong is now undoubtedly the best known of Chinese new religious movements and, as I argue elsewhere, a key to the reevaluation of a centuries-old tradition of popular religious practice in China which has long been condemned and suppressed by Chinese authorities. The present article, based on fieldwork in North America, on research in Falun Gong written sources and on my previous work in the history of Chinese popular religion traces a portrait of Falun Gong practices both in China and in North America.
Afterword: On Global Nation-States and Rooted Universalisms
Authors: Weller Robert P.
Published: April 2022

How far can wings of belief carry us? What kinds of new social and moral systems evolve out of transnational religious movements? The recent literature on globalisation has shown only little interest in religion, in spite of the cutting-edge global role of beliefs like evangelical Christianity. The literature has attended even less to the movement of non-Western traditions. We do, however, have numerous alternative models of how global ideas in general spread: they can seep through the cracks within and between systems of control based in nation-states; they can flow through mobile cosmopolitans with a global sense of belonging; they can reside in diasporas centred around the idea of a common homeland; they can exist in the institutions of transnational villages; and so on.

These various images of global culture are not mutually exclusive, of course, and none of them alone captures the full complexity of the possibilities. Here I want to explore briefly just two dialectical relationships that characterise some of the features of the transnational Chinese religions discussed in the essays collected here. The first is the relationship between global culture and the continuing institutional power of the nation-state. The second is the counterintuitive combination of universalising beliefs with a strong sense of rootedness in specific places or ethnicities.
Imperial Institutions and Drama in the Qing Court
Authors: Xiaoqing Ye
Published: April 2022

This article is based on largely uninvestigated archival material in the First Historical Archives in Beijing. It addresses the following issues: (1) How and why an internal office, the Nanfu, which was responsible for drama performances inside the palace, expanded its functions to become a monitoring organisation, the Shengpingshu, which exercised censorship over all the drama groups in the capital. (2) How political events were reflected in drama performed on both public and private occasions, thus shedding light on the inner world of individual emperors. (3) How these institutional changes led to the Qing court playing an active role in the transformation of a regional lower-class entertainment into Peking opera, a national art form appreciated by all classes.
Liberal Nationalism in Substantive and Performative Perspectives
Authors: Lægaard Sune
Published: April 2022

This paper sketches some developments in the discussion of liberal nationalism since the early 1990s and proposes a generic understanding of nationalism according to which its main feature is the act of sorting people into members and non-members of the nation with a view to regulating access to political goods linked to the state. One discussion of liberal nationalism that has recently received renewed attention is the relation between nationalism and multiculturalism. Liberal nationalism sees nationalism as a response to increased diversity and involves normative demands on nationalism for accommodating this diversity. In light of the proposed generic understanding of nationalism, the question arises whether such a liberal nationalism is coherent. This question requires us to distinguish between a substantive and a performative perspective on nationalism, raising the possibility that liberal nationalism can be substantively coherent but performatively incoherent.
Inclusive Membership as Fairness? A Rawlsian Argument for Provisional Immigrants
Authors: Baycan-Herzog Esma
Published: April 2022

Infamously, Rawls assumed a democratic society to be “a complete and closed social system,” in that “entry into it is only by birth and exit from it is only by death.” Since the beginning of the present millennium, however, debates about the ethical issues related to immigration have been prominent. In this context, these methodological departure points seem long outdated, if not simply biased. This paper will rework Rawls’s theory of migration for application to the case of provisional immigrants by reworking its theoretical underpinnings. I will argue that once his assumptions are adjusted, Rawlsian notions of ‘stability’ in conjunction with his idea of a ‘society understood as a fair system of cooperation’ justify inclusive membership regimes. In other words, Rawlsian domestic justice requires inclusive membership regimes for provisional immigrants.
Alternative Organizations as Systems Hijacking: The Commercial Trust as a Thought Experiment
Authors: Hachigian Heather M.
Published: April 2022

The COVID-19 crisis has renewed interest in alternative forms of organizing business and investment but our understanding of how these organizations can transform social systems is limited. The purpose of this article is to contribute to this understanding. In the context of one of the greatest transfers of wealth in global retail history that could see unprecedented numbers of businesses close or sold to distant, private interests, the article performs a thought experiment using the analogy of a commercial trust to encourage new ideas and critical reflection on community wealth building. The article introduces systems hijacking—a process of leveraging incumbent forms and systems in which they are embedded for new purposes—as an analytically useful concept for understanding how alternative organizations can transform social systems. The article finds organizational governance is necessary to transcend structural deficiencies in inherited or borrowed forms to make way for transformation.
Impact of Breastfeeding Support Services on Mothers’ Breastfeeding Experiences When Provided by an MD/IBCLC in the Pediatric Medical Home
Authors: Glassman Melissa E. , Blanchet Kelly , Andresen Jane , Lewis Rachel A. , Rosenthal Susan L.
Published: April 2022

Addressing breastfeeding issues enables mothers to reach their breastfeeding goals. We embedded a breastfeeding consultation service run by a pediatrician/International Board Certified Lactation Consultant (MD/IBCLC) in a medical home. This mixed-methods study investigated breastfeeding preparedness and the service’s perceived benefits. Mothers with breastfeeding issues/concerns identified at well-baby appointments were referred to the service. Telephone interviews and chart reviews were conducted with 28 participating mothers approximately 1 month after the visits. Breastfeeding Self-Efficacy Scale scores improved significantly from the time of the in-person appointment to 1 month later. Most mothers felt unprepared for breastfeeding despite prenatal efforts. Trust in the pediatrician’s recommendation, easy access, and insurance coverage were key factors in seeking the service. Reassurance provided by the MD/IBCLC increased mothers’ confidence to breastfeed. The COVID-19 pandemic heightened feelings of isolation and anxiety due to lack of hands-on support from friends and family during the birth hospitalization and when at home.
Challenge and opportunity: Making sense of the ‘first lockdown’ experience of families with young children and health and social care practitioners in Southend-on-Sea (the United Kingdom)
Authors: Ioakimidis Vasilios , O’Connell Lauren , Baxter Vanessa , Chard Kathryn , Speed Ewen , White Gregory
Published: April 2022

COVID-19 has had a significant and measurable impact on individuals and families in economically deprived areas both in the United Kingdom and internationally. This article examines issues of community resilience and service adaptability and focuses on the period during the first lockdown in the United Kingdom (May to July 2020). Data were collected from members of the local community in Southend, with specific reference to the ‘A Better Start Southend’ programme of support. The evidence presented in this article uncovers the impact of the ‘first lockdown’ on families with young children, and local children’s and community services.
How You Talk About It Matters: Cultural Variation in Communication Directness in Romantic Relationships
Authors: Ge Fiona , Park Jiyoung , Pietromonaco Paula R.
Published: April 2022

Communication plays an integral role in shaping romantic relationship quality. Yet, little is known about whether people from different cultural backgrounds communicate differently in their romantic relationships. Here, we addressed this issue by examining (a) whether the extent to which individuals communicate directly or indirectly in their romantic relationships varies by culture, (b) what mechanism underlies these cultural differences, and (c) how the fit between culture and communication style contributes to expected relationship satisfaction. Three key findings emerged across three studies (total N = 1,193). First, Chinese preferred indirect (vs. direct) communication more than European Americans, and this effect was more strongly pronounced in positively (vs. negatively) valenced situations (Studies 1–3). Second, interdependent (vs. independent) self-construal mediated the cultural difference in indirect communication both in positive and negative situations (Study 3). Finally, both cultural groups anticipated greater relationship satisfaction when they imagined their partner using the culturally preferred mode of communication—that is, indirect communication for Chinese and direct communication for European Americans (Study 3). These findings advance theory on culture and romantic relationship processes by demonstrating cultural differences in preferred communication styles across different situational contexts, identifying self-construal differences underlying these preferred communication styles, and highlighting the importance of congruence between culture and communication style for the quality of relationships.
Second-Line Parades: A Trauma-Informed Response to Grief
Authors: Hunter Lauren D.
Published: April 2022

New Orleans is no stranger to trauma. The Crescent City has a vast history of environmental calamities and oppression. Yet, New Orleans is renowned for its “joie de vivre”—or “love of life.” Specifically, this community is known for its unique practice of second-line parades. Researchers have noted the healing power of second-line processions, but none have analyzed the practice and psychology of this ritual through a trauma-informed lens. The aim of this conceptual paper is to begin the conversation, rather than deliver hard fast conclusions, on the potential therapeutic function of second-line parades in response to grief. Relevant literature is presented to illustrate second-line parades, trauma theory, and to provide evidence that the therapeutic effects of second-lining may, in part, be explained by trauma theory. This paper concludes with remarks on conceptualizing the second-line funeral as a sophisticated trauma-informed approach to grief and a note for future research.
The Use of Social Justice Concepts in Rehabilitation Counselor Education: Results of an Exploratory Study
Authors: Levine Allison , Harley Debra A. , Fleming Allison
Published: April 2022

Divisive social rhetoric and prevalent racism make the need for infusing social justice throughout counselor education even more urgent than the decades-long calls for it. There is a dearth of empirical inquiry into the ways social justice concepts are enacted across rehabilitation counseling curricula. The current study used an exploratory survey to collect information about the techniques used by U.S. rehabilitation counselor educators ( N = 71) to infuse social justice across all of their courses, including their pedagogical choices, rates of frequency for updating coursework, and professional development choices. Findings reveal that educators have favorable attitudes about social justice, are more likely to use academic journals and related disciplines in course development, and are more likely to use self-reflection and intuition-based opportunities for social justice professional development. Implications of the findings also include relevancy for supervisors and practitioners, who have the responsibility to and lead social justice education once trainees have entered the field as professionals.
A dynamic modeling approach to the moving filament during high-speed winding by absolute nodal coordinate formulation
Authors: Li Shujia , Ma Xunxun , Hou Xi , Wang Shengze , Wang Yongxing
Published: April 2022

During the winding process, the filament moves at a high speed with multiple configurations and large deformations, and is acted upon by winding tension, contact force, transverse force, air resistance, and so on. Accurately predicting the trajectory and tension fluctuation of the filament under the high-speed running condition is the basis for regulating winding parameters and ensuring high-quality winding. This paper proposed a novel dynamic approach for modeling the polyester filament winding system. The filament element was established by absolute nodal coordinate formulation. The nonlinear spring and viscous damper elements were used to establish the contact model between the filament and the mechanical parts, and the mechanical model of the influence of the airflow on the filament was established. Through considering the moving filament and all the force factors, the dynamic model of the multi-body coupling system of the filament winding and the corresponding nonlinear dynamic equation were established, and the dynamic equations were solved using MATLAB. An example of the high-speed winding system was simulated and further analyzed, and the simulated trajectory of the moving filament was highly consistent with the experimental image record.
Merger Reversal in St. Louis: Implementation and Implications
Authors: Duncan Daniel
Published: April 2022

While examples have been clearly attested in the literature, the reversal of a merger is an uncommon occurrence that apparently contradicts principles underlying sound change. Understanding the implications of merger reversal therefore requires understanding of their implementation: whether there was a full merger in the first place, what the phonetic path taken to separate the merger was, and whether there was a social motivation behind the reversal. I take this approach in a case study of the traditional start-north merger of St. Louis English, which has reversed in recent decades. I show that the merger was most likely a near merger, that the reversal was achieved by raising north and fronting start, and that the reversal, at least the raising of north, was socially motivated. I argue that the data highlights the role of perceptual salience in reversing mergers and illustrates that merger reversal can at times be chain shift-like in appearance, if not execution.
The Spectrum-Beamformer for Conventional B-Mode Ultrasound Imaging System: Principle, Validation, and Robustness
Authors: Jiang Chen , Liu Chengcheng , Zhan Yiqiang , Ta Dean
Published: April 2022

Fast and efficient imaging techniques are important for real-time ultrasound imaging. The delay and sum (DAS) beamformer is the most widely-used strategy in focused ultrasound imaging (FUI) modality. However, calculating the time delays and coherently summing the amplitude response in DAS is computationally expensive and generally require a high-performance processor to realize real-time processing. In this study, an efficient spectrum beamformer, namely full-matrix capture (FMC)-stolt, is proposed in FUI system with a linear phased array. The imaging performance of FMC-stolt was validated with the point-scatter simulation and in vitro point and cyst phantoms, and then compared with that of five beamformers, that is, Multiline acquisition (MLA), retrospective transmit beamforming (RTB) in the FUI modality, as well as DAS, Garcia’s frequency-wavenumber (f-k), Lu’s f-k in the coherent plane wave compounding imaging (CPWCI) modality, under specific conditions. We show that the imaging performance of FMC-stolt is better than MLA-DAS in non-transmit-focal regions, and comparable with RTB-DAS at all imaging depths. FMC-stolt also shows better discontinuity alleviation than MLA and RTB. In addition, FMC-stolt has similar imaging characteristics (e.g., off-axis resolution, computational cost) as the f-k beamformers. The computational complexity and actual computational time indicate that FMC-stolt is comparable to Garcia’s f-k, Lu’s f-k, and faster than RTB and CPWCI-DAS if the transmitting numbers are close for FUI and CPWCI. The study demonstrates that the proposed FMC-stolt could achieve good reconstruction speed while preserving high-quality images and thus provide a choice for software beamforming for conventional B-mode ultrasound imaging, especially for hand-held devices with limited performance processors.
A Mixed-Methods Study of Marketing Students’ Game-Playing Motivations and Gamification Elements
Authors: Jaskari Minna-Maarit , Syrjälä Henna
Published: April 2022

In this article, we examine the linkage between students’ game-playing motivations and a wide variety of gamification elements within higher marketing education. Using an interpretive and convergent mixed-methods design, we discover four clusters of students that vary in terms of their game-motivational bases and views on gamification elements. Social completionists want to study together with others and enjoy the social aspects of gamification. Highly motivated completionists could be described as ambitious students who enjoy social learning but are also internally motivated and willing to accept most gamification elements. Independent completionists want to immerse themselves in learning but prefer the individual and noncompetitive elements of gamification. Pure completionists are the “let’s get it done” group, who want to focus on completing their studies and are likely to be critical toward any gamification. We propose that higher education should take into account the differences in students’ game-playing motivations and fine-tune their gamification efforts to engage and motivate different kinds of students. Finally, we provide suggestions to marketing educators on how to consider the various motivational bases of the participants in gamified experiences.
Signaling Nothing: Motivating the Masses with Status Signals That Encourage Anti-Consumption
Authors: Armstrong Soule Catherine A. , Sekhon Tejvir Singh
Published: April 2022

Anti-consumption is arguably the most impactful environmentally friendly behavior but can be very challenging for consumers and antithetical to marketing. However, it may be possible for brands to support consumers in difficult anti-consumption actions. This paper demonstrates that a conspicuous signal communicating environmental motives can encourage anti-consumption, particularly for consumers least likely to do so without it. Real social media behavioral data and two experiments show that willingness to engage in anti-consumption practices can be enhanced with use of conspicuous anti-consumption signals, specifically for consumers low-to-moderate on environmental concern and moderate-to-high on need for status, while increasing willingness-to-pay. This type of consumer is unlikely to be intrinsically motivated to reduce consumption and much more common than extremely green consumers, potentially resulting in very large positive impact. If more brands support reduced consumption, the dominant social paradigm around marketing and ever-increasing consumption could begin to shift for the good of the planet.