Miracle-dz/UniFAR-FTUs huggingface dataset:
A Two-layer Sketch for Entropy Estimation in Data Plane

Entropy-based approaches have been shown to aid a wide variety of network measurement applications such as load balancing, anomaly detection, traffic classification. Existing entropy estimation methods require frequent interaction between forwarding and control planes which increases the burden on the network and causes unnecessary delay. In this paper, we present Filter-Sketch, a two-layer sketch that supports frequency estimation with small and static memory allocation. Based on Filter-Sketch, we propose a new generation of mechanisms to calculate entropy at a line rate which completely executes in programmable data plane. The trace-driven evaluation shows that Filter-Sketch achieves higher accuracy than the existing data plane algorithm in entropy estimation where the relative error decreases 0.65 in average.
An Effective Predictive Torque Control Technique for Open-end Winding Permanent Magnet Synchronous Motor Drives with Reduced Ripples for EVs

Permanent Magnet Synchronous motors (PMSM) are commonly used in the applications of Electric Vehicles (EVs). Predictive torque control (PTC) is the method which is popularly used for the control of PMSM. Generally, a PMSM is fed with a two-level inverter for the above operation. But, PMSM fed with multi-level inverter will give better performance. To achieve this configuration, Open-End Winding PMSM (OEW-PMSM) is used which is fed by a dual inverter. OEW-PMSM with three level inversion will comparatively produce less torque ripples and flux ripples. In PTC, cost function is the absolute function of torque and flux errors. Since torque and flux are two different quantities, a weighting factor place an important role in the PTC. The proposed PTC reduces the torque ripples by introducing a new method of utilizing cost function to eliminate weighting factors. Simulation studies are performed with dual-inverter fed OEW-PMSM with conventional and proposed PTC with three level inversion. The effectiveness of the proposed method is verified by comparing conventional PTC with proposed PTC.
Modeling RTK-GNSS Trajectory Data using Sparse Gaussian Process Models

The Gaussian process regression (GPR) has been applied to model trajectory points from Global Navigation Satellite System (GNSS). Trajectory modeling using GP in previous works did not demonstrate its performance when training the GP using various kernel functions. In addition, residuals were not analyzed to ascertain the goodness of fit. In this paper, we aim to develop sparse GPR model with the best performing covariance function to model trajectory data collected using the RTK-GNSS (Real-Time Kinematics-Global Navigation Satellite Systems) in a sub-urban area. The sparse GPR was trained on three data sets collected using five types of kernel or covariance functions. The model was validated using 10-fold cross validation. The Bayesian information (BIC) and mean square error (MAE) from the cross-validation were used to identify the best performing kernel function. Subsequently sparse GPR model with the best kernel was implemented to predict the trajectory. Model residuals were analyzed using the autocorrelation, partial correlation, histograms and QuantileQuantile (Q-Q) plot. The sparse GPR could improve positioning errors ranging from 9.93 % to 34.91 %. However, the analyses on the residuals reveal poor model fit and the presence of correlation in the data.
Generalized Topology with Reduced Components for Multilevel Inverter Using Selective Harmonic Elimination Technique

Recently, Multilevel Inverters (MLIs) are developed for integrating the Renewable Energy Sources (RES) to the utility grid. Due to the dominance of MLIs over conventional inverters with respect to high power capability, less harmonics, greater levels in the output voltage and efficiency, research has been focused on development of new MLI topology. This paper presents the new generalized topology for MLI structure named as Reduced Switch Single Source (RSSS) MLI. Proposed RSSS MLI requires less number of switches and voltage source compared with some recently developed MLI topologies. For the elimination of harmonic contents from output voltage and current, Selective Harmonic Elimination (SHE) with Newton Raphson (NR) technique is used. This elimination of harmonics is done on seven and eleven level RSSS MLI and results have been discussed. The developed RSSS MLI is verified and validated through several MATLAB simulation.
An Investigation into Barriers in Online Learning during the Pandemic: View from Students of a Vocational College

COVID-19 has affected the learning process and learning experience of students around the world. This study was conducted with the aim to identify the barriers to the effectiveness of online learning in university education during the COVID-19 pandemic. The context of the study is a vocational college in Hanoi. Data were collected from 117 students who are taking online courses in the Spring 2022 semester. The online questionnaire link was sent to the students via their private class group by their lecturers. This study investigated certain barriers that students are facing, and at the same time proposed recommendations to limit the challenges found. The results of this study are valuable for the studied institution to improve the quality of training, and also for other educational institutions if they share the same context.
Real-time monitoring system for rotor temperature of a large turbogenerator based on SmartMesh IP wireless network communication technology

In this study, a real-time rotor temperature monitoring system for large turbogenerators using SmartMesh IP wireless network communication technology was designed and tested. The system is capable of providing comprehensive, accurate, continuous, and reliable real-time temperature monitoring for turbogenerators. Additionally, it has demonstrated satisfactory results in a real-time monitoring test of the rotor temperature of various famous large-scale turbogenerators and giant nuclear power half-speed turbogenerators designed and manufactured in China. The development and application of this wireless temperature measurement system would aid in improving the intelligent operation quality, safety, and stability of China's large turbine generators and even the entire power system.
Design of Automatic Charging System for Electric Vehicles using Rigid-Flexible Manipulator

Last few years have seen a remarkable growth in the number of Electric Vehicle (EV) users. Autonomous driving and parking of EV s are the future of vehicle industry and this calls for customer friendly and innovative charging infrastructure de-velopment. A fully autonomous charging system highly aid them. This paper proposes the design of an automatic charging system for EVs. In this work YOLO (You Only Look Once) algorithm, a deep neural network based object detection algorithm is used to automatically recognize and locate the charging port of an EV. Thus accurate positioning of charging port in a complex environment can be achieved. A rigid-flexible manipulator on a movable platform is then designed for conductive charging of an EV automatically. Irrespective of vehicle models and charging ports the proposed design can be used for the automatic charging of EVs. The designed robotic manipulator successfully follows the path traced by the charging port detection system and perform plug-in process. The simulation results show the efficacy of the proposed design.
An Implementation of Java Programming Learning Assistant System Platform Using Node.js

As a reliable and portable object-oriented program-ming language, Java has been used in a variety of practi-cal systems, including enterprise servers, smart phones, and embedded systems. To assist Java programming learning of novice students, we have developed the web-based Programming Learning Assistant System (JPLAS) using Tomcat for the platform. In this paper, we implement the JPLAS platform using Node.js and Docker to improve the usability and portability. Node.js is a popular web application server, since server-side programs can be made using JavaScript. Docker helps the easy and solid deployment of an application at any platform. For evaluations, we compared the number of program files in this implementation with that of the previous one, and asked 11 students in Japan and Indonesia to install and use it to confirm the validity.
Virtual Reality on Mobile Devices

Mobile 3D applications, especially games, are gaining popularity and due to the constant increase in graphics capabilities of mobile devices, the creation of more elaborate virtual worlds becomes possible. However, compared to traditional gaming platforms, mobile devices have a small form factor, which imposes new challenges on game designers, but also opens new opportunities. Shoebox VR offers a novel way of visualizing virtual environments and has already been applied in games. Whereas current games mainly use still scenes, we investigated the use of Shoebox VR in motion-based games. Our previous study demonstrated that Shoebox VR improved subjective user experience, in terms of subjective sense of depth perception, entertainment value and immersion. To further explore how user experience and gameplay are affected by Shoebox VR, this study investigated whether these variables are affected by factors like screen size and user interaction. By developing games, we were able to show that although screen size did not affect subjective experience, gameplay performance increased with a smartphone-sized device at low speeds using Shoebox VR. In addition, we demonstrated that touch screen interaction affects games using Shoebox VR, as gameplay performance was higher for Shoebox VR compared to standard visualization methods. In contrast, tilting interaction did not appear to affect Shoebox VR, indicating that the tilting controls can be used in combination with Shoebox VR without decreasing user experience or gameplay performance. Finally, our results suggested that Shoebox VR is especially functional and well-used when it is implemented as an essential part of the gameplay. Our study provided more insight in the usability of Shoebox VR in motion-based games, which contributes to the improvement of visualization methods of 3D environments on mobile devices.
Is a “Soft” monetary authority appropriate?

Palabras claves: Objetivos Inflación, Autoridad Monetaria, Modelos de Equilibro General Estocástico Dinámico, Regla de Taylor, Credibilidad. Abstract Taking the "objective inflation strategy" as a frame of reference, it is usual to discuss what is most convenient for a society in terms of the degree of "hardness" or "aggressiveness" of a monetary authority to defend its inflation target, and the credibility it has among the economic agents. In this document we use a Neo-Keynesian Stochastic Dynamic General Equilibrium (DSGE) model both with rational and adaptive expectations to analyze this question and we also quantify the effects of these two types of authorities on social welfare using an utility function. Our results suggest that the problem that can be derived from a "soft" authority is to risk the loss of credibility in its (supposed) effort to reach a certain inflation target. In addition, we present and use a solution of our model simple enough to allow other simulations related to this class of models to be implemented in a spreadsheet.
COMPARATIVE STUDY OF OPTIMIZED LOAD BALANCING MODELS USING FOG-CLOUD NETWORKS

-Fog computing helps in storing data near to end users and it is taken as the modified level of cloud computing. There are many cloud platforms where we can store the data but because of some limitations, lots of data could not be processed on time. Apart from that, there are various challenges in terms of load balancing over cloud which we need to handle very carefully sothat there is no congestion, less energy consumption and minimum delay in processing. With the help of optimized load balancing models and algorithms, we can increase the productivity of fog-cloud networks. The main objective of this study is to compare the results of load balancing algorithms which creates warehouse of data at very fast access rate to the mobile users. At present scenario, this can be easily done using fog computing in very accessible way. It is an interface between end users and cloud layer and provides higher data access and retrieval services to the end users. This paper includes architecture of cloud computing and its attributes which is necessary to concentrate on the interplay and coordination in between fog and cloud layer. This paper also focuses on some important parameters which are considered in minimizing load over fog-cloud and try to improve the data access rate.
Institutional Knowledge at Singapore Management University Big Data and Management: From the Editors

Editor’s Note: This editorial launches a series written by editors and co-authored with a senior executive, thought leader, or scholar from a different field, to explore new content areas and grand challenges with the goal of expanding the scope, interestingness and relevance of the work presented in the Journal. The principle is to use the editorial notes as “stage setters” for further work and opening up fresh new areas of inquiry for management research. GG to While management research and time management techniques of current practices using big Data to study entire organizations and workgroups in near time to predict individual and group behaviors, team social dynamics, coordination challenges, and performance outcomes. Scholars could examine questions around the differences between stated versus revealed preferences by tracking data on purchasing, mobile applications, and social media engagement and consumption to state a few examples. Social network studies could also use Big Data to examine the dynamics of formal and informal networks as they form and evolve as well as their impact on individual, network and organizational behaviors. Such granular, high volume data can tell us more about workplace practices and behaviors than our current data collection methods allow and have the potential to transform management theory and practice.
Arka plan Modellemesi ve Optik Akış ile Hareket Tespiti

Özet— Hareket tespiti çeşitli bilgisayarlı görme problemlerinde ön-işlem aşamasında kullanılmaktadır ve üzerinde çalışılan önemli konulardan birisidir. Hareket tanıma için önerilen yöntemler çoğunlukla arka plan modellemesi ve çıkarımına dayanmaktadır. Bu çalışmada, arka plan modelleme ve optik akış vektörlerinin kullanıldığı bir yöntem önerilmiştir. Optik akış tahmin edilmesinde Farneback yöntemi kullanılmıştır. Önerilen yöntemde optik akış, arka plan çıkarımı aşamasında her bir piksel için uygulanacak eşik değeri belirlemek için kullanılmıştır. Deneysel sonuçlar arka plan çıkarımı yaparken optik akış bilgisini kullanmanın sabit eşik değer uygulamaya nazaran performansı arttırdığını göstermiştir. Önerilen yöntem CDNET-2014 veri kümesinden farklı altküme görüntüleri üzerinde
The Operator or the Automation: In Whom Should We Place Ultimate Trust?

This paper investigates the conflict between two competing safety philosophies. According to one philosophy, dangerous system states should be explicitly prevented through system design. According to the alternate philosophy, human operators should be the final arbiters of safety. These principles come into conflict in situations where any attempt to prevent the system entering an unsafe state may limit the freedom of the operator to recover from a dangerous situation not envisaged by the system designers. We argue that conventional hazard analysis and mitigation techniques have limited power to resolve this dilemma. We present a framework for making decisions about where final authority in a system should lie, and explore the implications of this framework. (6 pages)
Modal analysis of radiation and energy storage mechanisms on conducting scatterers

The manifestation of radiation and stored energy by electric currents on conducting bodies is studied via modal expansions. The novel modal expansions are based on the quadratic operators which map a current distribution to each quantity. Adaptations of the continuous forms of these operators into the Method of Moments is reviewed. The discrete modal expansions are studied on several example objects, leading to conclusions regarding the sparsity of the radiation mode spectrum. Analytic forms for the sparse radiation modes on electrically small objects are derived. Negative energy current distributions are studied using the energy storage modal expansions. The role of ground plane radiation on the determination of an embedded antenna’s Q factor is studied using radiation modes, giving a new perspective on the convergence behavior of this parameter with respect to ground plane size. Leveraging the invariance of radiation modes on small objects, an example procedure for the design of an embedded antenna array using radiation modes is presented.
Encapsulación de Probióticos de Secado por Spray Spray-Drying Encapsulation of Probiotics

: The probiotic microorganisms have gained importance in recent years because their consumption has benefits on health mainly of the digestive system. For this reason, the industry is in a constant search of processes for these micro-organisms don´t lose their viability and they do their function. Because of that, the microencapsulation has been used as method of protection in the internal and external climate conditions. In this same vein, probiotics need prebiotic substances, such as malanga and rice starches, to stay viable and perform beneficial functions inside the host. The objective of this work was assess two prebiotics (malanga and rice starches) as wall material in the viabiity of a microorganism Lactobacillus casei subs. Paracasei encapsulated through spray dryed. The isolated malanga and rice starches, got 82.60 and 86.68% of starch overall respectively, in the amylose content rice presented 17.34% and malanga 9.44%, the exponential phase of microoganisms was presented at 14 h, aggregates with a popcorn shape were accomplished and finally the encapsulation effiency satyed in the order of 1008 .
A stretchable and screen-printable conductive ink for stretchable electronics

Stretchable electronics can offer an added degree of design freedom and generate products with unprecedented capabilities. Stretchable conductive ink serving as interconnect, is a key enabler for stretchable electronics. This paper focuses on the development of a stretchable and screen printable conductive ink which could be stretched more than 500 cycles at 20% strain while maintaining electrical and mechanical integrity. The screen printable and stretchable conductive ink developed in this paper marks an important milestone for this nascent technology.
The impact of processing on wheat grain components associated with health benefits

Wheat based foods, mainly in the form of bread and pasta, are staples in many countries around the world and as such contribute substantially to nutrient intake of human beings. The mature wheat grain is composed for over 70-75% of its dry weight of starch and for around 10-14 % of protein, which has led to the widely spread perception of wheat foods as providers mainly of energy and protein to the human diet. Nonetheless, whole grains are also an important source of dietary fibers, vitamins and minerals and contain notable levels of bioactive compounds of health benefit as for examples lignans, phenolic acids, alkylresorcinols, phytosterols, folates and tocols. Processing is a pre-requisite for using cereal grains as food and obtaining a safe to consume and appealing final product for the consumer. It can help reducing potential hazardous molecules as pesticides, mycotoxins and heavy metals and allows to obtain products with varied and unique properties. Indeed, most of the importance of wheat grain in the human diet is due to its versatility to be processed into various end products like flour, semolina, and other bakery products. Processing of wheat grain involves different regulated steps each impacting either or both on the composition and physical-chemical properties of its different components, which in turn define the technological quality and the nutritional and health promoting properties of the end product. While the unique textural properties of wheat foods are largely determined by starch and gluten proteins present in the starchy endosperm, and therefore associated with white flour or semolina, health effects of wheat-based products are mainly associated with their dietary fibers and bioactive compounds. These compounds are enriched in the grain peripheral layers, Some examples of the effect of grain processing procedures on bioavailability of important grain components in the wheat products will be presented in this Suggestions of how to improve these processes light of their implication for human health will also be discussed.
Hierarchical approach for identifying social groups from mobile phone call detail records

With the increasing use of mobile devices, now it is possible to collect different data about the day-to-day activities of personal life of the user. Call Detail Record (CDR) is the available mobile phone usage dataset at large-scale, as they are already constantly collected by the mobile operator mostly for billing purpose. By examining this data it is possible to analyze the activities of the people in urban areas and discover the human behavioral patterns of their daily life. These datasets can be used for many applications that vary from urban and transportation planning to predictive analytics of human behavior. In our research work, we have proposed a hierarchical analytical model for finding facts from CDR dataset for progressive exploration of facts on the day-to-day social activities of urban users in multiple layers. In our model, only the raw CDR data are used as the input in the initial layer and the outputs from each consecutive layer is used as new input combined with the original CDR data in the next layers to learn more detailed and deeper facts on social interaction, work and travel activity, friends, family and working relationship and predicting social groups based on these facts. Our proposed model starts with an aggregated overview of the activities of the users in their social life and allows us to gradually focus on smaller groups, using multiple layers of abstraction by applying clustering techniques and prediction classifiers. The uniqueness of our model is that the output in each layer is dependent on the results of the previous layers, thus, allow us to explore fact on social relationships and groups which can not be predicted in a single layered approach. This model utilized the CDR dataset of one month collected from the Dhaka city, which is one of the most densely populated cities of the world. So, our main focus of this research work is to explore the applications of CDR data containing spatio-temporal traces of the mobile phone users for progressive predicting of facts and features of social groups and relationships in a busy city.