Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated Multiple Kernel Learning for Device-Free Localization in Cluttered Environments Using Spatiotemporal Information

Ubiquitous WiFi signals not only provide fundamental communications for a large number of Internet of Things devices, but also enable to estimate target’s location in a contactless manner. However, most of the existing device-free localization (DFL) methods only utilize the time dynamics of the received WiFi signals, leading to inaccurate DFL in the cluttered indoor environments. Because different layouts of environments and deployments of WiFi devices cause the different mathematical distributions of the data collected from the cluttered indoor environments. In this article, a multiple kernel representation-based extreme learning machine (ELM) is proposed, named integrated multiple kernel ELM (IMK-ELM), for strengthening the localization performance in the cluttered indoor environments utilizing spatiotemporal information. In the proposed IMK-ELM-based DFL, the whole data set is first divided into several subsets depending on their mathematical distributions through the $K$ -means clustering algorithm, and then a corresponding number of local DFL models are built for all the subsets to capture both the time dynamics and spatial properties of the data. Finally, a global DFL model is achieved by seamlessly integrating all the local DFL models due to the consistency mechanism. In addition, the Fresnel zone sensing theory is utilized for helping understand and explain the essence of indoor DFL. Comprehensive experiments indicate that the proposed IMK-ELM-based DFL outperforms state-of-the-art methods in the cluttered indoor environments.
Using Survey Information for Improving the Density Nowcasting of U.S. GDP

Abstract We provide a methodology that efficiently combines the statistical models of nowcasting with the survey information for improving the (density) nowcasting of U.S. real GDP. Specifically, we use the conventional dynamic factor model together with stochastic volatility components as the baseline statistical model. We augment the model with information from the survey expectations by aligning the first and second moments of the predictive distribution implied by this baseline model with those extracted from the survey information at various horizons. Results indicate that survey information bears valuable information over the baseline model for nowcasting GDP. While the mean survey predictions deliver valuable information during extreme events such as the Covid-19 pandemic, the variation in the survey participants’ predictions, often used as a measure of “ambiguity,” conveys crucial information beyond the mean of those predictions for capturing the tail behavior of the GDP distribution.
Use of Facebook to Serve Information Needs of Persons with Diabetes in the Philippines amid the COVID-19 Pandemic

Objectives The use of Facebook (FB) to share and gather information on diabetes is commonplace but no data is available on its use among Filipinos during the COVID-19 pandemic. We sought to determine the engagement from instructional slide decks on diabetes and its management shown on two Philippine-based FB pages under the Enhanced Community Quarantine (ECQ). Methodology We used Insights data from the slide decks and slide shows shown on the Philippine Society of Endocrinology, Diabetes and Metabolism’s (PSEDM) public FB page and the Endocrine Witch’s FB page. The slide set contained a mix of mostly images and text on COVID-19 and Diabetes, dietary advice, medications and self-care in the setting of the ECQ where access to insulin, ambulatory clinics and healthy food is limited. Data was summarized in terms of post clicks, reactions, shares and comments. Total engagement rate was computed. Results We noted a high engagement rate (4-15%) in both public FB pages with higher engagement rates in slides shown in the Filipino language for most topics. The slides that gathered more shares and reactions were primarily those containing general information on COVID-19 and diabetes, nutrition including the safety of canned goods, as well as sick day rules. Conclusion In the setting of the ECQ, the use of image and text-based slide-decks on the PSEDM and Endocrine Witch FB pages to communicate health information yielded high engagement.
A COMPACT FREQUENCY RECONFIGURABLE PRINTED ANTENNA FOR WLAN, WIMAX MULTIPLE APPLICATIONS

In this research work a compact patch antenna which is reconfigurable for frequency is presented. Frequency reconfigurability is achieved by the use of two PIN diodes. Antenna operates over four frequencies, i.e., for WiMax (4.94 GHz), WLAN (5.35), and C-Band (6.25 and 6.83 GHz) applications. The overall dimension of antenna is 25× 25 mm2, and an FR-4 substrate having dielectric constant of 4.4 and thickness 1.6 mm is used to fabricate the prototype of the proposed antenna. Different resonant frequencies are obtained by cutting a ∏ -slot and a U-slot in radiating patch and by modifying ground slot with a modified slotted structure. One diode is used in ground, and another PIN diode is used on the patch at an appropriate position. Maximum gain of 3.91 dBi and stable radiation characteristics and VSWR < 2 are obtained at the operating bands in simulation and measurement. The antenna elicits its novelty through compactness, portability for communication devices through combination of only two PIN diode switching in cellphones, tablets PCs, and other satellite communication devices operating in C-band as per FCC standard. A prototype of antenna is fabricated, and the measured and simulated parameters are in good agreement.
A Reduced Single-Phase Switched-Diode Cascaded Multilevel Inverter

The cascaded multilevel inverters (MLIs) are suitable topologies when a high number of voltage levels are needed. Nonetheless, cascaded topologies possess the main drawback of a high number of power switches and gate drivers that make sophisticated control, reducing efficiency, and increasing cost. This article proposes a new fundamental switched-diode topology that is capable of generating five positive-voltage levels with only three power switches, three power diodes, and three dc voltage sources. Based on a combination of the $n$ number of new fundamental topology, two cascaded topologies are proposed, which increases the number of voltage levels and decreases the number of power switches and voltage stress. The proposed cascaded topologies can operate in asymmetric dc sources, so different dc voltage source magnitudes are submitted to minimize the number of components. The main advantages of the proposed cascaded topologies are reducing the number of power switches, and gate drivers with reasonable dc voltage sources count in comparison with other state-of-the-art cascaded topologies. Furthermore, the proposed topologies reduce the cost in comparison with other recent MLI topologies. The power loss analysis and the recommended application for the proposed topologies are discussed. The simulation and experimental works are presented to verify the operation correctness of the proposed topologies.
Entrepreneurial Decisions in Conditions of Uncertainty as a Result of the Health and Economic Crisis Caused by COVID 19

The current period is suffocated by a crisis both in health and economics. At the level of the global economy, there is a continuous fight against this virus, but at the same time there are battles on various fronts in order to save the world economy, in strategic geopolitical conditions, in the hidden fight for supremacy. Now the real entrepreneurs with vision and creativity, able to adapt to changes and especially to digitize the business, will be differentiated from those who will closed the doors in their business activities. This paper presents the importance of the resources held and how to manage them in conditions of business uncertainty. The efficient use of resources, creativity and investments in a field that will be part of the future society, will turn this moment of crisis into a great achievement for those who see the opportunity where others see only threats.
DNA Barcoding in Selected Species and Subspecies of Rye (Secale) Using Three Chloroplast Loci (matK, rbcL, trnH-psbA)

DNA barcoding is a relatively new method of identifying plant species using short sequences of chloroplast DNA. Although there is a large number of studies using barcoding on various plant species, there are no such studies in the genus Secale. In this study the plant material consisted of 10 cultivated and non-cultivated species and subspecies of rye genus. Three chloroplast DNA regions (rbcL, matK, trnH-psbA) were tested for their suitability as DNA barcoding regions. Universal primers were used, and sequenced products were analyzed using Neighbor Joining and the Maximum Likelihood in the MEGA 7.1 program. We did not observe high variability in nucleotide sequences within the matK and rbcL regions. Only 2.2% of the sequences showed polymorphism in the rbcL region, while 6.5% in the matK region. The most variable trnH-psbA (15.6%) intergenic region was the most useful for rye barcoding. Individual application of the studied regions did not provide the expected results. None of the regions used in the study allowed the division of rye species and subspecies according to the adopted classification of the genus Secale. The results confirm that the use of matK and rbcL is insufficient for DNA barcoding in rye species, and better discrimination within the genus Secale can be obtained only in combination with the non-coding trnH-psbA sequence. Our results also indicate the necessity of using a different region. All of the new sequences have been deposited in Genbank.
A Digital Control Strategy With Simple Transfer Matrix for Three-Phase Buck Rectifier Under Unbalanced AC Input Conditions

In this letter, a digital control strategy with a simple transfer matrix between three-phase ac input voltages and dc-link voltage is proposed for a three-phase buck rectifier (3ph-BR) under unbalanced ac input conditions. The proposed digital control strategy can eliminate both the odd harmonics of the ac input currents and the even harmonics of the output voltage ripple under unbalanced ac input conditions. Compared with the state-of-the-art control strategies, the proposed control strategy does not require the extraction of the positive sequence voltage and the negative sequence voltage, thus a three-phase lock loop and complex calculation are not required. The proposed control strategy is essentially an input voltage feedforward control, which is independent of the loop bandwidth of the feedback system. Therefore, the processing speed of the digital processor is no longer the critical factor for the 3ph-BR under the unbalanced ac input conditions. The proposed control strategy makes it possible to utilize low-cost and small-sized digital processors. An experimental prototype of a 1.5-kW 3ph-BR with the proposed control strategy is built to verify the analysis results.
A football player rating system

Association football (soccer) is the most popular sport in the world, resulting in a large economic interest from investors, team managers, and betting agencies. For this reason, a vast number of rating systems exists to assess the strength of football teams or individual players. Nevertheless, most of the existing approaches incorporate deficiencies, e. g. , that they depend on subjective ratings from experts. The objective of this work was the development of a new rating system for determining the playing strength of football players. The Elo algorithm, which has established itself as an objective and adaptive rating system in numerous individual sports, has been expanded in accordance with the requirements of team sports. Matches from 16 different European domestic leagues, the UEFA Champions and Europa Leagues have been recorded, with more than 17 000 matches played in recent years, and 12 400 different players. The developed rating system produced promising results, when evaluating the matches based on its predictions. A high relevance of the created system results from the fact that only the associated match report is needed and thus—in relation to existing valuation models—significantly more football players can be assessed.
Isolated endobronchial juvenile xanthogranuloma: a case report

Juvenile xanthogranuloma (JXG) is a rare non-Langerhans cell tumour usually diagnosed during infancy. The lesion is typically located in the skin; however, extracutaneous lesions have been described. The symptoms vary depending on the location and size of the lesion. Presented here is a case of 13-year-old girl with this type of tumour located within the bronchus. She reported chest discomfort, difficulty breathing, and cough. A month prior to admission she had suffered from a respiratory tract infection. Prolonged surgical treatment was required due to the tumour’s atypical location and recurrence of the tumour following initial resection. Isolated pulmonary JXG is an extremely rare finding, which requires accurate diagnosis and careful planning of therapeutic treatment. Severe pulmonary symptoms, inconclusive histopathological examination, malignancy risk, and large tumour size are indications for radical surgical resection of the tumour. Non-surgical treatment with chemotherapy is useful in cases of inoperable tumours.
Analysis of Markov Chain-based Methods for Synthesis of Driving Cycles of Different Dimensionality

Driving cycles reflect driver behavior and local traffic characteristics, and they are often described in terms of vehicle velocity time profile and widely used for different certification purposes. In order to obtain reliable fuel consumption estimates, realistic driving cycles including the road slope profile should be used, especially for electric vehicles whose energy consumption may significantly vary depending on road and traffic conditions. As a continuation of previous research related to statistical analysis of a rich set of city bus driving cycles, this paper focuses on multidimensional driving cycle synthesis using the Markov chain method. Five Markov chain models are derived with respect to different selections of states and correspondingly different dimensionalities of transition probability matrix, and they are systematically compared against certain statistical criteria. In order to reduce memory demand while improving computational efficiency, a sparse implementation of transition probability matrix based on dictionaries of keys is employed. Finally, the analyzed synthesis methods are used to generate a small set of synthetic driving cycles that represent the recorded driving cycles in statistically reliable sense.
Dual-Side Asymmetrical Voltage-Cancelation Control for Bidirectional Inductive Power Transfer Systems

Bidirectional inductive power transfer (BIPT) systems for electric vehicles allow power exchange between grid and vehicle. To achieve high transfer efficiency under a wide range of transmission power, this article proposes a dual-side asymmetrical voltage-cancelation (AVC) control technique. With the proposed dual-side AVC control, the adjustment of the fundamental component amplitude of the excitation voltage, the maintenance of a large phase angle between excitation voltages as well as zero-voltage switching (ZVS) of the power switches, and the optimization of the resonant tank power transfer efficiency can be achieved simultaneously. The basic characteristics and the conditions for maximum transfer efficiency of the resonant tank are derived. The control scheme for the overall system including the control of the primary-side and secondary-side full bridges is proposed, which considers both efficiency optimization and ZVS operation of all switches. The ZVS range of the proposed dual-side AVC control technique is presented. Experiments are performed with dual-phase-shift, triple-phase-shift, and the proposed dual-side AVC control technique, which show that the BIPT system with the proposed dual-side AVC control technique achieves a higher efficiency over the others in a wide range of transmission power.
Social Media and News: Content Bundling and News Quality

The growing influence of internet platforms acting as content aggregators is one of the most important challenges facing the media industry. We develop a simple model to understand the impact of third-party content bundling by a social platform that has a monopoly on showing user-generated content to consumers. In our model, consumers can access news either directly through a newspaper’s website or indirectly through a platform, which also offers social content. We show that content bundling, when unilaterally implemented by the platform, tends to harm publishers and to increase the dispersion of quality across outlets, with initially high-quality outlets investing more and low-quality ones investing less. With many heterogenous newspapers, the result is robust even if each newspaper can prevent the platform from using its content. When content bundling follows an agreement between the platform and publisher, its effects are reversed, as publishers’ profits go up while quality dispersion goes down. In a setup with heterogeneous consumers, we also show that the platform’s ability to personalize the mix of content it shows to users induces publishers to invest more in the quality of their content. This paper was accepted by Dmitri Kuksov, marketing.
The Meta Distributions of Secrecy Rate for the Downlink NOMA Systems

In this letter, the Meta distributions (MDs) of the secrecy rate in downlink non-orthogonal multiple access (NOMA) systems with randomly located eavesdroppers are investigated. Due to the complexity of calculation, the MDs for NOMA users are approximated by Beta approximation and the analytical expressions for the first two moments of conditional secrecy connection probability of NOMA users are derived, while perfect/imperfect successive interference cancellations on the near user are considered. Finally, the accuracy of the result is verified by Monte Carlo simulations. The results show that the MD can capture the statistics of the secrecy rate in a given secrecy connection probability.
A Compact Wideband Millimeter-Wave Substrate-Integrated Double-Line Slot Array Antenna

A novel slot array antenna based on substrate-integrated double-line (SIDL) technology is proposed in this article. By using the SIDL technology, the feed network of the array is simplified and the high-order mode is suppressed. As a consequence, the proposed antenna can obtain a compact size, a wide bandwidth, and a high radiation efficiency. To excite the proposed antenna, the microstrip-to-SIDL transition is designed by adopting coupling slots at the bottom plate of the SIDL. A $16 \times 8$ element slot array antenna is designed and fabricated for verification by using multilayer printed circuit board (PCB) technology. The measured −10 dB impedance bandwidth is from 23.35 to 27.55 GHz (16.5%). A 21.6 dBi gain is obtained at the designed frequency of 25.8 GHz in the measurements. The measured 1 dB gain bandwidth and simulated radiation efficiency are 12.5% and 75%, respectively. The measured results agree well with the simulated results. The proposed antenna can be used to develop compact and high-efficiency millimeter-wave systems.
Strengthening Inflation Targeting: Review and Renewal Processes in Canada and Other Advanced Jurisdictions

A growing number of advanced economies with monetary policy frameworks that involve inflation targeting have adopted formal processes of review and renewal. These allow policy-makers and other stakeholders to assess the current framework’s performance to date, explore the merits of potential alternative frameworks and reach decisions about how best to enhance design and implementation. In this paper, we argue that well-governed review and renewal processes can contribute importantly to the success of a monetary policy framework: (1) they help to adjust the framework in response to experience, theoretical developments and changes in the economy; and (2) they enhance the legitimacy and credibility of changes made to the framework. However, as these processes involve inputs from the government or legislature, they also create potential for tensions regarding central bank independence. We use an international comparison to show that these considerations have been balanced in different ways across countries and time, with a spectrum running from relatively technocratic processes to ones more closely linked to the political cycle. We also highlight several unique aspects of the modern review and renewal experience in Canada, where renewals of the Bank of Canada’s joint inflation-control agreement with the government have regularly been preceded by in-depth framework reviews, each involving a large amount of original research and significant levels of transparency.
Trace-SRL: A Framework for Analysis of Microlevel Processes of Self-Regulated Learning From Trace Data

The recent focus on learning analytics (LA) to analyze temporal dimensions of learning holds the promise of providing insights into latent constructs, such as learning strategy, self-regulated learning (SRL), and metacognition. These methods seek to provide an enriched view of learner behaviors beyond the scope of commonly used correlational or cross-sectional methods. In this article, we present a methodological sequence of techniques that comprises: 1) the strategic clustering of learner types; 2) the use of microlevel processing to transform raw trace data into SRL processes; and 3) the use of a novel process mining algorithm to explore the generated SRL processes. We call this the “Trace-SRL” framework. Through this framework, we explored the use of microlevel process analysis and process mining (PM) techniques to identify optimal and suboptimal traits of SRL. We analyzed trace data collected from online activities of a sample of nearly 300 computer engineering undergraduate students enrolled on a course that followed a flipped class-room pedagogy. We found that using a theory-driven approach to PM, a detailed account of SRL processes emerged, which could not be obtained from frequency measures alone. PM, as a means of learner pattern discovery, promises a more temporally nuanced analysis of SRL. Moreover, the results showed that more successful students regularly engage in a higher number of SRL behaviors than their less successful counterparts. This suggests that not all students are sufficiently able to regulate their learning, which is an important finding for both theory and LA, and future technologies that support SRL.