Miracle-dz/UniFAR-FTUs huggingface dataset:
Bidirectional Soft-Switching Series AC-Link Inverter

This paper proposes a novel bidirectional inverter, named series ac-link inverter. This three-phase inverter belongs to a new class of partial resonant ac-link converters in which the link is formed by a series ac inductor/capacitor (LC) pair having low reactive ratings. The input and output of this converter can be either dc, ac, single-phase, or multiphase. Therefore, they can appear as dc-dc, dc-ac, ac-dc, and ac-ac configurations. In all of these configurations, the ac capacitor is the main energy-storage element, and the inductor is merely added to facilitate the zero-current turnoff of the switches and their soft turn-on. Due to the zero-current turnoff of the switches in the proposed converter, the use of SCRs with natural commutation is possible as well. Since the current and voltage of the link are both alternating, no bulky dc-electrolytic capacitors are required in this converter. This paper mainly focuses on bidirectional dc to three-phase ac conversion. This single-stage inverter can step up or step down the voltage in a wide range. If galvanic isolation is required a single-phase high-frequency transformer can be added to the link. In the proposed inverter, the power can flow in both directions, and therefore, it is an excellent candidate for battery-utility interface and electric vehicle applications. In this paper, the principles of the operation of the proposed inverter, along with its design and analysis, are studied. Moreover, the performance of the proposed configuration is evaluated in this paper. Both simulation and experimental results are included.
Optimization and Application of OPTICS Algorithm on Text Clustering

Text clustering is of great importance in data mining, information fusion, artificial intelligence and some other fields. There are many methods in literatures that can be used to classify text. Most of them require some parameters, such as the number of categories, which should be assigned in advance or estimated in classifying process. However, it is difficult to determine these quantities in text clustering. OPTICS is one of clustering algorithms that does not depend on the preset number of categories. In this paper, we introduce an optimization method based on OPTICS to simplify the cluster identification process and improve classification accuracy, and then apply it on text clustering. We also test it on a widely used text corpus. Results show that the proposed method can weaken the influence of data noise and bring more precision to text clustering.
Exclusion of Polymorphisms in Carnosinase Genes (CNDP1 and CNDP2) as a Cause of Diabetic Nephropathy in Type 1 Diabetes

OBJECTIVES— Recently, an association was found between diabetic nephropathy and the D18S880 microsatellite, located in the carnosinase gene (CNDP1) on chromosome 18q. Alleles of this microsatellite encode for a variable number of leucine residues (from four to seven) in the leader peptide of the carnosinase precursor. The frequency of subjects homozygous for the five leucines was higher in control subjects than in case subjects in studies focusing on type 2 diabetic patients. To test whether this finding can be extended to type 1 diabetic patients, we carried out a comprehensive study on association between diabetic nephropathy and the D18S880 microsatellite and 21 additional SNPs that tagged the genomic region containing CNDP1 and CNDP2. RESEARCH DESIGN AND METHODS— Overall, 1,269 Caucasian patients with type 1 diabetes were included in the study, including 613 patients with normoalbuminuria and a long duration of diabetes, 445 patients with persistent proteinuria, and 211 patients with end-stage renal disease (ESRD). All patients were genotyped for selected polymorphisms, the associations with diabetic nephropathy were tested by a χ2 test, and odds ratios were calculated. RESULTS— We did not find any significant association between diabetic nephropathy and any examined genetic markers. The negative findings of the case-control study were supported further by negative findings obtained from the 6-year follow-up study of 445 patients with persistent proteinuria, during which 135 patients developed ESRD. CONCLUSIONS— Our large, comprehensive study did not find an association between the D18S880 microsatellite or any other polymorphisms in the CNDP2–CNDP1 genomic region and susceptibility for diabetic nephropathy in type 1 diabetes.
Rancang Bangun Sistem E-learning Pemrograman Pada Modul Deteksi Plagiarisme Kode Program Dan Student Feedback System

Kompetensi utama yang harus dimiliki oleh mahasiswa jurusan ilmu komputer/informatika adalah pemrograman. Perkuliahan yang berbasis pemrograman seringkali mewajibkan mahasiswa untuk mengerjakan soal yang cukup banyak. Hal ini tentunya akan menyulitkan dosen dalam mengevaluasi hasil pekerjaan mahasiswa. Selain itu, dimungkinkan pula adanya praktik mahasiswa yang memplagiat hasil dari mahasiswa lain. Penelitian ini bertujuan untuk menjawab permasalahan tersebut. Pada penelitian ini dikembangkan sebuah sistem pembelajaran/e-learning pemrograman. Modul sistem e-learning yang dibuat pada artikel ini terbatas pada modul deteksi kemiripan kode program dan student feedback system. Modul deteksi kemiripan kode program berfungsi untuk mengecek kemiripan kode program antar mahasiswa. Kemudian kode-kode program yang memiliki tingkat kemiripan tinggi akan dikelompokkan menjadi satu menggunakan algoritma hierarchical clustering. Proses pengecekan kemiripan program dimulai dari proses transformasi kode program ke dalam Abstract Syntax Tree (AST), kemudian ditransformasi menjadi sequence dan dihitung kemiripannya menggunakan algoritma Levenshtein Distance. Modul student feedback system berfungsi untuk mengecek kemiripan kode program mahasiswa dengan dosen. Mahasiswa akan mendapatkan informasi apakah kode program mereka sudah sesuai dengan yang diinginkan oleh dosen atau belum. Sebelum sistem memberikan umpan Balik, terlebih dahulu kode program dosen dan mahasiswa diproses menjadi AST dan kemudian menjadi sequence. Sistem akan membandingkan kemiripan kode program dosen dan mahasiswa menggunakan algoritma Smith-Waterman yang telah dimodifikasi. Kemudian sistem menampilkan baris-baris kode mana saja yang sama antara kode program dosen dengan kode program mahasiswa. Dari hasil pengujian dapat disimpulkan bahwa modul deteksi plagiarisme dan student feedback system telah terimplementasi dengan baik.
Role of sevoflurane in organ protection during cardiac surgery in children: a randomized controlled trial.

OBJECTIVES The protective effects of volatile anaesthetics against ischaemia-reperfusion injury have been shown in vitro, but clinical studies have yielded variable results. We hypothesized that, in children, sevoflurane provides superior cardioprotection after cardiac surgery on cardiopulmonary bypass (CPB) compared with totally intravenous anaesthesia (TIVA). METHODS In this randomized controlled, single-centre study, 60 children with cyanotic and acyanotic heart defects undergoing elective cardiac surgery under CPB (RACHS-1 1-3) were randomized to sevoflurane or TIVA (midazolam <6 months of age, propofol >6 months of age). The primary end-point was the postoperative peak cardiac troponin I/T (cTnI/T). Perioperative cardiac function (as determined by brain-type natriuretic peptide, echocardiography and postoperative vasopressor/inotrope requirements), short-term clinical outcomes (duration of intubation, intensive care unit and hospital length of stay), postoperative inflammatory profile, and pulmonary, renal and liver function were defined as secondary end-points. Analysis of variance was used for statistical analysis. RESULTS There was no statistically significant difference in postoperative peak troponin values or any of the secondary end-points. In the subgroup of acyanotic patients under 6 months, sevoflurane led to significantly lower postoperative troponin levels compared with midazolam [reduction of 54% (95% confidence interval 29-71%, P = 0.002)], without any differences in secondary outcome parameters. CONCLUSIONS Sevoflurane did not provide superior myocardial protection in our general paediatric cardiac surgical population. In children under 6 months, however, sevoflurane might be beneficial in comparison with midazolam. The conditioning effects of sevoflurane in specific paediatric subgroups need to be further investigated.
Speech enhancement based on spectral subtraction in wavelet domain

In this paper we propose a new approach for speech enhancement. The method used to remove the noise components is a combination of two methods: Wavelet de-noising and spectral subtraction. The idea is to apply the spectral subtraction to wavelet approximations and details coefficients. A new parameter for spectral subtraction in unvoiced speech frames is introduced and the existing power factor in spectral subtraction method is improved. Also, for reduction of musical noise, we propose to use iterative Wiener filtering. Experimental results demonstrate that the proposed speech enhancement algorithm is very promising.
Abstract Routing Models and Abstractions in the Context of Vehicle Routing

The functional and the algebraic routing problem are generalizations of the shortest path problem. This paper shows that both problems are equivalent with respect to the concept of profile searches known from time-dependent routing. Because of this, it is possible to apply various shortest path algorithms to these routing problems. This is demonstrated using contraction hierarchies as an example. Furthermore, we show how to use Cousots' concept of abstract interpretation on these routing problems generalizing the idea of routing approximations, which can be used to find approximative solutions and even to improve the performance of exact queries. The focus of this paper lies on vehicle routing while both the functional and algebraic routing models were introduced in the context of internet routing. Due to our formal combination of both fields, new algorithms abound for various specialized vehicle routing problems. We consider two major examples, namely the time-dependent routing problem for public transportation and the energy-efficient routing problem for electric vehicles.
Multimodal intervention in older adults improves resting-state functional connectivity between the medial prefrontal cortex and medial temporal lobe†

The prefrontal cortex and medial temporal lobe are particularly vulnerable to the effects of aging. The disconnection between them is suggested to be an important cause of cognitive decline in normal aging. Here, using multimodal intervention training, we investigated the functional plasticity in resting-state connectivity of these two regions in older adults. The multimodal intervention, comprised of cognitive training, Tai Chi exercise, and group counseling, was conducted to explore the regional connectivity changes in the default-mode network, as well as changes in prefrontal-based voxel-wise connectivity in the whole brain. Results showed that the intervention selectively affected resting-state functional connectivity between the medial prefrontal cortex and medial temporal lobe. Moreover, the strength of resting-state functional connectivity between these regions correlated with individual cognitive performance. Our results suggest that multimodal intervention could postpone the effects of aging and improve the function of the regions that are most heavily influenced by aging, as well as play an important role in preserving the brain and cognition during old age.
Ant colony search for edge detection

A novel edge detection algorithm based on ant colony optimization and heuristic search is presented. It firstly uses traditional gradient based detector to get the possible edge points. Then a heuristic ant colony search(HACS) algorithm is applied to search the possible edge points repeatedly. In each cycle, pheromones on the traversed route of each ant are updated proportional to the length of the route, and the transition routes converge on real edges progressively based on the pheromone updating rule. At last, real edges can be extracted according to the intensity of pheromones. Compared with traditional ant colony algorithms, the proposed method uses heuristic information to guide the searching process of the ants, which enhances the intention of the search, and improves the efficiency of the algorithm. Experimental results on noise images show that our method can extract real edges effectively, which keeps the edge details and suppresses the noise at the same time.
Connected Dominating Sets

Wireless sensor networks (WSNs), consist of small nodes with sensing, computation, and wireless communications capabilities, are now widely used in many applications, including environment and habitat monitoring, traffic control, and etc. Routing in WSNs is very challenging due to the inherent characteristics that distinguish these networks from other wireless networks like mobile ad hoc networks or cellular networks. Hierarchical or cluster-based methods, originally proposed in wireline networks, are well-known techniques with special advantages related to scalability and efficient communication. As such, the concept of hierarchical routing is also utilized to perform energy-efficient routing in WSNs. Using a virtual backbone infrastructure which is one kind of hierarchical methods has received more attention. Thus, a Connected Dominating Set (CDS) has been recommended to serve as a virtual backbone for a WSN to reduce routing overhead. Having such a CDS simplifies routing by restricting the main routing tasks to the dominators only. Fault tolerance and routing flexibility are necessary for routing since nodes in WSNs are prone to failures and nodes may have mobility and turn on and off frequently. Thus, it is important to maintain a certain degree of redundancy in a CDS. Unfortunately, a CDS only preserves 1-connectivity and it is therefore very vulnerable. Therefore, the concept of k-connected m-dominating sets (kmCDS) are used to provide these redundancy. In this chapter, we first survey some existing cluster-based algorithms. After that, we focus on connected dominating set algorithms, including both centralized and distributed, for how to construct CDS. Theoretical analysis are also presented. Furthermore, some algorithms for kmCDS are described in detail.
Risk Reduction in Natural Disaster Management Through Information Systems: A Literature Review and an IS Design Science Research Agenda

Natural disasters, including earthquakes, Tsunamis, floods, hurricanes, and volcanic eruptions, have caused tremendous harm and continue to threaten millions of humans and various infrastructure capabilities each year. In their efforts to take countermeasures against the threats posed by future natural disasters, the United Nations formulated the "Hyogo Framework for Action", which aims at assessing and reducing risk. This framework and a global review of disaster reduction initiatives of the United Nations acknowledge the need for information systems research contributions in addressing major challenges of natural disaster management. In this paper, the authors provide a review of the literature with regard to how information systems research has addressed risk assessment and reduction in natural disaster management. Based on the review the authors identify research gaps that are centered around the need for acquiring general knowledge on how to design IS artifacts for risk assessment and reduction. In order to close these gaps in further research, the authors develop a research agenda that follows the IS design science paradigm.
Beware of density dependent pair potentials

Density (or state) dependent pair potentials arise naturally from coarse-graining procedures in many areas of condensed matter science. However, correctly using them to calculate physical properties of interest is subtle and cannot be uncoupled from the route by which they were derived. Furthermore, there is usually no unique way to coarse-grain to an effective pair potential. Even for simple systems like liquid argon, the pair potential that correctly reproduces the pair structure will not generate the right virial pressure. Ignoring these issues in naive applications of density dependent pair potentials can lead to an apparent dependence of thermodynamic properties on the ensemble within which they are calculated, as well as other inconsistencies. These concepts are illustrated by several pedagogical examples, including effective pair potentials for systems with many-body interactions, and the mapping of charged (Debye–Huckel) and uncharged (Asakura–Oosawa) two-component systems onto effective one-component ones. The differences between the problems of transferability and representability for effective potentials are also discussed.
: A Model for Sequence Databases

This paper presents the model which is the basis for a system to manage various kinds of sequence data. The model separates the data from the ordering information, and includes operators based on two distinct abstractions of a sequence. The main contributions of the model are: (a) it can deal with different types of sequence data, (b) it supports an expressive range of sequence queries, (c) it draws from many of the diverse existing approaches to modeling sequence data.
Nursing Terminologies as Evolving Large-Scale Information Infrastructures

This paper describes the slowly evolving nature of large-scale terminology- based information infrastructures. The strategic aim of implementing standardized ter - minologies is to share and compare information within and across domain-specific and organizational boundaries. We are particularly interested in working classification sys - tems focused on specific domains' and classes, and even more specifically in reference terminologies with the capability to interconnect different existing classification sys - tems. We examine this empirically through a threefold case based on data from three Norwegian university hospitals, where we also track a national recommendation of a reference terminology. The reference terminology, which was initially promoted as a means to achieve integration and harmonization, is increasingly perceived as compet - ing with other terminologies. This "gateway" has been presented as a purely techni- cal and politically neutral system, but may be more complex in reality: such integration processes require considerable adaptations, negotiations, and manual maintenance.
Applications of hierarchical support vector machines for identifying load operation in nonintrusive load monitoring systems

Due to the global warming and climate changes, using and conserving of the electrical energy effectively becomes a very important issue recently. If each appliance operates efficiently, the power energy can be used and conserved effectively. Further, the greenhouse gases can also gradually be reduced. This paper* proposes a Non-Intrusive Load Monitoring (NILM) system that employs a decision mechanism based on hierarchical support vector machines (HSVM) to identify the energizing and de-energizing statuses of each load. In the proposed system, the load energizing and de-energizing transient features are extracted from load current waveforms that are acquired at the power entering point. The HSVM performs load identification tasks based on the features. Although a support vector machine (SVM) identifier can solve nonlinear separable cases and optimize the decision hyper-plane, it is a two-class identifier. On the other hand, the NILM problem is a multi-class identification problem. Since any multi-class identification problem can be decomposed into a series of two-class identification sub-problems, the proposed system applies a group of binary SVMs that are arranged into a form of hierarchical tree to identify the operation status of each load. Each node within the tree represents a binary SVM identifier, and each identifier is assigned to solve a corresponding two-class sub-problem. Through this hierarchical decision process, the class of an undetermined datum can be identified. Finally, the results in different experiment environments show that the proposed system is able to identify the operation status of each load, and it also has appropriate robustness.
Big-Data Inspired, Proximity-Aware 4G/5G Service Supporting Urban Social Interactions

Unlike virtual sociality, in their daily social behavior individuals are used to communicate with a limited number of persons and periodically meet their inner social circle in specific city locations to perform common social activities. Physical encounters among a restricted number of people interestingly give rise to a significant amount of in-proximity voice/data traffic on the cellular network and advocate the provisioning of a new class of services supporting it. This paper gives empirical evidence of the role played by these location-centered social interactions through the extensive analysis of a large anonymized dataset of Call Detail Records (CDR) relying on the phone activities of nearly 1 million people in the city of Milano. The analysis and understanding of these human interactions have inspired the design of a new mobile service that detects, after user's consent, proximity with a person in my inner social circle and autonomously deploys the mobile social network supporting proximity interactions. The approach we propose brings together a few important contributions: first, it concretely shows that the current NFV-enabled trend of placing cloud services at the edge of the operator's network has a payoff in terms of traffic offloading and improved user's experience; secondly, it demonstrates for the first time that a few typical cloud-based services can actually be directly performed by the mobile network operator by simply leveraging the rich amount of data they possess and never exploit.
Understanding the power of the "solo"

Solitude is a fundamental aspect of wilderness experiences and solo experiences, lasting 5 hours or more, have a strong 'survival' element and are a beneficial component to outdoor therapy programmes, sometimes marking life transitions for people. A shift has been made, however, towards solo experiences that centre on the natural environment rather than 'survival'. Shorter experiences of solitude in wilderness, e.g. quiet time or mini-solos, can offer the most "powerful" form of private reflection and can be self-initiated or prescribed. These 'shorter' solos have not, however, been extensively researched and neither have they been investigated in local green or semi-natural areas. This paper discusses a study that qualitatively explored people's experience, meaning-making and human-environment interaction during a mini-solo in a local green space and identified the impact of the experience on participants' sense of well-being. The mini-solo involved participants spending time in nature without distraction from technology or books and, if possible, people, lasting from 20 minutes to 1 hour. 12 older adults (55-74 years; 8 females and 4 males) recruited from walking groups and six younger adults (19-22 years; 4 females and 2 males) undertook a mini-solo. Pre- and post-experience interviews and journal writing (before, during and after the mini-solo) were analysed using thematic analysis. Four themes were created: ' Exerting Control', 'Aspects of Distraction' and 'Receptivity to Solo Experience'. Findings will be explained in relation to theory, literature and policy and may have implications for 'green prescriptions' as a short-term nature-based solution for well-being. Future directions for research are discussed. Keywords: mini-solo experience, wellbeing.