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Purpose: Ludruk has a socio-cultural role for the people of East Java in the effort to preserve and develop the local culture. Especially as performing arts, ludruk can act as entertainment that can be enjoyed by various layers of society in East Java, the purpose of this study is: Describe the Improvement of the Management of the Organization of Performing Arts Ludruk Irama Sinar Nusantara Culture. Design/methodology/approach: This research is a qualitative sociological phenomenological study, based on the literature review. The data in this study form qualitative data consisting of three types, namely data behavior, oral data, and writing data. Instruments in this study are researchers themselves. Data analysis in this research consists of several activities that are done jointly, according to Miles and Huberman data reduction, display data and conclusion drawing / verification. Findings: The results of this study are: 1) In general in the approach of critical theorists of art and entertainment ludruk is the idea that they deserve attention for three reasons. First, the contents of art and works present a potentially revealing story of the human, social, and world way of working in the same way as the myth that offers a mimetic representation of the world of life experience. Secondly, ludruk as a means of art and entertainment produced reflects something from the way people live with real conditions is significant. Third, ludruk as an art, if not entertainment how able to entertain the fans as they start to switch to other entertainment. 2) Changes in the paradigm of technical managers in management skills so that the focus to practice the skills required to successfully manage ludruk seriously from various circles to preserve and develop it, to build maximum functional relationships with internal and external clients, it must have a management infusion by adopting the model most recently covering the organizational structure, the function of the marketing channel for the performing arts will lead to the improvement of the delivery of performing arts through more effective inter-organizational management, or certain services to predetermined consumption points, and more importantly improved performance is a change organizations in which managers and organizations that organize organizations place and manage programs that measure the current level of organizational performance and then generate ideas to modify organizational behavior and infrastructure incorporated into the temp at to achieve higher results. Originality/value: This paper is original Paper type: a Research Paper

Background The health system in South Sudan faces extreme domestic resource constraints, low capacity, and protracted humanitarian crises. Supportive supervision is believed to improve the quality of health care and service delivery by compensating for flaws in health workforce management. This study aimed to explore the current supervision practices in South Sudan and identify areas for quality improvement. Methods The study employed qualitative approaches to collect and analyse data from six purposefully selected counties. Data were collected from 194 participants using semi-structured interviews (43 health managers) and focus group discussions (151 health workers). Thematic content analysis was used to yield an in-depth understanding of the supervision practices in the health sector. Results The study found that integrated supportive supervision and monitoring visits were the main approaches used for health services supervision in South Sudan. Supportive supervision focused more on health system administration and less on clinical matters. Although fragmented, supportive supervision was carried out quarterly, while monitoring visits were either conducted monthly or ad hoc. Prioritization for supportive supervision was mainly data driven. Paper-based checklists were the most commonly used supervision tools. Many supervisors had no formal training on supportive supervision and only learned on the job. The health workers received on-site verbal feedback and, most times, on-the-job training sessions through coaching and mentorship. Action plans developed during supervision were inadequately followed up due to insufficient funding. Insecurity, poor road networks, lack of competent health managers, poor coordination, and lack of adequate means of transport were some of the challenges experienced during supervision. The presumed outcomes of supportive supervision were improvements in human resource management, drug management, health data reporting, teamwork, and staff respect for one another. Conclusion Supportive supervision remains a daunting task in the South Sudan health sector due to a combination of external and health system factors. Our study findings suggest that strengthening the processes and providing inputs for supervision should be prioritized if quality improvement is to be attained. This necessitates stronger stewardship from the Ministry of Health, integration of different supervision practices, investment in the capacity of the health workforce, and health infrastructure development.

In heterogeneous wireless networks, random packet loss and high latency lead to conventional TCP variants performing unsatisfactorily in the case of competing communications. Especially on high-latency wireless links, conventional TCP variants are unable to estimate congestion degrees accurately for fine-grained congestion control because of the effects of random packet loss and delay oscillations. This paper proposes a TCP variant at the sender side to identify congestion degrees, namely TCP-WBQ, which quickly responses to the real congestion and effectively shields against random packet loss and oscillations of latency time. The proposed algorithm of congestion control firstly constructs a backlog-queue model based on the dynamics of the congestion window, and deduces the two bounds of the model which delimit oscillations of the backlog queue for non-congestion and random packet loss respectively. TCP-WBQ detects congestion degrees more accurately and thus implements the corresponding schemes of adjusting the congestion window, maintaining a tradeoff between high throughputs and congestion avoidance. The comprehensive simulations show that TCP-WBQ works efficiently in bandwidth utilization with single and multiple bottleneck scenarios, and achieves high performance and competitive fairness in heterogeneous wireless networks.

As a result of their cell structures, elastomeric foams exhibit high compressibility and are frequently used as buffer cushions in energy absorption. Foam pads between two surfaces typically withstand uniaxial loads. In this paper, we considered the effects of porosity and cell size on the mechanical behavior of random elastomeric foams, and proposed a constitutive model based on an artificial neural network (ANN). Uniform cell size distribution was used to represent monodisperse foam. The constitutive relationship between Cauchy stress and the four input variables of axial stretch λU, lateral stretch λL, porosity φ, and cell size θ was given by con-ANN. The mechanical responses of 500 different foam structures (20% < φ < 60%, 0.1 mm < θ < 0.5 mm) under compression and tension loads (0.4 < λU < 3) were simulated, and a dataset containing 100,000 samples was constructed. We also introduced a pre-ANN to predict lateral stretch to address the issue of missing lateral strain data in practical applications. By combining physical experience, we chose appropriate input forms and activation functions to improve ANN’s extrapolation capability. The results showed that pre-ANN and con-ANN could provide reasonable predictions for λU outside the dataset. We can obtain accurate lateral stretch and axial stress predictions from two ANNs. The porosity affects the stress and λL, while the cell size only affects the stress during foam compression.

This paper aims to investigate the hysteric tendencies, inconsistent speeches and silences of woman in Jhumpa Lahiri’s two short stories “The Treatment of Bibi Haldar” and “The Real Durwan.” The paper addresses this objective through the application of subaltern perspective: subaltern cannot speak. More specifically, single, poor and helpless women’s position and their inability to speak in need are analyzed in the light of subaltern studies. These two stories expose the issue of hysteric woman and an elderly street woman with different stories, respectively. The disadvantaged women’s inability to speak – parallels the subaltern’s inability to speak. This paper analyses hysterical tendencies, inconsistent behavior of Lahiri’s protagonists as the outburst, thus, the subtle ways of resistance. Thus, the paper draws the conclusion that Lahiri’s stories demonstrate economically and socially marginalized woman who lack the act of protest as they cannot speak, tending to develop the different verbal and physical inconsistencies.

Cavernous lymphangioma often occurs in the head, neck, trunk, and extremities of infants and children, and it is rare to cause a small intestine intussusception in adults. In this case, a 32-year-old woman presented with abdominal pain, vomiting, and a 5 cm × 5 cm abdominal mass on the left side of the abdomen. Laboratory tests showed anemia and CT showed small intestinal intussusception. After conservative treatments, her symptoms disappeared. However, 18F-FDG PET/CT suggested malignancy and her symptoms reappeared after eating something. Segmental jejunal resection was performed and pathology showed submucosal cavernous lymphangioma. At the 1-year follow-up, the patient was asymptomatic. Then this paper reviewed the literature on small intestinal cavernous lymphangioma in adults and found that this is the first English case report of intussusception caused by a jejunal submucosal cavernous lymphangioma in an adult. Current problem is that adult intussusception and intestinal lymphangioma are difficult to diagnose preoperatively. Imaging techniques such as tomography and PET/CT aid in the diagnosis of these benign lesions. Surgical resection was considered to be the required treatment and seems to have had no recurrence in adults according to the literature.

Focal boost to dominant intraprostatic lesions (DILs) has recently been proposed for prostate radiation therapy. Accurate and fast delineation of the prostate and DILs is thus required during treatment planning. In this paper, we develop a learning-based method using positron emission tomography (PET)/computed tomography (CT) images to automatically segment the prostate and its DILs. To enable end-to-end segmentation, a deep learning-based method, called cascaded regional-Net, is utilized. The first network, referred to as dual attention network, is used to segment the prostate via extracting comprehensive features from both PET and CT images. A second network, referred to as mask scoring regional convolutional neural network (MSR-CNN), is used to segment the DILs from the PET and CT within the prostate region. Scoring strategy is used to diminish the misclassification of the DILs. For DIL segmentation, the proposed cascaded regional-Net uses two steps to remove normal tissue regions, with the first step cropping images based on prostate segmentation and the second step using MSR-CNN to further locate the DILs. The binary masks of DILs and prostates of testing patients are generated on the PET/CT images by the trained model. For evaluation, we retrospectively investigated 49 prostate cancer patients with PET/CT images acquired. The prostate and DILs of each patient were contoured by radiation oncologists and set as the ground truths and targets. We used five-fold cross-validation and a hold-out test to train and evaluate our method. The mean surface distance and DSC values were 0.666 ± 0.696 mm and 0.932 ± 0.059 for the prostate and 0.814 ± 1.002 mm and 0.801 ± 0.178 for the DILs among all 49 patients. The proposed method has shown promise for facilitating prostate and DIL delineation for DIL focal boost prostate radiation therapy.

Underwater marine object detection, as one of the most fundamental techniques in the community of marine science and engineering, has been shown to exhibit tremendous potential for exploring the oceans in recent years. It has been widely applied in practical applications, such as monitoring of underwater ecosystems, exploration of natural resources, management of commercial fisheries, etc. However, due to complexity of the underwater environment, characteristics of marine objects, and limitations imposed by exploration equipment, detection performance in terms of speed, accuracy, and robustness can be dramatically degraded when conventional approaches are used. Deep learning has been found to have significant impact on a variety of applications, including marine engineering. In this context, we offer a review of deep learning-based underwater marine object detection techniques. Underwater object detection can be performed by different sensors, such as acoustic sonar or optical cameras. In this paper, we focus on vision-based object detection due to several significant advantages. To facilitate a thorough understanding of this subject, we organize research challenges of vision-based underwater object detection into four categories: image quality degradation, small object detection, poor generalization, and real-time detection. We review recent advances in underwater marine object detection and highlight advantages and disadvantages of existing solutions for each challenge. In addition, we provide a detailed critical examination of the most extensively used datasets. In addition, we present comparative studies with previous reviews, notably those approaches that leverage artificial intelligence, as well as future trends related to this hot topic.

Serial limiting dilution (SLD) assays are a widely used tool in many areas of public health research to measure the concentration of target entities. This concentration can be estimated via maximum likelihood. Asymptotic as well as exact inference methods have been proposed for hypothesis testing and confidence interval construction in this one-sample problem. However, in many scientific applications, it may be of interest to compare the concentration of target entities between a pair of samples and construct valid confidence intervals for the difference in concentrations. In this paper, an exact, computationally efficient inferential procedure is proposed for hypothesis testing and confidence interval construction in the two-sample SLD assay problem. The proposed exact method is compared to an approach based on asymptotic approximations in simulation studies. The methods are illustrated using data from the University of North Carolina HIV Cure Center.

In this paper I demonstrate some major changes within the traditional disciplinary boundaries of archaeology during the last 25-30 years, and the subsequent formation of new frontiers of theory and practice. They are the result of the expansion and diversification of the discipline in modern society. In that process archaeology has lost its former hegemonic identity which is replaced by pluralism and overlapping functions and identities. This has resulted in institutional and organisational discrepances. My analysis serves as a platform for forrnulating a strategy for cooperation between these new sectors, especially the heritage sector and the universities, leading to the formation of a more coordinated archaeological research practice.

Searching for information about a specific person is a frequent online activity. In most cases, users are aided in the search process by queries containing a name in Web search engines. Typically, Web search engines provide just a few accurate results associated with a name-containing query. Most existing solutions for suggesting synonyms in online search are based on pattern matching and phonetic encoding, however very often, the performance of such solutions is less than optimal. In this paper, we propose SpokenName2Vec, a novel and generic algorithm which addresses the synonym suggestion problem by utilizing automated speech generation, and deep learning to produce novel spoken name embeddings. These embeddings capture the way people pronounce names in a particular language and accent. Utilizing a name’s pronunciation can help detect names that sound alike, but are written differently. We demonstrated the proposed approach on a large-scale dataset with more than 250,000 forenames and surnames and evaluated it on two ground truth datasets containing 7400 forenames and 25,000 surnames (including their verified synonyms). The performance of SpokenName2Vec was found superior to the 10 other algorithms evaluated, including phonetic encoding, string similarity, and machine learning algorithms. The results obtained emphasize the potential of spoken name embeddings for improved synonym suggestion.

Wide field application of curve number (CN) methodology in design flood estimation and forecasting studies is a well-accepted reality. The parameter CN is often regarded as a constant, but it is in fact a random variable, for it relies on a number of factors governing the process of rainfall-runoff. This paper suggests an alternative procedure to estimate design runoff (Q) using design storm (P) and design curve number (CN) values. To this end, design CN values for different durations and return periods have been derived from 25 years of daily annual maximum P-Q data of 10 Indian catchments. When compared, the computed design Q from design CN values was either very close to or slightly greater than the observed Q. The performance is also evaluated using coefficient of determination (R2), percentage of bias (PBIAS), and normalized Nash-Sutcliffe efficiency (NNSE). The magnitude of design CN is found to decrease for longer durations and smaller return periods, and vice versa, and such a behavior invoked the development of an empirical relation for estimation of design CN from given return period and duration for gauged as well as ungauged watersheds. The statistical analysis revealed the general extreme value (GEV) to fit best the P-CN series, whereas multiple probability distributions, viz., GEV, Gumbel max, log Pearson 3, and Gen Pareto fitted best the Q series. The 50-year, 100-year, and 200-year runoff estimated from the P-CN series exceeded only marginally those derived from the conventional Q series approach.

The untapped potential of offshore wind is vast, and will be critical in the global transition to renewable energy and carbon neutrality. Although Australia’s waters are home to enough wind energy to cover its entire electricity needs, the lack of a regulatory framework has prevented the establishment of an offshore wind industry. However, with the passage of the Offshore Electricity Infrastructure Act 2021, there are now significant opportunities for the offshore generation of renewable energy, as well as the transmission of electricity within—and beyond—Australian waters. Framed by consideration of the global and regional context, this paper provides a meaningful perspective on the potential for offshore wind energy in Australia, outlines the new regulatory framework which will enable it to be realised, and highlights key points of contact with contemporary issues of ocean law and policy.

Event horizon imaging requires a third-generation space Very Long Baseline Interferometer on a 500 GHz band. The interferometer challenges available frequency standards. Namely, the practical coherent integration time is about 45 times shorter than needed. A self-calibration could aid this though a 3rd satellite is needed hence, an increased mission cost. This paper is devoted to experimental verification of a novel concept for two-way frequency transfer.We built a dedicated breadboard, test set-up, and run tests with and without temperature differences between branches of the breadboard. A phase difference between derived oscillators is the white noise-like function of the time with 1-σ of 0.5° at 103.2 GHz over more than 3 hours. Varying the temperature difference between branches ±3 C during 4.5 hours, being the orbit period, confirmed that the phase difference is the function of this temperature difference too. The Allan Deviation demonstrated between two derived 103.2 GHz oscillators is of 1.1×10−14/τ over 10 ms < τ < 1000 s, where τ is the averaging time, and the optical communication link path length is 5 km (17 ms). Degradation of this Allan Deviation is of 2 times at the longest-possible delay of 0.2 s in the interferometer system; the 0.2 s is the biggest sum of geometric and communication delays. This worst-case satisfies the requirement with a margin of 11 times. An obtained coherence is in the range of 0.997−0.9998 which is beneficial for the interferometer, at 557 GHz. This is one of the key technology enablers for black hole imaging from space.

This paper considers the musical output of Detroit-based hardcore punk band Negative Approach (and particularly its vocalist John Brannon), as a lens through which to understand Detroit’s place in what Andreas Huyssen calls the “imaginary of ruins.” During their short existence from 1981-1984, Negative Approach developed a sound that is frequently understood to reflect Detroit, the band’s intensity and Brannon’s vicious vocal timbre correlated with the image of a city ‘ruined’ by the economic decline and racial inequities hastened by its infamous 1967 riots. Drawing on ruin studies, a history of Detroit, the context of American hardcore rock, and on the timbral and structural qualities of Brannon’s music, the paper considers both the usefulness and problematic limitations of using ruin imagery to understand a surviving city, of reducing its material reality solely to metonymic expression of post-Fordist decline. While the paper does elucidate the correlation between Brannon’s music and the city’s struggles—which include a strained relationship with its wealthier, de facto segregated suburbs—it also illustrates the extent to which such designations are inherently problematic both for flattening the music’s affect and for overlooking the material reality of a city and its citizens, who struggle onwards with dignity and imagination rather than defining themselves solely in reference to their challenges.

For many recent generations the city of Mombasa, Kenya, on the east African coast (pop. 1.2 million) has been a cosmopolitan racial-cultural-religious milieu of the African, Arab, Indian-Asian, and European. The purpose of this paper is to clarify religious pluralism (r/p) in this urban context to see if there are any instructions to be drawn for the academic understanding of religion in keeping with the methodologies of Religious Studies (RS). Especially of interest here is the effectiveness of the sociological theory of religion developed in the 1987 book A Theory of Religion (ATOR) by Rodney Stark and William Sims Bainbridge to (de)problematize religious behaviour as distinct from political behaviour, which too often become confused and misappropriated as causes. In addition, ATOR provides the terminology for a more critical theory of religion whereby the state’s involvement can be accounted for by examining its use of the cultural means of coercion, thereby clearing the way for a typology of east African r/p to emerge.

While prior research has provided insights into challenges and capabilities related to effective Big Data use, much of this contribution has been conceptual in nature. The aim of this study is to explore such challenges and capabilities through an empirical approach. Accordingly, this paper reports on a multiple case study approach, involving eight organizations from the private and public sectors. The study provides empirical support for capabilities and challenges identified through prior research and identifies additional insights viz. problem-driven approach, time to value, data readiness, data literacy, data misuse, operational agility, and organizational maturity assessment.

This paper depicts a case study of an organizational strategy for the promotion of ethical practice when introducing a new, high-risk, ethically-charged medical practice like Medical Assistance in Dying (MAiD). We describe the development of an interprofessional program that enables the delivery of high-quality, whole-person MAiD care that is values-based and sustainable. A "care ecology" strategy recognizes the interconnected web of relationships and structures necessary to support a quality experience of MAiD for patients, families, and clinicians. This program exemplifies a care ecology approach that addresses common barriers to entry to MAiD practice, and also meets the needs of a variety of stakeholders through the creation of patient and family resources, team supports, standards of practice, professional development opportunities, organizational infrastructure, and community partnerships. We also describe how a thriving care ecology evolves to remain resilient, and to enable integration as the needs of the organization, team and program change over time. The design and development of this program may be adapted to other jurisdictions and organizations where MAiD is introduced, or where new patient populations become eligible for MAiD. This care ecology model may also be applicable to the creation of sustainable programs that provide other morally controversial or novel clinical services.

This paper summarizes the perspectives of health and wellness tourism consumers, to better understand the factors that influence this tourism product. A quantitative approach was adopted to collect primary data through the application of an online survey to effective and potential health and wellness tourism consumers between January and April 2021. Results show that growing number of consumers tend to value health and wellness tourism as a holistic experience, in which not only products specifically related to health and wellness treatments are of particular importance, but also activities related to leisure, recreation and culture. This paper provides a basis of research and analysis for global wellness and tourism industry stakeholders. The aim is to help the industry understand consumer behaviour and preferences in the traveller’s process of choosing a destination for a wellness vacation. This is achieved by predicting wellness tourism trends and developments, by acknowledging the gaps in the research available for understanding wellness tourism and reflecting the experience economy perspective in the sector.

This companion paper is to support the replication of paper "Campus3D: A Photogrammetry Point Cloud Benchmark for Outdoor Scene Hierarchical Understanding", which was presented at ACM Multimedia 2020. The supported paper's main purpose was to provide a photogrammetry point cloud-based dataset with hierarchical multilabels to facilitate the area of 3D deep learning. Based on this provided dataset and source code, in this work, we build a complete package to reimplement the proposed methods and experiments (i.e., the hierarchical learning framework and the benchmarks of the hierarchical semantic segmentation task). Specifically, this paper contains the technical details of the package, including file structure, dataset preparation, installation package, and the conduction of the experiment. We also present the replicated experiment results and indicate our contributions to the original implementation.

Under the development goal of “Carbon Peak, Carbon Neutralization”, the concept of novel power system is proposed. Its representative features include AC/DC interconnection of power grid and large-scale access of new energy power stations. Under these characteristics, higher requirements are put forward for the short-circuit current breaking capacity of the circuit breaker. The DC component of short-circuit current and the injection of new energy into the system short-circuit current cannot be ignored. Based on the 330kV local power grid in Northwest China, this paper studies the power grid operation mode, DC component of short-circuit current and the influence of photovoltaic power station on short-circuit current. The influence law of DC component of short-circuit current on the actual breaking capacity of circuit breaker and access of photovoltaic power station on the short-circuit current are summarized. It can provide a theoretical basis for the selection of circuit breaker in novel power system.

Waste activated sludge (WAS) is formed by a diverse microorganisms, organic and inorganic compounds merged and mixed together in an extracellular polymeric substances (EPS) network. EPS is a complex high-molecular weight macromolecules in WAS that happens to be one of the common analysis to determine the efficiency of treatment. Therefore, different extraction methods has been applied in order to achieve better EPS extraction yield. This paper serves as a base to review the commonly used chemical extraction methods to extract EPS components. The mechanisms, conditions and efficiencies of each of the chemical extraction methods were discussed and compared accordingly. The possible use of different chemical extraction methods for different type of activated sludge were summarized.

Recently, Internet of Things (IoT) and multimedia are gaining popularity because of their usages in various applications. Numerous sensors and automated devices are generating huge volumes of data. Therefore, it is required to efficiently and effectively analyze this voluminous data. It can be achieved by using appropriate machine leaning techniques such as clustering. Among the clustering techniques, the k-means method/algorithm is one of the simplest, effective and commonly used methods. For making the cluster, it uses a measure of similarity/distance among the data observations. Nearby/similar data observations are placed within the same cluster whereas distant/dis-similar data observations are placed in other clusters. Hence, the similarity/distance metric plays a major role on the performance and accuracy of the k-means. Therefore, using an appropriate similarity/distance metric, the performance and accuracy of the k-means can be improved. K-means algorithm is majorly implemented using Euclidean distance metric. With the objective to explore the better and/or alternate similarity/distance metric(s) for k-means, a case study, based on empirical evaluation, of thirteen different similarity/distance metrics on six well-known datasets is performed and presented in this paper. By using the efficient and effective similarity / distance metrics, the performance and accuracy of the k-means algorithm can be improved which leads to formation of good clusters of various data observations or things or images etc. The results of the empirical study are analyzed and compared on the basis of widely used statistical clustering evaluation/validation measures. Based on the comparative results, these metrics are assigned with the ranks. Overall, the results demonstrate that Manhattan and Minkowski distance metrics gives better results for k-means algorithm.

This paper evaluates the reaction of systemically important banks in Europe to the shock of the Russian invasion of Ukraine in 2022. Using the event study methodology and three of the most commonly used models for estimating theoretical returns (CAPM, Fama-French with 3 factors, Fama-French with 5 factors), we show that banks react differently relative to the event date (February 24, 2022) depending on the country. Overall, systemically important banks recorded massive cumulative abnormal returns in the event window. The results differ at the country level depending on the exposure of the respective banks to Russia, the dependence of countries on Russian gas and oil, and the level of informational efficiency of the markets on which they are traded.

This paper describes the design and development of an active device that was applied to shoulder rotation rehabilitation. It implements a force control in a similar way to the haptic devices that reflect a force on the user’s hand according to the rehabilitation parameters. This device was tested with patients, combining clinician manipulation and programmed exercises. The results were excellent, given that the range of movement of the shoulder increased in most of the pa-tients. The results of the Usability Scale questionnaire were also promising.

In this paper we study metric deformations of indecomposable metric Lie superalgebras with dimensions less or equal to 6. We consider formal deformations obtained by even cocycles, because the odd ones can not be used for constructing formal deformations., Comment: 18 pages

Hadoop distributed file system (HDFS) is the file system whereby Hadoop is use it to store all the upcoming data inside it. Since it been declared, HDFS is consuming a huge memory amount in order to serve a normal dataset. Nonetheless, the current file saving mechanism in HDFS save only one file in one datablock. Thus, a file with just 5 Mb in size will take up the whole datablock capacity causing the rest of the memory unavailable for other upcoming files, and this is considered a huge waste of memory in serving a normal size dataset. This paper proposed a method called tiny datablock-HDFS (TD-HDFS) to increase the usability of HDFS memory and increase the file hosting capabilities by reducing the datablock size to the minimum capacity, and then merging all the related datablocks into one master datablock. This master datablock consists of tiny virtual datablocks that contain the related small files together; will exploit the full memory of the master datablock. The result of this study is a running HDFS with a minimum amount of wasted memory with the same read/write data performance. The results were examined through a comparison between the standard HDFS file hosting and the proposed solution of this study.TRANSLATE with x EnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster PortalBack

The use of Electric Vehicles (EVs) is almost inevitable in the near future for the sake of the environment and our plant’s long-term sustainability. The availability of an Electric-Vehicle-Charging Station (EVCS) is the key challenge that owners are worried about. Therefore, we suggest benefiting from individual EVs that have excess energy and are willing to share it with other EVs in order to maximize the availability of EVCSs without the need to rely on the existing charging infrastructure. The Internet of Electric Vehicles (IoEV) is gradually gaining traction, allowing for a more efficient and intelligent transportation system by leveraging these capabilities between EVs. However, the IoEV is considered a trustless environment, with untrustworthy trading partners such as data sellers, buyers, and brokers. Data exchanged between the EV and the Energy AGgregator (EAG) or EV/EV can be used to analyze users’ behavior and compromise their privacy. Thus, a Vehicle-to-Vehicle (V2V)-charging system that is both secure and private must be established. Several V2V-charging systems with security and privacy features have been proposed. However, even if the transmitted communications are entirely anonymous, anonymity alone will not prevent the tracking adversary from reconstructing the target vehicle’s route. These systems frequently fail to find a balance between privacy concerns (e.g., trade traceability to achieve anonymity, and so on) and security measures. In this paper, we propose an efficient privacy-preserving and secure authentication based on Elliptic Curve Qu–Vanstone (ECQV) for a V2V-charging system that fulfils the essential requirements and re-authentication protocol in order to reduce the overhead of future authentication processes. The proposed scheme utilizes the ECQV implicit-certificate mechanism to create credentials and authenticate EVs. The proposed protocols provide efficient security and privacy to EVs, as well as an 88% reduction in computational time through re-authentication, as compared to earlier efforts.

The analysis of the nonproductive time when drilling wells is conducted in the paper. it is established that the most of it is associated with the accidents and complications, with the main share (60%)-seizures. The statistical analysis of the reasons for the occurrence of seizures and the effectiveness of methods for their elimination is presented. A drill string disconnector (RBC) developed at the Tyumen Industrial University is proposed for unscrewing drill pipes and freeing them from trapped pipes. Keywords: well; drill pipes; accidents; seizure; drilling tool; drill string break.

The Internet of Things (IoT) is composed of wireless embedded devices which sense, analyze and communicate the state of the physical world. To achieve truly wireless operation, today’s IoT devices largely depend on batteries for power. However, this leads to high maintenance costs due to battery replacement, or the environmentally damaging concept of disposable devices. Energy harvesting has emerged as a promising approach to delivering long-life, environmentally friendly IoT device operation. However, with the exception of solar harvesting, it remains difficult to ensure sustainable system operation using environmental power alone. This paper tackles this problem by contributing Static, a Radio Frequency (RF) energy harvesting and wireless power transfer platform. Our approach comprises autonomous energy management techniques, adaptive power transfer algorithms and an open-source hardware reference platform to enable further research. We evaluate Static in laboratory conditions and show that 1) ambient RF energy harvesting can deliver sustainable operation using common industrial sources, while 2) wireless power transfer provides a simple means to power motes at a range of up to 3 m through a variety of media.

Deep neural networks (DNNs) technique has achieved impressive performance on semantic segmentation,while its training process requires a large amount of pixel-wise labelled data. Domain adaptation,as a promising solution,can break the restriction by training the model on synthetic data,and generalising it in real-world data. However,there is still a lack of attention paid to the imbalance problems on semantic segmentation adaptation,including the imbalance problem between i) source and target data,ii) different classes. To solve these problems,a progressive hierarchical feature alignment method is proposed in this paper. To alleviate the data imbalance problem,the network is progressively trained by the data from multisource domains,so as to obtain domain-invariant features. To address the class imbalance problem,the features are aligned hierarchically across domains. According to the experimental results,our method shows the competitive adapted segmentation performance on three benchmark datasets.

Sexually transmitted diseases (STD) are transmitted from one person to another through sexual contact, caused by bacteria, viruses or parasites. STDs are becoming a major public health problem in India. The objective of this paper is to determine the prevalence of awareness of STD among the youth age group of 15-24 years old residing in the urban slum of Jorhat town. The study shows that in the age group 15-19 years, 62% individuals were not aware about STDs while about 52% were not aware in the age group 20-24 years. The present study reveals that only about 61% individuals opined that STDs are transmissible and only 42% say that STD is preventable. It is concluded from the study that majority of the individuals in the study group are unaware about STD's.

The Blasius equation dates back to the early twentieth century and describes the boundary layer caused by a uniform flow over a flat plate. Due to the asymptotic condition on the first derivative of the solution, the problem is not an initial value one. The non-linear nature of the equation has led many authors to exploit approximation strategies to obtain an estimate of the solution. Several papers deal with series expansions, but the solutions are partly numerical and do not converge rapidly everywhere. In the present paper, a strategy is proposed to obtain an approximate solution of the Blasius problem in the closed form, i.e., without the use of series expansions. Motivated by the asymptotic behavior of the second derivative, a parametric definition of the third derivative of the Blasius solution is introduced and successive integrations are performed. By imposing the expected asymptotic conditions, a final approximate solution is obtained. This latter has the notable advantage of possessing the same behavior at 0 and at [Formula: see text] as the analytical solution up to the third derivative. It will also be shown how this result can be extended to the Falkner–Skan problem with non-zero pressure gradient and provide an accurate estimation of the thermal boundary layer over a flat plate under isothermal and adiabatic conditions.

This paper deals with the use of social networks in agricultural enterprises and focuses mainly on their role and share in increasing the competitiveness of agricultural enterprises in the market. Primary data were obtained from an extensive survey of the development of information and communication technologies in agricultural enterprises, which was conducted in the first quarter of 2021 throughout the Czech Republic (“Survey 2021”). The research was primarily focused on capturing current trends in the use of ICT with emphasis on selected key areas (broadband, social networks, communication tools, regional Internet portals, used hardware categories, used software, mobile communications, Internet of Things, data storage and security, social networks, etc.). This survey builds on previous extensive surveys conducted by the Department of Information Technologies, Faculty of Electrical Engineering, CULS in Prague in several phases since 1999, with the last stage being conducted in 2017. Some surveys were conducted in cooperation with the Ministry of Agriculture of Czech Republic.Compared to recent years, the survey includes new domains, such as the use of the Internet of Things in plant and animal production, data storage and security, the impact of the Covid-19 pandemic on the company's core operations, etc. The survey was prepared, conducted and administered by the Department of Information Technology, Faculty of Economics and Management, University of Life Sciences Prague.

This paper addresses an action that, from a Deleuzian perspective, is capable of modifying the despairing current social situation in which we are immersed, through the creation of political Ideas. Even though Deleuze conceives social Ideas as vast civilizing structures, we propose to bring into the political domain the logic of other acts of creation, such as the artistic or the philosophical, where the monumental coexists with minor figures that are nonetheless capable of introducing novelty into the world. The politician is the figure of those who are capable of having an Idea that allows to break the habits that perpetuate the current situation, and gives consistency to the intensive forms of life that continually create and dissolve themselves in the flow of becoming. Thus, macro- and micro-politics do not oppose each other, but offer in their immanence an alternative to social nihilism.

This paper seeks to examine the concept of “Merdeka Belajar” or “Freedom of Learning” which was initiated by the Indonesian Minister of Education and Culture, Nadiem Makarim. The study of freedom of learning uses text study with content analysis method. The concept of “Freedom of Learning” is very interesting when studied with a multicultural education perspective. Moreover, the two concepts have the same relevance and spirit, namely freedom and justice in the human resources development context, particularly through the educational process. Based on the results, the implementation of “MerdekaBelajar” program so far includes four aspects, namely financing, teachers / educators, assessment, and graduates. In a multicultural perspective, problems in management and assessment aspects basically caused by a misunderstanding of the meaning of standards and standardization. Meanwhile, the teacher and graduate aspects lie in the importance of developing multicultural competencies.Integrating a multicultural education perspective in the “Freedom of Learning” policy also transforms an education system that is creative, innovative, and character.

From the researches carried out in literature it appears how gaming is a behaviour in continuous evolution and expansion (Mauceri & Di Censi, 2020) and is widespread in the entire population, particularly among teenagers. The present paper is the result of a multi-professional and inter-sectorial research carried out and shared with operators of the health service Azienda Sanitaria Universitaria Friuli Centrale (ASUFC), teachers of the Regional School Office (Uff. VI), the Provincial Student Council (CPS) of Udine and with a professional educator. One of the targets of this research was to analyse the feelings and beliefs of players regarding the use of videogames and this was done in March 2021 through a questionnaire. 596 students of upper secondary schools of Udine territory joined this survey and to reach the target four videoplayer profiles have been outlined taking into account the play time: the occasional player (N = 61; 10.2%) who uses the videogames for maximum 30 minutes per day, the habitual player – mild (N=57; 9.6%) between 30 minutes and 1 hour, the habitual player – moderate (N=250, 41.9%) between 1 and 4 hours and the severe player (N=71, 11.9%) between 4 and more than 6 hours. The analysis of the replies demonstrates how all statements (21), following the chi-squared test, have a statistically important difference with respect to the profiles, except for two. It appears how the severe players run more often into potential experiences of risk of addiction or trouble, and they prefer to play instead of going out with friends, sometime also stopping friendship relations and feeling a higher desire to going on playing at the end of the session, also forgoing some hours of sleep. The research group, taking into consideration the spreading of the behaviour of severe players (11.9%), would deem useful to plan and carry out future interventions aimed at encouraging the technological health since the first classes of upper secondary schools, in order to allow the students the acquainted use of technologies and gaming activities and to prevent the relative risks coming from the massive and improper use of these tools and actions.

This paper is a revised abundance analysis of four yellow supergiant stars Cepheids which are located in the Galactic nucleus. The results are based on the spectra secured with the help of Subaru telescope, which are of the better quality comparing to previously analysed spectra taken with the Infrared Telescope Facility. A significantly improved method of the effective temperature determination of program stars, which is based on the calibrating relations between the temperature and line depth ratios, was applied. The present results confirmed our previous finding about the solar metallicity level at the Galaxy centre. It is very likely that the four stars of our program were born from an interstellar medium having homogeneous chemical properties, since all the stars are located close to each other, have close pulsation periods, and hence the age. However, one of the stars has a somewhat increased abundance of all studied elements compared to the abundance in the other three stars. A possible reason of this fact is discussed.

Next Point-of-interest (POI) recommendation has been recognized as an important technique in location-based services, and existing methods aim to utilize sequential models to return meaningful recommendation results. But these models fail to fully consider the phenomenon of user interest drift, i.e. a user tends to have different preferences when she is in out-of-town areas, resulting in sub-optimal results accordingly. To achieve more accurate next POI recommendation for out-of-town users, an adaptive attentional deep neural model HOPE is proposed in this paper for modeling user’s out-of-town dynamic preferences precisely. Aside from hometown preferences of a user, it captures the long and short-term preferences of the user in out-of-town areas using “Asymmetric-SVD” and “TC-SeqRec” respectively. In addition, toward the data sparsity problem of out-of-town preference modeling, a region-based pattern discovery method is further adopted to capture all visitor’s crowd preferences of this area, enabling out-of-town preferences of cold start users to be captured reasonably. In addition, we adaptively fuse all above factors according to the contextual information by adaptive attention, which incorporates temporal gating to balance the importance of the long-term and short-term preferences in a reasonable and explainable way. At last, we evaluate the HOPE with baseline sequential models for POI recommendation on two real datasets, and the results demonstrate that our proposed solution outperforms the state-of-art models significantly.

Objective: To propose a deep-learning network for the diagnosis of two corneal diseases: Fuchs’ endothlelial dystrophy and keratoconus, based on optical coherence tomography (OCT) images of the cornea. Methods: In this paper, we propose a novel network with parallel resolution-specific encoders and composite classification features to directly diagnose Fuchs’ endothelial dystrophy and keratoconus using OCT images. Our proposed network consists of a multi-resolution input, multiple parallel encoders, and a composite of convolutional and dense features for classification. The purpose of using parallel resolution-specific encoders is to perform multi-resolution feature fusion. Also, using composite classification features enhances the dense feature learning. We implemented other related networks for comparison with our network and performed k-fold cross-validation on a dataset of 16,721 OCT images. We used saliency maps and sensitivity analysis to visualize our proposed network. Results: The proposed network outperformed other networks with an image classification accuracy of 0.91 and a scan classification accuracy of 0.94. The visualizations show that our network learned better features than other networks. Significance: The proposed methods can potentially be a step towards the early diagnosis of corneal diseases, which is necessary to prevent their progression, hence, prevent loss of vision.

2Clinical Research Facility, Alder Hey Children’s HospitalIntroductionIn 2018 the Centers for Disease Control published updated Standards of Care for Duchenne Muscular Dystrophy – newly included was the recommendation for all patients with DMD who received steroids to receive prescriptions for intramuscular (IM) hydrocortisone for emergency administration at home.The aim of this systematic review was to assess the current understanding of the pharmacodynamics and kinetics of intramuscular therapies in patients affected by DMD.MethodsA systematic review was conducted according to Cochrane methodology. Medline, EMBASE and PubMed databases were searched. Two independent reviewers reviewed the abstract of each identified paper. Where there was any discrepancy in the decision to include or exclude a paper, a third reviewer arbitrated.ResultsThe search returned a total of 98 papers. 96 papers were excluded: 61 described animal or in-vitro studies, whilst the remaining studies did not study an intramuscular pharmacological intervention or were review articles.Of the two included articles, one compared the immunogenicity of intramuscular and subcutaneous administration of influenza vaccination, and the other studied ten patients with DMD who were injected with two different doses of plasmidic DNA. Neither study reported on the pharmacodynamics or kinetics of the interventions.ConclusionsThere is very limited evidence into the pharmaco-kinetics and -dynamics of IM therapies for children affected by muscular dystrophy. Given the recognised changes in the muscle structure and function, studies to explore if this causes clinically significant changes in boys with DMD are required.

Background: The term "outpatient surgery" has become a common procedure in most hospitals around the world. On other hand, Spinal aesthesia can mimic the outcome sought by the principle of outpatient surgeries since it takes a short time to recover and limits the need for post-operative pain medication Therefore, the objective of this study is to focus on finding a method to reduce the side effects that commonly accompany the procedure of spinal aesthesia and to avoid the possible hemodynamic changes that may occur. Methods: The method for the study will be a narrative review of various medical journals, conferences papers, and unpublished documents using the dual keywords, outpatient surgeries spinal aesthesia, and ambulatory aesthesia, we include in this research thirty-one original articles, fifty-three reviews articles, two books, three handbooks, and two guidelines searched in the deferent database (google scholar, Research gate, pub med, science direct). Results: Consideration should be given to the quality of patients who participate in outpatient concepts. Finally, in terms of cost, side effects, and patient satisfaction, the spinal aesthetic approach gives a favourable outcome since it covers post-operative time without the need for analgesia and reduces the percentage of postoperative nausea and vomiting, and reduces the time staying in the hospital. Conclusions: In conclusion, the study discovered that a major proportion of surgeries performed over our lifetimes are outpatient procedures. Therefore, Discharge criteria should be posed with one precise criterion. There is no standard protocol to serve these types of surgeries and patients. The only criteria found and practiced served general conditions for outpatients and inpatients. There have been several attempts to create a protocol that can meet the pleasing outcome of outpatient surgeries. Consequently, we need more research to cover this lack and serve the Genuine needs of a protocol to define the criteria and categories that concern the term outpatient and outpatient surgeries and lead to improving the quality of outpatient surgeries with fewer side effects and minimum hemodynamic changes.

This paper investigates six possible SLAs which are run for the evaluation trials developed at the AWMP Intersessional Workshop (IWC, 2015). Candidates are presented ranging from providing complete satisfaction of the conservation performance criterion for all evaluation trials, to alternatives that sacrifice performance on this count to increasing extents for improved need satisfaction. Need is better satisfied over the first 20 years than over 100 years for these SLAs in these trials.

The optimization of cutter shape has become one of the main innovation direction of PDC bit technology. At present, both domestic and foreign bit manufacturers have put forward various special shaped cutters to improve rock breaking efficiency. However, there are relatively few researches which focus on the rock breaking efficiency of special-shaped cutters. Therefore, three kinds of typical cutters (flat cutter, convex cutter and concave cutter) are selected as the study object in this paper. Based on the single cutter test, the relationship of axial cutting force, cutting area and cutting specific energy under different working conditions will be provided. The experimental results show that the axial cutting force and specific energy of concave cutter and convex cutter are lower than that of flat cutter in most test cases. The results are almost the same for both Vosges sandstone and Marcellus shale cases. In other words, the tested concave cutters are easier to intrude into rock and obtain higher rock brea king efficiency under the same cutting conditions, when compared with flat cutter and convex cutter. The experimental method provides a technica l reference for studying the rock breaking efficiency of three-dimensional cutters with different shapes.

Energy harvesting technology is a key enabler for the application of sensing systems in remote locations. For condition monitoring of large-scale electrical engines (LSEE) magnetic energy harvesting (MEH) has been suggested as a suitable technique. MEH can provide comparatively high output powers. A critical parameter for the design of a MEH system is the ratio between the maximum and the minimum operating current. In the case of a large ration the design of a MEH system becomes challenging. Protective measures are required to prevent a destruction at high primary currents. In this paper we investigate a miniaturized magnetic energy harvesting design, where the transformer consists of a single sheet of steel. We investigate the output power performance of the design with respect to low power applications and show, that the miniaturized design is intrinsically safe with respect to high primary currents.

Neural Cryptography is a new thread that integrates cryptography and neural networks for cryptanalysis and encryption applications. We show that Neural Networks can execute symmetric encryption in an adversarial context in this paper, and we build on the existing literature on the subject. Cryptography's purpose is to make it difficult to decipher a cypher and recreate the plain text without the associated key. Your messages are encrypted with excellent cryptography in such a way that brute force attacks against the algorithm or key are nearly impossible. Good cryptography is secure because it employs extremely long keys and encryption techniques that are resistant to various types of attack. The neural net application is the next step in the evolution of good cryptography. This paper discusses the use of neural networks in cryptography, including how to create neural networks that can be utilized in cryptography. Keywords: Cryptography key, encryption system, encryption algorithm, artificial neural network,chaos maps, logistic encryption.

Introduction In the past decade there has been an increasing interest in the field of patient-reported outcome measures (PROMs) which are now commonly used alongside traditional outcome measures, such as morbidity and mortality. Since the FACE-Q Aesthetic development in 2010, it has been widely used in clinical practice and research, measuring the quality of life and patient satisfaction. It quantifies the impact and change across different aspects of cosmetic facial surgery and minimally invasive treatments. We review how researchers have utilized the FACE-Q Aesthetic module to date, and aim to understand better whether and how it has enhanced our understanding and practice of aesthetic facial procedures. Methods We performed a systematic search of the literature. Publications that used the FACE-Q Aesthetic module to evaluate patient outcomes were included. Publications about the development of PROMs or modifications of the FACE-Q Aesthetic, translation or validation studies of the FACE-Q Aesthetic scales, papers not published in English, reviews, comments/discussions, or letters to the editor were excluded. Results Our search produced 1189 different articles; 70 remained after applying in- and exclusion criteria. Significant findings and associations were further explored. The need for evidence-based patient-reported outcome caused a growing uptake of the FACE-Q Aesthetic in cosmetic surgery and dermatology an increasing amount of evidence concerning facelift surgery, botulinum toxin, rhinoplasty, soft tissue fillers, scar treatments, and experimental areas. Discussion The FACE-Q Aesthetic has been used to contribute substantial evidence about the outcome from the patient perspective in cosmetic facial surgery and minimally invasive treatments. The FACE-Q Aesthetic holds great potential to improve quality of care and may fundamentally change the way we measure success in plastic surgery and dermatology. Level of Evidence III This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.