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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.

The paper deals with the stress-strain state of the metal structure of the load lifting mechanism test bench that is calculated on the basis of the limiting state using the finite element method. It is shown that stresses, that do not lead to accumulation of damages, occur in all design zones and the metal structure has unlimited durability. The results of the experimental attachments of the stressed-deformed mill of the metal cladding are added to the result of the use of the tensometric method of non-verbal control. The crippled pornographic analisys of analitic and experimental dosensis., В работе проведен расчет напряженного деформированного состояния металлоконструкции стенда механизма подъема груза по предельному состоянию с применением метода конечных элементов. Показано, что во всех расчётных зонах действуют напряжения, которые не приводят к накоплению повреждений и их металлоконструкции имеют неограниченную долговечность. Приведены результаты експментальних исследований напряженно-деформированного состояния металлоконструкции клетки с помощью тензометрического метода неразрушающего контроля. Сделан сравнительный анализ аналитических и експментальних исследований., У роботі проведено розрахунок напружено-деформованого стану металоконструкції стенду механізму підйому вантажу за граничним станом із застосуванням методу скінченних елементів. Показано, що у всіх розрахункових зонах діють напруження, що не приводять до накопичення ушкоджень і їх металоконструкції мають необмежену довговічність. Наведено результати експериментальних досліджень напружено- деформованого стану металоконструкції клітки за допомогою тензометричного методу неруйнівного контролю. Зроблено порівняльний аналіз аналітичних та експериментальних досліджень.

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.

This paper considers the design of observational longitudinal studies with a continuous response and a binary time-invariant exposure, where, typically, the exposure is unbalanced, the mean response in the two groups differs at baseline and the measurement times might not be the same for all participants. We consider group differences that are constant and those that increase linearly with time. We study power, number of study participants (N) and number of repeated measures (r), and provide formulas for each quantity when the other two are fixed, for compound symmetry, damped exponential and random intercepts and slopes covariances. When both N and r can be chosen by the investigator, we study the optimal combination for maximizing power subject to a cost constraint and minimizing cost for fixed power. Intuitive parameterizations are used for all quantities. All calculations are implemented in freely available software.

Research on political apologies spans sociopolitical contexts and disciplines and methodological frameworks. In the rise of interest in political apologies, especially in light of ‘the age of apologies’, social psychologists strive to understand mechanisms of issuing, perception and evaluation of political apologies from many perspectives. This special issue aims to highlight the important role of social psychological theory in understanding political apologies and deepening knowledge in this field. The papers, which comprise the special issue, offer a detailed and comprehensive study of political apology, including both theoretical and methodological lens to enrich understanding of the topic. Concluding, all the papers of this special issue can be of interest in academics and researchers, as well as policy-makers and other stakeholders beyond academia.

The article analyzes the peculiarities of organization of museum-pedagogical activities in institutions of general secondary education in conditions of mixed education. Raising a sense of patriotism and active citizenship in the younger generation is now recognized as a general national problem. In modern conditions in our country the requirements for education and training of the younger generation are growing. Thus, one of the most important pedagogical tasks is to educate children in love for Ukraine, respectful attitude towards the family, respect for national traditions and customs, the State and native language, and national values of Ukrainian people. Museum pedagogy considers the museum as a place where feelings are nurtured. The museum does not “illustrate” history, does not teach history. It forms a personʼs personal emotional attitude to one or the other historical facts. The main purpose of the museumʼs existence is to serve people; it provides visitors with a symbolic access to the space of culture. The author reveals the meaning of the terms “museum pedagogy” and “mixed learning”, outlines the possibilities of the teacherʼs use of museum tours for teaching and educating students, determines the potential of Internet resources of museums of Cherkasy region in the context of digitalization of school education and introduction of virtual educational technologies. Especially valuable for the work of a history teacher are the virtual tours presented on the official Internet resources of museums and on other tourist-related sites, which provide an opportunity to work with the museum environment both during lessons and in extracurricular activities.The author emphasizes the fact that the representation of the museum on the Internet allows free access to the objects of historical and cultural heritage for a mass audience. The number of visits to relevant museum Internet resources is increasing significantly. Representation of museums on the Internet is the most effective communication channel for informing about news and events in the institution and allows to interest the younger generation (“raised” on the Internet), to study the history of their native land. Keywords: museum pedagogy; site; virtual tour; Internet network; virtual space; communication; reserve; museums., У статті проаналізовано особливості організації музейно-педагогічної діяльності у закладах загальної середньої освіти в умовах змішаного навчання. Розкрито значення термінів «музейна педагогіка» та «змішане навчання», окреслено можливості використання вчителем історії екскурсій у музеях для навчання та виховання учнів. Визначено потенційні можливості Інтернет-ресурсів музеїв Черкаської області у контексті цифровізації шкільної освіти й упровадження віртуальних навчальних технологій. Особливо цінними для роботи вчителя історії є представлені віртуальні екскурсії на офіційних Інтернет-ресурсах музеїв та на інших сайтах із туристичної тематики, які дають можливість працювати з музейним середовищем як під час уроків, так і в позаурочній діяльності. Ключові слова: музейна педагогіка; сайт; віртуальна екскурсія; мережа Інтернет; віртуальний простір; комунікація; заповідник; музеї.

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.

Traditional deep learning compilers rely on heuristics for subgraph generation, which impose extra constraints on graph optimization, e.g., each subgraph can only contain at most one complex operator. In this paper, we propose AGO, a framework for graph optimization with arbitrary structures to boost the inference performance of deep models by removing such constraints. To create new optimization opportunities for complicated subgraphs, we propose intensive operator fusion, which can effectively stitch multiple complex operators together for better performance. Further, we design a graph partitioning scheme that allows an arbitrary structure for each subgraph while guaranteeing the acyclic property among all generated subgraphs. Additionally, to enable efficient performance tuning on complicated subgraphs, we devise a novel divide-and-conquer tuning mechanism to orchestrate different system components. Through extensive experiments on various neural networks and mobile devices, we show that our system can improve the inference performance by up to 3.3x when compared with state-of-the-art deep compilers.

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.

(1) Background: Clinical reasoning is essential to the effective practice of autonomous health professionals and is, therefore, an essential capability to develop as students. This review aimed to systematically identify the tools available to health professional educators to evaluate students’ attainment of clinical reasoning capabilities in clinical placement and simulation settings. (2) Methods: A systemic review of seven databases was undertaken. Peer-reviewed, English-language publications reporting studies that developed or tested relevant tools were included. Searches included multiple terms related to clinical reasoning and health disciplines. Data regarding each tool’s conceptual basis and evaluated constructs were systematically extracted and analysed. (3) Results: Most of the 61 included papers evaluated students in medical and nursing disciplines, and over half reported on the Script Concordance Test or Lasater Clinical Judgement Rubric. A number of conceptual frameworks were referenced, though many papers did not reference any framework. (4) Conclusions: Overall, key outcomes highlighted an emphasis on diagnostic reasoning, as opposed to management reasoning. Tools were predominantly aligned with individual health disciplines and with limited cross-referencing within the field. Future research into clinical reasoning evaluation tools should build on and refer to existing approaches and consider contributions across professional disciplinary divides.

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.

What are realistic emissions targets for the world's six largest emitters that sum up to Paris-compatible emissions? To answer this question, this paper varies key framework data on the available budget and the sharing mechanism to calculate top-down national emissions targets using the Extended Smooth Pathway Model (ESPM). The Paris ambition mechanism provides a combination of top-down and bottom-up approaches. For each country in the word the question arises to what extent their bottom-up targets fit with global needs. This might initiate a discourse on the global framework data that contributes to Paris-compatible NDCs in sum.

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.

Language MOOCs (L-MOOCs) are the MOOCs (Massive Open Online Courses) that focus on language learning. They may often present several problems in their design and development, such as their feasibility to improve students’ linguistic levels or in their materials’ adequacy and variety. Many of these courses have subsequently become Open Educational Resources (OERs), and their activities can be implemented in different learning situations. Our paper discusses the evaluation of the integration of the L-MOOC titled “Learn academic Spanish” (Aprende español académico) into existing curricula and the validation process carried out to evaluate its validity for the purpose of learning languages. The L-MOOC was developed within the MOOC2move project between 2018–2021 and was designed by the Open University, with the collaboration of the Spanish universities of León and Alicante. The evaluation and validation were carried out in October 2020. In an exceptional hybrid teaching situation, due to the COVID-19 pandemic, the L-MOOC was taken by 345 students from the Faculty of Education of the University of Alicante. The validation of the course consisted of taking the L-MOOC, participating in the forums on the MOOC and completing the questionnaires to improve the materials. In our study, a quantitative analysis was carried out through two questionnaires provided to the students before and after implementing this L-MOOC. The results obtained underlined the effectiveness of this L-MOOC. This course and the materials provided allowed the use of OERs to practice academic Spanish and improve communicative competence of its users.

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.

Eukaryotic autonomously replicating sequences (ARSs) are composed of three domains, A, B, and C. Domain A is comprised of an ARS consensus sequence (ACS), while the B domain has the DNA unwinding element and the C domain is important for DNA-protein interactions. In Saccharomyces cerevisiae and Kluyveromyces lactis ARS101, the ACS is commonly composed of 11 bp, 5ˊ-(A/T)AAA(C/T)ATAAA(A/T)-3ˊ. This core sequence is essential for S. cerevisiae and K. lactis ARS activity. In this study, we identified ARS-containing sequences from genomic libraries of the yeast Kluyveromyces marxianus DMKU3-1042 and validated their replication activities. The identified K. marxianus DMKU3-1042 ARSs (KmARSs) have very effective replication ability but their sequences are divergent and share no common consensus. We have carried out point mutations, deletions, and base pairs substitutions within the sequences of some of the KmARSs to identify the sequence(s) that influence the replication activity. Consensus sequences same as the 11 bp ACS of S. cerevisiae and K. lactis were not found in all minimum functional KmARSs reported here except KmARS7. Moreover, partial sequences from different KmARSs are interchangeable among each other to retain the ARS activity. We have also specifically identified the essential nucleotides, which are indispensable for replication, within some of the KmARSs. Our deletions analysis revealed that only 21 bp in KmARS18 could retain the ARS activity. The identified KmARSs in this study are unique compared to other yeasts’ ARSs, do not share common ACS, and are interchangeable., Highlights • Identification of minimal autonomously replicating sequences (ARSs) from the yeast Kluyveromyces marxianus DMKU3-1042. • The identities of the isolated ARSs are divergent and have no common consensus with the ARSs of other yeasts. • A short ARS sequence of twenty-one nucleotides functions as an effective replicator in K. marxianus DMKU3-1042. • Segments of ARSs from the yeast K. marxianus are interchangeable among each other. • Functional ARSs are found in both the intergenic and coding sequences of the strain DMKU3-1042.

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

In the past years, a number of static application security testing tools have been proposed which make use of so-called code property graphs, a graph model which keeps rich information about the source code while enabling its user to write language-agnostic analyses. However, they suffer from several shortcomings. They work mostly on source code and exclude the analysis of third-party dependencies if they are only available as compiled binaries. Furthermore, they are limited in their analysis to whether an individual programming language is supported or not. While often support for well-established languages such as C/C++ or Java is included, languages that are still heavily evolving, such as Rust, are not considered because of the constant changes in the language design. To overcome these limitations, we extend an open source implementation of a code property graph to support LLVM-IR which can be used as output by many compilers and binary lifters. In this paper, we discuss how we address challenges that arise when mapping concepts of an intermediate representation to a CPG. At the same time, we optimize the resulting graph to be minimal and close to the representation of equivalent source code. Our evaluation indicates that existing analyses can be reused without modifications and that the performance requirements are comparable to operating on source code. This makes the approach suitable for an analysis of large-scale projects.

This paper proposes the initial strategy of designing two degree of freedom proportional integral derivative (2DOF-PID) made load frequency control (LFC) action optimized using Jaya optimization algorithm for a hydro-hydro system. At first, the PID optimized through Jaya is used for hydro-dominated system, and the comparative analysis of all possible error definitions are carried out to show the benefits of selecting integral time absolute error (ITAE) for LFC. Then, 2DOF-PID is designed for the hydro governing system, and its performance is compared with other designs to show the efficacy of the present LFC about computed error values gain of the various models via graphical LFC. The results obtained through simulations are promising but oscillatory with greater settling time. Hence, the proposed controller is retuned by considering the unified power flow control (UPFC) in arrangement with the tie-line and redox flow battery (RFB) units in area-2, and it is further seen that the outcomes of the application show the prevalence of the proposed work.

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 near-globally distributed ecto-parasitic mite of theApis melliferahoneybee,Varroa destructor,has formed a lethal association with Deformed wing virus, a once rare and benign RNA virus. In concert, the two have killed millions of wild and managed colonies, particularly across the Northern Hemisphere, forcing the need for regular acaricide application to ensure colony survival. However, despite the short association (in evolutionary terms), a small but increasing number ofA. melliferapopulations across the globe have been surviving many years without any mite control methods. This long-term survival, orVarroaresistance, is consistently associated with the same suite of traits (recapping, brood removal and reduced mite reproduction) irrespective of location. Here we conduct an analysis of data extracted from 60 papers to illustrate how these traits connect together to explain decades of mite resistance data. We have potentially a unified understanding of naturalVarroaresistance that will help the global industry achieve widespread miticide-free beekeeping and indicate how different honeybee populations across four continents have resolved a recent threat using the same suite of behaviours.

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.

Розмір пояснювальної записки – 103 аркуші, містить 25 ілюстрацій, 36 таблиць, 7 додатків. Актуальність теми. У роботі розглянуто проблему в галузі 3D моделювання для реконструкції зображень реального світу, показано основні особливості існуючих рішень проблеми реконструкції зображень, їх переваги та недоліки. Виявлено проблему в удосконаленні методів реконструкції зображень для отримання кращої якості утворених моделей, їх текстур, а також швидкості роботи алгоритмів для забезпечення можливості виконання реконструкцій в реальному часі. Метою цієї роботи є підвищення якості результуючої моделі об’єкту на основі нового алгоритму для перетворення 2D зображень в 3D моделі, прискорення алгоритму реконструкції 3D моделей на основі 2D зображень для забезпечення можливості відтворення в реальному часі з мінімальними втратами якості та покращення методів накладання текстур на 3D об’єкти для отримання кращої якості моделей та їх відповідність реальним об’єктам. Для досягнення мети необхідно виконати наступні завдання: - виконати аналіз основних методів перетворення 2D зображень в 3D моделі; - здійснити порівняльний аналіз зазначених методів; - розробити алгоритми перетворення 2D зображень в 3D моделі з високою швидкістю та якістю; - розробити алгоритми накладення текстур для моделей з високою якістю; - розробити програмне забезпечення, що реалізовуватиме розроблені алгоритми; - виконати аналіз результатів роботи створеного програмного забезпечення. Об’єкт дослідження – програмне забезпечення, що використовується для побудови тривимірних об’єктів. Предмет дослідження – Моделі, алгоритми та методи для обробки зображень та відеопотоків. Методи дослідження, застосовані в даній роботі базуються на підходах комп’ютерного зору, комп’ютерної графіки та машинного навчання. Наукова новизна одержаних результатів: запропоновано новий алгоритм, що утворений як комбінації алгоритмів виконання перетворення 2D зображень в 3D моделі. В результаті, алгоритм дозволяє отримувати моделі без видимих візуальних дефектів, що мають високий рівень схожості з реальним об’єктом. Практичне значення одержаних результатів: розроблений алгоритм та програмне забезпечення з підтримкою високої якості моделей дозволяє швидко генерувати 3D моделі порівняно з задіянням 3D дизайнерів в разі виникнення необхідності в генерації великого обсягу 3D моделей. Розроблений алгоритм та програмне забезпечення з підтримкою генерації моделей з високою швидкістю уможливлює ряд задач, таких як: відеорепортажі, VR конференції та інші. Зв'язок роботи з науковими програмами, планами, темами. Робота виконувалась на кафедрі інформатики та програмної інженерії Національного технічного університету України «Київський політехнічний інститут ім. Ігоря Сікорського» згідно з планом науково-дослідницьких робіт кафедри інформатики та програмної інженерії. Апробація. Наукові положення дисертації пройшли апробацію на Першій Всеукраїнській науково-практичній конференції молодих вчених та студентів «Інженерія програмного забезпечення і передові інформаційні технології» (SoftTech- 2021) – м. Київ. Публікації. Наукові положення дисертації опубліковані в: Линник В.В. Практичне застосування методу генерації текстур об’єктів в розрізі задачі тривимірної реконструкції/ В.В.Линник, О.П. Сирота // Матеріали першої всеукраїнської науково-практичної конференції молодих вчених та студентів «Інженерія програмного забезпечення і передові інформаційні технології» (SoftTech- 2021) – м. Київ: НТУУ «КПІ ім. Ігоря Сікорського», 22-26 листопада 2021 р. Explanatory note size – 103 pages, contains 25 illustrations, 36 tables, 7 applications. Topicality. Examines the problem of 3D modeling for the reconstruction of realworld images, shows the main features of existing solutions to the problem of image reconstruction, their advantages and disadvantages. The problem in improving the methods of image reconstruction to obtain the best quality of the formed models, their textures, as well as the speed of the algorithms to ensure the possibility of performing reconstructions in real time. The aim of the study. The main target is improving the quality of the resulting object model based on a new algorithm for converting 2D images to 3D models, accelerating the algorithm for reconstructing 3D models based on 2D images to provide real-time playback with minimal quality loss and improving methods of applying textures to 3D objects for obtaining the best quality models and their compliance with real objects. To achieve this goal, you must perform the following tasks: - perform an analysis of the main methods of converting 2D images into 3D models; - carry out the comparative analysis of the specified methods; - develop algorithms for high-speed converting 2D images into 3D models; - develop algorithms for converting 2D images into 3D models with high quality; - develop algorithms for texturing models with high quality; - develop software that will implement the developed algorithms; - perform analysis of the results of the created software. The object of research is software used to build three-dimensional objects. Subjects of research are models, algorithms and methods for processing images and video streams. The research methods used in this paper are based on the approaches of computer vision, computer graphics and machine learning. 10 The scientific novelty of the results is a proposing of a new algorithm, which is formed as a combination of algorithms for converting 2D images into 3D models. As a result, the algorithm allows to obtain models without visible visual defects that have a high level of similarity to real objects. The practical significance of the obtained results. The developed algorithm and software support high quality models and allows to quickly generate 3D models comparing to the use of 3D designers in case when a large volume of 3D models needs to be generated. The developed algorithm and software for high-speed model generation enables a number of tasks, such as: video reporting, VR conferencing etc. Relationship with working with scientific programs, plans, topics. The work was performed at the Department of Informatics and Software Engineering of the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" according to the research works plan of informatics and software engineering department. Approbation. The scientific provisions of the dissertation were tested at the All- Ukrainian Scientific and Practical Conference of Young Scientists and Students “Software Engineering and Advanced Information Technologies” (SoftTech-2021) - Kyiv. Publications. Lynnyk V.V. Practical application of the method of generating textures of objects in the context of the problem of three-dimensional reconstruction / V.V. Lynnyk, O.P. Syrota // Proceedings of the All-Ukrainian Scientific and Practical Conference of Young Scientists and Students “Software Engineering and Advanced Information Technologies” (SoftTech-2021) - Kyiv: NTUU “KPI them. Igor Sikorsky”, November 22- 26, 2021.

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.

Hadi Putra, No. BP. 1920842004, Evaluasi Kebijakan Pendirian Badan Usaha Milik Daerah PT. Balairung Citrajaya Sumbar, Program Magister Administrasi Publik, Fakultas Ilmu Sosial dan Ilmu Politik, Universitas Andalas, Padang, 2021. Dibimbing oleh: Dr. Hendri Koeswara, S.IP., M.Soc.Sc.dan Dr. Syamsurizaldi, S.IP., S.E., M.M. Tesis ini terdiri dari 169Halaman,34buku teori,7buku metode,1 Disertasi, 3 Tesis, 18Artikel Jurnal/Karya Ilmiah,2 Undang-undang, 1 Peraturan Pemerintah, 3 Peraturan Daerah, 1 Laporan, 2dokumen, dan7website internet. Evaluasi kebijakan merupakan bagian dari siklus kebijakan yang memiliki peran penting untuk menilai keberhasilan sebuah kebijakan. Salah satu bentuk kebijakan publik pemerintah daerah yaitu kebijakan Pendirian Badan Usaha Milik Daerah. Tujuan penelitian ini adalah mengevaluasi kebijakan Pendirian Badan Usaha Milik Daerah PT. Balairung Citrajaya Sumbar milik Provinsi Sumatera Barat yang menuai banyak sorotan.Teori yang digunakan adalah tipe evaluasi efektifitas dan evaluasi efisiensi oleh Althaus, Brigman & Davis dengan indikator evaluasi yaitu: input, proses, output, dan outcome. Pendekatan yang digunakan yaitu deskriptif kualitatif dengan pengumpulan data melalui telaah dokumen, observasi, dan wawancara dengan menggunakan teknik purposive sampling. Analisis data dengan cara reduksi data, pemodelan/display data, dan penarikan/verifikasi kesimpulan. Validitas data menggunakan triangulasi sumber. Hasil penelitian menunjukkan bahwa kebijakan pendirian PT. Balairung Citrajaya Sumbar belum efektif dan tidak efisien berdasarkan;(1) Pada input kebijakan terdapat komponen utama yang tidak disediakan yaitu feasibility study, sumber daya manusia sudah memadai, sumberdaya keuangan belum sepenuhnya diterima dari beberapa kabupaten/kota sesuai perjanjian kerjasama pendirian PT.BCS.(2) Proses kebijakan sudah mencapai sasaran yaitu terbentuk dan beroperasinya PT. BCS. Implementor kebijakan sudah menjalankan peran sesuai fungsi masing-masing. Namun belum efektif dalam pencapaian tujuan serta tidak efisien dalam mengelola input menjadi output,(3) Output kebijakan sudah diterima berupa deviden, namun belum bisa secara kontiniu danrasionya masih sangat kecil dibanding investasi yang dikeluarkan karena perusahaan selalu merugi akibat beban penyusutan aset tetap yang terlalu besar. (4) Outcome kebijakan sesuai tujuan formalnya belum signifikan karena kecilnya pendapatan daerah yang diterima dari BUMD ini. Dampak positif lainnya yaitu pada aspek sosial budaya Hotel Balairung menjadi iconkebanggaan dan meeting point masyarakat Sumatera Barat di Jakarta. Sedangkan dampak negatifnya antara lain image Pemerintah Provinsi Sumatera Barat yang tidak mampu mengelola PT.BCS dengan baik dan berkurangnya fungsi Balairung sebagai tempat bernaungnya orang Minang di Jakarta. Selain itu juga penambahan beban APBD untuk sewa kantor Badan Penghubung Provinsi Sumatera Barat di Jakarta. Kata Kunci : Evaluasi Kebijakan, BUMD, PT.Balairung Citrajaya Sumbar

The transmit error vector magnitude (EVM) performance measurements of a slant-polarized 28 GHz gapwaveguidebased phased array is analyzed in this paper. The performance is studied by using a large range of signals, with varied powers, symbol rates, and quadrature amplitude modulation (QAM) orders. The measurements have been conducted for four different scanning angles. A non-standardized over-the-air (OTA) link between the phased array and the receiver in a laboratory environment is used. The results show that the phased array antenna supports a 31 dB effective isotropic radiated power (EIRP) dynamic range at a maximum 2% EVM when transmitting a 64QAMmodulated signal with 250 MS/s symbol rate at all scanning directions.

This paper deals with the spread of diseases over both a population network and an infrastructure network. We develop a layered networked spread model for a susceptible-infected-susceptible (SIS) pathogen-borne disease spreading over a human contact network and an infrastructure network, and refer to it as a layered networked susceptible-infected-water-susceptible (SIWS) model. The SIWS network is in the healthy state (also referred to as the disease-free equilibrium) if none of the individuals in the population are infected nor is the infrastructure network contaminated; otherwise, we say that the network is in the endemic state (also referred to as the endemic equilibrium). First, we establish sufficient conditions for local exponential stability and global asymptotic stability (GAS) of the healthy state. Second, we provide sufficient conditions for existence, uniqueness, and GAS of the endemic state. Building off of these results, we provide a necessary, and sufficient, condition for the healthy state to be the unique equilibrium of our model. Third, we show that the endemic equilibrium of the SIWS model is worse than that of the networked SIS model without any infrastructure network, in the sense that at least one subpopulation has strictly larger infection proportion at the endemic equilibrium in the former model than that in the latter. Fourth, we study an observability problem, and, assuming that the measurements of the sickness-levels of the human contact network are available, provide a necessary and sufficient condition for estimation of the pathogen levels in the infrastructure network. Furthermore, we provide another sufficient, but not necessary, condition for estimation of pathogen levels in the infrastructure network.

It is found that nodes in Delay Tolerant Networks (DTN) exhibit stable social attributes similar to those of people. In this paper, an adaptive routing algorithm based on Relation Tree (AR-RT) for DTN is proposed. Each node constructs its own Relation Tree based on the historical encounter frequency, and will adopt different forwarding strategies based on the Relation Tree in the forwarding phase, so as to achieve more targeted forwarding. To further improve the scalability of the algorithm, the source node dynamically controls the initial maximum number of message copies according to its own cache occupancy, which enables the node to make negative feedback to network environment changes. Simulation results show that the AR-RT algorithm proposed in this paper has significant advantages over existing routing algorithms in terms of average delay, average hop count, and message delivery rate.