A Survey of Deep Active Learning

Active learning (AL) attempts to maximize a model’s performance gain while annotating the fewest samples possible. Deep learning (DL) is greedy for data and requires a large amount of data supply to optimize a massive number of parameters if the model is to learn how to extract high-quality features. In recent years, due to the rapid development of internet technology, we have entered an era of information abundance characterized by massive amounts of available data. As a result, DL has attracted significant attention from researchers and has been rapidly developed. Compared with DL, however, researchers have a relatively low interest in AL. This is mainly because before the rise of DL, traditional machine learning requires relatively few labeled samples, meaning that early AL is rarely according the value it deserves. Although DL has made breakthroughs in various fields, most of this success is due to a large number of publicly available annotated datasets. However, the acquisition of a large number of high-quality annotated datasets consumes a lot of manpower, making it unfeasible in fields that require high levels of expertise (such as speech recognition, information extraction, medical images, etc.). Therefore, AL is gradually coming to receive the attention it is due. It is therefore natural to investigate whether AL can be used to reduce the cost of sample annotation while retaining the powerful learning capabilities of DL. As a result of such investigations, deep active learning (DeepAL) has emerged. Although research on this topic is quite abundant, there has not yet been a comprehensive survey of DeepAL-related works; accordingly, this article aims to fill this gap. We provide a formal classification method for the existing work, along with a comprehensive and systematic overview. In addition, we also analyze and summarize the development of DeepAL from an application perspective. Finally, we discuss the confusion and problems associated with DeepAL and provide some possible development directions.

Assessing Large-Scale Power Relations among Locations from Mobility Data

The pervasiveness of smartphones has shaped our lives, social norms, and the structure that dictates human behavior. They now directly influence how individuals demand resources or interact with network services. From this scenario, identifying key locations in cities is fundamental for the investigation of human mobility and also for the understanding of social problems. In this context, we propose the first graph-based methodology in the literature to quantify the power of Point-of-Interests (POIs) over its vicinity by means of user mobility trajectories. Different from literature, we consider the flow of people in our analysis, instead of the number of neighbor POIs or their structural locations in the city. Thus, we modeled POI’s visits using the multiflow graph model where each POI is a node and the transitions of users among POIs are a weighted direct edge. Using this multiflow graph model, we compute the attract, support, and independence powers . The attract power and support power measure how many visits a POI gathers from and disseminate over its neighborhood, respectively. Moreover, the independence power captures the capacity of a POI to receive visitors independently from other POIs. We tested our methodology on well-known university campus mobility datasets and validated on Location-Based Social Networks (LBSNs) datasets from various cities around the world. Our findings show that in university campus: (i) buildings have low support power and attract power ; (ii) people tend to move over a few buildings and spend most of their time in the same building; and (iii) there is a slight dependence among buildings, even those with high independence power receive user visits from other buildings on campus. Globally, we reveal that (i) our metrics capture places that impact the number of visits in their neighborhood; (ii) cities in the same continent have similar independence patterns; and (iii) places with a high number of visitation and city central areas are the regions with the highest degree of independence.

System for Fake Currency Detection Using Image Processing

Counterfeit money has always existed an issue that has caused many problems in the market. Technological growth development has made it possible to create extra counterfeit items which are distributed in the mitigation market the global economy. Bangui existing banking equipment and so on trading sites to check the authenticity of funds. But the average person does not do that have access to such systems and that is why they are needed in order for the software to receive counterfeit money, which can be used by ordinary people. This the proposed system uses image processing to find out if the money is real or fake. System built uses the Python system completely language. It contains similar steps grayscale modification, edge detection, separation, etc. made using appropriate methods. Keyword: Counterfeit currency, Image Processing, Python programming language, grayscale conversion, edge detection, segmentation.

Evaluation of the steady state performance of a squirrel cage induction motor using per-phase equivalent circuit

The performance evaluation of cage induction motor continues to receive tremendous attention because of its vital effect on the overall system stability. The model has predicted the behavior of cage induction motor under different operating conditions and in selecting the appropriate motor for a specific load application. There is often a challenge when a squirrel cage induction motor is connected to a time-varying load, particularly when the motor is selected without considering the effects of pulsating torques. The usual method used for steady state analysis of induction motors is the equivalent circuit method. Using the per phase equivalent circuit of the induction motor, stator current and referred rotor current were computed using simple circuit analysis. Once the currents are available, then power can be computed because the voltage is already known.

COVID MED - An Early Pandemic Trial of Losartan for Hospitalized COVID-19 Patients

Background ACEi/ARB medications have been hypothesized to have potential benefit in COVID-19. Despite concern for increased ACE-2 expression in some animal models, preclinical and observational-retrospective and uncontrolled trials suggested possible benefit. Two RCTs of the ARB losartan from University of Minnesota showed no benefit yet safety signals for losartan in outpatient and hospitalized COVID-19 patients. COVID MED, started early in the pandemic, also assessed losartan in a RCT in hospitalized patients with COVID-19. Methods COVID MED was quadruple-blinded, placebo-controlled, multicenter randomized clinical trial (RCT). Hospitalized COVID-19 patients were randomized to receive standard care and hydroxychloroquine, lopinavir/ritonavir, losartan, or placebo. Hydroxychloroquine and lopinavir/ritonavir arms were discontinued after RCTs showed no benefit. We report data from the losartan arm compared to combined (lopinavir-ritonavir and placebo) and prespecified placebo-only controls. The primary endpoint was the NCOSS slope of change. Slow enrollment prompted early stopping. Results Of 432 screened patients, 14 were enrolled (3.5%), 9 received losartan and 5 combined control (lopinavir/ritonavir [N=2], placebo [N=3]); 1 hydroxychloroquine arm patient was excluded. Most baseline parameters were balanced. Treatment with losartan was not associated with a difference in NCOSS slope of change in comparison with combined control (p=0.4) or placebo-only control (p=0.05) (trend favoring placebo). 60-day mortality and overall AE and SAE rates were numerically but not significantly higher with losartan. Conclusions In this small blinded RCT in hospitalized COVID-19 patients, losartan did not improve outcome vs. control comparisons and was associated with adverse safety signals.

Pandangan Hukum Islam terhadap Status Muflis (Debitur Pailit) sebagai Gharimin (Mustahik Zakat)

The development of sharia economy in Indonesia is increasing. Islamic economic development can be seen from the development of Islamic financial institutions and the Islamic financial instruments they offer, ranging from Islamic banks, Islamic capital markets, and Islamic insurance. With these developments, nowadays financing activities with sharia contracts are increasing and growing rapidly. However, only a few can pay it off. In other words, non-performing financing or bad loans at Islamic financial institutions often occur. Non-performing financing caused by the inability of the customer as a debtor to pay debts to a financial institution as a creditor resulted in the customer being bankrupted by the financial institution as a creditor. Bankruptcy is defined as the inability of the debtor or debtor (can be a person, legal entity, company) which is proven based on a court decision that the debtor has stopped paying his debts (unable to pay off debts) which results in general confiscation of his assets, so that the debtor is no longer entitled to manage his assets. . If it is associated with zakat, one of the ashnaf of zakat is gharimin or people who are in debt. Zakat institutions in Indonesia have not made bankrupt customers as gharimin who are entitled to receive zakat. The formulation of the problem in this paper is to find out the views of Islamic law on the status of bankrupt debtors as gharimin. The conclusion is that the status of a bankrupt debtor can be determined as a gharimin who is entitled to receive zakat. The use of debt in question can be for personal or public interest. The distribution pattern can use the qardh hasan pattern where the zakat given to the gharimin is not to be owned but to be returned again. The zakat funds are not only used to pay off debts, they can also be used as initial capital for bankrupt debtors to restart their business. Keywords: bankrupt debtor, gharimin, zakat mustahik.

OPTIMALISASI PELAYANAN PUBLIK SECARA ONLINE PADA KANTOR WILAYAH KEMENTERIAN HUKUM DAN HAM PROVINSI SULAWESI TENGGARA

This study aims to determine and describe optimizing public services online at the regional office of the Ministry of the Law and Human Rights in Southeast Sulawesi, this study uses descriptive qualitative methods to 5 informants determined by snowball sampling technique, data analysis techniques consist of data collection, data reduction, presentation data, drawing conclusions/verification, the data obtained were analyzed qualitatively and described in descriptive form. The results of this study indicate that public services carried out online at the regional office of the Ministry of Law and Human Rights in Southeast Sulawesi are very good, this can be seen from the implementation of services with standard operating procedures that apply during the pandemic and the handling that is in accordance with what has been determined at the regional office of the Ministry of Law and Human Rights by upholding the values of professionalism, accountability, synergy, transparency, and innovation. Based on the research, one form of research on optimizing public services is the existence of a digital-based service system that makes it easier for the public to receive services, supporting facilities, and infrastructure, as well as services provided quickly and responsively at the region of the Ministry of Law and Human Rights in Southeast Sulawesi.

Effects of Sambiloto (Andrographis paniculata) on GLP-1 and DPP-4 Concentrations between Normal and Prediabetic Subjects: A Crossover Study

Background. The extract of Andrographis paniculata (Burm. F.) Wall. Ex. Nees. (sambiloto) (穿心蓮 chuān xīn lián) has been reported to have an antidiabetic effect on mice models and has been used traditionally in the community. The exact mechanism of sambiloto extract in decreasing plasma glucose is unclear, so we investigated the role of sambiloto extract in the incretin pathway in healthy and prediabetic subjects. Methods. This study was a randomized, placebo-controlled, crossover, double-blind trial. It included 38 people who were healthy and 35 people who had prediabetes. All subjects were randomly assigned to receive either the intervention sambiloto extract or a placebo. All subjects were randomly assigned to receive the first intervention for 14 days. There was a washout period between subsequent interventions. The primary outcome was glucagon-like peptide 1 (GLP-1) concentration, and secondary outcomes were fasting insulin, 2-hour postprandial insulin, homeostasis model assessment of insulin resistance (HOMA-IR), fasting blood glucose, 2-hour postprandial blood glucose, dipeptidyl peptidase-4 (DPP-4), and glycated albumin before and after the intervention. Result. After the intervention, GLP-1 concentration significantly increased in prediabetes by 19.6% compared to the placebo ( p = 0.043 ). There were no significant differences in the changes of fasting insulin, 2-hour postprandial insulin, HOMA-IR, fasting blood glucose, 2-hour postprandial blood glucose, DPP-4, and glycated albumin levels after the intervention. Sambiloto extract did not inhibit the DPP-4 enzyme in healthy and prediabetic subjects. Conclusion. Sambiloto extract increased GLP-1 concentration without inhibiting the DPP-4 enzyme in prediabetic subjects. This trial is registered with ClinicalTrials.gov (ID: NCT03455049), registered on 6 March 2018—retrospectively registered (https://clinicaltrials.gov/ct2/show/NCT03455049).

Establishing the Mutational Spectrum of Hungarian Patients with Familial Hypercholesterolemia

Familial hypercholesterolemia (FH) is one of the most common autosomal, dominantly inherited diseases affecting cholesterol metabolism, which, in the absence of treatment, leads to the development of cardiovascular complications. The disease is still underdiagnosed, even though an early diagnosis would be of great importance for the patient to receive proper treatment and to prevent further complications. No studies are available describing the genetic background of Hungarian FH patients. In this work, we present the clinical and molecular data of 44 unrelated individuals with suspected FH. Sequencing of five FH-causing genes (LDLR, APOB, PCSK9, LDLRAP1 and STAP1) has been performed by next-generation sequencing (NGS). In cases where a copy number variation (CNV) has been detected by NGS, confirmation by multiplex ligation-dependent probe amplification (MLPA) has also been performed. We identified 47 causal or potentially causal (including variants of uncertain significance) LDLR and APOB variants in 44 index patients. The most common variant in the APOB gene was the c.10580G>A p.(Arg3527Gln) missense alteration, this being in accordance with literature data. Several missense variants in the LDLR gene were detected in more than one index patient. LDLR variants in the Hungarian population largely overlap with variants detected in neighboring countries.

Observer-Based Control of Tilting-Pad Thrust Bearings

The active control of hydrodynamic bearings is beginning to receive more attention in the pursuit of lower power losses and reduced maintenance. This paper presents a method by which, from simple measurements, rich information can be deduced from a running bearing that can used to modify the operating parameters of the unit. The bearing is a line-pivot, unidirectional, steadily loaded, directly lubricated tilting pad thrust bearing. This control is achieved by designing an Observer whose inputs include the output measurement(s) from the bearing. The Observer is, in some ways, an inverse model of the bearing (or Plant) that runs in parallel to the bearing and estimates the states of the bearing, such as the applied load, pivot height, minimum film thickness, maximum temperature, effective temperature and power loss. These estimated parameters can then be used in a control algorithm to modify bearing parameters such as inlet temperature or pivot location. It is demonstrated that disturbances in the load on the bearing can be detected simply by measuring a representative temperature in the bearing or changes in pivot height. Appropriate corrective action can then be employed. Whilst only steady-state operation is considered, the method could be developed to study time-varying situations.