Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Neural Networks to Forecast Box Office Success

Predicting box office receipts of a particular movie has intrigued many researchers, domain experts and industry leaders as a challenging problem. In this paper, we report on the current status of a prediction system being built at the Institute for Research in Information Systems (IRIS) at Oklahoma State University since 1998. In our model, the forecasting problem is converted into a classification problem, that is, rather than forecasting the pinpoint estimate of box office receipts, a movie is classified into one of nine financial success categories, ranging from a “flop” to a “blockbuster. ” The prediction results of different datasets representing different time windows and different combination of predictors are presented using average percent hit rate of bingo and oneaway predictions. In the latest tests the prediction results of artificial neural networks improved to almost 50% on “bingo” and close to 90% on “one-away”.
QoE-Aware Proactive Caching of Scalable Videos Over Small Cell Networks

The explosion of mobile video traffic imposes tremendous challenges on present cellular networks. To alleviate the pressure on backhaul links and to enhance the quality of experience (QoE) of video streaming service, small cell base stations (SBS) with caching ability are introduced to assist the content delivery. In this paper, we present the first study on the optimal caching strategy of scalable video coding (SVC) streaming in small cell networks with the consideration of channel diversity and video scalability. We formulate an integer programming problem to maximize the average SVC QoE under the constraint of cache size at each SBS. By establishing connections between QoE and caching state of each video, we simplify the proactive caching of SVC as a multiple-choice knapsack problem (MCKP), and propose a low-complexity algorithm using dynamic programming. Our proactive caching strategy reveals the structural properties of cache allocation to each video based on their popularity profiles. Simulation results manifest that the SBSs with caching ability can greatly improve the average QoE of SVC streaming service, and that our proposed caching strategy acquires significant performance gain compared with other conventional caching policies.
Prognostics and Health Management of Bearings Based on Logarithmic Linear Recursive Least-Squares and Recursive Maximum Likelihood Estimation

Prognostics and health management allows us to predict the remaining useful life (RUL) of machinery, which is important in reducing maintenance costs and downtime, and even preventing casualties. Bearing faults account for a large proportion of machine faults. To predict the RUL of bearings, health indicators that represent the degeneration state are extracted based on the Hilbert–Huang transform and selected according to Spearman's coefficient. A model-based particle filter method is then used to track the degradation state. The unknown parameters in the nonlinear system are updated by a new method of logarithmic linear recursive least squares. A recursive maximum likelihood estimation algorithm is introduced to learn the noise in the system, and an innovative parameter fusion technique based on normalized partial derivative weights is used. Finally, the RUL of the bearings is predicted. The proposed method is validated using data from the test platform PRONOSTIA.
Identification of target candidate in Polycystic ovarian syndrome and invitro evaluation of therapeutic activity of the designed RNA Aptamer

Prevalence of poly cystic ovary syndrome has been gradually increasing among adult females and Laparoscopy drilling on the ovary is only available temporary solution with high incidence of reoccurrence. Confidential gene disease association studies combined with various graph theory analysis on the biological protein interaction network of this syndrome has resulted, the 15 genes are overexpressed as central nodes among 434 proteins of disease specific proteome network. Through the Intensive Structural and functional prioritization analysis we have identified S100A8, calprotectin is the ideal drug target protein. In this research, we have constructed RNA library of consensus DNA sequence of Glucocorticoid Response Element (GRE) and screened the best RNA Aptamer fragment which competitively binds with minimal energy to inhibit the cell migration activity of S100A8. In order to prove this computational research, Lipofectamine mediated RNA aptamer delivered and Wound scrap assay in cell lines confirms that the synthesized 18mer oligo has significant molecular level inhibition activity toward cyst formation and spreading in poly cystic condition in ovary.
Smart Garbage Segregation System Using IoT

--In last 5 years Indian Prime Minister has put a lot effort on ‘Smart City’ and ‘Swacch Bharat Mission’ as per his vision India should be considered as a clean nation in world by 2nd October 2022 which is 150th birth anniversary of Father of Nation. A lot of work has done for public awareness to clean their surroundings and put the garbage into dustbins. We have also seen a problem that wet and dry garbage is thrown in same dustbin which is little bit harder to separate afterwards. So, we have tried to overcome this problem by using a well-known concept in Computer Science called IOT. In this System we will use a microcontroller based on Arduino platform which will control all the sensors. In this system we are using Ultrasonic Sensor, Humidity Sensor, GSM module, Servo Motor. The Humidity Sensor will measure the respective humidity in the garbage if it is greater than specific value than the Arduino board will be programmed in such a way that it will trigger the motor which is fitted in wet portion of dustbin, it will open the door of wet portion otherwise the dry portion of dustbin will be opened. The ultrasonic sensor will measure that how much garbage is in the dustbin. If the dustbin will be filled more than threshold value then Arduino board will trigger GSM module to send message that specific part is filled (wet or dry). Using this system we will be able to overcome the problem of separation of dry and wet garbage.
Image decomposition using deconvolution

We present a novel method for decomposing an image into base and texture layers. Our method is simple and effective, and can handle textures of high contrast, which traditional image filtering techniques may not handle efficiently. The method first removes high-frequency texture information using low-pass filtering, and then restores structural information of the image using a deconvolution operation. Experimental results demonstrate the effectiveness of our method.
Identifying User Goals from Web Search Results

With the fast growth of the Web, users often suffer from the problem of information overload since many existing search engines response lots of non-relevant documents containing query terms based on the search mechanism of keyword matching. In fact, it is eagerly expected by both users and search engine developers to reduce overloaded information by understanding user goals clearly. In this paper, we intend to utilize Web search results to identify user goals. We propose one novel probabilistic inference model which effectively employs syntactic features to discover a variety of confined user goals
Dynamic Resource Optimization for Decentralized Signal Estimation in Energy Harvesting Wireless Sensor Networks

We study decentralized estimation of time-varying signals at a fusion center (FC), when energy harvesting sensors transmit sampled data over rate-constrained links. We propose a dynamic strategy based on stochastic optimization for selecting radio parameters, sampling set, and harvested energy at each node, with the aim of estimating a time-varying signal with guaranteed performance while ensuring stability of the batteries around a prescribed operating level. Numerical results validate the proposed approach for dynamic signal estimation under communication and energy constraints.
Learning of Bounded Active Classifiers

Since resources for data acquisition are seldom infinite, the need exists for learners and classifiers that act intelligently under hard budgets. In this paper, we consider problems in which feature values are unknown to the learner and classifier, but can be acquired at a cost. The goal is a learner that spends its learning budget bL acquiring training data so as to produce the most accurate active classifier that spends at most bC per instance. From the learner’s perspective, purchasing every feature of every instance is sure to approach the underlying distribution asymptotically, but will this yield the best distribution when only bL dollars worth of data can be collected? In this work, we show empirically that the answer is no (especially for small bL) and present alternate learning strategies that achieve superior performance on a variety of realworld datasets.
A Population-Based Prescription Study of Asthma Drugs during Pregnancy: Changing the Intensity of Asthma Therapy and Perinatal Outcomes

Background: Among the goals of gestational asthma, therapy is optimisation of pulmonary function. According to the US Food and Drug Administration, no asthma drugs can be considered ‘safe’ during pregnancy. Fear of adverse fetal effects may thus lead to restrictive use of asthma drugs during pregnancy, and no population-based studies concerning gestational asthma therapy exist. Objectives: To examine whether asthma drugs or changing intensity of asthma therapy during pregnancy was associated with deviations from expected values of gestational age, birth weight, length at birth, or malformations. Methods: The Birth Registry was used to identify all 15,756 primiparous women who gave birth in the County of North Jutland between 1991 and 1996. According to the North Jutland Prescription Database, 303 of these women received prescriptions for asthma drugs during pregnancy. Women who did not purchase any prescription drugs during pregnancy constituted the reference group. Conclusion: Women who received prescriptions for asthma drugs during pregnancy gave birth to infants with birth weight and length at birth within the expected limits. Reducing intensity of asthma treatment during pregnancy was associated with lower birth weight and length at birth. This may indicate that pregnant women chose to discontinue therapy although their disease severity justifies continuation of treatment. However, analyses did not take into account important clinical variables, and results could also be due to confounding factors or chance.
Low-Profile and Low-Dispersion Artificial Impedance Surface in the UHF Band Based on Non-Foster Circuit Loading

Conventional artificial impedance surfaces are too thick for practical use at ultrahigh frequencies (UHFs). Thin structures with passive capacitive loading are possible in the UHF band, but only with narrow bandwidth. This paper presents a non-Foster loaded artificial impedance surface to achieve lowprofile and wide bandwidth simultaneously in the UHF band. The high resonant frequency associated with a thin structure is reduced by the synthesized non-Foster-type impedance load. For a demonstration, we designed a 5-mm-thick actively loaded surface for obtaining a high-impedance condition supporting slow transverse magnetic (TM) surface waves with a propagation index of 1.5, which corresponds to a 420jΩ impedance surface. The non-Foster impedance is synthesized to be equivalent to -2.8 pF || -3.6 nH. Both the non-Foster impedance and the surface are fabricated and tested with a near-field measurement. The retrieved refractive index shows a constant TM propagation index of 1.5 over a bandwidth of 450-800 MHz, a 56% fractional bandwidth. By varying the biasing voltage of the non-Foster circuit, the impedance can be tuned from 250 to 420 jΩ, while maintaining low dispersion over the same bandwidth.
Utilizing software reuse experience for automated test recommendation

The development of defect tests is still a very labour intensive process that demands a high-level of domain knowledge, concentration and problem awareness from software engineers. Any technology that can reduce the manual effort involved in this process therefore has the potential to significantly reduce software development costs and time consumption. An idea for achieving this is to reuse the knowledge bound up in already existing test cases, either directly or indirectly, to assist in the development of tests for new software components and systems. Although general software reuse has received a lot of attention in the past - both in academia and industry - previous research has focussed on the reuse and recommendation of existing software artifacts in the creation of new product code rather than on the recommendation of tests. In this paper we focus on the latter, and present a novel automated test recommendation approach that leverages lessons learned from traditional software reuse to proactively make test case suggestions while an engineer is developing tests. In contrast, most existing testing-assistance tools provide ex post assistance to test developers in the form of coverage assessments and test quality evaluations. Our goal is to create an automated, non-intrusive recommendation system for efficient software test development. In this paper we set out the basic strategy by which this can be achieved and present a prototypical implementation of our test recommender system for Eclipse.
Passive integration and RF MEMS: a toolkit for adaptive LC circuits

RF MEMS variable capacitors have been realized in an industrialized thin-film process for manufacturing high-quality inductors and capacitors on high-ohmic silicon. The fixed as well as the moveable electrode consists of aluminium, the native aluminium oxide is used as a dielectric. A tuning ratio of 1.35 and a switching ratio up to 29 have been measured. At RF frequencies they show low ohmic losses, which make them very suitable for use in high-quality adaptive LC networks. The feasibility of the application of switched capacitors for load switching in GSM power amplifiers has been demonstrated through simulations based on experimentally derived components and systems parameters.
Clinical timelines development from textual medical reports in Italian

Patients diagnosed with chronic conditions are visited multiple times over the years. The medical reports produced during these visits often include valuable knowledge in the form of free text. To help physician access and review this knowledge, natural language processing and aggregation techniques are needed. In this work, we propose a system that extracts and summarizes information from medical reports written in Italian. For each patient, the system builds and visualizes a timeline of the extracted events. The proposed approach has the potential to enhance the process of reviewing patient clinical histories, reducing the time needed to access large amounts of data. In the future, an extension of the visualized timeline and an extrinsic evaluation will be performed.
Experimentally increased aggressiveness reduces population kin structure and subsequent recruitment in red grouse Lagopus lagopus scoticus

Summary 1. According to the ‘territorial behaviour’ hypothesis, red grouse population cycles are caused by delayed density-dependent changes in male aggressiveness influencing recruitment. These lagged changes in aggressiveness might be caused by changes in the kin structuring of male populations and differential aggressive behaviour between kin and non-kin (‘kinship’ hypothesis). 2. A population-level manipulation of male aggressiveness in autumn affected the kin structure of male populations, their subsequent aggressiveness, and recruitment of both sexes. On two moors, we implanted the old territorial cocks in autumn with testosterone on an experimental area (T-areas) and with sham implants on a control area (C-areas). 3. Increased aggressiveness in autumn t reduced recruitment in autumns t and t + 1, and breeding density of both sexes in springs t + 1 and t + 2, confirming previous studies elsewhere. A new observation was that cocks on T-areas had bigger combs (an ornament whose size is testosterone-dependent) than those on C-areas for at least 1·5 years after treatment, evidence that they remained more aggressive. 4. Increased aggressiveness reduced not only subsequent density but also kin structuring among territorial cocks. This is consistent with the ‘kinship’ hypothesis that changes in the kin structure of male populations mediate year-to-year changes in male aggressiveness. 5. Increased aggressiveness did not increase intensity of infection by the dominant intestinal nematode Trichostrongylus tenuis , which might have affected recruitment through reduced breeding success. Moreover, breeding success after treatment was no lower on the T- than on the C-areas. 6. The results show for the first time that increased aggressiveness affects both kin structure and subsequent recruitment, supporting a key assumption of the kinship hypothesis for red grouse population cycles.
Effects of architectural and technological advances on the HP/Convex Exemplar's memory and communication performance

Advances in microarchitecture, packaging, and manufacturing processes enable designers to build new systems with higher performance and scalability. Using microbenchmark techniques, we contrast the memory and communication performance of two generations of the HP/Convex Exemplar scalable parallel processing system. The SPP1000 and SPP2000 have significant architectural and implementation differences, but maintain upward binary compatibility. The SPP2000 employs manufacturing and packaging advances to obtain shorter system interconnects with wider data paths and improved functionality thereby reducing the latency and increasing the bandwidth of remote communication. Although the memory latency is not significantly improved, newer out-of-order execution processors coupled with nonblocking caches achieve much higher memory bandwidth. The SPP2000 has a richer system interconnect topology that allows scalability to a larger number of processors. The SPP2000 also employs innovations in its coherence protocols to improve synchronization and communication performance. This paper characterizes the performance effects of these changes, and identifies some remaining inefficiencies, in the cache coherence protocol and the node configuration, that future systems should address.
Robust and Blind Watermarking of Relational Database Systems

Problem statement: Digital multimedia watermarking technology was suggested in the last decade to embed copyright information in digital objects such images, audio and video. However, the increasing use of relational database systems in many real-life applications created an ever increasing need for watermarking database systems. As a result, watermarking relational database systems is now merging as a research area that deals with the legal issue of copyright protection of database systems. Approach: In this study, we proposed an efficient database watermarking algorithm based on inserting binary image watermarks in non-numeric mutli-word attributes of selected database tuples. Results: The algorithm is robust as it resists attempts to remove or degrade the embedded watermark and it is blind as it does not require the original database in order to extract the embedded watermark. Conclusion: Experimental results demonstrated blindness and the robustness of the algorithm against common database attacks.
Roads to the development of improved pertussis vaccines paved by immunology

Current acellular pertussis vaccines have various shortcomings, which may contribute to their suboptimal efficacy and waning immunity in vaccinated populations. This calls for the development of new pertussis vaccines capable of inducing long-lived protective immunity. Immunization with whole cell pertussis vaccines and natural infection with Bordetella pertussis induce distinct and more protective immune responses when compared with immunization with acellular pertussis vaccines. Therefore, the immune responses induced with whole cell vaccine or after infection can be used as a benchmark for the development of third-generation vaccines against pertussis. Here, we review the literature on the immunology of B. pertussis infection and vaccination and discuss the lessons learned that will help in the design of improved pertussis vaccines.
Production of lexical tones by Southern Min-Mandarin bilinguals

This is a preliminary study examining the tonal production of L1 Taiwanese Southern Min (TSM) speakers who are also fluent in Mandarin. Both languages have tone sandhi rules in which certain lexical tones are neutralized in non-XP-final positions. Disyllabic Mandarin and TSM words with different tonal combinations in frame sentences were examined. The results suggest that Mandarin Tone 1, Tone 3 and Tone 4 were assimilated to TSM high level, low falling and high falling tones respectively due to their surface phonetic similarity. L1 TSM speakers can apply Mandarin Tone 3 sandhi without difficulties, but the L1 sandhi rule has affected the production of Mandarin Tone 2. Mandarin Tone 2 (rising tone) was mapped to TSM rising tone (Tone 5) in phrase-final position, but not elsewhere due to the phonological constraints operated through tone sandhi. Mandarin Tone 2 at a non-XP-final position was produced with pitch contours in-between TSM rising and mid level tones, creating a “merged” category. The findings seem to indicate that aside from the phonetic properties, the L2 tones are also influenced by the L1 phonological rules such as tone sandhi in the production of non-native tones, creating context-specific tone production.
Joint queue-perturbed and weakly coupled power control for wireless backbone networks

Abstract Wireless Backbone Networks (WBNs) equipped with Multi-Radio Multi-Channel (MRMC) configurations do experience power control problems such as the inter-channel and co-channel interference, high energy consumption at multiple queues and unscalable network connectivity. Such network problems can be conveniently modelled using the theory of queue perturbation in the multiple queue systems and also as a weak coupling in a multiple channel wireless network. Consequently, this paper proposes a queue perturbation and weakly coupled based power control approach forWBNs. The ultimate objectives are to increase energy efficiency and the overall network capacity. In order to achieve this objective, a Markov chain model is first presented to describe the behaviour of the steady state probability distribution of the queue energy and buffer states. The singular perturbation parameter is approximated from the coefficients of the Taylor series expansion of the probability distribution. The impact of such queue perturbations on the transmission probability, given some transmission power values, is also analysed. Secondly, the inter-channel interference is modelled as a weakly coupled wireless system. Thirdly, Nash differential games are applied to derive optimal power control signals for each user subject to power constraints at each node. Finally, analytical models and numerical examples show the efficacy of the proposed model in solving power control problems in WBNs.
Hedge Fund Seeding Via Fees-for-Seed Swaps Under Idiosyncratic Risk

We develop a dynamic valuation model of the hedge fund seeding business by solving the consumption and portfolio-choice problem for a risk-averse manager who launches a hedge fund through a seeding vehicle. This vehicle, i.e. fees-for-seed swap, specifies that a strategic partner (seeder) provides a critical amount of capital in exchange for participation in the funds revenue. Our results indicate that the new swap not only solves the serious problem of widespread financing constraints for new and early-stage funds (ESFs) managers, but can be highly beneficial to both the manager and the seeder if structured properly.