Miracle-dz/UniFAR-FTUs huggingface dataset:
Embedded system to recognize the heat power of a fuel gas and to classificate the quality of alcohol fuel

This work presents the result obtained to develop an electronic nose to recognize the fuel gas heat power. As a first approach, synthetic data was generated for each sensor. It was considered the use of raw data and the use of a principal component analysis (PCA) to reduce the number of sensors. Two topologies of neural networks have been used, the backpropagation and learning vector quantization (LVQ). A fuzzy inference system (FIS) also has been used as a solution to this problem.
Multiple Smart Home Controlling System using Database Replication Method

The smart-house technology aims to increase home automation for personal comfort, security, and reduced energy consumption. The approach that has been done is direct control over smart home devices, this approach needs fixed IP. Unfortunately to use fixed IP need expensive cost. and in the case of multiple smart homes, it also makes multiple expensive costs. This paper purpose the method to create a smart home controlling and monitoring system with lower cost, and in the case multiple smart homes cost still not grow up. This paper purpose new approach with using database replication. The Result of this research is can make online multiple smart homes, and easy to access with HTTP and www.
Iterative channel estimation and pilot design rules for high‐mobility comb‐pilot OFDM system

With wireless communications in high‐mobility environment becoming popular, this poses a big challenge for communication systems based on the comb‐pilot OFDM, such as IEEE 802.11p, since it has not the enough pilots to estimate the time‐ and frequency‐selective channel accurately. In this paper, several comb‐pilot schemes and three comb‐pilot design rules are proposed to meet the Nyquist criterion for sampling the vehicle‐to‐vehicle (V2V) channel and the requirements of second‐order statistic of V2V channel. Based on the proposed pilot schemes, an iterative channel estimation method from the CE‐BEM model is proposed, together with three ICI cancellation methods. After thorough simulation, the effectiveness of the comb‐pilot design rules, the proposed channel estimation method, and intercarrier interference (ICI) cancellation methods is verified. Compared with other channel estimation methods, the proposed method performs better. The simulation results also reveal that the channel order L+1 has a great impact on the performance of the comb‐pilot OFDM system.
Tash: Toward Selective Reading as Hash Primitives for Gen2 RFIDs

Deployment of billions of commercial off-the-shelf (COTS) radio frequency identification (RFID) tags has drawn much of the attention of the research community because of the performance gaps of current systems. In particular, hash-enabled protocol (HEP) is one of the most thoroughly studied topics in the past decade. HEPs are designed for a wide spectrum of notable applications (e.g., missing detection) without need to collect all tags. HEPs assume that each tag contains a hash function, such that a tag can select a random but predictable time slot to reply with a one-bit presence signal that shows its existence. However, the hash function has never been implemented in COTS tags in reality, which makes HEPs a ten-year untouchable mirage. This paper designs and implements a group of analog on-tag hash primitives (called Tash) for COTS Gen2-compatible RFID systems, which moves prior HEPs forward from theory to practice. In particular, we design three types of hash primitives, namely, tash function, tash table function, and tash operator. All of these hash primitives are implemented through the selective reading, which is a fundamental and mandatory functionality specified in Gen2 protocol, without any hardware modification and fabrication—a feature allowing zero-cost fast deployment on billions of Gen2 tags. We further apply our hash primitives in one typical HEP application (i.e., missing detection) to show the feasibility and effectiveness of Tash. Results from our prototype, which is composed of one ImpinJ reader and 3000 Alien tags, demonstrate that the new design lowers 70% of the communication overhead in the air. The tash operator can additionally introduce an overhead drop of 29.7%.
Effect of Fasting Prior to Slaughter on Yield of Broilers

Abstract THE objective of broiler production is to produce edible meat at the lowest cost. Many factors are involved. Nutrition and management are both important. Rapid growth is desirable, but feed required to produce a specific weight of broiler is often a more important factor in production cost. Feed consumed is of no economic value unless it is converted into edible tissue. It is economically wasteful when birds arrive at the processing line with full digestive tracts (Brown, 1963). The birds consumed feed which they did not have time to convert into edible tissue. The full digestive tracts are more difficult to remove and breakage may result. Soiling may result in condemnation of the carcass. Carcass composition can be changed by varying the diet, but there is little evidence that yield is materially altered by different rations (Harkin et al., 1960). The yield of eviscerated carcass tends to increase with increasing…
Modeling, Analysis and Control of a Class of Elastically Joints-actuated Multibody Systems

The majority of elastic actuator mechanisms are based on the series elastic actuator (SEA) configuration. Elastic actuator has the advantage of high bandwidth mechanical compliance and can be used in force control. To increase suitability for different situations, a number of mechanisms extend the SEA allowing what is termed variable, adjustable or controllable stiffness. Adding compliance reduces the bandwidth and requires more control effort.
THE RELATIONSHIP BETWEEN INTERNATIONALIZATION AND CAPITAL STRUCTURES OF TAIWAN FIRMS

Using a sample of Taiwan firms over the period of 2001 to 2005, this study investigates the relationship between internationalization and a firmâ€™s capital structure, measured by the leverage ratio. Univariate tests show that multinational corporations (MNCs) are significantly less leveraged than domestic corporations (DCs). In addition, MNCs have lower business risks, lower exchange rate risks and higher agency costs, and are more profitable than DCs. The results of multivariate regressions show that some threshold of internationalization exists. The degree of internationalization is negatively associated with a firmâ€™s leverage ratio only before this threshold, and there will be a positive relationship beyond this threshold.
High Prevalence of Viral Infections Among Hospitalized Pneumonia Patients in Equatorial Sarawak, Malaysia

Abstract Background Although pneumonia is a known cause of morbidity and mortality in Sarawak, Malaysia, the etiology and epidemiology of pneumonia are not well described in this equatorial region. Routine clinical diagnostics for pneumonia etiology at government hospitals in Sarawak had historically involved only bacterial diagnostics. Viral diagnostics were only obtained through outside consultations. Methods From June 15, 2017 to May 14, 2018, we collected nasopharyngeal swabs from 600 patients of all ages older than 1 month hospitalized with pneumonia at Sibu and Kapit Hospitals. Specimens were examined at our collaborating institutions with a panel of molecular assays for viral pathogens including influenza A (IAV), IBV, ICV, and IDV, human adenovirus (AdV), human enterovirus (EV), human coronavirus (CoV), respiratory syncytial virus subtype A (RSV-A) or RSV-B, and parainfluenza virus (PIV) types 1–4. Results Of 599 samples examined, 288 (48%) had molecular evidence of 1 or more respiratory viruses. Overall, the most prevalent virus detected was RSV-A (14.2%) followed by AdV (10.4%) and IAV (10.4%), then RSV-B (6.2%), EV (4.2%), IBV (2.2%), PIV-3 (1.7%), CoV (1.0%), PIV-1 (1.0%), PIV-4 (0.7%), and PIV-2 (0.2%). No specimens were confirmed positive for ICV or IDV. Conclusions The high prevalence of viruses detected in this study suggest that respiratory viruses may be responsible for considerable morbidity in equatorial regions such as Sarawak. Access to viral diagnostics are very necessary for medical staff to determine appropriate pneumonia treatments.
Genetic differences among the predominant beef cattle breeds in Canada: An analysis of published results

Published information on the relative performance of beef breed crosses was used to derive single estimates of purebred breed values for the predominant beef breeds in Canada. A range of commercial traits was considered. The breed cross estimates were taken from four large breed comparison trials from 1970 to 1983, each with representative samples of the breeds from the North American population. Variances of the breed cross estimates, derived allowing for the number of sires and progeny sampled, were used in a Weighted Least Squares analysis to obtain single purebred breed effects. Birth weight, and growth rate breed values were also expressed on a 1991 base by adjusting for the estimated breed genetic trends. Important genetic differences are shown to exist between the breeds for many of the traits. Breeds with larger mature size tended to be larger and leaner at a constant age and better for maternal calving ease and maternal calf survival. In contrast, smaller breeds were superior in their direct gene.
CONFIRMATION OF DOMOIC ACID PRODUCTION BY PSEUDONITZSCHIA AUSTRALIS (BACILLARIOPHYCEAE) CULTURES 1

Single done isolates of Pseudonitzschia australis Frenguelli (= Nitzschia pseudoseriata Hasle) isolated from a toxic bloom in Monterey Bay, California produced domoic acid in culture. Although long‐term historical records do not indicate previous blooms of this species on the Pacific coast, this is probably because it has been often misidentified as Nitzschia seriata Hasle; previous evidence for toxicity is lacking. Hydrographic data suggest that areas such as Monterey Bay might be “hot spots” for domoic acid‐producing blooms.
OCCURRENCE OF A TWO GENERATION STRAIN OF THE EUROPEAN CORN BORER, OSTRINIA NUBILALIS (LEPIDOPTERA: PYRALIDAE), IN QUEBEC

Abstract There are now two strains of the European corn borer, Ostrinia nubilalis (Hübner), in Quebec. The strain normally found produces one generation while the more recently introduced strain produces two generations per year. Both strains have been characterized and compared with corn borer strains from Ontario and New York State. The two attributes of the recently introduced strain that promote the development of a second generation are (1) early emergence in the spring with less intense diapause and (2) a lower critical photoperiod for diapause induction. The latter characteristic allows pupation of first generation larvae. Field and laboratory tests on the pheromone response of adult male moths demonstrated that the origin of this recent introduction was New York State.
Evaluating counterterrorism performance: a comparative study

work is a foreword by former militant actor turned author Ahmed Rashid, as well as an appendix detailing the leadership of the IS organisation. The book is of high value to those interested in Middle Eastern affairs or terrorism studies, specifically IS. Chapter 1 shows the evolution of Abu Musab al-Zarqawi’s organisation from inception as Jama’at al-Tawhid wal-Jihad in 1999, to affiliation with al-Qaeda as Al-Qaeda in Iraq in 2004, to continued expansion as Mujahideen Shura Council and Islamic State of Iraq in 2006–2009. Key to IS’s rise and fall during this period was its anti-Sunni ideology and financial acquirements that enabled capability and radicalisation through organised leadership. Its recovery and expansion to caliphate in 2009–2014 drew upon multiple leadership models and used social media to a new level of expertise and effect. Chapter 2 expands on the history lessons learned, and provides specific, contextual examples of religious, military and political leadership, as well as the potent social media campaigning by IS. Lister’s analysis clearly shows that the organisation has consistently maintained its core aim of establishing a ‘Sunni Islamic State’ founded in Wahhabism and Sharia law. Chapter 3 provides Lister’s conclusions and commentary on tried and untried methods for combating IS. Lister is a Brookings InstitutionMiddle East expert, so the depth of analysis of this case study comes as no surprise. Of the more than half a dozen books currently on the market, this book easily stands out as one of the most accurate, unbiased and scholarly in its theses.
Practical applications of large-scale stochastic control for learning and optimization

This thesis explores a variety of techniques for large-scale stochastic control. These range from simple heuristics that are motivated by the problem structure and are amenable to analysis, to more general deep reinforcement learning (RL) which applies to broader classes of problems but is trickier to reason about. In the first part of this thesis, we explore a less known application of stochastic control in Multi-armed bandits. By assuming a Bayesian statistical model, we get enough problem structure so that we can formulate an MDP to maximize total rewards. If the objective involved total discounted rewards over an infinite horizon, then the celebrated Gittins index policy would be optimal. Unfortunately, the analysis there does not carry over to the non-discounted, finite-horizon problem. In this work, we propose a tightening sequence of ‘optimistic’ approximations to the Gittins index. We show that the use of these approximations together with the use of an increasing discount factor appears to offer a compelling alternative to state-of-theart algorithms. We prove that these optimistic indices constitute a regret optimal algorithm, in the sense of meeting the Lai-Robbins lower bound, including matching constants. The second part of the thesis focuses on the collateral management problem (CMP). In this work, we study the CMP, faced by a prime brokerage, through the lens of multi-period stochastic optimization. We find that, for a large class of CMP instances, algorithms that select collateral based on appropriately computed asset prices are near-optimal. In addition, we back-test the method on data from a prime brokerage and find substantial increases in revenue. Finally, in the third part, we propose novel deep reinforcement learning (DRL) methods for option pricing and portfolio optimization problems. Our work on option pricing enables one to compute tighter confidence bounds on the price, using the same number of Monte Carlo samples, than existing techniques. We also examine constrained portfolio optimization problems and test out policy gradient algorithms that work with somewhat different objective functions. These new objectives measure the performance of a projected version of the policy and penalize constraint violation. 3 Thesis Supervisor: Vivek F. Farias Title: Patrick J. McGovern (1959) Professor Sloan School of Management
Adaptive wavelet algorithms for elliptic PDE's on product domains

With standard isotropic approximation by (piecewise) polynomials of fixed order in a domain D subset of R-d, the convergence rate in terms of the number N of degrees of freedom is inversely proportional to the space dimension d. This so-called curse of dimensionality can be circumvented by applying sparse tensor product approximation, when certain high order mixed derivatives of the approximated function happen to be bounded in L-2. It was shown by Nitsche (2006) that this regularity constraint can be dramatically reduced by considering best N-term approximation from tensor product wavelet bases. When the function is the solution of some well-posed operator equation, dimension independent approximation rates can be practically realized in linear complexity by adaptive wavelet algorithms, assuming that the infinite stiffness matrix of the operator with respect to such a basis is highly compressible. Applying piecewise smooth wavelets, we verify this compressibility for general, non-separable elliptic PDEs in tensor domains. Applications of the general theory developed include adaptive Galerkin discretizations of multiple scale homogenization problems and of anisotropic equations which are robust, i.e., independent of the scale parameters, resp. of the size of the anisotropy.
Outlier Detection for Data Streams

Outlier detection is a well established area of study for statistical data. However, most of the existing outlier detection techniques are designed targeting the regular data model, where the entire dataset is available for random access. Typical outlier detection techniques construct a standard data distribution or model from the entire dataset and execute their detection algorithms over each data point. Evidently these techniques are not suitable for online data streams where the entire dataset, due to its unbounded volume, is not available for random access. Moreover, the data distribution in data streams change over time which challenges the existing outlier detection techniques that assume a constant standard data distribution for the entire dataset. In addition, data streams are characterized by uncertainty which imposes further complexity. In this work we propose two outlier detection techniques, called Distance Based Outline Detection for Data Streams (DB-ODDS) and Automatic Outlier Detection for Data Streams (A-ODDS). Both techniques are based on a novel continuously adaptive data distribution function that addresses all the issues of data streams.
The Costs of Mycotoxin Management to the USA: Management of Aflatoxins in the United States

Mycotoxin losses and costs of mycotoxin management are overlapping areas of concern. Costs of mycotoxin management include research production practices, testing and research necessary to try to prevent the toxins from appearing in food and feed products of affected commodities. Mycotoxin losses result from (American Association of Veterinary Laboratory Diagnosticians (AAVLD), ) lowered animal production and any human toxicity attributable to the presence of the toxin, (CAST (Council for Agricultural Science and Technology), ) the presence of the toxin in the affected commodity which lowers its market value, as well as (Hawk, ) secondary effects on agriculture production and agricultural communities.
Studies on Rye Starch Properties and Modification. Part II: Swelling and Solubility Behaviour of Rye Starch Granules

Rye starch shows the typical inhibited swelling behaviour of triticeae starches with an onset of swelling at rather low temperature (50–55°C). Swollen rye starch granules exist as individuals even after swelling at 100°C. The total dispersion of rye starch needs temperatures above 120°C with pressure cooking. On heating of the rye starch suspension preferentially amylose is leached. Defatting of rye starch exhibits no influence on swelling power but results in higher solubility and in increased amylose leaching. The drying procedures applied here resulted in stronger assoziation of the polymer molecules in the starch granule leading to higher swelling temperatures and a reduced solubility. Shiftings of the crystalline/ amorphous-ratio of the starch granules as caused by different drying procedures, had no influence on the results of swelling power investigation but the highest swelling enthalpy as well as Brabender viscosity were exhibited by a sample dried at room temperature. It is proved to be possible to change the swelling behaviour of rye starch to “potato starch type” by slight chemical modification like succination. Untersuchungen uber Roggenstarke-Eigenschaften und -Modifizierung. Teil 2: Quellung und Loslichkeitsverhalten von Roggenstarkekornern. Roggenstarke zeigt das typische inhibierte Quellverhalten der Triticeen-Starken mit fruhem Quellungsbeginn (50…55°C). Die gequollenen Roggenstarkekorner bleiben auch nach dem Erhitzen auf 100°C intakt. Vollstandige Dispergierung erfordert Druckkochung mit Temperaturen >120°C. Beim Erhitzen von Roggenstarkesuspensionen wird Amylose bevorzugt extrahiert. Entfettung ist ohne Einflus auf das Quellvermogen, fuhrt aber zu erhohter Loslichkeit und Amyloseauslaugung. Die hier angewandten Trockenprozesse bewirken verstarkte Assoziation der Polymermolekule im Starkekorn mit den Folgeerscheinungen hohere Quellungs Anfangstemperaturen und verminderte Loslichkeit. Verschiebungen des kristallin-amorph-Verhaltnisses in den Starkekornern durch verschiedene thermische Prozesse blieben ohne Einflus auf die Ergebnisse der Quellfahigkeitsuntersuchungen. Die Quellungsenthalpien und Brabender-Viskositaten waren dagegen bei den bei Raumtemperatur getrockneten Proben am hochsten. Es wird der Nachweis erbracht, das der Quellungstyp der Roggenstarke durch schwache chemische Modifizierung (Succinylierung) in den Kartoffelstarke-Quelltyp uberfuhrbar ist.
Boosting with Lexicographic Programming: Addressing Class Imbalance without Cost Tuning

A large amount of research effort has been dedicated to adapting boosting for imbalanced classification. However, boosting methods are yet to be satisfactorily immune to class imbalance, especially for multi-class problems. This is because most of the existing solutions for handling class imbalance rely on expensive cost set tuning for determining the proper level of compensation. We show that the assignment of weights to the component classifiers of a boosted ensemble can be thought of as a game of Tug of War between the classes in the margin space. We then demonstrate how this insight can be used to attain a good compromise between the rare and abundant classes without having to resort to cost set tuning, which has long been the norm for imbalanced classification. The solution is based on a lexicographic linear programming framework which requires two stages. Initially, class-specific component weight combinations are found so as to minimize a hinge loss individually for each of the classes. Subsequently, the final component weights are assigned so that the maximum deviation from the class-specific minimum loss values (obtained in the previous stage) is minimized. Hence, the proposal is not only restricted to two-class situations, but is also readily applicable to multi-class problems. Additionally, we also derive the dual formulation corresponding to the proposed framework. Experiments conducted on artificial and real-world imbalanced datasets as well as on challenging applications such as hyperspectral image classification and ImageNet classification establish the efficacy of the proposal.
A Review on Predictive Modeling Technique for Student Academic Performance Monitoring

Despite of providing high quality of education, demand on predicting student academic performance become more critical to improve the quality and assisting students to achieve a great performance in their studies. The lack of existing an efficiency and accurate prediction model is one of the major issues. Predictive analytics can provide institution with intuitive and better decision making. The objective of this paper is to review current research activities related to academic analytics focusing on predicting student academic performance. Various methods have been proposed by previous researchers to develop the best performance model using variety of students data, techniques, algorithms and tools. Predictive modeling used in predicting student performance are related to several learning tasks such as classification, regression and clustering. To achieve best prediction model, a lot of variables have been chosen and tested to find most influential attributes to perform prediction. Accurate performance prediction will be helpful in order to provide guidance in learning process that will benefit to students in avoiding poor scores. The predictive model furthermore can help instructor to forecast course completion including student final grade which are directly correlated to student performance success. To harvest an effective predictive model, it requires a good input data and variables, suitable predictive method as well as powerful and robust prediction model.