Search results for: Annotated Facial Expression Dataset

Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

Abstract:

Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: Stacking, multi-layers, ensemble, multi-class.

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Authors: Shi Qi Koo, Ahmad Beng Hong Kueh

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In the present work, the finite element formulation for the investigation of the effects of a localized interfacial degeneration on the dynamic behavior of the [90°/0°] laminated composite plate employing the state-space technique is performed. The stiffness of the laminate is determined by assembling the stiffnesses of subelements. This includes an introduction of an interface layer adopting the virtually zero-thickness formulation to model the interfacial degeneration. Also, the kinematically consistent mass matrix and proportional damping have been formulated to complete the free vibration governing expression. To simulate the interfacial degeneration of the laminate, the degenerated areas are defined from the center propagating outwards in a localized manner. It is found that the natural frequency, damped frequency and damping ratio of the plate decreases as the degenerated area of the interface increases. On the contrary, the loss factor increases correspondingly.

Keywords: Dynamic finite element, localized interface degeneration, proportional damping, state-space modeling.

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Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

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We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: Daily activity recognition, healthcare, IoT sensors, transfer learning.

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Authors: J. Zamastil, V. Patkos

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Recent progress in calculation of the one-loop selfenergy of the electron bound in the Coulomb field is summarized. The relativistic multipole expansion is introduced. This expansion is based on a single assumption: except for the part of the time component of the electron four-momentum corresponding to the electron rest mass, the exchange of four-momentum between the virtual electron and photon can be treated perturbatively. For non Sstates and normalized difference n3
En −
E1 of the S-states this itself yields very accurate results after taking the method to the third order. For the ground state the perturbation treatment of the electron virtual states with very high three-momentum is to be avoided. For these states one can always rearrange the pertinent expression in such a way that free-particle approximation is allowed. Combination of the relativistic multipole expansion and free-particle approximation yields very accurate result after taking the method to the ninth order. These results are in very good agreement with the previous results obtained by the partial wave expansion and definitely exclude the possibility that the uncertainity in determination of the proton radius comes from the uncertainity in the calculation of the one-loop selfenergy.

Keywords: Hydrogen-like atoms, self-energy.

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Authors: Luciana C. Azevedo, Reinaldo S. Dantas, Antonio G. B. De Sá, Adalberto M. Filho, Patrícia M. Azoubel

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Fermented beverages have high expression in the market for beverages in general, is increasingly valued in situations where the characteristic aroma and flavor of the material that gave rise to them are kept after processing. This study aimed to develop a distilled beverage from passion fruit, and assess, by sensory tests and chromatographic profile, the influence of different treatments (FM1- spirit with pulp addiction and FM2 – spirit with bigger ratio of pulp in must) in the setting of volatiles in the fruit drink, and performing chemical characterization taking into account the main parameters of quality established by the legislation. The chromatograms and the first sensorial tests had indicated that sample FM1 possess better characteristics of aroma, as much of how much quantitative the qualitative point of view. However, it analyzes it sensorial end (preference test) disclosed the biggest preference of the cloth provers for sample FM2-2 (note 7.93), being the attributes of decisive color and flavor in this reply, confirmed for the observed values lowest of fixed and total acidity in the samples of treatment FM2.

Keywords: Fermented-distilled drink, fruit spirits, passion fruit.

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Authors: Sakol Udomsiri, Masahiro Iwahashi

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This paper presents comparative study on recent integer DCTs and a new method to construct a low sensitive structure of integer DCT for colored input signals. The method refers to sensitivity of multiplier coefficients to finite word length as an indicator of how word length truncation effects on quality of output signal. The sensitivity is also theoretically evaluated as a function of auto-correlation and covariance matrix of input signal. The structure of integer DCT algorithm is optimized by combination of lower sensitive lifting structure types of IRT. It is evaluated by the sensitivity of multiplier coefficients to finite word length expression in a function of covariance matrix of input signal. Effectiveness of the optimum combination of IRT in integer DCT algorithm is confirmed by quality improvement comparing with existing case. As a result, the optimum combination of IRT in each integer DCT algorithm evidently improves output signal quality and it is still compatible with the existing one.

Keywords: DCT, sensitivity, lossless, wordlength.

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Authors: Pham Ngoc Thang, Le Thai Hung, Nguyen Quang Bau

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The influence of confined acoustic phonons on the Shubnikov – de Haas magnetoresistance oscillations in a doped semiconductor superlattice (DSSL), subjected in a magnetic field, DC electric field, and a laser radiation, has been theoretically studied based on quantum kinetic equation method. The analytical expression for the magnetoresistance in a DSSL has been obtained as a function of external fields, DSSL parameters, and especially the quantum number m characterizing the effect of confined acoustic phonons. When m goes to zero, the results for bulk phonons in a DSSL could be achieved. Numerical calculations are also achieved for the GaAs:Si/GaAs:Be DSSL and compared with other studies. Results show that the Shubnikov – de Haas magnetoresistance oscillations amplitude decrease as the increasing of phonon confinement effect.

Keywords: Shubnikov–de Haas magnetoresistance oscillations, quantum kinetic equation, confined acoustic phonons, laser radiation, doped semiconductor superlattices.

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Authors: Matías Micheletto, Rodrigo Santos, Sergio F. Ochoa

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In developing countries, most roads in rural areas are dirt road. They require frequent maintenance since they are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the maintenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: Dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision.

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Authors: El Sayed A. Sharara, A. Tsuji, K. Terada

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Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

Keywords: Call center agents, fatigue, skin color detection, face recognition.

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Authors: Seyed Ali Mir Heydari, Mohsen Sayadiharikandeh

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Static analysis of source code is used for auditing web applications to detect the vulnerabilities. In this paper, we propose a new algorithm to analyze the PHP source code for detecting LFI and RFI potential vulnerabilities. In our approach, we first define some patterns for finding some functions which have potential to be abused because of unhandled user inputs. More precisely, we use regular expression as a fast and simple method to define some patterns for detection of vulnerabilities. As inclusion functions could be also used in a safe way, there could occur many false positives (FP). The first cause of these FP-s could be that the function does not use a usersupplied variable as an argument. So, we extract a list of usersupplied variables to be used for detecting vulnerable lines of code. On the other side, as vulnerability could spread among the variables like by multi-level assignment, we also try to extract the hidden usersupplied variables. We use the resulted list to decrease the false positives of our method. Finally, as there exist some ways to prevent the vulnerability of inclusion functions, we define also some patterns to detect them and decrease our false positives.

Keywords: User-supplied Variables, hidden user-supplied variables, PHP vulnerabilities.

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Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri

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Dosimetry is an indispensable and precious factor in patient treatment planning to minimize the absorbed dose in vital tissues. In this study, compartmental model was used in order to estimate the human absorbed dose of ¹⁷⁷Lu-DOTATOC from the biodistribution data in wild type rats. For this purpose, ¹⁷⁷Lu-DOTATOC was prepared under optimized conditions and its biodistribution was studied in male Syrian rats up to 168 h. Compartmental model was applied to mathematical description of the drug behaviour in tissue at different times. Dosimetric estimation of the complex was performed using radiation absorbed dose assessment resource (RADAR). The biodistribution data showed high accumulation in the adrenal and pancreas as the major expression sites for somatostatin receptor (SSTR). While kidneys as the major route of excretion receive 0.037 mSv/MBq, pancreas and adrenal also obtain 0.039 and 0.028 mSv/MBq. Due to the usage of this method, the points of accumulated activity data were enhanced, and further information of tissues uptake was collected that it will be followed by high (or improved) precision in dosimetric calculations.

Keywords: Compartmental modeling, human absorbed dose, 177Lu-DOTATOC, Syrian rats.

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Authors: Kiurski S. Jelena, Kecić S. Vesna, Aksentijević M. Snežana

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Samples of tap and wastewater were collected in three offset printing facilities in Novi Sad, Serbia. Ten physicochemical parameters were analyzed within all collected samples: pH, conductivity, m - alkalinity, p - alkalinity, acidity, carbonate concentration, hydrogen carbonate concentration, active oxygen content, chloride concentration and total alkali content. All measurements were conducted using the standard analytical and instrumental methods. Comparing the obtained results for tap water and wastewater, a clear quality difference was noticeable, since all physicochemical parameters were significantly higher within wastewater samples. The study also involves the application of simple linear regression analysis on the obtained dataset. By using software package ORIGIN 5 the pH value was mutually correlated with other physicochemical parameters. Based on the obtained values of Pearson coefficient of determination a strong positive correlation between chloride concentration and pH (r = -0.943), as well as between acidity and pH (r = -0.855) was determined. In addition, statistically significant difference was obtained only between acidity and chloride concentration with pH values, since the values of parameter F (247.634 and 182.536) were higher than F_critical (5.59). In this way, results of statistical analysis highlighted the most influential parameter of water contamination in offset printing, in the form of acidity and chloride concentration. The results showed that variable dependence could be represented by the general regression model: y = a₀ + a₁x+ k, which further resulted with matching graphic regressions.

Keywords: Pollution, printing industry, simple linear regression analysis, wastewater.

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Authors: N. Q. Bau, N. V. Nghia

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The acoustomagnetoelectric (AME) field in a rectangular quantum wire with an infinite potential (RQWIP) is calculated in the presence of an external magnetic field (EMF) by using the quantum kinetic equation for the distribution function of electrons system interacting with external phonons and electrons scattering with internal acoustic phonon in a RQWIP. We obtained ananalytic expression for the AME field in the RQWIP in the presence of the EMF. The dependence of AME field on the frequency of external acoustic wave, the temperature T of system, the cyclotron frequency of the EMF and the intensity of the EMF is obtained. Theoretical results for the AME field are numerically evaluated, plotted and discussed for a specific RQWIP GaAs/GaAsAl. This result has shown that the dependence of the AME field on intensity of the EMF is nonlinearly and it is many distinct maxima in the quantized magnetic region. We also compared received fields with those for normal bulk semiconductors, quantum well and quantum wire to show the difference. The influence of an EMF on AME field in a RQWIP is newly developed.

Keywords: Rectangular quantum wire, acoustomagnetoelectric field, electron-phonon interaction, kinetic equation method.

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Authors: Aslı Taş, Şebnem Ertaş

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Culture consists of material and spiritual values adopted by the emerging societies during the historical and social processes and continues to exist from past to present by being transferred through generations. Culture and cultural sustainability are interdependent concepts. Cultural sustainability exists when the requirements established cultural expression are added to the social life as lifestyle and habits. However, sustainability renders change inevitable. Changes that take place in the culture of a society also shows the impact in the daily life places. Functional changes occur in the spaces in order to adapt particularly to cultural change that appear in the aftermath of the user change, to modern technology and living standards. In this context, in this study, it was aimed to investigate the effect of the time-dependent functional changes that took place in the housing where non-Muslim population who was subject to population exchange and Muslim population lived after the population exchange in the vacated housing in Sille. Therefore, the changed and newly added venues in the house belonging to Ali Oğuz in Hacı Ali Ağa Street were investigated over the generated graphic in order to clearly perceive the cultural exchange on the housing and settlement and the functional changes were demonstrated.

Keywords: Culture, house, spatial changes, sustainability.

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Authors: V. Piscopo

Abstract:

In the classical buckling analysis of rectangular plates subjected to the concurrent action of shear and uniaxial forces, the Euler shear buckling stress is generally evaluated separately, so that no influence on the shear buckling coefficient, due to the in-plane tensile or compressive forces, is taken into account. In this paper the buckling problem of simply supported rectangular plates, under the combined action of shear and uniaxial forces, is discussed from the beginning, in order to obtain new project formulas for the shear buckling coefficient that take into account the presence of uniaxial forces. Furthermore, as the classical expression of the shear buckling coefficient for simply supported rectangular plates is considered only a “rough" approximation, as the exact one is defined by a system of intersecting curves, the convergence and the goodness of the classical solution are analyzed, too. Finally, as the problem of the Euler shear buckling stress evaluation is a very important topic for a variety of structures, (e.g. ship ones), two numerical applications are carried out, in order to highlight the role of the uniaxial stresses on the plating scantling procedures and the goodness of the proposed formulas.

Keywords: Buckling analysis, Shear, Uniaxial Stresses.

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Authors: Marcos Amado Petroli

Abstract:

This paper investigates civic representation in mid-century diplomatic buildings through the case of the U.S. Embassy in Karachi (1955-59), Pakistan, designed by the Austrian-American architect Richard Neutra (1892-1970) and the American architect Robert Alexander (1907-92). Texts, magazines, and oral histories at that time highlighted the need for a new postwar expression of American governmental architecture, leaning toward modernization, technology, and monumentality. Descriptive, structural, and historical analyses of the U.S. Embassy in Karachi revealed the emergence of a new prototypical solution for postwar diplomatic buildings: the combination of one main orthogonal block, seen as a modern-day corps de logis, and a flanking arcuated pavilion, often organized in one or two stories. Although the U.S. Embassy relied on highly industrialized techniques and abstract images of social progress, archival work at the Neutra’s archives at the University of California, Los Angeles, revealed that much of this project was adapted to vernacular elements and traditional forms—such as the intriguing use of reinforced concrete barrel vaults.

Keywords: Modern monumentality, post-WWII diplomatic buildings, theory of character, thin-shells.

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Authors: Aakash Subramanian, Vansh Pal Singh Makh, Abhijit Mitra

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A new digital transceiver circuit for asynchronous frame detection is proposed where both the transmitter and receiver contain all digital components, thereby avoiding possible use of conventional devices like monostable multivibrators with unstable external components such as resistances and capacitances. The proposed receiver circuit, in particular, uses a combinational logic block yielding an output which changes its state as soon as the start bit of a new frame is detected. This, in turn, helps in generating an efficient receiver sampling clock. A data latching circuit is also used in the receiver to latch the recovered data bits in any new frame. The proposed receiver structure is also extended from 4- bit information to any general n data bits within a frame with a common expression for the output of the combinational logic block. Performance of the proposed hardware design is evaluated in terms of time delay, reliability and robustness in comparison with the standard schemes using monostable multivibrators. It is observed from hardware implementation that the proposed circuit achieves almost 33 percent speed up over any conventional circuit.

Keywords: Asynchronous Communication, Digital Detector, Combinational logic output, Sampling clock generator, Hardwareimplementation.

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Authors: Xiaoshu Lu, Päivi Leino-Arjas, Kustaa Piha, Akseli Aittomäki, Peppiina Saastamoinen, Ossi Rahkonen, Eero Lahelma

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Sickness absence represents a major economic and social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model selection and a critical analysis of the temporal trends, the occurrence and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model applicability to complicated longitudinal data.

Keywords: Sickness absence, longitudinal data, methodologies, mix-distribution model.

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Authors: Youngjae Jin, Daeshik Kim

Abstract:

This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in VerilogHDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: Auto-encoder, Behavior model simulation, Digital hardware design, Pre-route simulation, Unsupervised feature learning.

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Authors: Feng Chia Hsieh, Sheng Kuo Hsieh, Tzyy Rong Jinn

Abstract:

Characterization and evaluation of the activity of Vespa basalis DPP-IV, which expressed in Spodoptera frugiperda 21 cells. The expression of rDPP-IV was confirmed by SDS–PAGE, Western blot analyses, LC-MS/MS and measurement of its peptidase specificity. One-step purification by Ni-NTA affinity chromatography and the total amount of rDPP-IV recovered was approximately 6.4mg per liter from infected culture medium; an equivalent amount would be produced by 1x109 infected Sf21 insect cells. Through the affinity purification led to highly stable rDPP-IV enzyme was recovered and with significant peptidase activity. The rDPP-IV exhibited classical Michaelis–Menten kinetics, with kcat/Km in the range of 10-500 mM-1×S-1 for the five synthetic substrates and optimum substrate is Ala-Pro-pNA. As expected in inhibition assay, the enzymatic activity of rDPP-IV was significantly reduced by 80 or 60% in the presence of sitagliptin (a DPP-IV inhibitor) or PMSF (a serine protease inhibitor), but was not apparently affected by iodoacetamide (a cysteine protease inhibitor).

Keywords: Dipeptidyl-Peptidase IV, Phenylmethylsulfonyl fluoride; Serine protease, Sitagliptin, Vespa basalis

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Authors: Md. Sohidul Islam, Mohammad Rakibul Islam

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In this paper, we consider a non-identically independently distributed (non-i.i.d.) Hoyt fading single-input multiple-out put (SIMO) channel, where the transmitter sends some confidential information to the legitimate receiver in presence of an eavesdropper. We formulated the probability of non-zero secrecy mutual information; secure outage probability and average secrecy mutual information (SMI) for the SIMO wireless communication system. The calculation has been carried out using small limit argument approximation (SLAA) on zeroth-order modified Bessel function of first kind. In our proposed model, an eavesdropper observes transmissions of information through another Hoyt fading channel. First, we derived the analytical expression for non-zero secrecy mutual information. Then, we find the secure outage probability to investigate the outage behavior of the proposed model. Finally, we find the average secrecy mutual information. We consider that the channel state information (CSI) is known to legitimate receiver.

Keywords: Hoyt fading, main channel, eavesdropper channel, secure outage probability, average secrecy mutual information.

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Authors: Jamal Abdi

Abstract:

This paper is largely a response/critique of Samuel P. Huntington´s Clash of Civilizations thesis. The overriding argument is that Huntington´s thesis is characterized by failure to distinguish between ´groups´ and ´categories´. Multinational civilizations overcoming their internal collective action problems, which would enable them to pursue a unified strategy vis-à-vis the West, is a rather foundational assumption in his theory. Without assigning sufficient intellectual attention to the processes through which multinational civilizations may gain capacity for concerted action i.e. become a group, he contended that the post-cold-war world would be shaped in large measure by interactions among seven or eight major civilizations. Thus, failure in providing a convincing analysis of multi-national civilizations´ transition from categories to groups is a significant weakness in Huntington´s clash theory. It is also suggested that so-called Islamic terrorism and the war on terror is not to be taken as an expression of presence of clash between a Western and an Islamic civilization, as terrorist organizations would be superfluous in a world characterized by clash of civilizations. Consequences of multinational civilizations becoming a group are discussed in relation to contemporary Western superiority.

Keywords: Clash of civilizations, groups, categories, groupism.

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Authors: Avdhesh K. Sharma

Abstract:

Formulation for drying and pyrolysis process in packed beds at slow heating rates is presented. Drying of biomass particles bed is described by mass diffusion equation and local moisture-vapour-equilibrium relations. In gasifiers, volatilization rate during pyrolysis of biomass is modeled by using apparent kinetic rate expression, while product compositions at slow heating rates is modeled using empirical fitted mass ratios (i.e., CO/CO₂, ME/CO₂, H₂O/CO₂) in terms of pyrolysis temperature. The drying module is validated fairly with available chemical kinetics scheme and found that the testing zone in gasifier bed constituted of relatively smaller particles having high airflow with high isothermal temperature expedite the drying process. Further, volatile releases more quickly within the shorter zone height at high temperatures (isothermal). Both, moisture loss and volatile release profiles are found to be sensitive to temperature, although the influence of initial moisture content on volatile release profile is not so sensitive.

Keywords: Modeling downdraft gasifier, drying, pyrolysis, moist woody biomass.

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

Abstract:

Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: Time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition.

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: Consensus, curse of correlation, imbalanced classification, rank-based chain-mode ensemble.

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Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton

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Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Keywords: Cold-start, expectation propagation, multi-armed bandits, Thompson sampling, variational inference.

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Authors: Petter Eklund, Jonathan Sjölund, Sandra Eriksson, Mats Leijon

Abstract:

The spoke type rotor can be used to obtain magnetic flux concentration in permanent magnet machines. This allows the air gap magnetic flux density to exceed the remanent flux density of the permanent magnets but gives problems with leakage fluxes in the magnetic circuit. The end leakage flux of one spoke type permanent magnet rotor design is studied through measurements and finite element simulations. The measurements are performed in the end regions of a 12 kW prototype generator for a vertical axis wind turbine. The simulations are made using three dimensional finite elements to calculate the magnetic field distribution in the end regions of the machine. Also two dimensional finite element simulations are performed and the impact of the two dimensional approximation is studied. It is found that the magnetic leakage flux in the end regions of the machine is equal to about 20% of the flux in the permanent magnets. The overestimation of the performance by the two dimensional approximation is quantified and a curve-fitted expression for its behavior is suggested.

Keywords: End effects, end leakage flux, permanent magnet machine, spoke type rotor.

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Authors: Mohd Hasmadi Ismail, Kamaruzaman Jusoff

Abstract:

In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

Keywords: Image Classification, Reference Data, Accuracy Assessment, Kappa Statistic, Forest Land Cover

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

Abstract:

Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars, and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: Remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction.

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

Abstract:

In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: Augmented reality framework, server-client model, vision-based tracking, image search.

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