Search results for: Secure Real Time Protocol

Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behavior data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: Personalized recommendation, generative user modeling, user intention identification, large language models, chain-of-thought prompting.

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Authors: A. Shayeghi, H. Shayeghi, H. Eimani Kalasar

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In recent years, tuned mass damper (TMD) control systems for civil engineering structures have attracted considerable attention. This paper emphasizes on the application of particle swarm application (PSO) to design and optimize the parameters of the TMD control scheme for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using the PSO technique which has a story ability to find the most optimistic results. An 11- story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed method. The results analysis through the time-domain simulation and some performance indices reveals that the designed PSO based TMD controller has an excellent capability in reduction of the seismically excited example building.

Keywords: TMD, Particle Swarm Optimization, Tall Buildings, Structural Dynamics.

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Authors: Svetlana T. Djambova, Natalia B. Ivanova, Roumiana A. Zaharieva

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Small size acoustic chamber test method has been applied to experimentally evaluate and compare the airborne sound insulation provided by plasterboard sandwich panels filled with mineral wool and with its alternative from recycled textile material (produced by two different technologies). An original small-size acoustic chamber is used as a sound source room. It has been specially built in a real-size room, which is utilized as a sound receiving room. The experimental results of one of the recycled textile material specimens have demonstrated sound insulation properties similar to those of the mineral wool specimen and even superior in the 1600-3150 Hz frequency range. This study contributes to the improvement of recycled textile material production, as well as to the synergy of heat insulation and sound insulation performances of building materials.

Keywords: Airborne sound insulation, heat insulation products, mineral wool, recycled textile material.

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Authors: Kahil Amar, Meziani Faroudja, Khelil Nacim

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The principal objective of this study is the evaluation of the seismic performance of reinforced concrete frame structures, taking into account of the behavior laws, reflecting the real behavior of materials, using CASTEM2000 software. A finite element model used is based in modified Takeda model with Timoshenko elements for columns and beams. This model is validated on a Vecchio experimental reinforced concrete (RC) frame model. Then, a study focused on the behavior of a RC frame with three-level and three-story in order to visualize the positioning the plastic hinge (plastic rotation), determined from the curvature distribution along the elements. The results obtained show that the beams of the 1^st and 2^nd level developed a very large plastic rotations, or these rotations exceed the values corresponding to CP (Collapse prevention with cp q_CP = 0.02 rad), against those developed at the 3^rd level, are between IO and LS (Immediate occupancy and life Safety with q_IO = 0.005 rad and rad q_LS = 0.01 respectively), so the beams of first and second levels submit a very significant damage.

Keywords: Seismic performance, performance level, pushover analysis, plastic rotation, plastic hinge.

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Authors: Moustafa Osman Mohammed

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This paper introduces Luhmann’s autopoietic social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. A specific type of autopoietic system is explained in the three existing groups of the ecological phenomena: interaction, social and medical sciences. This hypothesis model, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for the exchange of photon energy with molecular without any changes in topology. The external forces in the systems environment might be concomitant with the natural fluctuations’ influence (e.g. radioactive radiation, electromagnetic waves). The cantilever sensor deploys insights to the future chip processor for prevention of social metabolic systems. Thus, the circuits with resonant electric and optical properties are prototyped on board as an intra–chip inter–chip transmission for producing electromagnetic energy approximately ranges from 1.7 mA at 3.3 V to service the detection in locomotion with the least significant power losses. Nowadays, therapeutic systems are assimilated materials from embryonic stem cells to aggregate multiple functions of the vessels nature de-cellular structure for replenishment. While, the interior actuators deploy base-pair complementarity of nucleotides for the symmetric arrangement in particular bacterial nanonetworks of the sequence cycle creating double-stranded DNA strings. The DNA strands must be sequenced, assembled, and decoded in order to reconstruct the original source reliably. The design of exterior actuators have the ability in sensing different variations in the corresponding patterns regarding beat-to-beat heart rate variability (HRV) for spatial autocorrelation of molecular communication, which consists of human electromagnetic, piezoelectric, electrostatic and electrothermal energy to monitor and transfer the dynamic changes of all the cantilevers simultaneously in real-time workspace with high precision. A prototype-enabled dynamic energy sensor has been investigated in the laboratory for inclusion of nanoscale devices in the architecture with a fuzzy logic control for detection of thermal and electrostatic changes with optoelectronic devices to interpret uncertainty associated with signal interference. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other and forms its unique spatial structure modules for providing the environment mutual contribution in the investigation of mass temperature changes due to pathogenic archival architecture of clusters.

Keywords: Autopoiesis, quantum photonics, portable energy, photonic structure, photodynamic therapeutic system.

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Authors: Seyed Hossein Iranmanesh, Mansoureh Zarezadeh

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This paper presents an application of Artificial Neural Network (ANN) to forecast actual cost of a project based on the earned value management system (EVMS). For this purpose, some projects randomly selected based on the standard data set , and it is produced necessary progress data such as actual cost ,actual percent complete , baseline cost and percent complete for five periods of project. Then an ANN with five inputs and five outputs and one hidden layer is trained to produce forecasted actual costs. The comparison between real and forecasted data show better performance based on the Mean Absolute Percentage Error (MAPE) criterion. This approach could be applicable to better forecasting the project cost and result in decreasing the risk of project cost overrun, and therefore it is beneficial for planning preventive actions.

Keywords: Earned Value Management System (EVMS), Artificial Neural Network (ANN), Estimate At Completion, Forecasting Methods, Project Performance Measurement.

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Authors: Ahmed Mudhafar Hashim, Aseel Mahmood Abdullah

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The present work introduced a green composite consisting of corn natural fiber of constant concentration of 10% by weight incorporation with poly methyl methacrylate matrix biomaterial prepared by hand lay-up technique. Corn natural fibers were treated with two concentrations of sodium hydroxide solution (3% and 5%) with different immersed time (1.5 and 3 hours) at room temperature. The fracture toughness test of untreated and alkali treated corn fiber composites were performed. The effect of chemically treated on fracture properties of composites has been analyzed using Fourier transform infrared (FTIR) spectroscopy. The experimental results showed that the alkali treatment improved the fracture properties in terms of plane strain fracture toughness KIC. It was found that the plane strain fracture toughness KIC increased by up to 62% compared to untreated fiber composites. On the other hand, increases in both concentrations of alkali solution and time of soaking to 5% NaOH and 3 hours, respectively reduced the values of KIC lower than the value of the unfilled material.

Keywords: green composites, fracture toughness, corn natural fiber, Bio-PMMA

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Authors: A. Buasri, N. Chaiyut, V. Loryuenyong, E. Phakdeepataraphan, S. Watpathomsub, V. Kunakemakorn

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In this research, the optimum conditions for the synthesis of activated carbon from biodiesel wastes such as palm shells (PS) and Jatropha curcas fruit shells (JS) by chemical activation method using potassium hydroxide (KOH) as an activating agent under nitrogen atmosphere were investigated. The effects of soaking in hydrofluoric acid (HF), impregnation ratio, activation temperature and activation time on adsorption capacity of methylene blue (MB) and iodine (I2) solution were examined. The results showed that HF-treated activated carbons exhibited higher adsorption capacities by eliminating ash residues, which might fill up the pores. In addition, the adsorption capacities of methylene blue and iodine solution were also significantly influenced by the types of raw materials, the activation temperature and the activation time. The highest adsorption capacity of methylene blue 257.07mg/g and iodine 847.58mg/g were obtained from Jatropha curcas wastes.

Keywords: Activated Carbon, Palm Shells (PS), Jatropha Curcas Fruit Shells (JS), Agricultural Wastes, Biodiesel Wastes, Optimum Conditions.

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Authors: Kevin. S. Badni

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Due to the rapid advances in the use of information technology and students’ familiarity with technology, learning styles in higher education are being reshaped. One of the technology developments that has gained considerable attention in recent years is Augmented Reality (AR), where technology is used to combine overlays of digital data on physical real-world settings. While AR is being heavily promoted for entertainment by mobile phone manufacturers, it has had little adoption in higher education due to the required upfront investment that an instructor needs to undertake in creating relevant AR applications. This paper discusses a case study that uses a low upfront development approach and examines the impact on generation-Z students’ motivation whilst studying design history over a four-semester period. Even though the upfront investment in creating the AR support was minimal, the results showed a noticeable increase in student motivation. The approach used in this paper can be easily transferred to other disciplines and other areas of design education.

Keywords: Augmented reality, history, motivation, technology.

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Authors: H. Afer, N. Rouag, R. Penelle

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In the Fe-3%Si sheets, grade Hi-B, with AlN and MnS as inhibitors, the Goss grains which abnormally grow do not have a size greater than the average size of the primary matrix. In this heterogeneous microstructure, the size factor is not a required condition for the secondary recrystallization. The onset of the small Goss grain abnormal growth appears to be related to a particular behavior of their grain boundaries, to the local texture and to the distribution of the inhibitors. The presence and the evolution of oriented clusters ensure to the small Goss grains a favorable neighborhood to grow. The modified Monte-Carlo approach, which is applied, considers the local environment of each grain. The grain growth is dependent of its real spatial position; the matrix heterogeneity is then taken into account. The grain growth conditions are considered in the global matrix and in different matrixes corresponding to A component clusters. The grain growth behaviour is considered with introduction of energy only, energy and mobility, energy and mobility and precipitates.

Keywords: Abnormal grain growth, grain boundary energy andmobility, neighbourhood, oriented clusters.

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Authors: Hani Shafeek, Mohammed Aman, Muhammad Marsudi

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Applied industrial engineering is concerned with imparting employable skills to improve the productivity for current situation of products and services. The purpose of this case study is to present the results of an initial research study conducted to identify the desired professional characteristics of an industrial engineer with an undergraduate degree and the emerging topic areas that should be incorporated into the curriculum to prepare industrial engineering (IE) graduates for the future workforce. Conclusions and recommendations for applied industrial engineering syllabus have been gathered and reported below. A two-pronged approach was taken which included a method of benchmarking by comparing the applied industrial engineering curricula of various universities and an industry survey to identify job market requirements. This methodology produced an analysis of the changing nature of industrial engineering from learning to practical education. A curriculum study for engineering is a relatively unexplored area of research in the Middle East, much less for applied industrial engineering. This work is an effort to bridge the gap between theoretical study in the classroom and the real world work applications in the industrial and service sectors.

Keywords: Applied industrial engineering, Faculty of Engineering, Industrial Engineering Curriculum, Syllabus.

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Authors: Manas Ranjan Kabat, Manoj Kumar Patel, Chita Ranjan Tripathy

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Many multimedia communication applications require a source to transmit messages to multiple destinations subject to quality of service (QoS) delay constraint. To support delay constrained multicast communications, computer networks need to guarantee an upper bound end-to-end delay from the source node to each of the destination nodes. This is known as multicast delay problem. On the other hand, if the same message fails to arrive at each destination node at the same time, there may arise inconsistency and unfairness problem among users. This is related to multicast delayvariation problem. The problem to find a minimum cost multicast tree with delay and delay-variation constraints has been proven to be NP-Complete. In this paper, we propose an efficient heuristic algorithm, namely, Economic Delay and Delay-Variation Bounded Multicast (EDVBM) algorithm, based on a novel heuristic function, to construct an economic delay and delay-variation bounded multicast tree. A noteworthy feature of this algorithm is that it has very high probability of finding the optimal solution in polynomial time with low computational complexity.

Keywords: EDVBM, Heuristic algorithm, Multicast tree, QoS routing, Shortest path.

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Authors: Abdelhakam A. Noreldien, Sakhr B. Abudarag, Muslim S. Eltoum, Salih O. Osman

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This paper presents an analytical study of Small Unmanned Aerial Vehicle (SUAV) dynamic stability derivatives. Simulating SUAV dynamics and analyzing its behavior at the earliest design stages is too important and more efficient design aspect. The approach suggested in this paper is using the wind tunnel experiment to collect the aerodynamic data and get the dynamic stability derivatives. AutoCAD Software was used to draw the case study (wildlife surveillance SUAV). The SUAV is scaled down to be 0.25% of the real SUAV dimensions and converted to a wind tunnel model. The model was tested in three different speeds for three different attitudes which are; pitch, roll and yaw. The wind tunnel results were then used to determine the case study stability derivative values, and hence it used to calculate the roots of the characteristic equation for both longitudinal and lateral motions. Finally, the characteristic equation roots were found and discussed in all possible cases.

Keywords: Model, simulating, SUAV, wind tunnel.

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Authors: A. Özköse, A. Tamkoç

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The present study involved analysis of certain characteristics of the perennial ryegrass (Lolium perenne L.) genotypes collected from the natural flora of Ankara, and explores a correlation among them. In order to evaluate the plants for breeding purpose as per Turkey's environmental conditions, the perennial ryegrass plants were collected from natural pasture of Ankara in 2004 and were utilized for the study. Seeds of the collected plants were sown in pots and seedlings were prepared in a greenhouse. In 2005, the seedlings were transplanted at 50 × 50 cm2 intervals in Randomized Complete Blocks Design in an experimental field. In 2007 and 2008, data were recorded from the observations and measurements of 568 perennial ryegrasses. The plant characteristics, which were investigated, included re-growth time in spring, color, density, growth habit, tendency to form inflorescence, time of inflorescence, plant height, length of upper internode, spike length, leaf length, leaf width, leaf area, leaf shape, number of spikelets per spike, seed yield per spike and 1000 grain weight and the correlation analyses were made using this data. Correlation coefficients were estimated between all paired combinations of the studied traits. The yield components exhibited varying trends of association among themselves. Seed yield per spike showed significant and positive association with the number of spikelets per spike, 1000 grain weight, plant height, length of upper internode, spike length, leaf length, leaf width, leaf area and color, but significant and negative association with the growth habit and re-growth time in spring.

Keywords: Correlation, morphological traits, Lolium perenne.

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Authors: M. M. Qasaymeh, M. A. Khodeir

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Subspace channel estimation methods have been studied widely, where the subspace of the covariance matrix is decomposed to separate the signal subspace from noise subspace. The decomposition is normally done by using either the eigenvalue decomposition (EVD) or the singular value decomposition (SVD) of the auto-correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. This paper considers the estimation of the multipath slow frequency hopping (FH) channel using noise space based method. In particular, an efficient method is proposed to estimate the multipath time delays by applying multiple signal classification (MUSIC) algorithm which is based on the null space extracted by the rank revealing LU (RRLU) factorization. As a result, precise information is provided by the RRLU about the numerical null space and the rank, (i.e., important tool in linear algebra). The simulation results demonstrate the effectiveness of the proposed novel method by approximately decreasing the computational complexity to the half as compared with RRQR methods keeping the same performance.

Keywords: Time Delay Estimation, RRLU, RRQR, MUSIC, LS-ESPRIT, LS-ESPRIT, Frequency Hopping.

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Authors: Serkan Ozbay, Ergun Ercelebi

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Automatic Vehicle Identification (AVI) has many applications in traffic systems (highway electronic toll collection, red light violation enforcement, border and customs checkpoints, etc.). License Plate Recognition is an effective form of AVI systems. In this study, a smart and simple algorithm is presented for vehicle-s license plate recognition system. The proposed algorithm consists of three major parts: Extraction of plate region, segmentation of characters and recognition of plate characters. For extracting the plate region, edge detection algorithms and smearing algorithms are used. In segmentation part, smearing algorithms, filtering and some morphological algorithms are used. And finally statistical based template matching is used for recognition of plate characters. The performance of the proposed algorithm has been tested on real images. Based on the experimental results, we noted that our algorithm shows superior performance in car license plate recognition.

Keywords: Character recognizer, license plate recognition, plate region extraction, segmentation, smearing, template matching.

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Authors: Hidehiko Okada

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Evolution strategy (ES) is a well-known instance of evolutionary algorithms, and there have been many studies on ES. In this paper, the author proposes an extended ES for solving fuzzy-valued optimization problems. In the proposed ES, genotype values are not real numbers but fuzzy numbers. Evolutionary processes in the ES are extended so that it can handle genotype instances with fuzzy numbers. In this study, the proposed method is experimentally applied to the evolution of neural networks with fuzzy weights and biases. Results reveal that fuzzy neural networks evolved using the proposed ES with fuzzy genotype values can model hidden target fuzzy functions even though no training data are explicitly provided. Next, the proposed method is evaluated in terms of variations in specifying fuzzy numbers as genotype values. One of the mostly adopted fuzzy numbers is a symmetric triangular one that can be specified by its lower and upper bounds (LU) or its center and width (CW). Experimental results revealed that the LU model contributed better to the fuzzy ES than the CW model, which indicates that the LU model should be adopted in future applications of the proposed method.

Keywords: Evolutionary algorithm, evolution strategy, fuzzy number, feedforward neural network, neuroevolution.

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Authors: Branislav V. Šojić, Ljiljana S. Petrović, Vladimir M. Tomović, Natalija R. Džinić, Anamarija I. Mandić, Snežana B. Škaljac, Marija R. Jokanović, Predrag M. Ikonić, Tatjana A. Tasić, Ivana J. Sedej

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The influence of ripening conditions (traditional and industrial) on oxidative and sensory stability of dry fermented sausage (Petrovská klobása), during 7 months of storage, was investigated. During the storage period the content of free fatty acids was significantly higher (P<0.05), while the content of malondialdehyde was significantly lower in the sausage subjected to traditional conditions of drying. At the end of the storage period, content of hexanal in the sausage subjected to traditional conditions of ripening (1.67μg/g) was significantly lower (P<0.05) in comparison with this content in the sausage subjected to industrial conditions of ripening (4.94µg/g). Traditional conditions of ripening at lower temperatures have led to better sensory properties of odor and taste of traditional dry fermented sausage, Petrovská klobása after 2 and 7 months of storage.

Keywords: Lipid oxidation, Petrovská klobása, sensory stability, storage time.

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Authors: M. Bakhouya, S. A. Bahra, T. El-Ghazawi

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The Partitioned Global Address Space (PGAS) programming paradigm offers ease-of-use in expressing parallelism through a global shared address space while emphasizing performance by providing locality awareness through the partitioning of this address space. Therefore, the interest in PGAS programming languages is growing and many new languages have emerged and are becoming ubiquitously available on nearly all modern parallel architectures. Recently, new parallel machines with multiple cores are designed for targeting high performance applications. Most of the efforts have gone into benchmarking but there are a few examples of real high performance applications running on multicore machines. In this paper, we present and evaluate a parallelization technique for implementing a local DNA sequence alignment algorithm using a PGAS based language, UPC (Unified Parallel C) on a chip multithreading architecture, the UltraSPARC T1.

Keywords: Partitioned Global Address Space, Unified Parallel C, Multicore machines, Multi-threading Architecture, Sequence alignment.

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Authors: Tao Dai, Andy Adler, Behnam Shahrrava

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This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (APA). The proposed scheme uses a forgetting processed input matrix as the projection matrix of pseudo-inverse to estimate system deviation. This method introduces temporal weights into the projection matrix, which is typically a better model of the real error's behavior than homogeneous temporal weights. The regularization overcomes the ill-conditioning introduced by both the forgetting process and the increasing size of the input matrix. This algorithm is tested by independent trials with coloured input signals and various parameter combinations. Results show that the proposed algorithm is superior in terms of convergence rate and misadjustment compared to existing algorithms. As a special case, a variable step size NLMS with forgetting factor is also presented in this paper.

Keywords: Adaptive signal processing, affine projection algorithms, variable step-size adaptive algorithms, regularization.

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Authors: Sheetal Chavan, P. J. Kulkarni, Vivek Shanbhag

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Although achieving zero-defect software release is practically impossible, software industries should take maximum care to detect defects/bugs well ahead in time allowing only bare minimums to creep into released version. This is a clear indicator of time playing an important role in the bug detection. In addition to this, software quality is the major factor in software engineering process. Moreover, early detection can be achieved only through static code analysis as opposed to conventional testing. BugCatcher.Net is a static analysis tool, which detects bugs in .NET® languages through MSIL (Microsoft Intermediate Language) inspection. The tool utilizes a Parser based on Finite State Automata to carry out bug detection. After being detected, bugs need to be corrected immediately. BugCatcher.Net facilitates correction, by proposing a corrective solution for reported warnings/bugs to end users with minimum side effects. Moreover, the tool is also capable of analyzing the bug trend of a program under inspection.

Keywords: Dependence, Early solution, Finite State Automata, Grammar, Late solution, Parser State Transition Diagram, StaticProgram Analysis.

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity is a disease with an ever-increasing prevalence throughout the world. The metabolic network associated with obesity is very complicated. In metabolic syndrome (MetS), it becomes even more difficult to understand. Within this context, hormones, cytokines, and many others participate in this complex matrix. The collaboration among all of these parameters is a matter of great wonder. Cortisol, as a stress hormone, is closely associated with obesity. Thyroid hormones are involved in the regulation of energy as well as glucose metabolism with all of its associates. Fetuin A has been known for years; however, the involvement of this parameter in obesity discussions is rather new. Recently, it has been defined as one of the new generation markers of obesity. In this study, the aim was to introduce complex interactions among all to be able to make clear comparisons, at least for a part of this complicated matter. Morbid obese (MO) children participated in the study. Two groups with 46 MO children and 43 with MetS were constituted. All children included in the study were above 99th age- and sex-adjusted body mass index (BMI) percentiles according to World Health Organization criteria. Forty-three morbid obese children in the second group also had MetS components. Informed consent forms were filled by the parents of the participants. The institutional ethics committee has given approval for the study protocol. Data as well as the findings of the study were evaluated from a statistical point of view. Two groups were matched for their age and gender compositions. Significantly higher body mass index (BMI), waist circumference, thyrotropin, and insulin values were observed in the MetS group. Triiodothyronine concentrations did not differ between the groups. Elevated levels for thyroxin, cortisol, and fetuin-A were detected in the MetS group compared to the first group (p > 0.05). In MO MetS- group, cortisol was correlated with thyroxin and fetuin-A (p < 0.05). In the MO MetS+ group, none of these correlations were present. Instead, a correlation between cortisol and thyrotropin was found (p < 0.05). In conclusion, findings have shown that cortisol was the key player in severely obese children. The association of this hormone with the participants of thyroid hormone metabolism was quite important. The lack of association with fetuin A in the morbid obese MetS+ group has suggested the possible interference of MetS components in the behavior of this new generation obesity marker. The most remarkable finding of the study was the unique correlation between cortisol and thyrotropin in the morbid obese MetS+ group, suggesting that thyrotropin may serve as a target along with cortisol in the morbid obese MetS+ group. This association may deserve specific attention during the development of remedies against MetS in the pediatric population.

Keywords: children, cortisol, fetuin A, morbid obesity, thyrotropin

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Authors: Ali Beydoun, Hamzé H. Alaeddine

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MIMO-OFDM communication system presents a key solution for the next generation of mobile communication due to its high spectral efficiency, high data rate and robustness against multi-path fading channels. However, MIMO-OFDM system requires a perfect knowledge of the channel state information and a good synchronization between the transmitter and the receiver to achieve the expected performances. Recently, we have proposed two algorithms for channel estimation and timing synchronization with good performances and very low implementation complexity compared to those proposed in the literature. In order to validate and evaluate the efficiency of these algorithms in real environments, this paper presents in detail the implementation of 2 × 2 MIMO-OFDM system based on LabVIEW and USRP 2920. Implementation results show a good agreement with the simulation results under different configuration parameters.

Keywords: MIMO-OFDM system, timing synchronization, channel estimation, STBC, USRP 2920.

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Authors: Vytautas Galvanauskas, Vykantas Grincas, Rimvydas Simutis

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This paper investigates a possible practical solution for reasonable oxygen supply during the pluripotent stem cells expansion processes, where the stem cells propagate as aggregates in stirred-suspension bioreactors. Low glucose and low oxygen concentrations are preferred for efficient proliferation of pluripotent stem cells. However, strong oxygen limitation, especially inside of cell aggregates, can lead to cell starvation and death. In this research, the oxygen concentration profile inside of stem cell aggregates in a stem cell expansion process was predicted using a modified oxygen diffusion model. This profile can be realized during the stem cells cultivation process by manipulating the oxygen concentration in inlet gas or inlet gas flow. The proposed approach is relatively simple and may be attractive for installation in a real pluripotent stem cell expansion processes.

Keywords: Aggregated stem cells, dissolved oxygen profiles, modeling, stirred-tank, 3D expansion.

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Authors: Sangsuree Vasupongayya

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Fair share objective has been included into the goaloriented parallel computer job scheduling policy recently. However, the previous work only presented the overall scheduling performance. Thus, the per-user performance of the policy is still lacking. In this work, the details of per-user fair share performance under the Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair share priority backfill policy namely RelShare(1d) is also studied. The performance of all policies is collected using an event-driven simulator with three real job traces as input. The experimental results show that the high demand users are usually benefited under most policies because their jobs are large or they have a lot of jobs. In the large job case, one job executed may result in over-share during that period. In the other case, the jobs may be backfilled for performances. However, the users with a mixture of jobs may suffer because if the smaller jobs are executing the priority of the remaining jobs from the same user will be lower. Further analysis does not show any significant impact of users with a lot of jobs or users with a large runtime approximation error.

Keywords: deviation, fair share, discrepancy search, priority scheduling.

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: Pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction.

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Authors: F. Havas Beigi, E. Mohammadi, M.Vafaee Yeganeh

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Curriculum is one of the most important inputs in higher education system and for knowing the strong and weak spots of it we need evaluation. The main purpose of this study was to survey of the curriculum quality of Insurance Management field. Case: University of Allameh Taba Tabaee(according to view point of students,alumni,employer and faculty members).Descriptive statistics (mean, tables, percentages, frequency distribution) and inferential statistics (CHI SQUARE) were used to analyze the data. Six criterions considered for the Quality of curriculum: objectives, content, teaching and learning methods, space and facilities, Time, assessment of learning. objectives, teaching and learning methods criterions was desirable level, content criteria was undesirable level, space and facilities, time and assessment of learning were rather desirable level. The quality of curriculum of insurance management field was relatively desirable level.

Keywords: Quality, curriculum, insurance management, higher education.

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Authors: C. N. Vanitha, M. Usha

Abstract:

In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: Neural networks, pattern learning, security, wireless sensor networks.

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Authors: H. Iranmanesh, S. Nazari Shirkouhi, M. R. Skandari

Abstract:

Information Technology (IT) projects are always accompanied by various risks and because of high rate of failure in such projects, managing risks in order to neutralize or at least decrease their effects on the success of the project is strongly essential. In this paper, fuzzy analytical hierarchy process (FAHP) is exploited as a means of risk evaluation methodology to prioritize and organize risk factors faced in IT projects. A real case of IT projects, a project of design and implementation of an integrated information system in a vehicle producing company in Iran is studied. Related risk factors are identified and then expert qualitative judgments about these factors are acquired. Translating these judgments to fuzzy numbers and using them as an input to FAHP, risk factors are then ranked and prioritized by FAHP in order to make project managers aware of more important risks and enable them to adopt suitable measures to deal with these highly devastative risks.

Keywords: Information technology projects, Risk evaluation, Analytic hierarchal process, fuzzy logic.

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Authors: O. Yavuz, L. Ozyilmaz

Abstract:

HIV-1 genome is highly heterogeneous. Due to this variation, features of HIV-I genome is in a wide range. For this reason, the ability to infection of the virus changes depending on different chemokine receptors. From this point of view, R5 HIV viruses use CCR5 coreceptor while X4 viruses use CXCR5 and R5X4 viruses can utilize both coreceptors. Recently, in Bioinformatics, R5X4 viruses have been studied to classify by using the experiments on HIV-1 genome. In this study, R5X4 type of HIV viruses were classified using Auto Regressive (AR) model through Artificial Neural Networks (ANNs). The statistical data of R5X4, R5 and X4 viruses was analyzed by using signal processing methods and ANNs. Accessible residues of these virus sequences were obtained and modeled by AR model since the dimension of residues is large and different from each other. Finally the pre-processed data was used to evolve various ANN structures for determining R5X4 viruses. Furthermore ROC analysis was applied to ANNs to show their real performances. The results indicate that R5X4 viruses successfully classified with high sensitivity and specificity values training and testing ROC analysis for RBF, which gives the best performance among ANN structures.

Keywords: Auto-Regressive Model, HIV, Neural Networks, ROC Analysis.

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