Search results for: Structural identification

Authors: Vishal Awasthi, Atul Kumar Agnihotri

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Face is a non-intrusive strong biometrics for identification of original and dummy facial by different artificial means. Face recognition is extremely important in the contexts of computer vision, psychology, surveillance, pattern recognition, neural network, content based video processing. The availability of a widespread face database is crucial to test the performance of these face recognition algorithms. The openly available face databases include face images with a wide range of poses, illumination, gestures and face occlusions but there is no dummy face database accessible in public domain. This paper presents a face detection algorithm based on the image segmentation in terms of distance from a fixed point and template matching methods. This proposed work is having the most appropriate number of nodal points resulting in most appropriate outcomes in terms of face recognition and detection. The time taken to identify and extract distinctive facial features is improved in the range of 90 to 110 sec. with the increment of efficiency by 3%.

Keywords: Face recognition, Principal Component Analysis, PCA, Linear Discriminant Analysis, LDA, Improved Support Vector Machine, iSVM, elastic bunch mapping technique.

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Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

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For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: High-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network.

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Authors: Thanut Kallaka, Ching-Jong Wang

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High level and high velocity flood flows are potentially harmful to bridge piers as evidenced in many toppled piers, and among them the single-column piers were considered as the most vulnerable. The flood flow characteristic parameters including drag coefficient, scouring and vortex shedding are built into a pier-flood interaction model to investigate structural safety against flood hazards considering the effects of local scouring, hydrodynamic forces, and vortex induced resonance vibrations. By extracting the pier-flood simulation results embedded in a neural networks code, two cases of pier toppling occurred in typhoon days were reexamined: (1) a bridge overcome by flash flood near a mountain side; (2) a bridge washed off in flood across a wide channel near the estuary. The modeling procedures and simulations are capable of identifying the probable causes for the tumbled bridge piers during heavy floods, which include the excessive pier bending moments and resonance in structural vibrations.

Keywords: Bridge piers, Neural networks, Scour depth, Structural safety, Vortex shedding

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Authors: Marco Kennemann, Steffen C. Eickemeyer, Peter Nyhuis

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Due to the growing dynamic and complexity within the market environment production enterprises in particular are faced with new logistic challenges. Moreover, it is here in this dynamic environment that the Logistic Operating Curve Theory also reaches its limits as a method for describing the correlations between the logistic objectives. In order to convert this theory into a method for dynamically monitoring productions this paper will introduce methods for reliably and quickly identifying structural changes relevant to logistics.

Keywords: Dynamics, Logistic Operating Curves, Production Logistics, Production Planning and Control

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Authors: A. Azuraida, M. K. Halimah, C. A. C. Azurahanim, M. Ishak

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The changes of the optical and structural properties of Bismuth-Boro-Tellurite glasses pre and post gamma irradiation were studied. Six glass samples, with different composition [(TeO2)0.7 (B2O3)0.3]1-x (Bi2O3)x prepared by melt quenching method were irradiated with 25kGy gamma radiation at room temperature. The Fourier Transform Infrared Spectroscopy (FTIR) was used to explore the structural bonding in the prepared glass samples due to exposure, while UV-VIS Spectrophotometer was used to evaluate the changes in the optical properties before and after irradiation. Gamma irradiation causes profound changes in the peak intensity as shown by FTIR spectra which is due to the breaking of the network bonding. Before gamma irradiation, the optical band gap, Eg value decreased from 2.44 eV to 2.15 eV with the addition of Bismuth content. The value kept decreasing (from 2.18 eV to 2.00 eV) following exposure to gamma radiation due to the increase of non-bridging oxygen (NBO) and the increase of defect in the glass. In conclusion, the glass with high content of Bi2O3 (0.30Bi) give smallest Eg and show less changes in FTIR spectra after gamma irradiation which indicate that this glass is more resistant to gamma radiation compared to other glasses.

Keywords: Boro-Tellurite, bismuth, gamma radiation, optical properties.

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Authors: Sumith Matharage, Damminda Alahakoon

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Textual data plays an important role in the modern world. The possibilities of applying data mining techniques to uncover hidden information present in large volumes of text collections is immense. The Growing Self Organizing Map (GSOM) is a highly successful member of the Self Organising Map family and has been used as a clustering and visualisation tool across wide range of disciplines to discover hidden patterns present in the data. A comprehensive analysis of the GSOM’s capabilities as a text clustering and visualisation tool has so far not been published. These functionalities, namely map visualisation capabilities, automatic cluster identification and hierarchical clustering capabilities are presented in this paper and are further demonstrated with experiments on a benchmark text corpus.

Keywords: Text Clustering, Growing Self Organizing Map, Automatic Cluster Identification, Hierarchical Clustering.

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Authors: Jiashang Jiang

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Model updating is an inverse eigenvalue problem which concerns the modification of an existing but inaccurate model with measured modal data. In this paper, an efficient gradient based iterative method for updating the mass, damping and stiffness matrices simultaneously using a few of complex measured modal data is developed. Convergence analysis indicates that the iterative solutions always converge to the unique minimum Frobenius norm symmetric solution of the model updating problem by choosing a special kind of initial matrices.

Keywords: Model updating, iterative algorithm, damped structural system, optimal approximation.

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Authors: Zhiying Zhang, Chongdu Cho

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Accurate evaluation of damping ratios involving soilstructure interaction (SSI) effects is the prerequisite for seismic design of in-situ buildings. This study proposes a combined approach to identify damping ratios of SSI systems based on ambient excitation technique. The proposed approach is illustrated with main test process, sampling principle and algorithm steps through an engineering example, as along with its feasibility and validity. The proposed approach is employed for damping ratio identification of 82 buildings in Xi-an, China. Based on the experimental data, the variation range and tendency of damping ratios of these SSI systems, along with the preliminary influence factor, are shown and discussed. In addition, a fitting curve indicates the relation between the damping ratio and fundamental natural period of SSI system.

Keywords: Damping ratio, seismic design, soil-structure interaction, system parameter identification.

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Authors: Woo Young Jung, Min Ho Kwon, Bu Seog Ju

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The primary objective of this research is to improve the flexural capacity of FRP strengthened RC Beam structures with Aluminum and Titanium laminates. FRP rupture of flexural strengthened RC beams using FRP plates generally occurs at the interface between FRP plate and the beam. Therefore, in order to prevent brittle rupture and improve the ductility of the system, this research was performed by using Aluminum and Titanium materials between the two different structural systems. The research also aims to provide various strengthening/retrofitting methods for RC beam structures and to conduct a preliminary analysis of the demands on the structural systems. This was achieved by estimation using the experimental data from this research to identify a flexural capacity for the systems. Ultimately, the preliminary analysis of current study showed that the flexural capacity and system demand ductility was significantly improved by the systems inserted with Aluminum and Titanium anchor plates. Further verification of the experimental research is currently on its way to develop a new or reliable design guideline to retrofit/strengthen the concrete-FRP structural system can be evaluated.

Keywords: Reinforced Concrete, FRP Laminate, Flexural Capacity, Ductility.

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Authors: Lorenzo Putzu, Cecilia Di Ruberto

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The counting and analysis of blood cells allows the evaluation and diagnosis of a vast number of diseases. In particular, the analysis of white blood cells (WBCs) is a topic of great interest to hematologists. Nowadays the morphological analysis of blood cells is performed manually by skilled operators. This involves numerous drawbacks, such as slowness of the analysis and a nonstandard accuracy, dependent on the operator skills. In literature there are only few examples of automated systems in order to analyze the white blood cells, most of which only partial. This paper presents a complete and fully automatic method for white blood cells identification from microscopic images. The proposed method firstly individuates white blood cells from which, subsequently, nucleus and cytoplasm are extracted. The whole work has been developed using MATLAB environment, in particular the Image Processing Toolbox.

Keywords: Automatic detection, Biomedical image processing, Segmentation, White blood cell analysis.

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Authors: Frank Emmert Streib

Abstract:

The classification of the protein structure is commonly not performed for the whole protein but for structural domains, i.e., compact functional units preserved during evolution. Hence, a first step to a protein structure classification is the separation of the protein into its domains. We approach the problem of protein domain identification by proposing a novel graph theoretical algorithm. We represent the protein structure as an undirected, unweighted and unlabeled graph which nodes correspond the secondary structure elements of the protein. This graph is call the protein graph. The domains are then identified as partitions of the graph corresponding to vertices sets obtained by the maximization of an objective function, which mutually maximizes the cycle distributions found in the partitions of the graph. Our algorithm does not utilize any other kind of information besides the cycle-distribution to find the partitions. If a partition is found, the algorithm is iteratively applied to each of the resulting subgraphs. As stop criterion, we calculate numerically a significance level which indicates the stability of the predicted partition against a random rewiring of the protein graph. Hence, our algorithm terminates automatically its iterative application. We present results for one and two domain proteins and compare our results with the manually assigned domains by the SCOP database and differences are discussed.

Keywords: Graph partitioning, unweighted graph, protein domains.

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Authors: S. Ali, R. Yunus, A. Arif, Y. Ayaz, M. Baber Sial, R. Asif, N. Naseer, M. Jawad Khan

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In this study, we have proposed a gesture to emotion recognition method using flex sensors mounted on metacarpophalangeal joints. The flex sensors are fixed in a wearable glove. The data from the glove are sent to PC using Wi-Fi. Four gestures: finger pointing, thumbs up, fist open and fist close are performed by five subjects. Each gesture is categorized into sad, happy, and excited class based on the velocity and acceleration of the hand gesture. Seventeen inspectors observed the emotions and hand gestures of the five subjects. The emotional state based on the investigators assessment and acquired movement speed data is compared. Overall, we achieved 77% accurate results. Therefore, the proposed design can be used for emotional state detection applications.

Keywords: Emotion identification, emotion models, gesture recognition, user perception.

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Authors: Munazza A. Mirza, Khawar Khurshid

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Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.

Keywords: Learning style, VARK, sensory preferences, identification model, didactic practices.

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: Structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm.

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Authors: Meng-Hao Tsai, Tsuei-Chiang Huang

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Interior brick-infill partitions are usually considered as non-structural components, and only their weight is accounted for in practical structural design. In this study, the brick-infill panels are simulated by compression struts to clarify their effect on the progressive collapse potential of an earthquake-resistant RC building. Three-dimensional finite element models are constructed for the RC building subjected to sudden column loss. Linear static analyses are conducted to investigate the variation of demand-to-capacity ratio (DCR) of beam-end moment and the axial force variation of the beams adjacent to the removed column. Study results indicate that the brick-infill effect depends on their location with respect to the removed column. As they are filled in a structural bay with a shorter span adjacent to the column-removed line, more significant reduction of DCR may be achieved. However, under certain conditions, the brick infill may increase the axial tension of the two-span beam bridging the removed column.

Keywords: Progressive collapse, brick-infill partition, compression strut.

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Authors: Che Z. Zulkifli, Nursyahida M. Noor, Siti N. Semunab, Shafawati A. Malek

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Wireless sensors, also known as wireless sensor nodes, have been making a significant impact on human daily life. The Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two complementary technologies; hence, an integrated implementation of these technologies expands the overall functionality in obtaining long-range and real-time information on the location and properties of objects and people. An approach for integrating ZigBee and RFID networks is proposed in this paper, to create an energy-efficient network improved by the benefits of combining ZigBee and RFID architecture. Furthermore, the compatibility and requirements of the ZigBee device and communication links in the typical RFID system which is presented with the real world experiment on the capabilities of the proposed RFID system.

Keywords: Mesh network, RFID, wireless sensor network, zigbee.

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Authors: Parkpoom Ch., Narongkorn D.

Abstract:

This paper presents the system identification by physical-s law method and designs the controller for the Azimuth Angle Control of the Platform of the Multi-Launcher Rocket System (MLRS) by Root Locus technique. The plant mathematical model was approximated using MATLAB for simulation and analyze the system. The controller proposes the implementation of PID Controller using Programmable Logic Control (PLC) for control the plant. PID Controllers are widely applicable in industrial sectors and can be set up easily and operate optimally for enhanced productivity, improved quality and reduce maintenance requirement. The results from simulation and experiments show that the proposed a PID Controller to control the elevation angle that has superior control performance by the setting time less than 12 sec, the rise time less than 1.6 sec., and zero steady state. Furthermore, the system has a high over shoot that will be continue development.

Keywords: Azimuth angle control, PID Controller, The platform of Multi-Launcher Rocket System.

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Authors: Carmen Grigoraş, Victor Grigoraş, Daniela Boişteanu

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The standard investigational method for obstructive sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG), which consists of a simultaneous, usually overnight recording of multiple electro-physiological signals related to sleep and wakefulness. This is an expensive, encumbering and not a readily repeated protocol, and therefore there is need for simpler and easily implemented screening and detection techniques. Identification of apnea/hypopnea events in the screening recordings is the key factor for the diagnosis of OSAS. The analysis of a solely single-lead electrocardiographic (ECG) signal for OSAS diagnosis, which may be done with portable devices, at patient-s home, is the challenge of the last years. A novel artificial neural network (ANN) based approach for feature extraction and automatic identification of respiratory events in ECG signals is presented in this paper. A nonlinear principal component analysis (NLPCA) method was considered for feature extraction and support vector machine for classification/recognition. An alternative representation of the respiratory events by means of Kohonen type neural network is discussed. Our prospective study was based on OSAS patients of the Clinical Hospital of Pneumology from Iaşi, Romania, males and females, as well as on non-OSAS investigated human subjects. Our computed analysis includes a learning phase based on cross signal PSG annotation.

Keywords: Artificial neural networks, feature extraction, obstructive sleep apnea syndrome, pattern recognition, signalprocessing.

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Authors: R. E. Waters, M. J. Whiting, V. Stolojan

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A method of collecting composition data and examining structural features of pearlite lamellae and the parent austenite at the growth interface in a 13wt. % manganese steel has been demonstrated with the use of Scanning Transmission Electron Microscopy (STEM). The combination of composition data and the structural features observed at the growth interface show that available theories of pearlite growth cannot explain all the observations.

Keywords: Interfaces, Phase transformations, Pearlite, Scanning Transmission Electron Microscopy (STEM).

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Authors: Y. Harold Robinson, M. Rajaram, Honey Raju

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Image segmentation and color identification is an important process used in various emerging fields like intelligent robotics. A method is proposed for the manipulator to grasp and place the color object into correct location. The existing methods such as PSO, has problems like accelerating the convergence speed and converging to a local minimum leading to sub optimal performance. To improve the performance, we are using watershed algorithm and for color identification, we are using EPSO. EPSO method is used to reduce the probability of being stuck in the local minimum. The proposed method offers the particles a more powerful global exploration capability. EPSO methods can determine the particles stuck in the local minimum and can also enhance learning speed as the particle movement will be faster.

Keywords: Color information, EPSO, hue, saturation, value (HSV), image segmentation, particle swarm optimization (PSO). Active Contour, GMM.

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Authors: S. S. Sharma, P. R. Prabhu, Rajagopal Chadaga

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The main emphasis of metallurgists has been to process the materials to obtain the balanced mechanical properties for the given application. One of the processing routes to alter the properties is heat treatment. Nearly 90% of the structural applications are related to the medium carbon an alloyed steels and hence are regarded as structural steels. The major requirement in the conventional steel is to improve workability, toughness, hardness and grain refinement. In this view, it is proposed to study the mechanical and tribological properties of unalloyed structural (AISI 1140) steel with different thermal (heat) treatments like annealing, normalizing, tempering and hardening and compared with as brought (cold worked) specimen. All heat treatments are carried out in atmospheric condition. Hardening treatment improves hardness of the material, a marginal decrease in hardness value with improved ductility is observed in tempering. Annealing and normalizing improve ductility of the specimen. Normalized specimen shows ultimate ductility. Hardened specimen shows highest wear resistance in the initial period of slide wear where as above 25KM of sliding distance, as brought steel dominates the hardened specimen. Both mild and severe wear regions are observed. Microstructural analysis shows the existence of pearlitic structure in normalized specimen, lath martensitic structure in hardened, pearlitic, ferritic structure in annealed specimen.

Keywords: Annealing, hardness, heat treatment, normalizing, wear.

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Authors: Jing Zhou, Steven Su, Aihuang Guo

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COSMED K4b2 is a portable electrical device designed to test pulmonary functions. It is ideal for many applications that need the measurement of the cardio-respiratory response either in the field or in the lab is capable with the capability to delivery real time data to a sink node or a PC base station with storing data in the memory at the same time. But the actual sensor outputs and data received may contain some errors, such as impulsive noise which can be related to sensors, low batteries, environment or disturbance in data acquisition process. These abnormal outputs might cause misinterpretations of exercise or living activities to persons being monitored. In our paper we propose an effective and feasible method to detect and identify errors in applications by principal component analysis (PCA) and a back propagation (BP) neural network.

Keywords: BP Neural Network, Exercising Testing, Fault Detection and Identification, Principal Component Analysis.

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Authors: S. K. Madan, R. S. Malik, V. K. Sehgal

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R.C.C. buildings with dual structural system consisting of shear walls (or braces) and moment resisting frames have been widely used to resist lateral forces during earthquakes. The dual systems are designed to resist the total design lateral force in proportion to their lateral stiffness. The response of combination of braces and shear walls has not yet been studied. The combination may prove to be more effective to resist lateral forces during earthquakes. This concept has been applied to regular R.C.C. buildings provided with shear walls, braces and their combinations.

Keywords: Dynamic analysis, Displacement, Dual structural system, Storey drift.

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Authors: Mansi Dhuria, Aalok Misra

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In the context of large volume Big Divisor (nearly) SLagy D3/D7 μ-Split SUSY [1], after an explicit identification of first generation of SM leptons and quarks with fermionic superpartners of four Wilson line moduli, we discuss the identification of gravitino as a potential dark matter candidate by explicitly calculating the decay life times of gravitino (LSP) to be greater than age of universe and lifetimes of decays of the co-NLSPs (the first generation squark/slepton and a neutralino) to the LSP (the gravitino) to be very small to respect BBN constraints. Interested in non-thermal production mechanism of gravitino, we evaluate the relic abundance of gravitino LSP in terms of that of the co-NLSP-s by evaluating their (co-)annihilation cross sections and hence show that the former satisfies the requirement for a potential Dark Matter candidate. We also show that it is possible to obtain a 125 GeV light Higgs in our setup.

Keywords: Split Supersymmetry, Large Volume Swiss-Cheese Calabi-Yau's, Dark Matter, (N)LSP decays, relic abundance.

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Authors: Amr A. El Hanafy, Yasir Anwar, Saleh A. Mohamed, Saleh Mohamed Saleh Al-Garni, Jamal S. M. Sabir, Osama A. H. Abu Zinadah, Mohamed Morsi Ahmed

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In the vicinity of red sea about 15 fungi species were isolated from oil contaminated sites. On the basis of aptitude to degrade the crude oil and DCPIP assay, two fungal isolates were selected amongst 15 oil degrading strains. Analysis of ITS-1, ITS-2 and amplicon pyrosequencing studies of fungal diversity revealed that these strains belong to Penicillium and Aspergillus species. Two strains that proved to be the most efficient in degrading crude oil was Aspergillus niger (54%) and Penicillium commune (48%) Subsequent to two weeks of cultivation in BHS medium the degradation rate were recorded by using spectrophotometer and GC-MS. Hence, it is cleared that these fungal strains has capability of degradation and can be utilize for cleaning the Saudi Arabian environment.

Keywords: Fungal strains, hydrocarbon contaminants, molecular identification, biodegradation, GC-MS.

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Authors: Ahmad T. Al-Taani

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In this paper, an efficient structural approach for recognizing on-line handwritten digits is proposed. After reading the digit from the user, the slope is estimated and normalized for adjacent nodes. Based on the changing of signs of the slope values, the primitives are identified and extracted. The names of these primitives are represented by strings, and then a finite state machine, which contains the grammars of the digits, is traced to identify the digit. Finally, if there is any ambiguity, it will be resolved. Experiments showed that this technique is flexible and can achieve high recognition accuracy for the shapes of the digits represented in this work.

Keywords: Digits Recognition, Pattern Recognition, FeatureExtraction, Structural Primitives, Document Processing, Handwritten Recognition, Primitives Selection.

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Authors: Patrick T. I. Lam, Wenjing Yang

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A smart city project embraces benefits and costs which can be classified under direct and indirect categories. Externalities come into the picture, but they are often difficult to quantify. Despite this barrier, policy makers need to carry out cost-benefit analysis to justify the huge investments needed to make a city smart. The recent trend is towards the engagement of the private sector to utilize their resources and expertise, especially in the Information and Communication Technology (ICT) areas, where innovations blossom. This study focuses on the identification of costs (on a life cycle basis) and benefits associated with smart city project developments based on a comprehensive literature review and case studies, where public-private partnerships would warrant consideration, the related costs and benefits are highlighted. The findings will be useful for policy makers of cities.

Keywords: Costs and benefits, identification, public-private partnerships, smart city projects.

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Authors: Panam. Zarfam, Mohsen. Javan Pour

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Recently, analysis and designing of the structures based on the Reliability theory have been the center of attention. Reason of this attention is the existence of the natural and random structural parameters such as the material specification, external loads, geometric dimensions etc. By means of the Reliability theory, uncertainties resulted from the statistical nature of the structural parameters can be changed into the mathematical equations and the safety and operational considerations can be considered in the designing process. According to this theory, it is possible to study the destruction probability of not only a specific element but also the entire system. Therefore, after being assured of safety of every element, their reciprocal effects on the safety of the entire system can be investigated.

Keywords: Probability, Reliability, Statistics, Uncertainty

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Authors: Muhamad Abduh, Jarita Duasa, Mohd. Azmi Omar

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Unlike its conventional counterpart, Islamic principles forbid Islamic banks to take any interest-related income and thus makes deposits from depositors as an important source of fund for its operational and financing. Consequently, the risk of deposit withdrawal by depositors is an important aspect that should be wellmanaged in Islamic banking. This paper aims to investigate factors that influence depositors- withdrawal behavior in Islamic banks, particularly in Malaysia, using the framework of theory of reasoned action. A total of 368 respondents from Klang valley are involved in the analysis. The paper finds that all the constructs variable i.e. normative beliefs, subjective norms, behavioral beliefs, and attitude towards behavior are perceived to be distinct by the respondents. In addition, the structural equation model is able to verify the structural relationships between subjective norms, attitude towards behavior and behavioral intention. Subjective norms gives more influence to depositors- decision on deposit withdrawal compared to attitude towards behavior.

Keywords: Islamic bank, structural equation model, theory of reasoned action, withdrawal behavior

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Authors: Kailash, Rajeev Kumar Saha, Sanjeev Goyal

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Each and every manufacturing industry has a goal that describes its purpose and destination. The goal of any industry may be achieved by team work and managerial skills of all departments. However, achieving goals and objectives is not enough to improve the internal supply chain management performance of manufacturing industries therefore proper identification of performance indicators for benchmarking of internal supply chain management is essential for the growth of manufacturing industry. The identification of benchmarking performance indicators and their impact on internal supply chain management performance is vital for productivity and performance improvement. This study identifies the benchmarking performance indicators to improve internal supply chain performance of Indian manufacturing industries through literature review.

Keywords: Benchmarking, Internal supply chain management, performance indicators, scenario of Indian manufacturing industries.

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