Search results for: Chandan Deep Singh

Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Prevent abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep Long Short-Term Memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviours far from the expected one, depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behaviour analysis, LSTM

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Authors: Jaibir Sharma, Lee JaeWung, Merugu Srinivas, Navab Singh

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This paper presents thermal annealing de-wetting technique for the preparation of porous metal membrane for Thin Film Encapsulation (TFE) application. Thermal annealing de-wetting experimental results reveal that pore size formation in porous metal membrane depend upon i.e. 1. The substrate at which metal is deposited, 2. Melting point of metal used for porous metal cap layer membrane formation, 3. Thickness of metal used for cap layer, 4. Temperature used for formation of porous metal membrane. In order to demonstrate this technique, Silver (Ag) was used as a metal for preparation of porous metal membrane on amorphous silicon (a-Si) and silicon oxide. The annealing of the silver thin film of various thicknesses was performed at different temperature. Pores in porous silver film were analyzed using Scanning Electron Microscope (SEM). In order to check the usefulness of porous metal film for TFE application, the porous silver film prepared on amorphous silicon (a- Si) and silicon oxide was released using XeF2 and VHF, respectively. Finally, guide line and structures are suggested to use this porous membrane for robust TFE application.

Keywords: De-wetting, thermal annealing, metal, melting point, porous.

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: Edge network, embedded network, MMA, matrix multiplication accelerator and semantic segmentation network.

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Authors: S. E. Musa, N. E. Mohamed, N. A. Ahmed

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In this study, several crossplots of the P-impedance with the lithology logs (gamma ray, neutron porosity, deep resistivity, water saturation and Vp/Vs curves) were made in three available wells, which were drilled in central part of the Blue Nile basin in depths varies from 1460m to 1600m. These crossplots were successful to discriminate between sand and shale when using PImpedance values, and between the wet sand and the pay sand when using both P-impedance and Vp/Vs together. Also some impedance sections were converted to porosity sections using linear formula to characterize the reservoir in terms of porosity. The used crossplots were created on log resolution, while the seismic resolution can identify only the reservoir, unless a 3D seismic angle stacks were available; then it would be easier to identify the pay sand with great confidence; through high resolution seismic inversion and geostatistical approach when using P-impedance and Vp/Vs volumes.

Keywords: Basin, Blue Nile, Inversion, Seismic.

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Authors: Parvinder S. Sandhu, Hardeep Singh

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The requirement to improve software productivity has promoted the research on software metric technology. There are metrics for identifying the quality of reusable components but the function that makes use of these metrics to find reusability of software components is still not clear. These metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the component and hence improve the productivity due to probabilistic increase in the reuse level. CK metric suit is most widely used metrics for the objectoriented (OO) software; we critically analyzed the CK metrics, tried to remove the inconsistencies and devised the framework of metrics to obtain the structural analysis of OO-based software components. Neural network can learn new relationships with new input data and can be used to refine fuzzy rules to create fuzzy adaptive system. Hence, Neuro-fuzzy inference engine can be used to evaluate the reusability of OO-based component using its structural attributes as inputs. In this paper, an algorithm has been proposed in which the inputs can be given to Neuro-fuzzy system in form of tuned WMC, DIT, NOC, CBO , LCOM values of the OO software component and output can be obtained in terms of reusability. The developed reusability model has produced high precision results as expected by the human experts.

Keywords: CK-Metric, ID3, Neuro-fuzzy, Reusability.

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Authors: Treepon Kirdnark

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This paper examines the depiction of Muslim militants in Thai newspapers in 2004. Stuart Hall-s “representation" and “public idioms" are used as theoretical frameworks. Critical Discourse Analysis is employed as a methodology to examine 240 news articles from two leading Thai language newspapers. The results show that the militants are usually labeled as “southern bandits." This suggests that they are just a culprit of the violence in the deep south of Thailand. They are usually described as people who cause turbulence. Consequently, the military have to get rid of them. However, other aspects of the groups such as their political agenda or the failures of the Thai state in dealing with the Malay Muslims were not mention in the news stories. In the time of violence, the researcher argues that this kind of newspaper coverage may help perpetuate the discourse of Malay Muslim, instead of providing fuller picture of the ongoing conflicts.

Keywords: News Discourse, Newspapers, Thailand, Thai Muslims.

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Authors: Hari Shankar, Kshitij Raj, Priya Keshari, Pragya Singh

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Headache is one of the most ubiquitous and frequent neurological disorders interfering with everyday life in all countries. India appears to be no exception. Objectives are to assess the prevalence of headache among adult population in urban area of Varanasi and to find out factors influencing the occurrence of headache. A community based cross sectional study was conducted among adult population in urban area of Varanasi district, Uttar Pradesh, India. Total 151 eligible respondents were interviewed by simple random sampling technique. Proportion percentage and Chisquare test were applied for data analysis. Out of 151 respondents, majority (58.3%) were females. In this study, 92.8% respondents belonged to age group 18-60 years while 7.2% was either 60 year of age or above. The overall prevalence of headache was found to be 51.1%. Highest and lowest prevalence of headache was recorded in age groups 18-29 year & 40-49 year respectively. Headache was 62.1% in illiterate and was 40.0% among graduate & above. Unskilled workers had more headache 73.1% than other type of occupation. Headache was more prevalent among unemployed (35.9%) than employed (6.4%). Females had higher family history of headache (48.9%) as compared to males (41.3%). Study subjects having peaceful relation with family members, relatives and neighbors had more headache than those having no peaceful relation.  

Keywords: Family relationship, headache, neighbors, ration cards.

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Authors: Prakash Singh

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For schools to be desirable places in which to work, it is necessary for principals to recognise their teachers’ emotions, and be sensitive to their needs. This necessitates that principals are capable to correctly identify their emotionally intelligent behaviours (EIBs) they need to use in order to be successful leaders. They also need to have knowledge of their emotional intelligence and be able to identify the factors and situations that evoke emotion at an interpersonal level. If a principal is able to do this, then the control and understanding of emotions and behaviours of oneself and others could improve vastly. This study focuses on the interpersonal EIBS of principals affecting the job satisfaction of teachers. The correlation coefficients in this quantitative study strongly indicate that there is a statistical significance between the respondents’ level of job satisfaction, the rating of their principals’ EIBs and how they believe their principals’ EIBs will affect their sense of job satisfaction. It can be concluded from the data obtained in this study that there is a significant correlation between the sense of job satisfaction of teachers and their principals’ interpersonal EIBs. This means that the more satisfied a teacher is at school, the more appropriate and meaningful a principal’s EIBs will be. Conversely, the more dissatisfied a teacher is at school the less appropriate and less meaningful a principal’s interpersonal EIBs will be. This implies that the leaders’ EIBs can be construed as one of the major factors affecting the job satisfaction of employees.

Keywords: Emotional intelligence, teachers’ emotions, teachers’ job satisfaction, principals’ emotionally intelligent behaviours.

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Authors: Afaf Alharbi, Qianni Zhang

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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: Attention Multiple Instance Learning, Multiple Instance Learning, transfer learning, histopathological slides, cancer tissue classification.

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Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: BERT, chatbot, cryptocurrency, deep learning.

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Authors: M. Maronek, J. Barta, P. Palcek, K. Ulrich

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Low carbon deep drawing steel DC 01 according to EN 10130-91 was nitrooxidized in dissociated ammonia at 580°C/45 min and consequently oxidised at 380°C/5 min in vapour of distilled water. Material after nitrooxidation had 54 % increase of yield point, 34 % increase of strength and 10-times increased resistance to atmospheric corrosion in comparison to the material before nitrooxidation. The microstructure of treated material consisted of thin ε-phase layer connected to layer containing precipitated massive needle shaped Fe4N - γ' nitrides. This layer passed to a diffusion layer consisting of fine irregular shaped Fe16N2 - α'' nitrides regularly dispersed in ferritic matrix. Fatigue properties were examined under bending load with frequency of 20 kHz and sinusoidal symmetric cycle. The results confirmed positive influence of nitrooxidation on fatigue properties as fatigue limit of treated material was double in comparison to untreated material.

Keywords: steel sheet, fatigue, nitrooxidation, S-N diagram

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Authors: Sourabh Jain, Sukhvir Singh Jain, Gaurav V. Jain

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Intelligent Transportation System is an integrated application of communication, control and monitoring and display process technologies for developing a user–friendly transportation system for urban areas in developing countries. In fact, the development of a country and the progress of its transportation system are complementary to each other. Urban traffic has been growing vigorously due to population growth as well as escalation of vehicle ownership causing congestion, delays, pollution, accidents, high-energy consumption and low productivity of resources. The development and management of urban transport in developing countries like India however, is at tryout stage with very few accumulations. Under the umbrella of ITS, urban corridor management strategy have proven to be one of the most successful system in accomplishing these objectives. The present study interprets and figures out the performance of the 27.4 km long Urban Bus route having six intersections, five flyovers and 29 bus stops that covers significant area of the city by causality analysis. Performance interpretations incorporate Passenger Boarding and Alighting, Dwell time, Distance between Bus Stops and Total trip time taken by bus on selected urban route.

Keywords: Congestion, Dwell time, delay, passengers boarding alighting, travel time.

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Authors: Michele V. Carbinatto, Wagner Wey Moreira, Myrian Nunomura; Mariana H. C. Tsukamoto, VilmaLeni Nista-Piccolo

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Sports Sciences has been historically supported by the positivism idea of science, especially by the mechanistic/reductionist and becomes a field that views experimentation and measurement as the mayor research domains. The disposition to simplify nature and the world by parts has fragmented and reduced the idea of bodyathletes as machine. In this paper we intent to re-think this perception lined by Complexity Theory. We come with the idea of athletes as a reflexive and active being (corporeity-body). Therefore, the construction of a training that considers the cultural, biological, psychological elements regarding the experience of the human corporal movements in a circumspect and responsible way could bring better chances of accomplishment. In the end, we hope to help coaches understand the intrinsic complexity of the body they are training, how better deal with it, and, in the field of a deep globalization among the different types of knowledge, to respect and accepted the peculiarities of knowledge that comprise this area.

Keywords: Sport science, body, complexity theory, corporeity.

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Authors: Randhir Singh Baghel, Joydip Dhar, Renu Jain

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In this paper, for the understanding of the phytoplankton dynamics in marine ecosystem, a susceptible and an infected class of phytoplankton population is considered in spatiotemporal domain. Here, the susceptible phytoplankton is growing logistically and the growth of infected phytoplankton is due to the instantaneous Holling type-II infection response function. The dynamics are studied in terms of the local and global stabilities for the system and further explore the possibility of Hopf -bifurcation, taking the half saturation period as (i.e., ) the bifurcation parameter in temporal domain. It is also observe that the reaction diffusion system exhibits spatiotemporal chaos and pattern formation in phytoplankton dynamics, which is particularly important role play for the spatially extended phytoplankton system. Also the effect of the diffusion coefficient on the spatial system for both one and two dimensional case is obtained. Furthermore, we explore the higher-order stability analysis of the spatial phytoplankton system for both linear and no-linear system. Finally, few numerical simulations are carried out for pattern formation.

Keywords: Phytoplankton dynamics, Reaction-diffusion system, Local stability, Hopf-bifurcation, Global stability, Chaos, Pattern Formation, Higher-order stability analysis.

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Authors: Pardeep Singh, Sanjay Sharma

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Content-Based Image Retrieval (CBIR) has been one on the most vivid research areas in the field of computer vision over the last 10 years. Many programs and tools have been developed to formulate and execute queries based on the visual or audio content and to help browsing large multimedia repositories. Still, no general breakthrough has been achieved with respect to large varied databases with documents of difering sorts and with varying characteristics. Answers to many questions with respect to speed, semantic descriptors or objective image interpretations are still unanswered. In the medical field, images, and especially digital images, are produced in ever increasing quantities and used for diagnostics and therapy. In several articles, content based access to medical images for supporting clinical decision making has been proposed that would ease the management of clinical data and scenarios for the integration of content-based access methods into Picture Archiving and Communication Systems (PACS) have been created. This paper gives an overview of soft computing techniques. New research directions are being defined that can prove to be useful. Still, there are very few systems that seem to be used in clinical practice. It needs to be stated as well that the goal is not, in general, to replace text based retrieval methods as they exist at the moment.

Keywords: CBIR, GA, Rough sets, CBMIR

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Authors: Saeed Delara, Kendra MacKay

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Varying methodologies are considered for pile design for both Russian and Western approaches. Although both approaches rely on toe and side frictional resistances, different calculation methods are proposed to estimate pile capacity. The Western approach relies on compactness (internal friction angle) of soil for cohesionless soils and undrained shear strength for cohesive soils. The Russian approach relies on grain size for cohesionless soils and liquidity index for cohesive soils. Though most recommended methods in the Western approaches are relatively simple methods to predict pile settlement, the Russian approach provides a detailed method to estimate single pile and pile group settlement. Details to calculate pile axial capacity and settlement using the Russian and Western approaches are discussed and compared against field test results.

Keywords: Pile capacity, pile settlement, Russian approach, western approach.

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Authors: Azam Akbari, Mohammadreza Omidkhah, Jafar Toufighi Darian

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The mesoporous MoO3/γ-Al2O3 catalyst was prepared by incipient wetness impregnation method aiming to investigate the effect of drying method and molybdenum content on the catalyst property and performance towards the oxidation of benzothiophene (BT), dibenzothiophene (DBT) and 4,6-dimethyle dibenzothiophene (4,6-DMDBT) with H2O2 for deep oxidative desulfurization of diesel fuel. The catalyst was characterized by XRD, BET, BJH and SEM method. The catalyst with 10wt.% and 15wt.% Mo content represent same optimum performance for DBT and 4,6-DMDBT removal, but a catalyst with 10wt.% Mo has higher efficiency than 15wt.% Mo for BT conversion. The SEM images show that use of rotary evaporator in drying step reaches a more homogenous impregnation. The oxidation reactivity of different sulfur compounds was studied which followed the order of DBT>4,6-DMDBT>>BT.

Keywords: desulfurization, oxidation, MoO3/Al2O3 catalyst

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Authors: Vishal Awasthi, Tanya Soni, Vigya Awasthi, Swati Singh, Shivali Verma

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There is a growing demand for a network that grants a high level of data security and confidentiality. For this reason, the semantic web was introduced, which allows data to be shared and reused across applications while safeguarding users privacy and user’s will grab back control of their data. The earlier Web 1.0 and Web 2.0 versions were built on client-server architecture, in  which there was the risk of data theft and unconsented sale of user data. A decentralized version, Known as Web 3.0, that is mostly built on blockchain technology was interjected to resolve these issues. The recent research focuses on blockchain technology, deals with privacy, security, transparency, and innovation of decentralized applications (DApps), e.g. a Twitter Clone, Whatsapp clone. In this paper the Twitter Alike built on the Ethereum blockchain will replace traditional techniques with improved latency, throughput, and data ownership. The central principle of this DApp is smart contract implemented using Solidity which is an object- oriented and highlevel language. Consequently, this will provide a better Quality Services, high data security, and integrity for both present and future internet technologies.

Keywords: Blockchain, DApps, Ethereum, Semantic Web, Smart Contract, Solidity.

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Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

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Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: Channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, Lévy flight distribution, optimization, improved multi–objective Firefly algorithms, Pareto optimal.

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: Customer relationship management, churn prediction, telecom industry, deep learning, Artificial Neural Networks, ANN.

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Authors: N. Basanta Singh, Sanjoy Deb, G. P Mishra, Subir Kumar Sarkar

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Carrier mobility has become the most important characteristic of high speed low dimensional devices. Due to development of very fast switching semiconductor devices, speed of computer and communication equipment has been increasing day by day and will continue to do so in future. As the response of any device depends on the carrier motion within the devices, extensive studies of carrier mobility in the devices has been established essential for the growth in the field of low dimensional devices. Small-signal ac transport of degenerate two-dimensional hot electrons in GaAs quantum wells is studied here incorporating deformation potential acoustic, polar optic and ionized impurity scattering in the framework of heated drifted Fermi-Dirac carrier distribution. Delta doping is considered in the calculations to investigate the effects of double delta doping on millimeter and submillimeter wave response of two dimensional hot electrons in GaAs nanostructures. The inclusion of delta doping is found to enhance considerably the two dimensional electron density which in turn improves the carrier mobility (both ac and dc) values in the GaAs quantum wells thereby providing scope of getting higher speed devices in future.

Keywords: Carrier mobility, Delta doping, Hot carriers, Quantum wells.

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Authors: Mohd. Hasan, Ajmal Kafeel, S. D. Pable

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Ultra-low-power (ULP) circuits have received widespread attention due to the rapid growth of biomedical applications and Battery-less Electronics. Subthreshold region of transistor operation is used in ULP circuits. Major research challenge in the subthreshold operating region is to extract the ULP benefits with minimal degradation in speed and robustness. Process, Voltage and Temperature (PVT) variations significantly affect the performance of subthreshold circuits. Designed performance parameters of ULP circuits may vary largely due to temperature variations. Hence, this paper investigates the effect of temperature variation on device and circuit performance parameters at different biasing voltages in the subthreshold region. Simulation results clearly demonstrate that in deep subthreshold and near threshold voltage regions, performance parameters are significantly affected whereas in moderate subthreshold region, subthreshold circuits are more immune to temperature variations. This establishes that moderate subthreshold region is ideal for temperature immune circuits.

Keywords: Subthreshold, temperature variations, ultralow power.

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Authors: Remica Aggarwal, Sanjeet Singh

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The decision to recruit manpower in an organization requires clear identification of the criteria (attributes) that distinguish successful from unsuccessful performance. The choice of appropriate attributes or criteria in different levels of hierarchy in an organization is a multi-criteria decision problem and therefore multi-criteria decision making (MCDM) techniques can be used for prioritization of such attributes. Analytic Hierarchy Process (AHP) is one such technique that is widely used for deciding among the complex criteria structure in different levels. In real applications, conventional AHP still cannot reflect the human thinking style as precise data concerning human attributes are quite hard to be extracted. Fuzzy logic offers a systematic base in dealing with situations, which are ambiguous or not well defined. This study aims at defining a methodology to improve the quality of prioritization of an employee-s performance measurement attributes under fuzziness. To do so, a methodology based on the Extent Fuzzy Analytic Hierarchy Process is proposed. Within the model, four main attributes such as Subject knowledge and achievements, Research aptitude, Personal qualities and strengths and Management skills with their subattributes are defined. The two approaches conventional AHP approach and the Extent Fuzzy Analytic Hierarchy Process approach have been compared on the same hierarchy structure and criteria set.

Keywords: AHP, Extent analysis method, Fuzzy AHP, Prioritization.

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Authors: Surita Maini

Abstract:

There are many perceived advantages of microwave ablation have driven researchers to develop innovative antennas to effectively treat deep-seated, non-resectable hepatic tumors. In this paper a coaxial antenna with a miniaturized sleeve choke has been discussed for microwave interstitial ablation therapy, in order to reduce backward heating effects irrespective of the insertion depth into the tissue. Two dimensional Finite Element Method (FEM) is used to simulate and measure the results of miniaturized sleeve choke antenna. This paper emphasizes the importance of factors that can affect simulation accuracy, which include mesh resolution, surface heating and reflection coefficient. Quarter wavelength choke effectiveness has been discussed by comparing it with the unchoked antenna with same dimensions.

Keywords: Microwave ablation, tumor, Finite Element Method, Coaxial slot antenna, Coaxial dipole antenna.

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Authors: Manjeet Bansal, Diwan Singh, V.K.Garg, Pawan Rose

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The potential of economically cheaper cellulose containing natural materials like rice husk was assessed for nickel adsorption from aqueous solutions. The effects of pH, contact time, sorbent dose, initial metal ion concentration and temperature on the uptake of nickel were studied in batch process. The removal of nickel was dependent on the physico-chemical characteristics of the adsorbent, adsorbate concentration and other studied process parameters. The sorption data has been correlated with Langmuir, Freundlich and Dubinin-Radush kevich (D-R) adsorption models. It was found that Freundlich and Langmuir isotherms fitted well to the data. Maximum nickel removal was observed at pH 6.0. The efficiency of rice husk for nickel removal was 51.8% for dilute solutions at 20 g L-1 adsorbent dose. FTIR, SEM and EDAX were recorded before and after adsorption to explore the number and position of the functional groups available for nickel binding on to the studied adsorbent and changes in surface morphology and elemental constitution of the adsorbent. Pseudo-second order model explains the nickel kinetics more effectively. Reusability of the adsorbent was examined by desorption in which HCl eluted 78.93% nickel. The results revealed that nickel is considerably adsorbed on rice husk and it could be and economic method for the removal of nickel from aqueous solutions.

Keywords: Adsorption, nickel, SEM, EDAX.

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Authors: Rampal Singh, S. Balasundaram

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In this paper, we study the application of Extreme Learning Machine (ELM) algorithm for single layered feedforward neural networks to non-linear chaotic time series problems. In this algorithm the input weights and the hidden layer bias are randomly chosen. The ELM formulation leads to solving a system of linear equations in terms of the unknown weights connecting the hidden layer to the output layer. The solution of this general system of linear equations will be obtained using Moore-Penrose generalized pseudo inverse. For the study of the application of the method we consider the time series generated by the Mackey Glass delay differential equation with different time delays, Santa Fe A and UCR heart beat rate ECG time series. For the choice of sigmoid, sin and hardlim activation functions the optimal values for the memory order and the number of hidden neurons which give the best prediction performance in terms of root mean square error are determined. It is observed that the results obtained are in close agreement with the exact solution of the problems considered which clearly shows that ELM is a very promising alternative method for time series prediction.

Keywords: Chaotic time series, Extreme learning machine, Generalization performance.

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Authors: Arvind Kumar, Manoj Kumar, Dattatraya H. Nagaraj, Amanpreet Singh, Jayanthi Prattapati

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The purpose of this paper is to study and compare two maximum power point tracking (MPPT) algorithms in a photovoltaic simulation system and also show a simulation study of maximum power point tracking (MPPT) for photovoltaic systems using perturb and observe algorithm and Incremental conductance algorithm. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize the array efficiency and minimize the overall system cost. Since the maximum power point (MPP) varies, based on the irradiation and cell temperature, appropriate algorithms must be utilized to track the (MPP) and maintain the operation of the system in it. MATLAB/Simulink is used to establish a model of photovoltaic system with (MPPT) function. This system is developed by combining the models established of solar PV module and DC-DC Boost converter. The system is simulated under different climate conditions. Simulation results show that the photovoltaic simulation system can track the maximum power point accurately.

Keywords: Incremental conductance Algorithm, Perturb and Observe Algorithm, Photovoltaic System and Simulation Results.

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Authors: Laveen Sundararaj, Palanisamy Vellaiyan

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Delay and Disruption Tolerant Networking is part of the Inter Planetary Internet with primary application being Deep Space Networks. Its Terrestrial form has interesting research applications such as Alagappa University Delay Tolerant Water Monitoring Network which doubles as test beds for improvising its routing scheme. DTNs depend on node mobility to deliver packets using a store-carry-and forward paradigm. Throwboxes are small and inexpensive stationary devices equipped with wireless interfaces and storage. We propose the use of Throwboxes to enhance the contact opportunities of the nodes and hence improve the Throughput. The enhancement is evaluated using Alunivdtnsim, a desktop simulator in C language and the results are graphically presented.

Keywords: Alunivdtnsim – Alagappa University Delay TolerantNetwork Simulator, AUDTWMN- Alagappa University DelayTolerant Water Monitoring Network, DTN - Delay and DisruptionTolerant Networking, LTP – Lick Lider Transmission Protocol.

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Authors: Parvinder S. Sandhu, Roma Jaswal, Sandeep Khimta, Shailendra Singh

Abstract:

As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done in time especially for the critical applications. As, Neural networks, which have been already applied in software engineering applications to build reliability growth models predict the gross change or reusability metrics. Neural networks are non-linear sophisticated modeling techniques that are able to model complex functions. Neural network techniques are used when exact nature of input and outputs is not known. A key feature is that they learn the relationship between input and output through training. In this present work, various Neural Network Based techniques are explored and comparative analysis is performed for the prediction of level of need of maintenance by predicting level severity of faults present in NASA-s public domain defect dataset. The comparison of different algorithms is made on the basis of Mean Absolute Error, Root Mean Square Error and Accuracy Values. It is concluded that Generalized Regression Networks is the best algorithm for classification of the software components into different level of severity of impact of the faults. The algorithm can be used to develop model that can be used for identifying modules that are heavily affected by the faults.

Keywords: Neural Network, Software faults, Software Metric.

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Authors: Nazirah Zainul Abidin

Abstract:

The creation of a sustainable future depends on the knowledge and involvement of the people, as well as an understanding of the consequences of individual actions. Construction industry has long been associated with the detrimental effects to our mother earth. In Malaysia, the government, professional bodies and private companies are beginning to take heed in the necessity to reduce this environmental problem without restraining the need for development. This paper focuses on the actions undertaken by the Malaysian government, non-government organizations and construction players in promoting sustainability in construction. To ensure that those concerted efforts are not only skin deep in its impact, a survey was conducted to investigate the awareness of the developers regarding this issue and whether those developers has absorb the concept of sustainable construction in their current practices. The survey revealed that although the developers are aware of the rising issues on sustainability, little efforts are generated from them in implementing it. More effort is necessary to boost this application and further stimulate actions and strategies towards a sustainable built environment.

Keywords: Environmental sustainability, Malaysian construction industry, Malaysian developers, Sustainable construction.

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