Search results for: Usha Rani Gogoi Jr.

Authors: Geetanjli Rani

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The physical forms and network pattern of the city is expected to be enhanced with the advancement of technology. Reason being, the era of virtualisation and digital urban realm convergence with physical development. By means of comparative Spatial graphics and visuals of cities, the present paper attempts to revisit the very base of efficient physical forms and patterns to sync the emergence of virtual activities. Thus, the present approach to integrate spatial Smartness of Cities and Intelligent Transportation Systems is a brief assessment of smart forms and intelligent transportation network pattern to the dualism of physical and virtual urban activities. Finally, the research brings out that the grid iron pattern, radial, ring-radial, orbital etc. stands to be more efficient, effective and economical transit friendly for users, resource optimisation as well as compact urban and regional systems. Moreover, this paper concludes that the idea of flow and contiguity hidden in such smart forms and intelligent transportation network pattern suits to layering, deployment, installation and development of Intelligent Transportation Systems of Smart Cities such as infrastructure, facilities and services.

Keywords: smart form, smart infrastructure, intelligent transportation network pattern, physical and virtual integration

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Authors: Manpreet Kaur, Amita Rani, Sanjay Kumar

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The Internet of Things (IoT), a cyber-physical paradigm, allows a large number of devices to connect and send the sensory data in the network simultaneously. This tremendous amount of data generated leads to very high network load consequently resulting in network congestion. It further amounts to frequent loss of useful information and depletion of significant amount of nodes’ energy. Therefore, there is a need to control congestion in IoT so as to prolong network lifetime and improve the quality of service (QoS). Hence, we propose a two-level clustering based routing algorithm considering congestion score and packet priority metrics that focus on minimizing the network congestion. In the proposed Priority based Congestion Control (PBCC) protocol the sensor nodes in IoT network form clusters that reduces the amount of traffic and the nodes are prioritized to emphasize important data. Simultaneously, a congestion score determines the occurrence of congestion at a particular node. The proposed protocol outperforms the existing Packet Discard Network Clustering (PDNC) protocol in terms of buffer size, packet transmission range, network region and number of nodes, under various simulation scenarios.

Keywords: internet of things, cyber-physical systems, congestion control, priority, transmission rate

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Authors: Usha Barahmand, Ruhollah Heydari Sheikh Ahmad

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Distress refers to an unpleasant metal state or emotional suffering marked by negative affect such as depression (e.g., lost interest; sadness; hopelessness), anxiety (e.g., restlessness; feeling tense). These negative affect have been mostly suggested to be concomitant of metal disorders such as positive psychosis symptoms and also of proneness to psychotic features in non-clinical population. Psychotic features proneness including hallucination, delusion and schizotypal traits, have been found to be associated with metacognitive beliefs. Metacognition has been conceptualized as ‘thinking about thoughts, monitoring and controlling of cognitive processes’. The aim of the current study was to investigate the role of psychosis proneness in the association of metacognitions and distress. We predicted psychosis proneness would mediate the association of metacognitive beliefs and the distress. A sample of 420 university students was randomly recruited to endorse questionnaires of the study that consisted of DASS-21questionnaire for assessing levels of distress, Cartwright–Hatton & Wells, Meta-cognitions Questionnaire (MCQ-30) for assessing metacognitive beliefs, Launay-Slade Hallucination Scale-revised (LSHS-R), Peters et al. Delusions Inventory, Schizotypal Personality Questionnaire-Brief. Conducting a bootstrapping approach in order to investigate our hypothesis, the result showed that there was no a direct association between metacognitive dimensions and psychological distress and psychosis proneness significantly mediated the association. Finding suggested that individuals with dysfunctional metacognitive beliefs experience high levels of distress if they are prone to psychosis symptoms. In other words, psychosis proneness is a path through which individuals with dysfunctional metacognitions experience high levels of psychological distress.

Keywords: metacognition, non-clinical population, psychological distress, psychosis proneness

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Authors: Usha Barahmand, Ruhollah Heydari Sheikh Ahmad, Sara Alaie Khoraem

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Introduction: The association of epilepsy with several psychological disorders and reduced quality of life has long been recognized. The present study aimed at comparing the personality profiles, quality of life and symptomatology of anxiety and depression in patients with epilepsy and healthy controls. Materials and Methods: Forty seven patients (29 men and 18 women) with diagnosed epilepsy participated in this study. Forty seven healthy controls who matched the patients in age and gender were also recruited. The participants’ personality and psychological profiles were assessed using the Depression, Anxiety, and Stress Scale (DASS-21), the Short-Form Health Survey (SF-36) and the HEXACO Personality Inventory (HEXACO-PI). Scoring algorithms were applied to the SF-36 produce the physical and mental component scores (PCS and MCS). Results: There were statistically significant differences in the total SF-36 score, anxiety, depression and stress scores of the DASS-21 between patients and controls. Anxiety, stress and depression scores significantly correlated inversely with the PCS and MCS. Data analysis showed that females had higher depression scores than males in both patients and controls, while males in both groups scored higher on stress. Patients’ personality scores were also different from those reported by controls on emotional, agreeableness and extroversion. Patients scored higher on emotionality, and lower on agreeableness and extraversion. Patients also scored lower on indices of quality of life. Regression analysis revealed that emotionality, anxiety, stress and MCS accounted for a significant proportion of the variance in severity of epileptic seizures. Conclusion: Stressful situations and psychological conditions as well as the personality trait of neuroticism were related to the occurrence of recurrent epileptic seizures.

Keywords: anxiety, depression, epilepsy, neuroticism, personality, quality of life, stress

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Shubham Dwivedi, Raghavender Medishetti, Rita Rani, Aarti Sevilimedu, Pushkar Kulkarni, Yogeeswari Perumal

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Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder of early onset, characterized by impaired sociability, cognitive function and stereotypies. There is a significant urge to develop and establish new animal models with ASD-like characteristics for better understanding of underlying mechanisms. The aim of the present study was to develop a cost and time effective zebrafish model with quantifiable parameters to facilitate mechanistic studies as well as high-throughput screening of new molecules for autism. Zebrafish embryos were treated with valproic acid and a battery of behavioral tests (anxiety, inattentive behavior, irritability and social impairment) was performed on larvae at 7th day post fertilization, followed by study of molecular markers of autism. This model shows a significant behavioural impairment in valproic acid treated larvae in comparison to control which was again supported by alteration in few marker genes and proteins of autism. The model also shows a rescue of behavioural despair with positive control drugs. The model shows robust parameters to study behavior, molecular mechanism and drug screening approach in a single frame. Thus we postulate that our 7 days zebrafish larval model for autism can help in high throughput screening of new molecules on autism.

Keywords: autism, zebrafish, valproic acid, neurodevelopment, behavioral assay

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Authors: Pooja Rani, G. S. Mahapatra, S. K. Pandey

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In this paper, we propose a novel approach of Neural Network and Particle Swarm Optimization methods for software reliability prediction. We first explain how to apply compound function in neural network so that we can derive a Flexible Logistic (S-shaped) Growth Curve (FLGC) model. This model mathematically represents software failure as a random process and can be used to evaluate software development status during testing. To avoid trapping in local minima, we have applied Particle Swarm Optimization method to train proposed model using failure test data sets. We drive our proposed model using computational based intelligence modeling. Thus, proposed model becomes Neuro-Particle Swarm Optimization (NPSO) model. We do test result with different inertia weight to update particle and update velocity. We obtain result based on best inertia weight compare along with Personal based oriented PSO (pPSO) help to choose local best in network neighborhood. The applicability of proposed model is demonstrated through real time test data failure set. The results obtained from experiments show that the proposed model has a fairly accurate prediction capability in software reliability.

Keywords: software reliability, flexible logistic growth curve model, software cumulative failure prediction, neural network, particle swarm optimization

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Authors: Sabitha Rani A., Nagamani V.

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Embelia ribes Burm.f (Family-Myrsinaceae) commonly known as Vidanga or Baibirang, is one of the important medicinal plants of India. The seed extract is reported to be antidiabetic, antitumour, analgesic, anti-inflammatory, antispermatogenic, free radical scavenging activities and widely used in more than 75 Ayurvedic commercial formulations. Among the 100 different species of Embelia, E. ribes is considered as a major source of Embelin, a bioactive compound. Because of high demand and low availability, the seeds of E. ribes are substituted with many cheaper alternatives. Therefore, the present study of RAPD-PCR analysis was undertaken to develop molecular markers for identification of E. ribes. A total of 13 different seed samples of Embelia were collected from different agro-climatic regions of India. The seeds of E.ribes were collected from Kalpetta, Kerala and three different seed samples were collected from traders of Odisha, Madhya Pradesh, Maharastra. The other nine seed samples were collected from local traders which they have collected from different regions of India. Genomic DNA was isolated from different seed samples E. ribes and RAPD-PCR was performed on 13 different seed samples using 47 random primers. Out of all the primers, only 22 primers produced clear and highly-reproducible banding patterns. The 22 selected RAPD primers generated a total of 280 alleles with an average of 12 alleles per primer pair. In the present study, we have identified three RAPD-PCR markers i.e. OPF5_480 bp, OPH11_520 bp and OPH4_530 bp which can be used for genetic fingerprinting of E. ribes. This methodology can be employed for identification of original E. ribes and also distinguishing it from other substitutes and adulterants.

Keywords: Embelia ribes, RAPD-PCR, primers, genetic analysis

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Authors: Jyoti Rani, Ashima Anand, Shivendra Shivani

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In recent years, physiological signals obtained in telemedicine have been stored independently from patient information. In addition, people have increasingly turned to mobile devices for information on health-related topics. Major authentication and security issues may arise from this storing, degrading the reliability of diagnostics. This study introduces an approach to reversible watermarking, which ensures security by utilizing the electrocardiogram (ECG) signal as a carrier for embedding patient information. In the proposed work, Pan-Tompkins++ is employed to convert the 1D ECG signal into a 2D signal. The frequency subbands of a signal are extracted using RDWT(Redundant discrete wavelet transform), and then one of the subbands is subjected to MSVD (Multiresolution singular valued decomposition for masking. Finally, the encrypted watermark is embedded within the signal. The experimental results show that the watermarked signal obtained is indistinguishable from the original signals, ensuring the preservation of all diagnostic information. In addition, the DnCNN (Denoising convolutional neural network) concept is used to denoise the retrieved watermark for improved accuracy. The proposed ECG signal-based watermarking method is supported by experimental results and evaluations of its effectiveness. The results of the robustness tests demonstrate that the watermark is susceptible to the most prevalent watermarking attacks.

Keywords: ECG, VMD, watermarking, PanTompkins++, RDWT, DnCNN, MSVD, chaotic encryption, attacks

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Authors: Triveni Gogoi, Rima Chatterjee

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Shear wave velocity (Vs) estimation is an important approach in the seismic exploration and characterization of a hydrocarbon reservoir. There are varying methods for prediction of S-wave velocity, if recorded S-wave log is not available. But all the available methods for Vs prediction are empirical mathematical models. Shear wave velocity can be estimated using P-wave velocity by applying Castagna’s equation, which is the most common approach. The constants used in Castagna’s equation vary for different lithologies and geological set-ups. In this study, multiple regression analysis has been used for estimation of S-wave velocity. The EMERGE module from Hampson-Russel software has been used here for generation of S-wave log. Both single attribute and multi attributes analysis have been carried out for generation of synthetic S-wave log in Upper Assam basin. Upper Assam basin situated in North Eastern India is one of the most important petroleum provinces of India. The present study was carried out using four wells of the study area. Out of these wells, S-wave velocity was available for three wells. The main objective of the present study is a prediction of shear wave velocities for wells where S-wave velocity information is not available. The three wells having S-wave velocity were first used to test the reliability of the method and the generated S-wave log was compared with actual S-wave log. Single attribute analysis has been carried out for these three wells within the depth range 1700-2100m, which corresponds to Barail group of Oligocene age. The Barail Group is the main target zone in this study, which is the primary producing reservoir of the basin. A system generated list of attributes with varying degrees of correlation appeared and the attribute with the highest correlation was concerned for the single attribute analysis. Crossplot between the attributes shows the variation of points from line of best fit. The final result of the analysis was compared with the available S-wave log, which shows a good visual fit with a correlation of 72%. Next multi-attribute analysis has been carried out for the same data using all the wells within the same analysis window. A high correlation of 85% has been observed between the output log from the analysis and the recorded S-wave. The almost perfect fit between the synthetic S-wave and the recorded S-wave log validates the reliability of the method. For further authentication, the generated S-wave data from the wells have been tied to the seismic and correlated them. Synthetic share wave log has been generated for the well M2 where S-wave is not available and it shows a good correlation with the seismic. Neutron porosity, density, AI and P-wave velocity are proved to be the most significant variables in this statistical method for S-wave generation. Multilinear regression method thus can be considered as a reliable technique for generation of shear wave velocity log in this study.

Keywords: Castagna's equation, multi linear regression, multi attribute analysis, shear wave logs

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Authors: Kulwinder Singh Mann, Manmohan Singh Heer, Asha Rani

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The safe storage of radioactive materials has become an important issue. Nuclear engineering necessitates the safe handling of radioactive materials emitting high energy gamma-rays. Hazards involved in handling radioactive materials insist suitable shielded enclosures. With overgrowing use of nuclear energy for meeting the increasing demand of power, there is a need to investigate the shielding behavior of cost effective shielded enclosure (CESE) made from clay-bricks (CB) and fire-bricks (FB). In comparison to the lead-bricks (conventional-shielding), the CESE are the preferred choice in nuclear waste management. The objective behind the present investigation is to evaluate the double layered transmission exposure buildup factors (DLEBF) for gamma-rays for CESE in energy range 0.5-3MeV. For necessary computations of shielding parameters, using existing huge data regarding gamma-rays interaction parameters of all periodic table elements, two computer programs (GRIC-toolkit and BUF-toolkit) have been designed. It has been found that two-layered slabs show effective shielding for gamma-rays in orientation CB followed by FB than the reverse. It has been concluded that the arrangement, FB followed by CB reduces the leakage of scattered gamma-rays from the radioactive source.

Keywords: buildup factor, clay bricks, fire bricks, nuclear wastage management, radiation protective double layered slabs

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Authors: Chandra Sekhar Singh, P. Chakrapani, B. Arun Jyothi, A. Roja Rani

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The green synthesis of metallic nanoparticles (NPs) involves biocompatible ingredients under physiological conditions of temperature and pressure. Moreover, the biologically active molecules involved in the green synthesis of NPs act as functionalizing ligands, making these NPs more suitable for biomedical applications. Among the most important bioreductants are plant extracts, which are relatively easy to handle, readily available, low cost, and have been well explored for the green synthesis of other nanomaterials. Various types of metallic NPs have already been synthesized using plant extracts. They have wide applicability in various areas such as electronics, catalysis, chemistry, energy, and medicine. Metallic nanoparticles are traditionally synthesized by wet chemical techniques, where the chemicals used are quite often toxic and flammable. In our study, we were described a cost effective and environment friendly technique for green synthesis of silver nanoparticles from 1mM AgNO3 solution through the aqueous extract of Erythrina indica as reducing as well as capping agent. Nanoparticles were characterized using UV–Vis absorption spectroscopy, FTIR, XRD, X-ray diffraction, SEM and TEM analysis showed the average particle size of 30 nm as well as revealed their spherical structure. Further these biologically synthesized nanoparticles were found to be highly toxic against different human pathogens viz. two Gram positive namely Klebsiella pneumonia and Bacillus subtilis bacteria and two were Gram negative bacteria namely Staphylococcus aureus and Escherichia coli (E. coli). This is for the first time reporting that Erythrina indica plant extract was used for the synthesis of nanoparticles.

Keywords: silver nanoparticles, green synthesis, antibacterial activity, FTIR, TEM, SEM

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Authors: Wan Azuati Wan Omar, Selva Rani John Jasudass, Siti Rohaiza Md. Saad

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Introduction & objective: The objectives of this study were to assess patient’s knowledge of appropriate sublingual glyceryl trinitrate (GTN) use as well as to investigate how patients commonly store and carry their sublingual GTN tablets. Methodology: This was a cross-sectional survey, using a validated researcher-administered questionnaire. The study involved cardiac patients receiving sublingual GTN attending the outpatient and inpatient departments of Taiping Hospital, a non-academic public care hospital. The minimum calculated sample size was 92, but 100 patients were conveniently sampled. Respondents were interviewed on 3 areas, including demographic data, knowledge and use of sublingual GTN. Eight items were used to calculate each subject’s knowledge score and six items were used to calculate use score. Results: Of the 96 patients who consented to participate, majority (96.9%) were well aware of the indication of sublingual GTN. With regards to the mechanism of action of sublingual GTN, 73 (76%) patients did not know how the medication works. Majority of the patients (66.7%) knew about the proper storage of the tablet. In relation to the maximum number of sublingual GTN tablets that can be taken during each angina episode, 36.5% did not know that up to 3 tablets of sublingual GTN can be taken during each episode of angina. Fifty four (56.2%) patients were not aware that they need to replace sublingual GTN every 8 weeks after receiving the tablets. Majority (69.8%) of the patients demonstrated lack of knowledge with regards to the use of sublingual GTN as prevention of chest pain. Conclusion: Overall, patients’ knowledge regarding the self administration of sublingual GTN is still inadequate. The findings support the need for more frequent reinforcement of patient education, especially in the areas of preventive use, storage and drug stability.

Keywords: glyceryl trinitrate, knowledge, adherence, patient education

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Authors: Rezvan Ravanfar Haghighi, S. Chatterjee, Pratik Kumar, V. C. Vani, Priya Jagia, Sanjiv Sharma, Susama Rani Mandal, R. Lakshmy

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The dual energy computed tomography (DECT) aims at noting the HU(V) values for the sample at two different voltages V=V1, V2 and thus obtain the electron densities (ρe) and effective atomic number (Zeff) of the substance. In the present paper, we aim to obtain a numerical algorithm by which (ρe, Zeff) can be obtained from the HU(100) and HU(140) data, where V=100, 140 kVp. The idea is to use this inversion method to characterize and distinguish between the lipid and fibrous coronary artery plaques.With the idea to develop the inversion algorithm for low Zeff materials, as is the case with non calcified coronary artery plaque, we prepare aqueous samples whose calculated values of (ρe, Zeff) lie in the range (2.65×1023≤ ρe≤ 3.64×1023 per cc ) and (6.80≤ Zeff ≤ 8.90). We fill the phantom with these known samples and experimentally determine HU(100) and HU(140) for the same pixels. Knowing that the HU(V) values are related to the attenuation coefficient of the system, we present an algorithm by which the (ρe, Zeff) is calibrated with respect to (HU(100), HU(140)). The calibration is done with a known set of 20 samples; its accuracy is checked with a different set of 23 known samples. We find that the calibration gives the ρe with an accuracy of ± 4% while Zeff is found within ±1% of the actual value, the confidence being 95%.In this inversion method (ρe, Zeff) of the scanned sample can be found by eliminating the effects of the CT machine and also by ensuring that the determination of the two unknowns (ρe, Zeff) does not interfere with each other. It is found that this algorithm can be used for prediction of chemical characteristic (ρe, Zeff) of unknown scanned materials with 95% confidence level, by inversion of the DECT data.

Keywords: chemical composition, dual-energy computed tomography, inversion algorithm

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Authors: Rani Silvia

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English has surpassed other languages to become the most widely taught and studied foreign language in Indonesia. This reflects the tendency of the Indonesian public to participate in global mainstream culture, which is longstanding but has been greatly facilitated by the widespread availability of television, the traditional media, and more recently the Internet and social media. However, despite increasing exposure and a history of teaching and study, mastery of English remains low, even as interest and perceived importance continue to increase. This along with Indonesia’s extremely complex linguistic environment has increased the status and value associated with the use of English and is changing the dynamic of language use nationwide. This study investigates the use of English in public settings in Indonesia as well as the attitudes of Indonesian speakers towards English. A case study was developed to explicate this phenomenon in a major Indonesian city. Fifty individuals, including both professionals and lay people, were interviewed about their language preferences as well as their perceptions about English as compared to other languages, such as the local language, Indonesian as the national language, and other foreign languages. Observations on the use of language in the public environment in advertising, signs, and other forms of public expression were analyzed to identify language preferences at this level and their relationship to current language policy. This study has three major findings. First, Indonesian speakers have more positive attitudes towards English than other languages; second, English has encroached on domains in which Indonesian should be used; and third, perceived awareness of the importance of Indonesian as an introduced national language seems to be declining to suggest a failure of policy. The study includes several recommendations for the future development of language planning in determining and directing language use in a public context in Indonesia.

Keywords: English, Indonesia, language attitudes, language policy

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Authors: Anupalli Roja Rani, Saraswathi Jaggali

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Rose-scented geranium (Pelargonium graveolens L’Hér.) is an erect, much-branched shrub. It is indigenous to various parts of southern Africa, and it is often called Geranium. Pelargonium species are widely used by traditional healers in the areas of Southern Africa by Sotho, Xhosa, Khoi-San and Zulus for its curative and palliative effects in the treatment of diarrhea, dysentery, fever, respiratory tract infections, liver complaints, wounds, gastroenteritis, haemorrhage, kidney and bladder disorders. We have used Plant materials for extracting active compounds from analytical grades of solvents methanol, ethyl acetate, chloroform and water by a soxhlet apparatus. The phytochemical screening reveals that extracts of Pelargonium graveolens contains alkaloids, glycosides, steroids, tannins, saponins and phenols in ethyl acetate solvent. The antioxidant activity was determined using 1, 1-diphenyl-2-picrylhydrazyl (DPPH) bleaching method and the total phenolic content in the extracts was determined by the Folin–Ciocalteu method. Due to the presence of different phytochemical compounds in Pelargonium the anti-microbial activity against different micro-organisms like E.coli, Streptococcus, Klebsiella and Bacillus. Fractionation of plant extract was performed by column chromatography and was confirmed with HPLC analysis, NMR and FTIR spectroscopy for the compound identification in different organic solvent extracts.

Keywords: Pelargonium graveolens L’Hér, DPPH, micro-organisms, HPLC analysis, NMR, FTIR spectroscopy

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Authors: Rani Danavath, V. B. Narsimha

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Cloud computing is emerging as a new paradigm of large scale distributed computing. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., three service models, and four deployment networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics models. Load balancing is one of the main challenges in cloud computing, which is required to distribute the dynamic workload across multiple nodes, to ensure that no single node is overloaded. It helps in optimal utilization of resources, enhancing the performance of the system. The goal of the load balancing is to minimize the resource consumption and carbon emission rate, that is the direct need of cloud computing. This determined the need of new metrics energy consumption and carbon emission for energy-efficiency load balancing techniques in cloud computing. Existing load balancing techniques mainly focuses on reducing overhead, services, response time and improving performance etc. In this paper we introduced a Technique for energy-efficiency, but none of the techniques have considered the energy consumption and carbon emission. Therefore, our proposed work will go towards energy – efficiency. So this energy-efficiency load balancing technique can be used to improve the performance of cloud computing by balancing the workload across all the nodes in the cloud with the minimum resource utilization, in turn, reducing energy consumption, and carbon emission to an extent, which will help to achieve green computing.

Keywords: cloud computing, distributed computing, energy efficiency, green computing, load balancing, energy consumption, carbon emission

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Authors: Ravi Kiran Pothamsetty, Radha Rani Ghosh, Baby Paul Thaliath

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Radiation therapy has undergone many advancements and evloved from 2D to 3D. Recently, with rapid pace of drug discoveries, cutting edge technology, and clinical trials has made innovative advancements in computer technology and treatment planning and upgraded to intensity modulated radiotherapy (IMRT) which delivers in homogenous dose to tumor and normal tissues. The present study was a hospital-based experience comparing two different conformal radiotherapy techniques for brain tumors. This analytical study design has been conducted at Regional Cancer Centre, India from January 2014 to January 2015. Ten patients have been selected after inclusion and exclusion criteria. All the patients were treated on Artiste Siemens Linac Accelerator. The tolerance level for maximum dose was 6.0 Gyfor lenses and 54.0 Gy for brain stem, optic chiasm and optical nerves as per RTOG criteria. Mean and standard deviation values of PTV98%, PTV 95% and PTV 2% in IMRT were 93.16±2.9, 95.01±3.4 and 103.1±1.1 respectively; for 3DCRT were 91.4±4.7, 94.17±2.6 and 102.7±0.39 respectively. PTV max dose (%) in IMRT and 3D-CRT were 104.7±0.96 and 103.9±1.0 respectively. Maximum dose to the tumor can be delivered with IMRT with acceptable toxicity limits. Variables such as expertise, location of tumor, patient condition, and TPS influence the outcome of the treatment.

Keywords: brain tumors, intensity modulated radiotherapy (IMRT), three dimensional conformal radiotherapy (3D-CRT), radiation therapy oncology group (RTOG)

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Authors: Arun Jyothi Bheemagani, Chakrapani Pullagummi, Anupalli Roja Rani

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Exploration of the chemical constituents of the plants and pharmacological screening may provide us the basis for the development of novel agents. Plants have provided us some of the very important life saving drugs used in the modern medicine. The aim of our work was to screen the phytochemical constituents and antimicrobial and antioxidant activities of methanol extract of leaves of Annona cherimola Mill plant from Tirumala forest, Tirupathi. It was originally called Chirimuya by the Inca people who lived where it was growing in the Andes of South America, is an edible fruit-bearing species of the genus Annona from the family Annonaceae. Annona cherimola Mill is a multipurpose tree with edible fruits and is one of the sources of the medicinal products. The antibacterial activity was measured by agar well diffusion method; the diameter of the zone of bacterial growth inhibition was measured after incubation of plates. The inhibitory effect was studied against the pathogenic bacteria (Klebsiella pneumonia, Bacillus subtilis, Staphylococcus aureus and Escherichia coli (E. coli). Antioxidant assays were also performed for the same extracts by spectrophotometric methods using known standard antioxidants as reference. The studied plant extracts were found to be very effective against the pathogenic microorganisms tested. The methanolic extract of Annona cherimola Mill from showed maximum activity against Escherichia coli and Staphylococcus aureus and the least concentration required showing the activity was 0.5mg/ml. Phytochemical screening of the plants revealed the presence of flavonoids, alkaloids, steroids and carbohydrates. Good presence of antioxidants was also found in the methanolic extracts.

Keywords: annona cherimola, phytochemicals, antioxidant and antibacterial activity, methanol extract

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Authors: V. P. Muhamed Shajudheen, K. Viswanathan, K. Anitha Rani, A. Uma Maheswari, S. Saravana Kumar

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We are reporting a simple and low-cost chemical precipitation method adopted to prepare zinc oxide nanoparticles (ZnO) using polyvinyl pyrrolidone (PVP) as a capping agent. The Differential Scanning Calorimetry (DSC) and Thermo Gravimetric Analysis (TGA) was applied on the dried gel sample to record the phase transformation temperature of zinc hydroxide Zn(OH)2 to zinc oxide (ZnO) to obtain the annealing temperature of 800C. The thermal, structure, morphology and optical properties have been employed by different techniques such as DSC-TGA, X-Ray Diffraction (XRD), Fourier Transform Infra-Red spectroscopy (FTIR), Micro Raman spectroscopy, UV-Visible absorption spectroscopy (UV-Vis), Photoluminescence spectroscopy (PL) and Field Effect Scanning Electron Microscopy (FESEM). X-ray diffraction results confirmed the wurtzite hexagonal structure of ZnO nanoparticles. The two intensive peaks at 160 and 432 cm-1 in the Raman Spectrum are mainly attributed to the first order modes of the wurtzite ZnO nanoparticles. The energy band gap obtained from the UV-Vis absorption spectra, shows a blue shift, which is attributed to increase in carrier concentration (Burstein Moss Effect). Photoluminescence studies of the single crystalline ZnO nanoparticles, show a strong peak centered at 385 nm, corresponding to the near band edge emission in ultraviolet range. The mixed shape of grapes, sphere, hexagonal and rock like structure has been noticed in FESEM. The results showed that PVP is a suitable capping agent for the preparation of ZnO nanoparticles by simple chemical precipitation method.

Keywords: ZnO nanoparticles, simple chemical precipitation route, mixed shape morphology, UV-visible absorption, photoluminescence, Fourier transform infra-Red spectroscopy

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Authors: Joshna Rani S., Ahmadi Banu

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Artificial Intelligence (AI) has a significant task to carry out in the medical care contributions of things to come. As AI, it is the essential capacity behind the advancement of accuracy medication, generally consented to be a painfully required development in care. Albeit early endeavors at giving analysis and treatment proposals have demonstrated testing, we anticipate that AI will at last dominate that area too. Given the quick propels in AI for imaging examination, it appears to be likely that most radiology, what's more, pathology pictures will be inspected eventually by a machine. Discourse and text acknowledgment are now utilized for assignments like patient correspondence and catch of clinical notes, and their utilization will increment. The best test to AI in these medical services areas isn't regardless of whether the innovations will be sufficiently skilled to be valuable, but instead guaranteeing their appropriation in day by day clinical practice. For far reaching selection to happen, AI frameworks should be affirmed by controllers, coordinated with EHR frameworks, normalized to an adequate degree that comparative items work likewise, instructed to clinicians, paid for by open or private payer associations, and refreshed over the long haul in the field. These difficulties will, at last, be survived, yet they will take any longer to do as such than it will take for the actual innovations to develop. Therefore, we hope to see restricted utilization of AI in clinical practice inside 5 years and more broad use inside 10 years. It likewise appears to be progressively evident that AI frameworks won't supplant human clinicians for a huge scope, yet rather will increase their endeavors to really focus on patients. Over the long haul, human clinicians may advance toward errands and work plans that draw on remarkably human abilities like sympathy, influence, and higher perspective mix. Maybe the lone medical services suppliers who will chance their professions over the long run might be the individuals who will not work close by AI

Keywords: artificial intellogence, health care, breast cancer, AI applications

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Authors: Kalsoom Rani

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Tobacco contains nicotine, which causes addiction to many toxic chemicals. In the world, people consume it in the form of smoke, chew, and sniffing, smoke of it is composed of almost 7000 active chemicals, which are very harmful to human health as well as for eye health, inhalation of tobacco smoke and fumes can accelerate and cause many blinding eye diseases. Dry eye and smoking have not been covered extensively in researches; more studies are required to unveil the relationship between smoking and dry eye. This study was conducted to determine the quantity and quality of tears in smokers. 60 subjects participated in the study, which was divided into two groups on the basis of consumption of cigarettes per day with age matched non smokers of 15-50 years. All participants have gone through a study based questioner, eye examination, and diagnostic 'Dry Eye Tests' for evaporative tears evaluation and measurement of basal tear secretion. Subjects were included in the criteria of 10 cigarettes per day with a minimum duration of 1 year; passive smokers for control groups were excluded. The study was carried out in a Medina Teaching Hospital, Faisalabad, Pakistan, ophthalmology department for the duration of 8 months. Mean values for tear break up time (TBUT), was reported 10sec with SD of +3.74 in controlled group, 5sec with SD + 2.32 in smokers and 4sec SD +3.77 heavy smokers in right eye (RE) and left eye (LE) 10.35sec with SD of +3.88 in controlled 5sec with SD + 2.3 in smokers and much reduced TBUT in heavy smokers was 3.85sec SD+2.20. Smoking has a very strong association with TRUT with a significance of P=.00 both eyes. Mean Schirmer-I value of the subjects was reported 12.6mm with SD + 8.37 in RE and 12.59mm with SD + 8.96 LE. The mean Schirmer-II test value was reported in the right, and left eye with a mean value for control was 20.23mm with SD + 8.93, 20.75mm with SD + 8.84 respectively, and in Smokers 9.90mm with SD + 5.74, and 10.07mm with SD + 6.98, and in heavy smokers 7.7mm, SD + 3.22 and 6.9, SD + 3.50 mm, association with smoking showed p=.001 in RE and .003 in LE. Smoking has deteriorated effect on both evaporative tear and aqueous tear secretion and causing symptoms of dry eye burning, itching, redness, and watering with epithelial cell damage.

Keywords: tear break-up time, basal tear secretion, smokers, dry eye

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Authors: Usha Dinakaran, Richa Ganguly

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Gastronomic tourism has evolved into a prominent niche within the travel industry, with tourists increasingly seeking unique culinary experiences as a primary motivation for their journeys. This research explores the intricate relationship between gastronomic tourism and its profound influence on the overall image of travel destinations. It delves into the multifaceted aspects of culinary experiences, tourists' perceptions, and the preservation of cultural identity, all of which play pivotal roles in shaping a destination's image. The primary aim of this study is to comprehensively examine the interplay between gastronomy and tourism, specifically focusing on its impact on destination image. The research seeks to achieve the following objectives: (1) Investigate how tourists perceive and engage with gastronomic tourism experiences. (2) Understand the significance of food in shaping the tourism image. (3.) Explore the connection between gastronomy and the destination's cultural identity Quantify the relationship between tourists' engagement in co-creation activities related to gastronomic tourism and their overall satisfaction with the quality of their culinary experiences. To achieve these objectives, a mixed-method research approach will be employed, including surveys, interviews, and content analysis. Data will be collected from tourists visiting diverse destinations known for their culinary offerings. This research anticipates uncovering valuable insights into the nexus between gastronomic tourism and destination image. It is expected to shed light on how tourists' perceptions of culinary experiences impact their overall perception of a destination. Additionally, the study aims to identify factors influencing tourist satisfaction and how cultural identity is preserved and promoted through gastronomic tourism. The findings of this research hold practical implications for destination marketers and stakeholders. Understanding the symbiotic relationship between gastronomy and tourism can guide the development of more targeted marketing strategies. Furthermore, promoting co-creation activities can enhance tourists' culinary experiences and contribute to the positive image of destinations.This study contributes to the growing body of knowledge regarding gastronomic tourism by consolidating insights from various studies and offering a comprehensive perspective on its impact on destination image. It offers a platform for future research in this domain and underscores the importance of culinary experiences in contemporary travel. In conclusion, this research endeavors to illuminate the dynamic interplay between gastronomic tourism and destination image, providing valuable insights for both academia and industry stakeholders in the field of tourism and hospitality.

Keywords: gastronomy, tourism, destination image, culinary

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Authors: Daya Rani

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Non-metal-based compounds have emerged as promising electrodes in recent years to replace scarce and expensive transition-metals for energy storage applications. Herein, a simple electro-spinning technique followed by carbonization is used to create tetraphosphorus triselenide(P4Se3)nano-flakes encapsulated in carbon nanofiber (P4Se3@CNF) to obtain a binder-free, metal-free and flexible hybrid electrode with high electrical conductivity and cyclic stability. A remarkable capacitive performance (5.5-folds@P4Se3) of 810Fg-1/[email protected] has been obtained using P4Se3@CNF electrode with an excellent rate capability compared to pristine(P4Se3) which is further supported by theoretical calculations via intercalating graphene within bare P4Se3 flakes inducing partial charge redistribution in hetero-structure. A flexible pouch-type hybrid-supercapacitor followed by coin-cell has been manufactured offering exceptional energy-density without sacrificing power density and ultra-long durability over 35000 and 100000-cycles with capacitance-retention of 99.77% and 100%, respectively. It has been demonstrated that as-fabricated device has practical usefulness towards renewable energy harvesting and storage via integrating commercial solar cell module with supercapattery array that can enlighten the blue LED approximately for 31minutes, rotate the homemade windmill device, power Arduino and glow “INST” against 2minutes of charging. This work demonstrates a facile route towards the development of metal-free electrochemical renewable energy storage/transfer devices offering an inevitable adoption in industrial platforms.

Keywords: metal free, carbon nano-fiber, pouch-type hybrid super-capacitor, nano-flakes

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Authors: Rani Fernandez

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As global concerns regarding environmental degradation and climate change intensify, the imperative for sustainable living has never been more critical. This research delves into the role of eco-products in everyday life as a pivotal strategy for achieving sustainability. The study investigates the awareness, adoption, and impact of eco-friendly products on individual and community levels. The research employs a mixed-methods approach, combining surveys, interviews, and case studies to explore consumer perceptions, behaviours, and motivations surrounding the use of eco-products. Additionally, life cycle assessments are conducted to evaluate the environmental footprint of selected eco-products, shedding light on their tangible contributions to sustainability. The findings reveal the diverse range of eco-products available in the market, from biodegradable packaging to energy-efficient appliances, and the extent to which consumers integrate these products into their daily routines. Moreover, the research examines the challenges and opportunities associated with widespread adoption, considering factors such as cost, accessibility, and efficacy. In addition to individual consumption patterns, the study investigates the broader societal impact of eco-product integration. It explores the potential for eco-products to drive systemic change by influencing supply chains, corporate practices, and government policies. The research highlights successful case studies of communities or businesses that have effectively incorporated eco-products, providing valuable insights into scalable models for sustainability. Ultimately, this research contributes to the discourse on sustainable living by elucidating the pivotal role of eco-products in shaping environmentally conscious behaviours. By understanding the dynamics of eco-product adoption, policymakers, businesses, and individuals can collaboratively work towards a more sustainable future. The implications of this study extend beyond academia, informing practical strategies for fostering a global shift towards sustainable consumption and production.

Keywords: eco-friendly, sustainablity, environment, climate change

Procedia PDF Downloads 40

Authors: Alok Kumar Yadav, Saurabh Saraswat, Preeti Sirohi, Manjoo Rani, Sameer Srivastava, Manish Pratap Singh, Nand K. Singh

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The development of antibiotic resistance in bacteria is increasing at an alarming rate, and this is considered as one of the most serious threats in the history of medicine, and an alternative solution should be derived so as to tackle this problem. In many countries, people use the medicinal plants for the treatment of various diseases as these are cheaper, easily available and least toxic. Syzygium cumini is used for the treatment of various kinds of diseases but their mechanism of action is not reported. The antimicrobial activity of Syzygium cumini was tested by the well diffusion assay and zone of inhibition was reported to be 20.06 mm as compared to control with MIC of 0.3 mg/ml. Genomic DNA fragmentation of Bacillus subtilis revealed apoptosis and FE-SEM indicate cell wall cracking on several intervals of time. Propidium iodide staining results showed that few bacterial cells were stained in the control and population of stained cells increase after exposing them for various period of time. Flow cytometric kinetic data analysis on the membrane permeabilization in bacterial cell showed the significant contribution of antimicrobial potential of the seed extract on antimicrobial-induced permeabilization. Two components of Syzygium cumini methanolic seed extract was found to be quite active against four enzymes like PDB ID- 1W5D, 4OX3, 3MFD and 5E2F which have a very crucial role in membrane synthesis in Bacillus subtilis by in silico analysis. Through in silico analysis, lupeol showed highest binding energy for macromolecule 1W5D and 4OX3 whereas stigmasterol showed the highest binding energy for macromolecule 3MFD and 5E2F respectively. It showed that methanolic seed extract of Syzygium cumini can be used for the inhibition of foodborne infections caused by Bacillus subtilis and also as an alternative of prevalent antibiotics.

Keywords: antibiotics, Bacillus subtilis, inhibition, Syzygium cumini

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Authors: V. P. Muhamed Shajudheen, K. Viswanathan, K. Anitha Rani, A. Uma Maheswari, S. Saravana Kumar

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In this paper, a simple chemical precipitation route for the preparation of titanium dioxide nanoparticles, synthesized by using titanium tetra isopropoxide as a precursor and polyvinyl pyrrolidone (PVP) as a capping agent, is reported. The Differential Scanning Calorimetry (DSC) and Thermo Gravimetric Analysis (TGA) of the samples were recorded and the phase transformation temperature of titanium hydroxide, Ti(OH)₄ to titanium oxide, TiO₂ was investigated. The as-prepared Ti(OH)₄ precipitate was annealed at 800°C to obtain TiO₂ nanoparticles. The thermal, structural, morphological and textural characterizations of the TiO₂ nanoparticle samples were carried out by different techniques such as DSC-TGA, X-Ray Diffraction (XRD), Fourier Transform Infra-Red spectroscopy (FTIR), Micro Raman spectroscopy, UV-Visible absorption spectroscopy (UV-Vis), Photoluminescence spectroscopy (PL) and Field Effect Scanning Electron Microscopy (FESEM) techniques. The as-prepared precipitate was characterized using DSC-TGA and confirmed the mass loss of around 30%. XRD results exhibited no diffraction peaks attributable to anatase phase, for the reaction products, after the solvent removal. The results indicate that the product is purely rutile. The vibrational frequencies of two main absorption bands of prepared samples are discussed from the results of the FTIR analysis. The formation of nanosphere of diameter of the order of 10 nm, has been confirmed by FESEM. The optical band gap was found by using UV-Visible spectrum. From photoluminescence spectra, a strong emission was observed. The obtained results suggest that this method provides a simple, efficient and versatile technique for preparing TiO₂ nanoparticles and it has the potential to be applied to other systems for photocatalytic activity.

Keywords: TiO2 nanoparticles, chemical precipitation route, phase transition, Fourier Transform Infra-Red spectroscopy (FTIR), micro-Raman spectroscopy, UV-Visible absorption spectroscopy (UV-Vis), Photoluminescence Spectroscopy (PL) and Field Effect Scanning electron microscopy (FESEM)

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Authors: Chakrapani Pullagummi, Arun Jyothi Bheemagani, B. Chandra Sekhar Singh, Prem Kumar, A. Roja Rani

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Diabetes mellitus describes a metabolic disorder of multiple aetiology characterized by chronic hyperglycaemia with disturbances of carbohydrate, fat and protein metabolism resulting from defects in insulin secretion and its action. The objective of present study was alloxan induced diabetes in S.D (Sprague Dawley) rats, treated with leaf extract of Andrographis paniculata and bark extract of Erythrina indica. Plant extract treated rats were analyzed biochemically and molecularly. on normal and diabetic rats. The changes in MDA (lipid peroxidation) and glucose (by GOD method) levels in blood of both normal and diabetic rat were analyzed. Diabetes induced rats were treated with methanolic extracts of Andrographis paniculata leaf and Erythrina indica bark which are of medicinal importance. Later after inducing diabetes the rats were treated with medicinal plant extracts, Andrographis paniculata leaf and Erythrina indica bark which are well known for their anti diabetic and antioxidative property in order to control the glucose and MDA levels. The blood plasma of diabetic and normal rats was analyzed for the levels of MDA (lipid peroxidation) and glucose levels. Results of this study suggested that the Andrographis paniculata leaf and Erythrina indica can be used as a potential natural antidiabetic agent for treating and postponing the appearance of complications that arise due to Diabetes. Molecular study deals with the analysis of binding mechanism of 2 selected natural compounds from Andrographis and Erythrina extracts against the novel target for type T2D namely PPAR-γ compared with Rosiglitazone (standard compound). The results revealed that most of the selected herbal lead compounds were effective targets against the receptors. These compounds showed favorable interactions with the amino acid residues thereby substantiating their proven efficacy as anti-diabetic compounds.

Keywords: andrographis paniculata, erythrina indica, alloxan, lipid peroxidation, blood glucose level, PPAR-γ

Procedia PDF Downloads 476

Authors: Mohd Zaki Hamzah, Roslan Rani, Ahmad Bazli Razali, Satiful Bahri Mamat, Abdul Hadi Ripin, Mohd Harun Esa

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Ever since 1901, forest management and silviculture practices in Malaysia have been frequently reviewed and updated to take into account changes in forest conditions, markets, timber demand/supply and technical advances that can be achieved in industrial processes, logging and forest harvesting, and currently, the forest management system practiced in Peninsular Malaysia is the Selective Management System (SMS) which was introduced in 1978. This system requires the selection of management regime (felling) based on Pre-Felling Forest Inventory (Pre-F) data to ensure economical harvesting and also ensuring adequate standing stands for subsequent rounds of felling, while maintaining ecological balance and environmental quality. SMS regulates forest harvesting through area and volume controls, with the cutting cycle 30 years. Most of the forest management units (FMU) (in Peninsular Malaysia) implementing SMS have been certified by Forest Stewardship Council (FSC) and/or Program for Endorsement of Forest Certification (PEFC), and one such FMU belongs to Kumpulan Pengurusan Kayu Kayan Terengganu (KPKKT). KPKKT, a timber management subsidiary of Golden Pharos Berhad (GPB), adopts the SMS to manage its 108,900 ha of timber concessionary areas in its role as logs’ supplier for the consumption of three subsidiaries of GPB. KPKKT is also responsible for the sustainable development and management of its concession in accordance with the Sustainable Forest Management (SFM) standards to ensure that it addresses the loss of forest cover and forest degradation, forest-based economic, social and environmental benefits, and ecologically protecting forests while mobilising financial resources for the implementation of sustainable forest management planning, harvesting, monitoring and the marketing of products. This paper will detail out the management and harvesting guidelines imposed by the controlling government agency, and harvesting processes taken by KPKKT to comply with guidelines and eventually supplying timber to the relevant subsidiaries (downstream mills under GPB).

Keywords: sustainable forest management, silviculture, reduce impact logging, forest certification

Procedia PDF Downloads 99

Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

Procedia PDF Downloads 418