Addition of chemical binders such as lime and cement improves the strength and stiffness of fine grained soils. However, the treated soils exhibit brittle stress-strain behaviour. Inclusion of randomly oriented discrete fibers in the soil-binder mixture changes its brittle behaviour into ductile behaviour. Most synthetic fibers, however, tend to get entangled and cannot be easily separated from one another. Therefore, it is difficult to realize soil-binder-fiber mixtures in which the fibers are distributed uniformly throughout the mass. This issue has been an impediment in the utilization of the positive modification in the behaviours of soils and soil-binder mixtures by the fibers. The present study aims to address the limitations in using fibers as soil reinforcement. Further, it also aims to investigate the use of synthetic mesh or net elements as an alternative type of soil reinforcement. The paper presents the experimental study on a fine grained soil. Lime has been chosen as the binder due to its low cost and the scarcity of fiber reinforced soil studies in which lime has been used as a binder. The main experimental program is a series of unconfined compression tests on samples prepared using untreated soil, soil-reinforcement mixture, soil-lime mixture, and soil-lime-reinforcement mixture. The lime treated samples were cured up to 120 days at laboratory temperature. The results demonstrate the combinational effects of lime and discrete reinforcement elements on the behaviour and mechanical properties of the soil. The performances of the fiber and mesh element reinforcements have also been compared.
Educational videos are one of the best means of imparting knowledge to the users/learners. Videos can convey information in an effective and interesting manner. These videos can be accessed through online or from stored repositories using queries. Search queries play important role in the retrieval. Whenever a user gives an ambiguous query, the search engine may produce irrelevant results. Thus a lot of time is being spent by the users in retrieving the relevant videos. In order to improve the probability of retrieving relevant results, semantic web technologies are applied. This paper aims to extract keywords from the videos and to find the association between the extracted terms. The associated terms are arranged based on their frequency of occurrences. These terms are used to annotate the video automatically, which in turn improves the retrieval of more relevant videos. An ontology is created by experts based on the e-learning video domain. Videos are grouped based on the keywords and on domain ontology, which also helps in enhancing the retrieval results. Videos containing text are only considered for processing.
Annotation, e-learning, ontology, semantics, Term Frequency Inverse Document Frequency (TF-IDF), video retrieval
Hydro power is one of the renewable sources of energy which plays a significant role in the development of any country. Ranoli Branch Canal splits from Sakarda Branch Canal, one of the branch canals of Narmada Main Canal. The objective of this study is to find the best location for a small hydro power project out of four feasible locations on Ranoli Branch, using the Analytical Hierarchy Process (AHP)-weighted sum method. Result of weighted sum method has been validated using PROMETHEE method. The problem has been evaluated based on criteria for project cost, rated power, distance of the power house to the grid line, distance of the power house to the road, and distance of the power house to the village, and four canal fall locations, at chainage 7525 m, 9825 m, 17367 m, and 19844 m, as alternatives. The project cost was calculated by designing hydro power components (using Indian Standards Guideline) and applying actual market rates. The distance of the power house to the grid line, road, and village were obtained with the Google Play Store application called 'Map Distance Ruler Lite'. Optimisation resulted in the best location for hydro power generation in each canal. The fourth alternative, A4 at chainage 19844 m, is the best location.
AHP, branch canal, small hydro power project, weighted sum method
Crop models can accurately estimate crop growth, biomass yield (BY) and grain yield (GY) with a priori information of the crop, soil properties and water management. Generation of new knowledge through traditional agricultural practices is not possible to meet the requirements for novel agro-technologies and they are generally season specific, expensive and time consuming. Hence, the CERES (Crop Environmental Resource Synthesis) model was calibrated using the data of 2009 and validated with the data of 2010 acquired from the field data of WTC, IARI, India. Irrigation applications comprised rainfed, i.e. no irrigation (I1), irrigation at 50% of field capacity (FC) (I2), at 75 % FC (I3) and 100% FC or full irrigation (I4). Nitrogen levels were: no nitrogen (N1), 75 kg ha-1 (N2) and 150 kg ha-1 (N3). Model performance statistics of model efficiency (E), root mean square error (RMSE) and normalized root mean square error (NRMSE) were applied to evaluate the model performance. Model calibration for simulation of GY and BY provided prediction error statistics of 0.78<E<0.84, 0.238<RMSE<0.70 t ha-1 and 6<NRMSE<7 %, respectively for all irrigation levels. Also, the model was validated for simulation of GY and BY for all treatment levels with the prediction error statistics of 0.86<E<0.88, 0.36<RMSE<0.86 t ha-1, 0.95<R2<0.98 and 6<NRMSE<8%. Nonetheless, it was observed that the CERES-maize model could be applied to estimate yield and biomass under the regional situations with reasonable accuracy.
Investment funds are growing in Malaysia since people are more knowledgeable about investments and aware of investment opportunities in order to secure good savings for the future. These investments include unit trusts, gold, fixed deposits, stock prices and property investments. It is essential for individuals or organisations to know the value of future share prices of their investment portfolio in order to predict the profit or loss in the future. The purpose of study is to identify the best duration of historical data and forecast days in order to accurately forecast share prices. The study uses Geometric Brownian Motion model in forecasting share prices of companies in Bursa Malaysia. This study focused on 40 listed companies in Bursa Malaysia from the top gainers list. It was found that 65 historical days could forecast the share prices for 21 days accurately.
In this article, we want to solve the complication of production of the product for the newly launched product and integrate it with the value of time, product, and inflation value. To address such problems, we have used a linear demand rate, which is directly proportional to the stock level i.e. if the stock level is maximum, the demand will automatically increase and the inventory level will also increase. If the level of the stock decreases then the demand and inventory level will also decrease. Moreover, the production will be stopped, when the level of stock will reach level S and there is no effect of demand. The S0 stock level is definite. The prospective of this research is to increase the total profit of the model. For which the use of the Centroid method of defuzzification is used to defuzzify the total profit. This model will be explained with the help of numerical examples and sensitivity analysis and Java and MATLAB R2015a are used to get the optimal values of this model.
Sign Language is the only method used in communication between the hearing-impaired community and common community. Sign Language Recognition (SLR) system, which is required to recognize sign languages, has been widely studied for years. The studies are based on various input sensors, gesture segmentation, extraction of features and classification methods. This paper aims to analyze and compare the methods employed in the SLR systems, classifications methods that have been used, and suggests the most promising method for future research. Due to recent advancement in classification methods, many of the recent proposed works mainly contribute on the classification methods, such as hybrid method and Deep Learning. This paper focuses on the classification methods used in prior Sign Language Recognition system. Based on our review, HMM-based approaches have been explored extensively in prior research, including its modifications. Deep Learning such as Convolutional Neural Network is popular in the past five years. Hybrid CNN-HMM and fully Deep Learning approaches have shown promising results and offer opportunities for further exploration. However, overfitting and high computational requirements still hinder their adoption. We believe the future direction of the research is toward developing a simpler network that can achieve high performance and requires low computational load, which embeds the feature learner into the classifier in multi-layered neural network fashion.
Classification methods, Hidden Markov model, neural networks, sign language recognition
In this paper, the secrecy performance of two energy harvesting (EH) protocols, known as, time switching (TS) and power splitting (PS) is analyzed for a single hop relaying network, in which the sender sends the data to legitimate destination using a relay in the presence of an eavesdropper. In the considered network, the relay and source are powered up by using energy harvesting techniques. The performance of the systems with EH is compared with that of the conventional physical layer security model, where nodes are powered up by individual battery sources. The secrecy rates with the two different types of EH protocols and conventional system are analyzed for two relaying schemes: decode-and-forward (DF), and amplify-and-forward (AF). Resulting analysis shows that the TS EH system has higher secrecy rate as compared to conventional system and the secrecy rate of the conventional system is higher than that of PS EH protocol.Further, the simulation results show that AF relays outperforms DF relays in all the scenarios.
Amplify and forward, energy harvesting, jamming, physical layer security, secrecy rate
The feasibility study on Chlorella sp. lipid extraction using an electrolysis treatment (ET) as pre-treatment was investigated. Stainless steel was used as the anode and cathode material. The ET method was conducted in a batch or continuous system with or without air aeration and recycling flow. The total lipid in Chlorella sp. AWET and AWET were not analysed due to small sample volume. Approximately same amount of lipids were attained from Chlorella sp. BWOET (7.97 ± 0.43% glipid/gdry wt) and BWET (7.95 ± 0.37% glipid/gdry wt) if treated at 5 V/cm and aerated at 16.7 µm3/s for 1800s. Whereas, if Chlorella sp. was treated at 13 V/cm and aerated at 16.7 µm3/s for 1800 s, the total lipid obtained in Chlorella sp. CWOET (8.18 ± 0.49% glipid/gdry wt) was 1.13-fold higher than CWET (7.22 ± 0.47% glipid/gdry wt). Meanwhile under semi-continuous system, similar pattern of result was achieved in Chlorella sp. DWOET (8.58 ± 0.49% glipid/gdry wt) with 1.11-fold higher than DWET (7.72 ± 0.54% glipid/gdry wt), if treated at 14 V/cm and recycled at 2.3 µm3/s for 3000s. This corresponded to lipid oxidation that might have occurred during the ET method. The fatty acid methyl ester (FAME) composition of Chlorella sp. DWOET and DWET contained predominantly methyl linolenate (C18:3) and methyl palmitate (C16:0). The concentrations of methyl palmitate attained in Chlorella sp. DWOET and DWET were 0.049 ± 0.005 g/m3 and 0.045 ± 0.005 g/m3, respectively.
Chlorella sp., electrolysis treatment, lipid extraction, methyl palmitate, total lipid
A power 'Grid' is a network that carries electricity from power plants to consumer premises. The grid is made 'smart' as it can monitor and control the distribution system by taking intelligent decisions. Smart Grid is an automated and broadly distributed energy generation, transmission and distribution network. Smart Grid network integrates an electrical distribution system with information and communication network. Communication network protocols are engineered, developed and established based on the layered approach. Each layer is designed to serve a specific functionality in collaboration with other layers. Layered approach for wired communication approach can be modified with cross layer approach for wireless communication for performance enhancement. Smart grid technology comprises of hierarchical and heterogeneous network with diverse set of communication protocols. This demands a divergence from primitive approach and adaptation of an innovative approach. This paper describes network design and optimization of routing protocol for Smart grid Neighborhood Area Network using Riverbed-OPNET software. A Cross layer approach is considered in parameter optimization of IEEE 802.11 standard. The proposed work shows parameter optimization of routing protocol for better network performance using simulation approach.
Communication, cross layer optimization, home area network, IEEE 802.11, neighborhood area network, smart grid, wide area network
From a diagnostic perspective, image enhancement has diverse potential in image processing applications related to biomedical images. A hybrid algorithm obtained by combining discrete wavelet transformation with soft computing techniques is proposed for enhancing the biomedical images. This paper proposes an approach for effective visual enhancement of biomedical images. The proposed approach uses scale-invariant feature transform algorithm and principal component analysis as pre-enhancement steps, followed by the combination of DWT and the genetic algorithm to enhance the biomedical images. In GA, a new fitness function, which can efficiently reduce the noise in biomedical images while preserving the details, is proposed for the enhancement process. In order to accurately evaluate the enhanced image's quality, various metrics like peak signal to noise ratio, contrast to noise ratio, BETA coefficient, standard deviation, and mean square error have been considered. Finally, the comparison of the proposed algorithm with other soft computing techniques like Bacterial Foraging, Particle Swarm Optimization and Fuzzy Logic is carried out. The results show that the proposed technique outperformed over the other methods and provided better image quality.
The LDPC (Low-Density Parity-Check) decoder must operate soft decisions calculated using: LLR (Log-Likelihood Ratio) or APP (A Posteriori Probability) according to the decoding algorithm used. The exact calculation of these decisions for high order constellations involves complicated operations. In this work, a method to simplify the APP calculation is introduced. It is programmed to adapt as perfectly as possible the transmission system to the channel type in question. This method leads to simplify the implementation of the transmission system. Simulation results show that, under the Gaussian channel, the simplified APP algorithm for 16-QAM achieves the same performance that obtained with the exact APP, while for 64-QAM we have a small performance degradation. The same simplified APP algorithm that used for the Gaussian channel can be applied, with minor operations added, for Rayleigh channel, and it shows a small performance loss with respect to the exact APP.
A Priori Probability (APP), Binary LDPC code, Gaussian channel, Log-Likelihood Ratio (LLR), Rayleigh channel, Square-QAM-Gray mapping
The need for high speed, low cost and smaller area has increased the integration of electronic devices. As the number of components increases, the reliability of system becomes a major challenge. The bipolar junction transistor is an immensely used passive component in the various electronics industry. Reliability and failure prediction are the major constraints for the estimation of the residual life of the component. In this paper, Artificial intelligence techniques are employed on bipolar junction transistor which provides knowledge of failure mechanism of a component in actual operating conditions such that if it deviates from the actual output, a preventive measure to be taken before serious failure occurs. The end of life has been explored using the design of experiments approach. After calculating lifetime, an expert system has been modeled which predicts the sudden crash of transistor before it actual fails, using various statistical and analytical techniques. The comparison of accuracy has been conducted on all techniques of artificial intelligence and statistical method. The comparison shows that ANFIS is the most accurate technique with an accuracy of 96.65%. A graphical user interface is created which indicates the failure of bipolar junction transistor at various level of inputs.
Access to sufficient and confident hydrometric data is necessary for water resources management. Most of the Iran's hydrometric stations do not have sufficient data. The method of producing synthetic data should use probability concepts and retains main characteristics of the data, too. In this research, synthetic hydrometric data are generated by the monthly and annual Markov chain method at the Telezang station in the upstream of the Dez River. Using the discharge of the driest day and the wettest day of each month and the generated monthly hydrometric data, the probable highest and lowest daily discharge for each month was calculated. At the end, artificial neural network was trained with a number of observed and generated hydrometric data. The results of artificial neural network were compared with a number of observed hydrometric data which were not used in training of the network. The training of artificial neural network (ANN) with the generated hydrometric data can improve results of network. For more improvement of the results of network, genetic algorithm (GA) is used in its training and optimizing its parameters. The GA method can reduce the MSE (mean of square error) by 97% that of ANN.
Artificial neural network, Dez River, genetic algorithm, Markov chain, Telezang station
The paper proposes a methodology to compute reliability of the screw plant. A screw plant consists of four subsystems A, B, C, D working in series namely heading machine, slotting machine, thread rolling machine and polishing machine. Subsystem A is supported by standby units having perfect switching over device and subsystem C has two units in parallel redundancy and remaining two subsystems B and D are subjected to major failure only. For system configuration and establishment of the model we prefer Boolean algebra method and orthogonal matrix method has been used for reliability calculation. Reliability of the Screw Plant has been estimated when the failure rate expressed by weibull and exponential time distribution. Mean time to failure has also been determined for exponential time distribution, which is also a relevant characteristic of reliability.
Boolean function, failure rate, mean time to failure, reliability
Named Entity Recognition (NER) is defined as identification and classification of Named Entities (NEs) into set of well-defined categories. Many rule-based, machine learning based, and hybrid approaches have been devised to deal with NER, particularly, for the English language. However, in case of Hindi language several perplexing challenges occur that are detailed in this research paper. A new approach is proposed to perform Hindi NE Recognition using semantic properties to handle some of the Hindi language specific NER challenges. And because of increasing demand in Hindi health care applications, Hindi Health Data (HHD) is crawled from four well-known Indian websites: Traditional Knowledge Digital Library; Ministry of Ayush; University of Patanjali; and Linguistic Data Consortium for Indian Languages. Four novel NE types are determined, namely- Person NE, Disease NE, Symptom NE and Consumable NE. For training purpose, HHD data is converted into Hyperspace Analogue to Language (HAL) vectors, thereby, maps each word into a high dimensional space. Conditional Random Field model is applied based on HHD feature engineering, HHD gazetteers and HAL. Blind test data is then mapped into the high dimensional space created during the training phase and outputs the annotated test data. The results obtained are quite significant; and HAL accompanied with CRF approach seems to provide effective outcome for Hindi NE Recognition.
Conditional Random Field, Hindi, Hyperspace Analogue to Language, Named Entity Recognition
Clustering is basically one of the major sources of primary data mining tools. It makes researchers understand the natural grouping of attributes in datasets. Clustering is an unsupervised classification method with the major aim of partitioning, where objects in the same cluster are similar, and objects which belong to different clusters vary significantly, with respect to their attributes. However, the classical Standardized Euclidean distance, which uses standard deviation to down weight maximum points of the ith features on the distance clusters, has been criticized by many scholars that the method produces outliers, lack robustness, and has 0% breakdown points. It also has low efficiency in normal distribution. Therefore, to remedy the problem, we suggest two statistical estimators which have 50% breakdown points namely the Sn and Qn estimators, with 58% and 82% efficiency, respectively. The proposed methods evidently outperformed the existing methods in down weighting the maximum points of the ith features in distance-based clustering analysis.
The present paper encompasses the fabrication, experimentation, testing and thermal property evaluation of LM25-Borosilicate glass (p) composites obtained through stir casting route with judicious selection and placement of different end chills within the sand molds. The composites required for the present study were cast by melting LM25 aluminum alloy into which varied weight percent of Borosilicate glass powder was introduced under the application of a mechanical stirrer. The melt with required content of reinforcement was introduced in a sand mold containing one end chill. Metallic end chills (copper and mild steel) and non- metallic end chills (silicon carbide and graphite) were employed in the current research. Various thermal tests were conducted on the specimens drawn from near the chill end to evaluate thermal diffusivity and thermal conductivity of the fabricated composite. The analysis of the obtained results illustrate the fact that end chill materials have a pronounced effect on the evaluated thermal properties of the composite as employment of metallic end chills resulted in the reduction of the thermal conductivity of the specimens as opposed with the thermal conductivity values for specimens fabricated with the aid of non-metallic end chills.
In this article, performance analysis of speech recognition system for different acoustical models has been presented. In the present work, one of the well-known south Indian language named "Kannada" language is considered. Significantly large amount of work has been reported for Automatic Speech Recognition (ASR) in European languages whereas quite a small number of publications can be found in Indian languages. One of the reasons for this gap is that standard speech database in Indian languages is not available. In this study, Kannada speech corpus based on Kannada broadcast news data has been developed. The isolated speaker independent speech recognition system has been developed using Hidden Markov Tool Kit (HTK). The system front-end uses Mel frequency cepstral coefficients (MFCC) and its derivatives as acoustic features whereas acoustical models are developed by using Hidden Markov Models (HMM). Syllable and mono-phone based Kannada dictionaries have been developed in this study. Various mono-phone models considered in this work are word-level, syllable-level and phone-level models. Further, performance evaluation of mono-phone and tri-phone acoustical models for large sized dictionary also carried out. The best word recognition accuracies of 67.82% and 70.56% are reported for mono-phone and tri-phone based systems respectively. The recognition results for different HMM based acoustical models are obtained and hence the recognition performance has been analyzed.
Hidden Markov Tool Kit (HTK), Kannada language, Mel frequency cepstral coefficients (MFCC), Isolated Word Recognition (IWR) system, mono-phone model, phone dictionary, syllable dictionary, tri-phone model
Data traffic has been increasing at an exponential rate causing extremely heavy demand on cellular networks. Device-to-Device (D2D) communication is seen as a potential solution for data traffic offloading and enhanced performance of cellular networks. It improves the spectrum and energy efficiency of the network. But co-channel interference is the major concern while performing spectrum sharing in D2D communication. Most of the existing works have proposed power control schemes for non-overlapping spectrum allocation among D2D pairs. This paper focuses on reducing the co-channel interference by dynamic power control while allocating multiple resources to single D2D user. D2D system performance is formulated as an overlapping coalition game coupled with interference based transmit power distribution among the resource blocks assigned to a single user. Simulation results show that the proposed scheme outperforms the other existing techniques in terms of D2D throughput and total transmit power
Device-to-Device communication, overlapping coalition game, power control, resource allocation
The huge potential of solar energy and increasing demand of energy, made researchers to work on solar photovoltaic systems. In this paper, experimental investigations and exergy based thermodynamic assessment of 1 kW solar photovoltaic (SPV) plant have been carried out. The system is installed at Amity University Gurgaon, India. With the aim to assess the performance/efficiency of the plant, two exergy techniques have been applied based on concepts of thermodynamics and chemical/photonic energy of input solar insolation. The input energy and exergy at different wavelengths ranging from 0.4 µm-0.7 µm have been formulated and illustrated. The electrical and operating parameters of SPV plant includes short-circuit current, open-circuit voltage, temperature of photovoltaic (PV) modules, and fill factor are found, carrying an experiment on a sunny day of 5th October 2017. The variations of electrical exergy input at different fill factors have been computed which signifies its role in characteristic behavior of PV system. The energy/exergy efficiencies are found to be between 7.76% to 9.98% and 9.86% to 11.63% whereas the photonic energy/exergy efficiencies are found to be between 4.85% to 11.24% and 6.08% to 12.89%. It is also found that the temperature of SPV plays a vital role on exergy efficiency and it can be improved with a mechanism which removes the generated heat from the system. With the experimental results, it can be noticed that the exergy loss increases as the temperature of SPV module goes up.
Chemical/Photonic energy, energy analysis, exergy analysis, electrical energy, solar insolation rate, solar photovoltaic system, thermal energy
Merbok river catchment situated in the Kedah State receives its input from Bongkok River and Puntar River flowing down and joining Lalang River to flow down to the Merbok Estuary. The Merbok catchment (440 km2) is experiencing several degrees of complex land uses activities that poses some impact on the suspended sediment production of the Merbok river. A study was conducted to investigate the suspended sediment loading of rivers draining the Merbok catchment from January to December 2013. Suspended sediment budget of the Merbok catchment were estimated. The river suspended sediment concentrations (SSC) and suspended sediment (SS) load increased during wet season compared to dry season. The SS loads increases from upper catchment to river mouth. The sediment loadings were divided into three segments- the upstream, middle segment and lower segment. The SS loads increased from 10 t yr-1 in the upper part of Bongkok river to 3336 t yr-1 in upper segment. The sediment loading then increase to 4299 t yr-1 in the middle segment of the catchment (at Bongkok 4), and then exiting the Merbok Estuary, as the lower segment, with a total amount of sediment output estimated at 7156 t yr-1. From this total sediment output, most of the sediment source came from the tributaries; the Bongkok River at B3 (3337 t yr-1), Puntar River (2924 t yr-1) and Lalang River (1370 t yr-1), which were much higher than its proportion in terms of its length and drainage area. As a conclusion, the inconsistence in SSC in the river were influenced by the various anthropogenic activities (especially agriculture and urbanization activities) in the catchment area which necessitate future land use and sediment control to avoid sediment and possible nutrient loading into the estuary.
Kedah, land use changes, Merbok River catchment, sediment load, sediment budget
With the development of next-generation sequencing technology, a massive amount of genomic data are being generated day by day. To efficiently handle these data for storage, processing and transmission, some specialized genomic data compression techniques are need of today. In the near future, personalized genomics may come into existence where doctors may give the treatment on the basis of patient genome. It creates a huge challenge to securely store and transmit the genomic data over the cloud servers or remote servers. This problem can be solved by applying a combination of encryption and compression techniques. Most of the state of the art algorithms for secure and efficient storage of genomic data adopt the policy of encryption after compression. The computational costs of these algorithms are very high, so there is a need to develop a unified encryption-compression algorithm (encryption during compression) to provide the confidentiality/secrecy also to genomic data. In this paper an approach applying encryption during compression is proposed to efficiently and securely store the genomic data in fasta/multi-fasta file format. Here MWBTC (Modified Word Based Tag Code) and Delta Encoding are used for compression and AES-256 is used for encryption. Experiments show that the proposed algorithm (WBMFC) outperforms the state of the art algorithms in terms of processing time and compression ratio both.
Since 1958, most of the world's countries including Turkey depend on the Empirical Pavement Design Method established by AASHO (which is now known as AASHTO). The limitation of the data used for preparing AASHTO 1993 and Non-Mechanical Based procedure are the main reasons for the needs of new design procedure. The new AASHTO design procedure MEPDG has been established in 2002 and adopted by most of the states in the USA which is based on Mechanistic-Empirical (M-E) principles. The aim of this paper is to prepare a plan for the implementation of MEPDG in TURKEY starting with Third Region. The plan consists of two stages. Stage one is concerned with data collection and preparing of input files. This stage is subdivided into three tasks namley, Climate File, Material File and Traffic File. Stage two is associated with the use of the files prepared in Stage one to conduct studies using MEPDG software. These studies are recommended by AASHTO to evaluate the applicability of the procedure and the recommended enhancements. The studies of this stage are: (a) Sensitivity Analysis of MEPDG to Design Inputs; (b) Comparison of specific Third Region Designs with MEPDG designs; and (c) Calibration of Performance Models for Third Region in Turkey. The outcomes of this paper can be used as guidance for further studies on the implementation of MEPDG in other Regions in Turkey. Also the results of these researches can be assembled to implement the procedure for whole Turkey.
Energy efficient and load-balanced routing based on QoS requirements in Wireless Multimedia Sensor Network have been achieved using Energy Enhanced Load Balancing Pairwise Directional Geographical Routing (EELB-PWDGR). However, the process of path selection is a time-consuming one. Hence, Artificial Bee Colony (ABC) is used to select the optimal path satisfying QoS constraints. Though the ABC-EELB-PWDGR outperforms EELB-PWDGR, the ABC algorithm exhibits unsatisfactory performance with a lower search speed, poor population diversity, stagnation within working methods, and struck to the local optimal solution. This study uses an enhanced ABC algorithm in which the global best solution information is added into the solution search equations in order to find the new solution only around the best solutions of the previous iterations for improved exploitation. Since Population initialization is imperative due to its impact on convergence speed, an initialization approach which based on chaotic systems and opposition based learning method has been employed to balance the diversity and convergence capability of ABC. Thus the Enhanced ABC based EELB-PWDGR (EABC- EELB-PWDGR) constructs an initial population with a maximum diversity to provide the best search solutions and a high degree of accuracy. The experimental results prove that the proposed EABC-EELB-PWDGR provides better routing performance than ABC-EELB-PWDGR.
The thermodynamic analysis of thermoelectric devices (TEs) discards the impact caused by heat leak between source and sink. It could lead towards the partial/incomplete modelling of TEs along with some analytical gaps in their performance evaluation. Conversely, appropriate agreement among different design constraints of TEs is a must to upgrade their operating characteristics. In view of this, the modelling of multi-element single-stage thermoelectric generator (TEG) and thermoelectric heat pump (TEHP) is carried out in matrix laboratory (MATLAB 9.2). The irreversibilities caused by heat leak between the source/sink along with Fourier/Joule effects are considered for the modelling and analysis. The power output/thermal efficiency and heating capacity/coefficient of performance (COP) of TEs are analytically derived and optimized on the basis of finite time thermodynamic principles. The predetermined thermoelectric couples are chosen to maximize the heating capacity/COP in proposed configurations. Moreover, the influence of design variables viz electrical current, thermoelectric couples on system throughput is analyzed and presented. The effects of geometrical parameters viz length and area of individual modules on the performance of TEG and TEHP are also discussed.
Heavy metal pollution in water, especially in the North Jakarta area, has become severe from time to time. A heavy metal adsorbent is one of the alternative solutions to clean the waste water from industries before it is released into the environment. In this paper, we create pectin that has been proven to be an effective absorbent for heavy metal (Pb) and is made of Musa Acuminata Cavendish (cavendish banana) and Musa Paradisiaca Formatypica (horn shaped banana). These two banana species can be easily found in the markets of Jakarta. Therefore, we compare the two species to find out which is more effective to use as heavy metal adsorbent. The selection is based on the reduction of the Pb concentration after the introduction of banana pectin by means of Pb emission intensity reading taken using commercially available laser-induced breakdown spectroscopy (LIBS) system. The effectiveness of pectin from the two banana skins as Pb adsorbent is comparable either in pellet form or solution in water. The result shows that the average effectiveness of homemade pectin as Pb adsorbent is 37.5%, which is lower than the commercial pectin available in the market. In the future, the technique of producing homemade pectin will be improved to get better Pb absorption efficiency.
Rib turbulators are largely utilized for enhancement of heat transfer in cooling channels of gas turbine blades. The present study focuses on the heat transfer, fluid flow and pressure drop study of perforated ribs fixed to the bottom wall of a two-pass square channel. The turbulent flow details for heat transfer and fluid flow for perforated ribs are simulated by using commercial software Comsol 5.3a with an established turbulence model i.e. Standard k-ε. The assiduity is towards analyzing the possible effects of varying inclination angle (0 to 30°) and shape of hole (cylinder to square) on heat transfer and friction factor characteristics for turbulent flow. The studied Reynolds number varies from 10000 to 50,000. Computations are carried out to determine inter-rib distribution of local heat transfer coefficient over the bottom ribbed wall. The phenomenon responsible for the heat transfer enhancement by perforated ribs is delineated. The results reveal that perforated ribs lead to enhancement of local heat transfer distribution (Nu/Nuo) on the end wall downstream the ribs. Perforated ribs develop longitudinal vortices. These vortices cause an increase in flow mixing and turbulent kinetic energy. The square perforated ribs provide a 37.1-57.3% higher normalized average Nusselt number relative to the solid ribs, however induce high pressure drop. Overall, square perforated ribs (Case-3) provide the best thermal-hydraulic performance.
As we know, drinking young coconut water and eating the tender meat give many benefit to the body for its nutritious value rather than its taste; but do we realize that it requires a dangerous tasks in processing it. The process of trimming requires skills which only can be obtained by those who run the work daily. Thus, a portable apparatus which has the capabilities of reducing the hazardous tasks and fasten the time consumed for processing the young coconut fruit has been proposed and developed. The development of the product begins with collecting and analyzing the data of 30 young coconut fruits. Then, it is followed by designing the whole product at main and component level. The conceptual design is done initially using freehand sketching technique. Next, the 3D solid modeling relies totally on the CATIA V5R19 software. Finally, a complete details drawing is produced using CAD software. In this work, the design focuses on the blade slicing and punch bit head to reduce the hazardous tasks during processing of the young coconut. The blade is designed to allow the slicing movement to be maneuvered during the husk removal process. Meanwhile, the puncher has replaced the usage of chopper in creating an opening at the top of the endocarp. Thus, the device developed will reduce the hazardous task by eliminating the chopping process and replacing it with the slicing process. Therefore, the tendency to get caught in accidental injury during the chopping process can be significantly reduced.
The crab carapace is a waste which cannot be decomposed. This waste was used to remove the Reactive Orange 16 (RO16) and Basic Blue 3 (BB3) from aqueous solution at different operational parameters such as pH, mass load, the concentrations of dye and the temperature. The crab collected was modified to obtain quaternized crab (QC) using (3-chloro-2-hydroxypropyl) trimethylammonium chloride solution (C6H15Cl2NO, 65% w/w in water). The pH of the dyes solution was varied from pH 4 to 10. The highest adsorption percentage was achieved at pH 7 for both dyes. Increasing the QC mass for the adsorption process had granted an increase of dyes removal percentage. The highest adsorption percentage was achieved at 91.00% for RO16 and 29.40% for BB3 dyes with 7.5 g/L QC used. However, the adsorption capacity of QC decreased with higher QC mass because the dye molecules occupied on the surface and prevented other molecules to diffuse into the QC. At higher concentration beyond 20 mg/L and 10 mg/L of RO16 and BB3, respectively, the maximum adsorption was achieved at 2.5362 mg/g and 0.6812 mg/g. The adsorption of both dyes by QC was best fitted using Langmuir isotherm model, explaining the adsorption mainly occurred as a single layer on the surface of QC. Comparison to the results obtained from the kinetic models, the adsorption was chemisorption in nature. According to the thermodynamic studies, the adsorption of RO16 was an exothermic, while BB3 was an endorthermic process.