This paper reports the result of an investigation on the potential energy saving of the lighting systems at selected buildings of the Universiti Tenaga Nasional. The scope of this project includes evaluation of the lighting system in the Library, Admin Building, College of Engineering, College of Information Technology, Apartments, and COE Food court of the university. The main objectives of this project are to design the proper retrofit scenario and to calculate the potential electricity saving, the payback period, and the potential environmental benefits. In this survey the policy for retrofitting the old lighting system with the new energy saving LEDs starts with 10% for the first year and continues constantly for 10 years until all the lighting systems have been replaced. The result of the life cycle analysis reveals that after four years, the selected buildings will bring profit for the investment.
Matched MeSH terms: Conservation of Energy Resources/methods; Lighting/methods
In a computerized image analysis environment, the irregularity of a lesion border has been used to differentiate between malignant melanoma and other pigmented skin lesions. The accuracy of the automated lesion border detection is a significant step towards accurate classification at a later stage. In this paper, we propose the use of a combined Spline and B-spline in order to enhance the quality of dermoscopic images before segmentation. In this paper, morphological operations and median filter were used first to remove noise from the original image during pre-processing. Then we proceeded to adjust image RGB values to the optimal color channel (green channel). The combined Spline and B-spline method was subsequently adopted to enhance the image before segmentation. The lesion segmentation was completed based on threshold value empirically obtained using the optimal color channel. Finally, morphological operations were utilized to merge the smaller regions with the main lesion region. Improvement on the average segmentation accuracy was observed in the experimental results conducted on 70 dermoscopic images. The average accuracy of segmentation achieved in this paper was 97.21 % (where, the average sensitivity and specificity were 94 % and 98.05 % respectively).
Advent of medical image digitalization leads to image processing and computer-aided diagnosis systems in numerous clinical applications. These technologies could be used to automatically diagnose patient or serve as second opinion to pathologists. This paper briefly reviews cervical screening techniques, advantages, and disadvantages. The digital data of the screening techniques are used as data for the computer screening system as replaced in the expert analysis. Four stages of the computer system are enhancement, features extraction, feature selection, and classification reviewed in detail. The computer system based on cytology data and electromagnetic spectra data achieved better accuracy than other data.
Designing a biosensor for versatile biomedical applications is a sophisticated task and how dedicatedly functionalized fullerene (C60) can perform on this stage is a challenge for today and tomorrow's nanoscience and nanotechnology. Since the invention of biosensor, many ideas and methods have been invested to upgrade the functionality of biosensors. Due to special physicochemical characteristics, the novel carbon material "fullerene" adds a new dimension to the construction of highly sensitive biosensors. The prominent aspects of fullerene explain its outstanding performance in biosensing devices as a mediator, e.g. fullerene in organic solvents exhibits five stages of reversible oxidation/reduction, and hence fullerene can work either as an electrophile or nucleophile. Fullerene is stable and its spherical structure produces an angle strain which allows it to undergo characteristic reactions of addition to double bonds (hybridization which turns from sp(2) to sp(3)). Research activities are being conducted worldwide to invent a variety of methods of fullerene functionalization with a purpose of incorporating it effectively in biosensor devices. The different types of functionalization methods include modification of fullerene into water soluble derivatives and conjugation with enzymes and/or other biomolecules, e.g. urease, glucose oxidase, hemoglobin, myoglobin (Mb), conjugation with metals e.g. gold (Au), chitosan (CS), ferrocene (Fc), etc. to enhance the sensitivity of biosensors. The state-of-the-art research on fullerene functionalization and its application in sensor devices has proven that fullerene can be implemented successfully in preparing biosensors to detect glucose level in blood serum, urea level in urine solution, hemoglobin, immunoglobulin, glutathione in real sample for pathological purpose, to identify doping abuse, to analyze pharmaceutical preparation and even to detect cancer and tumor cells at an earlier stage. Employing fullerene-metal matrix for the detection of tumor and cancer cells is also possible by the inclusion of fullerene in single-walled carbon nanotubes (SWCNTs) known as peapods as well as in double-walled carbon nanotubes (DWCNTs), to augment the effectiveness of biosensors. This review discusses various approaches that have been reported for functionalizing fullerene (C60) derivatives and their application in different types of biosensor fabrication.
This paper presents a novel features mining approach from documents that could not be mined via optical character recognition (OCR). By identifying the intimate relationship between the text and graphical components, the proposed technique pulls out the Start, End, and Exact values for each bar. Furthermore, the word 2-gram and Euclidean distance methods are used to accurately detect and determine plagiarism in bar charts.
Matched MeSH terms: Pattern Recognition, Automated/methods*; Data Mining/methods*
Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.
Matched MeSH terms: Information Storage and Retrieval/methods*; Information Management/methods*
Socket is an important part of every prosthetic limb as an interface between the residual limb and prosthetic components. Biomechanics of socket-residual limb interface, especially the pressure and force distribution, have effect on patient satisfaction and function. This paper aimed to review and evaluate studies conducted in the last decades on the design of socket, in-socket interface pressure measurement, and socket biomechanics. Literature was searched to find related keywords with transtibial amputation, socket-residual limb interface, socket measurement, socket design, modeling, computational modeling, and suspension system. In accordance with the selection criteria, 19 articles were selected for further analysis. It was revealed that pressure and stress have been studied in the last decaeds, but quantitative evaluations remain inapplicable in clinical settings. This study also illustrates prevailing systems, which may facilitate improvements in socket design for improved quality of life for individuals ambulating with transtibial prosthesis. It is hoped that the review will better facilitate the understanding and determine the clinical relevance of quantitative evaluations.
Test collection is used to evaluate the information retrieval systems in laboratory-based evaluation experimentation. In a classic setting, generating relevance judgments involves human assessors and is a costly and time consuming task. Researchers and practitioners are still being challenged in performing reliable and low-cost evaluation of retrieval systems. Crowdsourcing as a novel method of data acquisition is broadly used in many research fields. It has been proven that crowdsourcing is an inexpensive and quick solution as well as a reliable alternative for creating relevance judgments. One of the crowdsourcing applications in IR is to judge relevancy of query document pair. In order to have a successful crowdsourcing experiment, the relevance judgment tasks should be designed precisely to emphasize quality control. This paper is intended to explore different factors that have an influence on the accuracy of relevance judgments accomplished by workers and how to intensify the reliability of judgments in crowdsourcing experiment.
Matched MeSH terms: Pattern Recognition, Automated/methods*; Information Storage and Retrieval/methods*
The aim of this study was to determine the best parameter for extracting phenolic-enriched kenaf (Hibiscus cannabinus L.) seeds by a pulsed ultrasonic-assisted extraction. The antioxidant activities of ultrasonic-assisted kenaf seed extracts (KSE) were determined by a 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging capacity assay, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) radical scavenging assay, β -carotene bleaching inhibition assay, and ferric reducing antioxidant power (FRAP) assay. Total phenolic content (TPC) and total flavonoid content (TFC) evaluations were carried out to determine the phenolic and flavonoid contents in KSE. The KSE from the best extraction parameter was then subjected to high performance liquid chromatography (HPLC) to quantify the phenolic compounds. The optimised extraction condition employed 80% ethanol for 15 min, with the highest values determined for the DPPH, ABTS, and FRAP assay. KSE contained mainly tannic acid (2302.20 mg/100 g extract) and sinapic acid (1198.22 mg/100 g extract), which can be used as alternative antioxidants in the food industry.
Matched MeSH terms: Chemical Fractionation/methods*; Sonication/methods*
This paper introduces a dielectrophoretic system for the manipulation and separation of microparticles. The system is composed of five layers and utilizes microarray dot electrodes. We validated our system by conducting size-dependent manipulation and separation experiments on 1, 5 and 15 μm polystyrene particles. Our findings confirm the capability of the proposed device to rapidly and efficiently manipulate and separate microparticles of various dimensions, utilizing positive and negative dielectrophoresis (DEP) effects. Larger size particles were repelled and concentrated in the center of the dot by negative DEP, while the smaller sizes were attracted and collected by the edge of the dot by positive DEP.
The Electrocardiogram (ECG) is the P-QRS-T wave depicting the cardiac activity of the heart. The subtle changes in the electric potential patterns of repolarization and depolarization are indicative of the disease afflicting the patient. These clinical time domain features of the ECG waveform can be used in cardiac health diagnosis. Due to the presence of noise and minute morphological parameter values, it is very difficult to identify the ECG classes accurately by the naked eye. Various computer aided cardiac diagnosis (CACD) systems, analysis methods, challenges addressed and the future of cardiovascular disease screening are reviewed in this paper. Methods developed for time domain, frequency transform domain, and time-frequency domain analysis, such as the wavelet transform, cannot by themselves represent the inherent distinguishing features accurately. Hence, nonlinear methods which can capture the small variations in the ECG signal and provide improved accuracy in the presence of noise are discussed in greater detail in this review. A CACD system exploiting these nonlinear features can help clinicians to diagnose cardiovascular disease more accurately.
In recent times, the size of biological databases has increased significantly, with the continuous growth in the number of users and rate of queries; such that some databases have reached the terabyte size. There is therefore, the increasing need to access databases at the fastest rates possible. In this paper, the decision tree indexing model (PDTIM) was parallelised, using a hybrid of distributed and shared memory on resident database; with horizontal and vertical growth through Message Passing Interface (MPI) and POSIX Thread (PThread), to accelerate the index building time. The PDTIM was implemented using 1, 2, 4 and 5 processors on 1, 2, 3 and 4 threads respectively. The results show that the hybrid technique improved the speedup, compared to a sequential version. It could be concluded from results that the proposed PDTIM is appropriate for large data sets, in terms of index building time.
Matched MeSH terms: Sequence Analysis/methods*; Data Mining/methods*
Imaging techniques are high in demand for modern nondestructive evaluation of large-scale concrete structures. The travel-time tomography (TTT) technique, which is based on the principle of mapping the change of propagation velocity of transient elastic waves in a measured object, has found increasing application for assessing in situ concrete structures. The primary aim of this technique is to detect defects that exist in a structure. The TTT technique can offer an effective means for assessing tendon duct filling of prestressed concrete (PC) elements. This study is aimed at clarifying some of the issues pertaining to the reliability of the technique for this purpose, such as sensor arrangement, model, meshing, type of tendon sheath, thickness of sheath, and material type as well as the scale of inhomogeneity. The work involved 2D simulations of wave motions, signal processing to extract travel time of waves, and tomography reconstruction computation for velocity mapping of defect in tendon duct.
In this study the environmental impact of consolidated rice farms (CF) - farms which have been integrated to increase the mechanization index - and traditional farms (TF) - small farms with lower mechanization index - in Guilan Province, Iran, were evaluated and compared using Life cycle assessment (LCA) methodology and adaptive neuro-fuzzy inference system (ANFIS). Foreground data were collected from farmers using face-to-face questionnaires and background information about production process and inventory data was taken from the EcoInvent®2.0 database. The system boundary was confined to within the farm gate (cradle to farm gate) and two functional units (land and mass based) were chosen. The study also included a comparison of the input-output energy flows of the farms. The results revealed that the average amount of energy consumed by the CFs was 57 GJ compared to 74.2 GJ for the TFs. The energy ratios for CFs and TFs were 1.6 and 0.9, respectively. The LCA results indicated that CFs produced fewer environmental burdens per ton of produced rice. When compared according to the land-based FU the same results were obtained. This indicates that the differences between the two types of farms were not caused by a difference in their production level, but rather by improved management on the CFs. The analysis also showed that electricity accounted for the greatest share of the impact for both types of farms, followed by P-based and N-based chemical fertilizers. These findings suggest that the CFs had superior overall environmental performance compared to the TFs in the study area. The performance metrics of the model based on ANFIS show that it can be used to predict the environmental burdens of rice production with high accuracy and minimal error.
Matched MeSH terms: Agriculture/methods*; Conservation of Natural Resources/methods*
A novel technique has been introduced in this research which lends its basis to the Directional Slack-Based Measure for the inverse Data Envelopment Analysis. In practice, the current research endeavors to elucidate the inverse directional slack-based measure model within a new production possibility set. On one occasion, there is a modification imposed on the output (input) quantities of an efficient decision making unit. In detail, the efficient decision making unit in this method was omitted from the present production possibility set but substituted by the considered efficient decision making unit while its input and output quantities were subsequently modified. The efficiency score of the entire DMUs will be retained in this approach. Also, there would be an improvement in the efficiency score. The proposed approach was investigated in this study with reference to a resource allocation problem. It is possible to simultaneously consider any upsurges (declines) of certain outputs associated with the efficient decision making unit. The significance of the represented model is accentuated by presenting numerical examples.
Matched MeSH terms: Statistics as Topic/methods*; Resource Allocation/methods*
The advent of web-based applications and services has created such diverse and voluminous web log data stored in web servers, proxy servers, client machines, or organizational databases. This paper attempts to investigate the effect of temporal attribute in relational rule mining for web log data. We incorporated the characteristics of time in the rule mining process and analysed the effect of various temporal parameters. The rules generated from temporal relational rule mining are then compared against the rules generated from the classical rule mining approach such as the Apriori and FP-Growth algorithms. The results showed that by incorporating the temporal attribute via time, the number of rules generated is subsequently smaller but is comparable in terms of quality.
Matched MeSH terms: Information Storage and Retrieval/methods*; Data Mining/methods*
Regenerative medicine has rapidly evolved over the past decade owing to its potential applications to improve human health. Targeted differentiations of stem cells promise to regenerate a variety of tissues and/or organs despite significant challenges. Recent studies have demonstrated the vital role of the physical microenvironment in regulating stem cell fate and improving differentiation efficiency. In this review, we summarize the main physical cues that are crucial for controlling stem cell differentiation. Recent advances in the technologies for the construction of physical microenvironment and their implications in controlling stem cell fate are also highlighted.
Alstonia scholaris (L.) R. Br. and Alstonia macrophylla Wall. ex G. Don are two vital medicinal plant species (family: Apocynaceae). In India, the therapeutic use of Alstonia scholaris has been described in both codified and non-codified drug systems for the treatment of malaria, jaundice, gastrointestinal troubles, cancer and in many other ailments. Other species, Alstonia macrophylla has been used in conventional medicines in Thailand, Malaysia and Philippines as a general tonic, aphrodisiac, anticholeric, antidysentery, antipyretic, emmenagogue, and vulnerary agents. In India, Alstonia macrophylla is used as a substitute for Alstonia scholaris in various herbal pharmaceutical preparations. However, one certainly cannot evaluate the truthfulness of a practice (i.e. in scientific terms). In this article we discuss and summarize comparative data about traditional uses, phytochemistry, pharmacology and toxicity of Alstonia scholaris and Alstonia macrophylla. Moreover, in order to unfold future research opportunities, lacunae in the present knowledge are also highlighted.
The population of the world reached seven billion in 2012. Pakistan's population stands at more than 180 million, is growing rapidly, and has the highest unmet need for family planning (FP) in isolated rural areas. The low usage of contraception in the rural areas of Pakistan correlates with the level of isolation, poverty, illiteracy, and to a large extent, religious misinterpretations/misconceptions. Almost 25% of couples who desired FP services were not receiving them for a variety of reasons of which religion could be one, especially in the rural remote areas where the media is still not reaching and influencing mind-sets. In this scenario, the role of social marketing in bringing about attitudinal and behavioural change among users in underserved areas and gatekeepers and opinion makers in society must not be neglected. The work in promoting FP, contraception and birth spacing requires authentic evidence from similar sociocultural contexts and this endeavour of compiling case studies from various Islamic countries on their FP initiatives is a good step. Governments around the world, including many in the Islamic world, support FP programmes to enable individuals and couples to choose the number and timing of their children.
Matched MeSH terms: Contraception/methods*; Sex Education/methods*
When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets.