Displaying publications 81 - 100 of 365 in total

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  1. Fulltext An Enhanced Distributed Data Aggregation Method in the Internet of Things
    Homaei MH, Salwana E, Shamshirband S
    Sensors (Basel), 2019 Jul 18;19(14).
    PMID: 31323905 DOI: 10.3390/s19143173
    "Internet of Things (IoT)" has emerged as a novel concept in the world of technology and communication. In modern network technologies, the capability of transmitting data through data communication networks (such as Internet or intranet) is provided for each organism (e.g. human beings, animals, things, and so forth). Due to the limited hardware and operational communication capability as well as small dimensions, IoT undergoes several challenges. Such inherent challenges not only cause fundamental restrictions in the efficiency of aggregation, transmission, and communication between nodes; but they also degrade routing performance. To cope with the reduced availability time and unstable communications among nodes, data aggregation, and transmission approaches in such networks are designed more intelligently. In this paper, a distributed method is proposed to set child balance among nodes. In this method, the height of the network graph increased through restricting the degree; and network congestion reduced as a result. In addition, a dynamic data aggregation approach based on Learning Automata was proposed for Routing Protocol for Low-Power and Lossy Networks (LA-RPL). More specifically, each node was equipped with learning automata in order to perform data aggregation and transmissions. Simulation and experimental results indicate that the LA-RPL has better efficiency than the basic methods used in terms of energy consumption, network control overhead, end-to-end delay, loss packet and aggregation rates.
    Matched MeSH terms: Data Collection
  2. Social Profiling: A Review, Taxonomy, and Challenges
    Bilal M, Gani A, Lali MIU, Marjani M, Malik N
    Cyberpsychol Behav Soc Netw, 2019 Jul;22(7):433-450.
    PMID: 31074639 DOI: 10.1089/cyber.2018.0670
    Social media has taken an important place in the routine life of people. Every single second, users from all over the world are sharing interests, emotions, and other useful information that leads to the generation of huge volumes of user-generated data. Profiling users by extracting attribute information from social media data has been gaining importance with the increasing user-generated content over social media platforms. Meeting the user's satisfaction level for information collection is becoming more challenging and difficult. This is because of too much noise generated, which affects the process of information collection due to explosively increasing online data. Social profiling is an emerging approach to overcome the challenges faced in meeting user's demands by introducing the concept of personalized search while keeping in consideration user profiles generated using social network data. This study reviews and classifies research inferring users social profile attributes from social media data as individual and group profiling. The existing techniques along with utilized data sources, the limitations, and challenges are highlighted. The prominent approaches adopted include Machine Learning, Ontology, and Fuzzy logic. Social media data from Twitter and Facebook have been used by most of the studies to infer the social attributes of users. The studies show that user social attributes, including age, gender, home location, wellness, emotion, opinion, relation, influence, and so on, still need to be explored. This review gives researchers insights of the current state of literature and challenges for inferring user profile attributes using social media data.
    Matched MeSH terms: Data Collection/methods*
  3. Acute Kidney Injury and Risk of Death After Elective Surgery: Prospective Analysis of Data From an International Cohort Study
    Chaudery H, MacDonald N, Ahmad T, Chandra S, Tantri A, Sivasakthi V, et al.
    Anesth Analg, 2019 05;128(5):1022-1029.
    PMID: 30418232 DOI: 10.1213/ANE.0000000000003923
    BACKGROUND: Postoperative acute kidney injury (AKI) is associated with a high mortality rate. However, the relationship among AKI, its associations, and mortality is not well understood.

    METHODS: Planned analysis of data was collected during an international 7-day cohort study of adults undergoing elective in-patient surgery. AKI was defined using Kidney Disease Improving Global Outcomes criteria. Patients missing preoperative creatinine data were excluded. We used multivariable logistic regression to examine the relationships among preoperative creatinine-based estimated glomerular filtration rate (eGFR), postoperative AKI, and hospital mortality, accounting for the effects of age, major comorbid diseases, and nature and severity of surgical intervention on outcomes. We similarly modeled preoperative associations of AKI. Data are presented as n (%) or odds ratios (ORs) with 95% confidence intervals.

    RESULTS: A total of 36,357 patients were included, 743 (2.0%) of whom developed AKI with 73 (9.8%) deaths in hospital. AKI affected 73 of 196 (37.2%) of all patients who died. Mortality was strongly associated with the severity of AKI (stage 1: OR, 2.57 [1.3-5.0]; stage 2: OR, 8.6 [5.0-15.1]; stage 3: OR, 30.1 [18.5-49.0]). Low preoperative eGFR was strongly associated with AKI. However, in our model, lower eGFR was not associated with increasing mortality in patients who did not develop AKI. Conversely, in older patients, high preoperative eGFR (>90 mL·minute·1.73 m) was associated with an increasing risk of death, potentially reflecting poor muscle mass.

    CONCLUSIONS: The occurrence and severity of AKI are strongly associated with risk of death after surgery. However, the relationship between preoperative renal function as assessed by serum creatinine-based eGFR and risk of death dependent on patient age and whether AKI develops postoperatively.

    Matched MeSH terms: Data Collection
  4. Observation of Single Top Quark Production in Association with a Z Boson in Proton-Proton Collisions at sqrt[s]=13  TeV
    Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Asilar E, Bergauer T, et al.
    Phys Rev Lett, 2019 Apr 05;122(13):132003.
    PMID: 31012605 DOI: 10.1103/PhysRevLett.122.132003
    The observation of single top quark production in association with a Z boson and a quark (tZq) is reported. Events from proton-proton collisions at a center-of-mass energy of 13 TeV containing three charged leptons (either electrons or muons) and at least two jets are analyzed. The data were collected with the CMS detector in 2016 and 2017 and correspond to an integrated luminosity of 77.4fb^{-1}. The increased integrated luminosity, a multivariate lepton identification, and a redesigned analysis strategy improve significantly the sensitivity of the analysis compared to previous searches for tZq production. The tZq signal is observed with a significance well over 5 standard deviations. The measured tZq production cross section is σ(pp→tZq→tℓ^{+}ℓ^{-}q)=111±13(stat)_{-9}^{+11}(syst)  fb, for dilepton invariant masses above 30 GeV, in agreement with the standard model expectation.
    Matched MeSH terms: Data Collection
  5. Fulltext Real Time Microwave Biochemical Sensor Based on Circular SIW Approach for Aqueous Dielectric Detection
    Mohd Bahar AA, Zakaria Z, Md Arshad MK, Isa AAM, Dasril Y, Alahnomi RA
    Sci Rep, 2019 04 02;9(1):5467.
    PMID: 30940843 DOI: 10.1038/s41598-019-41702-3
    In this study, a critical evaluation of analyte dielectric properties in a microvolume was undertaken, using a microwave biochemical sensor based on a circular substrate integrated waveguide (CSIW) topology. These dielectric properties were numerically investigated based on the resonant perturbation method, as this method provides the best sensing performance as a real-time biochemical detector. To validate these findings, shifts of the resonant frequency in the presence of aqueous solvents were compared with an ideal permittivity. The sensor prototype required a 2.5 µL volume of the liquid sample each time, which still offered an overall accuracy of better than 99.06%, with an average error measurement of ±0.44%, compared with the commercial and ideal permittivity values. The unloaded Qu factor of the circular substrate-integrated waveguide (CSIW) sensor achieved more than 400 to ensure a precise measurement. At 4.4 GHz, a good agreement was observed between simulated and measured results within a broad frequency range, from 1 to 6 GHz. The proposed sensor, therefore, offers high sensitivity detection, a simple structural design, a fast-sensing response, and cost-effectiveness. The proposed sensor in this study will facilitate real improvements in any material characterization applications such as pharmaceutical, bio-sensing, and food processing applications.
    Matched MeSH terms: Data Collection
  6. Combination of Searches for Higgs Boson Pair Production in Proton-Proton Collisions at sqrt[s]=13  TeV
    Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Asilar E, Bergauer T, et al.
    Phys Rev Lett, 2019 Mar 29;122(12):121803.
    PMID: 30978057 DOI: 10.1103/PhysRevLett.122.121803
    This Letter describes a search for Higgs boson pair production using the combined results from four final states: bbγγ, bbττ, bbbb, and bbVV, where V represents a W or Z boson. The search is performed using data collected in 2016 by the CMS experiment from LHC proton-proton collisions at sqrt[s]=13  TeV, corresponding to an integrated luminosity of 35.9  fb^{-1}. Limits are set on the Higgs boson pair production cross section. A 95% confidence level observed (expected) upper limit on the nonresonant production cross section is set at 22.2 (12.8) times the standard model value. A search for narrow resonances decaying to Higgs boson pairs is also performed in the mass range 250-3000 GeV. No evidence for a signal is observed, and upper limits are set on the resonance production cross section.
    Matched MeSH terms: Data Collection
  7. First Measurements of Absolute Branching Fractions of the Ξ_{c}^{0} Baryon at Belle
    Li YB, Shen CP, Yuan CZ, Adachi I, Aihara H, Al Said S, et al.
    Phys Rev Lett, 2019 Mar 01;122(8):082001.
    PMID: 30932568 DOI: 10.1103/PhysRevLett.122.082001
    We present the first measurements of absolute branching fractions of Ξ_{c}^{0} decays into Ξ^{-}π^{+}, ΛK^{-}π^{+}, and pK^{-}K^{-}π^{+} final states. The measurements are made using a dataset comprising (772±11)×10^{6} BB[over ¯] pairs collected at the ϒ(4S) resonance with the Belle detector at the KEKB e^{+}e^{-} collider. We first measure the absolute branching fraction for B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0} using a missing-mass technique; the result is B(B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0})=(9.51±2.10±0.88)×10^{-4}. We subsequently measure the product branching fractions B(B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0})B(Ξ_{c}^{0}→Ξ^{-}π^{+}), B(B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0})B(Ξ_{c}^{0}→ΛK^{-}π^{+}), and B(B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0})B(Ξ_{c}^{0}→pK^{-}K^{-}π^{+}) with improved precision. Dividing these product branching fractions by the result for B^{-}→Λ[over ¯]_{c}^{-}Ξ_{c}^{0} yields the following branching fractions: B(Ξ_{c}^{0}→Ξ^{-}π^{+})=(1.80±0.50±0.14)%, B(Ξ_{c}^{0}→ΛK^{-}π^{+})=(1.17±0.37±0.09)%, and B(Ξ_{c}^{0}→pK^{-}K^{-}π^{+})=(0.58±0.23±0.05)%. For the above branching fractions, the first uncertainties are statistical and the second are systematic. Our result for B(Ξ_{c}^{0}→Ξ^{-}π^{+}) can be combined with Ξ_{c}^{0} branching fractions measured relative to Ξ_{c}^{0}→Ξ^{-}π^{+} to yield other absolute Ξ_{c}^{0} branching fractions.
    Matched MeSH terms: Data Collection
  8. Search for the Higgs Boson Decaying to Two Muons in Proton-Proton Collisions at sqrt[s]=13  TeV
    Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Asilar E, Bergauer T, et al.
    Phys Rev Lett, 2019 Jan 18;122(2):021801.
    PMID: 30720313 DOI: 10.1103/PhysRevLett.122.021801
    A search for the Higgs boson decaying to two oppositely charged muons is presented using data recorded by the CMS experiment at the CERN LHC in 2016 at a center-of-mass energy sqrt[s]=13  TeV, corresponding to an integrated luminosity of 35.9  fb^{-1}. Data are found to be compatible with the predicted background. For a Higgs boson with a mass of 125.09 GeV, the 95% confidence level observed (background-only expected) upper limit on the production cross section times the branching fraction to a pair of muons is found to be 3.0 (2.5) times the standard model expectation. In combination with data recorded at center-of-mass energies sqrt[s]=7 and 8 TeV, the background-only expected upper limit improves to 2.2 times the standard model value with a standard model expected significance of 1.0 standard deviation. The corresponding observed upper limit is 2.9 with an observed significance of 0.9 standard deviation. This corresponds to an observed upper limit on the standard model Higgs boson branching fraction to muons of 6.4×10^{-4} and to an observed signal strength of 1.0±1.0(stat)±0.1(syst).
    Matched MeSH terms: Data Collection
  9. Search for a Light CP-odd Higgs Boson and Low-Mass Dark Matter at the Belle Experiment
    Seong IS, Vahsen SE, Adachi I, Aihara H, Al Said S, Asner DM, et al.
    Phys Rev Lett, 2019 Jan 11;122(1):011801.
    PMID: 31012694 DOI: 10.1103/PhysRevLett.122.011801
    We report on the first Belle search for a light CP-odd Higgs boson, A^{0}, that decays into low mass dark matter, χ, in final states with a single photon and missing energy. We search for events produced via the dipion transition ϒ(2S)→ϒ(1S)π^{+}π^{-}, followed by the on-shell process ϒ(1S)→γA^{0} with A^{0}→χχ, or by the off-shell process ϒ(1S)→γχχ. Utilizing a data sample of 157.3×10^{6} ϒ(2S) decays, we find no evidence for a signal. We set limits on the branching fractions of such processes in the mass ranges M_{A^{0}}<8.97  GeV/c^{2} and M_{χ}<4.44  GeV/c^{2}. We then use the limits on the off-shell process to set competitive limits on WIMP-nucleon scattering in the WIMP mass range below 5  GeV/c^{2}.
    Matched MeSH terms: Data Collection
  10. Fulltext An audit of paediatric dental patient assessment and recall in faculty of dentistry UiTM Sungai Buloh
    Aimi Shafiqah Shukri, Muhammad Syazwan Hassan, Venkiteswaran, Annapurny
    Compendium of Oral Science, 2019;6(1):26-34.
    MyJurnal
    Objective: To assess if the recall appointments and the use of radiographs for paediatric dental patients at Faculty of Dentistry, UiTM comply with current guidelines. Materials and Method: A retrospective study was conducted using patients’ dental records that were registered at the Faculty of Dentistry UiTM. The sample consisted of 350 randomly chosen treatment records of paediatric patients aged between birth and 16 years of age at the time of data collection which was in the year 2016. Data collection included demographic details, whom the cases were treated by, caries risk assessment, radiographs taken and time taken for the patient’s review appointments. Results: An initial sample size of 350 records were assessed. The mean age of patients seen when they were first seen is 6.3 years old. Caries Risk Assessment was not reported in majority of the cases (58%,). Baseline radiographs were taken in 44.6% of the cases. For the assessment of recall attendance, only samples with data on CRA was analysed (n=145). The review appointments at 3 months interval was 70% whereas at 6 months was 6.2% and one year recall was 6.7%. A chi-square test showed significant difference (p=0.013) between the category of operators for the 1-year review whereby review was higher among students and specialists as compared to dental officers. Conclusion: This study shows poor adherence to the recommended recall protocol as suggested by NICE and AAPD guidelines. Further studies need to be done to assess the patients’ and clinicians awareness regarding the recall protocol and determine the problems causing poor recall attendance.
    Matched MeSH terms: Data Collection
  11. Fulltext The value of stories in qualitative interviews: using narrative inquiry as a methodology
    JEFFREY, YEE KHONG LOONG
    Malaysian Journal of Qualitative Research, 2019;5(1):17-27.
    MyJurnal
    The research interview is a common method of choice for collecting data, particularly within the qualitative research tradition. This is because it lends well to the emergent nature and exploratory aims of qualitative research. Detailed accounts of what and how things happened, and who was involved, that is elaborate stories, can be located in interview responses. This is irrespective of whether or not the stories were deliberately elicited or regardless of the methodological stance adopted by the researcher. The ubiquity of stories therein signals the need for researchers using qualitative interviews to be cognizant of the narratives surrounding these stories and the analytical value they hold in their research. This paper presents the philosophical underpinnings and strategy of narrative inquiry, and illustrates how methods of collection and analysis can be shaped in concert with the methodology
    Matched MeSH terms: Data Collection
  12. Fulltext A study on patient's decision-making process in deciding treatment strategies: an illustration of using grounded theory approach
    LOW, LEE LAN, TONG, SENG FAH, LOW, WAH YUN
    Malaysian Journal of Qualitative Research, 2019;5(1):28-40.
    MyJurnal
    The learning curve for doing a good qualitative study is steep because qualitative methodologies are often vague and lack explicit steps. We detail the formulation of the grounded theory approach in a study of patients with type 2 diabetes mellitus who made decisions while strategizing their treatment types. This undertaking is to demonstrate how this systematic and yet flexible methods contributed to the understanding of the issue we were investigating. The process from deciding on research objectives and research questions, follow with systematic process for data collection and analysis allows us to generate a substantive theoretical model. By paying critical attention to theoretical saturation, grounded theory approach enabled us to construct all possible explanatory concepts related to decision making in strategizing diabetes treatment. We also describe the challenges throughout the whole research journey, including getting permission to interview patients, gaining the trust of research participants and staying open to the participants’ views.
    Matched MeSH terms: Data Collection
  13. Fulltext The primary health care performance initiative (PHCPI): Issues and challenges for Malaysia as a trailblazer country
    Anis Safura Ramli, Sri Wahyu Taher, Zainal Fitri Zakaria, Norsiah Ali, Nurainul Hana Shamsuddin, Wong Ping Foo, et al.
    Journal of Clinical and Health Sciences, 2019;4(1):4-21.
    MyJurnal
    A strong and robust Primary Health Care system is essential to achieving universal health
    coverage and to save lives. The Global Conference on Primary Health Care 2018: from Alma-Ata towards achieving Universal Health Coverage and the Sustainable Development Goals at
    Astana, Kazakhstan provided a platform for low‐ and middle‐ income countries to join the
    Primary Health Care Performance Initiative (PHCPI). At this Global Conference, Malaysia has
    declared to become a Trailblazer Country in the PHCPI and pledged to monitor her Vital Signs
    Profiles (VSP). However, the VSP project requires an honest and transparent data collection
    and monitoring of the Primary Health Care system, so as to identify gaps and guide policy in
    support of Primary Health Care reform. This is a huge commitment and can only be materialised
    if there is a collaborative partnership between Primary Care and Public Health providers.
    Fundamental to all of these, is the controversy concerning whether or not ‘Primary Care’ and
    ‘Primary Health Care’ represent the same entity. Confusion also occurs with regards to the role
    of ‘Primary Care’ and ‘Public Health’ providers in the Malaysian Primary Health Care system.
    This review aims to differentiate between Primary Care, Primary Health Care and Public Health,
    describe the relationships between the three entities and redefine the role of Primary Care and
    Public Health in the PHCPI-VSP in order to transform the Malaysian Primary Health Care
    system.
    Matched MeSH terms: Data Collection
  14. Fulltext DeepMoney: counterfeit money detection using generative adversarial networks
    Ali T, Jan S, Alkhodre A, Nauman M, Amin M, Siddiqui MS
    PeerJ Comput Sci, 2019;5:e216.
    PMID: 33816869 DOI: 10.7717/peerj-cs.216
    Conventional paper currency and modern electronic currency are two important modes of transactions. In several parts of the world, conventional methodology has clear precedence over its electronic counterpart. However, the identification of forged currency paper notes is now becoming an increasingly crucial problem because of the new and improved tactics employed by counterfeiters. In this paper, a machine assisted system-dubbed DeepMoney-is proposed which has been developed to discriminate fake notes from genuine ones. For this purpose, state-of-the-art models of machine learning called Generative Adversarial Networks (GANs) are employed. GANs use unsupervised learning to train a model that can then be used to perform supervised predictions. This flexibility provides the best of both worlds by allowing unlabelled data to be trained on whilst still making concrete predictions. This technique was applied to Pakistani banknotes. State-of-the-art image processing and feature recognition techniques were used to design the overall approach of a valid input. Augmented samples of images were used in the experiments which show that a high-precision machine can be developed to recognize genuine paper money. An accuracy of 80% has been achieved. The code is available as an open source to allow others to reproduce and build upon the efforts already made.
    Matched MeSH terms: Data Collection
  15. Fulltext Novel trajectory clustering method based on distance dependent Chinese restaurant process
    Arfa R, Yusof R, Shabanzadeh P
    PeerJ Comput Sci, 2019;5:e206.
    PMID: 33816859 DOI: 10.7717/peerj-cs.206
    Trajectory clustering and path modelling are two core tasks in intelligent transport systems with a wide range of applications, from modeling drivers' behavior to traffic monitoring of road intersections. Traditional trajectory analysis considers them as separate tasks, where the system first clusters the trajectories into a known number of clusters and then the path taken in each cluster is modelled. However, such a hierarchy does not allow the knowledge of the path model to be used to improve the performance of trajectory clustering. Based on the distance dependent Chinese restaurant process (DDCRP), a trajectory analysis system that simultaneously performs trajectory clustering and path modelling was proposed. Unlike most traditional approaches where the number of clusters should be known, the proposed method decides the number of clusters automatically. The proposed algorithm was tested on two publicly available trajectory datasets, and the experimental results recorded better performance and considerable improvement in both datasets for the task of trajectory clustering compared to traditional approaches. The study proved that the proposed method is an appropriate candidate to be used for trajectory clustering and path modelling.
    Matched MeSH terms: Data Collection
  16. Fulltext Usage and completeness of antimicrobial prescribing form within general intensive care unit in a tertiary hospital
    Nordin N. N., Lau, C. L., Wan Mat W. R., Yow, H. Y.
    Malaysian Journal of Medicine and Health Sciences, 2019;15(102):3-3.
    MyJurnal
    Introduction: The incidence of antimicrobial resistance (AMR) has increased worldwide including Malaysia, which may be attributed partly to inappropriate prescribing of antimicrobials. Antimicrobial prescribing form has been introduced to mandate appropriate antimicrobial prescription including documented indication as a key standard of antimicrobial stewardship practice. Hence, this current study aimed to determine the usage and completeness of the designated antimicrobial prescribing form that had been implemented in the General Intensive Care Unit (GICU), Universiti Kebangsaan Malaysia Medical Centre (UKMMC). Methods: This prospective observational study was carried out in GICU UKMMC from 30 August 2018 to 30 November 2018 by convenience sampling. The information that was recorded in the antimicrobial prescribing form was collected by using the designated data collection form. A total of 68 patients were included and 205 antimicrobial prescribing forms were evaluated. Results: There were 100% usage of antimicrobial prescribing forms found in this study. However, only 81 ± 8 % of these forms were completely filled. Indication for the antimicrobial prescription was not filled in 47% of the forms. Almost two thirds of the antimicrobial prescriptions were empirically indicated and one percent de-escalation of antimicrobial therapy was filled in the forms. These prescriptions comprised of 91.7% antibiotics, 7.8% antifungals and 0.5% antivirals. The suspected site of infections were primarily from the lungs (27%), gastrointestinal (16%), blood (16%) and central nervous system (14%). Piperacillin/Tazobactam was the most frequent antibiotic prescribed (21%), followed by third and fourth generation cephalosporins (20%). Conclusion: This study provided an overview of the uptake of the antimicrobial prescribing form implementation and highlighted the requirement for supplementary efforts to maximize the compliance of this form.
    Matched MeSH terms: Data Collection
  17. Fast and robust parameter estimaation in the application of fuzzy logistic equations in population growth
    Nor Atirah Izzah Zulkefli, Yeak Su Hoe, Normah Maan
    MATEMATIKA, 2019;35(2):249-259.
    MyJurnal
    In this paper, extended Runge-Kutta fourth order method for directly solving the fuzzy logistic problem is presented. The extended Runge-Kutta method has lower number of function evaluations, compared with the classical Runge-Kutta method. The numerical robustness of the method in parameter estimation is enhanced via error minimization in predicting growth rate and carrying capacity. The results of fuzzy logistic model with the estimated parameters have been compared with population growth data in Malaysia, which indicate that this method is more accurate that the data population. Numerical example is given to illustrate the efficiency of the proposed model. It is concluded that robust parameter estimation technique is efficient in modelling population growth.
    Matched MeSH terms: Data Collection
  18. Fulltext Portfolio optimization of risky assets using mean variance and mean cvar
    Hannah Nadiah Abdul Razak, Mohd. Azdi Maasar, Nur Hafidzah Hafidzuddin, Ernie Syufina Chun Lee
    Journal of Academia Universiti Teknologi MARA Negeri Sembilan, 2019;7(101):25-32.
    MyJurnal
    The aim of this research is to apply the variance and conditional value at risk (CVaR) as risk measures in portfolio selection problem. Consequently, we are motivated to compare the behavior of two different type of risk measures (variance and CVaR) when the expected returns of a portfolio vary from a low return to a higher return. To obtain an optimum portfolio of the assets, we minimize the risks using mean variance and mean CVaR models. Dataset with stocks for FBMKLCI is used to generate our scenario returns. Both models and dataset are coded and implemented in AMPL software. We compared the performance of both optimized portfolios constructed from the models in term of risk measure and realized returns. The optimal portfolios are evaluated across three different target returns that represent the low risk low returns, medium risk medium returns and high risk high returns portfolios. Numerical results show that the composition of portfolios for mean variance are generally more diversified compared to mean CVaR portfolios. The in sample results show that the seven optimal mean CVaR0:05 portfolios have lower CVaR0:05 values as compared to their optimal mean variance counterparts. Consequently, the standard deviation for mean variance optimal portfolios are lower than the standard deviation of its mean CVaR0:05 counterparts. For the out of sample analysis, we can conclude that mean variance portfolio only minimizes standard deviation at low target return. While, mean CVaR portfolios are favorable in minimizing risks at high target return.
    Matched MeSH terms: Data Collection
  19. Fulltext EXPERT SYSTEM TO DIAGNOSE DENGUE FEVER
    Mohd Zulhilmi Aqil Muhamad, Noor Hafhizah Abd Rahim
    UMT Journal of Undergraduate Research, 2019;1(4):67-76.
    MyJurnal
    Expert system is a system that emulates experts to aid in decision making. This system can be applied in various categories such as diagnosis, prediction, interpretation, and others. Expert System to Diagnose Dengue Fever is a web-based system which is integrated with prolog language in order to provide rules for dengue fever detection. The aims of this research are to study dengue fever symptoms and other illnesses related to the fever, to design an inference engine, and to build an expert system. The challenges faced while developing this expert system were the complexity of prolog codes and their integration with the web development. In this system, rules were developed by prolog language which define dengue fever and accuracy based on input from the user. This system is expected to aid users in self-detecting early symptoms of dengue fever before seeing the doctors.
    Matched MeSH terms: Data Collection
  20. Fulltext DAD-match; Security technique to prevent denial of service attack on duplicate address detection process in IPv6 link-local network
    Al-Ani AK, Anbar M, Manickam S, Al-Ani A
    PLoS One, 2019;14(4):e0214518.
    PMID: 30939154 DOI: 10.1371/journal.pone.0214518
    An efficiently unlimited address space is provided by Internet Protocol version 6 (IPv6). It aims to accommodate thousands of hundreds of unique devices on a similar link. This can be achieved through the Duplicate Address Detection (DAD) process. It is considered one of the core IPv6 network's functions. It is implemented to make sure that IP addresses do not conflict with each other on the same link. However, IPv6 design's functions are exposed to security threats like the DAD process, which is vulnerable to Denial of Service (DoS) attack. Such a threat prevents the host from configuring its IP address by responding to each Neighbor Solicitation (NS) through fake Neighbor Advertisement (NA). Various mechanisms have been proposed to secure the IPv6 DAD procedure. The proposed mechanisms, however, suffer from complexity, high processing time, and the consumption of more resources. The experiments-based findings revealed that all the existing mechanisms had failed to secure the IPv6 DAD process. Therefore, DAD-match security technique is proposed in this study to efficiently secure the DAD process consuming less processing time. DAD-match is built based on SHA-3 to hide the exchange tentative IP among hosts throughout the process of DAD in an IPv6 link-local network. The obtained experimental results demonstrated that the DAD-match security technique achieved less processing time compared with the existing mechanisms as it can resist a range of different threats like collision and brute-force attacks. The findings concluded that the DAD-match technique effectively prevents the DoS attack during the DAD process. The DAD-match technique is implemented on a small area IPv6 network; hence, the author future work is to implement and test the DAD-match technique on a large area IPv6 network.
    Matched MeSH terms: Data Collection
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