19672 research outputs found
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Root Exploit Detection and Features Optimization: Mobile Device and Blockchain Based Medical Data Management
No full textThe increasing demand for Android mobile devices and blockchain has motivated malware creators to develop mobile malware to compromise the blockchain. Although the blockchain is secure, attackers have managed to gain access into the blockchain as legal users, thereby comprising important and crucial information. Examples of mobile malware include root exploit, botnets, and Trojans and root exploit is one of the most dangerous malware. It compromises the operating system kernel in order to gain root privileges which are then used by attackers to bypass the security mechanisms, to gain complete control of the operating system, to install other possible types of malware to the devices, and finally, to steal victims’ private keys linked to the blockchain. For the purpose of maximizing the security of the blockchain-based medical data management (BMDM), it is crucial to investigate the novel features and approaches contained in root exploit malware. This study proposes to use the bio-inspired method of practical swarm optimization (PSO) which automatically select the exclusive features that contain the novel android debug bridge (ADB). This study also adopts boosting (adaboost, realadaboost, logitboost, and multiboost) to enhance the machine learning prediction that detects unknown root exploit, and scrutinized three categories of features including (1) system command, (2) directory path and (3) code-based. The evaluation gathered from this study suggests a marked accuracy value of 93% with Logitboost in the simulation. Logitboost also helped to predicted all the root exploit samples in our developed system, the root exploit detection system (RODS)
Discovering optimal features using static analysis and a genetic search based method for Android malware detection
No full textMobile device manufacturers are rapidly producing miscellaneous Android versions worldwide. Simultaneously, cyber criminals are executing malicious actions, such as tracking user activities, stealing personal data, and committing bank fraud. These criminals gain numerous benefits as too many people use Android for their daily routines, including important communi-cations. With this in mind, security practitioners have conducted static and dynamic analyses to identify malware. This study used static analysis because of its overall code coverage, low resource consumption, and rapid processing. However, static analysis requires a minimum number of features to efficiently classify malware. Therefore, we used genetic search (GS), which is a search based on a genetic algorithm (GA), to select the features among 106 strings. To evaluate the best features determined by GS, we used five machine learning classifiers, namely, Naïve Bayes (NB), functional trees (FT), J48, random forest (RF), and multilayer perceptron (MLP). Among these classifiers, FT gave the highest accuracy (95%) and true positive rate (TPR) (96.7%) with the use of only six features
A sustainable quality assessment model for the information delivery in E-learning systems
No full textPurpose: The purpose of this study is to propose a sustainable quality assessment approach (model) for the e-learning systems keeping software perspective under consideration. E-learning is becoming mainstream due to its accessibility, state-of-the-art learning, training ease and cost effectiveness. However, the poor quality of e-learning systems is one of the major causes of several failures reported. Moreover, this arena lacks well-defined quality assessment measures. Hence, it is quite difficult to measure the overall quality of an e-learning system effectively. Design/methodology/approach: A pragmatic mixed-model philosophy was adopted for this study. A systematic literature review was performed to identify existing e-learning quality models and frameworks. Semi-structured interviews were conducted with e-learning experts following empirical investigations to identify the crucial quality characteristics of e-learning systems. Various statistical tests like principal component analysis, logistic regression, chi-square and analysis of means were applied to analyze the empirical data. These led to an adequate set of quality indicators that can be used by higher education institutions to assure the quality of e-learning systems. Findings: A sustainable quality assessment model for the information delivery in e-learning systems in software perspective has been proposed by exploring the state-of-the-art quality assessment/evaluation models and frameworks proposed for the e-learning systems. The proposed model can be used to assess and improve the process of information discovery and delivery of e-learning. Originality/value: The results obtained led to conclude that very limited attention is given to the quality of e-learning tools despite the importance of quality and its effect on e-learning system adoption and promotion. Moreover, the identified models and frameworks do not adequately address quality of e-learning systems from a software perspective
Neural Network-Based Muscle Torque Estimation Using Mechanomyography During Electrically-Evoked Knee Extension and Standing in Spinal Cord Injury
No full textThis study sought to design and deploy a torque monitoring system using an artificial neural network (ANN) with mechanomyography (MMG) for situations where muscle torque cannot be independently quantified. The MMG signals from the quadriceps were used to derive knee torque during prolonged functional electrical stimulation (FES)assisted isometric knee extensions and during standing in spinal cord injured (SCI) individuals. Three individuals with motor-complete SCI performed FES-evoked isometric quadriceps contractions on a Biodex dynamometer at 30° knee angle and at a fixed stimulation current, until the torque had declined to a minimum required for ANN model development. Two ANN models were developed based on different inputs; Root mean square (RMS) MMG and RMS-Zero crossing (ZC) which were derived from MMG. The performance of the ANN was evaluated by comparing model predicted torque against the actual torque derived from the dynamometer. MMG data from 5 other individuals with SCI who performed FES-evoked standing to fatigue-failure were used to validate the RMS and RMS-ZC ANN models. RMS and RMS-ZC of the MMG obtained from the FES standing experiments were then provided as inputs to the developed ANN models to calculate the predicted torque during the FES-evoked standing. The average correlation between the knee extension-predicted torque and the actual torque outputs were 0.87 ± 0.11 for RMS and 0.84 ± 0.13 for RMS-ZC. The average accuracy was 79 ± 14% for RMS and 86 ± 11% for RMS-ZC. The two models revealed significant trends in torque decrease, both suggesting a critical point around 50% torque drop where there were significant changes observed in RMS and RMS-ZC patterns. Based on these findings, both RMS and RMS-ZC ANN models performed similarly well in predicting FES-evoked knee extension torques in this population. However, interference was observed in the RMS-ZC values at a time around knee buckling. The developed ANN models could be used to estimate muscle torque in real-time, thereby providing safer automated FES control of standing in persons with motor-complete SCI
Defining potentials and barriers to trade in the Malaysia–Chile partnership
No full textPurpose: The purpose of this paper is to investigate the potentials and barriers to trade in the Malaysia–Chile partnership. Design/methodology/approach: This paper estimates two-way export potentials from an augmented three-dimensional panel gravity model of bilateral trade between Malaysia and the Latin America and the Caribbean (LAC) region, spanning the 1990–2014 period. Utilizing interviews with government officials and industry experts in Malaysia and Chile, this paper also provides insights into market access issues. Findings: The empirical findings of this study suggest that Malaysia has trade potential in Chile, but Chile is “overtrading” with Malaysia. By major products traded, both countries are found to be “overtrading,” as the export basket remains concentrated in this partnership. Through the interviews, fewer restrictions are reported by the various stakeholders, as the extent of trade engagement remains somewhat low. The main challenge identified within specific sectors in both the countries relates mainly to procedures established to secure compliance with labeling regulations for food products. Research limitations/implications: The sectoral findings reveal that there is indeed scope for expanding exports beyond the current major products traded, particularly in base metal and scientific and measuring equipment from the Malaysia and Chile perspectives, respectively. Thus, product diversification matters to intensify trade cooperation between the two countries. Non-tariff measures need to be streamlined by both parties to ensure further product diversification to food trade, particularly for Chile. Originality/value: The limited literature on cross-regional trade within the broader framework of Southeast Asia and LAC only support the fact that potentials do exist but do not appear to provide much research evidence. Empirically, this paper will add to the existing literature on the potentials that hold in the Malaysia–Chile partnership. Further, a lack of adequate information remains on market access and other barriers in both the nations to facilitate decisions on trade opportunities. The findings of the study fill that vacuum of information pertaining to market access and trade facilitation through interviews with various stakeholders in Malaysia and Chile
Not Everyone Wants Roads: Assessing Indigenous People’s Support for Roads in a Globally Important Tiger Conservation Landscape
No full text[No abstract available
Complementary and Alternative Medicine Use and Symptom Burden in Women Undergoing Chemotherapy for Breast Cancer in Malaysia
No full textBackground: Complementary and alternative medicine (CAM) is commonly used for cancer- and chemotherapy-related symptoms. Nurses are likely to encounter many CAM users in their practice. Objective: The aims of this study were to assess CAM use and examine the symptom burden of CAM and non-CAM users among patients with breast cancer who are undergoing chemotherapy. Methods: A CAM use questionnaire and the Side-Effect Burden Scale were administered to 546 patients. Complementary and alternative medicine use was categorized as mind-body practices (MBPs), natural products (NPs), or traditional medicine (TM). Results: We identified 386 CAM users (70.7%) in this study. The CAM users reported a higher marginal mean total symptom burden score (40.39 ± 2.6) than non-CAM users (36.93 ± 3.21), although this difference was not statistically significant (P =.09). Triple-modality (MBP-NP-TM) CAM users had a significantly higher marginal mean total symptom burden score (47.44 ± 4.12) than single-modality (MBP) users (34.09 ± 4.43). The risk of having a high total symptom burden score was 12.9-fold higher among the MBP-NP-TM users than among the MBP users. Conclusions: Complementary and alternative medicine use is common among Malaysian patients who are undergoing chemotherapy for breast cancer. However, CAM and non-CAM users reported similar symptom burdens, although single-modality use of MBP is likely associated with a lower symptom burden. Implications for Practice: Nurses should keep abreast of current developments and trends in CAM use. Understanding CAM use and the related symptom burden will allow nurses to initiate open discussion and guide their patients in seeking additional information or referrals for a particular therapy
Genetic and haplotype analyses targeting cytochrome b gene of Plasmodium knowlesi isolates of Malaysian Borneo and Peninsular Malaysia
No full textMalaria is a notorious disease which causes major global morbidity and mortality. This study aims to investigate the genetic and haplotype differences of Plasmodium knowlesi (P. knowlesi) isolates in Malaysian Borneo and Peninsular Malaysia based on the molecular analysis of the cytochrome b (cyt b) gene. The cyt b gene of 49 P. knowlesi isolates collected from Sabah, Malaysian Borneo and Peninsular Malaysia was amplified using PCR, cloned into a commercialized vector and sequenced. In addition, 45 cyt b sequences were retrieved from humans and macaques bringing to a total of 94 cyt b gene nucleotide sequences for phylogenetic analysis. Genetic and haplotype analyses of the cyt b were analyzed using MEGA6 and DnaSP ver. 5.10.01. The haplotype genealogical linkage of cyt b was generated using NETWORK ver. 4.6.1.3. Our phylogenetic tree revealed the conservation of the cyt b coding sequences with no distinct cluster across different geographic regions. Nucleotide analysis of cyt b showed that the P. knowlesi isolates underwent purifying selection with population expansion, which was further supported by extensive haplotype sharing between the macaques and humans from Malaysian Borneo and Peninsular Malaysia in the median-joining network analysis. This study expands knowledge on conservation of the zoonotic P. knowlesi cyt b gene between Malaysian Borneo and Peninsular Malaysia
The number of subgroups of a direct product of cyclic p-groups
No full textFor a prime p and positive integer n, let Cp (n) and Cp (n) denote the elementary abelian p-group of order pn and the cyclic group of order pn, respectively. In this paper, we obtain an explicit formula for determining the number of subgroups of the direct product Cp (r) ×Cps where r and s are positive integers
Employment as a journey or a destination? Interpreting graduates’ and employers’ perceptions – a Malaysia case study
No full textAs human capital came to the fore in the discourse on economic growth, so too has the concepts of employment prospects and employability attributes as students transit to the labor market. This paper examines three issues in this transition in the context of Malaysia. These are, first, how important is employment prospects a consideration when students choose institutions to join and programs to pursue? Second, what is their understanding of the attributes needed for employability? Third, how well do students’ understanding of both concepts accord with how employers understand them? Using a combination of survey and face-to-face interviews, this study confirmed the considerable importance of both concepts in students’ study decisions. Their understanding was broadly congruent with that of employers. These findings have implications for students’ learning experiences, for the education system, and for policy-makers hoping for the human capital needed to make the leap from a middle-income to a high-income nation