Calf massager: Intervention for body muscle discomfort during prolonged standing

Many occupations require workers to stand for long periods of time without proper interventions, which causes discomfort in the back and lower limbs. Therefore, this study aims to assess the effectiveness in alleviating body muscle discomfort during prolonged standing through the use of a calf massager. This study was conducted among male workers at a manufacturer with production line workers and the list was obtained from the HR Department and simple random sampling was done by number categorization. A total of 100 respondents (50 respondents for both the control and the experimental groups) participated in this study. The experiment took place in a room with a similar setup for the production line. Each respondent was requested to perform the simulated task for 2 hr. For the experimental group, the calf massager was turned on every 15 min. At every 15‐min interval after turning on the calf massager, respondents from both groups were required to evaluate their discomfort level on a Borg's scale CR‐10 questionnaire. The results showed that the level of body discomfort among respondents in the experimental group reduced (20–30%) compared with that of the control group. Multivariate analysis results revealed that the discomfort rating for the lower back, knees, thighs, calves, and feet was significantly lower (p < .05) among the experimental group compared with the control group. For lower body parts, the lower back region was statistically significant (p < .05) at the 90th, 105th, and 120th min; the thigh region was statistically significant (p < .05) at the 120th min; the knee region was statistically significant (p < .05) at the 105th and 120th min; the calf region was statistically significant (p < .05) at all minute intervals except the 15th and 45th min, while the feet region, was statistically significant at the 105th and 120th min. Therefore, this study indicates that calf massage treatment is capable of reducing body muscle discomfort during prolonged standing and highlights the significance of calf massage.     

Detection of dental abnormalities using SVM and PSVM

Landmarks needed for detecting dental abnormalities in cephalometric analysis were selected from the digital image, and the angle values needed for dental analysis were calculated and stored in a database which is used for developing training dataset. Principal component analysis was applied for dimension reduction to get the desired feature vectors which are trained and tested using support vector machine and proximal support vector machine classifier to detect the dental abnormalities, the performance of the classifiers were also compared.     

Optimal temperature policies for catalytic transport reactors under periodic operation

The influence of inlet gas concentration cycling on the optimal temperature policy of catalytic transport reactors is studied theoretically. The model considered is based on plug flow of gas and catalyst particles with negligible interand intra-particle diffusional resistances and concentration dependent deactivation kinetics. To utilise the concentration of the reactant and the activity of the deactivating catalyst fully a proper temperature sequence along the reactor is needed. Thus, a general optimal temperature policy using the continuous minimum principle is derived for the reactor under periodic operation. The model equations are solved analytically for gas concentration, activity and temperature profiles. Resonance behaviour (maximum in conversion with pulse width) is obtained using the optimal temperature policy for certain sets of parameters. The effects of activation energy groups, reaction and deactivation constant groups and inlet temperature on the optimal temperature policy under periodic operation are evaluated. In all cases an improvement in conversion with the optimal temperature policy under periodic operation over that with an isothermal policy under periodic operation is obtained. A suboptimal policy, comprising constant temperature over different reactor sections, which is useful for implementation purposes is also discussed.     

Fine grinding of silicon wafers: a mathematical model for the chuck shape

Fine grinding of silicon wafers is a patented technology to manufacture super flat semiconductor wafers cost-effectively. Two papers on fine grinding were previously published in this journal, one discussed its uniqueness and special requirements, and the other presented the results of a designed experimental investigation. As a follow up, this paper presents a study aiming at overcoming one of the technical barriers that have hindered the widespread application of this technology, namely, the difficulty and uncertainty in chuck preparation. Although the chuck shape is critically important in fine grinding, there are no standard procedures for its preparation. Furthermore, the information on the relation between the set-up parameters and the resulting chuck shape is not readily available. In this paper, a mathematical model for the chuck shape is first developed. Then the model is used to predict the relations between the chuck shape and the set-up parameters. Finally, the results of the pilot experiments to verify the model are discussed.     

Probabilistic Health-lnformatics and Bioterrorism

In this article, new probabilistic health-informatics indices connecting probabilities： Pr（A）,Pr（B）,Pr（A IB） and P r（A ]B-） are discovered, where .4 and B denote respectively the ＂ability of a hospital to treat anthrax patients＂ and ＂whether a hospital drilled to be prepared to deal with an adverse bioterrorism＂. These probabilistic informatics are not seen in any textbooks or journal articles and yet, they are too valuable to be unnoticed to comprehend the hospitals＇ preparedness to treat anthrax patients in an outbreak of bioterrorism. A demonstration of this new probabilistic informatics is made in this article with the data in the U.S. Government＇s General Accounting Office＇s report GA0-03-924. Via this example, this article advocates the importance of the above mentioned probabilistic-informatics for health professionals to understand and act swiftly to deal with public health emergencies.     

An Efficient Lossless Telemetry Data Compression and Fault Analysis System Using 2SMLZ and CMOW-DLNN

Wireless Personal Communications - In this paper, the effect of perfect electric conductor (PEC) as a ground plane on antenna array is investigated. Vertical electric dipole which is of...     

Evaluation of potential anti‐cancer activity of cationic liposomal nanoformulated Lycopodium clavatum in colon cancer cells

Research dealing with early diagnosis and efficient treatment in colon cancer to improve patient''s survival is still under investigation. Chemotherapeutic agent result in high systemic toxicity due to their non‐specific actions on DNA repair and/or cell replication. Traditional medicine such as Lycopodium clavatum (LC) has been claimed to have therapeutic potentials against cancer. The present study focuses on targeted drug delivery of cationic liposomal nanoformulated LC (CL‐LC) in colon cancer cells (HCT15) and comparing the efficacy with an anti‐colon cancer drug, 7‐ethyl‐10‐hydroxy‐camptothecin (SN38) along with its nanoformulated form (CL‐SN38). The colloidal suspension of LC was made using thin film hydration method. The drugs were characterised using ultraviolet, dynamic light scattering, scanning electron microscopy, energy, dispersive X‐ray spectroscopy. In vitro drug release showed kinetics of 49 and 89% of SN38 and LC, whereas CL‐SN38 and CL‐LC showed 73 and 74% of sustained drug release, respectively. Studies on morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis of Bcl‐2, Bax, p53 by real‐time polymerase chain reaction and western blot analysis of Bad and p53 protein were performed. Nanoformulated LC significantly inhibited growth and increased the apoptosis of colon cancer cells indicating its potential anti‐cancer activity against colon cancer cells.Inspec keywords: cancer, biological organs, cellular biophysics, drug delivery systems, drugs, nanomedicine, genetics, DNA, molecular biophysics, biochemistry, lipid bilayers, toxicology, suspensions, colloids, light scattering, X‐ray chemical analysis, solvation, enzymes, nanostructured materialsOther keywords: energy dispersive X‐ray spectroscopy, in vitro drug release, morphological changes, cell viability, cytotoxicity, apoptosis, cancer‐associated gene expression analysis, Bcl‐2, Bax, real‐time polymerase chain reaction, western blot analysis, Bad protein, p53 protein, scanning electron microscopy, dynamic light scattering, ultraviolet scattering, thin film hydration method, colloidal suspension, nanoformulated form CL‐SN38, 7‐ethyl‐10‐hydroxy‐camptothecin, anticolon cancer drug, colon cancer cells HCT15, cationic liposomal nanoformulated LC, targeted drug delivery, therapeutic potentials, Lycopodium clavatum, traditional medicines, cell replication, DNA repair, nonspecific actions, high systemic toxicity, chemotherapeutic agents, patient survival, colon cancer treatment, colon cancer diagnosis, CL‐LC, potential anticancer activity     

Automatic classification of Tamil documents using vector space model and artificial neural network

Automatic text classification based on vector space model (VSM), artificial neural networks (ANN), K-nearest neighbor (KNN), Naives Bayes (NB) and support vector machine (SVM) have been applied on English language documents, and gained popularity among text mining and information retrieval (IR) researchers. This paper proposes the application of VSM and ANN for the classification of Tamil language documents. Tamil is morphologically rich Dravidian classical language. The development of internet led to an exponential increase in the amount of electronic documents not only in English but also other regional languages. The automatic classification of Tamil documents has not been explored in detail so far. In this paper, corpus is used to construct and test the VSM and ANN models. Methods of document representation, assigning weights that reflect the importance of each term are discussed. In a traditional word-matching based categorization system, the most popular document representation is VSM. This method needs a high dimensional space to represent the documents. The ANN classifier requires smaller number of features. The experimental results show that ANN model achieves 93.33% which is better than the performance of VSM which yields 90.33% on Tamil document classification.     

MELOC-X: extended memory and location optimized caching for large mobile ad hoc networks of UAVs

Effective caching in mobile ad hoc network increases data availability. However, caching at strategic locations with reduced (controlled) number of copies is needed for many military applications involving UAVs to address security concerns, less maintenance overhead and maintaining availability. In general, existing cooperative caching approaches are deficient in finding the reduced number of strategic cache locations. One such technique to reduce the number of strategic cache locations without affecting the efficacy of data access for a small network topology of UAVs is called “memory and location optimized caching scheme (MELOC)”. However, having a single broker and metadata broadcast across the whole network in MELOC lead to severe performance hindrance in case of a large network topology of UAVs. Moreover, frequent cache replacements due to a change in network topology do not favor cache hit and bandwidth conservation in case of large mobile networks consisting of UAVs. In this paper, we design and evaluate an extended version of “MELOC called MELOC-X”, which suits large network topologies of UAVs by overcoming the above challenges. Our comparison with one such recent scheme with similar objectives showcased a significant improvement in performance. We also evaluate the impact of this scheme with respect to different metrics including the average number of hops, the average roundtrip time (i.e., average query latency), cache hits and mobility to access cached data through extensive simulations.