An Adaptive Opportunistic Transmission for Unlicensed Spectrum Sharing in Heterogeneous Networks

Efficient utilization of spectrum resources is a fundamental issue of wireless communications due to its scarcity. To improve the efficiency of spectrum utilization, the spectrum sharing for unlicensed bands is being regarded as one of key technologies in the next generation wireless networks. A number of schemes such as Listen-Before-Talk(LBT) and carrier sensor adaptive transmission (CSAT) have been suggested from this aspect, but more efficient sharing schemes are required for improving spectrum utilization efficiency. This work considers an opportunistic transmission approach and a dynamic Contention Window (CW) adjustment scheme for LTE-U users sharing the unlicensed spectrum with Wi-Fi, in order to enhance the overall system throughput. The decision criteria for the dynamic adjustment of CW are based on the collision evaluation, derived from the collision probability of the system. The overall performance can be improved due to the adaptive adjustment of the CW. Simulation results show that our proposed scheme outperforms the Distributed Coordination Function (DCF) mechanism of IEEE 802.11 MAC.

Lyapunov Type Inequalities for Fractional Impulsive Hamiltonian Systems

This paper deals with study about fractional order impulsive Hamiltonian systems and fractional impulsive Sturm-Liouville type problems derived from these systems. The main purpose of this paper devotes to obtain so called Lyapunov type inequalities for mentioned problems. Also, in view point on applicability of obtained inequalities, some qualitative properties such as stability, disconjugacy, nonexistence and oscillatory behaviour of fractional Hamiltonian systems and fractional Sturm-Liouville type problems under impulsive conditions will be derived. At the end, we want to point out that for studying fractional order Hamiltonian systems, we will apply recently introduced fractional Conformable operators.

An Integrated Cloud Service of Application Delivery in Virtualized Environments

Virtualization technologies are experiencing a renewed interest as a way to improve system reliability, and availability, reduce costs, and provide flexibility. This paper presents the development on leverage existing cloud infrastructure and virtualization tools. We adopted some virtualization technologies which improve portability, manageability and compatibility of applications by encapsulating them from the underlying operating system on which they are executed. Given the development of application virtualization, it allows shifting the user’s applications from the traditional PC environment to the virtualized environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible and web-based application virtualization service represents the next significant step to the mobile workplace, and it lets user executes their applications from virtually anywhere. 

Hybrid MIMO-OFDM Detection Scheme for High Performance

In recent years, a multi-antenna system is actively used to improve the performance of the communication. A MIMO-OFDM system can provide multiplexing gain or diversity gain. These gains are obtained in proportion to the increase of the number of antennas. In order to provide the optimal gain of the MIMO-OFDM system, various transmission and reception schemes are presented. This paper aims to propose a hybrid scheme that base station provides both diversity gain and multiplexing gain at the same time.

Disaggregating and Forecasting the Total Energy Consumption of a Building: A Case Study of a High Cooling Demand Facility

Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  

Study on the Effect of Pre-Operative Patient Education on Post-Operative Outcomes

Patient satisfaction represents a crucial aspect in the evaluation of health care services. Preoperative teaching provides the patient with pertinent information concerning the surgical process and the intended surgical procedure as well as anticipated patient behavior (anxiety, fear), expected sensation, and the probable outcomes. Although patient education is part of Accreditation protocols, it is not uniform at most places. The aim of this study was to try to assess the benefit of preoperative patient education on selected post-operative outcome parameters; mainly, post-operative pain scores, requirement of additional analgesia, return to activity of daily living and overall patient satisfaction, and try to standardize few education protocols. Dependent variables were measured before and after the treatment on a study population of 302 volunteers. Educational intervention was provided by the Investigator in the preoperative period to the study group through personal counseling. An information booklet contained detailed information was also provided. Statistical Analysis was done using Chi square test, Mann Whitney u test and Fischer Exact Test on a total of 302 subjects. P value

Prevalence of Headache among Adult Population in Urban Varanasi, India

Headache is one of the most ubiquitous and frequent neurological disorders interfering with everyday life in all countries. India appears to be no exception. Objectives are to assess the prevalence of headache among adult population in urban area of Varanasi and to find out factors influencing the occurrence of headache. A community based cross sectional study was conducted among adult population in urban area of Varanasi district, Uttar Pradesh, India. Total 151 eligible respondents were interviewed by simple random sampling technique. Proportion percentage and Chisquare test were applied for data analysis. Out of 151 respondents, majority (58.3%) were females. In this study, 92.8% respondents belonged to age group 18-60 years while 7.2% was either 60 year of age or above. The overall prevalence of headache was found to be 51.1%. Highest and lowest prevalence of headache was recorded in age groups 18-29 year & 40-49 year respectively. Headache was 62.1% in illiterate and was 40.0% among graduate & above. Unskilled workers had more headache 73.1% than other type of occupation. Headache was more prevalent among unemployed (35.9%) than employed (6.4%). Females had higher family history of headache (48.9%) as compared to males (41.3%). Study subjects having peaceful relation with family members, relatives and neighbors had more headache than those having no peaceful relation.  

Submicron Size of Alumina/Titania Tubes for CO2-CH4 Conversion

This research provides a systematic way to study and better understand double nano-tubular structure of alunina (Al2O3) and titania (TiO2). The TiO2 NT was prepared by immersing Al2O3 template in 0.02 M titanium fluoride (TiF4) solution (pH=3) at 25 °C for 120 min, followed by annealing at 450 °C for 1 h to obtain anatase TiO2 NT in the Al2O3 template. Large-scale development of film for nanotube-based CO2 capture and conversion can potentially result in more efficient energy harvesting. In addition, the production process will be relatively environmentally friendly. The knowledge generated by this research will significantly advance research in the area of Al2O3, TiO2, CaO, and Ca2O3 nano-structure film fabrication and applications for CO2 capture and conversion. This green energy source will potentially reduce reliance on carbon-based energy resources and increase interest in science and engineering careers.

Using Information Theory to Observe Natural Intelligence and Artificial Intelligence

This paper takes a philosophical view as axiom, and reveals the relationship between information theory and Natural Intelligence and Artificial Intelligence under real world conditions. This paper also derives the relationship between natural intelligence and nature. According to communication principle of information theory, Natural Intelligence can be divided into real part and virtual part. Based on information theory principle that Information does not increase, the restriction mechanism of Natural Intelligence creativity is conducted. The restriction mechanism of creativity reveals the limit of natural intelligence and artificial intelligence. The paper provides a new angle to observe natural intelligence and artificial intelligence.

New Insights for Soft Skills Development in Vietnamese Business Schools: Defining Essential Soft Skills for Maximizing Graduates’ Career Success

Within Vietnam's system of higher education, its schools of business play a vital role in supporting the country’s economic objectives. However, the crucial contribution of soft skills for maximal success within the business sector has to date not been adequately recognized by its business schools. This being so, the development of the business school curriculum in Vietnam has not been able to 'catch up', so to say, with the burgeoning need of students for a comprehensive soft skills program designed to meet the national and global business objectives of their potential employers. The burden of the present paper is first to reveal the results of our survey in Vietnam which make explicit the extent to which major Vietnamese industrial employers’ value the potential role that soft skill competencies can play in maximizing business success. Our final task will be to determine which soft skills employers discern as best serving to maximize the economic interests of Vietnam within the global marketplace. Semi-structured telephone interviews have been conducted with the 15 representative Head Employers of Vietnam's reputedly largest and most successful of the diverse business enterprises across Vietnam. The findings of the study indicate that all respondents highly value the increasing importance of soft skills in business success. Our critical analysis of respondent data reveals that 19 essential soft skills are deemed by employers as integral to business workplace efficacy and should thus be integrated into the formal business curriculum. We are confident that our study represents the first comprehensive and specific survey yet undertaken within the business sector in Vietnam which accesses and analyses the opinions of representative employers from major companies across the country in regard to the growing importance of 19 specific soft skills essential for maximizing overall business success. Our research findings also reveal that the integration into business school curriculums nationwide of the soft skills we have identified is of paramount importance to advance the national and global economic interests of Vietnam.

Performance Comparison of ADTree and Naive Bayes Algorithms for Spam Filtering

Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Co-Pyrolysis of Olive Pomace with Plastic Wastes and Characterization of Pyrolysis Products

Waste polyethylene (PE) is classified as waste low density polyethylene (LDPE) and waste high density polyethylene (HDPE) according to their densities. Pyrolysis of plastic waste may have an important role in dealing with the enormous amounts of plastic waste produced all over the world, by decreasing their negative impact on the environment. This waste may be converted into economically valuable hydrocarbons, which can be used both as fuels and as feed stock in the petrochemical industry. End product yields and properties depend on the plastic waste composition. Pyrolytic biochar is one of the most important products of waste plastics pyrolysis. In this study, HDPE and LDPE plastic wastes were co-pyrolyzed together with waste olive pomace. Pyrolysis runs were performed at temperature 700°C with heating rates of 5°C/min. Higher pyrolysis oil and gas yields were observed by the using waste olive pomace. The biochar yields of HDPE- olive pomace and LDPEolive pomace were 6.37% and 7.26% respectively for 50% olive pomace doses. The calorific value of HDPE-olive pomace and LDPE-olive pomace of pyrolysis oil were 8350 and 8495 kCal.

Developing New Media Credibility Scale: A Multidimensional Perspective

The main purposes of this study are to develop a scale that reflects emerging theoretical understandings of new media credibility, based on the evolution of credibility studies in western researches, identification of the determinants of credibility in the media and its components by comparing traditional and new media credibility scales and building accumulative scale to test new media credibility. This approach was built on western researches using conceptualizations of media credibility, which focuses on four principal components: Source (journalist), message (article), medium (newspaper, radio, TV, web, etc.), and organization (owner of the medium), and adding user and cultural context as key components to assess new media credibility in particular. This study’s value lies in its contribution to the conceptualization and development of new media credibility through the creation of a theoretical measurement tool. Future studies should explore this scale to test new media credibility, which represents a promising new approach in the efforts to define and measure credibility of all media types.

Core Tourism Products and Destination Image: Case Study of Sabah, Malaysia

This paper empirically investigates the relationship between Sabah state core tourism products and its destination image. Through a descriptive design using a quantitative method with a self-reported and self-administered questionnaire, this research surveyed the individual international tourists who had visited Sabah and experienced the state’s core tourism products. The research findings clearly indicate that Sabah, one of the states in Malaysia has a lot of valuable resources in the eyes of the international tourists. Interestingly, it was found that Sabah’s core tourism products namely unique marine resources, various nature attractions and cultural diversities have undoubtedly contributed to the state’s tourism image. Good feedbacks and the promising insights from the international tourists’ point of view offer varying consequences, repercussion, and implication to the state government and the relevant authorities. Collaboration and cooperation between all responsible authorities are therefore crucial in strengthening the “total tourism experience” among the international tourists in this state.

Comparative Study of Tensile Properties of Cast and Hot Forged Alumina Nanoparticle Reinforced Composites

Particle reinforced Metal Matrix Composite (MMC) succeeds in synergizing the metallic matrix with ceramic particle reinforcements to result in improved strength, particularly at elevated temperatures, but adversely it affects the ductility of the matrix because of agglomeration and porosity. The present study investigates the outcome of tensile properties in a cast and hot forged composite reinforced simultaneously with coarse and fine particles. Nano-sized alumina particles have been generated by milling mixture of aluminum and manganese dioxide powders. Milled particles after drying are added to molten metal and the resulting slurry is cast. The microstructure of the composites shows good distribution of both the size categories of particles without significant clustering. The presence of nanoparticles along with coarser particles in a composite improves both strength and ductility considerably. Delay in debonding of coarser particles to higher stress is due to reduced mismatch in extension caused by increased strain hardening in presence of the nanoparticles. However, higher addition of powder mix beyond a limit results in deterioration of mechanical properties, possibly due to clustering of nanoparticles. The porosity in cast composite generally increases with the increasing addition of powder mix as observed during process and on forging it has got reduced. The base alloy and nanocomposites show improvement in flow stress which could be attributed to lowering of porosity and grain refinement as a consequence of forging.

A Flute Tracking System for Monitoring the Wear of Cutting Tools in Milling Operations

Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Pefloxacin as a Surrogate Marker for Ciprofloxacin Resistance in Salmonella: Study from North India

Fluoroquinolones form the mainstay of therapy for the treatment of infections due to Salmonella enterica subsp. enterica. There is a complex interplay between several resistance mechanisms for quinolones and various fluoroquinolones discs, giving varying results, making detection and interpretation of fluoroquinolone resistance difficult. For detection of fluoroquinolone resistance in Salmonella ssp., we compared the use of pefloxacin and nalidixic acid discs as surrogate marker. Using MIC for ciprofloxacin as the gold standard, 43.5% of strains showed MIC as ≥1 μg/ml and were thus resistant to fluoroquinoloes. Based on the performance of nalidixic acid and pefloxacin discs as surrogate marker for ciprofloxacin resistance, both the discs could correctly detect all the resistant phenotypes; however, use of nalidixic acid disc showed false resistance in the majority of the sensitive phenotypes. We have also tested newer antimicrobial agents like cefixime, imipenem, tigecycline and azithromycin against Salmonella spp. Moreover, there was a comeback of susceptibility to older antimicrobials like ampicillin, chloramphenicol, and cotrimoxazole. We can also use cefixime, imipenem, tigecycline and azithromycin in the treatment of multidrug resistant S. typhi due to their high susceptibility.

Active Islanding Detection Method Using Intelligent Controller

An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Genetic Diversity Based Population Study of Freshwater Mud Eel (Monopterus cuchia) in Bangladesh

As genetic diversity is most important for existing, breeding and production of any fish; this study was undertaken for investigating genetic diversity of freshwater mud eel, Monopterus cuchia at population level where three ecological populations such as flooded area of Sylhet (P1), open water of Moulvibazar (P2) and open water of Sunamganj (P3) districts of Bangladesh were considered. Four arbitrary RAPD primers (OPB-12, C0-4, B-03 and OPB-08) were screened and RAPD banding patterns were analyzed among the populations considering 15 individuals of each population. In total 174, 138 and 149 bands were detected in the populations of P1, P2 and P3 respectively; however, each primer revealed less number of bands in each population. 100% polymorphic loci were recorded in P2 and P3 whereas only one monomorphic locus was observed in P1, recorded 97.5% polymorphism. Different genetic parameters such as inter-individual pairwise similarity, genetic distance, Nei genetic similarity, linkage distances, cluster analysis and allelic information, etc. were considered for measuring genetic diversity. The average inter-individual pairwise similarity was recorded 2.98, 1.47 and 1.35 in P1, P2 and P3 respectively. Considering genetic distance analysis, the highest distance 1 was recorded in P2 and P3 and the lowest genetic distance 0.444 was found in P2. The average Nei genetic similarity was observed 0.19, 0.16 and 0.13 in P1, P2 and P3, respectively; however, the average linkage distance was recorded 24.92, 17.14 and 15.28 in P1, P3 and P2 respectively. Based on linkage distance, genetic clusters were generated in three populations where 6 clades and 7 clusters were found in P1, 3 clades and 5 clusters were observed in P2 and 4 clades and 7 clusters were detected in P3. In addition, allelic information was observed where the frequency of p and q alleles were observed 0.093 and 0.907 in P1, 0.076 and 0.924 in P2, 0.074 and 0.926 in P3 respectively. The average gene diversity was observed highest in P2 (0.132) followed by P3 (0.131) and P1 (0.121) respectively.

Switching Studies on Ge15In5Te56Ag24 Thin Films

Germanium Telluride based quaternary thin film switching devices with composition Ge15In5Te56Ag24, have been deposited in sandwich geometry on glass substrate with aluminum as top and bottom electrodes. The bulk glassy form of the said composition is prepared by melt quenching technique. In this technique, appropriate quantity of elements with high purity are taken in a quartz ampoule and sealed under a vacuum of 10-5 mbar. Then, it is allowed to rotate in a horizontal rotary furnace for 36 hours to ensure homogeneity of the melt. After that, the ampoule is quenched into a mixture of ice - water and NaOH to get the bulk ingot of the sample. The sample is then coated on a glass substrate using flash evaporation technique at a vacuum level of 10-6 mbar. The XRD report reveals the amorphous nature of the thin film sample and Energy - Dispersive X-ray Analysis (EDAX) confirms that the film retains the same chemical composition as that of the base sample. Electrical switching behavior of the device is studied with the help of Keithley (2410c) source-measure unit interfaced with Lab VIEW 7 (National Instruments). Switching studies, mainly SET (changing the state of the material from amorphous to crystalline) operation is conducted on the thin film form of the sample. This device is found to manifest memory switching as the device remains 'ON' even after the removal of the electric field. Also it is found that amorphous Ge15In5Te56Ag24 thin film unveils clean memory type of electrical switching behavior which can be justified by the absence of fluctuation in the I-V characteristics. The I-V characteristic also reveals that the switching is faster in this sample as no data points could be seen in the negative resistance region during the transition to on state and this leads to the conclusion of fast phase change during SET process. Scanning Electron Microscopy (SEM) studies are performed on the chosen sample to study the structural changes at the time of switching. SEM studies on the switched Ge15In5Te56Ag24 sample has shown some morphological changes at the place of switching wherein it can be explained that a conducting crystalline channel is formed in the device when the device switches from high resistance to low resistance state. From these studies it can be concluded that the material may find its application in fast switching Non-Volatile Phase Change Memory (PCM) Devices.