A multilevel association model for IT employees' life stress and job satisfaction: An Information Technology (IT) industry case study

The aim of this research was to investigate the association among IT employees’ life stress and job satisfaction in information technology (IT) firms. Data on 250 IT employees’ in 30 working groups was obtained from 10 Information Technology (IT) Chinese firms from Beijing, and analyzed using hierarchical linear modeling (HLM). Results found momentous association among life stress of IT employees’ and their job satisfaction at an individual-level and group-level in IT firms. Furthermore, life stress in Beijing at group-level moderates the association among job satisfaction and IT employees’ life stress at an individual-level. Finally, limitations and implications of the present study are also discussed

Improving Network Troubleshooting using Virtualization

Diagnosing problems, deploying new services, testing protocol interactions, or validating network configurations are hard problems in today’s Internet. This paper proposes to leverage the concept of Network Virtualization to overcome such problems: (1) Monitoring VNets can be created on demand along side any production network to enable network-wide monitoring in a robust and cost-efficient manner; (2) Shadow VNets enable troubleshooting as well as safe upgrades to both the software components and their configurations. Both approaches build on the agility and isolation properties of the underlying virtualized infrastructure. Neither requires changes to the physical or logical structure of the production network. Thus, they have the potential to substantially ease network operation and improve resilience against mistakes

How happy are your flows: an empirical study of packet losses in router buffers

Studies of Internet traffic have revealed that traffic is consistent with self-similar scaling, shows long-range dependence, and that flow sizes are consistent with heavytailed distributions. However, how such characteristics affect fundamental network properties such as buffer overflows and therefore the loss process and link utilization has not been explored in detail. Relying on advanced instrumentation via NetFPGA cards, we perform a sensitivity study of the packet loss process within routers for different network load levels, flow size distributions, and buffer sizes. We find that packet losses do not affect all flows similarly. Depending on the network load and the buffer sizes, some flows either suffer from significantly more drops or significantly less drops than the average loss rate. Very few flows actually observe a loss rate similar to the average loss rate. Therefore, any single flow is very unlikely to observe the global packet loss process. Furthermore, the loss process can exhibit scaling properties

Study of Multi-Classification of Advanced Daily Life Activities on SHIMMER Sensor Dataset

Today the field of wireless sensors have the dominance in almost every person’s daily life. Therefore researchers are exasperating to make these sensors more dynamic, accurate and high performance computational devices as well as small in size, and also in the application area of these small sensors. The wearable sensors are the one type which are used to acquire a person’s behavioral characteristics. The applications of wearable sensors are healthcare, entertainment, fitness, security and military etc. Human activity recognition (HAR) is the one example, where data received from wearable sensors are further processed to identify the activities executed by the individuals. The HAR system can be used in fall detection, fall prevention and also in posture recognition. The recognition of activities is further divided into two categories, the un-supervised learning and the supervised learning. In this paper we first discussed some existing wearable sensors based HAR systems, then briefly described some classifiers (supervised learning) and then the methodology of how we applied the multiple classification techniques using a benchmark data set of the shimmer sensors placed on human body, to recognize the human activity. Our results shows that the methods are exceptionally accurate and efficient in comparison with other classification methods. We also compare the results and analyzed the accuracy of different classifiers

Patient's Feedback Platform for Quality of Services via “Free Text Analysis” in Healthcare Industry

Data analysis of social media posting continues to offer a huge variety of information about the health situation faced by an individual. Social networking or social media websites provide us a wealth of information generated by users in a variety of domains, that generated information are unstructured and unlabeled and are not captured in an exceedingly systematic manner, as info generated is not humanly possible to process due to its size. One traditional way of collecting patients experience is by conducting surveys and questionnaires, as these methods ask fixed questions and are expensive to administer. In this paper, a patient feedback platform (PFP) using free text sentiment analysis is developed to computationally identify and categorize the polarity expressed in a piece of text. Six machine learning latest algorithms have been used as key evaluation for evaluating accuracy of the developed (PFP) model. Results achieved have shown 88 % accuracy on the basis of which it is recommended that developed (PFP) patient feedback platform could be used to improve E-health care services indeed

Intracranial Low Grade Glioma: a Clinical Study of 35 Cases in a Teaching Institute

Objective: To determine the clinical manifestation and surgical outcome of patients with low grade Glioma.Material and Methods: This descriptive (cross sectional) study was done at the Neurosurgery Department, Mardan Medical Complex Mardan. The study period was March 2017 to February 2018. Patient of any age and gender presented to outpatient department or referred from some other medical facility and diagnosed as low grade Glioma on clinical and radiological grounds and later confirmed by histopathology were included. Results: Out of 35 patients, 20 (57%) were male and 15 (42%) were female. 20 to 80 years was the age range and mean age was 46.36 ± 17.11 years. Frontal lobe was the most frequent area of location, followed by parietal 9 (25%) and temporal 8 (22%) lobe. Pre-operativeKarnofsky score was 90 in 16 (45%), 80 in 8 (22%), 70 in 6 (17%) and 60 in 5 (14%) of patients. Gross total resection was achieved in 13 (37%), radical subtotal resection in 10 (28%), subtotal resection in 10 (28%) and biopsy taken in 02 (5%) patients. histopathology revealed Astrocytoma in 15 (42%), mixed Oligoastrocytoma in 12 (34%) and Oligodendroglioma in 8 (22%) number of patients. Post operatively surgical outcome was measured by improvement in symptomatology, Karnofsky score and seizure control. Conclusion: Conscious level, Karnofsky Performance score, seizure control are important parameters for surgical outcome in patients with low grade Gliomas. Gross total resection of the tumor is a better option for good surgical outcome

FPGA IMPLEMENTATION OF ADVANCE ENCRYPTION STANDARD WITH SINGLE KEY

Advanced Encryption Standard (AES), is known as most secured encryption standard now a days. Many researchers have implemented it in different languages like java, C and C++ with different algorithms. Recently the AES 128-bit has been implemented using Verilog on FPGA with equipped key being encrypted along with data input in whole process. In this paper the AES 128-bit encryption and decryption process with key which is only used for data input and is not encrypted throughout the encryption/decryption process. Results are same but our algorithm is slightly faster because only data is encrypted in the process of encryption, thus process time and area is optimized

DESIGN AND IMPLEMENTATION OF BI-AXIAL SOLAR TRACKER USING ARDUINO

Solar energy is a renewable free source of energy that is inexhaustible and sustainable, unlike fossil fuels that are finite. Research is being performed for the development of more efficient systems by absorbing maximum sun light and converting it into electrical power.The purpose of this work is to make more efficient solar panels for photovoltaic perpendicular rays of the sun throughout the year.This includes the design and implementation of research-based Arduino dual axis solar tracking system. The development of experimental setup is comprised of two parts: hardware and software. During hardware development phase, four light dependent resisters have been installed in “+ shaped “mounting on the top of solar panel. Two DC geared motors have been fixed to rotate the solar panel in mutually perpendicular axis to each other so that the plane of each solar panel remains normal to the incident rays of the sun all the time in a day. Firstly, a code in C language is developed and fed to the microcontroller “Arduino UNO”. The graphical user interface (GUI) is developed in “Lab VIEW” and connected with microcontroller to examinethe real time displacement of solar panel in both axes by the feedback information of LDR sensors. This allows two-axis tracking of solar energy and the solar panel is capable of producing electrical energy with sunlight throughout the whole day.Therefore, average power produced by biaxial solar tracker in a day is 20.98% more than that by simple static system

Enhanced electrocatalytic performance of cobalt oxide nanocubes incorporating reduced graphene oxide as a modified platinum electrode for methanol oxidation

Herein, we report a facile hydrothermal method for the preparation of cobalt oxide nanocubes incorporating reduced graphene oxide (rGO–Co3O4 nanocubes) for electrocatalytic oxidation of methanol. The synthesized rGO–Co3O4 nanocubes were characterized using transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), and Raman techniques. The electrochemical behavior of an rGO–Co3O4 nanocube modified electrode was studied using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques. The electrocatalytic performances of rGO–Co3O4 nanocube-modified electrodes with different wt% of GO were investigated in relation to methanol oxidation in an alkaline medium. The rGO–Co3O4 nanocube modified electrode showed enhanced current density due to oxidation of methanol when compared to the bare Pt, rGO, and Co3O4 nanocube modified electrodes. The optimal GO content for an rGO–Co3O4 nanocube-modified electrode to achieve a high electrocatalytic oxidation of methanol was 2 wt%, and it showed an anodic peak current density of 362 μA cm−2