Hand Gesture Vocalizer for Dumb and Deaf People

The main purpose of this paper is to confer the system that converts a given sign used by disabled person into its appropriate textual, audio, and pictorial form using components such as Arduino Mega, Flex sensors, Accelerometer, which could be under standby a common person. A wearable glove controller is design with fl ex sensors attached on each finger, which allows the system to sense the finger movements, and aGy-61 accelerometer, which are uses to sense the hand movement of the disabled person. The wearable input glove controller sends the collected input signal to the system for processing. The system uses Random forest algorithm to predict the correct output to an accuracy of 85% on current training model.

Optimal Allocation of Capacitor Bank for Loss Minimization and Voltage Improvement Using Analytical Method

An electric distribution system plays an important role in achieving satisfactory power supply. The quality of power is measured by voltage stability and profile of voltage. The voltage profile is affected by the losses in distribution system. As the load is mostly inductive on the distribution system and requires large reactive power, most of the power quality problems can be resolved with requisite control of reactive power. Capacitors are often installed in distribution system for reactive power compensation. This paper presents two stage procedures to identify the location and size of capacitor bank. In the first stage, the load flow is carried out to find the losses of the system using sweep algorithm. In the next stage, different size of capacitors are initialized and placed in each possible candidate bus and again load flow for the system is carried out. The objective function of the cost incorporating capacitor cost and loss cost is formulated constrained with voltage limits. The capacitor with the minimum cost is selected as the optimized solution. The proposed procedure is applied to different standard test systems as 12-bus radial distribution systems. In addition, the proposed procedure is applied on a real distribution system, a section of Sallaghari Feeder of Thimi substation. The voltage drops and power loss before and after installing the capacitor were compared for the system under test in this work. The result showed better voltage profiles and power losses of the distribution system can be improved by using the proposed method and it can be a benefit to the distribution networks.

Analysis of Consumer Data on Black Friday Sales Using Apriori Algorithm

Ability to recognize and track patterns in data help businesses shift through the layers of seemingly unrelated data for meaningful relationships. Through this analysis it becomes easy for the online retailers to determine the dimensions that influence the uptake of online shopping and plan effective marketing strategies. This paper builds a roadmap for analyzing consumer’s online buying behavior with the help of Apriori algorithm. The major factors that affect the consumer’s online buying behavior are convenience, ease of use and perceived benefits. Security is also a major consideration when opting to conduct shopping activities online. This study will helping further analyzing the consumer online buying behavior towards Online shopping which will help the retailers to design appropriate marketing strategies for selling their products online which will further help in development of the country.

Implementing Neural Network and Multi resolution analysis in EEG signal for early detection of epilepsy

Epilepsy is a neurological disorder of brain and the electroencephalogram (EEG) signals are commonly used to detect the epileptic seizures, the result of abnormal electrical activity in the brain. This paper focuses on the analysis of EEG signal to detect the presence of the epileptic seizure prior to its occurrence. The result could aid the individual in the initiation of delay sensitive diagnostic, therapeutic and alerting procedures. The methodology involves the multi resolution analysis (MRA) of the EEG signals of epileptic patient. MRA is carried out using discrete wavelet transform with daubechies 8 as the mother wavelet. For EEG data, the database of MIT-BIH of seven patients with different cases of epileptic seizure was used. The result with one of the patients showed presence of a unique pattern during the spectral analysis of the signal over different bands. Hence, based on the first patient, similar region is selected with the other patients and the multi-resolution analysis along with the principal component analysis (PCA) for the dimension reduction is carried out. Finally, these are treated with neural network to perform the classification of the signal either the epilepsy is occurring or not. The final results showed 100% accuracy with the detection with the neural network however it uses a large amount of data for analysis. Thus, the same was tested with dimension reduction using PCA which reduced the average accuracy to 89.51%. All the results have been simulated within the Matlab environment.

Enabling and Limiting factors in eXtreme Programming (XP) with Evaluation Framework

As agile software development methodologies are used in many domains and come with different shapes and sizes, it is one of the complex human endeavors. Extreme Programming (XP) is one of the well-known agile software development methodologies and is driven by a set of values including simplicity, communication, feedback and courage, but lacks the mechanism to measure these values demanding the evaluation framework to make it measurable and attainable. The main aim of this study is to build the software process improvement model that can be used for evaluating XP values and practices. The proposed XP evaluation framework in this study is XP focused and evaluates the XP project, product and practices. The XP evaluation framework is a collection of some new and validated metrics used for evaluating XP projects, XP practices, XP products and some additional factors concerned with XP. The evaluation framework for extreme programming is basically based on the assessment and evaluation of various project characteristics, extreme programming characteristics, product characteristics and other additional characteristics. The metrics used for assessments and evaluations of XP are designed to be simple, precise, understandable, economical, timely, consistent, accountable, unambiguous, suitable and reliable.

Spreadsheet Implementation for Optimization of Power flow Network Problem: A Case Study of Kathmandu Valley

This paper is about the optimization of power loss in the power transmission network of the Kathmandu valley using spreadsheet modeling as an optimal power flow software. It is helpful for identifying the best path for the optimum power flow in dry as well as wet season. The available generating stations and substations taken as supply and demand nodes near Kathmandu valley are considered and the network is optimized as a transshipment flow problem. The main goal in this network flow model is to determine how much power should be allowed to flow across each transmission lines with minimal losses. In addition, optimization is performed considering the power import from India as well. Considering active power flow with a different scenario, and depending upon the load demand, the power system network is modeled in order to find out the best possible routes for efficient power flow with minimum loss.

An Insight on Social Media Stream Mining

Data stream mining is one of the realms gaining upper hand over traditional data mining methods. Transfinite volumes of data termed as Data Streams are often generated by Internet traffic, Communication networks, On-line bank or ATM transactions etc. The streams are dynamic and ever-shifting and need to be analysed online as they are obtained. Social media is one of the notable sources of such data streams. While social media streaming has received a lot of attention over the past decade, the ever-expanding streams of data presents huge challenges for learning and maintaining control. Dealing with billions of user’s data measured in pet bytes is a demanding task in itself. It is indeed a challenge to mine such dynamic data from social networks in an uninterrupted and competent way. This paper is purposed to introduce social data streams and the mining techniques involved in processing them. We analyse the most recent trends in social media data stream mining to translate to the detailed study of the matter. We also review innovative implementations of social media stream mining that are currently prevalent.

Socioeconomic Impacts of FMIS after Rehabilitation: Case Study of Bakultar Irrigation Project, Mahadevsthan, Dhading

The main purpose of the study is to focus on the socioeconomic impacts of rehabilitation of Bakultar Irrigation Project in the Mahadevsthan, Dhading district, Nepal. Primary information was collected through household survey, Key Informant Interview, and FGD. Both qualitative and quantitative techniques were used for data analysis. The rehabilitation intervention of the irrigation project has changed the cropping pattern and increased the crop productivity. The cropping intensity has increased to 244.6 % from174 %. The study shows that rehabilitation of irrigation project has positive impact over poverty reduction, food sufficiency, gender equity, migration control and reduction of women’s drudgery in household works.

Nepali Text to Speech Synthesis System using FreeTTS

This paper confers the tools and methodology used in developing a Nepali Text to Speech Synthesis System using FreeTTS and is entirely developed in Java and uses FreeTTS synthesize1: Vocalized form of human communication is Speech. Here the Nepali Language is Synthetized based on formant approach and the use of one of the popular generic frameworks FreeTTS that is available in public domain for the development of a TTS system. The Text To Speech Architecture has been developed putting more emphasis on the Natural Language Processing (NLP) component rather than Digital Signal Processing (DSP) component. Nepali language being mostly used language in Nepal and some parts of India and abroad, a text-to-speech (TTS} synthesizer for this language will prove to be a convenient tool and communication technology (JCT) based system to aid to those majorities of people who are illiterate and also to those who are physical impairments like visually handicapped and vocally disabled persons. This ability to convert text to voice may reduce the dependency, frustration, and sense of helplessness of these people. The system can be extended to include more features such as emotions, improved tokenization, interactive options and the use of minimal database.

Factors Affecting Project Based Learning Intention of Engineering Students

The factors affecting the project-based learning intention (PjBLI) of engineering students have been studied using theory of planned behaviour (TPB). Descriptive study was carried out utilizing quantitative technique. Primary data were collected through cross sectional survey, utilizing seven point Likert scaled questionnaire. The respondents were final year students of Nepal Engineering College. Statistical tool (SPSS) was used for analysis. The result shows that the levels of both the PjBLI and the attitude of students (ATTI) towards project-based learning (PjBL) are high followed by the level of perceived behavioural control (BC). However, the level of subjective norm (SN) is relatively lower. There are no significant differences in PjBLI, ATTI, SN and BC among students from different departments. However the BC (perception of self efficacy or capability) of female students is higher than that of male students. Regression analysis shows that 42.2 and 19.3 percentages of PjBLI are affected by SN and ATTI respectively. The study concludes that additional effort is essential to improve SN (support from project supervisor; department and colleague) which in turn helps to improve PjBLI of students and their performance.