Modified Scaling-Free CORDIC Based Pipelined Parallel MDC FFT and IFFT Architecture for Radix 2^2 Algorithm

An innovative approach to develop modified scaling free CORDIC based two parallel pipelined Multipath Delay Commutator (MDC) FFT and IFFT architectures for radix 22 FFT algorithm is presented. Multipliers and adders are the most important data paths in FFT and IFFT architectures. Multipliers occupy high area and consume more power. In order to optimize the area and power overhead, modified scaling-free CORDIC based complex multiplier is utilized in the proposed design. In general twiddle factor values are stored in RAM block. In the proposed work, modified scaling-free CORDIC based twiddle factor generator unit is used to generate the twiddle factor and efficient switching units are used. In addition to this, four point FFT operations are performed without complex multiplication which helps to reduce area and power in the last two stages of the pipelined architectures. The design proposed in this paper is based on multipath delay commutator method. The proposed design can be extended to any radix 2n based FFT/IFFT algorithm to improve the throughput. The work is synthesized using Synopsys design Compiler using TSMC 90-nm library. The proposed method proves to be better compared to the reference design in terms of area, throughput and power consumption. The comparative analysis of the proposed design with Xilinx FPGA platform is also discussed in the paper.

Study of Pre-Handwriting Factors Necessary for Successful Handwriting in Children

Handwriting is essential to academic success; however, the current literature is limited in the identification of pre-handwriting skills. The purpose of this study was to identify the pre-handwriting skills, which occupational therapy practitioners deem important to handwriting success, as well as those which aid in intervention planning. The online survey instrument consisted of 33 questions that assessed various skills related to the development of handwriting, as well as captured demographic information. Both occupational therapists and occupational therapy assistants were included in the survey study. The survey found that the respondents were in agreement that purposeful scribbling, the ability of a child to copy (vertical/horizontal lines, circle, squares, and triangles), imitating an oblique cross, cognitive skills (attention, praxis, self-regulation, sequencing), grasp patterns, hand dominance, in hand manipulation skills (shift, translation, rotation), bilateral integration, stabilization of paper, crossing midline, and visual perception were important indicators of handwriting readiness. The results of the survey support existing research regarding the skills necessary for the successful development of handwriting in children.

Optimizing Resource Allocation and Indoor Location Using Bluetooth Low Energy

The recent tendency of ”Internet of Things” (IoT) has developed in the last years, causing the emergence of innovative communication methods among multiple devices. The appearance of Bluetooth Low Energy (BLE) has allowed a push to IoT in relation to smartphones. In this moment, a set of new applications related to several topics like entertainment and advertisement has begun to be developed but not much has been done till now to take advantage of the potential that these technologies can offer on many business areas and in everyday tasks. In the present work, the application of BLE technology and smartphones is proposed on some business areas related to the optimization of resource allocation in huge facilities like airports. An indoor location system has been developed through triangulation methods with the use of BLE beacons. The described system can be used to locate all employees inside the building in such a way that any task can be automatically assigned to a group of employees. It should be noted that this system cannot only be used to link needs with employees according to distances, but it also takes into account other factors like occupation level or category. In addition, it has been endowed with a security system to manage business and personnel sensitive data. The efficiency of communications is another essential characteristic that has been taken into account in this work.

Quality of Bali Beef and Broiler after Immersion in Liquid Smoke on Different Concentrations and Storage Times

The aim of this study was to improve the durability and quality of Bali beef (M. Longissimus dorsi) and broiler carcass through the addition of liquid smoke as a natural preservative. This study was using Longissimus dorsi muscle from male Bali beef aged 3 years, broiler breast and thigh aged 40 days. Three types of meat were marinated in liquid smoke with concentrations of 0, 5, and 10% for 30 minutes at the level of 20% of the sample weight (w/w). The samples were storage at 2-5°C for 1 month. This study designed as a factorial experiment 3 x 3 x 4 based on a completely randomized design with 5 replications; the first factor was meat type (beef, chicken breast and chicken thigh); the 2nd factor was liquid smoke concentrations (0, 5, and 10%), and the 3rd factor was storage duration (1, 2, 3, and 4 weeks). Parameters measured were TBA value, total bacterial colonies, water holding capacity (WHC), shear force value both before and after cooking (80°C – 15min.), and cooking loss. The results showed that the type of meat produced WHC, shear force value, cooking loss and TBA differed between the three types of meat. Higher concentration of liquid smoke, the WHC, shear force value, TBA, and total bacterial colonies were decreased; at a concentration of 10% of liquid smoke, the total bacterial colonies decreased by 57.3% from untreated with liquid smoke. Longer storage, the total bacterial colonies and WHC were increased, while the shear force value and cooking loss were decreased. It can be concluded that a 10% concentration of liquid smoke was able to maintain fat oxidation and bacterial growth in Bali beef and chicken breast and thigh.

Analysis of Diverse Cluster Ensemble Techniques

Data mining is the procedure of determining interesting patterns from the huge amount of data. With the intention of accessing the data faster the most supporting processes needed is clustering. Clustering is the process of identifying similarity between data according to the individuality present in the data and grouping associated data objects into clusters. Cluster ensemble is the technique to combine various runs of different clustering algorithms to obtain a general partition of the original dataset, aiming for consolidation of outcomes from a collection of individual clustering outcomes. The performances of clustering ensembles are mainly affecting by two principal factors such as diversity and quality. This paper presents the overview about the different cluster ensemble algorithm along with their methods used in cluster ensemble to improve the diversity and quality in the several cluster ensemble related papers and shows the comparative analysis of different cluster ensemble also summarize various cluster ensemble methods. Henceforth this clear analysis will be very useful for the world of clustering experts and also helps in deciding the most appropriate one to determine the problem in hand.

Upgraded Rough Clustering and Outlier Detection Method on Yeast Dataset by Entropy Rough K-Means Method

Rough set theory is used to handle uncertainty and incomplete information by applying two accurate sets, Lower approximation and Upper approximation. In this paper, the rough clustering algorithms are improved by adopting the Similarity, Dissimilarity–Similarity and Entropy based initial centroids selection method on three different clustering algorithms namely Entropy based Rough K-Means (ERKM), Similarity based Rough K-Means (SRKM) and Dissimilarity-Similarity based Rough K-Means (DSRKM) were developed and executed by yeast dataset. The rough clustering algorithms are validated by cluster validity indexes namely Rand and Adjusted Rand indexes. An experimental result shows that the ERKM clustering algorithm perform effectively and delivers better results than other clustering methods. Outlier detection is an important task in data mining and very much different from the rest of the objects in the clusters. Entropy based Rough Outlier Factor (EROF) method is seemly to detect outlier effectively for yeast dataset. In rough K-Means method, by tuning the epsilon (ᶓ) value from 0.8 to 1.08 can detect outliers on boundary region and the RKM algorithm delivers better results, when choosing the value of epsilon (ᶓ) in the specified range. An experimental result shows that the EROF method on clustering algorithm performed very well and suitable for detecting outlier effectively for all datasets. Further, experimental readings show that the ERKM clustering method outperformed the other methods.

Zinc Sorption by Six Agricultural Soils Amended with Municipal Biosolids

Anthropogenic sources of zinc (Zn), including industrial emissions and effluents, Zn–rich fertilizer materials and pesticides containing Zn, can contribute to increasing the concentration of soluble Zn at levels toxic to plants in acid sandy soils. The application of municipal sewage sludge or biosolids (MBS) which contain metal immobilizing agents on coarse-textured soils could improve the metal sorption capacity of the low-CEC soils. The purpose of this experiment was to evaluate the sorption of Zn in surface samples (0-15 cm) of six Quebec (Canada) soils amended with MBS (pH 6.9) from Val d’Or (Quebec, Canada). Soil samples amended with increasing amounts (0 to 20%) of MBS were equilibrated with various amounts of Zn as ZnCl2 in 0.01 M CaCl2 for 48 hours at room temperature. Sorbed Zn was calculated from the difference between the initial and final Zn concentration in solution. Zn sorption data conformed to the linear form of Freundlich equation. The amount of sorbed Zn increased considerably with increasing MBS rate. Analysis of variance revealed a highly significant effect (p ≤ 0.001) of soil texture and MBS rate on the amount of sorbed Zn. The average values of the Zn-sorption capacity of MBS-amended coarse-textured soils were lower than those of MBS-amended fine textured soils. The two sandy soils (86-99% sand) amended with MBS retained 2- to 5-fold Zn than those without MBS (control). Significant Pearson correlation coefficients between the Zn sorption isotherm parameter, i.e. the Freundlich sorption isotherm (KF), and commonly measured physical and chemical entities were obtained. Among all the soil properties measured, soil pH gave the best significant correlation coefficients (p ≤ 0.001) for soils receiving 0, 5 and 10% MBS. Furthermore, KF values were positively correlated with soil clay content, exchangeable basic cations (Ca, Mg or K), CEC and clay content to CEC ratio. From these results, it can be concluded that (i) municipal biosolids provide sorption sites that have a strong affinity for Zn, (ii) both soil texture, especially clay content, and soil pH are the main factors controlling anthropogenic Zn sorption in the municipal biosolids-amended soils, and (iii) the effect of municipal biosolids on Zn sorption will be more pronounced for a sandy soil than for a clay soil.

Knowledge Management and Tourism: An Exploratory Study Applied to Travel Agents in Egypt

Knowledge management focuses on the development, storage, retrieval, and dissemination of information and expertise. It has become an important tool to improve performance in tourism enterprises. This includes improving decision-making, developing customer services, and increasing sales and profits. Knowledge management adoption depends on human, organizational and technological factors. This study aims to explore the concept of knowledge management in travel agents in Egypt. It explores the requirements of adoption and its impact on performance in these agencies. The study targets Category A travel agents in Egypt. The population of the study encompasses Category A travel agents having online presence. An online questionnaire is used to collect data from managers of travel agents. This study is useful for travel agents who are in urgent need to restructure their intermediary role and support their survival in the global travel market. The study sheds light on the requirements of adoption and the expected impact on performance. This could help travel agents identify their situation and the determine the extent to which they are ready to adopt knowledge management. This study is contributing to knowledge by providing insights from the tourism sector in a developing country where the concept of knowledge management is still in its infancy stages.

Improving Human Hand Localization in Indoor Environment by Using Frequency Domain Analysis

A human’s hand localization is revised by using radar cross section (RCS) measurements with a minimum root mean square (RMS) error matching algorithm on a touchless keypad mock-up model. RCS and frequency transfer function measurements are carried out in an indoor environment on the frequency ranged from 3.0 to 11.0 GHz to cover federal communications commission (FCC) standards. The touchless keypad model is tested in two different distances between the hand and the keypad. The initial distance of 19.50 cm is identical to the heights of transmitting (Tx) and receiving (Rx) antennas, while the second distance is 29.50 cm from the keypad. Moreover, the effects of Rx angles relative to the hand of human factor are considered. The RCS input parameters are compared with power loss parameters at each frequency. From the results, the performance of the RCS input parameters with the second distance, 29.50 cm at 3 GHz is better than the others.

Analytical Slope Stability Analysis Based on the Statistical Characterization of Soil Shear Strength

Increasing our ability to solve complex engineering problems is directly related to the processing capacity of computers. By means of such equipments, one is able to fast and accurately run numerical algorithms. Besides the increasing interest in numerical simulations, probabilistic approaches are also of great importance. This way, statistical tools have shown their relevance to the modelling of practical engineering problems. In general, statistical approaches to such problems consider that the random variables involved follow a normal distribution. This assumption tends to provide incorrect results when skew data is present since normal distributions are symmetric about their means. Thus, in order to visualize and quantify this aspect, 9 statistical distributions (symmetric and skew) have been considered to model a hypothetical slope stability problem. The data modeled is the friction angle of a superficial soil in Brasilia, Brazil. Despite the apparent universality, the normal distribution did not qualify as the best fit. In the present effort, data obtained in consolidated-drained triaxial tests and saturated direct shear tests have been modeled and used to analytically derive the probability density function (PDF) of the safety factor of a hypothetical slope based on Mohr-Coulomb rupture criterion. Therefore, based on this analysis, it is possible to explicitly derive the failure probability considering the friction angle as a random variable. Furthermore, it is possible to compare the stability analysis when the friction angle is modelled as a Dagum distribution (distribution that presented the best fit to the histogram) and as a Normal distribution. This comparison leads to relevant differences when analyzed in light of the risk management.

Public Squares and Their Potential for Social Interactions: A Case Study of Historical Public Squares in Tehran

Under the thrust of technological changes, population growth and vehicular traffic, Iranian historical squares have lost their significance and they are no longer the main social nodes of the society. This research focuses on how historical public squares can inspire designers to enhance social interactions among citizens in Iranian urban context. Moreover, the recent master plan of Tehran demonstrates the lack of public spaces designed for the purpose of people’s social gatherings. For filling this gap, first the current situation of 7 selected primary historical public squares in Tehran including Sabze Meydan, Arg, Topkhaneh, Baherstan, Mokhber-al-dole, Rah Ahan and Hassan Abad have been compared. Later, the influencing elements on social interactions of the public squares such as subjective factors (human relationships and memories) and objective factors (natural and built environment) have been investigated. As a conclusion, some strategies are proposed for improving social interactions in historical public squares like; holding cultural, national, athletic and religious events, defining different and new functions in public squares’ surrounding, increasing pedestrian routs, reviving the collective memory, demonstrating the historical importance of square, eliminating visual obstacles across the square, organization the natural elements of the square, appropriate pavement for social activities. Finally, it is argued that the combination of all influencing factors which are: human interactions, natural elements and built environment criteria will lead to enhance the historical public squares’ potential for social interaction.

Smart Meters and In-Home Displays to Encourage Water Conservation through Behavioural Change

Urbanization, population growth, climate change and the current increase in water demand have made the adoption of innovative demand management strategies crucial to the water industry. Water conservation in urban areas has to be improved by encouraging consumers to adopt more sustainable habits and behaviours. This includes informing and educating them about their households’ water consumption and advising them about ways to achieve significant savings on a daily basis. This paper presents a study conducted in the context of the European FP7 WISDOM Project. By integrating innovative Information and Communication Technologies (ICT) frameworks, this project aims at achieving a change in water savings. More specifically, behavioural change will be attempted by implementing smart meters and in-home displays in a trial group of selected households within Cardiff (UK). Using this device, consumers will be able to receive feedback and information about their consumption but will also have the opportunity to compare their consumption to the consumption of other consumers and similar households. Following an initial survey, it appeared necessary to implement these in-home displays in a way that matches consumer's motivations to save water. The results demonstrated the importance of various factors influencing people’s daily water consumption. Both the relevant literature on the subject and the results of our survey therefore led us to include within the in-home device a variety of elements. It first appeared crucial to make consumers aware of the economic aspect of water conservation and especially of the significant financial savings that can be achieved by reducing their household’s water consumption on the long term. Likewise, reminding participants of the impact of their consumption on the environment by making them more aware of water scarcity issues around the world will help increasing their motivation to save water. Additionally, peer pressure and social comparisons with neighbours and other consumers, accentuated by the use of online social networks such as Facebook or Twitter, will likely encourage consumers to reduce their consumption. Participants will also be able to compare their current consumption to their past consumption and to observe the consequences of their efforts to save water through diverse graphs and charts. Finally, including a virtual water game within the display will help the whole household, children and adults, to achieve significant reductions by providing them with simple tips and advice to save water on a daily basis. Moreover, by setting daily and weekly goals for them to reach, the game will expectantly generate cooperation between family members. Members of each household will indeed be encouraged to work together to reduce their water consumption within different rooms of the house, such as the bathroom, the kitchen, or the toilets. Overall, this study will allow us to understand the elements that attract consumers the most and the features that are most commonly used by the participants. In this way, we intend to determine the main factors influencing water consumption in order to identify the measures that will most encourage water conservation in both the long and short term.

Landfill Design for Reclamation of Şırnak Coal Mine Dumps: Shalefill Stability and Risk Assessment

By GEO5 FEM program with four rockfill slope modeling and stability analysis was performed for S1, S2, S3 and S4 slopes where landslides of the shalefills were limited. Effective angle of internal friction (φ'°) 17°-22.5°, the effective cohesion (c') from 0.5 to 1.8 kPa, saturated unit weight 1.78-2.43 g/cm3, natural unit weight 1.9-2.35 g/cm3, dry unit weight 1.97-2.40 g/cm3, the permeability coefficient of 1x10-4 - 6.5x10-4 cm/s. In cross-sections of the slope, GEO 5 FEM program possible critical surface tension was examined. Rockfill dump design was made to prevent sliding slopes. Bulk material designated geotechnical properties using also GEO5 programs FEM and stability program via a safety factor determined and calculated according to the values S3 and S4 No. slopes are stable S1 and S2 No. slopes were close to stable state that has been found to be risk. GEO5 programs with limestone rock fill dump through FEM program was found to exhibit stability.

Factors Affecting M-Government Deployment and Adoption

Governments constantly seek to offer faster, more secure, efficient and effective services for their citizens. Recent changes and developments to communication services and technologies, mainly due the Internet, have led to immense improvements in the way governments of advanced countries carry out their interior operations Therefore, advances in e-government services have been broadly adopted and used in various developed countries, as well as being adapted to developing countries. The implementation of advances depends on the utilization of the most innovative structures of data techniques, mainly in web dependent applications, to enhance the main functions of governments. These functions, in turn, have spread to mobile and wireless techniques, generating a new advanced direction called m-government. This paper discusses a selection of available m-government applications and several business modules and frameworks in various fields. Practically, the m-government models, techniques and methods have become the improved version of e-government. M-government offers the potential for applications which will work better, providing citizens with services utilizing mobile communication and data models incorporating several government entities. Developing countries can benefit greatly from this innovation due to the fact that a large percentage of their population is young and can adapt to new technology and to the fact that mobile computing devices are more affordable. The use of models of mobile transactions encourages effective participation through the use of mobile portals by businesses, various organizations, and individual citizens. Although the application of m-government has great potential, it does have major limitations. The limitations include: the implementation of wireless networks and relative communications, the encouragement of mobile diffusion, the administration of complicated tasks concerning the protection of security (including the ability to offer privacy for information), and the management of the legal issues concerning mobile applications and the utilization of services.

Effect of L-Dopa on Performance and Carcass Characteristics in Broiler Chickens

Pure form of L-Dopa is used to enhance muscular development, fat breakdown and suppress Parkinson disease in humans. However, the L-Dopa in mucuna seed, when present with other antinutritional factors, causes nutritional disorders in monogastric animals. Information on the utilisation of pure L-Dopa in monogastric animals is scanty. Therefore, effect of L-Dopa on growth performance and carcass characteristics in broiler chickens was investigated. Two hundred and forty one-day-old chicks were allotted to six treatments, which consisted of a positive control (PC) with standard energy (3100Kcal/Kg) and negative control (NC) with high energy (3500Kcal/Kg). The rest 4 diets were NC+0.1, NC+0.2, NC+0.3 and NC+0.4% L-Dopa, respectively. All treatments had 4 replicates in a completely randomized design. Body weight gain, final weight, feed intake, dressed weight and carcass characteristics were determined. Body weight gain and final weight of birds fed PC were 1791.0 and 1830.0g, NC+0.1% L-Dopa were 1827.7 and 1866.7g and NC+0.2% L-Dopa were 1871.9 and 1910.9g respectively, and the feed intake of PC (3231.5g), were better than other treatments. The dressed weight at 1375.0g and 1357.1g of birds fed NC+0.1% and NC+0.2% L-Dopa, respectively, were similar but better than other treatments. Also, the thigh (202.5g and 194.9g) and the breast meat (413.8g and 410.8g) of birds fed NC+0.1% and NC+0.2% L-Dopa, respectively, were similar but better than birds fed other treatments. The drum stick of birds fed NC+0.1% L-Dopa (220.5g) was observed to be better than birds on other diets. Meat to bone ratio and relative organ weights were not affected across treatments. L-Dopa extract, at levels tested, had no detrimental effect on broilers, rather better bird performance and carcass characteristics were observed especially at 0.1% and 0.2% L-Dopa inclusion rates. Therefore, 0.2% inclusion is recommended in diets of broiler chickens for improved performance and carcass characteristics.

Analysis of the Strip Shape and Microstructure with Consideration of Roll Crossing and Shifting

Optimisation of the physical and mechanical properties of cold rolled thin strips is achieved by controlling the rolling parameters. In this paper, the factors affecting the asymmetrical cold rolling of thin low carbon steel strip have been studied at a speed ratio of 1.1 without lubricant applied. The effect of rolling parameters on the resulting microstructure was also investigated. It was found that under dry condition, work roll shifting and work roll cross angle can improve the strip profile, and the result is more significant with an increase of work roll cross angle rather than that of work roll shifting. However, there was no obvious change in microstructure. In addition, effects of rolling parameters on strip profile and microstructure have also been discussed.

HRV Analysis Based Arrhythmic Beat Detection Using kNN Classifier

Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.

A Method for Consensus Building between Teachers and Learners in a Value Co-Creative Learning Service

Improving added value and productivity of services entails improving both value-in-exchange and value-in-use. Value-in-use is realized by value co-creation, where providers and receivers create value together. In higher education services, value-in-use comes from learners achieving learning outcomes (e.g., knowledge and skills) that are consistent with their learning goals. To enhance the learning outcomes of a learner, it is necessary to enhance and utilize the abilities of the teacher along with the abilities of the learner. To do this, however, the learner and the teacher need to build a consensus about their respective roles. Teachers need to provide effective learning content; learners need to choose the appropriate learning strategies by using the learning content through consensus building. This makes consensus building an important factor in value co-creation. However, methods to build a consensus about their respective roles may not be clearly established, making such consensus difficult. In this paper, we propose some strategies for consensus building between a teacher and a learner in value co-creation. We focus on a teacher and learner co-design and propose an analysis method to clarify a collaborative design process to realize value co-creation. We then analyze some counseling data obtained from a university class. This counseling aimed to build a consensus for value-in-use, learning outcomes, and learning strategies between the teacher and the learner.

The Role of Knowledge Management in Innovation: Spanish Evidence

In the knowledge-based economy, innovation is considered essential in order to achieve survival and growth in organizations. On the other hand, knowledge management is currently understood as one of the keys to innovation process. Both factors are generally admitted as generators of competitive advantage in organizations. Specifically, activities on R&D&I and those that generate internal knowledge have a positive influence in innovation results. This paper examines this effect and if it is similar or not is what we aimed to quantify in this paper. We focus on the impact that proportion of knowledge workers, the R&D&I investment, the amounts destined for ICTs and training for innovation have on the variation of tangible and intangibles returns for the sector of high and medium technology in Spain. To do this, we have performed an empirical analysis on the results of questionnaires about innovation in enterprises in Spain, collected by the National Statistics Institute. First, using clusters methodology, the behavior of these enterprises regarding knowledge management is identified. Then, using SEM methodology, we performed, for each cluster, the study about cause-effect relationships among constructs defined through variables, setting its type and quantification. The cluster analysis results in four groups in which cluster number 1 and 3 presents the best performance in innovation with differentiating nuances among them, while clusters 2 and 4 obtained divergent results to a similar innovative effort. However, the results of SEM analysis for each cluster show that, in all cases, knowledge workers are those that affect innovation performance most, regardless of the level of investment, and that there is a strong correlation between knowledge workers and investment in knowledge generation. The main findings reached is that Spanish high and medium technology companies improve their innovation performance investing in internal knowledge generation measures, specially, in terms of R&D activities, and underinvest in external ones. This, and the strong correlation between knowledge workers and the set of activities that promote the knowledge generation, should be taken into account by managers of companies, when making decisions about their investments for innovation, since they are key for improving their opportunities in the global market.

Probabilistic Wavelet Neural Network Based Vibration Analysis of Induction Motor Drive

In this paper proposed the effective fault detection of industrial drives by using Biorthogonal Posterior Vibration Signal-Data Probabilistic Wavelet Neural Network (BPPVS-WNN) system. This system was focused to reducing the current flow and to identify faults with lesser execution time with harmonic values obtained through fifth derivative. Initially, the construction of Biorthogonal vibration signal-data based wavelet transform in BPPVS-WNN system localizes the time and frequency domain. The Biorthogonal wavelet approximates the broken bearing using double scaling and factor, identifies the transient disturbance due to fault on induction motor through approximate coefficients and detailed coefficient. Posterior Probabilistic Neural Network detects the final level of faults using the detailed coefficient till fifth derivative and the results obtained through it at a faster rate at constant frequency signal on the industrial drive. Experiment through the Simulink tool detects the healthy and unhealthy motor on measuring parametric factors such as fault detection rate based on time, current flow rate, and execution time.