Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance evaluation of 4 × 12 Gbps DWDM system using CO-OFDM detection scheme with and without dispersion compensation scheme

Coherent Optical Orthogonal Frequency Division Multiplexing (CO-OFDM) is one of the technologies having ultrahigh capacity in transparent optical networks. CO-OFDM offers the most distant performance in spectral receiver sensitivity, spectral efficiency and polarization or chromatic dispersion tolerance. MIMO-OFDM opens path for doubling the spectral efficiency while providing robustness and polarization dispersion. Simulation of 4 × 12 Gb/s over Single Mode Fiber (SMF) for different distances is done and analysis is done on the basis of Bit Error Rate (BER) and Quality Factor (Q).
Synthesizing Scenario-based Dataset for User Behavior Pattern Mining

— User behavior pattern mining has drawn great attention in business and security areas. Realistic and accurate datasets are required for evaluating various user behavior pattern mining approaches, their implementations and optimization results. Synthetic datasets are crucial due to restricted access to production datasets, security and privacy issues, meeting specific needs of consumers, or the high costs of real datasets. This paper presents a synthetic dataset generator that effectively assists data scientists and analysts in designing scenario-driven datasets with embedded user behavior patterns, and visually analyzing the quality of the generated datasets. We developed an interactive data exploration environment to such a design-generate-visualize-analyze-optimize process. An abstract representation of the real-world user behavior pattern is proposed, which allows data analysts to create datasets with both intended and random patterns injected. Dataset generation is controlled by both data statistics (e.g., data size, and attribute distribution) and scenario-based user behavior patterns (e.g., association pattern, sequential pattern and time constraint). A prototype toolkit has been developed to synthesize and analyze the datasets in different application domains.
Emotion Recognition from Chhattisgarhi Speech using Neural Network

— Speech Emotion Recognition (SER) is emerging as a crucial research area. Many works have been done in field of SER for example speaker dependent / independent SER system, language dependent/independent SER system, extracting different emotions like happiness, anger, sadness, disgust, boredom, neutral. All these works have been achieved by working on speech sample, for which we need speech emotion database. In this work we have developed speech emotion database in Chhattisgarhi language. Speech emotions can be recognized by using different features of speech, which may be prosodic feature (pitch, energy) or phonetic features (MFCC, Format Frequency) etc. Thus for selecting feature of speech for emotion identification, a review of works on speech emotion recognition is given in this paper. The aim of this paper is to present the works which are important to design and develop SER system for Chhattisgarhi language using neural network and analyze it.
Evaluation of ECG Signals for Mental Stress Assessment using Fuzzy Technique

— This paper presents the evaluation of mental stress assessment using heart rate variability. The activity of the autonomic nervous system (ANS) is studied by means of frequency analysis of the Electrocardiogram (ECG) signal. Spectral decomposition of the Heart Rate Variability before smoking and after smoking was obtained. Mental stress is accompanied by dynamic changes in ANS activity. ECG signal analysis is popular for assessing the activities of autonomic nervous system. The approach consists of 1) Recording the ECG signals, 2) Signal processing using wavelets, 3) Fuzzy evaluation techniques to provide robustness in ECG signal analysis, 4) Monitoring the function of ANS under different stress conditions. Our experiment involves 20 physically fit persons under different conditions. Fuzzy technique has been used to model the experimental data.
ARPN Journal of Science and Technology::Vulnerability of HL-60 cells towards TGHQ-mediated apoptosisDuring the Cell Cycle

TGHQ, a hematotoxic metabolite of benzene, depletes intracellular glutathione and induces rapid ROS-dependent apoptosis in HL60 cells. To determine the influence of the cell cycle on TGHQ induced apoptosis, we investigated synchronized and asynchronous cells by biochemical and flow cytometric analysis. Synchronized HL-60 cells were more sensitive to TGHQ induced apoptosis than their asynchronous counterparts. Synchronized cells underwent TGHQinduced apoptosis in as little as 2 hours, compared to 6 hours in asynchronous cell culture. S-phase cells exposed to TGHQ initiate apoptosis as early as 40 minutes after treatment and G2-M cells were less sensitive to PS externalization compared to S-phase cells. The proteosome inhibitor MG 132 induce apoptosis but did not potentate TGHQ mediated apoptosis in ROS induced HL-60 cells.
OPTIMAL CHANNEL ACCESS THROUGH IMPLICIT RESOURCE RESERVATION IN CSMA NETWORKS

: Carrier Sense Multiple Access (CSMA) networks are basically wireless LANs. The CSMA is a method that uses carrier sensing scheme in which the station which transmits data can detect collision and takes appropriate steps to have collision-free communication. Many stations in these networks share common resources for successful transmission of data. Resource reservation is one of the well known techniques that enable reserving shared resources to stations in order to improve communication efficiency and reduce contention. Especially the time-slot reservation in CSMA networks is a challenging and open problem to be addressed. Recently He et al. proposed a semi-random back off (SRB) method for contention based wireless networks that facilitate resource reservation. The SRB is different from random back off approach where it employs deterministic slot assignments in CSMA networks. The notion of back off counter is used which is set to zero on successful transmission of packets. As time slots are reused effectively on successive back off cycles continuously the implicit resource reservation is achieved besides reducing collision probability. In this paper we implemented this methodology using NS2. The simulation results reveal that the approach is useful in optimal utilization of resources .
Analysis of Different Error Detection Schemes over OFDM Signal

— A High speed communication is the basic requirement for any network. But such kind of networks always suffers from the problem noise and the internal interference. These problems can destroy or alter the communication data. The data reliability is the main concentration in such communication network. To get the integrity and reliability in such high speed network number of error detection and correction approaches are present. The effect of these approaches also change according to the capacity and the SNR ratio. This paper is about the analysis of different error correction schemes over the high speed OFDM networks so that the error rate can be reduced. In this work, a efficient scheme is suggested to reduce the error rate over the OFDM signal while transferring the video data.
PHOTOCATALYTIC DECOMPOSITION OF ISOLAN BLACK BY TIO

Anatase phase TiO 2, TiO2-SiO2 (TS) photocatalyst were prepared by wet chemical te chnique. The synthesized nano particles were characterized by XRD, SEM-EDAX, TEM, UV and FTIR sp ectroscopy. The grain size of the TiO 2 nanoparticles was found to be 24nm, while 7-10nm for TiO2-SiO2was calculated by using Scherrer’s formula. The TiO 2-SiO2 core shell nanocomposites were identified by TEM analysis. Ti-O, Si-O bonds were confirmed by ED AX and FTIR. The photocatalytic decomposition of Is olan black was investigated. The photo catalytic activity of TiO 2, enhanced by doping of SiO 2 on TiO2. The important factors such as pH, Wt % of dyes and nanoparticles, intensity of light are also affect the photocatalytic action.
Effects Of Livelihood Diversification On Food Se- curity Status Of Farm Households In North Gondar Zone A Case Study Of Gondar Zuria Woreda

Although still of central importance, farming on its own is increasingly unable to provide a sufficient means of survival in rural areas. Further, the asset base of farmers is not diversified, so loss of farming productivity during severe drought results in the total loss of assets and hence results in food insecurity and dependency on food aid. Therefore, it was crucial to identify the causes and consequences of food insecurity; assess the different livelihood strategies and their role to household food security status; and examine the effect of livelihood diversification to household food security status in order to recommend possible alternative actions. To achieve these objectives, data was collected from primary and secondary sources to understand the determinants, events and processes involved in people‟s livelihoods. Livelihood strategies and food security status of 120 farm households were examined. The qualitative data was analyzed in the form of narratives, content analysis, comparison and triangulation where as the quantitative data was analyzed using descriptive statistics, and chi-square to test the significance. The major findings of the study imply that rapid population growth, resource degradation and shrinkage of cultivated land, drought, land fragmentation, weak financial and institutional organizations have puts the farm households at risk of food insecurity. This necessitates the need for enormous efforts in interventions in areas that help households to diversify their livelihoods both within and outside the agricultural system even though the chisquare test indicates insignificant associations. However, based on this result the researcher did not jump to the conclusion that diversification has no effect on food security status of farm households, but this result may be due to the different types of livelihood diversification strategies, their nature, and level and I recommend further in-depth determinants studies/research for future policies/strategies and concerned stakeholders working towards achieving food security must coordinate and intensify their efforts to get feasible and tangible outcomes.
Implementing Web Data Mining Framework for Online Clothes Shopping

: Big Data starts with large-volume, heterogeneous, autonomous sources with distributed and decentralized control, and seeks to explore complex and evolving relationships among data so the personalized and helped in meeting better requirements of users. Growing data memory capacity as fuelled the development of data management and processing. The developers tried to build taxonomy of web knowledge so that it can be used in a better ways and succeeded in developing sound framework. However, data mining is relevant considering the deliberately demanding change in diversity of the web, information acquisition retrieving and extracting of interestingness contents which are web based has become a very complex task. Web mining framework makes highly attempts to make view of gathering useful relevant data by reducing the complexity field in the data which received from the interaction of users from the web which is determinant feature of web data mining, and this is of our best information of web knowledge, we analyse the challenging issues in the big data revolution, this projects helps in drawing a comprehensive overall virtual framework and summarizes the corresponding techniques and methods to analyse in knowledge framework namely for e-business.
Detection of Glaucoma and Hypertension using Artery or Vein Classification

This paper recognizes the detection of vascular changes in retinal vessels. From the retinal vasculature, artery/vein classification is done. It classifies the types of graph nodes and assigns graph links for one of two labels. Finally for the classification of artery/vein (A/V), graph based labeling results with a set of intensity features are performed. For doing this, list of 30 features are to be extracted. To measure the distance between nodes, a biometric graph matching algorithm (BGM) is used. In this diseases like glaucoma, hypertension is detected by using feed forward neural network (FFN). A gray level co-occurrence matrix (GLCM) is used for feature extraction. Here STARE, DRIVE, MESSIDOR databases are used.
Meta Management - Virtual Organization: a new approach in the leadership and select qualified individuals for virtual organizations with an emphasis on the role of IT

Recent progress in the field of information technology taken have caused the emergence of a new form of organization called virtual organizations, these organizations as a new paradigm for competitive advantage organizational plan, and respond to e-commerce requirements have been crystallized . Virtual Organization Management, which is called meta-management, a systematic approach for taking advantage of a competitive economic advantage is a virtual organization. This article reviews the definitions, dimensions of virtual organizations, virtual organization features, the basic factors in the success of virtual teams and organizations, meta - management and requirements management in virtual organizations, selecting the right people for virtual organizations, led all comprehensive role for enabling IT organizations, virtual organizations, virtual role in the twenty-first century and eventually paid the sum and pay a conclusion.
Journal of Diabetes and Obesity

Objectives: Obesity is associated with abnormal adipokines production and activation of inflammatory signal pathways in adipose tissue. Also, there is rising facts about the relation between the adiponectin function and pathogenesis of type 2 diabetes. The aim of this study is to investigate the relationship between the levels of leptin, adiponectin, tumor necrosis factor alpha (TNF-α) and lymphocytes count in diabetic and obese diabetic participants and its significance in the etiology of diabetes and obesity in Sohag Governorate. Methods: 91 unrelated subjects include 34 normal, 49 obese and 8 obese with type 2 diabetes at Hospital of Sohag University were enrolled in this study. Serum leptin, adiponectin and TNF-α levels were measured using ELIZA kit. Fasting and postprandial 2 hours blood glucose level was measured by colorimetric method. Other measurements including blood pressure, BMI and CBR were measured in hospital laboratory. Results: Both obese and obese diabetic subjects have hyperglycemia and hypertension in comparison with control, however, obese diabetic subjects have higher significant level than obese. Leptin level in plasma was significantly higher in obese and obese with type 2 diabetes subjects than control group, where adiponectin level was lower in these subjects than control group. In obese and obese with type 2 diabetes subjects, both of lymphocytes count and level of TNF-α were higher than control and in obese diabetic than obese non diabetic subjects. Conclusion: The present results showed in obesity with or without type 2 diabetes serum levels of leptin and TNF-α and lymphocytes count were increased, however, adiponectin level was decreased. Moreover, the high level of TNF-α reflect risk factor for vascular diseases like hypertension. *Corresponding Author: Hossam El-Din M. Omar, Department of Zoology, Faculty of Science, Assiut University, Assiut 71516, Egypt. E-mail: hossameldin.mo@gmail.com
Variable-5bits Algorithm for Compression Inverted Index

One of the most important characteristics of file compression is to preserve memory with all its temporary and permanent images, in addition to maintaining the speed of performance in the process of compression and decompression and increase the frequency range in the transmission and reception from long distances. The examined the performance of Variable-Byte compression scheme over sequences of integers. Variable-Byte algorithm which has high compression speed and decompression speed while the algorithm's compression ratio is weak in the case of small integers. A new compression algorithm - Variable-5bits, has been designed, the ratio of compression is improved from 4 to 6.4 in the case of small integers. In the case of large integers, the Variable-5bits algorithm is roughly equal in the compression ratio with the Variable-Byte algorithm. A number of experiments were performed to test the compression ratio in the new algorithm in different and varied samples when the range is small between integers, the compression ratio is high and when the range is large between the integers we get a low compression ratio.
Efficient Indexing of Spatial Query

-In past few years the Geographical Information Retrieval is very active field for research. Due to this research a new type of search engine came into existence called as Geographical Search Engine. Geographical search engine help to retrieve document which more textually and spatially relevant to our query. Indexing structure for spatial relevant is the main goal of this field and also to store and retrieve document having spatial scope of the given query. In this context we give an efficient tree structure called IR-tree, which allows searches to adopt different scope on textual and spatial relevance of document.
DVS Scheduling in Multi Core Real Time System

-Embedded systems have been widely used in portable devices. To meet real time application demands computing capability of the embedded system should be high. It is very important for designing of embedded system to enable minimum energy consumption to while meeting the real time application demands. Dynamic voltage scaling technology enables effective reduction of energy consumption by utilizing slack time to modify operation voltage and frequency of processor in order to reduce energy consumption. Multi-core systems providing better throughput capability than single-core processor working under in same clock frequency. The proposed IEDF-DVS (Improved EDF with Dynamic Voltage Scaling) scheduling algorithm can effectively reduce energy consumption in multi-core environment and ensure all tasks to meet their deadlines.
Thermo-Mechanical Characterization of Unreinforced and Carbon-Reinforced Shape Memory Polymer

Shape Memory Polymer (SMP) is a class of smart materials with unique capability of remembering its shape. It can be restored from a temporary fixed shape to permanent shape upon exposure to an external stimulus like heat, light, magnetic field, moisture etc. As opposed to its widespread use in many engineering applications, low stiffness and strength has restricted its excessive usage in structural engineering field. This research focuses on manufacturing and characterizing SMP and its carbon fiber reinforced composite (SMPC). The material is thermo-mechanically characterized for its transition temperature (Tg) using Dynamic Mechanical Analysis (DMA). Fold-deploy tests are conducted to determine shape fixity and shape recovery ratios. Additionally, the effect of temperature increase in recovery ratio is also investigated. Mechanical characterization is done via static uniaxial tensile tests. A substantial increase (100%) is observed in stiffness of SMPC compared to SMP. The samples are analysed for the effect of increasing shape memory cycles, which show that the major decline in stiffness essentially occurs after the first cycle. Similarly, on studying the effect of degree of deformation, the major decline in stiffness or increase in strength is found to occur after an angle of deformation of 45 ̊.
Marketing Practices Of Small Medium Size Enterprises A

Small and Medium Size Enterprises are the backbone of every major economy and empirical studies prove that small firms are more efficient and innovative in their operation, product development and marketing strategies. The objective of this research study is to analyze marketing practices (strategies) of Small and Medium Size Enterprises running entrepreneurs in Multan.This study is qualitative in nature in which we have studied the major characteristics of selected Small and Medium Size Enterprises. Primary Data was collected through a structured questionnaire by having interviews with the entrepreneurs. At least thirteen Small Medium Size Enterprises operating in Multan District were selected as a sample of study and a formal questionnaire was prepared. A field survey method was applied and faced to faced interviews were recorded to analyze the marketing strategies of SME’s. The evidences show that SME’s under study achieved success and established their names and brands through innovations. Their innovations were in the shape of unique designs that not only meet the need of customers. Their services are innovative in a sense that they satisfy the customers. Thus our consistent with previous studies which pinpoint that small medium enterprise are innovative and more efficient than large firms.
MAPREDUCE FOR BIG DATA PROCESSING BASED ON NETWORK TRAFFIC PERFORMANCE

: After the Map phase and before the beginning of the Reduce phase is a handoff process, known as shuffle and sort. Here, data from the mapper tasks is prepared and moved to the nodes where the reducer tasks will be run. When the mapper task is complete, the results are sorted by key, partitioned if there are multiple reducers, and then written to disk. The MapReduce programming model simplifies large-scale data processing on commodity cluster by exploiting parallel map tasks and reduce tasks. Although many efforts have been made to improve the performance of MapReduce jobs, they ignore the network traffic generated in the shuffle phase, which plays a critical role in performance enhancement.
Clinical-Diagnostic Features of Duchenne Muscular Dystrophy in Children

Duchenne Muscular Dystrophy (DMD) is a severe, progressive disease that affects about 1 out of every 5,000 male infants; this is the most destructive of all muscular dystrophies, which worsens rapidly. In this study, we performed a clinical analysis of 37 children with DMD. They ranged in age from 3 to 15 years, mean age being 7.8±0.48 years. The mean age at onset was 4.3±0.36 years and ranged from birth to 8 years. The biochemical examination included the determination of the serum levels of the following enzymes, AST, ALT, CPK-MM, and LDH. A genealogical analysis was conducted among 240 first-degree relatives of children with DMD. Electroneuromyography examination included registration of the biopotentials of the hand and foot muscles, measurement of the muscle response (M-wave) and the late-evoked responses. The clinical-diagnostic features of DMD in children were characterized.