Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Affecting Quality of Building Construction Projects in Informal Settlements within Nairobi City County, Kenya

Construction industry plays a major role in the development and achievement of society’s goals, contributing to about 10% of the Gross National Product (GNP) in industrialized countries and, it constitute 60-70% of the national wealth and about 20% of the annual wealth creation in less developed countries. Despite of the weight given to the construction industry, quality of construction projects has been questioned as indicated by widespread collapse of building structures in Kenya. This study sought to find out factors contributing to the quality of construction projects with the focus on the effects of technical factors and economic factors. A descriptive research design was adopted. The target population of 412 completed and ongoing projects was used, which had a workforce of 1678, from which a sample of 30% (503) was selected. Primary data was collected using questionnaire. Statistical Package for Social Statistics V 22.0 was used to analyses the data. Descriptive statistics indicated study variables were very important as shown by high values of mean and the opinions of respondents had low variations as shown by low values of standard deviation. The study findings indicate that technical factors and quality of the construction projects are positively and significantly relate (r=0.145, p=0.005) and economic factors and quality of construction projects are positively and significantly related (r=0.076, p=0.001). The study concludes that technical and economic factors contribute to the quality of construction projects in informal settlement and should be given weight they deserve. The study recommends that the government should ensure there is documentation and enforcement of the policies, systems, processes and procedures to help the construction practitioners manage construction work effectively.
Analysis of Wormhole Attack Detection and Prevention Techniques in MANET

— MANET is a collection of autonomous system of mobile nodes connected with each other using wireless link and each node communicates with each other using wireless link that are within its transmission range. Mobile Ad-Hoc Network (MANET) is an infrastructure less self-configured collection of mobile nodes that can arbitrarily change their geographic locations such that these networks have dynamic topologies and random mobility with constrained resources. The network is unbounded by any fixed infrastructure or any central authority. The absence of any central coordination mechanism and open nature makes the Mobile Ad Hoc Network more vulnerable to security threats. Wireless networks are susceptible to many attacks, including an attack known as the wormhole attack . Wormhole attack is one such security threat at network layer which causes routing disruption. The attacker at one point in the network records the packet and forwards it through a high speed tunnel to the other attacker present at distant location giving an false impression to nodes in both the network that they are immediate neighbors. This paper presents a study on wormhole attack and various existing techniques to detect and prevent wormhole attack in MANET.
Multimedia Information Retrieval for Lecture Video using Automatic Speech Recognition and Optical Character Recognition

- Now-a-days increased development in multimedia technology allows the capturing and storing of video data with highly expensive computers. Users are not satisfied with video retrieval systems available because of analogue VCR functionality provided. This research represents an approach for automated audio, video content retrieving over huge lecture video repositories. It apply/uses automated video segmentation and key-frame detection method. Subsequently, It extract/takes out textual meta-data by applying video Optical Character Recognition (OCR) technology algorithm on lecture video key-frames and Automatic Speech Recognition (ASR) on lecture audio tracks content of the video to retrieve audio from video and then convert that audio track into text details. Main purpose is to provide multimedia data such as image and video for extracted words. It provides relevant information i
A Survey Paper On Single Image Dehazing

— Images taken in foggy weather condition often suffer from poor visibility and clarity. Images of the outdoor scene which are captured under bad weather conditions contain atmospheric degradation such as haze, fog, smoke caused by the particles present in the atmosphere resulting in the absorption and scattering of the light, which travels from the scene point of the observer. Due to the presence of the various atmospheric particles (like fog, mist, smoke, water-droplets etc.) there is a resultant decay in the color and contrast of the images captured under the bad weather conditions. Such images also exhibit some losses in their quality which are dependent on the distance. Sometimes it may also causes difficulty in detecting the objects in the hazy images or scene. So, if the depth and the atmospheric condition are known, we can enhance the images by compensating the effect of the fog. This paper describes the various haze removal techniques to remove the haze from the captured hazy images and to recover a better and improved quality haze free images.
Incidence of Campylobacter Species in Poultry Products and Beef Sold in Owerri, Imo State, Nigeria

The incidence of Campylobacter species in beef and poultry products sold in Owerri, Nigeria, was assessed. A total of 400 samples were analysed. Isolates were recovered on selective media and characterized using the API Campy Kits. Incidence data revealed that Campylobacter jejuni ssp jejuni 2 was predominant in all samples with an incidence of 53(13.25%), 51(12.75%), 51(12.75%) and 49(12.25%) respectively for the Ready-to-eat meat, Turkey meat, Chicken meat and Beef; Campylobacter jejuni ssp jejuni 1 had an incidence of 20% on the Ready-to-eat meat, 17% each on the others. On the other hand, Campylobacter coli had an incidence of 22%, 27%, 28% and 34% on the Ready-to-eat meat, Turkey meat, Chicken meat and Beef respectively while the least abundant isolate was the Campylobacter jejuni bv fecalis with an incidence of 5 (1.25%), 5 (1.25%), 4 (1%) and 0(0%) respectively.
Leaf Disease Identification using Image Processing

: Every year farmers are experiencing large amount of losses because of diseases that are occurring on leaves of various crops. Leaf diseases leads to reduction in both quality and quantity of agricultural products. Detection of diseases occurring on plant leafs automatically is an essential topic as it may prove beneficial for monitoring large field of crops. Various image processing techniques are used to detect diseases occurring on plant leafs. The given system is software solution for automatic detection and classification of plant leaf diseases. This system consists of four steps, first step includes formation of color transformation structure of input RGB image, in the second step masking of green pixels is done & those green pixels are removed using specific threshold value followed by segmentation process, third step includes computing of texture statistics for useful segments and finally those extracted features are passed through classifier.
Hybrid Beamforming Based mmWave for Future Generation Communication

— Massive MIMO is the key technology that will enable us to develop and implement 5G networks. But there are a few problems with MIMO technology. These MIMO systems will use huge antenna arrays. Now, this will hugely improve gain, but they also pose a lot of problems including increase in cost. All of these problems can be solved by the use of hybrid beamforming.
Modern Trends in Engineering

-A sketch is freehand picture which serves various purposes such as tracing something that the artist can visualize so that they quickly explore concepts. Sketch-based communication is no newer, it is the oldest form of writing, and therefore Sketch-Based Image Retrieval (SBIR) can be a very valuable information search tool. Although sketch is good way to express people’s ideas, but sketches and photorealistic images are very different in the term of appearance. The photorealistic image shows attention to realistic detail. There is a large appearance gap in user sketches and photorealistic images, when people sketch, they usually focus on main structure or shape of object and only draw the semantic contour boundary. On the other hand the color, texture and shape of an object are main elements of photorealistic images, which makes it very difficult to directly match a sketch and the corresponding photo-realistic image. Therefore, to bridge this gap is fundamental challenge in SBIR. The existence of noisy edges on photo realistic image degrades retrieval performance and to bridge this gap there is framework consisting of line segment descriptor and noise impact reduction algorithm. Proposed descriptor extracts edges and captures the relationship between the edges. Object boundary selection algorithm used to reduce the noisy edges for which the hypothesis is used to maximize retrieval score, for which multiple hypotheses are generated.
Fabrication and Testing of Al-Cu-B4C Composite by Mechanical Alloying

The present work focuses on the fabrication of reinforced with 12 wt. % of B4C particulates through ball milling. Ethanol (5 wt. %) has been used as a process control agent (PCA). In this work, mechanical alloying was used to synthesize aluminium matrix composite powder in a conventional ball mill under argon atmosphere with different milling time of 5, 10 and 15 hours. The ball to powder weight ratio was maintained at 10:1. Scanning electron microscopy (SEM) of the ball milled powder shows that addition of boron carbide particles accelerates the milling process, leading to a faster work hardening rate and fracture of aluminum matrix. SEM images show that distribution of boron carbide particles in aluminum matrix reaches a full homogeneity when steady state takes place.Energy-dispersive X-ray spectroscopy (EDX) is performed to check the contamination of composites during the mechanical alloying. Green densities and Hardness of each composite have been calculated.The Hardness of the composites was increased with increase in the milling time.
Strength and Shrinkage Characteristics of Geo-Polymer Concrete

Geo-polymer concrete (GPC) is a concrete manufactured without using cement. This type of concrete has environmental benefit as it has very low greenhouse gas emission compared to that resulted from the production of Portland cement. In addition, it also utilizes the by-product materials which make it more environmentally friendly. Geo-polymer concrete in the present study is manufactured by using the industrial by products such as Ground Granulated Blast Furnace (GGBS), fly-ash as source materials which are rich in silica and aluminum; alkaline solution and aggregates normally used for ordinary Portland cement concrete. In this paper, the strength and drying shrinkage characteristics of geo-polymer concrete have been compared with that of ordinary Portland cement concrete.
Knowledge Management Strategy and Initiative for Development of Digital Energy Hub

This article revised several Knowledge Management (KM) strategies and initiatives, in order to develop the digital energy hub. This digital platform employs robust computers and network technology to cater for a wide-range exchange of information and knowledge, which eventually supports new businesses, collaboration and globalization for the energy players. The objective of this article is to analyze KM strategy and initiative for the purpose of developing a digital energy hub. Among the important strategies are goal setting, KM leadership, structure and skill; supported by essential initiatives such as knowledge creation, transfer and sharing. Thus, by accurately identifying the relevant KM strategies and initiatives, the probability for future development and deployment of this platform to be successful can be enhanced.
Smartphone Sensor Based Human Activity Recognition using Deep Learning Models

: The significant intent is to generate the model for anticipating the activities of a human that ensures the aversion of human life. Activity Recognition (AR) is monitoring the liveliness of a person by using smart phone. Smart phones are used in a wider manner and it becomes one of the ways to identify the human’s environmental changes by using the sensors in smart mobiles. Smart phones are equipped in detecting sensors like compass sensor, gyroscope, GPS sensor and accelerometer. The contraption is demonstrated to examine the state of an individual. Human Activity Recognition (HAR) framework collects the raw data from sensors and observes the human movement using different deep learning approach. Deep learning models are proposed to identify motions of humans with plausible high accuracy by using sensed data. HAR Dataset from UCI dataset storehouse is utilized. The performance of a framework is analyzed using Convolutional Neural Network with Long-Short Term Memory [ConvLSTM] and Recurrent Neural Network with Long-Short Term Memory [RNNLSTM] using only the raw data. The act of the model is analyzed in terms of exactness and efficiency. The designed activity recognition model can be manipulated in medical domain for predicting any disease by monitoring human actions.
Spatial Distribution Adaptive Protocol for Multicast Routing in MANET

—Mobile ad-hoc network is an important and emerging application of wireless systems. Number of applications are developed on broadcast communications, so efficient routing methods are critical for their success. Blindly retransmitting broadcast packets can lead to an explosive growth of traffic called the Flooding and looping problem that attenuates broadcast performance as a result of collisions and congestion. A major design issue for an efficient and effective routing protocol for MANETs is to achieve optimum values of performance parameters under network different scenarios where nodes are subjected to different types of mobility that dynamically change the network topology. In this paper the Distribution-Adaptive Distance with Channel Quality (DADCQ) protocol used and designed to tackle various multicast problems and shown some simulation results that it performs well compared to several existing multihop broadcast proposals. DADCQ protocol performs better than several existing broadcast protocols by using distance method and adaptive decision threshold value.
ACQUISITION BASED ON NONLINEAR DIMENSIONAL REDUCTION

: Hand gestures are the way of communication between speech impaired people and normal persons. It provides human-machine interaction, Gestures are the inputs in hand sign recognition as we use input devices such as keyboard and mouse in computer system. The aim of this paper is to provide interface that connect digital world to physical world. Keyboard and mouse are the input devices used to get information about news, weather, business news etc. Hand gestures are the medium of communication through expressions, through sign language. In every state of India there are different languages used, so sign language is also different but having same grammar. Distributed locally linear embedding (DLLE) is a learning algorithm which is used for the dimensionality reduction. This algorithm is used to specify the intrinsic structure of data.
In vivo activity and pharmacokinetic analysis of combination of piperine and subtherapeutic dose of sodium valproate in refractory epilepsy

Sodium valproate (SVP), a broad spectrum anticonvulsant, is associated with liver toxicity. The long term treatment may result in adverse consequences. Piperine (PIP), the major constituent obtained from the peppercorns of black pepper is used in anticonvulsant formulations in traditional Chinese medicine. A combination of subtherapeutic dose of SVP and PIP was evaluated for their activity in refractory epilepsy, using 6-Hz psychomotor seizure model (6 Hz, 44 mA for 3s duration) in mice. Further, the mechanism of seizure control by PIP was evaluated through reserpinisation, which was used as pathology inducer. A gas chromatography-mass spectrometry method was developed and validated for simultaneous analysis of SVP and PIP to evaluate their pharmacokinetic interaction. SVP in presence of PIP produced highest protection against 6 Hz induced seizures. However, the protection afforded by SVP and PIP was abolished in reserpinised mice, which was attributed to the depletion of monoamines by reserpine. The plasma estimation indicated 11-fold increase in the concentration of SVP in presence of PIP. Plasma analysis of SVP and PIP suggests that the doses can further be reduced to obtain therapeutic plasma concentrations. Attenuation of monoamine lowering effect of reserpine by PIP and SVP indicates that the mechanism is related to the levels of monoamine neurotransmitters in brain. Further, studies are warranted measuring the levels of neurotransmitters to provide clear insights on the role of monoamines in seizure control.
Energy management system for smart home using IoT

One of the major attribute of the Smart home automation and energy management systems integrate IOT and renewable energy resources at the consumption premises. With advancement of Automation technology, today’s world prefers Automatic systems over manual systems. This paper presents the design, implementation and testing of an embedded system using arduino that integrates solar energy resources and energy management to a smart home incorporated with IOT. The proposed system provides and manages a smart home energy requirement by installing renewable energy and scheduling the power flow during peak and off-peak period. IOT (Internet of things) is the latest and emerging internet technology. Internet of things is a growing network of everyday object-from industrial machine to consumer goods that can share the sensors information to the Automation system using WIFI communication. IoT is a system that uses computers or mobile devices to control all home functions and features automatically through internet. In addition to that, a two-ways is developed to enable the home owner and the utility provider to better optimization of the energy flow and the consumption efficiency. A prototype for the proposed system was designed, implemented and tested using a controlled load bank to simulate a scaled random real house consumption behavior.
Face Recognition Techniques: A Survey

-Face Recognition technique is generally used for real time application. Reliability is the more important thing for security. Facial Recognition is rapidly becoming area of interest. Face biometrics is useful for authentication that recognizes face. In this paper survey of face recognition methods exhibit and discuss their pros and cons. The objective of this paper is to provide a survey of face recognition methods that appeared in the previous literature over the past decade and also differentiate them into meaningful approaches
AN EFFICIENT MULTICAST ROUTING PROTOCOL TO IMPROVE PERFORMANCE METRICES IN MANET

A vital and vital issue for multicast versatile specially appointed systems (MANETs) is directing convention plan i.e. a noteworthy specialized test because of the dynamism of the system. Versatile Ad-Hoc Network (MANET) is an element, multi-bounce and self-ruling system made out of light remote portable hubs. A considerable measure of control messages are required to manufacture ideal multicast trees and keeping up gathering enrollment because of the dynamism of MANETs. Because of these overheads we devour more prominent vitality resourses of portable hubs and system resourses like remote connections transfer speed . This paper displays a compelling multicast steering convention for MANET with minimum control overhead. The convention builds shared multicast tree utilizing the physical position of the hubs for the multicast sessions. To get the physical area of the hubs we utilize the idea of appropriated area administration , which viably diminishes the overheads for course looking and shared multicast tree maintenance.In this convention we utilize the idea of little covered zones around every hub for dynamic topology support with in the zone. To interest for a current multicast tree outside the zone, obliged directional sending is utilized which guarantee a decent decrease in overhead in contrast with system wide flooding for pursuit method.The convention utilizes neighborhood availability procedure and defensive course reconfiguration on the premise of the present status of the hubs are being proposed which diminishes the overhead, power and transmission capacity prerequisite and attempt to expand the execution and unwavering quality.
STUDY OF METHODS USED IN NGS ( NEXT GENERATION SEQUENCING ) IN GENE EXPRESSION

Study of Central Dogma in biology at molecular level is much more important which helps us to understand the genetic arrangement and aspects of gene expression at different level and scenario, which can be useful in studying the expression level for disease and their cause and precautionary measures.DNA sequencinf has come a long way since the days of two-dimensional chromatography in 1970‘s,Genome sequencing is one of the method which helps to provide the details of every sequence and Base pair, which means to determine the primary structure (sometimes falsely called primary sequence) of an unbranched biopolymer. Sequencing results in a symbolic linear depiction known as a sequence which succinctly summarizes much of the atomic-level structure of the sequenced molecule. NGS (Next generation sequencing) makes sequence-based gene expression analysis a ―digital‖ alternative to analog techniques. It lets you quantify RNA expression with the breadth of a microarray and the resolution of qPCR.
Multiple-Criteria Decision Analysis: A Novel Rank Aggregation Method

------------------------------------------------------------------- ABSTRACT --------------------------------------------------------------- Ranking among several objects is a very crucial operation for different applications to find a vote value for each object against the others. Multiple metrics can be combined to get a single vote value of an object. There are many studies in the literature that convert the ranking problem into a graph structure to solve it with a discrete mathematical process. Generally, these studies define multiple metrics as matrix forms and then relate them with the computations of eigenvectors to find the best ranked object. However, due to the dynamic nature of the metric values, ranking approaches should be fast and less complex. In this study a different approach for the ranking process with multiple metrics is proposed. This approach is fast and easy to implement. In order to test the approach, a network scenario is designed with computer programs. The experimental results show that this method outperforms a common conventional method in terms of various metric values, namely transmission time, packet loss rate, jitter, availability, and throughput. As a consequence, the proposed method gives the average value of each individual metric as more advantageous and without rescaling the numerical values.
A New Approach for Face Recognition and Age Classification using LDP

— The present paper proposes a novel local texture features on facial images that recognise facial images based on the Morphological primitive patterns with grain components (MPP-g) on a Local Directional Pattern (LDP). A LDP feature is obtained by computing the edge response values in all eight directions at each pixel position and generating a code from the relative strength magnitude. The local descriptor LDP is more consistent in the presence of noise, and illumination changes, since edge response magnitude is more stable than pixel intensity. The present paper proposes Morphological primitive patterns with grain components (MPP-g) which are rotationally and pose invariant for face recognition and age classification. The experimental result on FGnet database images shows the efficacy of the proposed method.