Analysis of Data for Diabetics Patient

Diabetes, a disease responsible for different kinds of diseases such as heart attack, kidney disease, blindness and renal failure etc. The most common disorder is the endocrine (hormone) system, occurs when blood sugar levels in the body consistently stay above normal. There are two types of diabetic; one is body's inability to make insulin and another is body not responding to the effects of insulin. In our developing country Bangladesh, Diabetes is a costly disease whose risk is increasing at alarming rate. This paper evaluates the selected classification algorithms for the classification of some Diabetes patient datasets. Classification algorithms considered here are Naive Bayes classification (NBC), Bagging algorithm, KStar algorithm, Logistic algorithm and Hoeffding tree. These algorithms are evaluated based on four criteria: Accuracy, Precision, Sensitivity and Specificity. Collected datasets of diabetes affected people are firstly preprocessed then some investigation based on mentioned algorithm has been executed successfully. From the investigation result it is found that, KStar algorithm is the best as it gives high accuracy with the low error. Here it is said that, some parameters are responsible for diabetes

An Improved Multi-Hop-Enabled Energy Efficient MAC Protocol for Underwater Acoustic Sensor Networks

Packet collisions occurred by hidden and local nodes in multi-hop enabled underwater acoustic sensor networks (UWASNs) have effect on throughput, energy efficiency and end-to-end delay. Existing Multi-HopEnabled Energy Efficient MAC Protocol for Underwater Acoustic Sensor Networks (MHEE MAC) utilized a double-phase contention resolution mechanism, which causes visit multiple time slot and energy overhead. In this paper, we propose a MAC protocol that use contention resolution mechanism with unique priority to provide energy efficiency. First, local nodes are eliminated comparing their priority and later, hidden nodes are mitigated. A simulation of proposed protocol is also developed to analyze the performance. Results obtained through simulation show that the proposed protocol achieves significantly lower energy consumption, reserve more energy and more stable throughput compared to MHEE-MAC, T-Lohi and slotted floor acquisition multiple access (S-FAMA)

Priority based Congestion Control Mechanism in Multipath Wireless Sensor Network

Wireless Sensor Network (WSN) is a network composed of distributed autonomous devices using sensors. Sensor nodes send their collected data to a determined node called Sink. The sink processes data and performs appropriate actions. Nodes using routing protocol determine a path for sending data to sink. Congestion occurs when too many sources are sending too much of data for network to handle. Congestion in a wireless sensor network can cause missing packets, long delay, overall channel quality to degrade, leads to buffer drops. Congestion control mechanism has three phases, namely congestion detection, congestion notification and congestion control. In this paper is propose two bit binary notification flag to notify the congested network status for implicit congestion detection. For congested network status, we propose a priority based rate adjustment technique for controlling congestion in link level. Congested packet will be distributed equally to the child node to avoid packet loss and transition delays based on technique. Furthermore, this technique allocates the priority of many applications simultaneously running on the sensor nodes, which route is own data as well as the data generated from other sensor nodes. The results show that the proposed technique achieves better normalized throughput and total scheduling rate with the avoiding packet loss and delay

An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features

Gastrointestinal polyps are considered to be the precursors of cancer development in most of the cases. Therefore, early detection and removal of polyps can reduce the possibility of cancer. Video endoscopy is the most used diagnostic modality for gastrointestinal polyps. But, because it is an operator dependent procedure, several human factors can lead to misdetection of polyps. Computer aided polyp detection can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention to. In this paper, an automatic system has been proposed as a support to gastrointestinal polyp detection. This system captures the video streams from endoscopic video and, in the output, it shows the identified polyps. Color wavelet (CW) features and convolutional neural network (CNN) features of video frames are extracted and combined together which are used to train a linear support vector machine (SVM). Evaluations on standard public databases show that the proposed system outperforms the state-of-the-art methods, gaining accuracy of 98.65%, sensitivity of 98.79%, and specificity of 98.52%

A Novel Design and Implementation of New Double Feynman and Six-correction logic (DFSCL) gates in Quantum-dot Cellular Automata (QCA)

In recent years, quantum cellular automata (QCA) have been used widely to digital circuits and systems. QCA technology is a promising alternative to CMOS technology. It is attractive due to its fast speed, small area and low power consumption. The QCA offers a novel electronics paradigm for information processing and communication. It has the potential for attractive features such as faster speed, higher scale integration, higher switching frequency, smaller size and low power consumption than transistor based technology. In this paper, Double Feynman and Six-correction logic gate (DFSCL) is proposed based on QCA logic gates: MV gate and Inverter gate. The proposed circuit is a promising future in constructing of nano-scale low power consumption information processing system and can stimulate higher digital applications in QCA

Efficacy of Neem Kernal Powder and Neem Oil against Helicoverpa Armigera on Sunflower Crop

A field study was carried out during 2013 at the experimental area of Sindh Agriculture University Tandojam during, in RCBD to exmine the efficacy of neem kernal powder, neem oil and Radaint against Helicoverpa armigera on sunflower crop. Four treatments with T1=Neem kernel powder, T2=Neem oil, T3=Radiant and control (Untreated). Variety HO-1 was sown on 1st March 2013. The experiment replicated three times. The results reveled that biopesticides and synthetic pesticides were sprayed against H. armigera on the sunflower crop. The plots treated with radiant showed heighest efficacy (52.60%), followed by the plots treated with Neem seed kernel extract (31.32%) and the plots treated with Neem oil (30.14%) was recorded after 1st spray on sunflower crop. In the second spray the plots treated with radiant also showed heighest efficacy (57.30%), followed by the plots treated with Neem seed kernel extract (33.34%) and plots treated with neem oil (32.27%) was recorded on sunflower crop. However, in 3rd spray the heighest efficacy was recorded in the plots treated with radiant (50.48%), followed by the plots treated with Neem extracts (40.39%) and plots treated with neem oil (36.40%) was recorded. While, in fourth spray, the heighest efficacy was recorded the plots treated with Neem extracts (42.60%), followed by the plots treated with Neem oil (31.40%) and plots treated with Radaint (39.40%) was recorded on sunflower crop. The overall results showed that the biopesticids reduced H. armigera population progressively, as compared to synthetic pesticides. Keywords: Sunflower, Helicoverpa armigera and Neem Product

Surveillance on the Sucking Insect Pests and their Natural Enemies on Tomato Crop

The experiment was conducted at the experimental area of Sindh Agriculture University Tandojam during 2013. The Roma variety was cultivated for this purpose, the all agronomic practices were carried out accordingly. The temperature 15-24ºC and relative humidity 45-68% was recorded during research work. The results of the present experiment showed that sucking insect pests as well as natural enemies’ population was observed through out cropping season from 1st week of March to 1st week of May 2013. The results reveled that the maximum population of whitefly (5.5±0.16/leaf) was recorded followed by jassid (4.7±0.21/leaf), aphid (4.4±0.37/leaf) and thrip (2.9±0.17/leaf) on tomato crop. However, the maximum population chrysoperla carniea (1.2±0.16/plant) was recorded followed by spider (2.6±0.23/plant) and lady bird beetle (2.5±0.22/plant) was recorded on tomato crop. The results further reveled that the over all impact of relative humidity on the most of the insect pests showed negative correlation. However, the temperature showed that over all positive impact of all the insect pests and predators except whitefly and spider. Key Word: Solanum lycopersicum, Surveillance, sucking insect pest, Predator

Efficacy of Insecticides on Rice Crop Against Rice Leaf Folder, Cnaphalocrocis Medinalis Guen. (Pyralidae: Lepidoptera)

A field study was carried out during 2010 at experimental area Sindh Agriculture University Tandojam in RCBD to examine the reduction percentage in the population of C. medinalis on rice crop with three insecticides viz; Deltophos, Tracer, Thioluxan and impact of these insecticides was composed with control plot (untreated). The data showed the maximum reduction (76.19%) in the population of C.medinalis was recorded in the plots treated with Deltaphos followed by Tracer (65.93%) and Thioluxan (46.92%) after 1st spray on rice crop. In the second spray maximum reduction (71.08%) was also recorded in the plots treated with Deltaphos followed by Tracer (57.40%) and Thioluxan (30.15%). Similarly, after 3rd spray the maximum reduction (78.99%) was recorded in the plots treated with Deltaphos followed by Thioluxan (55.88%) and Tracer (54.34%) on rice crop. While, in fourth spray, the maximum reduction (71.92%) was recorded in plots treated with Deltaphos followed by Tracer (39.36%) and Thioluxan (14.36%) on rice crop. The results further indicated that the maximum yield (4783.00kg/ha?1) was recorded in plots treated with Deltophos followed by Tracer (4486.46kg/ha ?1) and  Thioluxan (4033.66kg/ha?1) as compared control (3066.50kg/ ha?1).Highly significantly (P < 0.01) difference in the efficacy of insecticides was recorded during all sprays carried out in cropping season of rice crop. Key word: Oryza sativa, Cnaphalocrocis medinalis. Management and Insecticides

Insect Infestation on Bt. and Non-Bt. Cotton Cultivars

A field study was carried out to examine the resistance potential of promising cotton cultivars to insect pest infestation, during the year 2012. Five cotton varieties were examined for their resistance against insect pests including Hari Dost, Shahbaz-95, NIAB-78, Sindh-1 and Bt Cotton. The insect pests monitored in this study included thrips, jassid, whitefly and bollworms. The experimental process for monitoring the insect pests was initiated on 15th June 2012 and lasted on 12th October, 2012. The results showed that thrips population was significantly (P<0.01) lowest (6.28/plant) on Haridost, against 9.22/plant on NIAB-78, 13.79/plant on Bt cotton 14.89/plant on Sindh-1. while the highest thrips population (15.21/plant) was recorded on  Shahbaz-95. The peak thrips population was noted on 12th July observation on all three verities while on Bt cotton, the peak thrips population was recorded on 19th July. Bt Cotton. The peak activities of jassid was recorded in the month of August. Overall mean showed that the signifactly highest (P<0.01) population of jassid was recorded as (3.59/leaf) on Sindh1 followed by Bt cotton (2.81/leaf), Shahbaz (2.80/leaf), Niab -78 (2.19/leaf) and Hari dost (1.63/leaf). Similarly, whitefly was found active in month of July and Augest. Significantly, more population (P<0.01) was recorded on Sindh-1 (3.20/leaf) and minimum on Haridost (1.40/leaf). Bollworms infestation was significantly lowest (P<0.01), (2.04/plant) on Bt cotton against 2.56/plant on NIAB-78, 3.04/plant on Haridost, 3.22/plant on Sindh-1; while the highest bollworms population (3.36/plant) was observed on cotton variety Shahbaz-95. Bt cotton variety showed considerable resistance against bollworm complex, while NIAB-78 also showed some resistance against sucking. The infestation of sucking insect pests on haridost. Shahbaz and Sindh-1 as compared to Bt cotton. The infestation of thrips, and whitefly was  peaked in the month of July. While Jassid was found most active in August. Bollworms appeared in first week of July and remained active in the field in relatively higher population upto the mid of September and later decreased to negligible level. Keywords: Cultivar Resistance, Insect Infestatio