Statistical analysis of mammographic features and its classification using support vector machine

This study aims at designing a support vector machine (SVM)-based classifier for breast cancer detection with higher degree of accuracy. It introduces a best possible training scheme of the features extracted from the mammogram, by first selecting the kernel function and then choosing a suitable training-test partition. Prior to classification, detailed statistical analysis viz., test of significance, density estimation have been performed for identifying discriminating power of the features in between malignant and benign classes. A comparative study has been performed in respect to diagnostic measures viz., confusion matrix, sensitivity and specificity. Here we have considered two data sets from UCI machine learning database having nine and ten dimensional feature spaces for classification. Furthermore, the overall classification accuracy obtained by using the proposed classification strategy is 99.385% for dataset-I and 93.726% for dataset-II, respectively.     

Minimizing total weighted tardiness on a batch-processing machine with non-agreeable release times and due dates

This study considers the scheduling problem observed in the burn-in operation of semiconductor final testing, where jobs are associated with release times, due dates, processing times, sizes, and non-agreeable release times and due dates. The burn-in oven is modeled as a batch-processing machine which can process a batch of several jobs as long as the total sizes of the jobs do not exceed the machine capacity and the processing time of a batch is equal to the longest time among all the jobs in the batch. Due to the importance of on-time delivery in semiconductor manufacturing, the objective measure of this problem is to minimize total weighted tardiness. We have formulated the scheduling problem into an integer linear programming model and empirically show its computational intractability. Due to the computational intractability, we propose a few simple greedy heuristic algorithms and meta-heuristic algorithm, simulated annealing (SA). A series of computational experiments are conducted to evaluate the performance of the proposed heuristic algorithms in comparison with exact solution on various small-size problem instances and in comparison with estimated optimal solution on various real-life large size problem instances. The computational results show that the SA algorithm, with initial solution obtained using our own proposed greedy heuristic algorithm, consistently finds a robust solution in a reasonable amount of computation time.     

Optimization of dry sliding wear behaviour of industrial wastes reinforced aluminium based metal matrix composites

Marble dust and basalt powder are industrial waste generated during the machining of marble stone and basalt rock. This paper presents an approach for the optimization of dry sliding wear parameters of aluminium 7075 reinforced with marble dust and basalt powder hybrid metal matrix composite using Taguchi based grey relational analysis. In this work, the composite is fabricated by stir casting technique and the wear parameters namely load, sliding velocity and sliding distance are optimized with consideration of multi responses such as wear rate and coefficient of friction. Experiments are conducted as per Taguchi's L9 orthogonal array. A grey relational analysis is carried out and grey relational grade is obtained. Based on the grey relational grade, optimum level of wear parameters has been identified by analysis of variance. The test results are validated by conducting the confirmation test. Experimental results have shown that the sliding velocity is the most effective factor among the control parameters on dry sliding wear, followed by the sliding distance and load. Finally, the micro structural investigations on the worn surfaces are performed by scanning electron microscope.     

E2IA-HWSN: Energy Efficient Dual Intelligent Agents based Data Gathering and Emergency Event Delivery in Heterogeneous WSN Enabled IoT

Heterogeneous sensors are equipped with a limited battery source that is concerned with network lifetime problems. However, this problem can be tackled with the effective design of WSN-IoT by clustering and sleep scheduling mechanisms. This paper addresses this issue by presenting novel ideas involved in the WSN operations such as grid construction, cluster head selection, sleep scheduling, and data gathering by intelligent Agents (iAgents). An energy-efficient dual iAgents based Heterogeneous WSN (E2IA-HWSN) is proposed. iAgents are used in this paper to automatically collect the sensed data from IoT sensors. In this E2IA-HWSN, a 3?×?3 grid is built and each cell is sub-divided into four in which cluster heads (CH) are selected in each sub-division, followed by ring partitioning for selecting a CH present at the center. Multi-Objective Harris Hawks optimization (MO-HHO) algorithm is used to select CH and supernode, here to minimize the energy consumption of CH, the supernode takes responsibility to assign sleep schedules to devices. The scheduling slots are assigned only after a sensor reaches below the energy threshold. For scheduling, the Bayes rule-based Markov model (BR-MM) is applied with the determination of residual energy and sensed packet counts. Generator de Bits Pseudo Aleatorios (GBPA) eliminates redundant data in CH and then inter-cluster routing is performed in case of emergency events. If not, then the CH waits for the arrival of iagents, the trajectory of iAgents is dynamically predicted with Deep Policy Gradient (DDPG). The implementation is carried out in NS3.26 and the results show betterment to the well-known methods.

     

Fault Detection and Diagnosis of Cyber-Physical System Using the Computer Vision and Image Processing

Wireless Personal Communications - This paper investigates the performance of an energy-harvesting (EH) relay network, where multiple sources communicate with a destination via multiple EH...     

Experimental investigation on pyramid solar still with single and double collector cover—Comparative study

Sun radiation is the heat energy source for solar still. That should be utilized maximum for increasing the evaporative rate at the top surface of the brine. The pyramid shape solar still (PSSS) can receive solar input radiation from all four directions. In this research, the top layer of conventional pyramid shape solar still (CPSSS) is covered with air‐packed cover and analysed the effect in the modified still after air packed in between the two glasses, finally, that result is compared with the CPSSS. The air inside the two glasses will be receiving maximum radiation and retain in it. It can be used as top side insulation and which can ensure the maximum insulation for heat energy inside the PSSS. The CPSSS and air‐packed pyramid shape solar still (APPSSS) were fabricated and experimented. The experiments were conducted at an ambient condition of the Chennai, Tamil Nadu (12.9416°N, 80.2362°E). The CPSSS gives good yield at evening when an increase in wind velocity. The APPSSS gives a lower performance as compared to the CPSSS due to the air‐packed cover.     

Fischer–Tropsch Synthesis: Studies on the Effect of Support Doping with Si,Mn and Cr on the Selectivity to Alcohols in Ceria Supported Cobalt Catalysts

Mn and Cr doped CeSi mixed oxides were used as supports for Co and tested for CO hydrogenation. Co/CeSi was found to be more active and significantly more selective to n-alcohols/olefins. An increasing selectivity to n-alcohols and decreasing selectivity to olefins as a function of time on stream was also observed, suggesting a trade-off between those two products. Addition of Mn led to similar behavior, although at slightly lower conversions. Addition of Cr, however, considerably suppressed n-alcohol formation, while it kept selectivities to olefins within a 20–30 % range over more than 250 h of testing, indicating either higher alcohol dehydration activity, or that the presence of Cr ions lowered the hydrogenating activity of Co. The present work indicates that enhanced contact area between Co and the reducible support is likely a key factor for enhancing selectivity to alcohols.     

Investigation of structural,optical, and thermal properties of 2-amino-4,6-dimethylpyrimidine benzoic acid (2APB) single crystal for non-linear optical (NLO) applications

The 2-amino-4,6-dimethylpyrimidine benzoic acid (2APB) single crystal has been successfully grown by the slow evaporation method by using water as a solvent. The single-crystal X-Ray diffraction (SXRD) analysis gives knowledge about the structure and morphology of the 2APB crystal. The Powder X-ray Diffraction (PXRD) pattern of grinded 2APB crystal was compared with standard CIF file and the peaks were indexed with their corresponding miller indices (hkl). The crystalline perfection of the grown 2APB single crystal was analysed using high-resolution X-ray diffraction (HR-XRD) measurement. The various functional groups and their vibrational assignments were studied using the Fourier-transform infrared (FTIR) spectrum analysis. The 2APB crystal has a lower cut-off wavelength of 325 nm, which is evident from the UV–visible–NIR analysis. The defects and etch pit density of 2APB crystal were examined using chemical etching studies. The 2APB crystal was thermally stable up to 140 °C, which was evident from the thermogravimetric (TG) and differential thermal analysis (DTA). The photoconductivity analysis was carried out to calculate the photo and dark current values. The laser damage threshold (LDT) value was determined using a 532 nm Nd:YAG laser in single shot mode. The third-order non-linear optical (NLO) susceptibility (χ⁽³⁾) value was calculated from Z-scan technique, which involves open and closed aperture measurements.

     

Year around distilled water production,energy, and economic analysis of solar stills—A comparative study

In this paper, a year around energy efficiency (EnE) and economic analysis of single slope solar still (SSSS), the single slope solar still with glass cooling (SSSSGC), the single slope solar still with basin heating (SSSSBH), and the single slope solar still with glass cooling and basin heating (SSSSGCBH) was carried out based on the distilled water production. The annual yield production from the SSSS, SSSSGC, SSSSBH, and SSSSGCBH were 476.16, 637.44, 970.24, and 1167.36 kg, respectively. The yearly yield produced from the SSSSBH and SSSSGCBH was increased by 50.92% and 59.21%, respectively, as compared with the SSSS. Moreover, the annual EnE of the SSSSGCBH was 28.75%. However, the EnE of the SSSS was 11.73%. Also, freshwater making cost is found to be 18.9, 24.9, 37.9, and 45.6 Rs/day for the SSSS, SSSSGC, SSSSBH, and SSSSGCBH, respectively, if the buying cost of freshwater is Rs 10.