Deep Learning for Software Defect Prediction: An LSTM-based Approach

Software defect prediction is an important aspect of software development, as it helps developers and organizations to identify and resolve bugs in the software before they become major issues. In this paper, we explore the use of machine learning algorithms for software defect prediction. We discuss the different types of machine learning algorithms that have been used for software defect prediction and their advantages and disadvantages. We also provide a comprehensive review of recent studies that have used machine learning algorithms for software defect prediction. The paper concludes with a discussion of the challenges and opportunities in using machine learning algorithms for software defect prediction and the future directions of research in this field. This paper surveys the existing literature on software defect prediction, focusing specifically on deep learning techniques. Compared to existing surveys on the topic, this paper offers a more in-depth analysis of the strengths and weaknesses of deep learning approaches for software defect prediction. It explores the use of LSTMs for this task, which have not been extensively studied in previous surveys. Additionally, this paper provides a comprehensive review of recent research in the field, highlighting the most promising deep learning models and techniques for software defect prediction. The results of this survey demonstrate that LSTM-based deep learning models can outperform traditional machine learning approaches and achieve state-of-the-art results in software defect prediction. Furthermore, this paper provides insights into the challenges and limitations of deep learning approaches for software defect prediction, highlighting areas for future research and improvement. Overall, this paper offers a valuable resource for researchers and practitioners interested in using deep learning techniques for software defect prediction.

Fabrication of nanoelectronic devices for applications in flexible and wearable electronics

Conventional electronic devices fabricated on rigid crystalline semiconductors wafers have evolved with the motivation to miniaturize thereby realizing faster, smaller and densely integrated devices. A parallel research that is rapidly evolving for future electronics is to integrate the property of flexibility and stretchablity to develop human friendly devices. There have been number of reports on fabricating sensors and electronic devices on stretchable, bendable and soft materials like polyimide, polyurethane sponge, natural rubber, cellulose paper, tissue paper etc. using various nanomaterials such as 2D materials, metal oxides, carbon nanomaterials and metal nanowires. These nanomaterials possess excellent electronic, thermal, mechanical and optical properties making them suitable for fabrication of broadband photodetectors, temperature, pressure and strain sensors which find applications in the field of optoelectronics, sensors, medical, security and surveillance. While most reports on photodetectors focus on improving the responsivity in one region of electromagnetic spectrum by fabricating materials hybrids, the main issue still remains unaddressed which is the inability to absorb wide range of electromagnetic spectrum. Most photodetectors comprise of p-n heterojunction, where one of the material is responsible for absorbance, having metal contacts on p and n type allows for effective separation of photogenerated carriers. But for a broadband photodetector, both the materials of the heterojunction should participate in the absorbance. In such a case, metal contacts on p and n type will trap either the photogenerated electrons or hole which leads to the failure of the device. The first part of the thesis focus on the development of flexible broadband photodetectors based on MoS2 hybrid. Next chapter of the thesis deals with the improvement of responsivity by fabrication of solution processed heterojunction and piezotronic diode on flexible paper substrate for enhanced broadband photodetector and active analog frequency modulator by application of external mechanical strain. The fabricated MoS2 based heterojunctions was further utilized at circuit level for frequency modulation. The external applied strain not only modulates the transport properties at the junction which not only enhances the broadband photoresponse but also changes the depletion capacitance of junction under reverse bias thereby utilizing it for frequency modulation at circuit level. The next part of thesis deals with fabrication of new type of electronic, skin-like pressure and strain sensor on flexible, bio-degradable pencil eraser substrate that can detect pressure variations and both tensile and compressive strain and has been fabricated by a solvent-free, low-cost and energy efficient process. Eraser, serves as a substrate for strain sensing as well as acts as a dielectric for capacitive pressure sensing, thereby eliminating the steps of dielectric deposition which is crucial in capacitive based pressure sensors. Detailed mechanism studies in terms of tunneling effect is presented to understand the proposed phenomena. As a proof of concept, an array of 6 x 8 devices were fabricated and pressure mapping of alphabets “I”, “T” and “H” were plotted which were highly consistent with the shape and weight distribution of the object

XAI Applications in Medical Imaging: A Survey of Methods and Challenges

Medical imaging plays a pivotal role in modern healthcare, aiding in the diagnosis, monitoring, and treatment of various medical conditions. With the advent of Artificial Intelligence (AI), medical imaging has witnessed remarkable advancements, promising more accurate and efficient analysis. However, the black-box nature of many AI models used in medical imaging has raised concerns regarding their interpretability and trustworthiness. In response to these challenges, Explainable AI (XAI) has emerged as a critical field, aiming to provide transparent and interpretable solutions for medical image analysis. This survey paper comprehensively explores the methods and challenges associated with XAI applications in medical imaging. The survey begins with an introduction to the significance of XAI in medical imaging, emphasizing the need for transparent and interpretable AI solutions in healthcare. We delve into the background of medical imaging in healthcare and discuss the increasing role of AI in this domain. The paper then presents a detailed survey of various XAI techniques, ranging from interpretable machine learning models to deep learning approaches with built-in interpretability and post hoc interpretation methods. Furthermore, the survey outlines a wide range of applications where XAI is making a substantial impact, including disease diagnosis and detection, medical image segmentation, radiology reports, surgical planning, and telemedicine. Real-world case studies illustrate successful applications of XAI in medical imaging. The challenges associated with implementing XAI in medical imaging are thoroughly examined, addressing issues related to data quality, ethics, regulation, clinical integration, model robustness, and human-AI interaction. The survey concludes by discussing emerging trends and future directions in the field, highlighting the ongoing efforts to enhance XAI methods for medical imaging and the critical role XAI will play in the future of healthcare. This survey paper serves as a comprehensive resource for researchers, clinicians, and policymakers interested in the integration of Explainable AI into medical imaging, providing insights into the latest methods, successful applications, and the challenges that lie ahead

Solvent-free fabrication of multi-walled carbon nanotube based flexible pressure sensors for ultra-sensitive touch pad and electronic skin applications

This paper reports the solvent free, low cost fabrication and clean process of an ultrasensitive touch pad by sandwiching multi walled carbon nanotubes (MWCNTs) between a bottom polyimide (PI) substrate and top cellulose paper using rolling pins and pre-compaction mechanical pressing techniques. The sensing mechanism is due to pressing force dependent contact of MWCNTs between the top cellulose paper and bottom PI. The recently developed solvent free pencil on paper approach for fabricating pressure sensors has the drawback of low throughput which hinders its applicability in commercial domain. Here in this work, the entire fabrication process is scalable and could be integrated to a large area for mapping spatial pressure distribution. The as fabricated sensor has sensitivity of 0.549 kPa(-1), response time of <32 ms and low power consumption of <1.9 mW. Apart from measuring pressing, tensile and compressive forces, the sensor can identify acoustic vibrations from a loud speaker. The fabricated pressure sensor was further applied as artificial electronic skin with 3 x 4 pixel array wherein it was observed that measured spatial distribution was consistent with shape and location of the object. This proposed flexible touch pad fabricated by a low energy fabrication and clean process technology paves way for future wearable electronics such as flexible touch pads and human-machine interfaces

Eraser-based eco-friendly fabrication of a skin-like large-area matrix of flexible carbon nanotube strain and pressure sensors

This paper reports a new type of electronic, recoverable skin-like pressure and strain sensor, produced on a flexible, biodegradable pencil-eraser substrate and fabricated using a solvent-free, low-cost and energy efficient process. Multi-walled carbon nanotube (MWCNT) film, the strain sensing element, was patterned on pencil eraser with a rolling pin and a pre-compaction mechanical press. This induces high interfacial bonding between the MWCNTs and the eraser substrate, which enables the sensor to achieve recoverability under ambient conditions. The eraser serves as a substrate for strain sensing, as well as acting as a dielectric for capacitive pressure sensing, thereby eliminating the dielectric deposition step, which is crucial in capacitive-based pressure sensors. The strain sensing transduction mechanism is attributed to the tunneling effect, caused by the elastic behavior of the MWCNTs and the strong mechanical interlock between MWCNTs and the eraser substrate, which restricts slippage of MWCNTs on the eraser thereby minimizing hysteresis. The gauge factor of the strain sensor was calculated to be 2.4, which is comparable to and even better than most of the strain and pressure sensors fabricated with more complex designs and architectures. The sensitivity of the capacitive pressure sensor was found to be 0.135 MPa-1.To demonstrate the applicability of the sensor as artificial electronic skin, the sensor was assembled on various parts of the human body and corresponding movements and touch sensation were monitored. The entire fabrication process is scalable and can be integrated into large areas to map spatial pressure distributions. This low-cost, easily scalable MWCNT pin-rolled eraser-based pressure and strain sensor has huge potential in applications such as artificial e-skin in flexible electronics and medical diagnostics, in particular in surgery as it provides high spatial resolution without a complex nanostructure architecture

Fabrication of a solution-processed, highly flexible few layer MoS2 (n)–CuO (p) piezotronic diode on a paper substrate for an active analog frequency modulator and enhanced broadband photodetector

In this work, we demonstrate for the first time, a solution-processed MoS2 (n)–CuO (p) piezotronic diode on a flexible paper substrate for an enhanced broadband photodetector and active analog frequency modulator by application of external mechanical strain. There are no reports on solution-processed large area fabrication of MoS2-based heterojunctions wherein the external mechanical strain modulates the transport properties at the device level which can be further utilized at the circuit level for frequency modulation. When external strain is applied, because of the non-centrosymmetric structure of MoS2, the piezopotential induced adjusts the band structure at the junction and broadens the depletion region, which decreases the depletion capacitance of the diode. The widening of the depletion region improves the separation of photo-generated carriers and enhances the performance of the diode under both visible and NIR illumination. The fabricated piezotronic diode exhibited higher responsivity towards visible light illumination when compared to NIR illumination. The responsivity of the fabricated piezotronic diode increased by 69.7% under 2% strain. Such a versatile technique for fabrication of a diode and its utilization at both the device and circuit levels is a major step ahead in flexible and wearable electronics with applications ranging from digital, to analog, and optoelectronics