Molecular Dynamics Studies on the Prediction of Interface Strength of Cu(Metal)-Cu50Zr50(Metallic glass) Metal Matrix Composites

The aim of this investigation is to predict the interface strength of metal (Cu-matrix)–metallic glass (Cu50Zr50-reinforcement) composites via molecular dynamics (MD) simulations. Simulation box size of 100 Å (x) × 110 Å (y) × 50 Å (z) is used for the investigation. At first Cu–Cu50Zr50 crystalline model is constructed with the bottom layer (Cu) of 50 Å and the top layer of 60 Å (Cu50Zr50) in height along y–direction. Thereafter, Cu50Zr50 metallic glass is obtained by rapid cooling at a cooling rate of 4 × 1012 s-1. The interface model is then equilibrated at 300 K for 500 ps to relieve the stresses. EAM (Embedded Atom Method) potential is used for modelling the interaction between Cu–Cu and Cu–Zr atoms. The fracture strength of Cu–Cu50Zr50 model interface is determined by tensile (mode–I) and shear (mode–II) loading. Periodic boundary conditions are applied along z–direction for shear while along x– and z–directions for tensile tests. A timestep of 0.002 ps is used for all the simulations. Tensile and shear tests are carried out at varying strain rates (108 s-1, 109 s-1 and 1010 s-1) and temperatures (100K, 300 K and 500 K). The interface model is allowed for full separation under both the deformation modes. It is found that tensile as well as shear strength decrease with increase in temperature and increase with strain rate, as expected. Further, the maximum stress in shear is smaller than that in tensile at all strain rates and temperatures. Critical observations of the obtained results on Cu–Cu50Zr50 composites indicate better shear strengths as compared to the results of metal (matrix)-ceramic (reinforcement) composites available in the literature. Hence it can be concluded that metallic glass acts as a better reinforcement material than the popular ceramic reinforcements

Mitigation of glass weave skew using a combination of low DK spread glass, multi-ply dielectric and routing direction

As the data rates increase into the multi-gigabit range, the bit periods fall in the range of few tens of picoseconds. At above few Gbps, it becomes very important to reduce skew between differential pairs as it can adversely impact the signal eye and thereby increase bit error rate. The goal of this study is to mitigate the skew contributed by woven glass fabric of PCB dielectrics. The glass weave skew between differential pairs in a PCB occurs due to the difference in dielectric constants (DK) of glass and resin. This thesis aims to mitigate the skew by reducing the effective DK difference experienced by the traces of a differential pair. Several strategies like using low DK glass, spread glass styles with less gaps in the glass fabric, 1-ply and 2-ply dielectrics, routing the traces in warp and fill directions are studied through measurements taken on several test vehicles. Since the relative location of traces with respect to glass bundles cannot be controlled, it is highly unlikely to capture the worst case skew from measurements on few test vehicles. Full wave simulation model of laminate with fiber weave is employed. A systematic approach using measurements and simulations to mitigate the differential pair skew is presented --Abstract, page iii

GR-334 Comparative Evaluation of EMBED Dataset for Mammogram Classification Using Deep Learning Techniques

Breast cancer is a global health concern for women. The detection of breast cancer in its early stages is crucial, and screening mammography serves as a vital leading-edge tool for achieving this goal. In this study, we evaluated the performance of centralized versions of Resnet 50v2 and Resnet 152v2 models for classification of mammograms using different datasets, which were divided by location number extracted from the EMBED dataset. The datasets were preprocessed and used various techniques to improve the performance of the models. The models are trained and evaluated using metrics such as accuracy, area under the curve (AUC), F1 score, precision, and recall. The results indicate good performance for both models, with the Resnet 152v2 model slightly outperforming the Resnet 50v2 model in terms of AUC score. Our findings demonstrate the potential of machine learning algorithms in breast cancer screening, with our model achieving an AUC score of 0.83

Verification of Well-formedness in Message-Passing Asynchronous Systems modeled as Communicating Finite-State Machines

Asynchronous systems with message-passing communication paradigm have made major inroads in many application domains in service-oriented computing, secure and safe operating systems and in general, distributed systems. Asynchrony and concurrency in these systems bring in new challenges in verification of correctness properties. In particular, the high-level behavior of message-passing asynchronous systems is modeled as communicating finite-state machines (CFSMs) with unbounded communication buffers/channels. It has been proven that, in general, state-space exploration based automatic verification of CFSMs is undecidable - specifically, reachability and boundedness problems for CFSMs are undecidable. In this context, we focus on an important path-based property for CFSMs, namely well-formedness - every message sent can be eventually consumed. We show that well-formedness is undecidable as well, and present decidable sub-classes for which verification of well-formedness can be automated. We implemented the algorithm for verifying the well-formedness for the decidable subclass, and present our results using several case studies such as service choreographies and Singularity OS contracts

Building a Competitive and Sustainable Horticulture Business Model for “tHuismerk”

The greenhouse horticulture sector in the Netherlands is experiencing serious competitive issues. A combination of factors such as excess production, insufficient local demand, declining exports and retail price pressure has made it impossible for growers to make any profits. In response to this situation, a group of 10 green house vegetable (tomatoes, cucumbers, eggplants and bell peppers) growers has agreed to join hands and work towards creating a new business model. To formalize this cooperation they have agreed to work on creating a joint brand and named it “tHuismerk” At this stage they need help in developing a differentiating and profitable business model for “tHuismerk”.To assist in this, the authors have developed a theoretical framework and have explained how the components of the theoretical framework can be used to develop an executable business model. The application of this framework is presented in the context of a real case study.Participating students are tasked with developing the business model using this background information and the theoretical framework presented in this paper. Four concrete questions have been provided to provide guidance

Melatih Komunikasi pada Anak Usia Dini dengan Cara Bermain di Tanjung Laidong, Labuhan Batu Utara

It is very important to train communication in children from an early age, when children are lazy and just stay silent it results in reduced communication skills in children, the fact that communication plays an important role in child development, good communication in children comes from activities carried out by children in it through playing but very much in I regret that the world of children's play is so sporadic and even difficult to produce. Making boundaries for children's playgrounds causes them to be more interested in playing indoors by playing with cellphones or watching television sometimes it has a positive impact but it makes children not interested in playing outside such as playing hide and seek, chasing and others. other. This makes children less social with other friends, thereby reducing communication in early childhood. Therefore, communication in early childhood must be trained so that it continues to develop. One way to practice communication is to play with other children, not only that, but also to hinder the development of children

Investigation of Effective Classification Method for Online Health Service Recommendation System

Hospital Recommendation Services have been gaining popularity these days. There are many applications and systems that are recommending hospitals based on the user’s requirements and to meet the patient satisfaction. These applications take the reviews of the patients and the users and based on these reviews, they recommend the hospitals. Also if a person is new to the location that he is currently residing, when the speciality is given as input by him, then these applications recommend the hospitals. But the problem is that everyone is not aware of the medical terms like specialities. For those people, “Health Service Recommendation System” comes handy. “Health Service Recommendation System” is an Android Application for finding hospitals within a specified range of distance and requirements provided by the client using the Naïve Bayes classification algorithm. Naïve Bayes algorithm classifies the speciality and thus helps in achieving the maximum accuracy compared to the other algorithms used. This application is helpful even for the people who are not aware of the specialities of the hospitals