Improving traffic and emergency vehicle clearence at congested intersections using fuzzy inference engine

Traffic signals play an important role in controlling and coordinating the traffic movement in cities especially in urban areas. As the traffic is exponentially increasing in cities and the pre-timed traffic light control is insufficient in effective timing of the traffic lights, it leads to poor traffic clearance and ultimately to heavy traffic congestion at intersections. Even the Emergency vehicles like Ambulance and Fire brigade are struck at such intersections and experience a prolonged waiting time. An adaptive and intelligent approach in design of traffic light signals is desirable and this paper contributes in applying fuzzy logic to control traffic signal of single four-way intersection giving priority to the Emergency vehicle clearance. The proposed control system is composed of two parallel controllers to select the appropriate lane for green signal and also to decide the appropriate green light time as per the real time traffic condition. Performance of the proposed system is evaluated by using simulations and comparing with pre-timed control system in changing traffic flow condition. Simulation results show significant improvement over the pre-timed control in terms of traffic clearance and lowering of Emergency vehicle wait time at the intersection especially when traffic intensity is high

High cardiovascular risks in a North Indian Agarwal community: a case series

Community specific cardiovascular disease risk factor studies may be useful to evaluate genetic versus environmental causes. Agarwal is a high profile business community in India. A family based narrative from this community reveals a high prevalence of cardiovascular diseases- stroke and coronary heart disease. This is associated with high prevalence of multiple cardiovascular risk factors such as central obesity, hypertension, lipid abnormalities and diabetes. Another study in the same community in Jaipur reveals high prevalence of obesity associated with low physical activity and high dietary calorie and fat intake. Lifestyle factors appear to be mediator of the cardiovascular epidemic in this community

Cyberbullying Detection System with Multiple Server Configurations

Due to the proliferation of online networking, friendships and relationships - social communications have reached a whole new level. As a result of this scenario, there is an increasing evidence that social applications are frequently used for bullying. State-of-the-art studies in cyberbullying detection have mainly focused on the content of the conversations while largely ignoring the users involved in cyberbullying. To encounter this problem, we have designed a distributed cyberbullying detection system that will detect bullying messages and drop them before they are sent to the intended receiver. A prototype has been created using the principles of NLP, Machine Learning and Distributed Systems. Preliminary studies conducted with it, indicate a strong promise of our approach

Peer-to-peer support for Matlab-style computing

Peer-to-peer technologies have shown a lot of promise in sharing the remote resources effectively. The resources shared by peers are information, bandwidth, storage space or the computing power. When used properly, they can prove to be very advantageous as they scale well, are dynamic, autonomous, fully distributed and can exploit the heterogeneity of peers effectively. They provide an efficient infrastructure for an application seeking to distribute numerical computation. In this thesis, we investigate the feasibility of using a peer-to-peer infrastructure to distribute the computational load of Matlab and similar applications to achieve performance benefits and scalability. We also develop a proof of concept application to distribute the computation of a Matlab style application

Leveraging Explainable AI to Analyze Researchers' Aspect-Based Sentiment about ChatGPT

The groundbreaking invention of ChatGPT has triggered enormous discussion among users across all fields and domains. Among celebration around its various advantages, questions have been raised with regards to its correctness and ethics of its use. Efforts are already underway towards capturing user sentiments around it. But it begs the question as to how the research community is analyzing ChatGPT with regards to various aspects of its usage. It is this sentiment of the researchers that we analyze in our work. Since Aspect-Based Sentiment Analysis has usually only been applied on a few datasets, it gives limited success and that too only on short text data. We propose a methodology that uses Explainable AI to facilitate such analysis on research data. Our technique presents valuable insights into extending the state of the art of Aspect-Based Sentiment Analysis on newer datasets, where such analysis is not hampered by the length of the text data

Joint Scheduling and Resource Allocation in CDMA Systems

Transactions on Information Theory. In this paper, the scheduling and resource allocation problem for the downlink in a CDMA-based wireless network is considered. The problem is to select a subset of the users for transmission and for each of the users selected, to choose the modulation and coding scheme, transmission power, and number of codes used. We refer to this combination as the physical layer operating point (PLOP). Each PLOP consumes different amounts of code and power resources. The resource allocation task is to pick the “optimal ” PLOP taking into account both system-wide and individual user resource constraints that can arise in a practical system. This problem is tackled as part of a utility maximization problem framed in earlier papers that includes both scheduling and resource allocation. In this setting, the problem reduces to maximizing the weighted throughput over the state-dependent downlink capacity region while taking into account the system-wide and individual user constraints. This problem is studied for the downlink of a Gaussian broadcast channel with orthogonal CDMA transmissions. This results in a tractable convex optimization problem. A dual formulation is used to obtain several key structural properties. By exploiting this structure, algorithms are developed to find the optimal solution with geometric convergence. Index Terms Cellular network, channel-aware scheduling, code division multiple access (CDMA), convex optimization, resource allocation, utility maximization. I

MPEG-7 Based Image Retrieval on the World Wide Web

Due to the rapid growth of the number of digital media elements like image, video, audio, graphics on Internet, there is an increasing demand for effective search and retrieval techniques. Recently, many search engines have made image search as an option like Google, AlltheWeb, AltaVista, Freenet. In addition to this, Ditto, Picsearch, can search only the images on Internet. There are also other domain specific search engines available for graphics and clip art, audio, video, educational images, artwork, stock photos, science and nature [www.faganfinder.com/img]. These entire search engines are directory based. They crawls the entire Internet and index all the images in certain categories. They do not display the images in any particular order with respect to the time and context. With the availability of MPEG-7, a standard for describing multimedia content, it is now possible to store the images with its metadata in a structured format. This helps in searching and retrieving the images. The MPEG-7 standard uses XML to describe the content of multimedia information objects. These objects will have metadata information in the form of MPEG-7 or any other similar format associated with them. It can be used in different ways to search the objects. In this paper we propose a system, which can do content based image retrieval on the World Wide Web. It displays the result in user-defined order

Industry 4.0 technologies for manufacturing sustainability: A systematic review and future research directions

Recent developments in manufacturing processes and automation have led to the new industrial revolution termed “Industry 4.0”. Industry 4.0 can be considered as a broad domain which includes: data management, manufacturing competitiveness, production processes and efficiency. The term Industry 4.0 includes a variety of key enabling technologies i.e., cyber physical systems, Internet of Things, artificial intelligence, big data analytics and digital twins which can be considered as the major contributors to automated and digital manufacturing environments. Sustainability can be considered as the core of business strategy which is highlighted in the United Nations (UN) Sustainability 2030 agenda and includes smart manufacturing, energy efficient buildings and low-impact industrialization. Industry 4.0 technologies help to achieve sustainability in business practices. However, very limited studies reported about the extensive reviews on these two research areas. This study uses a systematic literature review approach to find out the current research progress and future research potential of Industry 4.0 technologies to achieve manufacturing sustainability. The role and impact of different Industry 4.0 technologies for manufacturing sustainability is discussed in detail. The findings of this study provide new research scopes and future research directions in different research areas of Industry 4.0 which will be valuable for industry and academia in order to achieve manufacturing sustainability with Industry 4.0 technologies

Liposome-Mediated Immunosuppression Plays an Instrumental Role in the Development of “Humanized Mouse” to Study Plasmodium falciparum

The material world has been getting prone toward infectious diseases, and therefore novel strategies should be devised to treat chronic infectious disorders. The translational biomedical research scientists made early attempts to develop mouse-human chimera (humanized mouse) through the reconstitution of immunodeficient mouse with engraftment of human cells and tissues. Although the humanized mouse proved to be an effective tool in understanding various diseases such as human malaria and hepatitis, however, drug administration, retention capacity of the administered drug, toxicity, and ethical constraints are some of the major issues and need to be objectively addressed. The “humanization” of immunodeficient mouse needs pharmacological immunomodulatory reagents to control the excessively recruited cells of monocyte-macrophage lineage. Therefore, administration of liposome loaded with hydrophobic drug (clodronate) to induce selective apoptosis through “suicidal approach” in myeloid cells plays an instrumental role for controlling residual nonadaptive immune response of the host. Liposomes are spherical and hollow—structures consisting of lipid bilayer—and are used for the delivery of drug and vaccine candidates. The surface-engineered liposomes (ligand anchored) are used for targeted and controlled delivery. Clodronate-loaded liposomes play a pivotal role in developing humanized mouse. This mouse holds relevance to study pathophysiology and immunopathology of human malaria parasite, P. falciparum. The liposomal delivery of clodronate administered in immunodeficient mice to modulate their innate immune system is an amenable strategy with the minimal/acceptable range of systemic toxicity