Abstract: Methods and systems for improving retrieval accuracy in a Retrieval Augmented Generation (RAG) framework are disclosed. Input documents (102) are analyzed using a Small Language Model (SLM) to identify document types and extract content using type-specific methods. An adaptive chunking process generates chunked content based on variables including use case type, speed, cost, latency requirements, and Large Language Model (LLM) context window size. The chunked content undergoes tokenization using strategies based on accuracy and vocabulary requirements. An embedding model is selected based on user requirements, and quantization policies are applied to generate optimized vector representations. Document portions are retrieved using a multi-step strategy comprising hybrid search, meta filters, multi-query retrieval, and hypothetical document embeddings.

Abstract: A method and system for detecting anomalies in a structured dataset. An input interface receive an input dataset including a plurality of features for each data point across columns of the input dataset. The input dataset may include either labelled data or unlabeled data. A combining module combines the plurality of features to create a single column that contains a combined string of respective features of that data point. A transformation module transforms each combined string in the single column to an embedding vector by employing contextualized vector technique. The embedding captures interactions among the plurality of features in the respective data point. Anomaly detection module detects anomalies in the structured dataset by applying at least one of a supervised approach or an unsupervised approach to the embedding vector in the vector space.

Abstract: The present disclosure relates to a method of controlling an energy supply system comprising a central power grid (40) and at least one local power grid configured to supply at least one entity (31a) with energy, and a device (30) performing the method. In an aspect, a method of controlling an energy supply system comprising a central power grid (40) and at least one local power grid configured to supply at least one entity (31a) with energy is provided.

Abstract: A method for predicting cell accessibility issues for a mobile network. The method includes receiving a set of metrics from the mobile network, processing a set of key performance indicators (KPIs) derived from the set of metrics in an ensemble machine learning model, the ensemble machine learning model including an RRC model, an RACH model, an ERAB model, and an S1 signaling model to generate at least one cell accessibility degradation prediction and a confidence score, and applying a root cause mapping to the at least one cell accessibility degradation prediction and the confidence score to identify at least one recommended action to correct a correlated cell accessibility issue.

Abstract: A method for predicting cell accessibility issues for a mobile network. The method includes receiving a set of metrics from the mobile network, processing a set of key performance indicators (KPIs) derived from the set of metrics in an ensemble machine learning model, the ensemble machine learning model including an RRC model, an RACH model, an ERAB model, and an S1 signaling model to generate at least one cell accessibility degradation prediction and a confidence score, and applying a root cause mapping to the at least one cell accessibility degradation prediction and the confidence score to identify at least one recommended action to correct a correlated cell accessibility issue.

Abstract: Applications in a data center can be consolidated by identifying different combinations of software executing on hardware. The software can include a set of applications that execute upon a set of servers. The different combinations can have different arrangements of applications running on different ones of the servers. For each of the different combinations, a licensing cost, an operating cost, and a total cost can be calculated. The total cost of operation for each of the configurations can be calculated by summing the licensing costs, the operating costs adjusted for the cost savings for complementary workload patterns, and migration costs for adjusting a current configuration of the applications and servers to arrive at the configuration. The total cost results per configuration can be reported to a user for at least a set of the configurations.

Abstract: Methods and systems for image migration. There are received, at an image reader, files of at least one image of at least one virtual machine from a first environment. Points of variability are identified within the files, with respect to preparation for functioning in a second environment. Each point of variability is associated with corresponding metadata, and each point of variability is stored with its corresponding metadata. The at least one image is reconfigured to function in the second environment, such reconfiguring comprising adjusting the points of variability via using the metadata. The reconfigured image is deployed to the second environment.

Abstract: A virtual machine placement framework is described to enable a data center operator to develop a placement scheme to satisfy its particular constraints while simultaneously optimizing resource utilization. To generate a placement solution, the virtual machine placement problem is first characterized as a “bin packing” problem. The framework provides simple interface tools and processing modules, and a pluggable architecture for receiving placement algorithms. To generate a solution, an administrator creates an XML representation that abstracts physical entities (e.g., data center, subnet, rack, physical server, and the like) into a hierarchical tree of bins. The administrator also defines a set of “rules” that govern (direct) the placement of the virtual machines by placing constraints on the placement scheme. Using the hierarchical tree and the rules, the framework is executed to generate a placement as a solution to a bin packing problem, preferably on a layer-by-layer basis.

Abstract: Methods and systems for image migration. There are received, at an image reader, files of at least one image of at least one virtual machine from a first environment. Points of variability are identified within the files, with respect to preparation for functioning in a second environment. Each point of variability is associated with corresponding metadata, and each point of variability is stored with its corresponding metadata. The at least one image is reconfigured to function in the second environment, such reconfiguring comprising adjusting the points of variability via using the metadata. The reconfigured image is deployed to the second environment.

Abstract: A virtual machine placement framework is described to enable a data center operator to develop a placement scheme to satisfy its particular constraints while simultaneously optimizing resource utilization. To generate a placement solution, the virtual machine placement problem is first characterized as a “bin packing” problem. The framework provides simple interface tools and processing modules, and a pluggable architecture for receiving placement algorithms. To generate a solution, an administrator creates an XML representation that abstracts physical entities (e.g., data center, subnet, rack, physical server, and the like) into a hierarchical tree of bins. The administrator also defines a set of “rules” that govern (direct) the placement of the virtual machines by placing constraints on the placement scheme. Using the hierarchical tree and the rules, the framework is executed to generate a placement as a solution to a bin packing problem, preferably on a layer-by-layer basis.

Abstract: Applications in a data center can be consolidated by identifying different combinations of software executing on hardware. The software can include a set of applications that execute upon a set of servers. The different combinations can have different arrangements of applications running on different ones of the servers. For each of the different combinations, a licensing cost, an operating cost, and a total cost can be calculated. The total cost of operation for each of the configurations can be calculated by summing the licensing costs, the operating costs adjusted for the cost savings for complementary workload patterns, and migration costs for adjusting a current configuration of the applications and servers to arrive at the configuration. The total cost results per configuration can be reported to a user for at least a set of the configurations.

Abstract: Applications in a data center can be consolidated by identifying different combinations of software executing on hardware. The software can include a set of applications that execute upon a set of servers. The different combinations can have different arrangements of applications running on different ones of the servers. For each of the different combinations, a licensing cost, an operating cost, and a total cost can be calculated. The total cost of operation for each of the configurations can be calculated by summing the licensing costs, the operating costs adjusted for the cost savings for complementary workload patterns, and migration costs for adjusting a current configuration of the applications and servers to arrive at the configuration. The total cost results per configuration can be reported to a user for at least a set of the configurations.