INTERNATIONAL BUSINESS MACHINES CORPORATION patent applications on August 1st, 2024
Patent Applications by INTERNATIONAL BUSINESS MACHINES CORPORATION on August 1st, 2024
INTERNATIONAL BUSINESS MACHINES CORPORATION: 45 patent applications
INTERNATIONAL BUSINESS MACHINES CORPORATION has applied for patents in the areas of B29C64/393 (3), H04L9/40 (3), G06N20/00 (3), G06N5/022 (3), G06N3/08 (3) G06N3/08 (2), H04L63/1425 (2), G06N20/00 (2), G06F9/5027 (2), G06Q30/0206 (1)
With keywords such as: data, storage, based, include, computer, processor, application, further, training, and network in patent application abstracts.
Patent Applications by INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor(s): Jeremy R. Fox of Georgetown TX (US) for international business machines corporation, Randy A. Rendahl of Raleigh NC (US) for international business machines corporation, Mauro Marzorati of Lutz FL (US) for international business machines corporation, Sarbajit K. Rakshit of Kolkata (IN) for international business machines corporation
IPC Code(s): B29C64/393, B29C64/182, B29C64/209
CPC Code(s): B29C64/393
Abstract: according to one embodiment, a method, computer system, and computer program product for 3d printing is provided. the present invention may include arranging and manipulating an array of wheels on a baseplate; analyzing shape and/or dimensions of an object to be 3d printed; determining an arrangement of one or more blocks on which to print the object to be 3d printed based on the analyzing of the shape and/or dimensions of the object to be 3d printed; positioning, using the array of wheels, the one or more blocks into the determined arrangement; and printing the object to be 3d printed onto the one or more arranged blocks.
Inventor(s): Stephen W. Bedell of Wappingers Falls NY (US) for international business machines corporation, Patryk Gumann of Tarrytown NY (US) for international business machines corporation, William Thomas Spratt of Croton-on-Hudson NY (US) for international business machines corporation, David Zarsky of Bethlehem PA (US) for international business machines corporation, Gilbert Bauer of Peekskill NY (US) for international business machines corporation
IPC Code(s): F17C3/08
CPC Code(s): F17C3/085
Abstract: systems and techniques that facilitate scalable thermal energy recycling for cryogenic systems are provided. in various embodiments, a system can comprise at least one cryostat. in various aspects, the system can further comprise a thermal battery coupled to the at least one cryostat by a thermal exchange system. in various instances, the thermal battery can be configured to store thermal energy extracted from the at least one cryostat or to supply thermal energy to the at least one cryostat.
Inventor(s): Fearghal O'Donncha of Aran Islands (IE) for international business machines corporation, Andrew James Stanford-Clark of Hursley Park (GB) for international business machines corporation, Adam James Thompson of Ruderting (DE) for international business machines corporation, RICARDO MARTINHO of Lisbon (PT) for international business machines corporation, Moritz Johannes Stäbler of Koln (DE) for international business machines corporation, Jonathan Wright of New York NY (US) for international business machines corporation
IPC Code(s): G01N33/00
CPC Code(s): G01N33/004
Abstract: a method for quantifying oceanic carbon dioxide (co) sequestration is provided. the method includes obtaining a plurality of oceanic spatiotemporal carbon dioxide (co) measurements. a plurality of spatiotemporal chlorophyll a (chl-a) and a plurality of oceanic temperature measurements are obtained. the obtained plurality of oceanic spatiotemporal comeasurements is mapped to the obtained plurality of spatiotemporal chl-a and the plurality of oceanic temperature measurements in a multidimensional grid. at least one a priori oceanic spatiotemporal coestimate is generated based on the multidimensional grid.
Inventor(s): Roderick Guy Charles Moore of Bournemouth (GB) for international business machines corporation, Ben Sasson of North Baddesley (GB) for international business machines corporation, Lee Jason Sanders of Chichester (GB) for international business machines corporation, Paul Nicholas Cashman of Alton (GB) for international business machines corporation
IPC Code(s): G06F3/06
CPC Code(s): G06F3/0604
Abstract: a system for managing a storage array in a storage system may include an analysis component for analyzing a set of compression ratios used for a set of storage blocks written on a first storage device and a second storage device to determine a pattern. the system may include a determination component for determining, responsive to the pattern, a first compression ratio and a second compression ratio; the first compression ratio may be different from the second compression ratio. the system may include a data read/write component for writing a storage block to the first storage device with the first compression ratio and writing the storage block to the second storage device with the second compression ratio.
Inventor(s): Akshar Kaul of Bengaluru (IN) for international business machines corporation, Himanshu Gupta of Vasant Kunj (IN) for international business machines corporation, Sameep Mehta of Bengaluru (IN) for international business machines corporation, Srikanth Govindaraj Tamilselvam of Chennai (IN) for international business machines corporation, Amith Singhee of Bengaluru (IN) for international business machines corporation, Vaibhav Sudhakar Dantale of Bibwewadi (IN) for international business machines corporation, Ravi Vishnu Israni of Mumbai (IN) for international business machines corporation
IPC Code(s): G06F8/30, G06F8/65
CPC Code(s): G06F8/30
Abstract: a computer implemented method creates microservices for an application. a number of processor units clusters programs and data structures for the application using runtime metadata to form groups of the programs and data structures. the runtime metadata is obtained from running the application. the number of processor units creates a design for the microservices for the application using the groups of the programs and the data structures.
Inventor(s): Neeraj Kumar Kashyap of Bangalore (IN) for international business machines corporation, Ambika Nair of Bangalore (IN) for international business machines corporation, Mayank Singh Sachan of Hyderabad (IN) for international business machines corporation, Sandip Amin of Austin TX (US) for international business machines corporation
IPC Code(s): G06F8/61
CPC Code(s): G06F8/61
Abstract: an example operation may include one or more of receiving, via an application programming interface (api) of a cluster, a persistent volume claim (pvc) with a specification of a software application, identifying a namespace based on a namespace attribute of the pvc, identifying a storage class which is declared as a default storage class for the identified namespace based on the one or more attributes within the pvc and injecting storage criteria of the default storage class into the specification of the software application, and deploying the software application via a node within the identified namespace according to the predefined storage attributes of the default storage class injected into the specification of the software application.
Inventor(s): Motohiro Kawahito of Sagamihara-shi (JP) for international business machines corporation
IPC Code(s): G06F9/38, G06F9/30
CPC Code(s): G06F9/3867
Abstract: a computer-implemented method, system and computer program product for effectively searching for values in a multi-byte array of elements using an n-byte search instruction. multiple values to be searched in an n-byte array of elements in a loop are received. the loop is optimized by searching the received search values at the starting address of the n-byte array of elements using the n-byte search instruction. a successful search is performed if the received return address points to an address found in the lowest n-bytes of the n-byte array of elements and an element of the address corresponds to a search value. otherwise, a subsequent search for the search values at the address of the next element in the n-byte array of elements is performed if there are additional elements in the n-byte array of elements to be searched.
Inventor(s): Hemant Kumar Sivaswamy of Pune (IN) for international business machines corporation, Smitkumar Narotambhai Marvaniya of Bangalore (IN) for international business machines corporation, Jolly Dominic of Bangalore (IN) for international business machines corporation, Venkata Vara Prasad Karri of Visakhapatnam (IN) for international business machines corporation
IPC Code(s): G06F9/50
CPC Code(s): G06F9/5027
Abstract: disclosed embodiments provide techniques for analyzing a semantic priority of an activity utilizing computing resources, and provides mitigation actions to resolve resource shortages in real-time. the computing resources can include network bandwidth usage, as well as processing cycles, memory usage, and/or other shared computing resources. disclosed embodiments perform a semantic priority analysis of user activities. the semantic priority analysis can include utilizing natural language processing (nlp), analysis of a user calendar, and/or additional application data to infer a semantic priority. when computing resources such as network bandwidth exceed a predetermined level, then a mitigation action is executed, enabling the computing resources to be reduced while still allowing the higher priority activities (e.g., work and school) to continue.
Inventor(s): Mayank Sharma of Bengaluru (IN) for international business machines corporation, Aditi Bhattacharya of Kolkata (IN) for international business machines corporation
IPC Code(s): G06F9/50
CPC Code(s): G06F9/5027
Abstract: a computer implemented method determines resource affinity for an application is provided. a number of processor units determine connections in affinity data for the workloads for an application. the number of processor units assign weights to the connections based on a number of hops for the connections. the weights indicate the affinity to components related to the set of workloads.
Inventor(s): Imran Imtiaz of Manchester (GB) for international business machines corporation, Anuj Chandra of Pune (IN) for international business machines corporation, Miles Mulholland of Eastleigh (GB) for international business machines corporation
IPC Code(s): G06F11/14, G06F21/60
CPC Code(s): G06F11/1453
Abstract: a method, system, computer program product and computer program for managing a storage system, comprising a primary system and a backup system, wherein the backup system is in a copy relationship with the primary system, comprising: in response to a write operation, the write operation comprising first data: calculating a cryptographic value for the first data; scanning a first directory to identify an entry corresponding to the cryptographic value to determine a first set of addresses associated with the write operation; transmitting the first set of addresses to the backup system; and updating the first directory with a first entry for the write operation, the first entry comprising a pointer to the first set of addresses; updating a second directory with a second entry for the write operation, the second entry comprising a pointer to a second set of addresses corresponding to the first set of addresses.
Inventor(s): Daniel Jakub Ryszka of Kraków (PL) for international business machines corporation, Lukasz G. Cmielowski of Kraków (PL) for international business machines corporation, Jan Soltysik of Cracow (PL) for international business machines corporation, Szymon Kucharczyk of Cracow (PL) for international business machines corporation
IPC Code(s): G06F11/36
CPC Code(s): G06F11/3684
Abstract: a method for generating tests of a machine learning (ml) engine includes determining a feature space of the set of configuration parameters of at least part of initial test cases of the ml engine. one or more areas of low coverage may be identified in the feature space. a configuration of a new test case may be defined such that the new test case covers a low coverage area of the feature space. the new test case may be provided for testing a performance of the ml engine to find a ml model using an input dataset according to the configuration of the new test case.
Inventor(s): Roman Alexander PLETKA of Uster (CH) for international business machines corporation, Andrew D. WALLS of San Jose CA (US) for international business machines corporation, Nikolaos PAPANDREOU of Thalwil (CH) for international business machines corporation, Radu Ioan STOICA of Zurich (CH) for international business machines corporation, Timothy J. FISHER of Cypress TX (US) for international business machines corporation, Aaron Daniel FRY of Richmond TX (US) for international business machines corporation, Charalampos POZIDIS of Thalwil (CH) for international business machines corporation, Nikolas IOANNOU of Zurich (CH) for international business machines corporation
IPC Code(s): G06F12/02, G06F3/06
CPC Code(s): G06F12/0246
Abstract: a non-volatile memory includes physical blocks each including a respective plurality of cells, where each cell is capable of storing multiple bits of data. a controller maintains dynamically resizable pools of physical blocks, including at least a low-density pool in which cells are configured to store fewer bits and a high-density pool in which cells are configured to store more bits. the controller determines whether total utilization of physical blocks is less than a low-density pool utilization threshold above which the high-density pool of physical blocks is utilized for storing host write data and additionally identifies cold in-use logical block address (lba) regions having low total access frequencies. based on determining the total utilization of physical blocks is less than the low-density pool utilization threshold, the controller performs data placement of data from the cold in-use lba regions in blocks of the high-density pool.
Inventor(s): Lee Jason Sanders of Chichester (GB) for international business machines corporation, Ben Sasson of North Baddesley (GB) for international business machines corporation, Roderick Guy Charles Moore of Bournemouth (GB) for international business machines corporation, Paul Nicholas Cashman of Alton (GB) for international business machines corporation
IPC Code(s): G06F12/0802, G06F12/121
CPC Code(s): G06F12/0802
Abstract: a method, system, computer program product and computer program for managing a storage system, the storage system comprising a first storage device, a second storage device, a source storage device, a target storage device, and a cache, the method comprising: receiving a first host access request for a data block on the first storage device; receiving a mapping between the source storage device and the target storage device; and in response to the first host access request and the mapping: accessing a corresponding data block on the second storage device; and updating metadata for the cache.
Inventor(s): Ben Sasson of North Baddesley (GB) for international business machines corporation, Roderick Guy Charles Moore of Bournemouth (GB) for international business machines corporation, Lee Jason Sanders of Chichester (GB) for international business machines corporation, Paul Nicholas Cashman of Alton (GB) for international business machines corporation
IPC Code(s): G06F12/0891
CPC Code(s): G06F12/0891
Abstract: a method, system, and computer program product for managing a storage system, comprising: analyzing an access request for a first storage block of the set of storage blocks; in response to the access request comprising a read request: in response to the first storage block residing in the cache: processing the read request from the cache; promoting the first storage block within the cache; and destaging the first storage block to the storage device with the first compression ratio; and in response to the first storage block not residing in the cache: processing the read request from the storage device; and copying the first storage block to the cache; in response to the access request comprising a write request: writing the first storage block to the cache; and destaging the first storage block to the storage device using the first compression ratio.
Inventor(s): Dong CHEN of Beijing (CN) for international business machines corporation, Su LIU of Austin TX (US) for international business machines corporation, Syed I. HAIDERZAIDI of Round Rock TX (US) for international business machines corporation, Yang LIANG of Beijing (CN) for international business machines corporation
IPC Code(s): G06F16/174, G06F9/445
CPC Code(s): G06F16/174
Abstract: provided are techniques for intelligent preemptive processing to avoid data from becoming redundant, obsolete or trivial (rot). an application configuration is monitored to generate application configuration data. application settings are reconfigured based on the application configuration data and based on a risk data list, where the risk data list identifies one or more data files. a data file of the data files in an existing data format is preemptively converted to a new data format based on the reconfigured application settings. an attempt is made to verify the conversion by using the reconfigured application settings. in response to determining that the conversion succeeded and that a request is received from a new application to open the data file, the data file having the new data format is opened. in response to determining that the conversion failed, an error message is sent to request update of server data.
Inventor(s): Jens Müller of Stuttgart (DE) for international business machines corporation, Felix Beier of Haigerloch (DE) for international business machines corporation, Vassil Radkov Dimov of Stuttgart (DE) for international business machines corporation, Eirini Kalogeiton of Stuttgart (DE) for international business machines corporation, Johannes Severin Kern of Boeblingen (DE) for international business machines corporation
IPC Code(s): G06F16/27, G06F16/23
CPC Code(s): G06F16/273
Abstract: the present disclosure relates to a method for enabling access to data of a data analysis system by a set of one or more external database systems. the data analysis system comprises a source database system and target database system. the data analysis system is configured for synchronizing the data in the source database system with the target database system using a primary source transaction log in the source database system. the method comprises: creating a secondary transaction log. data changes applied at the target database system may be received from the target database system. at least one log entry that represents each received data change may be creating in the secondary transaction log. the secondary transaction log may be used by the set of external database systems for applying data changes according to the secondary transaction log, thereby storing the data in the set of external database systems.
Inventor(s): Oliver Suhre of Stuttgart (DE) for international business machines corporation, Thomas Hampp-Bahnmueller of Stuttgart (DE) for international business machines corporation, Peter Gerstl of Holzgerlingen (DE) for international business machines corporation, Yannick Saillet of Stuttgart (DE) for international business machines corporation, Albert Maier of Tuebingen (DE) for international business machines corporation, Michael Baessler of Bempflingen (DE) for international business machines corporation
IPC Code(s): G06F16/36, G06F16/35
CPC Code(s): G06F16/367
Abstract: described are techniques for a re-analysis of assignments of terms to assets. the techniques include detecting a change in a term ontology comprising a plurality of terms, and determining at least one selected from a group consisting of: a domain feature change vector (dfcv) for a domain of the term ontology affected by the change, and a term feature change vector (tfcv) for the term affected by the change. the techniques further include identifying assets for the re-analysis of the assignments of terms, wherein each of the identified assets is associated with an impact score value based on the dfcv and/or the tfcv, and performing the re-analysis of the assignments of terms for the identified assets ordered by the impact score value.
Inventor(s): Si Er Han of Xi'an (CN) for international business machines corporation, Xue Ying Zhang of Xi'an (CN) for international business machines corporation, Jing Xu of Xi'an (CN) for international business machines corporation, Jing James Xu of Xi'an (CN) for international business machines corporation, Xiao Ming Ma of Xi'an (CN) for international business machines corporation, Wen Pei Yu of Xi'an (CN) for international business machines corporation, Jun Wang of Xi'an (CN) for international business machines corporation, Ji Hui Yang of Beijing (CN) for international business machines corporation
IPC Code(s): G06F18/2321, G06F18/241
CPC Code(s): G06F18/2321
Abstract: a computer implemented method manages an ensemble model system to classify records. a number of processor units cluster records into groups of records based on classification predictions generated by base models in the ensemble model system for the records. the number of processor units determines sets of weights for the base models that increase a probability that the base models in the ensemble model system correctly predict the groups of records. each set of weights in the sets of weights is associated with a group of records in the groups of records.
Inventor(s): Fraser Iain MacIntosh of Reading (GB) for international business machines corporation, Rosanna Lickorish of Southampton (GB) for international business machines corporation
IPC Code(s): G06F21/44
CPC Code(s): G06F21/44
Abstract: a method for preventing unauthorized access to tape data is disclosed. in one embodiment, such a method includes maintaining, by a validation server, a lock on a tape drive. the method detects loading, by a requesting server, a tape into the tape drive so that it can be written to. the method confirms, using the validation server, that the requesting server is authorized to write to the tape. the method releases, using the validation server, the lock in response to confirming the authorization of the requesting server. in certain embodiments, the validation server is maintained in a separate environment from the requesting server and/or the validation server is not accessible using the same authentication methods used to access the requesting server. a corresponding system and computer program product are also disclosed.
Inventor(s): Tyler HANSEN of TUCSON AZ (US) for international business machines corporation, James E. BROWN of Sugarhill GA (US) for international business machines corporation, Zachary A. Silverstein of Georgetown TX (US) for international business machines corporation, Logan Bailey of Atlanta GA (US) for international business machines corporation
IPC Code(s): G06F30/12, B29C64/393, B33Y50/02, G06Q30/04
CPC Code(s): G06F30/12
Abstract: described are techniques for infusing environmental data into a computer-aided design (cad) workspace. the techniques include replicating a physical area in a cad workspace, where a static object of the physical area is replicated in the cad workspace with a single set of coordinates, and where a dynamic object of the physical area is replicated in the cad workspace with a range of coordinates representing movement. the techniques further include using the cad workspace to enable relative sizing of a modeled object in the cad workspace, where the relative sizing is relative to the single set of coordinates associated with the static object and the range of coordinates associated with the dynamic object.
Inventor(s): Fang Lu of Billerica MA (US) for international business machines corporation, Martin G. Keen of Cary NC (US) for international business machines corporation, Jeremy R. Fox of Georgetown TX (US) for international business machines corporation, Sarbajit K. Rakshit of Kolkata (IN) for international business machines corporation
IPC Code(s): G06F30/20, B29C64/393, B33Y50/02
CPC Code(s): G06F30/20
Abstract: an embodiment for correcting a problem during an assembly of a 3d object utilizing a 3d printing solution is provided. the embodiment may include receiving a 3d printing blueprint. the embodiment may also include executing a virtual simulation of the assembly of the plurality of 3d blocks. the embodiment may further include in response to determining at least one problem condition arises during the execution of the virtual simulation, identifying the at least one problem condition among the plurality of 3d blocks. the embodiment may also include executing a digital twin simulation of a digital twin model of a plurality of physically assembled 3d blocks. the embodiment may further include generating a correction plan including one or more corrective actions to be performed on the plurality of physically assembled 3d blocks. the embodiment may also include executing the one or more corrective actions.
Inventor(s): Avishai Gretz of Ramat Gan (IL) for international business machines corporation, Assaf Toledo of Ramat Gan (IL) for international business machines corporation, Edo Cohen-Karlik of Tel Aviv-Yafo (IL) for international business machines corporation, Noam Slonim of Jerusalem (IL) for international business machines corporation
IPC Code(s): G06F40/30, G06F40/284
CPC Code(s): G06F40/30
Abstract: automated detection of reasoning in arguments. a training set is generated by: obtaining multiple arguments, each comprising one or more sentences provided as digital text; automatically estimating a probability that each of the arguments includes reasoning, wherein the estimating comprises applying a contextual language model to each of the arguments; automatically labeling as positive examples those of the arguments which have a relatively high probability to include reasoning; and automatically labeling as negative examples those of the arguments which have a relatively low probability to include reasoning. based on the generated training set, a machine learning classifier is automatically trained to estimate a probability that a new argument includes reasoning. the trained machine learning classifier is applied to the new argument, to estimate a probability that the new argument includes reasoning.
Inventor(s): Steven I. Ross of S. Hamilton MA (US) for international business machines corporation, Fernando Carlos Martinez of La Plata (AR) for international business machines corporation, Stephanie Houde of Belmont MA (US) for international business machines corporation
IPC Code(s): G06F40/51, G06F40/284, G06F40/58
CPC Code(s): G06F40/51
Abstract: computer-implemented methods for determining and displaying correspondence between source data and target data. aspects include receiving source tokens associated with source data and target tokens associated with target data, generating source encodings for each source token of the set of source tokens, and generating target encodings for each target token of the set of target tokens. aspects include receiving an indication of a selected source token associated with the source data. aspects further include determining an identified target token from the set of target tokens corresponding to the selected source token by calculating distances between the selected source token and each of the target tokens in the high-dimensional latent space using the source encodings and the target encodings. aspects include displaying a correspondence between a portion of the source data corresponding to the selected source token and a portion of the target data associated with the identified target token.
Inventor(s): Lam Minh Nguyen of Ossining NY (US) for international business machines corporation, Wang Zhang of Cambridge MA (US) for international business machines corporation, Subhro Das of Cambridge MA (US) for international business machines corporation, Alexandre Megretski of Acton MA (US) for international business machines corporation, Luca Daniel of Cambridge MA (US) for international business machines corporation
IPC Code(s): G06N3/0464, G06N3/063
CPC Code(s): G06N3/0464
Abstract: one or more computer processors create a fully convolution network (fcn) comprising a plurality of 1�1 convolutions. the one or more computer processors append linear mapping layer (lm) to created fcn. the one or more computer processors capture a plurality of features utilizing multi-scale dilated convolutional kernels from the linear mapped fcn (lm-fcn). the one or more computer processors apply an average pool layer to the captured plurality of features along a temporal axis of a dilated convolutional kernel within the lm-fcn. the one or more computer processors predict a classification for subsequent time-series data utilizing the pooled plurality of features.
Inventor(s): Omri Soceanu of Haifa (IL) for international business machines corporation, Nir Drucker of Zichron Yaakov (IL) for international business machines corporation, Subhankar Pal of White Plains NY (US) for international business machines corporation, Roman Vaculin of Larchmont NY (US) for international business machines corporation, Kanthi Sarpatwar of Briarcliff Manor NY (US) for international business machines corporation, Alper Buyuktosunoglu of White Plains NY (US) for international business machines corporation, Pradip Bose of Yorktown Heights NY (US) for international business machines corporation, Hayim Shaul of Kfar Saba (IL) for international business machines corporation, Ehud Aharoni of Kfar Saba (IL) for international business machines corporation, James Thomas Rayfield of Ridgefield CT (US) for international business machines corporation
IPC Code(s): G06N3/08, H04L9/00
CPC Code(s): G06N3/08
Abstract: a trained neural network is partitioned into a client-side portion and a server-side portion, the client-side portion comprising a first set of layers of the trained neural network, the server-side portion comprising a second set of layers of the trained neural network, the trained neural network trained using a first set of training data. from a homomorphically encrypted intermediate result input to the server-side portion, a homomorphically encrypted output of the trained neural network is computed, the homomorphically encrypted intermediate result comprising a homomorphically encrypted output computed by the client-side portion.
Inventor(s): Jiaqing Yuan of Raleigh NC (US) for international business machines corporation, Michele Merler of New York NY (US) for international business machines corporation, Mihir Choudhury of Jersey City NJ (US) for international business machines corporation, Venkata Nagaraju Pavuluri of New Rochelle NY (US) for international business machines corporation, Maja Vukovic of New York NY (US) for international business machines corporation
IPC Code(s): G06N3/08, G06N5/022
CPC Code(s): G06N3/08
Abstract: standardizing a mention of an application component in a free-form text describing the technology stack of the application includes extracting the mention and encoding the mention with an embedding space encoder. the encoding creates an encoded representation of the mention in a multi-dimensional embedding space. the embedding space encoder implements a machine learning model trained using contrastive learning. the encoded representation of the mention is mapped to an encoded representation of an entity in the multi-dimensional embedding space, the entity extracted from a knowledge base of computer components. the entity whose encoded representation maps to the encoded representation of the mention can be output responsive to the mapping.
Inventor(s): Pin-Yu Chen of White Plains NY (US) for international business machines corporation, Bo Wu of Cambridge MA (US) for international business machines corporation, Zhenfang Chen of Cambridge MA (US) for international business machines corporation, Chuang Gan of Cambridge MA (US) for international business machines corporation, Huzaifa Arif of Troy NY (US) for international business machines corporation
IPC Code(s): G06N3/098
CPC Code(s): G06N3/098
Abstract: systems and techniques that facilitate reprogrammable federated learning are provided. in various embodiments, a server device can share a pre-trained and frozen neural network with a set of client devices. in various aspects, the server device can orchestrate reprogrammable federated learning of the pre-trained and frozen neural network among the set of client devices. in various instances, the pre-trained and frozen neural network can be positioned between at least one trainable input layer and at least one trainable output layer, and the reprogrammable federated learning can involve the at least one trainable input layer and the at least one trainable output layer, but not the pre-trained and frozen neural network, being locally adjusted by the set of client devices.
Inventor(s): Lam Minh NGUYEN of Ossining NY (US) for international business machines corporation, Huyen Trang Tran of Ithaca NY (US) for international business machines corporation, Kyong Min Yeo of Scarsdale NY (US) for international business machines corporation, Nam H. NGUYEN of Pleasantville NY (US) for international business machines corporation, Dzung Tien PHAN of Pleasantville NY (US) for international business machines corporation, Roman VACULIN of Larchmont NY (US) for international business machines corporation, Jayant R. KALAGNANAM of Briarcliff Manor NY (US) for international business machines corporation
IPC Code(s): G06N5/022
CPC Code(s): G06N5/022
Abstract: a prediction system may identify a first set of features of training data and a second set of features of the training data. the prediction system may train a deep learning model using the training data. training the deep learning model may comprise training a first function to determine a relationship between the first set of features and the second set of features. training the deep learning model may further comprise training a second function to determine a relationship between missing data of a first period of time and complete data of a second period of time that follows the first period of time. the prediction system may generate imputation time series data and forecasted time series data using the trained deep learning model. the imputation time series data is generated based on an imputation task and the forecasted time series data is generated based on a forecasting task.
Inventor(s): Ruchi MAHINDRU of Elmsford NY (US) for international business machines corporation, Amitkumar Manoharrao PARADKAR of Mohegan Lake NY (US) for international business machines corporation
IPC Code(s): G06N20/00
CPC Code(s): G06N20/00
Abstract: a method includes: creating, by a processor set, a training dataset using historic information technology (it) operations data and historic event data of a computer system; training, by the processor set, a machine learning model using the training dataset; receiving, by the processor set, run-time it operations data of the computer system; determining, by the processor set, a golden signal classification, a cause-effect classification, and an impact using the run-time it operations and the machine learning model; and generating, by the processor set, a resolution recommendation based on the golden signal classification, the cause-effect classification, and the impact.
Inventor(s): Dzung Tien PHAN of Pleasantville NY (US) for international business machines corporation, Dhavalkumar C. PATEL of White Plains NY (US) for international business machines corporation
IPC Code(s): G06N20/00
CPC Code(s): G06N20/00
Abstract: a method includes obtaining, by a processor set, labeled training data associated with a system; identifying, by the processor set, a first region and a second region in the labeled training data, wherein the first region is associated with a failure of the system and the second region is exclusive of the first region; and creating, by the processor set, re-labeled training data by altering one or more labels of the labeled training data in the first region based on data in the second region.
Inventor(s): Ketan Gupta of Dera Bassi (IN) for international business machines corporation, Santosh Suryawanshi of Pune (IN) for international business machines corporation, Keerthana Sharath of Bangalore (IN) for international business machines corporation, Karthick Ramanujam of Chennai (IN) for international business machines corporation
IPC Code(s): G06Q10/063, G06N3/042, G06N3/08
CPC Code(s): G06Q10/063
Abstract: a computer-implemented process for automatically generating business rules to be employed by a business rule management system includes the following operations. a plurality of external data sources from which to receive data updates are identified. a data update relevant to a collection of business rules is obtained from at least one of the plurality of external data sources. using a contextual analysis engine, a contextual analysis the data update is performed. using a machine learning engine and based upon the contextual analysis of the data update, an update to the collection of business rules is generated to form an updated collection of business rules. the machine learning engine is modified based upon feedback received on the update to the collection of business rules. the updated collection of business rules is forwarded to the business rule management system.
Inventor(s): Nadiya Kochura of Bolton MA (US) for international business machines corporation, Tiberiu Suto of Franklin NY (US) for international business machines corporation, Hemant Kumar Sivaswamy of Pune (IN) for international business machines corporation, Jeremy R. Fox of Georgetown TX (US) for international business machines corporation
IPC Code(s): G06Q10/083
CPC Code(s): G06Q10/083
Abstract: a method for dynamically rearranging one or more packages for delivery on a delivery vehicle in response to unforeseen changes in a pre-planned delivery route. the method detects, via one or more sensor-enabled shelves in a delivery vehicle, an address and package details of a respective delivery package. the method further integrates the one or more sensor-enabled shelves with a route map that depicts the pre-planned delivery route. the method further assigns new values to the one or more sensor-enabled shelves, in response to a change in the pre-planned delivery route, indicating a new sequence of delivery for each respective delivery package. the method further notifies a delivery person which delivery package is to be delivered at a current stop by illuminating the one or more sensor-enabled shelves containing the respective delivery package.
Inventor(s): Matthew Harrison Tong of Austin TX (US) for international business machines corporation, Apoorva Nitsure of Pittsburgh PA (US) for international business machines corporation, Rajesh Bordawekar of Westchester NY (US) for international business machines corporation
IPC Code(s): G06Q30/0202, G06F16/2455
CPC Code(s): G06Q30/0202
Abstract: tokenized rows of a training portion of a database are selected, each of the selected tokenized rows having a first token value stored in a first column of the database. training row vectors are grouped into clusters. from the clusters, prototypes are generated, each prototype comprising a numerical representation of a cluster. from input tokens, an input row vector is generated, the input row vector comprising a numerical representation of input tokens representing data in an input row of the database, the input row excluded from the training portion, each input token comprising a textual representation of data in a cell of the input row. based on similarity with the input row vector, a prototype is selected. data derived from the selected prototype is inserted into the first column of the input row.
Inventor(s): Rakesh Rameshrao Pimplikar of Bangalore (IN) for international business machines corporation, Ritwik Chaudhuri of Bangalore (IN) for international business machines corporation, Kushal Mukherjee of New Delhi (IN) for international business machines corporation, Gyana Ranjan Parija of Gurgaon (IN) for international business machines corporation, Tatiana De Campovilla Trevisan of Vnhedo (BR) for international business machines corporation, Prasant Parida of New Brunswick NJ (US) for international business machines corporation, Jill Harsh Roberts of Superior CO (US) for international business machines corporation
IPC Code(s): G06N5/022
CPC Code(s): G06Q30/0206
Abstract: a computer-implemented method includes publishing a prediction task and kpi information. the method further includes receiving, at a certain time, a plurality of prediction results, each of the plurality of prediction results being produced by one of a plurality of participants with one of a private model and private data association with the one of the plurality of participants. the method further includes calculating, for each of the plurality of participants, a trade score based on the kpi information and the plurality of prediction results for each of the plurality of participants. the method further includes determining an acquirement score for the one of the private model and the private data associated with each of the plurality of participants using the corresponding trade score. the method further includes publishing the acquirement score for trading the one of the private model and the private data among the plurality of participants.
Inventor(s): Swayam Prakash Ganguly of Kolkata (IN) for international business machines corporation
IPC Code(s): G06Q30/0601, G06F40/166, G06F40/253, G06F40/295, G06F40/30
CPC Code(s): G06Q30/0621
Abstract: a computer-implemented method includes: with a sentiment analyzer, assigning a sentiment value to each of a number of statements indicating user sentiment about a product or service of a producer; with a context-specific customization tool, determining a context in which the producer provides the product or service, the context-specific customization tool to adjust the assigned sentiment value for each statement indicating user sentiment based on the determined context; and with an accumulator, accumulating the adjusted sentiment values from the number of statements to produce an overall user sentiment determination that interprets an import of the number of statements corrected for the determined context.
Inventor(s): Kaoutar El Khiyaoui of Zürich (CH) for international business machines corporation, Angelo De Caro of Zürich (CH) for international business machines corporation, Elli Androulaki of Zürich (CH) for international business machines corporation
IPC Code(s): G06Q40/02
CPC Code(s): G06Q40/02
Abstract: the invention is notably directed to a computer-implemented method of managing user overdrafts in a privacy-preserving manner. the method comprises issuing a first overdraft token computed based on a user identifier of a given user, an initial overdraft value, a first serial number, and an encryption key that is shared with the given user. next, the method generates a zero-knowledge proof of that said overdraft value is equal to a maximal value of credit granted to said given user. the method subsequently computes an overdraft issuance transaction based on the first overdraft token and the first zero-knowledge proof, signs the computed overdraft issuance transaction using a secret key that is not shared with the given user, and finally submits the overdraft issuance transaction to a blockchain for validation.
Inventor(s): June-Ray Lin of Taipei City (TW) for international business machines corporation, Ye Chuan Wang of Beijing (CN) for international business machines corporation, Li Na Wang of Beijing (CN) for international business machines corporation, Nan Chen of Beijing (CN) for international business machines corporation, Ju Ling Liu of Beijing (CN) for international business machines corporation
IPC Code(s): G06T19/00, G06F3/01, G06T13/40
CPC Code(s): G06T19/00
Abstract: embodiments of the invention are directed to a computer system that includes a processor electronically coupled to a memory. the processor is operable to perform processor operations that includes accessing hypertext virtual markup language encoded (htvml-encoded) text. the htvml-encoded text is displayed in an immersive video frame of a display of a virtual reality (vr) environment. htvml content associated with the htvml-encoded text is also displayed in the 360-degree video frame. the htvml content include a three-dimensional (3d), immersive presentation format.
Inventor(s): Sarah Diane Green of Chandler AZ (US) for international business machines corporation, Ira L. Allen of Dallas TX (US) for international business machines corporation, Stan Kevin Daley of Española NM (US) for international business machines corporation, Michael Jack Martine of Chapel Hill NC (US) for international business machines corporation
IPC Code(s): G16H40/20, G06N20/00
CPC Code(s): G16H40/20
Abstract: at least one surplus distribution model can be trained by machine learning implemented using historical data. the surplus distribution model can be configured to process current data and, based on processing the current data, output first data indicating recommendations for distribution of surplus products. the current data can be processed, using the at least one surplus distribution model. based on the processing of the current data, the first data indicating the recommendations for distribution of the surplus products can be output. the recommendations for the distribution of the surplus products optimize the distribution of the surplus products based on demand for the surplus products.
Inventor(s): George Paulik of Rochester MN (US) for international business machines corporation, Timothy Lindquist of Rochester MN (US) for international business machines corporation, George Russell Zettles, IV of Rochester MN (US) for international business machines corporation, Jarrett Betke of Hoffman Estates IL (US) for international business machines corporation, Daniel Ramirez of Rochester MN (US) for international business machines corporation, Timothy Clyde Buchholtz of Rochester MN (US) for international business machines corporation, Kevin O'Connell of Mantorville MN (US) for international business machines corporation, Austin Carter of Olmsted MN (US) for international business machines corporation
IPC Code(s): H02J3/02, H02J3/14
CPC Code(s): H02J3/02
Abstract: techniques are provided to convert utility power having an unstable utility frequency into supply power having a stable frequency, which can be distributed and utilized as a system reference. for example, a system comprises a power generator and a power distribution system. the power generator is configured to convert utility power having an unstable utility frequency to supply power having a stable frequency component. the power distribution system is coupled to an output of the power generator, and is configured to distribute the supply power having the stable frequency component to at least one power consumer which is configured to utilize the stable frequency component of the supply power as a reference frequency.
Inventor(s): Sarbajit K. RAKSHIT of Kolkata (IN) for international business machines corporation, Naeem ALTAF of Round Rock TX (US) for international business machines corporation, Minsik LEE of Fort Lee NJ (US) for international business machines corporation, Joseph Dean COCKROFT of Kihei HI (US) for international business machines corporation
IPC Code(s): H04B10/29
CPC Code(s): H04B10/29
Abstract: disclosed embodiments provide systems and methods for implementing enhanced geo-restricted data management in satellite constellation datacenters. a disclosed system and methods implement a satellite constellation datacenter of multiple leo satellites that enables real-time satellite communications using lasers and secure data storage in the satellite constellation datacenter to protect critical data from unauthorized access and supports secure data transfer between the leo satellites using laser based data transfer. to enable secure storage of geo-location restricted data in a leo satellite, the leo satellite constellation datacenter defines a geo-location cone and requires that the geo-location restricted data be stored within the geo-location cone. leo satellites within the defined geo-location cone store the geo-location restricted data and securely transfer the geo-location restricted data from one satellite to another satellite within the defined geo-location cone.
Inventor(s): Nir DRUCKER of Zichron Yaakov (IL) for international business machines corporation, Eyal KUSHNIR of Kfar Vradim (IL) for international business machines corporation, Hayim SHAUL of Kfar Saba (IL) for international business machines corporation
IPC Code(s): H04L9/00, G06F9/30
CPC Code(s): H04L9/008
Abstract: an example system includes a processor to receive a circuit with a number of boolean variables to be simulated over real numbers. the processor can encode the circuit using a negation-based encoding in response to detecting a chain of and operations in the circuit. the processor can also execute the and operations in the encoded circuit by summing negated variables. the processor can further reduce positive integers in results of the summed negated variables to a value of one. the processor can also further negate the results with reduced positive integers to generate decoded results of the and operations.
Inventor(s): Binoy Thomas of Kozhikode (IN) for international business machines corporation, Sudheesh S. Kairali of Kozhikode (IN) for international business machines corporation, Malarvizhi Kandasamy of Bangalore (IN) for international business machines corporation, Sarbajit K. Rakshit of Kolkata (IN) for international business machines corporation
IPC Code(s): H04L9/40
CPC Code(s): H04L63/0414
Abstract: a method, computer system, and a computer program product are provided for establishing security measures for a content. in one embodiment, the method comprises identifying at least a microservice chain in a network computer. each microservice chain has more than one microservice linked to one another and each microservice includes a plurality of applications bundled together. any use profiles associated with the microservice chain are identified and all data entry points into each microservice are determined. each microservice is analyzed to predict when each microservice in the chain will provide a confidential output. once any microservice chain is deemed to be providing a confidential output, any predicted exits in the microservice deemed to be generating an output content are upgraded so that all predicted exists provide a confidential output.
Inventor(s): Zhi LI of Beijing (CN) for international business machines corporation, Xiao Dong LI of Beijing (CN) for international business machines corporation, He Jiang JIA of Beijing (CN) for international business machines corporation, Xing Xing SHEN of Beijing (CN) for international business machines corporation, Ye TIAN of Dalian (CN) for international business machines corporation, Sheng Jie HAN of Beijing (CN) for international business machines corporation
IPC Code(s): H04L9/40, H04L41/16
CPC Code(s): H04L63/1425
Abstract: processing within a computing environment is facilitated by using a machine learning implicit-anomaly model to determine a possibility of an implicit anomaly within a system based on system metrics data obtained during running of one or more test cases on the system. the process further includes determining, using artificial intelligence, occurrence of an incident within the system associated with running of the one or more test cases. determining the occurrence of the incident uses the determined possibility of the implicit anomaly within the system based on the system metrics data, and the process further includes initiating an action based on the occurrence of the incident within the system with running of the one or more test cases.
Inventor(s): Yair Allouche of Dvira (IL) for international business machines corporation, Bo-Yu Kuo of Kaohsiung (TW) for international business machines corporation, Aviad Cohen of Meitar (IL) for international business machines corporation
IPC Code(s): H04L9/40
CPC Code(s): H04L63/1425
Abstract: described are techniques for network anomaly detection. the techniques include generating, from network traffic, a plurality of network interactions, where respective network interactions comprise a communication source and a communication destination. the techniques further include generating, for the respective network interactions, a recommendation score using a trained collaborative filtering (cf) model. the techniques further include calculating, for the respective network interactions, an outlier score based on the recommendation score. the techniques further include generating a notification identifying an anomaly in the network traffic based on at least one outlier score satisfying a threshold.
Inventor(s): Atul Ashok Waghmare of Pleasanton CA (US) for international business machines corporation
IPC Code(s): H04N21/2343, G06F3/14
CPC Code(s): H04N21/2343
Abstract: a computer-implemented method (cim) of applying privacy filters to a screen share. the method includes the following operations: to establish a screen share between a first user and a second user, wherein the first user provides the screen share; to provide a privacy option, prior to the screen share with the second user, to the first user that offers at least one privacy filter to at least one portion of the screen share; the first user selects at least one privacy filter to the screen share; to apply the at least one privacy filter selected by the first user to the screen share; and to display the screen share to the second user with the at least one privacy filter applied to the screen share, wherein the at least one privacy filter masks the at least one portion of the screen share.
INTERNATIONAL BUSINESS MACHINES CORPORATION patent applications on August 1st, 2024
- INTERNATIONAL BUSINESS MACHINES CORPORATION
- B29C64/393
- B29C64/182
- B29C64/209
- CPC B29C64/393
- International business machines corporation
- F17C3/08
- CPC F17C3/085
- G01N33/00
- CPC G01N33/004
- G06F3/06
- CPC G06F3/0604
- G06F8/30
- G06F8/65
- CPC G06F8/30
- G06F8/61
- CPC G06F8/61
- G06F9/38
- G06F9/30
- CPC G06F9/3867
- G06F9/50
- CPC G06F9/5027
- G06F11/14
- G06F21/60
- CPC G06F11/1453
- G06F11/36
- CPC G06F11/3684
- G06F12/02
- CPC G06F12/0246
- G06F12/0802
- G06F12/121
- CPC G06F12/0802
- G06F12/0891
- CPC G06F12/0891
- G06F16/174
- G06F9/445
- CPC G06F16/174
- G06F16/27
- G06F16/23
- CPC G06F16/273
- G06F16/36
- G06F16/35
- CPC G06F16/367
- G06F18/2321
- G06F18/241
- CPC G06F18/2321
- G06F21/44
- CPC G06F21/44
- G06F30/12
- B33Y50/02
- G06Q30/04
- CPC G06F30/12
- G06F30/20
- CPC G06F30/20
- G06F40/30
- G06F40/284
- CPC G06F40/30
- G06F40/51
- G06F40/58
- CPC G06F40/51
- G06N3/0464
- G06N3/063
- CPC G06N3/0464
- G06N3/08
- H04L9/00
- CPC G06N3/08
- G06N5/022
- G06N3/098
- CPC G06N3/098
- CPC G06N5/022
- G06N20/00
- CPC G06N20/00
- G06Q10/063
- G06N3/042
- CPC G06Q10/063
- G06Q10/083
- CPC G06Q10/083
- G06Q30/0202
- G06F16/2455
- CPC G06Q30/0202
- CPC G06Q30/0206
- G06Q30/0601
- G06F40/166
- G06F40/253
- G06F40/295
- CPC G06Q30/0621
- G06Q40/02
- CPC G06Q40/02
- G06T19/00
- G06F3/01
- G06T13/40
- CPC G06T19/00
- G16H40/20
- CPC G16H40/20
- H02J3/02
- H02J3/14
- CPC H02J3/02
- H04B10/29
- CPC H04B10/29
- CPC H04L9/008
- H04L9/40
- CPC H04L63/0414
- H04L41/16
- CPC H04L63/1425
- H04N21/2343
- G06F3/14
- CPC H04N21/2343
