According to an embodiment, a method includes receiving sensor data measured by a plurality of SCADA-enabled sensors associated with an electrical grid and identifying a plurality of momentary outages associated with the electrical grid based on the sensor data. The method further includes predicting (1) a plurality of possible sustained outages associated with the electrical grid based on the plurality of momentary outages and (2) a sustained outage likelihood from a plurality of sustained outage likelihoods for each possible sustained outage from the plurality of possible sustained outages based on the plurality of momentary outages.
H02J 3/00 - Circuits pour réseaux principaux ou de distribution, à courant alternatif
H02J 13/00 - Circuits pour pourvoir à l'indication à distance des conditions d'un réseau, p. ex. un enregistrement instantané des conditions d'ouverture ou de fermeture de chaque sectionneur du réseauCircuits pour pourvoir à la commande à distance des moyens de commutation dans un réseau de distribution d'énergie, p. ex. mise en ou hors circuit de consommateurs de courant par l'utilisation de signaux d'impulsion codés transmis par le réseau
2.
SYSTEMS AND METHODS OF LIQUID EXTRACTION FROM EMPTY BARRELS
Embodiments described herein relate to systems and methods of extracting liquid from empty barrels. In one aspect, a method includes heating a barrel with less than about 10 ml of free liquid disposed therein to expand pores in the barrel. The method further includes applying, after the heating, a negative pressure to an interior of a vessel in which the barrel is disposed, such that an amount of liquid is extracted from the barrel. The method includes collecting, after the applying, the amount of liquid within a collection container. In some embodiments, collecting the amount of liquid includes pumping the liquid through a tube that is disposed between an outer surface of the barrel and the collection container. In some embodiments, heating the barrel is via a heated blanket wrapped around the barrel. In some embodiments, heating the barrel is via placing the barrel in an oven.
B67D 1/08 - Appareils ou dispositifs pour débiter des boissons à la pression Détails
B67C 3/16 - Mise en bouteilles de liquides ou de semi-liquidesRemplissage des bocaux ou bidons avec des liquides ou semi-liquides en utilisant des appareils de mise en bouteilles ou des appareils analogues par aspiration
Embodiments described herein relate to systems and methods of extracting liquid from empty barrels. In one aspect, a method includes heating a barrel with less than about 10 ml of free liquid disposed therein to expand pores in the barrel. The method further includes applying, after the heating, a negative pressure to an interior of a vessel in which the barrel is disposed, such that an amount of liquid is extracted from the barrel. The method includes collecting, after the applying, the amount of liquid within a collection container. In some embodiments, collecting the amount of liquid includes pumping the liquid through a tube that is disposed between an outer surface of the barrel and the collection container. In some embodiments, heating the barrel is via a heated blanket wrapped around the barrel. In some embodiments, heating the barrel is via placing the barrel in an oven.
B67D 1/08 - Appareils ou dispositifs pour débiter des boissons à la pression Détails
B67C 3/16 - Mise en bouteilles de liquides ou de semi-liquidesRemplissage des bocaux ou bidons avec des liquides ou semi-liquides en utilisant des appareils de mise en bouteilles ou des appareils analogues par aspiration
Embodiments described herein relate to systems and methods of extracting liquid from empty barrels. In one aspect, a method includes heating a barrel with less than about 10 ml of free liquid disposed therein to expand pores in the barrel. The method further includes applying, after the heating, a negative pressure to an interior of a vessel in which the barrel is disposed, such that an amount of liquid is extracted from the barrel. The method includes collecting, after the applying, the amount of liquid within a collection container. In some embodiments, collecting the amount of liquid includes pumping the liquid through a tube that is disposed between an outer surface of the barrel and the collection container. In some embodiments, heating the barrel is via a heated blanket wrapped around the barrel. In some embodiments, heating the barrel is via placing the barrel in an oven.
B67C 3/16 - Mise en bouteilles de liquides ou de semi-liquidesRemplissage des bocaux ou bidons avec des liquides ou semi-liquides en utilisant des appareils de mise en bouteilles ou des appareils analogues par aspiration
C12H 1/22 - Vieillissement ou mûrissage par emmagasinage, p. ex. blondissement de la bière
5.
Systems and methods for automated discovery and analysis of privileged access across multiple computing platforms
In some embodiments, a method includes retrieving data associated with each account from a set of accounts from one or more computing platforms and parsing the data to determine a set of characteristics associated with each account from the set of accounts. The method includes mapping, based on an entitlement value of each account, a first subset of accounts from the set of accounts to a first privilege value, and mapping, based on an entitlement value of each account, a second subset of accounts from the set of accounts to a second privilege value. The method includes generating a report indicating the first subset of accounts having the first privilege value and the second subset of accounts having the second privilege value. In some implementations, the method includes scheduling a set of jobs to execute the jobs automatically in response to at least one trigger event.
In some embodiments, a method includes retrieving data associated with each account from a set of accounts from one or more computing platforms and parsing the data to determine a set of characteristics associated with each account from the set of accounts. The method includes mapping, based on an entitlement value of each account, a first subset of accounts from the set of accounts to a first privilege value, and mapping, based on an entitlement value of each account, a second subset of accounts from the set of accounts to a second privilege value. The method includes generating a report indicating the first subset of accounts having the first privilege value and the second subset of accounts having the second privilege value. In some implementations, the method includes scheduling a set of jobs to execute the jobs automatically in response to at least one trigger event.
Embodiments described herein relate to systems and methods of extracting liquid from empty barrels. In one aspect, a method includes heating a barrel with less than about 10 ml of free liquid disposed therein to expand pores in the barrel. The method further includes applying, after the heating, a negative pressure to an interior of a vessel in which the barrel is disposed, such that an amount of liquid is extracted from the barrel. The method includes collecting, after the applying, the amount of liquid within a collection container. In some embodiments, collecting the amount of liquid includes pumping the liquid through a tube that is disposed between an outer surface of the barrel and the collection container. In some embodiments, heating the barrel is via a heated blanket wrapped around the barrel. In some embodiments, heating the barrel is via placing the barrel in an oven.
F26B 5/04 - Procédés de séchage d'un matériau solide ou d'objets n'impliquant pas l'utilisation de chaleur par évaporation ou sublimation de l'humidité sous une pression réduite, p. ex. sous vide
8.
Systems and methods of liquid extraction from empty barrels
Embodiments described herein relate to systems and methods of extracting liquid from empty barrels. In one aspect, a method includes heating a barrel with less than about 10 ml of free liquid disposed therein to expand pores in the barrel. The method further includes applying, after the heating, a negative pressure to an interior of a vessel in which the barrel is disposed, such that an amount of liquid is extracted from the barrel. The method includes collecting, after the applying, the amount of liquid within a collection container. In some embodiments, collecting the amount of liquid includes pumping the liquid through a tube that is disposed between an outer surface of the barrel and the collection container. In some embodiments, heating the barrel is via a heated blanket wrapped around the barrel. In some embodiments, heating the barrel is via placing the barrel in an oven.
B67C 3/16 - Mise en bouteilles de liquides ou de semi-liquidesRemplissage des bocaux ou bidons avec des liquides ou semi-liquides en utilisant des appareils de mise en bouteilles ou des appareils analogues par aspiration
B67D 1/08 - Appareils ou dispositifs pour débiter des boissons à la pression Détails
A method includes receiving a dataset that includes a plurality of input texts. Each input text from the plurality of texts is associated with a content category from a plurality of content categories based on a comparison between that input text and an intended meaning that is common for each comparison. For each model in a plurality of models, and for each content category from the plurality of content categories, that model is executed on each input text from the plurality of input texts to generate an average similarity/dissimilarity score for that content category. At least one model from the plurality of models is selected, based on the average similarity score for each content category from the plurality of content categories for each model in the plurality of models, to determine whether an input text is similar/dissimilar to the intended meaning.
A method includes receiving a dataset that includes a plurality of input texts. Each input text from the plurality of texts is associated with a content category from a plurality of content categories based on a comparison between that input text and an intended meaning that is common for each comparison. For each model in a plurality of models, and for each content category from the plurality of content categories, that model is executed on each input text from the plurality of input texts to generate an average similarity / dissimilarity score for that content category. At least one model from the plurality of models is selected, based on the average similarity score for each content category from the plurality of content categories for each model in the plurality of models, to determine whether an input text is similar / dissimilar to the intended meaning.
A processor-implemented method for the ownership transfer and tracking of tangible assets using a blockchain is described. In an embodiment, the method includes generating a root node associated with a tangible asset via a processor. The root node has a first hash value that represents a storage location of the root node, data associated with a tangible asset, and a second hash value that represents a storage location of the subsidiary node. The method also includes storing a hierarchical hash-linked tree structure in a non-transitory, processor-readable memory. The hierarchical hash-linked tree structure can include multiple nodes. The multiple nodes include the root node and the subsidiary node. The subsidiary node has the second hash value, and data associated with a tangible sub-asset of the tangible asset.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
12.
INTELLIGENT ASSERTION TOKENS FOR AUTHENTICATING AND CONTROLLING NETWORK COMMUNICATIONS USING A DISTRIBUTED LEDGER
A method for generating and controlling intelligent assertion tokens includes generating a first assertion token, during a first step of a supply chain process. The first assertion token is inspected to determine validity. If the first assertion token is not valid, the receipt of the first assertion token is rejected. If the first assertion token is determined to be valid, the use of the first assertion token in further transmissions and/or transactions is authorized. The first assertion token can be passed to a second step of the supply chain process, and a second assertion token may be generated based on the first assertion token. Upon receipt of the second assertion token, it is inspected to determine validity. If not valid, the transmission and/or transfer of the second assertion token is rejected. If valid, the transmission and/or transfer of the second assertion token to a further step of the supply chain process or to a customer is authorized.
An object-extraction method includes generating multiple partition objects based on an electronic document, and receiving a first user selection of a data element via a user interface of a compute device. In response to the first user selection, and using a machine learning model, a first subset of partition objects from the multiple partition objects is detected and displayed via the user interface. A user interaction, via the user interface, with one of the partition objects is detected, and in response, a weight of the machine learning model is modified, to produce a modified machine learning model. A second user selection of the data element is received via the user interface, and in response and using the modified machine learning model, a second subset of partition objects from the multiple partition objects is detected and displayed via the user interface, the second subset different from the first subset.
G06N 20/20 - Techniques d’ensemble en apprentissage automatique
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
G06V 10/22 - Prétraitement de l’image par la sélection d’une région spécifique contenant ou référençant une formeLocalisation ou traitement de régions spécifiques visant à guider la détection ou la reconnaissance
G06V 10/771 - Sélection de caractéristiques, p. ex. sélection des caractéristiques représentatives à partir d’un espace multidimensionnel de caractéristiques
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 10/98 - Détection ou correction d’erreurs, p. ex. en effectuant une deuxième exploration du motif ou par intervention humaineÉvaluation de la qualité des motifs acquis
G06V 30/19 - Reconnaissance utilisant des moyens électroniques
G06V 30/40 - Reconnaissance des formes à partir d’images axée sur les documents
14.
SYSTEMS, APPARATUS AND METHODS FOR IDENTIFYING AND SECURELY STORING DISTINGUISHING CHARACTERISTICS IN A DISTRIBUTED LEDGER WITHIN A DISTRIBUTED LEDGER-BASED NETWORK BASED ON FUNGIBLE AND NON-FUNGIBLE TOKENS
In some embodiments, a method includes storing data associated with fungible assets in a distributed ledger database. The method includes dividing fungible tokens into a first set of groups of fungible tokens based on the data and sending, via the distributed ledger-based network and based on an asymmetric cryptography key pair, each group of fungible tokens from the first set of groups of fungible tokens to a communication device from the first set of communication devices to cause the second plurality of communication devices to send, to a designated recipient communication device, non-fungible tokens for each group of fungible tokens from the second set of groups of fungible tokens. The first set of groups of fungible tokens is divided into a second set of groups of fungible tokens and received at a second set of communication devices.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G06Q 40/00 - FinanceAssuranceStratégies fiscalesTraitement des impôts sur les sociétés ou sur le revenu
G06Q 10/08 - Logistique, p. ex. entreposage, chargement ou distributionGestion d’inventaires ou de stocks
15.
APPARATUS AND METHODS FOR CONVERTING LINELESS TABLES INTO LINED TABLES USING GENERATIVE ADVERSARIAL NETWORKS
A method for converting a lineless table into a lined table includes associating a first set of tables with a second set of tables to form a set of multiple table pairs that includes tables with lines and tables without lines. A conditional generative adversarial network (cGAN) is trained, using the table pairs, to produce a trained cGAN. Using the trained cGAN, lines are identified for overlay ing onto a lineless table. The lines are overlaid onto the lineless table to produce a lined table.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
Business consulting services relating to the integration of the areas of business process technology, organizational learning, change management, and operational sustainability
Business consulting services relating to the integration of the areas of business process technology, organizational learning, change management, and operational sustainability
Business consulting services relating to the integration of the areas of business process technology, organizational learning, change management, and operational sustainability
19.
APPARATUS AND METHOD FOR EXTRACTING DATA FROM LINELESS TABLES USING DELAUNAY TRIANGULATION AND EXCESS EDGE REMOVAL
A method for extracting data from lineless tables includes storing an image including a table in a memory. A processor operably coupled to the memory identifies a plurality of text-based characters in the image, and defines multiple bounding boxes based on the characters. Each of the bounding boxes is uniquely associated with at least one of the text-based characters. A graph including multiple nodes and multiple edges is generated based on the bounding boxes, using a graph construction algorithm. At least one of the edges is identified for removal from the graph, and removed from the graph to produce a reduced graph. The reduced graph can be sent to a neural network to predict row labels and column labels for the table.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
20.
Biosignature-based tokenization of assets in a blockchain
An apparatus includes a tester to detect a biological signature of a biological sample, a processor, and a memory operably coupled to the processor. The memory stores instructions to cause the processor to receive an indication of the biological signature from the tester, and to generate, using a smart contract and through communication with a distributed ledger, a cryptographic token including a digital identifier based on the biological signature. The cryptographic token is transmitted to a remote processor for verification of the biological sample, in response to receiving the cryptographic token. The tester can detect the biological signature within a predetermined test duration that is less than a DNA sequencing duration associated with the biological sample, and the biological signature has a data precision sufficient to uniquely identify the biological sample from a plurality of biological samples.
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
G16H 10/40 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données relatives aux analyses de laboratoire, p. ex. pour des analyses d’échantillon de patient
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
21.
BIOSIGNATURE-BASED TOKENIZATION OF ASSETS IN A DISTRIBUTED LEDGER
An apparatus includes a tester to detect a biological signature of a biological sample, a processor, and a memory operably coupled to the processor. The memory stores instructions to cause the processor to receive an indication of the biological signature from the tester, and to generate, using a smart contract and through communication with a distributed ledger, a cryptographic token including a digital identifier based on the biological signature. The cryptographic token is transmitted to a remote processor for verification of the biological sample, in response to receiving the cryptographic token. The tester can detect the biological signature within a predetermined test duration that is less than a DNA sequencing duration associated with the biological sample, and the biological signature has a data precision sufficient to uniquely identify the biological sample from a plurality of biological samples.
G16H 10/60 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données spécifiques de patients, p. ex. pour des dossiers électroniques de patients
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
22.
METHODS AND SYSTEMS FOR BRIDGING PAIRWISE COMMUNICATION IN A NETWORK OF DISPARATE ENTERPRISE SYSTEMS
Embodiments of the instant disclosure include methods and systems directed at multi-token representation of assets involved in transactions occurring on distributed-ledger based networks that bridge or facilitate such transactions between disparate enterprise resource planning (ERP) systems. The disclose methods and systems improve network performance by at least reducing inefficiencies or errors that occur when disparate systems transact.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06Q 10/08 - Logistique, p. ex. entreposage, chargement ou distributionGestion d’inventaires ou de stocks
G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
An object-extraction method includes generating multiple partition objects based on an electronic document, and receiving a first user selection of a data element via a user interface of a compute device. In response to the first user selection, and using a machine learning model, a first subset of partition objects from the multiple partition objects is detected and displayed via the user interface. A user interaction, via the user interface, with one of the partition objects is detected, and in response, a weight of the machine learning model is modified, to produce a modified machine learning model. A second user selection of the data element is received via the user interface, and in response and using the modified machine learning model, a second subset of partition objects from the multiple partition objects is detected and displayed via the user interface, the second subset different from the first subset.
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06N 20/20 - Techniques d’ensemble en apprentissage automatique
24.
MACHINE LEARNING BASED EXTRACTION OF PARTITION OBJECTS FROM ELECTRONIC DOCUMENTS
An object-extraction method includes generating multiple partition objects based on an electronic document, and receiving a first user selection of a data element via a user interface of a compute device. In response to the first user selection, and using a machine learning model, a first subset of partition objects from the multiple partition objects is detected and displayed via the user interface. A user interaction, via the user interface, with one of the partition objects is detected, and in response, a weight of the machine learning model is modified, to produce a modified machine learning model. A second user selection of the data element is received via the user interface, and in response and using the modified machine learning model, a second subset of partition objects from the multiple partition objects is detected and displayed via the user interface, the second subset different from the first subset.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
An object-extraction method includes generating multiple partition objects based on an electronic document, and receiving a first user selection of a data element via a user interface of a compute device. In response to the first user selection, and using a machine learning model, a first subset of partition objects from the multiple partition objects is detected and displayed via the user interface. A user interaction, via the user interface, with one of the partition objects is detected, and in response, a weight of the machine learning model is modified, to produce a modified machine learning model. A second user selection of the data element is received via the user interface, and in response and using the modified machine learning model, a second subset of partition objects from the multiple partition objects is detected and displayed via the user interface, the second subset different from the first subset.
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
A method for real-time remediation of a software script includes, during execution of the script, attempting to identify a first user interface (UI) object. In response to failing to identify the first UI object, similarity scores are calculated based on the data of the plurality of UI objects and historical data associated with the first UI object. A second UI object is identified, from the plurality of UI objects, based on the calculated similarity scores. The script and/or an object repository referenced by the script are then automatically modified so that subsequent execution of the script includes attempting to identify the second UI object instead of the first UI object.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
A method for real-time remediation of a software script includes, during execution of the script, attempting to identify a first user interface (UI) object. In response to failing to identify the first UI object, similarity scores are calculated based on the data of the plurality of UI objects and historical data associated with the first UI object. A second UI object is identified, from the plurality of UI objects, based on the calculated similarity scores. The script and/or an object repository referenced by the script are then automatically modified so that subsequent execution of the script includes attempting to identify the second UI object instead of the first UI object.
A processor-implemented method for the ownership transfer and tracking of tangible assets using a blockchain is described. In an embodiment, the method includes generating a root node associated with a tangible asset via a processor. The root node has a first hash value that represents a storage location of the root node, data associated with a tangible asset, and a second hash value that represents a storage location of the subsidiary node. The method also includes storing a hierarchical hash-linked tree structure in a non-transitory, processor-readable memory. The hierarchical hash-linked tree structure can include multiple nodes. The multiple nodes include the root node and the subsidiary node. The subsidiary node has the second hash value, and data associated with a tangible sub-asset of the tangible asset.
Business management and business consulting services in the field of contingency planning, strategic planning, finance, operations, organizational structure design and reorganization through the preparation of custom communications and organizational and planning materials for businesses
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Software as a service (SAAS) services featuring software for creating forms, templates, and the like; Software as a service (SAAS) services, namely, hosting software for use by others for use in the creation of forms, templates, and the like
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
Regulatory compliance consulting in the field of employer and employee reporting requirements of the Affordable Care Act; reviewing standards and practices to assure support compliance with the Affordable Care Act's employer and employee reporting laws and regulations; tracking and monitoring regulatory requirements in the field of employer and employee reporting requirements of the Affordable Care Act for regulatory compliance purposes
32.
Method and system for providing telephony services
A method is provided for directing calls placed to a telephone number associated with a user according to a reservation identifying the user, a workspace, and a start time. The method includes acts of receiving a first message from a telephone device located at the workspace in response to a first input at the telephone device on or after the start time, retrieving the reservation from a reservation database in response to receiving the first message, sending a second message to the telephone device based at least in part on a portion of the reservation identifying the user, receiving a third message sent in response to a second input at the telephone device, the third message including an identifier of the telephone device, retrieving the telephone number associated with the user from a user database, and directing calls placed to the telephone number associated with the user to the telephone device.
42 - Services scientifiques, technologiques et industriels, recherche et conception
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
providing on-line, non-downloadable software for tracking business incentives; providing on-line, non-downloadable software for tracking tax and non-tax compliance reporting requirements generated by various incentive programs, measuring the performance in job creation and investment compared to agreed upon benchmarks, and tracking the value of awarded and received benefits tracking and monitoring regulatory requirements in the field of tax and other types of government incentive programs for regulatory compliance purposes
09 - Appareils et instruments scientifiques et électriques
Produits et services
computer software for use in inventory control and record keeping in the area of US customs and foreign trade zones with respect to petroleum and petro-chemical refining and processing operations
